{"pageNumber":"701","pageRowStart":"17500","pageSize":"25","recordCount":40789,"records":[{"id":70039185,"text":"sir20125130 - 2012 - Development of regional skews for selected flood durations for the Central Valley Region, California, based on data through water year 2008","interactions":[],"lastModifiedDate":"2012-07-25T01:02:05","indexId":"sir20125130","displayToPublicDate":"2012-07-24T00:00:00","publicationYear":"2012","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":"2012-5130","title":"Development of regional skews for selected flood durations for the Central Valley Region, California, based on data through water year 2008","docAbstract":"Flood-frequency information is important in the Central Valley region of California because of the high risk of catastrophic flooding. Most traditional flood-frequency studies focus on peak flows, but for the assessment of the adequacy of reservoirs, levees, other flood control structures, sustained flood flow (flood duration) frequency data are needed. This study focuses on rainfall or rain-on-snow floods, rather than the annual maximum, because rain events produce the largest floods in the region. A key to estimating flood-duration frequency is determining the regional skew for such data. Of the 50 sites used in this study to determine regional skew, 28 sites were considered to have little to no significant regulated flows, and for the 22 sites considered significantly regulated, unregulated daily flow data were synthesized by using reservoir storage changes and diversion records. The unregulated, annual maximum rainfall flood flows for selected durations (1-day, 3-day, 7-day, 15-day, and 30-day) for all 50 sites were furnished by the U.S. Army Corps of Engineers. Station skew was determined by using the expected moments algorithm program for fitting the Pearson Type 3 flood-frequency distribution to the logarithms of annual flood-duration data.\r\nBayesian generalized least squares regression procedures used in earlier studies were modified to address problems caused by large cross correlations among concurrent rainfall floods in California and to address the extensive censoring of low outliers at some sites, by using the new expected moments algorithm for fitting the LP3 distribution to rainfall flood-duration data. To properly account for these problems and to develop suitable regional-skew regression models and regression diagnostics, a combination of ordinary least squares, weighted least squares, and Bayesian generalized least squares regressions were adopted. This new methodology determined that a nonlinear model relating regional skew to mean basin elevation was the best model for each flood duration. The regional-skew values ranged from -0.74 for a flood duration of 1-day and a mean basin elevation less than 2,500 feet to values near 0 for a flood duration of 7-days and a mean basin elevation greater than 4,500 feet. This relation between skew and elevation reflects the interaction of snow and rain, which increases with increased elevation. The regional skews are more accurate, and the mean squared errors are less than in the Interagency Advisory Committee on Water Data's National skew map of Bulletin 17B.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125130","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Lamontagne, J.R., Stedinger, J.R., Berenbrock, C., Veilleux, A.G., Ferris, J.C., and Knifong, D.L., 2012, Development of regional skews for selected flood durations for the Central Valley Region, California, based on data through water year 2008: U.S. Geological Survey Scientific Investigations Report 2012-5130, viii, 35 p. Appendices, https://doi.org/10.3133/sir20125130.","productDescription":"viii, 35 p. Appendices","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":259128,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5130.gif"},{"id":259123,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5130/","linkFileType":{"id":5,"text":"html"}},{"id":259124,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5130/pdf/sir20125130.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Central Valley;Sierra Nevada Basins;North Coast Ranges Basins;South Coast Ranges Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.54,34.28 ], [ -124.54,42.01 ], [ -116.33,42.01 ], [ -116.33,34.28 ], [ -124.54,34.28 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0061e4b0c8380cd4f725","contributors":{"authors":[{"text":"Lamontagne, Jonathan R. 0000-0003-3976-1678","orcid":"https://orcid.org/0000-0003-3976-1678","contributorId":31640,"corporation":false,"usgs":true,"family":"Lamontagne","given":"Jonathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stedinger, Jery R.","contributorId":76198,"corporation":false,"usgs":true,"family":"Stedinger","given":"Jery","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berenbrock, Charles","contributorId":30598,"corporation":false,"usgs":true,"family":"Berenbrock","given":"Charles","email":"","affiliations":[],"preferred":false,"id":465751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":465750,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferris, Justin C. jcferris@usgs.gov","contributorId":4186,"corporation":false,"usgs":true,"family":"Ferris","given":"Justin","email":"jcferris@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":465749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knifong, Donna L. dknifong@usgs.gov","contributorId":1517,"corporation":false,"usgs":true,"family":"Knifong","given":"Donna","email":"dknifong@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":465748,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70039170,"text":"ofr20121148 - 2012 - Probability and volume of potential postwildfire debris flows in the 2012 High Park Burn Area near Fort Collins, Colorado","interactions":[],"lastModifiedDate":"2012-07-24T01:01:47","indexId":"ofr20121148","displayToPublicDate":"2012-07-23T00:00:00","publicationYear":"2012","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":"2012-1148","title":"Probability and volume of potential postwildfire debris flows in the 2012 High Park Burn Area near Fort Collins, Colorado","docAbstract":"This report presents a preliminary emergency assessment of the debris-flow hazards from drainage basins burned by the 2012 High Park fire near Fort Collins in Larimer County, Colorado. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the intermountain western United States were used to estimate the probability of debris-flow occurrence and volume of debris flows along the burned area drainage network and to estimate the same for 44 selected drainage basins along State Highway 14 and the perimeter of the burned area. Input data for the models included topographic parameters, soil characteristics, burn severity, and rainfall totals and intensities for a (1) 2-year-recurrence, 1-hour-duration rainfall (25 millimeters); (2) 10-year-recurrence, 1-hour-duration rainfall (43 millimeters); and (3) 25-year-recurrence, 1-hour-duration rainfall (51 millimeters). Estimated debris-flow probabilities along the drainage network and throughout the drainage basins of interest ranged from 1 to 84 percent in response to the 2-year-recurrence, 1-hour-duration rainfall; from 2 to 95 percent in response to the 10-year-recurrence, 1-hour-duration rainfall; and from 3 to 97 in response to the 25-year-recurrence, 1-hour-duration rainfall. Basins and drainage networks with the highest probabilities tended to be those on the eastern edge of the burn area where soils have relatively high clay contents and gradients are steep. Estimated debris-flow volumes range from a low of 1,600 cubic meters to a high of greater than 100,000 cubic meters. Estimated debris-flow volumes increase with basin size and distance along the drainage network, but some smaller drainages were also predicted to produce substantial volumes of material. The predicted probabilities and some of the volumes predicted for the modeled storms indicate a potential for substantial debris-flow impacts on structures, roads, bridges, and culverts located both within and immediately downstream from the burned area. Colorado State Highway 14 is also susceptible to impacts from debris flows.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121148","collaboration":"Prepared in cooperation with Colorado Department of Transportation","usgsCitation":"Verdin, K.L., Dupree, J.A., and Elliott, J.G., 2012, Probability and volume of potential postwildfire debris flows in the 2012 High Park Burn Area near Fort Collins, Colorado: U.S. Geological Survey Open-File Report 2012-1148, vi, 9 p.; 2 Plates: 87 x 56 cm., https://doi.org/10.3133/ofr20121148.","productDescription":"vi, 9 p.; 2 Plates: 87 x 56 cm.","numberOfPages":"15","onlineOnly":"Y","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":259113,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1148.gif"},{"id":259106,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1148/Plate1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259104,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1148/","linkFileType":{"id":5,"text":"html"}},{"id":259105,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1148/OF12-1148.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259107,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1148/Plate2.pdf","linkFileType":{"id":1,"text":"pdf"}}],"projection":"Universal Transverse Mercator, Zone 13 North","datum":"North American Datum 1983","country":"United States","state":"Colorado","county":"Larimer","city":"Fort Collins","otherGeospatial":"High Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.53333333333333,40.55 ], [ -105.53333333333333,40.75 ], [ -105.18333333333334,40.75 ], [ -105.18333333333334,40.55 ], [ -105.53333333333333,40.55 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a8ca8e4b0c8380cd7e7f3","contributors":{"authors":[{"text":"Verdin, Kristine L. 0000-0002-6114-4660 kverdin@usgs.gov","orcid":"https://orcid.org/0000-0002-6114-4660","contributorId":3070,"corporation":false,"usgs":true,"family":"Verdin","given":"Kristine","email":"kverdin@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dupree, Jean A. dupree@usgs.gov","contributorId":2563,"corporation":false,"usgs":true,"family":"Dupree","given":"Jean","email":"dupree@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":465720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, John G. jelliott@usgs.gov","contributorId":832,"corporation":false,"usgs":true,"family":"Elliott","given":"John","email":"jelliott@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":465719,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039163,"text":"ofr20121131 - 2012 - The fluorescent tracer experiment on Holiday Beach near Mugu Canyon, Southern California","interactions":[],"lastModifiedDate":"2012-07-25T01:02:05","indexId":"ofr20121131","displayToPublicDate":"2012-07-23T00:00:00","publicationYear":"2012","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":"2012-1131","title":"The fluorescent tracer experiment on Holiday Beach near Mugu Canyon, Southern California","docAbstract":"After revisiting sand tracer techniques originally developed in the 1960s, a range of fluorescent coating formulations were tested in the laboratory. Explicit steps are presented for the preparation of the formulation evaluated to have superior attributes, a thermoplastic pigment/dye in a colloidal mixture with a vinyl chloride/vinyl acetate copolymer. In September 2010, 0.59 cubic meters of fluorescent tracer material was injected into the littoral zone about 4 kilometers upcoast of Mugu submarine canyon in California. The movement of tracer was monitored in three dimensions over the course of 4 days using manual and automated techniques. Detailed observations of the tracer's behavior in the coastal zone indicate that this tracer successfully mimicked the native beach sand and similar methods could be used to validate models of tracer movement in this type of environment. Recommendations including how to time successful tracer studies and how to scale the field of view of automated camera systems are presented along with the advantages and disadvantages of the described tracer methodology.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121131","usgsCitation":"Kinsman, N., and Xu, J.P., 2012, The fluorescent tracer experiment on Holiday Beach near Mugu Canyon, Southern California: U.S. Geological Survey Open-File Report 2012-1131, v, 23 p., https://doi.org/10.3133/ofr20121131.","productDescription":"v, 23 p.","onlineOnly":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":259093,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1131/of2012-1131.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259094,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1131/","linkFileType":{"id":5,"text":"html"}},{"id":259096,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1131.gif"}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Channel;Mugu Lagoon","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bac1de4b08c986b32329f","contributors":{"authors":[{"text":"Kinsman, Nicole","contributorId":95737,"corporation":false,"usgs":true,"family":"Kinsman","given":"Nicole","affiliations":[],"preferred":false,"id":465700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, J. P.","contributorId":74528,"corporation":false,"usgs":true,"family":"Xu","given":"J.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":465699,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039135,"text":"tm4F3 - 2012 - TracerLPM (Version 1): An Excel® workbook for interpreting groundwater age distributions from environmental tracer data","interactions":[],"lastModifiedDate":"2023-08-17T19:04:09.341631","indexId":"tm4F3","displayToPublicDate":"2012-07-20T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-F3","title":"TracerLPM (Version 1): An Excel® workbook for interpreting groundwater age distributions from environmental tracer data","docAbstract":"TracerLPM is an interactive Excel® (2007 or later) workbook program for evaluating groundwater age distributions from environmental tracer data by using lumped parameter models (LPMs). Lumped parameter models are mathematical models of transport based on simplified aquifer geometry and flow configurations that account for effects of hydrodynamic dispersion or mixing within the aquifer, well bore, or discharge area. Five primary LPMs are included in the workbook: piston-flow model (PFM), exponential mixing model (EMM), exponential piston-flow model (EPM), partial exponential model (PEM), and dispersion model (DM). Binary mixing models (BMM) can be created by combining primary LPMs in various combinations. Travel time through the unsaturated zone can be included as an additional parameter. TracerLPM also allows users to enter age distributions determined from other methods, such as particle tracking results from numerical groundwater-flow models or from other LPMs not included in this program. Tracers of both young groundwater (anthropogenic atmospheric gases and isotopic substances indicating post-1940s recharge) and much older groundwater (carbon-14 and helium-4) can be interpreted simultaneously so that estimates of the groundwater age distribution for samples with a wide range of ages can be constrained. TracerLPM is organized to permit a comprehensive interpretive approach consisting of hydrogeologic conceptualization, visual examination of data and models, and best-fit parameter estimation. Groundwater age distributions can be evaluated by comparing measured and modeled tracer concentrations in two ways: (1) multiple tracers analyzed simultaneously can be evaluated against each other for concordance with modeled concentrations (tracer-tracer application) or (2) tracer time-series data can be evaluated for concordance with modeled trends (tracer-time application). Groundwater-age estimates can also be obtained for samples with a single tracer measurement at one point in time; however, prior knowledge of an appropriate LPM is required because the mean age is often non-unique. LPM output concentrations depend on model parameters and sample date. All of the LPMs have a parameter for mean age. The EPM, PEM, and DM have an additional parameter that characterizes the degree of age mixing in the sample. BMMs have a parameter for the fraction of the first component in the mixture. An LPM, together with its parameter values, provides a description of the age distribution or the fractional contribution of water for every age of recharge contained within a sample. For the PFM, the age distribution is a unit pulse at one distinct age. For the other LPMs, the age distribution can be much broader and span decades, centuries, millennia, or more. For a sample with a mixture of groundwater ages, the reported interpretation of tracer data includes the LPM name, the mean age, and the values of any other independent model parameters. TracerLPM also can be used for simulating the responses of wells, springs, streams, or other groundwater discharge receptors to nonpoint-source contaminants that are introduced in recharge, such as nitrate. This is done by combining an LPM or user-defined age distribution with information on contaminant loading at the water table. Information on historic contaminant loading can be used to help evaluate a model's ability to match real world conditions and understand observed contaminant trends, while information on future contaminant loading scenarios can be used to forecast potential contaminant trends.