Westslope Cutthroat Trout Oncorhynchus clarkii lewisi in Coeur d’Alene Lake, Idaho, have declined in recent years; predation by Northern Pike Esox lucius, a nonnative sport fish, is thought to be a causative mechanism. The goal of this study was to describe the seasonal food habits of Northern Pike and determine their influence on Westslope Cutthroat Trout in Coeur d’Alene Lake by using a bioenergetics modeling approach. Fish were sampled monthly from March 2012 to May 2013 using pulsed-DC electrofishing and experimental gillnetting in four bays. Northern Pike catch rates from electrofishing were generally low but increased slightly each season and were highest in the southern portion of the lake; catch rates from gillnetting were approximately 50% higher during the two spring sampling periods compared with the summer and fall. Seasonal growth and food habits of 695 Northern Pike (TL = 16.2–108.0 cm; weight = 24–9,628 g) were analyzed. Diets primarily consisted of kokanee O. nerka, Westslope Cutthroat Trout, and Yellow PerchPerca flavescens. Results of a bioenergetics model estimated that Westslope Cutthroat Trout represented approximately 2–30% of the biomass consumed by age-1–4 Northern Pike. Total Westslope Cutthroat Trout biomass consumed by Northern Pike (2008–2011 year-classes) across all seasons sampled was estimated to be 1,231 kg (95% CI = 723–2,396 kg), and the total number consumed was 5,641 (95% CI = 3,311–10,979). The highest occurrence of Westslope Cutthroat Trout in Northern Pike diets was observed during spring. Thus, reducing Northern Pike predation on Westslope Cutthroat Trout would be one tool worth considering for conserving Westslope Cutthroat Trout populations in Coeur d’Alene Lake.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2014.970678","usgsCitation":"Walrath, J., Quist, M.C., and Firehammer, J.A., 2015, Trophic ecology of northern pike and their effect on conservation of westslope cutthroat trout.: North American Journal of Fisheries Management, v. 35, no. 1, p. 158-177, https://doi.org/10.1080/02755947.2014.970678.","productDescription":"20 p.","startPage":"158","endPage":"177","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054888","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Coeur d’Alene Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.80801391601561,\n 47.68388118858139\n ],\n [\n -116.6473388671875,\n 47.64226084847303\n ],\n [\n -116.65008544921875,\n 47.60523713135211\n ],\n [\n -116.7572021484375,\n 47.62097541515849\n ],\n [\n -116.76406860351561,\n 47.57652571374621\n ],\n [\n -116.75170898437501,\n 47.53018378265907\n ],\n [\n -116.82449340820311,\n 47.49586436835717\n ],\n [\n -116.8341064453125,\n 47.47637579720936\n ],\n [\n -116.74758911132811,\n 47.48565697095909\n ],\n [\n -116.77093505859375,\n 47.44945112101852\n ],\n [\n -116.72973632812499,\n 47.41322033016902\n ],\n [\n -116.69540405273438,\n 47.37417465983494\n ],\n [\n -116.68304443359374,\n 47.37138457633081\n ],\n [\n -116.68579101562499,\n 47.33975331313596\n ],\n [\n -116.78878784179688,\n 47.344406158662096\n ],\n [\n -116.78192138671876,\n 47.41136166853917\n ],\n [\n -116.84509277343751,\n 47.441092383072515\n ],\n [\n -116.90277099609374,\n 47.46709298382172\n ],\n [\n -116.94671630859375,\n 47.45687999525879\n ],\n [\n -116.94534301757812,\n 47.48194469821279\n ],\n [\n -116.90414428710936,\n 47.52183788271235\n ],\n [\n -116.87393188476561,\n 47.518128167602484\n ],\n [\n -116.83959960937499,\n 47.55984733956309\n ],\n [\n -116.84371948242186,\n 47.581157652951454\n ],\n [\n -116.88629150390624,\n 47.597829241181465\n ],\n [\n -116.84646606445312,\n 47.623752267682875\n ],\n [\n -116.81213378906249,\n 47.619124098197325\n ],\n [\n -116.82449340820311,\n 47.65428791076272\n ],\n [\n -116.83959960937499,\n 47.674635091761616\n ],\n [\n -116.82037353515625,\n 47.68203210030427\n ],\n [\n -116.80801391601561,\n 47.68388118858139\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-06","publicationStatus":"PW","scienceBaseUri":"5757f065e4b04f417c24dd39","contributors":{"authors":[{"text":"Walrath, John D.","contributorId":171507,"corporation":false,"usgs":false,"family":"Walrath","given":"John D.","affiliations":[],"preferred":false,"id":637775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839 mquist@usgs.gov","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":171392,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":637291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Firehammer, Jon A.","contributorId":171508,"corporation":false,"usgs":false,"family":"Firehammer","given":"Jon","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":637776,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70138587,"text":"ofr20151009 - 2015 - Update of the Graizer-Kalkan ground-motion prediction equations for shallow crustal continental earthquakes","interactions":[],"lastModifiedDate":"2015-02-11T09:05:10","indexId":"ofr20151009","displayToPublicDate":"2015-02-05T14:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1009","title":"Update of the Graizer-Kalkan ground-motion prediction equations for shallow crustal continental earthquakes","docAbstract":"A ground-motion prediction equation (GMPE) for computing medians and standard deviations of peak ground acceleration and 5-percent damped pseudo spectral acceleration response ordinates of maximum horizontal component of randomly oriented ground motions was developed by Graizer and Kalkan (2007, 2009) to be used for seismic hazard analyses and engineering applications. This GMPE was derived from the greatly expanded Next Generation of Attenuation (NGA)-West1 database. In this study, Graizer and Kalkan’s GMPE is revised to include (1) an anelastic attenuation term as a function of quality factor (Q0) in order to capture regional differences in large-distance attenuation and (2) a new frequency-dependent sedimentary-basin scaling term as a function of depth to the 1.5-km/s shear-wave velocity isosurface to improve ground-motion predictions for sites on deep sedimentary basins. The new model (GK15), developed to be simple, is applicable to the western United States and other regions with shallow continental crust in active tectonic environments and may be used for earthquakes with moment magnitudes 5.0–8.0, distances 0–250 km, average shear-wave velocities 200–1,300 m/s, and spectral periods 0.01–5 s. Directivity effects are not explicitly modeled but are included through the variability of the data. Our aleatory variability model captures inter-event variability, which decreases with magnitude and increases with distance. The mixed-effects residuals analysis shows that the GK15 reveals no trend with respect to the independent parameters. The GK15 is a significant improvement over Graizer and Kalkan (2007, 2009), and provides a demonstrable, reliable description of ground-motion amplitudes recorded from shallow crustal earthquakes in active tectonic regions over a wide range of magnitudes, distances, and site conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151009","collaboration":"Prepared in cooperation with the U.S. Nuclear Regulatory Commission","usgsCitation":"Graizer, V., and Kalkan, E., 2015, Update of the Graizer-Kalkan ground-motion prediction equations for shallow crustal continental earthquakes: U.S. Geological Survey Open-File Report 2015-1009, vii, 79 p., https://doi.org/10.3133/ofr20151009.","productDescription":"vii, 79 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049464","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":297762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151009.gif"},{"id":297761,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1009/downloads/ofr2015-1009.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297760,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1009/"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ac7e4b08de9379b31ff","contributors":{"authors":[{"text":"Graizer, Vladimir","contributorId":138813,"corporation":false,"usgs":false,"family":"Graizer","given":"Vladimir","affiliations":[{"id":12536,"text":"U.S. Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":539921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":539922,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157345,"text":"70157345 - 2015 - Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape","interactions":[],"lastModifiedDate":"2017-11-20T15:40:32","indexId":"70157345","displayToPublicDate":"2015-02-05T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape","docAbstract":"Content Changing aspen distribution in response to climate change and fire is a major focus of biodiversity conservation, yet little is known about the potential response of aspen to these two driving forces along topoclimatic gradients. Objective This study is set to evaluate how aspen distribution might shift in response to different climate-fire scenarios in a semi-arid montane landscape, and quantify the influence of fire regime along topoclimatic gradients. Methods We used a novel integration of a forest landscape succession and disturbance model (LANDIS-II) with a fine-scale climatic water deficit approach to simulate dynamics of aspen and associated conifer and shrub species over the next 150 years under various climate-fire scenarios. Results Simulations suggest that many aspen stands could persist without fire for centuries under current climate conditions. However, a simulated 2–5 °C increase in temperature caused a substantial reduction of aspen coverage at lower elevations and a modest increase at upper elevations, leading to an overall reduction of aspen range at the landscape level. Increasing fire activity may favor aspen increase at its upper elevation limits adjacent to coniferous forest, but may also favor reduction of aspen at lower elevation limits adjacent to xeric shrubland. Conclusions Our study highlights the importance of incorporating fine-scale terrain effects on climatic water deficit and ecohydrology when modeling species distribution response to climate change. This modeling study suggests that climate mitigation and adaptation strategies that use fire would benefit from consideration of spatial context at landscape scales.