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4F3","collaboration":"National Research Program; National Water-Quality Assessment Program","usgsCitation":"Jurgens, B., Böhlke, J., and Eberts, S., 2012, TracerLPM (Version 1): An Excel® workbook for interpreting groundwater age distributions from environmental tracer data: U.S. Geological Survey Techniques and Methods 4-F3, viii, 60 p., https://doi.org/10.3133/tm4F3.","productDescription":"viii, 60 p.","onlineOnly":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":259039,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/4-f3/pdf/tm4-F3.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_4_f3.jpg"},{"id":259038,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/4-f3/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bb68be4b08c986b326d21","contributors":{"authors":[{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":22454,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant C.","affiliations":[],"preferred":false,"id":465667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Böhlke, J.K. 0000-0001-5693-6455","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":96696,"corporation":false,"usgs":true,"family":"Böhlke","given":"J.K.","affiliations":[],"preferred":false,"id":465668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eberts, Sandra M. smeberts@usgs.gov","contributorId":2264,"corporation":false,"usgs":true,"family":"Eberts","given":"Sandra M.","email":"smeberts@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":465666,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039117,"text":"70039117 - 2012 - Hatching and fledging times from grassland passerine nests","interactions":[],"lastModifiedDate":"2018-03-30T12:27:32","indexId":"70039117","displayToPublicDate":"2012-07-20T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5103,"text":"Studies in Avian Biology","printIssn":"0197-9922","active":true,"publicationSubtype":{"id":24}},"seriesNumber":"43","chapter":"4","title":"Hatching and fledging times from grassland passerine nests","docAbstract":"<p><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;Accurate estimates of fledging age are needed in field studies to avoid inducing premature fledging or missing the fledging event. Both may lead to misinterpretation of nest fate. Correctly assessing nest fate and length of the nestling period can be critical for accurate calculation of nest survival rates. For researchers who mark nestlings, knowing the age at which their activities may cause young to leave nests prematurely could prevent introducing bias to their studies. We obtained estimates of fledging age using data from grassland bird nests monitored from hatching through fledging with video-surveillance systems in North Dakota and Minnesota during 1996&amp;ndash;2001. We compared these values to those obtained from traditional nest visits and from available literature. Mean and modal fledging ages for video-monitored nests were generally similar to those for visited nests, although Clay-colored Sparrows (Spizella pallida) typically fledged 1 day earlier from visited nests. Average fledging ages from both video and nest visits occurred within ranges reported in the literature, but expanded by 1&amp;ndash;2 days the upper age limit for Clay-colored Sparrows and the lower age limit for Bobolinks (Dolichonyx oryzivorus). Video showed that eggs hatched throughout the day whereas most young fledged in the morning (06:30&amp;ndash;12:30 CDT). Length of the hatching period for a clutch was usually >1 day and was positively correlated with clutch size. Length of the fledging period for a brood was usually <1 day, and in nearly half the nests, fledging was completed within <2 hr. Video surveillance has proven to be a useful tool for providing new information and for corroborating published statements related to hatching and fledging chronology. Comparison of data collected from video and nest visits showed that carefully conducted nest visits generally can provide reliable data for deriving estimates of survival.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:8403202,&quot;4&quot;:[null,2,16777215],&quot;11&quot;:4,&quot;14&quot;:[null,2,0],&quot;15&quot;:&quot;Inconsolata, monospace, arial, sans, sans-serif&quot;,&quot;16&quot;:11,&quot;26&quot;:400}\" data-sheets-formula=\"=VLOOKUP(R[0]C[-5],Fixed!R2C[-6]:C[-4],3,false)\">Accurate estimates of fledging age are needed in field studies to avoid inducing premature fledging or missing the fledging event. Both may lead to misinterpretation of nest fate. Correctly assessing nest fate and length of the nestling period can be critical for accurate calculation of nest survival rates. For researchers who mark nestlings, knowing the age at which their activities may cause young to leave nests prematurely could prevent introducing bias to their studies. We obtained estimates of fledging age using data from grassland bird nests monitored from hatching through fledging with video-surveillance systems in North Dakota and Minnesota during 1996&amp;ndash;2001. We compared these values to those obtained from traditional nest visits and from available literature. Mean and modal fledging ages for video-monitored nests were generally similar to those for visited nests, although Clay-colored Sparrows (Spizella pallida) typically fledged 1 day earlier from visited nests. Average fledging ages from both video and nest visits occurred within ranges reported in the literature, but expanded by 1&amp;ndash;2 days the upper age limit for Clay-colored Sparrows and the lower age limit for Bobolinks (Dolichonyx oryzivorus). Video showed that eggs hatched throughout the day whereas most young fledged in the morning (06:30&amp;ndash;12:30 CDT). Length of the hatching period for a clutch was usually &gt;1 day and was positively correlated with clutch size. Length of the fledging period for a brood was usually &lt;1 day, and in nearly half the nests, fledging was completed within &lt;2 hr. Video surveillance has proven to be a useful tool for providing new information and for corroborating published statements related to hatching and fledging chronology. Comparison of data collected from video and nest visits showed that carefully conducted nest visits generally can provide reliable data for deriving estimates of survival.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Video surveillance of nesting birds (Studies in Avian Biology no. 43)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of California Press","publisherLocation":"Berkeley, CA","isbn":"9780520273139","usgsCitation":"Pietz, P., Granfors, D.A., and Grant, T.A., 2012, Hatching and fledging times from grassland passerine nests, chap. 4 <i>of</i> Video surveillance of nesting birds (Studies in Avian Biology no. 43): Studies in Avian Biology, v. 43, p. 47-60.","productDescription":"14 p.","startPage":"47","endPage":"60","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":259082,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259074,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://www.ucpress.edu/book.php?isbn=9780520273139","linkFileType":{"id":5,"text":"html"}}],"volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2f86e4b0c8380cd5ce76","contributors":{"editors":[{"text":"Ribic, Christine A. caribic@usgs.gov","contributorId":831,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","middleInitial":"A.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":509024,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Thompson, Frank R. III","contributorId":12608,"corporation":false,"usgs":true,"family":"Thompson","given":"Frank","suffix":"III","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":509026,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Pietz, Pamela J. ppietz@usgs.gov","contributorId":2382,"corporation":false,"usgs":true,"family":"Pietz","given":"Pamela J.","email":"ppietz@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":509025,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Pietz, Pamela J. ppietz@usgs.gov","contributorId":2382,"corporation":false,"usgs":true,"family":"Pietz","given":"Pamela J.","email":"ppietz@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":465641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granfors, Diane A.","contributorId":174567,"corporation":false,"usgs":false,"family":"Granfors","given":"Diane","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":465643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grant, Todd A.","contributorId":194194,"corporation":false,"usgs":false,"family":"Grant","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":465642,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039119,"text":"ofr20121139 - 2012 - Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009 - Image-mosaic production and comparison with 2002 and 2005 image mosaics","interactions":[],"lastModifiedDate":"2012-07-21T01:01:57","indexId":"ofr20121139","displayToPublicDate":"2012-07-19T00:00:00","publicationYear":"2012","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":"2012-1139","title":"Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009 - Image-mosaic production and comparison with 2002 and 2005 image mosaics","docAbstract":"Airborne digital-image data were collected for the Arizona part of the Colorado River ecosystem below Glen Canyon Dam in 2009. These four-band image data are similar in wavelength band (blue, green, red, and near infrared) and spatial resolution (20 centimeters) to image collections of the river corridor in 2002 and 2005. These periodic image collections are used by the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey to monitor the effects of Glen Canyon Dam operations on the downstream ecosystem. The 2009 collection used the latest model of the Leica ADS40 airborne digital sensor (the SH52), which uses a single optic for all four bands and collects and stores band radiance in 12-bits, unlike the image sensors that GCMRC used in 2002 and 2005. This study examined the performance of the SH52 sensor, on the basis of the collected image data, and determined that the SH52 sensor provided superior data relative to the previously employed sensors (that is, an early ADS40 model and Zeiss Imaging's Digital Mapping Camera) in terms of band-image registration, dynamic range, saturation, linearity to ground reflectance, and noise level. The 2009 image data were provided as orthorectified segments of each flightline to constrain the size of the image files; each river segment was covered by 5 to 6 overlapping, linear flightlines. Most flightline images for each river segment had some surface-smear defects and some river segments had cloud shadows, but these two conditions did not generally coincide in the majority of the overlapping flightlines for a particular river segment. Therefore, the final image mosaic for the 450-kilometer (km)-long river corridor required careful selection and editing of numerous flightline segments (a total of 513 segments, each 3.2 km long) to minimize surface defects and cloud shadows. The final image mosaic has a total of only 3 km of surface defects. The final image mosaic for the western end of the corridor has areas of cloud shadow because of persistent inclement weather during data collection. This report presents visual comparisons of the 2002, 2005, and 2009 digital-image mosaics for various physical, biological, and cultural resources within the Colorado River ecosystem. All of the comparisons show the superior quality of the 2009 image data. In fact, the 2009 four-band image mosaic is perhaps the best image dataset that exists for the entire Arizona part of the Colorado River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121139","collaboration":"In cooperation with the Western Area Power Authority and the Bureau of Reclamation","usgsCitation":"Davis, P.A., 2012, Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009 - Image-mosaic production and comparison with 2002 and 2005 image mosaics: U.S. Geological Survey Open-File Report 2012-1139, vi, 82 p., https://doi.org/10.3133/ofr20121139.","productDescription":"vi, 82 p.","onlineOnly":"Y","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":259021,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1139.JPG"},{"id":259017,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1139/","linkFileType":{"id":5,"text":"html"}},{"id":259018,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1139/of2012-1139.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114,35 ], [ -114,37 ], [ -111,37 ], [ -111,35 ], [ -114,35 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e91de4b0c8380cd480e2","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":465644,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70039116,"text":"sir20125129 - 2012 - Fate and transport of cyanobacteria and associated toxins and taste-and-odor compounds from upstream reservoir releases in the Kansas River, Kansas, September and October 2011","interactions":[],"lastModifiedDate":"2012-07-20T01:01:46","indexId":"sir20125129","displayToPublicDate":"2012-07-19T00:00:00","publicationYear":"2012","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":"2012-5129","title":"Fate and transport of cyanobacteria and associated toxins and taste-and-odor compounds from upstream reservoir releases in the Kansas River, Kansas, September and October 2011","docAbstract":"Cyanobacteria cause a multitude of water-quality concerns, including the potential to produce toxins and taste-and-odor compounds. Toxins and taste-and-odor compounds may cause substantial economic and public health concerns and are of particular interest in lakes, reservoirs, and rivers that are used for drinking-water supply, recreation, or aquaculture. The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Water released from Milford Lake to the Kansas River during a toxic cyanobacterial bloom in late August 2011 prompted concerns about cyanobacteria and associated toxins and taste-and-odor compounds in downstream drinking-water supplies. During September and October 2011 water-quality samples were collected to characterize the transport of cyanobacteria and associated compounds from upstream reservoirs to the Kansas River. This study is one of the first to quantitatively document the transport of cyanobacteria and associated compounds during reservoir releases and improves understanding of the fate and transport of cyanotoxins and taste-and-odor compounds downstream from reservoirs. Milford Lake was the only reservoir in the study area with an ongoing cyanobacterial bloom during reservoir releases. Concentrations of cyanobacteria and associated toxins and taste-and-odor compounds in Milford Lake (upstream from the dam) were not necessarily indicative of outflow conditions (below the dam). Total microcystin concentrations, one of the most commonly occurring cyanobacterial toxins, in Milford Lake were 650 to 7,500 times higher than the Kansas Department of Health and Environment guidance level for a public health warning (20 micrograms per liter) for most of September 2011. By comparison, total microcystin concentrations in the Milford Lake outflow generally were less than 10 percent of the concentrations in surface accumulations, and never exceeded 20 micrograms per liter. The Republican River, downstream from Milford Lake, was the only Kansas River tributary with detectable microcystin concentrations throughout the study period, and concentrations exceeded 1 microgram per liter for most of September 2011. Microcystin was detected periodically in other tributaries, but concentrations were low (less than 0.3 micrograms per liter). In contrast, the taste-and-odor compounds geosmin and 2-methylisoborneol (MIB) were detected in all tributaries located immediately downstream from reservoirs and total concentrations generally exceeded the human detection threshold (5 to 10 nanograms per liter) from