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-015-0160-1","usgsCitation":"Yang, J., Weisberg, P.J., Shinneman, D.J., Dilts, T.E., Earnst, S.L., and Scheller, R., 2015, Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape: Landscape Ecology, v. 30, no. 6, p. 1055-1073, https://doi.org/10.1007/s10980-015-0160-1.","productDescription":"24 p.","startPage":"1055","endPage":"1073","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054573","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":308332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":308306,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007/s10980-015-0160-1"}],"volume":"30","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-05","publicationStatus":"PW","scienceBaseUri":"56012a4ce4b03bc34f5443ff","contributors":{"authors":[{"text":"Yang, Jian","contributorId":147806,"corporation":false,"usgs":false,"family":"Yang","given":"Jian","email":"","affiliations":[{"id":16940,"text":"Institute of Applied Ecology, Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":572764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weisberg, Peter J.","contributorId":33631,"corporation":false,"usgs":true,"family":"Weisberg","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":572765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":572763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dilts, Thomas E.","contributorId":36833,"corporation":false,"usgs":true,"family":"Dilts","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":572766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Earnst, Susan L. susan_earnst@usgs.gov","contributorId":4446,"corporation":false,"usgs":true,"family":"Earnst","given":"Susan","email":"susan_earnst@usgs.gov","middleInitial":"L.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":572767,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scheller, Robert M","contributorId":147807,"corporation":false,"usgs":false,"family":"Scheller","given":"Robert M","affiliations":[{"id":16941,"text":"Environmental Science and Management Department, Portland State University","active":true,"usgs":false}],"preferred":false,"id":572768,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70140162,"text":"70140162 - 2015 - Understanding uncertainty in temperature effects on vector-borne disease: a Bayesian approach","interactions":[],"lastModifiedDate":"2015-02-04T14:58:08","indexId":"70140162","displayToPublicDate":"2015-02-04T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Understanding uncertainty in temperature effects on vector-borne disease: a Bayesian approach","docAbstract":"Extrinsic environmental factors influence the distribution and population dynamics of many organisms, including insects that are of concern for human health and agriculture. This is particularly true for vector-borne infectious diseases like malaria, which is a major source of morbidity and mortality in humans. Understanding the mechanistic links between environment and population processes for these diseases is key to predicting the consequences of climate change on transmission and for developing effective interventions. An important measure of the intensity of disease transmission is the reproductive number R0. However, understanding the mechanisms linking R0 and temperature, an environmental factor driving disease risk, can be challenging because the data available for parameterization are often poor. To address this, we show how a Bayesian approach can help identify critical uncertainties in components of R0 and how this uncertainty is propagated into the estimate of R0. Most notably, we find that different parameters dominate the uncertainty at different temperature regimes: bite rate from 15°C to 25°C; fecundity across all temperatures, but especially ~25–32°C; mortality from 20°C to 30°C; parasite development rate at ~15–16°C and again at ~33–35°C. Focusing empirical studies on these parameters and corresponding temperature ranges would be the most efficient way to improve estimates of R0. While we focus on malaria, our methods apply to improving process-based models more generally, including epidemiological, physiological niche, and species distribution models.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/13-1964.1","usgsCitation":"Johnson, L.R., Ben-Horin, T., Lafferty, K.D., McNally, A., Mordecai, E., Paaijmans, K., Pawar, S., and Ryan, S.J., 2015, Understanding uncertainty in temperature effects on vector-borne disease: a Bayesian approach: Ecology, v. 96, no. 1, p. 203-213, https://doi.org/10.1890/13-1964.1.","productDescription":"11 p.","startPage":"203","endPage":"213","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055638","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472289,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1310.5110","text":"External Repository"},{"id":297742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ac7e4b08de9379b31fd","contributors":{"authors":[{"text":"Johnson, Leah R.","contributorId":139035,"corporation":false,"usgs":false,"family":"Johnson","given":"Leah","email":"","middleInitial":"R.","affiliations":[{"id":12621,"text":"University of Chicago and University of South Florida","active":true,"usgs":false}],"preferred":false,"id":539845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ben-Horin, Tal","contributorId":58137,"corporation":false,"usgs":false,"family":"Ben-Horin","given":"Tal","email":"","affiliations":[],"preferred":false,"id":539846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":539844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNally, Amy","contributorId":53225,"corporation":false,"usgs":true,"family":"McNally","given":"Amy","affiliations":[],"preferred":false,"id":539847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mordecai, Erin A.","contributorId":9113,"corporation":false,"usgs":true,"family":"Mordecai","given":"Erin A.","affiliations":[],"preferred":false,"id":539848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paaijmans, Krijn P.","contributorId":139036,"corporation":false,"usgs":false,"family":"Paaijmans","given":"Krijn P.","affiliations":[{"id":12622,"text":"University of Barcelona","active":true,"usgs":false}],"preferred":false,"id":539849,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pawar, Samraat","contributorId":22622,"corporation":false,"usgs":true,"family":"Pawar","given":"Samraat","email":"","affiliations":[],"preferred":false,"id":539850,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ryan, Sadie J.","contributorId":139037,"corporation":false,"usgs":false,"family":"Ryan","given":"Sadie","email":"","middleInitial":"J.","affiliations":[{"id":12623,"text":"State University of New York College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":539851,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70138588,"text":"ofr20151008 - 2015 - Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual","interactions":[],"lastModifiedDate":"2015-02-04T14:31:17","indexId":"ofr20151008","displayToPublicDate":"2015-02-04T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1008","title":"Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual","docAbstract":"The geographic information system (GIS) tool, Social Values for Ecosystem Services (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 3.0 continues to extend the functionality of SolVES, which was designed to assess, map, and quantify the social values of ecosystem services. Social values—the perceived, nonmarket values the public ascribes to ecosystem services, particularly cultural services, such as aesthetics and recreation—can be evaluated for various stakeholder groups. These groups are distinguishable by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with previous versions, SolVES 3.0 derives a quantitative 10-point, social-values metric—the value index—from a combination of spatial and nonspatial responses to public value and preference surveys. The tool also calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. SolVES 3.0 is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relationship between the value index and explanatory environmental variables. A model’s goodness of fit to a primary study area and its potential performance in transferring social values to similar areas using value-transfer methodology can be evaluated. SolVES 3.0 provides an improved public-domain tool for decision makers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151008","usgsCitation":"Sherrouse, B.C., and Semmens, D.J., 2015, Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual: U.S. Geological Survey Open-File Report 2015-1008, Report: vi, 65 p.; SolVES 3.0, https://doi.org/10.3133/ofr20151008.","productDescription":"Report: vi, 65 p.; SolVES 3.0","startPage":"65","numberOfPages":"71","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059598","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":297741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151008.jpg"},{"id":297738,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1008/"},{"id":297739,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1008/pdf/ofr2015-1008.pdf","text":"Report","size":"5.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297740,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1008/downloads/SolVES_V3.zip","text":"SolVES 3.0","size":"54.2 MB","description":"SolVES 3.0"}],"publicComments":"Land Change Science Program","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab4e4b08de9379b3198","contributors":{"authors":[{"text":"Sherrouse, Benson C. 0000-0002-5102-5895 bcsherrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-5102-5895","contributorId":2445,"corporation":false,"usgs":true,"family":"Sherrouse","given":"Benson","email":"bcsherrouse@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":539842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":539843,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70140152,"text":"ofr20141258 - 2015 - Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis","interactions":[],"lastModifiedDate":"2015-02-04T10:58:40","indexId":"ofr20141258","displayToPublicDate":"2015-02-04T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1258","title":"Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis","docAbstract":"The U.S. Army Corps of Engineers (USACE), Chicago District, is responsible for monitoring and computation of the quantity of Lake Michigan water diverted by the State of Illinois. As part of this effort, the USACE uses the Hydrological Simulation Program–FORTRAN (HSPF) with measured meteorological data inputs to estimate runoff from the Lake Michigan diversion special contributing areas (SCAs), the North Branch Chicago River above Niles and the Little Calumet River above South Holland gaged basins, and the Lower Des Plaines and the Calumet ungaged that historically drained to Lake Michigan. These simulated runoffs are used for estimating the total runoff component from the diverted Lake Michigan watershed, which is accountable to the total diversion by the State of Illinois. The runoff is simulated from three interpreted land cover types in the HSPF models: impervious, grass, and forest. The three land cover data types currently in use were derived from aerial photographs acquired in the early 1990s.
\nThis study used the National Land Cover Dataset (NLCD) and developed an automated process for determining the area of the three land cover types, thereby allowing faster updating of future models, and for evaluating land cover changes by use of historical NLCD datasets. The study also carried out a raingage partitioning analysis so that the segmentation of land cover and rainfall in each modeled unit is directly applicable to the HSPF modeling. Historical and existing impervious, grass, and forest land acreages partitioned by percentages covered by two sets of raingages for the Lake Michigan diversion SCAs, gaged basins, and ungaged basins are presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141258","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Sharpe, J.B., and Soong, D.T., 2015, Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis: U.S. Geological Survey Open-File Report 2014-1258, Report: iv, 12 p.; Downloads Directory, https://doi.org/10.3133/ofr20141258.","productDescription":"Report: iv, 12 p.; Downloads Directory","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060110","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":297727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141258.jpg"},{"id":297724,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1258/"},{"id":297725,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1258/pdf/ofr2014-1258.pdf","text":"Report","size":"2.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297726,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1258/downloads/ofr2014-1258_tables5-20.xlsx","text":"Downloads Directory","description":"Downloads Directory","linkHelpText":"Contains: Excel spreadsheets of tables 5 through 20."}],"projection":"Albers Equal-Area Conic Projection","country":"United States","state":"Illinois","otherGeospatial":"Calumet River, Lake Michigan, Little Calumet River, Lower Des Plaines River, North Branch Chicago River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.989501953125,\n 41.3500103516271\n ],\n [\n -87.989501953125,\n 42.370720143531955\n ],\n [\n -87.286376953125,\n 42.370720143531955\n ],\n [\n -87.286376953125,\n 41.3500103516271\n ],\n [\n -87.989501953125,\n 41.3500103516271\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a8de4b08de9379b30ee","contributors":{"authors":[{"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":539829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soong, David T. dsoong@usgs.gov","contributorId":2230,"corporation":false,"usgs":true,"family":"Soong","given":"David","email":"dsoong@usgs.gov","middleInitial":"T.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539830,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70139655,"text":"ofr20141238 - 2015 - Maps showing the change in modern sediment thickness on the Inner Continental Shelf offshore of Fire Island, New York, between 1996-97 and 2011","interactions":[],"lastModifiedDate":"2015-02-03T11:45:19","indexId":"ofr20141238","displayToPublicDate":"2015-02-03T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1238","title":"Maps showing the change in modern sediment thickness on the Inner Continental Shelf offshore of Fire Island, New York, between 1996-97 and 2011","docAbstract":"The U.S. Geological Survey mapped approximately 336 square kilometers of the lower shoreface and inner continental shelf offshore of Fire Island, New York, in 1996 and 1997, using high-resolution sidescan-sonar and seismic-reflection systems, and again in 2011, using interferometric sonar and high-resolution chirp seismic-reflection systems. This report presents a comparison of sediment thickness and distribution as mapped during these two investigations. These spatial data support research on the Quaternary evolution of the Fire Island coastal system and provide baseline information for research on coastal processes along southern Long Island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141238","usgsCitation":"Schwab, W.C., Baldwin, W.E., and Denny, J.F., 2015, Maps showing the change in modern sediment thickness on the Inner Continental Shelf offshore of Fire Island, New York, between 1996-97 and 2011: U.S. Geological Survey Open-File Report 2014-1238, Report: HTML Document; Report: v, 8 p., https://doi.org/10.3133/ofr20141238.","productDescription":"Report: HTML Document; Report: v, 8 p.","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1996-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-058163","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141238.JPG"},{"id":297709,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1238/pdf/ofr2014-1238.pdf","text":"Report (PDF format)","size":"2.42 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297707,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1238/"},{"id":297708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1238/ofr2014-1238-title_page.html","text":"Report (HTML format)","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator projection","datum":"World Geodetic System 1984","country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.3392333984375,\n 40.64521960545374\n ],\n [\n -72.43560791015625,\n 40.887562618139405\n ],\n [\n -72.41912841796875,\n 40.63375667842965\n ],\n [\n -73.32412719726562,\n 40.42395127765169\n ],\n [\n -73.3392333984375,\n 40.64521960545374\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a95e4b08de9379b3115","contributors":{"authors":[{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, Wayne E. 0000-0001-5886-0917 wbaldwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5886-0917","contributorId":1321,"corporation":false,"usgs":true,"family":"Baldwin","given":"Wayne","email":"wbaldwin@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denny, Jane F. 0000-0002-3472-618X jdenny@usgs.gov","orcid":"https://orcid.org/0000-0002-3472-618X","contributorId":418,"corporation":false,"usgs":true,"family":"Denny","given":"Jane","email":"jdenny@usgs.gov","middleInitial":"F.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539500,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175239,"text":"70175239 - 2015 - Glacier-derived August runoff in northwest Montana","interactions":[],"lastModifiedDate":"2016-08-03T09:30:10","indexId":"70175239","displayToPublicDate":"2015-02-03T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":899,"text":"Arctic, Antarctic, and Alpine Research","active":true,"publicationSubtype":{"id":10}},"title":"Glacier-derived August runoff in northwest Montana","docAbstract":"The second largest concentration of glaciers in the U.S. Rocky Mountains is located in Glacier National Park (GNP), Montana. The total glacier-covered area in this region decreased by ∼35% over the past 50 years, which has raised substantial concern about the loss of the water derived from glaciers during the summer. We used an innovative weather station design to collect in situ measurements on five remote glaciers, which are used to parameterize a regional glacier melt model. This model offered a first-order estimate of the summer meltwater production by glaciers. We find, during the normally dry month of August, glaciers in the region produce approximately 25 × 106 m3 of potential runoff. We then estimated the glacier runoff component in five gaged streams sourced from GNP basins containing glaciers. Glacier-melt contributions range from 5% in a basin only 0.12% glacierized to >90% in a basin 28.5% glacierized. Glacier loss would likely lead to lower discharges and warmer temperatures in streams draining basins >20% glacier-covered. Lower flows could even be expected in streams draining basins as little as 1.4% glacierized if glaciers were to disappear.