September through mid-October. Microcystin, geosmin, and MIB were not detected in the Smoky Hill River upstream from the confluence with the Republican River that forms the Kansas River. Within a week after initial reservoir releases, microcystin, geosmin, and MIB were detected throughout a 173-mile reach of the Kansas River; these compounds remained detectable throughout the reach until mid-October. Losses to groundwater when streamflows in the Kansas River were increasing indicate the potential for reservoir releases to affect groundwater quality as well as surface-water quality. Total microcystin concentrations in the Kansas River generally were highest within about 24 miles of the confluence of the Smoky Hill and Republican Rivers, and decreased downstream; concentrations exceeded 1 microgram per liter in the Kansas River upstream from Topeka during the first 2 weeks of September. Patterns in microcystin occurrence and concentration at Kansas River tributary and main-stem sites indicate that Milford Lake was the source of microcystin in the Kansas River; however, the source of taste-and-odor compounds was not as evident, possibly because multiple tributaries contributed taste-and-odor compounds to the Kansas River. Microcystin and taste-and-odor compounds co-occurred in 56 percent of samples collected, indicating co-occurrence was common. Despite frequent co-occurrence, the spatial and temporal patterns in microcystin, geosmin, and MIB were unique and did not necessarily match patterns in cyanobacterial abundance. Use of a single compound or cyanobacterial abundance alone cannot necessarily be used as an indicator of the presence or concentration of these compounds. Measured concentrations of cyanobacteria and associated compounds were substantially higher than expected concentrations based on simple dilution models at some sites and substantially lower at others, though spatial and temporal patterns were unique for individual compounds. Data were not collected in such a way to determine whether differences between measured and expected concentrations were statistically significant. Results, however, indicate that simple dilution models were not sufficient to describe the downstream transport of cyanobacteria and associated compounds in the Kansas River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125129","collaboration":"Prepared in cooperation with the City of Lawrence, the City of Topeka, Johnson County WaterOne, the Kansas Water Office, and the Kansas Department of Health and Environment","usgsCitation":"Graham, J.L., Ziegler, A., Loving, B.L., and Loftin, K.A., 2012, Fate and transport of cyanobacteria and associated toxins and taste-and-odor compounds from upstream reservoir releases in the Kansas River, Kansas, September and October 2011: U.S. Geological Survey Scientific Investigations Report 2012-5129, vi, 65 p.; appendices, https://doi.org/10.3133/sir20125129.","productDescription":"vi, 65 p.; appendices","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":259019,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5129.JPG"},{"id":259016,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5129/sir2012-5129.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259014,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5129/","linkFileType":{"id":5,"text":"html"}}],"scale":"2000000","projection":"Albers Equal-area Conic","country":"United States","state":"Kansas","otherGeospatial":"Kansas River;Milford Lake;Republican River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.5,38.5 ], [ -97.5,40 ], [ -94.75,40 ], [ -94.75,38.5 ], [ -97.5,38.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0f08e4b0c8380cd5371c","contributors":{"authors":[{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":465637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loving, Brian L. bloving@usgs.gov","contributorId":4565,"corporation":false,"usgs":true,"family":"Loving","given":"Brian","email":"bloving@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":465640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":465638,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70190229,"text":"70190229 - 2012 - Carbon storage, timber production, and biodiversity: comparing ecosystem services with multi-criteria decision analysis","interactions":[],"lastModifiedDate":"2017-08-18T17:42:29","indexId":"70190229","displayToPublicDate":"2012-07-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Carbon storage, timber production, and biodiversity: comparing ecosystem services with multi-criteria decision analysis","docAbstract":"Increasingly, land managers seek ways to manage forests for multiple ecosystem services and functions, yet considerable challenges exist in comparing disparate services and balancing trade-offs among them. We applied multi-criteria decision analysis (MCDA) and forest simulation models to simultaneously consider three objectives: (1) storing carbon, (2) producing timber and wood products, and (3) sustaining biodiversity. We used the Forest Vegetation Simulator (FVS) applied to 42 northern hardwood sites to simulate forest development over 100 years and to estimate carbon storage and timber production. We estimated biodiversity implications with occupancy models for 51 terrestrial bird species that were linked to FVS outputs. We simulated four alternative management prescriptions that spanned a range of harvesting intensities and forest structure retention. We found that silvicultural approaches emphasizing less frequent harvesting and greater structural retention could be expected to achieve the greatest net carbon storage but also produce less timber. More intensive prescriptions would enhance biodiversity because positive responses of early successional species exceeded negative responses of late successional species within the heavily forested study area. The combinations of weights assigned to objectives had a large influence on which prescriptions were scored as optimal. Overall, we found that a diversity of silvicultural approaches is likely to be preferable to any single approach, emphasizing the need for landscape-scale management to provide a full range of ecosystem goods and services. Our analytical framework that combined MCDA with forest simulation modeling was a powerful tool in understanding trade-offs among management objectives and how they can be simultaneously accommodated.","language":"English","publisher":"Ecological Society of America","doi":"10.1890/11-0864.1","usgsCitation":"Schwenk, W.S., Donovan, T., Keeton, W.S., and Nunery, J.S., 2012, Carbon storage, timber production, and biodiversity: comparing ecosystem services with multi-criteria decision analysis: Ecological Applications, v. 22, no. 5, p. 1612-1627, https://doi.org/10.1890/11-0864.1.","productDescription":"16 p.","startPage":"1612","endPage":"1627","ipdsId":"IP-029668","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":344970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5997fc9fe4b0b589267cd220","contributors":{"authors":[{"text":"Schwenk, W. Scott","contributorId":172274,"corporation":false,"usgs":false,"family":"Schwenk","given":"W.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":708072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donovan, Therese tdonovan@usgs.gov","contributorId":171599,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":708033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeton, William S.","contributorId":195759,"corporation":false,"usgs":false,"family":"Keeton","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":708073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nunery, Jared S.","contributorId":195760,"corporation":false,"usgs":false,"family":"Nunery","given":"Jared","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":708074,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188563,"text":"70188563 - 2012 - Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment","interactions":[],"lastModifiedDate":"2017-06-15T12:38:38","indexId":"70188563","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment","docAbstract":"<p><span>Debris flows can dramatically increase their volume, and hence their destructive potential, by entraining sediment. Yet quantitative constraints on rates and mechanics of sediment entrainment by debris flows are limited. Using an in situ sensor network in the headwaters of a natural catchment we measured flow and bed properties during six erosive debris-flow events. Despite similar flow properties and thicknesses of bed sediment entrained across all events, time-averaged entrainment rates were significantly faster for bed sediment that was saturated prior to flow arrival compared with rates for sediment that was dry. Bed sediment was entrained from the sediment-surface downward in a progressive fashion and occurred during passage of dense granular fronts as well as water-rich, inter-surge flow.</span><i>En masse</i><span>failure of bed sediment along the sediment-bedrock interface was never observed. Large-magnitude, high-frequency fluctuations in total normal basal stress were dissipated within the upper 5 cm of bed sediment. Within this near surface layer, concomitant fluctuations in Coulomb frictional resistance are expected, irrespective of the influence of pore fluid pressure or fluctuations in shear stress. If the near-surface sediment was wet as it was overridden by a flow, additional large-magnitude, high-frequency pore pressure fluctuations were measured in the near-surface bed sediment. These pore pressure fluctuations propagated to depth at subsonic rates and in a diffusive manner. The depth to which large excess pore pressures propagated was typically less than 10 cm, but scaled as (</span><i>D</i><span>/</span><i>f</i><sub><i>i</i></sub><span>)</span><sup>0.5</sup><span>, in which </span><i>D</i><span> is the hydraulic diffusivity and </span><i>f</i><sub><i>i&nbsp;</i></sub><span>is the frequency of a particular pore pressure fluctuation. Shallow penetration depths of granular-normal-stress fluctuations and excess pore pressures demonstrate that only near-surface bed sediment experiences the full dynamic range of effective-stress fluctuations, and as a result, can be more easily entrained than deeper sediment. These data provide robust tests for mechanical models of entrainment and demonstrate that a debris flow over wet bed sediment will be larger than the same flow over dry bed sediment.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011JF002278","usgsCitation":"McCoy, S., Kean, J.W., Coe, J.A., Tucker, G., Staley, D.M., and Wasklewicz, T., 2012, Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment: Journal of Geophysical Research F: Earth Surface, v. 117, no. F3, 25 p., https://doi.org/10.1029/2011JF002278.","productDescription":"25 p.","ipdsId":"IP-037498","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":474410,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011jf002278","text":"Publisher Index Page"},{"id":342549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Chalk Cliffs","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.45820617675781,\n              38.493369048060764\n            ],\n            [\n              -106.0400390625,\n              38.493369048060764\n            ],\n            [\n              -106.0400390625,\n              38.79690830348427\n            ],\n            [\n              -106.45820617675781,\n              38.79690830348427\n            ],\n            [\n              -106.45820617675781,\n              38.493369048060764\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"117","issue":"F3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-08-10","publicationStatus":"PW","scienceBaseUri":"59439c95e4b062508e31a9d5","contributors":{"authors":[{"text":"McCoy, S.W.","contributorId":192978,"corporation":false,"usgs":false,"family":"McCoy","given":"S.W.","email":"","affiliations":[],"preferred":false,"id":698350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":698348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tucker, G.E.","contributorId":150423,"corporation":false,"usgs":false,"family":"Tucker","given":"G.E.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":698351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698347,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wasklewicz, T.A.","contributorId":64922,"corporation":false,"usgs":true,"family":"Wasklewicz","given":"T.A.","affiliations":[],"preferred":false,"id":698352,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70188520,"text":"70188520 - 2012 - Chronostratigraphic framework for the IODP Expedition 318 cores from the Wilkes Land Margin: Constraints for paleoceanographic reconstruction","interactions":[],"lastModifiedDate":"2019-12-17T09:53:09","indexId":"70188520","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3002,"text":"Paleoceanography","active":true,"publicationSubtype":{"id":10}},"title":"Chronostratigraphic framework for the IODP Expedition 318 cores from the Wilkes Land Margin: Constraints for paleoceanographic reconstruction","docAbstract":"<p><span>The Integrated Ocean Drilling Program Expedition 318 to the Wilkes Land margin of Antarctica recovered a sedimentary succession ranging in age from lower Eocene to the Holocene. Excellent stratigraphic control is key to understanding the timing of paleoceanographic events through critical climate intervals. Drill sites recovered the lower and middle Eocene, nearly the entire Oligocene, the Miocene from about 17&nbsp;Ma, the entire Pliocene and much of the Pleistocene. The paleomagnetic properties are generally suitable for magnetostratigraphic interpretation, with well-behaved demagnetization diagrams, uniform distribution of declinations, and a clear separation into two inclination modes. Although the sequences were discontinuously recovered with many gaps due to coring, and there are hiatuses from sedimentary and tectonic processes, the magnetostratigraphic patterns are in general readily interpretable. Our interpretations are integrated with the diatom, radiolarian, calcareous nannofossils and dinoflagellate cyst (dinocyst) biostratigraphy. The magnetostratigraphy significantly improves the resolution of the chronostratigraphy, particularly in intervals with poor biostratigraphic control. However, Southern Ocean records with reliable magnetostratigraphies are notably scarce, and the data reported here provide an opportunity for improved calibration of the biostratigraphic records. In particular, we provide a rare magnetostratigraphic calibration for dinocyst biostratigraphy in the Paleogene and a substantially improved diatom calibration for the Pliocene. This paper presents the stratigraphic framework for future paleoceanographic proxy records which are being developed for the Wilkes Land margin cores. It further provides tight constraints on the duration of regional hiatuses inferred from seismic surveys of the region.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2012PA002308","usgsCitation":"Tauxe, L., Stickley, C., Sugisaki, S., Bijl, P., Bohaty, S.M., Brinkhuis, H., Escutia, C., Flores, J., Houben, A., Iwai, M., Jimenez-Espejo, F., McKay, R., Passchier, S., Pross, J., Riesselman, C., Röhl, U., Sangiorgi, F., Welsh, K., Klaus, A., Fehr, A., Bendle, J., Dunbar, R., Gonzalez, J., Hayden, T., Katsuki, K., Olney, M., Pekar, S., Shrivastava, P., van de Flierdt, T., Williams, T., and Yamane, M., 2012, Chronostratigraphic framework for the IODP Expedition 318 cores from the Wilkes Land Margin: Constraints for paleoceanographic reconstruction: Paleoceanography, v. 27, no. 2, 19 p., https://doi.org/10.1029/2012PA002308.","productDescription":"19 p.","ipdsId":"IP-038138","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":474411,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2012pa002308","text":"Publisher Index Page"},{"id":342498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-06-28","publicationStatus":"PW","scienceBaseUri":"59424b3de4b0764e6c65dc79","contributors":{"authors":[{"text":"Tauxe, L.","contributorId":53522,"corporation":false,"usgs":true,"family":"Tauxe","given":"L.","affiliations":[],"preferred":false,"id":698177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stickley, C.E.","contributorId":64523,"corporation":false,"usgs":true,"family":"Stickley","given":"C.E.","email":"","affiliations":[],"preferred":false,"id":698178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sugisaki, S.","contributorId":192929,"corporation":false,"usgs":false,"family":"Sugisaki","given":"S.","email":"","affiliations":[],"preferred":false,"id":698179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bijl, P.K.","contributorId":192930,"corporation":false,"usgs":false,"family":"Bijl","given":"P.K.","email":"","affiliations":[],"preferred":false,"id":698180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bohaty, S. M.","contributorId":192931,"corporation":false,"usgs":false,"family":"Bohaty","given":"S.