","language":"English","publisher":"Institute of Arctic and Alpine Research","publisherLocation":"Boulder, CO","doi":"10.1657/AAAR0014-033","usgsCitation":"Clark, A., Harper, J.T., and Fagre, D.B., 2015, Glacier-derived August runoff in northwest Montana: Arctic, Antarctic, and Alpine Research, v. 47, no. 1, p. 1-16, https://doi.org/10.1657/AAAR0014-033.","startPage":"1","endPage":"16","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059157","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472292,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1657/AAAR0014-033","text":"External Repository"},{"id":326012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","volume":"47","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-05","publicationStatus":"PW","scienceBaseUri":"57a315c3e4b006cb45558ad3","contributors":{"authors":[{"text":"Clark, Adam","contributorId":173391,"corporation":false,"usgs":false,"family":"Clark","given":"Adam","affiliations":[{"id":16951,"text":"Department of Geosciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":644491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harper, Joel T.","contributorId":173392,"corporation":false,"usgs":false,"family":"Harper","given":"Joel","email":"","middleInitial":"T.","affiliations":[{"id":16951,"text":"Department of Geosciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":644492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644490,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70139777,"text":"ofr20151017 - 2015 - A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning","interactions":[],"lastModifiedDate":"2017-02-08T13:32:17","indexId":"ofr20151017","displayToPublicDate":"2015-02-02T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1017","title":"A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning","docAbstract":"The amount and quality of natural resources available for terrestrial and aquatic wildlife habitats are expected to decrease throughout the world in areas that are intensively managed for urban and agricultural uses. Changes in climate and management of increasingly limited water supplies may further impact water resources essential for sustaining habitats. In this report, we document adapting a Water Evaluation and Planning (WEAP) system model for the Central Valley of California. We demonstrate using this adapted model (WEAP-CVwh) to evaluate impacts produced from plausible future scenarios on agricultural and wetland habitats used by waterbirds and other wildlife. Processed output from WEAP-CVwh indicated varying levels of impact caused by projected climate, urbanization, and water supply management in scenarios used to exemplify this approach. Among scenarios, the NCAR-CCSM3 A2 climate projection had a greater impact than the CNRM-CM3 B1 climate projection, whereas expansive urbanization had a greater impact than strategic urbanization, on annual availability of waterbird habitat. Scenarios including extensive rice-idling or substantial instream flow requirements on important water supply sources produced large impacts on annual availability of waterbird habitat. In the year corresponding with the greatest habitat reduction for each scenario, the scenario including instream flow requirements resulted in the greatest decrease in habitats throughout all months of the wintering period relative to other scenarios. This approach provides a new and useful tool for habitat conservation planning in the Central Valley and a model to guide similar research investigations aiming to inform conservation, management, and restoration of important wildlife habitats.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151017","collaboration":"Prepared in cooperation with the California Landscape Conservation Cooperative, California Department of Fish and Wildlife, and U.S. Fish and Wildlife Service","usgsCitation":"Matchett, E., Fleskes, J.P., Young, C., and Purkey, D.R., 2015, A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning: U.S. Geological Survey Open-File Report 2015-1017, vi, 40 p., https://doi.org/10.3133/ofr20151017.","productDescription":"vi, 40 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053267","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":334995,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H13050","text":"Data for projected impacts of climate, urbanization, water management, and wetland restoration on waterbird habitat in California’s Central Valley"},{"id":297683,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1017/"},{"id":297684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151017.PNG"},{"id":297685,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1017/pdf/ofr2015-1017.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.16748046874999,\n 34.59704151614417\n ],\n [\n -124.16748046874999,\n 40.68063802521456\n ],\n [\n -119.68505859375,\n 40.68063802521456\n ],\n [\n -119.68505859375,\n 34.59704151614417\n ],\n [\n -124.16748046874999,\n 34.59704151614417\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a4ae4b08de9379b2fc4","contributors":{"authors":[{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":539694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":1889,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":539695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Charles A.","contributorId":139008,"corporation":false,"usgs":false,"family":"Young","given":"Charles A.","affiliations":[],"preferred":false,"id":539698,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Purkey, David R.","contributorId":139005,"corporation":false,"usgs":false,"family":"Purkey","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":539696,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133604,"text":"ds901 - 2015 - Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","interactions":[],"lastModifiedDate":"2016-02-08T14:09:10","indexId":"ds901","displayToPublicDate":"2015-02-02T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"901","title":"Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","docAbstract":"This report describes a series of geoelectrical soundings carried out on and near Mount St. Helens volcano, Washington, in 2010–2011. These soundings used a controlled-source audio-frequency magnetotelluric (CSAMT) approach (Zonge and Hughes, 1991; Simpson and Bahr, 2005). We chose CSAMT for logistical reasons: It can be deployed by helicopter, has an effective depth of penetration of as much as 1 kilometer, and requires less wire than a Schlumberger sounding.
\nThis Data Series provides the edited data for these CSAMT soundings as well as several different types of 1-D inversions (where the signal data are converted to conductivity-versus-depth models). In addition, we include a map showing station locations on and around the volcano and the Pumice Plain to the north.
\nThe apparent conductivity (or its inverse, apparent resistivity) measured by a geoelectrical system is caused by several factors. The most important of these are water-filled rock porosity and the presence of water-filled fractures; however, rock type and minerals (for instance, sulfides and clay content) also contribute to apparent conductivity. In situations with little recharge (for instance, in arid regions), variations in ionic content of water occupying pore space and fractures sampled by the measurement system must also be factored in (Wynn, 2006). Variations in ionic content may also be present in hydrothermal fluids surrounding volcanoes in wet regions. In unusual cases, temperature may also affect apparent conductivity (Keller, 1989; Palacky, 1989). There is relatively little hydrothermal alteration (and thus fewer clay minerals that might add to the apparent conductivity) in the eruptive products of Mount St. Helens (Reid and others, 2010), so conductors observed in the Fischer, Occam, and Marquardt inversion results later in this report are thus believed to map zones with significant water content. Geoelectrical surveys thus have the potential to reveal subsurface regions with significant groundwater content, including perched and regional aquifers. Reid and others (2001) and Reid (2004) have suggested that groundwater involvement may figure in both the scale and the character of some if not all volcanic edifice collapse events. Ongoing research by the U.S. Geological Survey (USGS) and others aims to better understand the contribution of groundwater to both edifice pore pressure and rock alteration as well as its direct influence on eruption processes by violent interaction with magma (Schmincke, 1998).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds901","usgsCitation":"Wynn, J., and Pierce, H., 2015, Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions: U.S. Geological Survey Data Series 901, HTML Document, https://doi.org/10.3133/ds901.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044700","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":297677,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds901.gif"},{"id":316600,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/ds901.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297676,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/cover.html","text":"Report","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator projection, Zone 10N","datum":"World Geodetic System 1984","country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.28675842285158,\n 46.150107913663334\n ],\n [\n -122.28675842285158,\n 46.27388525189855\n ],\n [\n -122.09415435791016,\n 46.27388525189855\n ],\n [\n -122.09415435791016,\n 46.150107913663334\n ],\n [\n -122.28675842285158,\n 46.150107913663334\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a9ce4b08de9379b3137","contributors":{"authors":[{"text":"Wynn, Jeff 0000-0002-8102-3882 jwynn@usgs.gov","orcid":"https://orcid.org/0000-0002-8102-3882","contributorId":2803,"corporation":false,"usgs":true,"family":"Wynn","given":"Jeff","email":"jwynn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierce, Herbert A.","contributorId":83093,"corporation":false,"usgs":true,"family":"Pierce","given":"Herbert A.","affiliations":[],"preferred":false,"id":539673,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148078,"text":"70148078 - 2015 - Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","interactions":[],"lastModifiedDate":"2017-07-26T17:13:27","indexId":"70148078","displayToPublicDate":"2015-02-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","docAbstract":"Background
\nIdentifying movement routes and stopover sites is necessary for developing effective management and conservation strategies for migratory animals. In the case of migratory birds, a collection of migration routes, known as a flyway, is often hundreds to thousands of kilometers long and can extend across political boundaries. Flyways encompass the entire geographic range between the breeding and non-breeding areas of a population, species, or a group of species, and they provide spatial frameworks for management and conservation across international borders. Existing flyway maps are largely qualitative accounts based on band returns and survey data rather than observed movement routes. In this study, we use satellite and GPS telemetry data and dynamic Brownian bridge movement models to build upon existing maps and describe waterfowl space use probabilistically in the Central Asian and East Asian-Australasian Flyways.
\nResults
\nOur approach provided new information on migratory routes that was not easily attainable with existing methods to describe flyways. Utilization distributions from dynamic Brownian bridge movement models identified key staging and stopover sites, migration corridors and general flyway outlines in the Central Asian and East Asian-Australasian Flyways. A map of space use from ruddy shelducks depicted two separate movement corridors within the Central Asian Flyway, likely representing two distinct populations that show relatively strong connectivity between breeding and wintering areas. Bar-headed geese marked at seven locations in the Central Asian Flyway showed heaviest use at several stopover sites in the same general region of high-elevation lakes along the eastern Qinghai-Tibetan Plateau. Our analysis of data from multiple Anatidae species marked at sites throughout Asia highlighted major movement corridors across species and confirmed that the Central Asian and East Asian-Australasian Flyways were spatially distinct.
\nConclusions
\nThe dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.
","language":"English","publisher":"Minerva Center for Movement Ecology","publisherLocation":"London","doi":"10.1186/s40462-015-0029-6","usgsCitation":"Palm, E., Newman, S.H., Prosser, D.J., Xiao, X., Luo, Z., Batbayar, N., Balachandran, S., and Takekawa, J.Y., 2015, Mapping migratory flyways in Asia using dynamic Brownian bridge movement models: Movement Ecology, v. 3, no. 1, p. 1-10, https://doi.org/10.1186/s40462-015-0029-6.","productDescription":"10 p.","startPage":"1","endPage":"10","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062254","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-015-0029-6","text":"Publisher Index Page"},{"id":300545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-02","publicationStatus":"PW","scienceBaseUri":"555c5eb6e4b0a92fa7eacc02","contributors":{"authors":[{"text":"Palm, E.C.","contributorId":40708,"corporation":false,"usgs":true,"family":"Palm","given":"E.C.","email":"","affiliations":[],"preferred":false,"id":547228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, S. H.","contributorId":21888,"corporation":false,"usgs":false,"family":"Newman","given":"S.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":547229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiao, Xiangming","contributorId":67212,"corporation":false,"usgs":true,"family":"Xiao","given":"Xiangming","affiliations":[],"preferred":false,"id":547231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luo, Ze","contributorId":41307,"corporation":false,"usgs":true,"family":"Luo","given":"Ze","affiliations":[],"preferred":false,"id":547232,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Batbayar, Nyambayar","contributorId":40338,"corporation":false,"usgs":true,"family":"Batbayar","given":"Nyambayar","affiliations":[],"preferred":false,"id":547233,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Balachandran, Sivananinthaperumal","contributorId":20593,"corporation":false,"usgs":true,"family":"Balachandran","given":"Sivananinthaperumal","affiliations":[],"preferred":false,"id":547234,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":547235,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70137956,"text":"ofr20151007 - 2015 - Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2016-04-12T17:29:26","indexId":"ofr20151007","displayToPublicDate":"2015-02-02T08:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1007","title":"Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin","docAbstract":"In 2009, the U.S. Geological Survey (USGS) developed a Spatially Referenced Regressions on Watershed Attributes (SPARROW) surface-water quality model for the Upper Colorado River Basin (UCRB) relating dissolved-solids sources and transport in the 1991 water year to upstream catchment characteristics. The SPARROW model focused on geologic and agricultural sources of dissolved solids in the UCRB and was calibrated using water-year 1991 dissolved-solids loads from 218 monitoring sites. A new UCRB SPARROW model is planned that will update the investigation of dissolved-solids sources and transport in the basin to circa 2010 conditions and will improve upon the 2009 model by incorporating more detailed information about agricultural-irrigation and rangeland-management practices, among other improvements. Geospatial datasets relating to circa 2010 rangeland conditions are required for the new UCRB SPARROW modeling effort. This study compiled geospatial datasets for the UCRB that relate to the biotic alterations and rangeland conditions of grazing, fire and other land disturbance, and vegetation type and cover. Datasets representing abiotic alterations of access control (off-highway vehicles) and sediment generation and transport in general, were also compiled. These geospatial datasets may be tested in the upcoming SPARROW model to better understand the potential contribution of rangelands to dissolved-solids loading in UCRB streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151007","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Tillman, F., Flynn, M., and Anning, D.W., 2015, Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin: U.S. Geological Survey Open-File Report 2015-1007, Report: v, 21 p.; 6 Geospatial Datasets, https://doi.org/10.3133/ofr20151007.","productDescription":"Report: v, 21 p.; 6 Geospatial Datasets","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060100","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":297671,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151007.gif"},{"id":297670,"rank":9,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/UCRB_R-factor.zip","text":"Rainfall-Runoff Erosivity","size":"962 kB","description":"Geospatial dataset","linkHelpText":"This tabular dataset presents the 1971–2000 average annual rainfall-runoff erosivity factor (R-factor) for the UCRB. The R-factor is a measure of the cumulative erosive force of individual precipitation events (Daly and Taylor, 2002). All other factors being constant, sediment generation from precipitation is directly proportional to the product of the total kinetic energy of a storm and the storm’s maximum 30-minute intensity. The mean annual R-factor is a sum of this product for all storms in a year, averaged over all years of record (Daly and Taylor, 2002)."},{"id":297663,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1007/"},{"id":297668,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_VegTypeCover.zip","text":"Existing Vegetation Type and Cover","size":"540 MB","description":"Geospatial dataset","linkHelpText":"These layers include information on the vegetation type and vegetation cover in 2010 in the UCRB. The 2010 existing vegetation cover (EVC) layer represents the vertically projected percent cover of the live canopy layer. The 2010 existing vegetation type (EVT) layer represents the species composition. Spatially, both grids cover the entire UCRB and have a 30-meter pixel resolution."},{"id":297664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/OFR2015-1007.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297666,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_USFS_Grazing_projected.zip","text":"U.S. Forest Service Grazing","size":"3.8 MB","description":"Geospatial dataset","linkHelpText":"The shapefile contains 444 polygons of USFS grazing allotments within or bordering the UCRB (fig. 4). Attributes for the allotment polygons include the allotment name (RMU_NAME) and number (RMU_CN), the authorized number of animal unit months for the allotment (AUTH_AUMS), and the area of the allotment in both acres (AREA_acres) and square kilometers (AREA_km2). USFS-billed grazing is referred to as the \"authorized\" amount and is equivalent to BLM’s \"billed\" grazing (U.S. Government Accountability Office, 2005)."},{"id":297669,"rank":8,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_Roads.zip","text":"2010 Roads","size":"172 MB","description":"Geospatial dataset","linkHelpText":"This layer contains information about the location and type of roads in the UCRB in 2010. One value in the MAF/TIGER Feature Class Code (MTFCC) attribute field in the roads layer is S1500, named \"Vehicular Trail (4WD)\", and is described as \"an unpaved dirt trail where a four-wheel drive vehicle is required\" (table 5). The Vehicular Trail (4WD) attribute presents potential UCRB locations of off-highway vehicle use—an activity directly related to the \"access controls\" abiotic alteration in Weltz and others (2014) (table 5; fig. 7). The 2010 roads layer covers the entire UCRB."},{"id":297665,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_BLM_Grazing_projected.zip","text":"Bureau of Land Management Grazing","size":"12.9 MB","description":"Geospatial dataset","linkHelpText":"The shapefile contains 2,367 polygons of BLM grazing allotments within or bordering the UCRB (fig. 4). Attributes for the allotment polygons include the allotment name (ALLOT_NAME) and number (ST_ALLOT), the authorized number of \"animal unit months\" for the allotment (AUTH_AUMS), and the area of the allotment in both acres (AREA_acres) and square kilometers (AREA_km2)."},{"id":297667,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/1999-2010_UCRB_LandDisturbance.zip","text":"Land Disturbance","size":"26 MB","description":"Geospatial dataset","linkHelpText":"These layers include temporal and spatial information on disturbances to the landscape as a result of management activities or natural events. Two types of grids are presented: yearly disturbance grids for 1999–2010 and a composite grid of the yearly disturbance grids that summarizes vegetation disturbance for 1999–2010. Spatially, all grids cover the entire UCRB and have a 30-meter pixel resolution."}],"datum":"North American Datum of 1983","country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.69937133789062,\n 36.730079507078415\n ],\n [\n -111.68083190917969,\n 36.730079507078415\n ],\n [\n -111.64581298828125,\n 36.72677751526221\n ],\n [\n -111.4068603515625,\n 36.67723060234619\n ],\n [\n -111.181640625,\n 36.54936246839778\n ],\n [\n -110.45654296875,\n 36.46105407505434\n ],\n [\n -109.8687744140625,\n 35.991340960635405\n ],\n [\n -109.5062255859375,\n 35.67068501330236\n ],\n [\n -109.21508789062499,\n 35.48751102385376\n ],\n [\n -108.907470703125,\n 35.34425514918409\n ],\n [\n -107.5286865234375,\n 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Center","active":true,"usgs":true}],"preferred":true,"id":539658,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155259,"text":"70155259 - 2015 - Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture","interactions":[],"lastModifiedDate":"2017-01-18T10:06:09","indexId":"70155259","displayToPublicDate":"2015-02-01T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture","docAbstract":"The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.