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":698181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brinkhuis, H.","contributorId":89719,"corporation":false,"usgs":true,"family":"Brinkhuis","given":"H.","affiliations":[],"preferred":false,"id":698182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Escutia, C.","contributorId":88514,"corporation":false,"usgs":true,"family":"Escutia","given":"C.","affiliations":[],"preferred":false,"id":698183,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Flores, J.A.","contributorId":192932,"corporation":false,"usgs":false,"family":"Flores","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":698184,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Houben, A.J.P.","contributorId":192933,"corporation":false,"usgs":false,"family":"Houben","given":"A.J.P.","email":"","affiliations":[],"preferred":false,"id":698185,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Iwai, M.","contributorId":192934,"corporation":false,"usgs":false,"family":"Iwai","given":"M.","affiliations":[],"preferred":false,"id":698186,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jimenez-Espejo, F.","contributorId":192935,"corporation":false,"usgs":false,"family":"Jimenez-Espejo","given":"F.","email":"","affiliations":[],"preferred":false,"id":698187,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McKay, R.","contributorId":67323,"corporation":false,"usgs":true,"family":"McKay","given":"R.","email":"","affiliations":[],"preferred":false,"id":698188,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Passchier, S.","contributorId":15117,"corporation":false,"usgs":false,"family":"Passchier","given":"S.","email":"","affiliations":[],"preferred":false,"id":698189,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pross, J.","contributorId":192936,"corporation":false,"usgs":false,"family":"Pross","given":"J.","affiliations":[],"preferred":false,"id":698190,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Riesselman, Christina 0000-0002-2436-4306 criesselman@usgs.gov","orcid":"https://orcid.org/0000-0002-2436-4306","contributorId":4290,"corporation":false,"usgs":true,"family":"Riesselman","given":"Christina","email":"criesselman@usgs.gov","affiliations":[],"preferred":true,"id":698127,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Röhl, U.","contributorId":192937,"corporation":false,"usgs":false,"family":"Röhl","given":"U.","affiliations":[],"preferred":false,"id":698191,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sangiorgi, F.","contributorId":15828,"corporation":false,"usgs":true,"family":"Sangiorgi","given":"F.","affiliations":[],"preferred":false,"id":698192,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Welsh, K.","contributorId":192938,"corporation":false,"usgs":false,"family":"Welsh","given":"K.","email":"","affiliations":[],"preferred":false,"id":698194,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Klaus, A.","contributorId":70957,"corporation":false,"usgs":true,"family":"Klaus","given":"A.","email":"","affiliations":[],"preferred":false,"id":698195,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Fehr, A.","contributorId":192939,"corporation":false,"usgs":false,"family":"Fehr","given":"A.","email":"","affiliations":[],"preferred":false,"id":698196,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Bendle, J.A.P.","contributorId":192940,"corporation":false,"usgs":false,"family":"Bendle","given":"J.A.P.","affiliations":[],"preferred":false,"id":698197,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Dunbar, R.","contributorId":16722,"corporation":false,"usgs":true,"family":"Dunbar","given":"R.","affiliations":[],"preferred":false,"id":698198,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Gonzalez, J.","contributorId":192941,"corporation":false,"usgs":false,"family":"Gonzalez","given":"J.","email":"","affiliations":[],"preferred":false,"id":698199,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Hayden, T.","contributorId":85468,"corporation":false,"usgs":true,"family":"Hayden","given":"T.","email":"","affiliations":[],"preferred":false,"id":698200,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Katsuki, K.","contributorId":192942,"corporation":false,"usgs":false,"family":"Katsuki","given":"K.","affiliations":[],"preferred":false,"id":698201,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Olney, M.P.","contributorId":192943,"corporation":false,"usgs":false,"family":"Olney","given":"M.P.","email":"","affiliations":[],"preferred":false,"id":698202,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Pekar, S.F.","contributorId":192944,"corporation":false,"usgs":false,"family":"Pekar","given":"S.F.","email":"","affiliations":[],"preferred":false,"id":698203,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Shrivastava, P.K.","contributorId":192945,"corporation":false,"usgs":false,"family":"Shrivastava","given":"P.K.","email":"","affiliations":[],"preferred":false,"id":698204,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"van de Flierdt, T.","contributorId":55613,"corporation":false,"usgs":true,"family":"van de Flierdt","given":"T.","affiliations":[],"preferred":false,"id":698205,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Williams, T.","contributorId":47584,"corporation":false,"usgs":false,"family":"Williams","given":"T.","affiliations":[],"preferred":false,"id":698206,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Yamane, M.","contributorId":192946,"corporation":false,"usgs":false,"family":"Yamane","given":"M.","email":"","affiliations":[],"preferred":false,"id":698207,"contributorType":{"id":1,"text":"Authors"},"rank":31}]}}
,{"id":70188517,"text":"70188517 - 2012 - Patterns and controlling factors of species diversity in the Arctic Ocean","interactions":[],"lastModifiedDate":"2019-12-17T09:49:05","indexId":"70188517","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Patterns and controlling factors of species diversity in the Arctic Ocean","docAbstract":"<p><strong>Aim </strong> The Arctic Ocean is one of the last near-pristine regions on Earth, and, although human activities are expected to impact on Arctic ecosystems, we know very little about baseline patterns of Arctic Ocean biodiversity. This paper aims to describe Arctic Ocean-wide patterns of benthic biodiversity and to explore factors related to the large-scale species diversity patterns.</p><p><strong>Location </strong> Arctic Ocean.</p><p><strong>Methods </strong> We used large ostracode and foraminiferal datasets to describe the biodiversity patterns and applied comprehensive ecological modelling to test the degree to which these patterns are potentially governed by environmental factors, such as temperature, productivity, seasonality, ice cover and others. To test environmental control of the observed diversity patterns, subsets of samples for which all environmental parameters were available were analysed with multiple regression and model averaging.</p><p><strong>Results </strong> Well-known negative latitudinal species diversity gradients (LSDGs) were found in metazoan Ostracoda, but the LSDGs were unimodal with an intermediate maximum with respect to latitude in protozoan foraminifera. Depth species diversity gradients were unimodal, with peaks in diversity shallower than those in other oceans. Our modelling results showed that several factors are significant predictors of diversity, but the significant predictors were different among shallow marine ostracodes, deep-sea ostracodes and deep-sea foraminifera.</p><p><strong>Main conclusions </strong> On the basis of these Arctic Ocean-wide comprehensive datasets, we document large-scale diversity patterns with respect to latitude and depth. Our modelling results suggest that the underlying mechanisms causing these species diversity patterns are unexpectedly complex. The environmental parameters of temperature, surface productivity, seasonality of productivity, salinity and ice cover can all play a role in shaping large-scale diversity patterns, but their relative importance may depend on the ecological preferences of taxa and the oceanographic context of regions. These results suggest that a multiplicity of variables appear to be related to community structure in this system.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1365-2699.2012.02758.x","usgsCitation":"Yasuhara, M., Hunt, G., van Dijken, G., Arrigo, K.R., Cronin, T.M., and Wollenburg, J.E., 2012, Patterns and controlling factors of species diversity in the Arctic Ocean: Journal of Biogeography, v. 39, no. 11, p. 2081-2088, https://doi.org/10.1111/j.1365-2699.2012.02758.x.","productDescription":"8 p.","startPage":"2081","endPage":"2088","ipdsId":"IP-042007","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Ocean","volume":"39","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-08-17","publicationStatus":"PW","scienceBaseUri":"59424b3de4b0764e6c65dc7e","contributors":{"authors":[{"text":"Yasuhara, Moriaki","contributorId":178705,"corporation":false,"usgs":false,"family":"Yasuhara","given":"Moriaki","email":"","affiliations":[],"preferred":false,"id":698119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Gene","contributorId":178704,"corporation":false,"usgs":false,"family":"Hunt","given":"Gene","email":"","affiliations":[],"preferred":false,"id":698117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Dijken, Gert","contributorId":192909,"corporation":false,"usgs":false,"family":"van Dijken","given":"Gert","email":"","affiliations":[],"preferred":false,"id":698120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arrigo, Kevin R.","contributorId":192907,"corporation":false,"usgs":false,"family":"Arrigo","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":698116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":698115,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wollenburg, Jutta E.","contributorId":192908,"corporation":false,"usgs":false,"family":"Wollenburg","given":"Jutta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":698118,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70038714,"text":"70038714 - 2012 - A collaborative approach for estimating terrestrial wildlife abundance","interactions":[],"lastModifiedDate":"2012-07-19T01:01:49","indexId":"70038714","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A collaborative approach for estimating terrestrial wildlife abundance","docAbstract":"Accurately estimating abundance of wildlife is critical for establishing effective conservation and management strategies. Aerial methodologies for estimating abundance are common in developed countries, but they are often impractical for remote areas of developing countries where many of the world's endangered and threatened fauna exist. The alternative terrestrial methodologies can be constrained by limitations on access, technology, and human resources, and have rarely been comprehensively conducted for large terrestrial mammals at landscape scales. We attempted to overcome these problems by incorporating local peoples into a simultaneous point count of Asiatic wild ass (Equus hemionus) and goitered gazelle (Gazella subgutturosa) across the Great Gobi B Strictly Protected Area, Mongolia. Paired observers collected abundance and covariate metrics at 50 observation points and we estimated population sizes using distance sampling theory, but also assessed individual observer error to examine potential bias introduced by the large number of minimally trained observers. We estimated 5671 (95% CI = 3611&ndash;8907) wild asses and 5909 (95% CI = 3762&ndash;9279) gazelle inhabited the 11,027 km<sup>2</sup> study area at the time of our survey and found that the methodology developed was robust at absorbing the logistical challenges and wide range of observer abilities. This initiative serves as a functional model for estimating terrestrial wildlife abundance while integrating local people into scientific and conservation projects. This, in turn, creates vested interest in conservation by the people who are most influential in, and most affected by, the outcomes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.biocon.2012.05.006","usgsCitation":"Ransom, J.I., Kaczensky, P., Lubow, B., Ganbaatar, O., and Altansukh, N., 2012, A collaborative approach for estimating terrestrial wildlife abundance: Biological Conservation, v. 153, p. 219-226, https://doi.org/10.1016/j.biocon.2012.05.006.","productDescription":"8 p.","startPage":"219","endPage":"226","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":259002,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258992,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.biocon.2012.05.006","linkFileType":{"id":5,"text":"html"}}],"volume":"153","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e349e4b0c8380cd45f38","contributors":{"authors":[{"text":"Ransom, Jason I. 0000-0002-5930-4004","orcid":"https://orcid.org/0000-0002-5930-4004","contributorId":71645,"corporation":false,"usgs":true,"family":"Ransom","given":"Jason","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":464764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaczensky, Petra","contributorId":74623,"corporation":false,"usgs":true,"family":"Kaczensky","given":"Petra","email":"","affiliations":[],"preferred":false,"id":464765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lubow, Bruce C.","contributorId":59520,"corporation":false,"usgs":true,"family":"Lubow","given":"Bruce C.","affiliations":[],"preferred":false,"id":464763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ganbaatar, Oyunsaikhan","contributorId":42082,"corporation":false,"usgs":true,"family":"Ganbaatar","given":"Oyunsaikhan","email":"","affiliations":[],"preferred":false,"id":464762,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Altansukh, Nanjid","contributorId":92531,"corporation":false,"usgs":true,"family":"Altansukh","given":"Nanjid","email":"","affiliations":[],"preferred":false,"id":464766,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70039098,"text":"70039098 - 2012 - Evaluating the ability of regional models to predict local avian abundance","interactions":[],"lastModifiedDate":"2012-08-02T17:16:17","indexId":"70039098","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","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":"Evaluating the ability of regional models to predict local avian abundance","docAbstract":"Spatial modeling over broad scales can potentially direct conservation efforts to areas with high species-specific abundances. We examined the performance of regional models for predicting bird abundance at spatial scales typically addressed in conservation planning. Specifically, we used point count data on wood thrush (Hylocichla mustelina) and blue-winged warbler (Vermivora cyanoptera) from 2 time periods (1995-1998 and 2006-2007) to evaluate the ability of regional models derived via Bayesian hierarchical techniques to predict bird abundance. We developed models for each species within Bird Conservation Region (BCR) 23 in the upper midwestern United States at 800-ha, 8,000-ha, and approximately 80,000-ha scales. We obtained count data from the Breeding Bird Survey and land cover data from the National Land Cover Dataset (1992). We evaluated predictions from the best models, as defined by an information-theoretic criterion, using point count data collected within an ecological subregion of BCR 23 at 131 count stations in the 1990s and again in 2006-2007. Competing (Deviance Information Criteria <5) blue-winged warbler models accounted for 67% of the variability and suggested positive associations with forest edge and proportion of forest at the 8,000-ha scale, and negative associations with forest patch area (800 ha) and wetness (800 ha and 80,000 ha). The regional model performed best for blue-winged warbler predicted abundances from point counts conducted in Iowa during 1995-1996 (<i>r</i><sub>s</sub> = 0.57; <i>P</i> = 0.14), the survey period that most closely aligned with the time period of data used for regional model construction. Wood thrush models exhibited positive correlations with point count data for all survey areas and years combined (<i>r</i><sub>s</sub> = 0.58, <i>P</i> &le; 0.001). In comparison, blue-winged warbler models performed worse as time increased between the point count surveys and vintage of the model building data (<i>r</i><sub>s</sub> = 0.03, <i>P</i> = 0.92 for Iowa and <i>r</i><sub>s</sub> = 0.13, <i>P</i> = 0.51 for all areas, 2006-2007), likely related to the ephemeral nature of their preferred early successional habitat. Species abundance and sensitivity to changing habitat conditions seems to be an important factor in determining the predictive ability of regional models. Hierarchical models can be a useful tool for concentrating efforts at the scale of management units and should be one of many tools used by land managers, but we caution that the utility of such models may decrease over time for species preferring relatively ephemeral habitats if model inputs are not updated accordingly.