","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JHM-D-14-0049.1","collaboration":"Amy McNally; Gregory J. Husak; Molly Brown; Mark Carroll; Chris Funk; Joel Michaelsen; Soni Yatheendradas; Kristi Arsenault, Christa Peters-Lidard; James P. Verdin","usgsCitation":"McNally, A., Gregory J. Husak, Brown, M., Carroll, M.L., Funk, C.C., Soni Yatheendradas, Arsenault, K., Christa Peters-Lidard, and Verdin, J., 2015, Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture: Journal of Hydrometeorology, v. 16, no. 1, p. 295-305, https://doi.org/10.1175/JHM-D-14-0049.1.","productDescription":"11 p.","startPage":"295","endPage":"305","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055181","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-14-0049.1","text":"Publisher Index Page"},{"id":306506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-04","publicationStatus":"PW","scienceBaseUri":"57f7ef86e4b0bc0bec09f1a4","contributors":{"authors":[{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gregory J. 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Gauge observations, however, are often sparse in regions with complicated terrain, clustered in valleys, and of poor quality. Consequently, the spatial extent of wet events is poorly represented. Satellite-derived precipitation data are an attractive alternative, though they tend to underestimate the magnitude of wet events due to their dependency on retrieval algorithms and the indirect relationship between satellite infrared observations and precipitation intensities. Here we offer a Bayesian kriging approach for blending precipitation gauge data and the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates for Central America, Colombia, and Venezuela. First, the gauge observations are modeled as a linear function of satellite-derived estimates and any number of other variables—for this research we include elevation. Prior distributions are defined for all model parameters and the posterior distributions are obtained simultaneously via Markov chain Monte Carlo sampling. The posterior distributions of these parameters are required for spatial estimation, and thus are obtained prior to implementing the spatial kriging model. This functional framework is applied to model parameters obtained by sampling from the posterior distributions, and the residuals of the linear model are subject to a spatial kriging model. Consequently, the posterior distributions and uncertainties of the blended precipitation estimates are obtained. We demonstrate this method by applying it to pentadal and monthly total precipitation fields during 2009. The model's performance and its inherent ability to capture wet events are investigated. We show that this blending method significantly improves upon the satellite-derived estimates and is also competitive in its ability to represent wet events. This procedure also provides a means to estimate a full conditional distribution of the “true” observed precipitation value at each grid cell.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2014WR015963","usgsCitation":"Verdin, A.P., Rajagopalan, B., Kleiber, W., and Funk, C.C., 2015, A Bayesian kriging approach for blending satellite and ground precipitation observations: Water Resources Research, v. 51, no. 2, p. 908-921, https://doi.org/10.1002/2014WR015963.","productDescription":"14 p.","startPage":"908","endPage":"921","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059780","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr015963","text":"Publisher Index Page"},{"id":306505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -64.81632212611561,\n 10.015029125925736\n ],\n [\n -71.2808031725719,\n 12.09555191269581\n ],\n [\n -74.73402713091187,\n 10.852006430112795\n ],\n [\n -77.21850797862407,\n 8.713663685154202\n ],\n [\n -79.41987151315135,\n 9.786489276111354\n ],\n [\n -81.04404574688206,\n 8.743926005251254\n ],\n [\n -82.41623838685905,\n 9.473469414609596\n ],\n [\n -83.73635743659167,\n 11.525091246808799\n ],\n [\n -83.23445386370992,\n 14.652633865094415\n ],\n [\n -84.32577316042915,\n 15.88928095391691\n ],\n [\n -88.79734742847882,\n 16.004790444581047\n ],\n [\n -88.21513890838666,\n 18.344083184580015\n ],\n [\n -90.40042887702003,\n 17.759482734359935\n ],\n [\n -91.04910311365558,\n 17.14123874170798\n ],\n [\n -90.35911384507358,\n 16.391142531706166\n ],\n [\n -92.22557510093608,\n 14.38136938077568\n ],\n [\n -90.87228561271752,\n 13.623920899226192\n ],\n [\n -87.61119935386394,\n 13.26864716978318\n ],\n [\n -82.09248872782524,\n 7.933279880637983\n ],\n [\n -80.86633169250197,\n 7.172026204942057\n ],\n [\n -80.09014204558488,\n 7.47701439779469\n ],\n [\n -80.46443299353692,\n 8.17781343122843\n ],\n [\n -79.01162994394076,\n 8.782940526946703\n ],\n [\n -77.32715639625906,\n 6.170679076154258\n ],\n [\n -78.63977018899459,\n 1.7560879959772535\n ],\n [\n -76.29608093885051,\n 0.4803896875874756\n ],\n [\n -64.81632212611561,\n 10.015029125925736\n ],\n [\n -64.81632212611561,\n 10.015029125925736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"55c9cb2ee4b08400b1fdb6df","contributors":{"authors":[{"text":"Verdin, Andrew P.","contributorId":35235,"corporation":false,"usgs":true,"family":"Verdin","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":565397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rajagopalan, Balaji","contributorId":145813,"corporation":false,"usgs":false,"family":"Rajagopalan","given":"Balaji","email":"","affiliations":[{"id":16240,"text":"U of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":565398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleiber, William","contributorId":145814,"corporation":false,"usgs":false,"family":"Kleiber","given":"William","email":"","affiliations":[{"id":16240,"text":"U of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":565399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157523,"text":"70157523 - 2015 - An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems","interactions":[],"lastModifiedDate":"2017-07-21T14:50:38","indexId":"70157523","displayToPublicDate":"2015-02-01T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5004,"text":"Fundamental and Applied Limnology","active":true,"publicationSubtype":{"id":10}},"title":"An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems","docAbstract":"In regulated rivers, managers must evaluate competing flow release scenarios that attempt to balance both human and natural needs. Meeting these natural flow needs is complex due to the myriad of interacting physical and hydrological factors that affect ecosystems. Tools that synthesize the voluminous scientific data and models on these factors will facilitate management of these systems. Here, we present the Riverine Environmental Flow Decision Support System (REFDSS), a tool that enables evaluation of competing flow scenarios and other variables on instream habitat. We developed a REFDSS for the Upper Delaware River, USA, a system that is regulated by three headwater reservoirs. This version of the REFDSS has the ability to integrate any set of spatially explicit data and synthesizes modeled discharge for three competing management scenarios, flow-specific 2-D hydrodynamic modeled estimates of local hydrologic conditions (e.g., depth, velocity, shear stress, etc.) at a fine pixel-scale (1 m2), and habitat suitability criteria (HSC) for a variety of taxa. It contains all individual model outputs, computationally integrates these data, and outputs the amount of potentially available habitat for a suite of species of interest under each flow release scenario. Users have the flexibility to change the time period of interest and vary the HSC. The REFDSS was developed to enable side-by-side evaluation of different flow management scenarios and their effects on potential habitat availability, allowing managers to make informed decisions on the best flow scenarios. An exercise comparing two alternative flow scenarios to a baseline scenario for several key species is presented. The Upper Delaware REFDSS was robust to minor changes in HSC (± 10 %). The general REFDSS platform was developed as a user-friendly Windows desktop application that was designed to include other potential parameters of interest (e.g., temperature) and for transferability to other riverine systems.
","language":"English","publisher":"International Association of Theoretical and Applied Limnology","publisherLocation":"Stuttgart, Germany","doi":"10.1127/fal/2015/0611","usgsCitation":"Maloney, K.O., Talbert, C., Cole, J.C., Galbraith, H.S., Blakeslee, C.J., Hanson, L., and Holmquist-Johnson, C.L., 2015, An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems: Fundamental and Applied Limnology, v. 186, no. 1-2, p. 171-192, https://doi.org/10.1127/fal/2015/0611.","productDescription":"22 p.","startPage":"171","endPage":"192","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054083","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":309723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, 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h-johnsonc@usgs.gov","contributorId":922,"corporation":false,"usgs":true,"family":"Holmquist-Johnson","given":"Christopher","email":"h-johnsonc@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":573438,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70148103,"text":"70148103 - 2015 - An assessment of morphometric indices, blood chemistry variables and an energy meter as indicators of the whole body lipid content in Micropterus dolomieu, Sander vitreus and Ictalurus punctatus","interactions":[],"lastModifiedDate":"2015-05-21T11:01:58","indexId":"70148103","displayToPublicDate":"2015-02-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of morphometric indices, blood chemistry variables and an energy meter as indicators of the whole body lipid content in Micropterus dolomieu, Sander vitreus and Ictalurus punctatus","docAbstract":"The effectiveness of several non-lethal techniques as indicators of total lipid content in smallmouth bass Micropterus dolomieu, walleye Sander vitreus and channel catfish Ictalurus punctatus was investigated. The techniques included (1) the Fulton and relative condition factors, (2) relative mass, (3) plasma indicators of nutritional status (alkaline phosphatase, calcium, cholesterol, protein, triglycerides and glucose) and (4) readings from a hand-held, microwave energy meter. Although simple linear regression analysis showed that lipid content was significantly correlated with several predictor variables in each species, the r2 values for the relations ranged from 0·17 to 0·50 and no single approach was consistent for all species. Only one model, between energy-meter readings and lipid content in I. punctatus, had an r2 value (0·83) high enough to justify using it as a predictive tool. Results indicate that no single variable was an accurate and reliable indicator of whole body lipid content in these fishes, except the energy meter for I. punctatus.
","language":"English","publisher":"Fisheries Society of the British Isles","publisherLocation":"London","doi":"10.1111/jfb.12600","usgsCitation":"Mesa, M.G., and Rose, B.P., 2015, An assessment of morphometric indices, blood chemistry variables and an energy meter as indicators of the whole body lipid content in Micropterus dolomieu, Sander vitreus and Ictalurus punctatus: Journal of Fish Biology, v. 86, no. 2, p. 755-764, https://doi.org/10.1111/jfb.12600.","productDescription":"10 p.","startPage":"755","endPage":"764","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056283","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":300634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-26","publicationStatus":"PW","scienceBaseUri":"555f01b2e4b0a92fa7eb968f","contributors":{"authors":[{"text":"Mesa, Matthew G. mmesa@usgs.gov","contributorId":3423,"corporation":false,"usgs":true,"family":"Mesa","given":"Matthew","email":"mmesa@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":547400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rose, Brien P. brose@usgs.gov","contributorId":3493,"corporation":false,"usgs":true,"family":"Rose","given":"Brien","email":"brose@usgs.gov","middleInitial":"P.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":547401,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155262,"text":"70155262 - 2015 - The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter","interactions":[],"lastModifiedDate":"2017-01-18T10:06:49","indexId":"70155262","displayToPublicDate":"2015-02-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter","docAbstract":"Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.
","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JCLI-D-14-00344.1","usgsCitation":"Hoell, A., Funk, C.C., and Barlow, M., 2015, The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter: Journal of Climate, v. 28, no. 4, p. 1511-1526, https://doi.org/10.1175/JCLI-D-14-00344.1.","productDescription":"16 p.","startPage":"1511","endPage":"1526","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058649","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-14-00344.1","text":"Publisher Index Page"},{"id":306490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"57f7ef86e4b0bc0bec09f1a6","contributors":{"authors":[{"text":"Hoell, Andrew","contributorId":145805,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Mathew","contributorId":145832,"corporation":false,"usgs":false,"family":"Barlow","given":"Mathew","email":"","affiliations":[{"id":16249,"text":"UMASS Lowel","active":true,"usgs":false}],"preferred":false,"id":565419,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70141757,"text":"70141757 - 2015 - Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles","interactions":[],"lastModifiedDate":"2018-09-04T16:26:28","indexId":"70141757","displayToPublicDate":"2015-02-01T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2809,"text":"Nanotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles","docAbstract":"The release of Ag nanoparticles (AgNPs) into the aquatic environment is likely, but the influence of water chemistry on their impacts and fate remains unclear. Here, we characterize the bioavailability of Ag from AgNO3 and from AgNPs capped with polyvinylpyrrolidone (PVP AgNP) and thiolated polyethylene glycol (PEG AgNP) in the freshwater snail, Lymnaea stagnalis, after short waterborne exposures. Results showed that water hardness, AgNP capping agents, and metal speciation affected the uptake rate of Ag from AgNPs. Comparison of the results from organisms of similar weight showed that water hardness affected the uptake of Ag from AgNPs, but not that from AgNO3. Transformation (dissolution and aggregation) of the AgNPs was also influenced by water hardness and the capping agent. Bioavailability of Ag from AgNPs was, in turn, correlated to these physical changes. Water hardness increased the aggregation of AgNPs, especially for PEG AgNPs, reducing the bioavailability of Ag from PEG AgNPs to a greater degree than from PVP AgNPs. Higher dissolved Ag concentrations were measured for the PVP AgNPs (15%) compared to PEG AgNPs (3%) in moderately hard water, enhancing Ag bioavailability of the former. Multiple drivers of bioavailability yielded differences in Ag influx between very hard and deionized water where the uptake rate constants (kuw, l g-1 d-1 ± SE) varied from 3.1 ± 0.7 to 0.2 ± 0.01 for PEG AgNPs and from 2.3 ± 0.02 to 1.3 ± 0.01 for PVP AgNPs. Modeling bioavailability of Ag from NPs revealed that Ag influx into L. stagnalis comprised uptake from the NPs themselves and from newly dissolved Ag.