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.374","usgsCitation":"LeBrun, J.J., Thogmartin, W.E., and Miller, J.R., 2012, Evaluating the ability of regional models to predict local avian abundance: Journal of Wildlife Management, v. 76, no. 6, p. 1177-1187, https://doi.org/10.1002/jwmg.374.","productDescription":"11 p.","startPage":"1177","endPage":"1187","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":258998,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258991,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.374","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"76","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-05-21","publicationStatus":"PW","scienceBaseUri":"505a0bf5e4b0c8380cd5297a","contributors":{"authors":[{"text":"LeBrun, Jaymi J.","contributorId":7959,"corporation":false,"usgs":true,"family":"LeBrun","given":"Jaymi","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":465614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":465612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, James R.","contributorId":6706,"corporation":false,"usgs":true,"family":"Miller","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465613,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039055,"text":"sim3185 - 2012 - Flood-Inundation Maps for a 1.6-Mile Reach of Salt Creek, Wood Dale, Illinois","interactions":[],"lastModifiedDate":"2012-07-18T01:01:44","indexId":"sim3185","displayToPublicDate":"2012-07-17T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3185","title":"Flood-Inundation Maps for a 1.6-Mile Reach of Salt Creek, Wood Dale, Illinois","docAbstract":"Digital flood-inundation maps for a 1.6-mile reach of Salt Creek from upstream of the Chicago, Milwaukee, St. Paul & Pacific Railroad to Elizabeth Drive, Wood Dale, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the DuPage County Stormwater Management Division. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent of flooding corresponding to selected water levels (gage heights) at the USGS streamgage on Salt Creek at Wood Dale, Illinois (station number 05531175). Current conditions at the USGS streamgage may be obtained on the Internet at http://waterdata.usgs.gov/usa/nwis/uv?05531175. In this study, flood profiles were computed for the stream reach by means of a one-dimensional unsteady flow Full EQuations (FEQ) model. The unsteady flow model was verified by comparing the rating curve output for a September 2008 flood event to discharge measurements collected at the Salt Creek at Wood Dale gage. The hydraulic model was then used to determine 14 water-surface profiles for gage heights at 0.5-ft intervals referenced to the streamgage datum and ranging from less than bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a Geographic Information System (GIS) Digital Elevation Model (DEM) (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The areal extent of the inundation was verified with high-water marks from a flood in July 2010 with a peak gage height of 14.08 ft recorded at the Salt Creek at Wood Dale gage. The availability of these maps along with Internet information regarding current gage height from USGS streamgages provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3185","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Division","usgsCitation":"Soong, D., Murphy, E., and Sharpe, J.B., 2012, Flood-Inundation Maps for a 1.6-Mile Reach of Salt Creek, Wood Dale, Illinois: U.S. Geological Survey Scientific Investigations Map 3185, v, 8 p.; Downloads Directory; PDF Downloads of Sheets 1-14: 18x 22 inches; ZIP Downloads of All 14 Map Sheets, https://doi.org/10.3133/sim3185.","productDescription":"v, 8 p.; Downloads Directory; PDF Downloads of Sheets 1-14: 18x 22 inches; ZIP Downloads of All 14 Map Sheets","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":258953,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3185.gif"},{"id":258949,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3185/","linkFileType":{"id":5,"text":"html"}},{"id":258950,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3185/contents/SIM3185_pamphlet.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"6500","projection":"Transverse Mercator","datum":"NAD 83","country":"United States","state":"Illinois","county":"Dupage County","city":"Wood Dale","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.98444444444445,41.95 ], [ -87.98444444444445,41.967222222222226 ], [ -87.96777777777778,41.967222222222226 ], [ -87.96777777777778,41.95 ], [ -87.98444444444445,41.95 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1158e4b0c8380cd53f7a","contributors":{"authors":[{"text":"Soong, David T.","contributorId":87487,"corporation":false,"usgs":true,"family":"Soong","given":"David T.","affiliations":[],"preferred":false,"id":465532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Elizabeth A.","contributorId":69660,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":465531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465530,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039065,"text":"sir20125052 - 2012 - Status of groundwater quality in the Upper Santa Ana Watershed, November 2006--March 2007--California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2012-07-18T01:01:44","indexId":"sir20125052","displayToPublicDate":"2012-07-17T00:00:00","publicationYear":"2012","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":"2012-5052","title":"Status of groundwater quality in the Upper Santa Ana Watershed, November 2006--March 2007--California GAMA Priority Basin Project","docAbstract":"Groundwater quality in the approximately 1,000-square-mile (2,590-square-kilometer) Upper Santa Ana Watershed (USAW) study unit was investigated as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is located in southern California in Riverside and San Bernardino Counties. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey and the Lawrence Livermore National Laboratory. The GAMA USAW study was designed to provide a spatially unbiased assessment of untreated groundwater quality within the primary aquifer systems in the study unit. The primary aquifer systems (hereinafter, primary aquifers) are defined as the perforation interval of wells listed in the California Department of Public Health (CDPH) database for the USAW study unit. The quality of groundwater in shallower or deeper water-bearing zones may differ from that in the primary aquifers; shallower groundwater may be more vulnerable to surficial contamination. The assessment is based on water-quality and ancillary data collected by the U.S. Geological Survey (USGS) from 90 wells during November 2006 through March 2007, and water-quality data from the CDPH database. The status of the current quality of the groundwater resource was assessed based on data from samples analyzed for volatile organic compounds (VOCs), pesticides, and naturally occurring inorganic constituents, such as major ions and trace elements. The status assessment is intended to characterize the quality of groundwater resources within the primary aquifers of the USAW study unit, not the treated drinking water delivered to consumers by water purveyors. Relative-concentrations (sample concentration divided by the health- or aesthetic-based benchmark concentration) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. A relative-concentration greater than (>) 1.0 indicates a concentration above a benchmark, and a relative-concentration less than or equal to (&le;) 1.0 indicates a concentration equal to or less than a benchmark. Organic and special-interest constituent relative-concentrations were classified as \"high\" (> 1.0), \"moderate\" (0.1 < relative-concentration &le; 1.0), or \"low\" (&le; 0.1). Inorganic constituent relative-concentrations were classified as \"high\" (> 1.0), \"moderate\" (0.5 < relative-concentration &le; 1.0), or \"low\" ( &le; 0.5). Aquifer-scale proportion was used as the primary metric in the status assessment for evaluating regional-scale groundwater quality. Aquifer-scale proportions are defined as the percentage of the area of the primary aquifer system with concentrations above or below specified thresholds relative to regulatory or aesthetic benchmarks. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifers with a relative-concentration greater than 1.0 for a particular constituent or class of constituents; percentage is based on an areal, rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the percentage of the primary aquifers with moderate and low relative-concentrations, respectively. Two statistical approaches&mdash;grid-based and spatially weighted&mdash;were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. Grid-based and spatially weighted estimates were comparable in the USAW study unit (within 90-percent confidence intervals). Inorganic constituents with human-health benchmarks had relative-concentrations that were high in 32.9 percent of the primary aquifers, moderate in 29.3 percent, and low in 37.8 percent. The high aquifer-scale proportion of these inorganic constituents primarily reflected high aquifer-scale proportions of nitrate (high relative-concentration in 25.3 percent of the aquifer), although seven other inorganic constituents with human-health benchmarks also were detected at high relative-concentrations in some percentage of the aquifer: arsenic, boron, fluoride, gross alpha activity, molybdenum, uranium, and vanadium. Perchlorate, as a constituent of special interest, was evaluated separately from other inorganic constituents, and had high relative-concentrations in 11.1 percent, moderate in 53.3 percent, and low or not detected in 35.6 percent of the primary aquifers. In contrast to the inorganic constituents, relative-concentrations of organic constituents (one or more) were high in 6.7 percent, moderate in 11.1 percent, and low or not detected in 82.2 percent of the primary aquifers. Of the 237 organic and special-interest constituents analyzed for, 39 constituents were detected (21 VOCs, 13 pesticides, 3 pharmaceuticals, and 2 constituents of special interest). All of the detected VOCs had health-based benchmarks, and five of these&mdash;1,1-dichloroethene, 1,2-dibromo-3-chloropropane (DBCP), tetrachloroethene (PCE), carbon tetrachloride, and trichloroethene (TCE)&mdash;were detected in at least one sample at a concentration above a benchmark (high relative-concentration). Seven of the 13 pesticides had health-based benchmarks, and none were detected above these benchmarks (no high relative-concentrations). Pharmaceuticals do not have health-based benchmarks. Thirteen organic constituents were frequently detected (detected in at least 10 percent of samples without regard to relative-concentrations): bromodichloromethane, chloroform, cis-1,2-dichloroethene, 1,1-dichloroethene, dichlorodifluoromethane (CFC-12), methyl tert-butyl ether (MTBE), PCE, TCE, trichlorofluoromethane (CFC-11), atrazine, bromacil, diuron, and simazine.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125052","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":"Kent, R., and Belitz, K., 2012, Status of groundwater quality in the Upper Santa Ana Watershed, November 2006--March 2007--California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2012-5052, viii, 88 p., https://doi.org/10.3133/sir20125052.","productDescription":"viii, 88 p.","numberOfPages":"100","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2006-11-01","temporalEnd":"2007-03-31","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":258970,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5052.jpg"},{"id":258955,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5052/","linkFileType":{"id":5,"text":"html"}},{"id":258956,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5052/pdf/sir20125052.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Upper Santa Ana Watershed","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b97cee4b08c986b31bc90","contributors":{"authors":[{"text":"Kent, Robert 0000-0003-4174-9467","orcid":"https://orcid.org/0000-0003-4174-9467","contributorId":20005,"corporation":false,"usgs":true,"family":"Kent","given":"Robert","affiliations":[],"preferred":false,"id":465551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":465550,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038948,"text":"70038948 - 2012 - Hotspot of accelerated sea-level rise on the Atlantic coast of North America","interactions":[],"lastModifiedDate":"2018-01-30T20:43:18","indexId":"70038948","displayToPublicDate":"2012-07-16T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Hotspot of accelerated sea-level rise on the Atlantic coast of North America","docAbstract":"Climate warming does not force sea-level rise (SLR) at the same rate everywhere. Rather, there are spatial variations of SLR superimposed on a global average rise. These variations are forced by dynamic processes, arising from circulation and variations in temperature and/or salinity, and by static equilibrium processes, arising from mass redistributions changing gravity and the Earth's rotation and shape. These sea-level variations form unique spatial patterns, yet there are very few observations verifying predicted patterns or fingerprints. Here, we present evidence of recently accelerated SLR in a unique 1,000-km-long hotspot on the highly populated North American Atlantic coast north of Cape Hatteras and show that it is consistent with a modelled fingerprint of dynamic SLR. Between 1950&ndash;1979 and 1980&ndash;2009, SLR rate increases in this northeast hotspot were ~ 3&ndash;4 times higher than the global average. Modelled dynamic plus steric SLR by 2100 at New York City ranges with Intergovernmental Panel on Climate Change scenario from 36 to 51 cm (ref. 3); lower emission scenarios project 24&ndash;36 cm (ref. 7). Extrapolations from data herein range from 20 to 29 cm. SLR superimposed on storm surge, wave run-up and set-up will increase the vulnerability of coastal cities to flooding, and beaches and wetlands to deterioration.","language":"English","publisher":"Nature Publishing Group","publisherLocation":"London, U.K.","doi":"10.1038/nclimate1597","usgsCitation":"Sallenger, Doran, K., and Howd, P.A., 2012, Hotspot of accelerated sea-level rise on the Atlantic coast of North America: Nature Climate Change, v. 2, no. 12, p. 884-888, https://doi.org/10.1038/nclimate1597.","productDescription":"5 p.","startPage":"884","endPage":"888","additionalOnlineFiles":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":258913,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Atlantic Coast, Cape Cod, Cape Hatteras, North America","volume":"2","issue":"12","noUsgsAuthors":false,"publicationDate":"2012-06-24","publicationStatus":"PW","scienceBaseUri":"505a323be4b0c8380cd5e624","contributors":{"authors":[{"text":"Sallenger, Jr.","contributorId":105768,"corporation":false,"usgs":true,"family":"Sallenger","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":465283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doran, Kara S. 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":33010,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","affiliations":[],"preferred":false,"id":465282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howd, Peter A. phowd@usgs.gov","contributorId":4105,"corporation":false,"usgs":true,"family":"Howd","given":"Peter","email":"phowd@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":465281,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039040,"text":"sir20125100 - 2012 - Geohydrology of Big Bear Valley, California: phase 1--geologic framework, recharge, and preliminary assessment of the source and age of groundwater","interactions":[],"lastModifiedDate":"2012-07-17T01:01:41","indexId":"sir20125100","displayToPublicDate":"2012-07-16T00:00:00","publicationYear":"2012","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":"2012-5100","title":"Geohydrology of Big Bear Valley, California: phase 1--geologic framework, recharge, and preliminary assessment of the source and age of groundwater","docAbstract":"The Big Bear Valley, located in the San Bernardino Mountains of southern California, has increased in population in recent years. Most of the water supply for the area is pumped from the alluvial deposits that form the Big Bear Valley groundwater basin. This study was conducted to better understand the thickness and structure of the groundwater basin in order to estimate the quantity and distribution of natural recharge to Big Bear Valley. A gravity survey was used to estimate the thickness of the alluvial deposits that form the Big Bear Valley groundwater basin. This determined that the alluvial deposits reach a maximum thickness of 1,500 to 2,000 feet beneath the center of Big Bear Lake and the area between Big Bear and Baldwin Lakes, and decrease to less than 500 feet thick beneath the eastern end of Big Bear Lake. Interferometric Synthetic Aperture Radar (InSAR) was used to measure pumping-induced land subsidence and to locate structures, such as faults, that could affect groundwater movement. The measurements indicated small amounts of land deformation (uplift and subsidence) in the area between Big Bear Lake and Baldwin Lake, the area near the city of Big Bear Lake, and the area near Sugarloaf, California. Both the gravity and InSAR measurements indicated the possible presence of subsurface faults in subbasins between Big Bear and Baldwin Lakes, but additional data are required for confirmation. The distribution and quantity of groundwater recharge in the area were evaluated by using a regional water-balance model (Basin Characterization Model, or BCM) and a daily rainfall-runoff model (INFILv3). The BCM calculated spatially distributed potential recharge in the study area of approximately 12,700 acre-feet per year (acre-ft/yr) of potential in-place recharge and 30,800 acre-ft/yr of potential runoff. Using the assumption that only 10 percent of the runoff becomes recharge, this approach indicated there is approximately 15,800 acre-ft/yr of total recharge in Big Bear Valley. The INFILv3 model was modified for this study to include a perched zone beneath the root zone to better simulate lateral seepage and recharge in the shallow subsurface in mountainous terrain. The climate input used in the INFILv3 model was developed by using daily climate data from 84 National Climatic Data Center stations and published Parameter Regression on Independent Slopes Model (PRISM) average monthly precipitation maps to match the drier average monthly precipitation measured in the Baldwin Lake drainage basin. This model resulted in a good representation of localized rain-shadow effects and calibrated well to measured lake volumes at Big Bear and Baldwin Lakes. The simulated average annual recharge was about 5,480 acre-ft/yr in the Big Bear study area, with about 2,800 acre-ft/yr in the Big Bear Lake surface-water drainage basin and about 2,680 acre-ft/yr in the Baldwin Lake surface-water drainage basin. One spring and eight wells were sampled and analyzed for chemical and isotopic data in 2005 and 2006 to determine if isotopic techniques could be used to assess the sources and ages of groundwater in the Big Bear Valley. This approach showed that the predominant source of recharge to the Big Bear Valley is winter precipitation falling on the surrounding mountains. The tritium and uncorrected carbon-14 ages of samples collected from wells for this study indicated that the groundwater basin contains water of different ages, ranging from modern to about 17,200-years old.The results of these investigations provide an understanding of the lateral and vertical extent of the groundwater basin, the spatial distribution of groundwater recharge, the processes responsible for the recharge, and the source and age of groundwater in the groundwater basin. Although the studies do not provide an understanding of the detailed water-bearing properties necessary to determine the groundwater availability of the basin, they do provide a framework for the future development of a groundwater model that would help to improve the understanding of the potential hydrologic effects of water-management alternatives in Big Bear Valley.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125100","collaboration":"Prepared in cooperation with Big Bear City Community Services District","usgsCitation":"Flint, L.E., Brandt, J., Christensen, A.H., Flint, A.L., Hevesi, J.A., Jachens, R., Kulongoski, J., Martin, P., and Sneed, M., 2012, Geohydrology of Big Bear Valley, California: phase 1--geologic framework, recharge, and preliminary assessment of the source and age of groundwater: U.S. Geological Survey Scientific Investigations Report 2012-5100, xiv, 112 p., https://doi.org/10.3133/sir20125100.","productDescription":"xiv, 112 p.","startPage":"i","endPage":"112","numberOfPages":"130","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":258929,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5100.jpg"},{"id":258920,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5100/pdf/sir20125100.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258917,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5100/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Big Bear Valley","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1802e4b0c8380cd55665","contributors":{"authors":[{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Justin 0000-0002-9397-6824","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":75798,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","affiliations":[],"preferred":false,"id":465507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, Allen H. 0000-0002-7061-5591 ahchrist@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-5591","contributorId":1510,"corporation":false,"usgs":true,"family":"Christensen","given":"Allen","email":"ahchrist@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":465503,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hevesi, Joseph A. 0000-0003-2898-1800 jhevesi@usgs.gov","orcid":"https://orcid.org/0000-0003-2898-1800","contributorId":1507,"corporation":false,"usgs":true,"family":"Hevesi","given":"Joseph","email":"jhevesi@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465504,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jachens, Robert","contributorId":54660,"corporation":false,"usgs":true,"family":"Jachens","given":"Robert","affiliations":[],"preferred":false,"id":465506,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":94750,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin T.","affiliations":[],"preferred":false,"id":465508,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Martin, Peter pmmartin@usgs.gov","contributorId":799,"corporation":false,"usgs":true,"family":"Martin","given":"Peter","email":"pmmartin@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465501,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465500,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70039029,"text":"70039029 - 2012 - Mate loss affects survival but not breeding in black brant geese","interactions":[],"lastModifiedDate":"2012-08-02T17:16:17","indexId":"70039029","displayToPublicDate":"2012-07-16T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":981,"text":"Behavioral Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mate loss affects survival but not breeding in black brant geese","docAbstract":"For birds maintaining long-term monogamous relationships, mate loss might be expected to reduce fitness, either through reduced survival or reduced future reproductive investment. We used harvest of male brant during regular sport hunting seasons as an experimental removal to examine effects of mate loss on fitness of female black brant (Branta bernicla nigricans; hereafter brant). We used the Barker model in program MARK to examine effects of mate loss on annual survival, reporting rate, and permanent emigration. Survival rates decreased from 0.847 &plusmn; 0.004 for females who did not lose their mates to 0.690 &plusmn; 0.072 for birds who lost mates. Seber ring reporting rate for females that lost their mates were 2 times higher than those that did not lose mates, 0.12 &plusmn; 0.086 and 0.06 &plusmn; 0.006, respectively, indicating that mate loss increased vulnerability to harvest and possibly other forms of predation. We found little support for effects of mate loss on fidelity to breeding site and consequently on breeding. Our results indicate substantial fitness costs to females associated with mate loss, but that females who survived and were able to form new pair bonds may have been higher quality than the average female in the population.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Behavioral Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Oxford Journals","publisherLocation":"Oxford, U.K.","doi":"10.1093/beheco/ars009","usgsCitation":"Nicolai, C.A., Sedinger, J.S., Ward, D.H., and Boyd, W.S., 2012, Mate loss affects survival but not breeding in black brant geese: Behavioral Ecology, v. 23, no. 3, p. 643-648, https://doi.org/10.1093/beheco/ars009.","productDescription":"6 p.","startPage":"643","endPage":"648","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":474412,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10.1093/beheco/ars009","text":"External Repository"},{"id":258916,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258908,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1093/beheco/ars009","linkFileType":{"id":5,"text":"html"}}],"volume":"23","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-02-09","publicationStatus":"PW","scienceBaseUri":"505a5270e4b0c8380cd6c3f7","contributors":{"authors":[{"text":"Nicolai, Christopher A.","contributorId":107140,"corporation":false,"usgs":true,"family":"Nicolai","given":"Christopher","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":465489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sedinger, James S.","contributorId":84861,"corporation":false,"usgs":false,"family":"Sedinger","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":465488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":465486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyd, W. Sean","contributorId":11048,"corporation":false,"usgs":true,"family":"Boyd","given":"W.","email":"","middleInitial":"Sean","affiliations":[],"preferred":false,"id":465487,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70039021,"text":"70039021 - 2012 - A climate for speciation: rapid spatial diversification within the Sorex cinereus complex of shrews","interactions":[],"lastModifiedDate":"2018-08-20T18:10:25","indexId":"70039021","displayToPublicDate":"2012-07-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2779,"text":"Molecular Phylogenetics and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A climate for speciation: rapid spatial diversification within the Sorex cinereus complex of shrews","docAbstract":"The cyclic climate regime of the late Quaternary caused dramatic environmental change at high latitudes. Although these events may have been brief in periodicity from an evolutionary standpoint, multiple episodes of allopatry and divergence have been implicated in rapid radiations of a number of organisms. Shrews of the Sorex cinereus complex have long challenged taxonomists due to similar morphology and parapatric geographic ranges. Here, multi-locus phylogenetic and demographic assessments using a coalescent framework were combined to investigate spatiotemporal evolution of 13 nominal species with a widespread distribution throughout North America and across Beringia into Siberia. For these species, we first test a hypothesis of recent differentiation in response to Pleistocene climate versus more ancient divergence that would coincide with pre-Pleistocene perturbations. We then investigate the processes driving diversification over multiple continents. Our genetic analyses highlight novel diversity within these morphologically conserved mammals and clarify relationships between geographic distribution and evolutionary history. Demography within and among species indicates both regional stability and rapid expansion. Ancestral ecological differentiation coincident with early cladogenesis within the complex enabled alternating and repeated episodes of allopatry and expansion where successive glacial and interglacial phases each promoted divergence. The Sorex cinereus complex constitutes a valuable model for future comparative assessments of evolution in response to cyclic environmental change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Molecular Phylogenetics and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ympev.2012.05.021","usgsCitation":"Hope, A.G., Speer, K.A., Demboski, J.R., Talbot, S.L., and Cook, J.A., 2012, A climate for speciation: rapid spatial diversification within the Sorex cinereus complex of shrews: Molecular Phylogenetics and Evolution, v. 64, no. 3, p. 671-684, https://doi.org/10.1016/j.ympev.2012.05.021.","productDescription":"14 p.","startPage":"671","endPage":"684","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":258881,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258878,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ympev.2012.05.021","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"North America;Siberia","volume":"64","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e343e4b0c8380cd45efc","contributors":{"authors":[{"text":"Hope, Andrew G. 0000-0003-3814-2891 ahope@usgs.gov","orcid":"https://orcid.org/0000-0003-3814-2891","contributorId":4309,"corporation":false,"usgs":true,"family":"Hope","given":"Andrew","email":"ahope@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":465456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Speer, Kelly A.","contributorId":104754,"corporation":false,"usgs":true,"family":"Speer","given":"Kelly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":465458,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Demboski, John R.","contributorId":101133,"corporation":false,"usgs":true,"family":"Demboski","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465457,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":465454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, Joseph A.","contributorId":8323,"corporation":false,"usgs":false,"family":"Cook","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":465455,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70039015,"text":"ofr20121143 - 2012 - Independent technical review and analysis of hydraulic modeling and hydrology under low-flow conditions of the Des Plaines River near Riverside, Illinois","interactions":[],"lastModifiedDate":"2012-07-14T01:01:39","indexId":"ofr20121143","displayToPublicDate":"2012-07-13T00:00:00","publicationYear":"2012","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":"2012-1143","title":"Independent technical review and analysis of hydraulic modeling and hydrology under low-flow conditions of the Des Plaines River near Riverside, Illinois","docAbstract":"The U.S. Geological Survey (USGS) has operated a streamgage and published daily flows for the Des Plaines River at Riverside since Oct. 1, 1943. A HEC-RAS model has been developed to estimate the effect of the removal of Hofmann Dam near the gage on low-flow elevations in the reach approximately 3 miles upstream from the dam. The Village of Riverside, the Illinois Department of Natural Resources-Office of Water Resources (IDNR-OWR), and the U. S. Army Corps of Engineers-Chicago District (USACE-Chicago) are interested in verifying the performance of the HEC-RAS model for specific low-flow conditions, and obtaining an estimate of selected daily flow quantiles and other low-flow statistics for a selected period of record that best represents current hydrologic conditions. Because the USGS publishes streamflow records for the Des Plaines River system and provides unbiased analyses of flows and stream hydraulic characteristics, the USGS served as an Independent Technical Reviewer (ITR) for this study.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121143","usgsCitation":"Over, T.M., Straub, T., Hortness, J., and Murphy, E., 2012, Independent technical review and analysis of hydraulic modeling and hydrology under low-flow conditions of the Des Plaines River near Riverside, Illinois: U.S. Geological Survey Open-File Report 2012-1143, v, 73 p., https://doi.org/10.3133/ofr20121143.","productDescription":"v, 73 p.","onlineOnly":"Y","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":258856,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1143.JPG"},{"id":258846,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1143/pdf/ofr20121143_071212.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258847,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1143/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois","otherGeospatial":"Hofmann Dam;Des Plaines River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.83416666666666,41.80138888888889 ], [ -87.83416666666666,41.83444444444444 ], [ -87.81666666666666,41.83444444444444 ], [ -87.81666666666666,41.80138888888889 ], [ -87.83416666666666,41.80138888888889 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3a11e4b0c8380cd61b37","contributors":{"authors":[{"text":"Over, Thomas M. 0000-0001-8280-4368 tmover@usgs.gov","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":1819,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"tmover@usgs.gov","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Straub, Timothy D. 0000-0002-5896-0851 tdstraub@usgs.gov","orcid":"https://orcid.org/0000-0002-5896-0851","contributorId":2273,"corporation":false,"usgs":true,"family":"Straub","given":"Timothy D.","email":"tdstraub@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":465431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hortness, Jon 0000-0002-9809-2876 hortness@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-2876","contributorId":3601,"corporation":false,"usgs":true,"family":"Hortness","given":"Jon","email":"hortness@usgs.gov","affiliations":[],"preferred":true,"id":465432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Elizabeth A.","contributorId":69660,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":465433,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70039004,"text":"sir20125136 - 2012 - Simulation of streamflow, evapotranspiration, and groundwater recharge in the middle Nueces River watershed, south Texas, 1961-2008","interactions":[],"lastModifiedDate":"2016-08-08T08:53:15","indexId":"sir20125136","displayToPublicDate":"2012-07-13T00:00:00","publicationYear":"2012","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":"2012-5136","title":"Simulation of streamflow, evapotranspiration, and groundwater recharge in the middle Nueces River watershed, south Texas, 1961-2008","docAbstract":"<p>The U.S. Geological Survey&mdash;in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe&ndash;Blanco River Authority; San Antonio River Authority; and San Antonio Water System&mdash; configured, calibrated, and tested a watershed model for a study area consisting of about 7,726 square miles of the middle Nueces River watershed in south Texas. The purpose of the model is to contribute to the understanding of watershed processes and hydrologic conditions in the middle Nueces River watershed. The model simulates streamflow, evapotranspiration, and groundwater recharge by using a numerical representation of physical characteristics of the landscape and meteorological and streamflow data.</p>\n<p>Model simulations of streamflow, evapotranspiration, and groundwater recharge were performed for various periods of record depending upon available gaged data for input and comparison, starting as early as 1961. Because of the large size of the study area, the middle Nueces River watershed was divided into eight subwatersheds, and separate Hydrological Simulation Program&mdash;FORTRAN models were developed for each subwatershed. Simulation of the overall study area involved running simulations in downstream order. Output from the model was summarized by subwatershed, point locations, stream and reservoir reaches, and the Carrizo&ndash; Wilcox aquifer outcrop area. Four long-term U.S. Geological Survey streamflow-gaging stations were used for streamflow model calibration and testing with data from 1990 to 2008. Monthly evaporation estimates from 2001 to 2008 and waterlevel data from 1961 to 2008 at Lake Corpus Christi also were used for model calibration. Additionally, evapotranspiration data for 2006&ndash;8 from a U.S. Geological Survey meteorological station in Medina County were used for calibration.</p>\n<p>Streamflow calibrations were considered poor to very good. The 2000&ndash;8 calibration results were characterized as good to very good for total flow volumes and for the volume of the highest 10 percent of daily flows. Calibration results for streamflow volumes of the lowest 50 percent of daily flows were considered poor. The daily streamflow calibration at U.S. Geological Survey streamflow-gaging station 08210000 Nueces River near Three Rivers, Tex., had the lowest (best) root mean square error, and U.S. Geological Survey streamflow-gaging station 08194500 Nueces River near Tilden, Tex., had the highest root mean square error expressed as a percentage of the mean flow rate. The mean daily reservoir volume during 1961&ndash;2008 was 182,000 acre-feet. Simulated mean daily reservoir volume was within 9 percent of this computed volume.</p>\n<p>Selected results of the model include streamflow yields for the subwatersheds and water-balance information for the Carrizo&ndash;Wilcox aquifer outcrop area. For the entire model domain, the area-weighted mean streamflow yield from 1961 to 2008 was 1.12 inches/year. The mean annual rainfall on the outcrop area during the 1961&ndash;2008 simulation period was 21.7 inches. Of this rainfall, an annual mean of 20.1 inches (about 93 percent) was simulated as evapotranspiration, 1.2 inches (about 6 percent) was simulated as groundwater recharge, and 0.5 inches (about 2 percent) was simulated as surface runoff.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125136","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe-Blanco River Authority; San Antonio River Authority; and San Antonio Water System","usgsCitation":"Dietsch, B.J., and Wehmeyer, L.L., 2012, Simulation of streamflow, evapotranspiration, and groundwater recharge in the middle Nueces River watershed, south Texas, 1961-2008: U.S. Geological Survey Scientific Investigations Report 2012-5136, vi, 37 p., https://doi.org/10.3133/sir20125136.","productDescription":"vi, 37 p.","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":258887,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5136.JPG"},{"id":258871,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5136/pdf/sir2012-5136.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258870,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5136/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator","datum":"North American Datum","country":"United States","state":"Texas","otherGeospatial":"Nueces River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.5,27.5 ], [ -100.5,30.000833333333333 ], [ -97.5,30.000833333333333 ], [ -97.5,27.5 ], [ -100.5,27.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9096e4b08c986b3195b4","contributors":{"authors":[{"text":"Dietsch, Benjamin J. 0000-0003-1090-409X bdietsch@usgs.gov","orcid":"https://orcid.org/0000-0003-1090-409X","contributorId":1346,"corporation":false,"usgs":true,"family":"Dietsch","given":"Benjamin","email":"bdietsch@usgs.gov","middleInitial":"J.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wehmeyer, Loren L.","contributorId":90412,"corporation":false,"usgs":true,"family":"Wehmeyer","given":"Loren","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":465397,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040434,"text":"pp1661F - 2012 - Turbidite event history—Methods and implications for Holocene paleoseismicity of the Cascadia subduction zone","interactions":[],"lastModifiedDate":"2022-05-13T20:01:45.91758","indexId":"pp1661F","displayToPublicDate":"2012-07-12T08:40:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1661","chapter":"F","displayTitle":"Turbidite Event History—Methods and Implications for Holocene Paleoseismicity of the Cascadia Subduction Zone","title":"Turbidite event history—Methods and implications for Holocene paleoseismicity of the Cascadia subduction zone","docAbstract":"<p>Turbidite systems along the continental margin of Cascadia Basin from Vancouver Island, Canada, to Cape Mendocino, California, United States, have been investigated with swath bathymetry; newly collected and archive piston, gravity, kasten, and box cores; and accelerator mass spectrometry radiocarbon dates. The purpose of this study is to test the applicability of the Holocene turbidite record as a paleoseismic record for the Cascadia subduction zone. The Cascadia Basin is an ideal place to develop a turbidite paleoseismologic method and to record paleoearthquakes because (1) a single subduction-zone fault underlies the Cascadia submarine-canyon systems; (2) multiple tributary canyons and a variety of turbidite systems and sedimentary sources exist to use in tests of synchronous turbidite triggering; (3) the Cascadia trench is completely sediment filled, allowing channel systems to trend seaward across the abyssal plain, rather than merging in the trench; (4) the continental shelf is wide, favoring disconnection of Holocene river systems from their largely Pleistocene canyons; and (5) excellent stratigraphic datums, including the Mazama ash and distinguishable sedimentological and faunal changes near the Pleistocene-Holocene boundary, are present for correlating events and anchoring the temporal framework. </p><p>Multiple tributaries to Cascadia Channel with 50- to 150-km spacing, and a wide variety of other turbidite systems with different sedimentary sources contain 13 post-Mazama-ash and 19 Holocene turbidites. Likely correlative sequences are found in Cascadia Channel, Juan de Fuca Channel off Washington, and Hydrate Ridge slope basin and Astoria Fan off northern and central Oregon. A probable correlative sequence of turbidites is also found in cores on Rogue Apron off southern Oregon. The Hydrate Ridge and Rogue Apron cores also include 12-22 interspersed thinner turbidite beds respectively. </p><p>We use <sup>14</sup>C dates, relative-dating tests at channel confluences, and stratigraphic correlation of turbidites to determine whether turbidites deposited in separate channel systems are correlative - triggered by a common event. In most cases, these tests can separate earthquake-triggered turbidity currents from other possible sources. The 10,000-year turbidite record along the Cascadia margin passes several tests for synchronous triggering and correlates well with the shorter onshore paleoseismic record. The synchroneity of a 10,000-year turbidite-event record for 500 km along the northern half of the Cascadia subduction zone is best explained by paleoseismic triggering by great earthquakes. Similarly, we find a likely synchronous record in southern Cascadia, including correlated additional events along the southern margin. We examine the applicability of other regional triggers, such as storm waves, storm surges, hyperpycnal flows, and teletsunami, specifically for the Cascadia margin. </p><p>The average age of the oldest turbidite emplacement event in the 10-0-ka series is 9,800±~210 cal yr B.P. and the youngest is 270±~120 cal yr B.P., indistinguishable from the A.D. 1700 (250 cal yr B.P.) Cascadia earthquake. The northern events define a great earthquake recurrence of ~500-530 years. The recurrence times and averages are supported by the thickness of hemipelagic sediment deposited between turbidite beds. The southern Oregon and northern California margins represent at least three segments that include all of the northern ruptures, as well as ~22 thinner turbidites of restricted latitude range that are correlated between multiple sites. At least two northern California sites, Trinidad and Eel Canyon/pools, record additional turbidites, which may be a mix of earthquake and sedimentologically or storm-triggered events, particularly during the early Holocene when a close connection existed between these canyons and associated river systems. </p><p>The combined stratigraphic correlations, hemipelagic analysis, and <sup>14</sup>C framework suggest that the Cascadia margin has three rupture modes: (1) 19-20 full-length or nearly full length ruptures; (2) three or four ruptures comprising the southern 50-70 percent of the margin; and (3) 18-20 smaller southern-margin ruptures during the past 10 k.y., with the possibility of additional southern-margin events that are presently uncorrelated. The shorter rupture extents and thinner turbidites of the southern margin correspond well with spatial extents interpreted from the limited onshore paleoseismic record, supporting margin segmentation of southern Cascadia. The sequence of 41 events defines an average recurrence period for the southern Cascadia margin of ~240 years during the past 10 k.y. </p><p>Time-independent probabilities for segmented ruptures range from 7-12 percent in 50 years for full or nearly full margin ruptures to ~21 percent in 50 years for a southern-margin rupture. Time-dependent probabilities are similar for northern margin events at ~7-12 percent and 37-42 percent in 50 years for the southern margin. Failure analysis suggests that by the year 2060, Cascadia will have exceeded ~27 percent of Holocene recurrence intervals for the northern margin and 85 percent of recurrence intervals for the southern margin. </p><p>The long earthquake record established in Cascadia allows tests of recurrence models rarely possible elsewhere. Turbidite mass per event along the Cascadia margin reveals a consistent record for many of the Cascadia turbidites. We infer that larger turbidites likely represent larger earthquakes. Mass per event and magnitude estimates also correlate modestly with following time intervals for each event, suggesting that Cascadia full or nearly full margin ruptures weakly support a time-predictable model of recurrence. The long paleoseismic record also suggests a pattern of clustered earthquakes that includes four or five cycles of two to five earthquakes during the past 10 k.y., separated by unusually long intervals. </p><p>We suggest that the pattern of long time intervals and longer ruptures for the northern and central margins may be a function of high sediment supply on the incoming plate, smoothing asperities, and potential barriers. The smaller southern Cascadia segments correspond to thinner incoming sediment sections and potentially greater interaction between lower-plate and upper-plate heterogeneities. </p><p>The Cascadia Basin turbidite record establishes new paleoseismic techniques utilizing marine turbidite-event stratigraphy during sea-level highstands. These techniques can be applied in other specific settings worldwide, where an extensive fault traverses a continental margin that has several active turbidite systems.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Earthquake Hazards of the Pacific Northwest Coastal and Marine Regions","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1661F","usgsCitation":"Goldfinger, C., Nelson, C.H., Morey, A.E., Johnson, J.E., Patton, J.R., Karabanov, E., Gutiérrez-Pastor, J., Eriksson, A.T., Gràcia, E., Dunhill, G., Enkin, R.J., Dallimore, A., and Vallier, T., 2012, Turbidite event history—Methods and implications for Holocene paleoseismicity of the Cascadia subduction zone: U.S. Geological Survey Professional Paper 1661–F, 170 p. (Available at https://pubs.usgs.gov/pp/pp1661f/).","productDescription":"Report: x, 170 p.; Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":379,"text":"Menlo Park Science Center","active":false,"usgs":true}],"links":[{"id":370579,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/pp1661f/pp1661f.pdf","size":"25.7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":370577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/pp1661f/coverthb3.jpg"},{"id":370581,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/pp1661f/appendixes.zip","size":"12.7 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130.000000,38.750000 ], [ -130.000000,49.000000 ], [ -122.000000,49.000000 ], [ -122.000000,38.750000 ], [ -130.000000,38.750000 ] ] ] } } ] }","contact":"<p><a href=\"http://activetectonics.coas.oregonstate.edu/\" data-mce-href=\"http://activetectonics.coas.oregonstate.edu/\">Active Tectonics and Seafloor Mapping Lab</a><br>Oregon State University<br>College of Earth, Ocean, and Atmospheric Sciences<br>Burt 130, Corvallis OR 97331<br></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Significance of Turbidite Paleoseismology</li><li>Cascadia Subduction Zone and Great Earthquake Potential</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Implications for Earthquake Hazards in Cascadia Basin and the Northern San Andreas</li><li>Fault</li><li>Conclusions</li><li>Lessons Learned</li><li>Acknowledgments</li><li>References Cited</li><li>Appendixes 1–11</li></ul>","publishedDate":"2012-07-12","noUsgsAuthors":false,"publicationDate":"2012-07-12","publicationStatus":"PW","scienceBaseUri":"50e55870e4b0a4aa5bb02d7d","contributors":{"editors":[{"text":"Kayen, Robert","contributorId":12030,"corporation":false,"usgs":true,"family":"Kayen","given":"Robert","affiliations":[],"preferred":false,"id":509061,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Goldfinger, Chris","contributorId":59460,"corporation":false,"usgs":true,"family":"Goldfinger","given":"Chris","affiliations":[],"preferred":false,"id":468316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, C. Hans","contributorId":34909,"corporation":false,"usgs":true,"family":"Nelson","given":"C.","email":"","middleInitial":"Hans","affiliations":[],"preferred":false,"id":468313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morey, Ann E.","contributorId":41694,"corporation":false,"usgs":true,"family":"Morey","given":"Ann E.","affiliations":[],"preferred":false,"id":468315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Joel E.","contributorId":29259,"corporation":false,"usgs":true,"family":"Johnson","given":"Joel E.","affiliations":[],"preferred":false,"id":468312,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Patton, Jason R.","contributorId":22619,"corporation":false,"usgs":true,"family":"Patton","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":468311,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karabanov, Eugene B.","contributorId":7960,"corporation":false,"usgs":false,"family":"Karabanov","given":"Eugene","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":468307,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gutierrez-Pastor, Julia","contributorId":14240,"corporation":false,"usgs":true,"family":"Gutierrez-Pastor","given":"Julia","email":"","affiliations":[],"preferred":false,"id":468309,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eriksson, Andrew T.","contributorId":97759,"corporation":false,"usgs":true,"family":"Eriksson","given":"Andrew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":468319,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gracia, Eulalia","contributorId":12735,"corporation":false,"usgs":true,"family":"Gracia","given":"Eulalia","email":"","affiliations":[],"preferred":false,"id":468308,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dunhill, Gita","contributorId":36169,"corporation":false,"usgs":true,"family":"Dunhill","given":"Gita","email":"","affiliations":[],"preferred":false,"id":468314,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Enkin, Randolph J.","contributorId":75373,"corporation":false,"usgs":true,"family":"Enkin","given":"Randolph","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":468317,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dallimore, Audrey","contributorId":98165,"corporation":false,"usgs":true,"family":"Dallimore","given":"Audrey","email":"","affiliations":[],"preferred":false,"id":468320,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Vallier, Tracy","contributorId":96948,"corporation":false,"usgs":true,"family":"Vallier","given":"Tracy","affiliations":[],"preferred":false,"id":468318,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70039008,"text":"70039008 - 2012 - Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions","interactions":[],"lastModifiedDate":"2012-07-13T01:01:54","indexId":"70039008","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions","docAbstract":"1. Understanding the factors affecting species occurrence is a pre-eminent focus of applied ecological research. However, direct information about species occurrence is lacking for many species. Instead, researchers sometimes have to rely on so-called presence-only data (i.e. when no direct information about absences is available), which often results from opportunistic, unstructured sampling. MAXENT is a widely used software program designed to model and map species distribution using presence-only data. 2. We provide a critical review of MAXENT as applied to species distribution modelling and discuss how it can lead to inferential errors. A chief concern is that MAXENT produces a number of poorly defined indices that are not directly related to the actual parameter of interest &ndash; the probability of occurrence (<i>&psi;</i>). This focus on an index was motivated by the belief that it is not possible to estimate <i>&psi;</i> from presence-only data; however, we demonstrate that <i>&psi;</i> is identifiable using conventional likelihood methods under the assumptions of random sampling and constant probability of species detection. 3. The model is implemented in a convenient r package which we use to apply the model to simulated data and data from the North American Breeding Bird Survey. We demonstrate that MAXENT produces extreme under-predictions when compared to estimates produced by logistic regression which uses the full (presence/absence) data set. We note that MAXENT predictions are extremely sensitive to specification of the background prevalence, which is not objectively estimated using the MAXENT method. 4. As with MAXENT, formal model-based inference requires a random sample of presence locations. Many presence-only data sets, such as those based on museum records and herbarium collections, may not satisfy this assumption. However, when sampling is random, we believe that inference should be based on formal methods that facilitate inference about interpretable ecological quantities instead of vaguely defined indices.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Methods in Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.2041-210X.2011.00182.x","usgsCitation":"Royle, J., Chandler, R.B., Yackulic, C., and Nichols, J., 2012, Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions: Methods in Ecology and Evolution, v. 3, no. 3, p. 545-554, https://doi.org/10.1111/j.2041-210X.2011.00182.x.","productDescription":"10 p.","startPage":"545","endPage":"554","numberOfPages":"10","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474417,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.2041-210x.2011.00182.x","text":"Publisher Index Page"},{"id":258435,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258431,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.2041-210X.2011.00182.x","linkFileType":{"id":5,"text":"html"}}],"volume":"3","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-01-31","publicationStatus":"PW","scienceBaseUri":"505a477fe4b0c8380cd67895","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":465405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, Richard B. rchandler@usgs.gov","contributorId":63524,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":465404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles","contributorId":21831,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","affiliations":[],"preferred":false,"id":465403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":465402,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70039009,"text":"70039009 - 2012 - An assessment of the carbon balance of arctic tundra: comparisons among observations, process models, and atmospheric inversions","interactions":[],"lastModifiedDate":"2012-07-13T01:01:54","indexId":"70039009","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of the carbon balance of arctic tundra: comparisons among observations, process models, and atmospheric inversions","docAbstract":"Although arctic tundra has been estimated to cover only 8% of the global land surface, the large and potentially labile carbon pools currently stored in tundra soils have the potential for large emissions of carbon (C) under a warming climate. These emissions as radiatively active greenhouse gases in the form of both CO<sub>2</sub> and CH<sub>4</sub> could amplify global warming. Given the potential sensitivity of these ecosystems to climate change and the expectation that the Arctic will experience appreciable warming over the next century, it is important to assess whether responses of C exchange in tundra regions are likely to enhance or mitigate warming. In this study we compared analyses of C exchange of Arctic tundra between 1990&ndash;1999 and 2000&ndash;2006 among observations, regional and global applications of process-based terrestrial biosphere models, and atmospheric inversion models. Syntheses of the compilation of flux observations and of inversion model results indicate that the annual exchange of CO<sub>2</sub> between arctic tundra and the atmosphere has large uncertainties that cannot be distinguished from neutral balance. The mean estimate from an ensemble of process-based model simulations suggests that arctic tundra acted as a sink for atmospheric CO<sub>2</sub> in recent decades, but based on the uncertainty estimates it cannot be determined with confidence whether these ecosystems represent a weak or a strong sink. Tundra was 0.6 &deg;C warmer in the 2000s compared to the 1990s. The central estimates of the observations, process-based models, and inversion models each identify stronger sinks in the 2000s compared with the 1990s. Similarly, the observations and the applications of regional process-based models suggest that CH<sub>4</sub> emissions from arctic tundra have increased from the 1990s to 2000s. Based on our analyses of the estimates from observations, process-based models, and inversion models, we estimate that arctic tundra was a sink for atmospheric CO<sub>2</sub> of 110 Tg C yr<sup>-1</sup> (uncertainty between a sink of 291 Tg C yr<sup>-1</sup> and a source of 80 Tg C yr<sup>-1</sup>) and a source of CH<sub>4</sub> to the atmosphere of 19 Tg C yr<sup>-1</sup> (uncertainty between sources of 8 and 29 Tg C yr<sup>-1</sup>). The suite of analyses conducted in this study indicate that it is clearly important to reduce uncertainties in the observations, process-based models, and inversions in order to better understand the degree to which Arctic tundra is influencing atmospheric CO<sub>2</sub> and CH<sub>4</sub> concentrations. The reduction of uncertainties can be accomplished through (1) the strategic placement of more CO<sub>2</sub> and CH<sub>4</sub> monitoring stations to reduce uncertainties in inversions, (2) improved observation networks of ground-based measurements of CO<sub>2</sub> and CH<sub>4</sub> exchange to understand exchange in response to disturbance and across gradients of hydrological variability, and (3) the effective transfer of information from enhanced observation networks into process-based models to improve the simulation of CO<sub>2</sub> and CH<sub>4</sub> exchange from arctic tundra to the atmosphere.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"European Geosciences Union","publisherLocation":"Munich, Germany","doi":"10.5194/bgd-9-4543-2012","usgsCitation":"McGuire, A., Christensen, T., Hayes, D., Heroult, A., Euskirchen, E., Yi, Y., Kimball, J., Koven, C., Lafleur, P., Miller, P., Oechel, W., Peylin, P., and Williams, M., 2012, An assessment of the carbon balance of arctic tundra: comparisons among observations, process models, and atmospheric inversions: Biogeosciences, v. 9, no. 4, p. 4543-4594, https://doi.org/10.5194/bgd-9-4543-2012.","productDescription":"52 p.","startPage":"4543","endPage":"4594","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":474415,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bgd-9-4543-2012","text":"Publisher Index Page"},{"id":258449,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258437,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/bgd-9-4543-2012","linkFileType":{"id":5,"text":"html"}}],"volume":"9","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ea17e4b0c8380cd4861a","contributors":{"authors":[{"text":"McGuire, A. D.","contributorId":16552,"corporation":false,"usgs":true,"family":"McGuire","given":"A. D.","affiliations":[],"preferred":false,"id":465408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, T.R.","contributorId":81440,"corporation":false,"usgs":true,"family":"Christensen","given":"T.R.","email":"","affiliations":[],"preferred":false,"id":465416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, D.","contributorId":15275,"corporation":false,"usgs":true,"family":"Hayes","given":"D.","email":"","affiliations":[],"preferred":false,"id":465407,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heroult, A.","contributorId":65732,"corporation":false,"usgs":true,"family":"Heroult","given":"A.","email":"","affiliations":[],"preferred":false,"id":465412,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Euskirchen, E.","contributorId":62473,"corporation":false,"usgs":true,"family":"Euskirchen","given":"E.","email":"","affiliations":[],"preferred":false,"id":465411,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yi, Y.","contributorId":79274,"corporation":false,"usgs":true,"family":"Yi","given":"Y.","email":"","affiliations":[],"preferred":false,"id":465415,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kimball, J.S.","contributorId":79141,"corporation":false,"usgs":true,"family":"Kimball","given":"J.S.","email":"","affiliations":[],"preferred":false,"id":465414,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koven, C.","contributorId":39655,"corporation":false,"usgs":true,"family":"Koven","given":"C.","email":"","affiliations":[],"preferred":false,"id":465410,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lafleur, P.","contributorId":23026,"corporation":false,"usgs":true,"family":"Lafleur","given":"P.","email":"","affiliations":[],"preferred":false,"id":465409,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Miller, P.A.","contributorId":89414,"corporation":false,"usgs":true,"family":"Miller","given":"P.A.","email":"","affiliations":[],"preferred":false,"id":465417,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Oechel, W.","contributorId":76104,"corporation":false,"usgs":true,"family":"Oechel","given":"W.","email":"","affiliations":[],"preferred":false,"id":465413,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Peylin, P.","contributorId":14265,"corporation":false,"usgs":true,"family":"Peylin","given":"P.","email":"","affiliations":[],"preferred":false,"id":465406,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Williams, Murray","contributorId":100499,"corporation":false,"usgs":true,"family":"Williams","given":"Murray","email":"","affiliations":[],"preferred":false,"id":465418,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70039007,"text":"70039007 - 2012 - General methods for sensitivity analysis of equilibrium dynamics in patch occupancy models","interactions":[],"lastModifiedDate":"2012-07-13T01:01:54","indexId":"70039007","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"General methods for sensitivity analysis of equilibrium dynamics in patch occupancy models","docAbstract":"Sensitivity analysis is a useful tool for the study of ecological models that has many potential applications for patch occupancy modeling. Drawing from the rich foundation of existing methods for Markov chain models, I demonstrate new methods for sensitivity analysis of the equilibrium state dynamics of occupancy models. Estimates from three previous studies are used to illustrate the utility of the sensitivity calculations: a joint occupancy model for a prey species, its predators, and habitat used by both; occurrence dynamics from a well-known metapopulation study of three butterfly species; and Golden Eagle occupancy and reproductive dynamics. I show how to deal efficiently with multistate models and how to calculate sensitivities involving derived state variables and lower-level parameters. In addition, I extend methods to incorporate environmental variation by allowing for spatial and temporal variability in transition probabilities. The approach used here is concise and general and can fully account for environmental variability in transition parameters. The methods can be used to improve inferences in occupancy studies by quantifying the effects of underlying parameters, aiding prediction of future system states, and identifying priorities for sampling effort.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ESA","publisherLocation":"Ithaca, NY","doi":"10.1890/11-1495.1","usgsCitation":"Miller, D.A., 2012, General methods for sensitivity analysis of equilibrium dynamics in patch occupancy models: Ecology, v. 93, no. 5, p. 1204-1213, https://doi.org/10.1890/11-1495.1.","productDescription":"10 p.","startPage":"1204","endPage":"1213","numberOfPages":"10","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":258434,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258430,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/11-1495.1","linkFileType":{"id":5,"text":"html"}}],"volume":"93","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1511e4b0c8380cd54c9c","contributors":{"authors":[{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":465401,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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