Smith and Heaton (2011) propose a model in which stress in the crust is fractal‐like and highly variable on a range of length scales, including short length‐scales of ~1 km. Smith and Heaton (2011) motivate the need for stress heterogeneity on short length‐scales by citing observations such as short length‐scale changes in stress directions inferred from borehole breakouts, short length‐scale changes in earthquake slip, and the success of numerical models that include short‐wavelength stress heterogeneity. The heterogeneous part of the stress field in their model is more than twice as large as the homogeneous part. The stress field in this model frequently reverses itself over short distances, as can be seen in figure14 a of Smith and Heaton (2011). The modeled stress field contains at least 10 areas of reversed shear stress direction over the length of a 100 km long profile, with the length of the reversed areas ranging from <1 to ~5 km.
\nThis model makes specific predictions about the orientations and heterogeneity of earthquake focal mechanisms. Smith and Heaton (2011) attempt to validate this heterogeneous stress model using observations of earthquake focal‐mechanism variability from Hardebeck (2006). They then demonstrate that the model predicts a bias in the orientations of earthquake focal mechanisms, which are biased away from the background stress and toward the stressing rate. They suggest the focal‐mechanism bias in this model invalidates the large body of work over the last several decades, that has inferred stress orientations from the inversion of earthquake focal mechanisms. The question of whether or not the Smith and Heaton (2011) model is applicable to the real Earth is therefore important not only for understanding spatial stress variability but also for evaluating the numerous studies that have inferred crustal stress orientations from earthquake focal mechanisms (e.g., as compiled by Heidbach et al., 2008).
","language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford, CA","doi":"10.1785/0120130127","usgsCitation":"Hardebeck, J.L., 2015, Comment on “Models of stochastic, spatially varying stress in the crust compatible with focal‐mechanism data, and how stress inversions can be biased toward the stress rate” by Deborah Elaine Smith and Thomas H. Heaton: Bulletin of the Seismological Society of America, v. 105, no. 1, p. 447-451, https://doi.org/10.1785/0120130127.","productDescription":"5 p.","startPage":"447","endPage":"451","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045509","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":300085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-13","publicationStatus":"PW","scienceBaseUri":"5549e9b4e4b064e4207ca432","contributors":{"authors":[{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":545856,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70145827,"text":"70145827 - 2015 - Integrated survival analysis using an event-time approach in a Bayesian framework","interactions":[],"lastModifiedDate":"2015-04-13T09:31:55","indexId":"70145827","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Integrated survival analysis using an event-time approach in a Bayesian framework","docAbstract":"Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.
","language":"English","publisher":"Blackwell Pub. Ltd.","publisherLocation":"Oxford, England","doi":"10.1002/ece3.1399","usgsCitation":"Walsh, D.P., Dreitz, V., and Heisey, D.M., 2015, Integrated survival analysis using an event-time approach in a Bayesian framework: Ecology and Evolution, v. 5, no. 3, p. 769-780, https://doi.org/10.1002/ece3.1399.","productDescription":"12 p.","startPage":"769","endPage":"780","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061696","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":472299,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1399","text":"Publisher Index Page"},{"id":299601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-17","publicationStatus":"PW","scienceBaseUri":"552ce8b8e4b0b22a157f50b5","chorus":{"doi":"10.1002/ece3.1399","url":"http://dx.doi.org/10.1002/ece3.1399","publisher":"Wiley-Blackwell","authors":"Walsh Daniel P., Dreitz Victoria J., Heisey Dennis M.","journalName":"Ecology and Evolution","publicationDate":"1/17/2015","auditedOn":"3/17/2016"},"contributors":{"authors":[{"text":"Walsh, Daniel P. 0000-0002-7772-2445 dwalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":4758,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"dwalsh@usgs.gov","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":544448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dreitz, VJ","contributorId":140149,"corporation":false,"usgs":false,"family":"Dreitz","given":"VJ","email":"","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":544449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heisey, Dennis M. dheisey@usgs.gov","contributorId":2455,"corporation":false,"usgs":true,"family":"Heisey","given":"Dennis","email":"dheisey@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":544450,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70146666,"text":"70146666 - 2015 - Site-scale disturbance and habitat development best predict an index of amphibian biotic integrity in Ohio shrub and forested wetlands","interactions":[],"lastModifiedDate":"2015-06-02T11:30:27","indexId":"70146666","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Site-scale disturbance and habitat development best predict an index of amphibian biotic integrity in Ohio shrub and forested wetlands","docAbstract":"We determined the best predictors of an index of amphibian biotic integrity calculated from 54 shrub and forested wetlands in Ohio, USA using a two-step sequential holdout validation procedure. We considered 13 variables as predictors: four metrics of wetland condition from the Ohio Rapid Assessment Method (ORAM), a wetland vegetation index of biotic integrity, and eight metrics from a landscape disturbance index. For all iterations, the best model included the single ORAM metric that assesses habitat alteration, substrate disturbance, and habitat development within a wetland. Our results align with results of similar studies that have associated high scores for wetland vegetation indices of biotic integrity with low habitat alteration and substrate disturbance within wetlands. Thus, implementing similar management practices (e.g., not removing downed woody debris, retaining natural morphological features, decreasing nutrient input from surrounding agricultural lands) could concurrently increase ecological integrity of both plant and amphibian communities in a wetland. Further, our results have the unexpected effect of making progress toward a more unifying theory of ecological indices.
","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-015-0638-2","usgsCitation":"Micacchion, M., Stapanian, M.A., and Adams, J.V., 2015, Site-scale disturbance and habitat development best predict an index of amphibian biotic integrity in Ohio shrub and forested wetlands: Wetlands, v. 35, no. 3, p. 509-519, https://doi.org/10.1007/s13157-015-0638-2.","productDescription":"11 p.","startPage":"509","endPage":"519","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053300","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":299809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.825439453125,\n 41.705728515237524\n ],\n [\n -84.83642578125,\n 39.07037913108751\n ],\n [\n -84.385986328125,\n 39.00211029922512\n ],\n [\n -84.19921875,\n 38.736946065676\n ],\n [\n -83.726806640625,\n 38.57393751557591\n ],\n [\n -83.232421875,\n 38.548165423046584\n ],\n [\n -82.891845703125,\n 38.685509760012\n ],\n [\n -82.584228515625,\n 38.36750215395045\n ],\n [\n -82.12280273437499,\n 38.522384090200845\n ],\n [\n -82.02392578125,\n 38.90813299596705\n ],\n [\n -81.9140625,\n 38.796908303484294\n ],\n [\n -81.474609375,\n 39.32579941789298\n ],\n [\n -81.38671875,\n 39.27478966170308\n ],\n [\n -80.804443359375,\n 39.605688178320804\n ],\n [\n -80.518798828125,\n 40.47202439692057\n ],\n [\n -80.518798828125,\n 42.00032514831621\n ],\n [\n -83.4521484375,\n 41.73852846935917\n ],\n [\n -84.825439453125,\n 41.705728515237524\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-14","publicationStatus":"PW","scienceBaseUri":"553774b1e4b0b22a15808516","contributors":{"authors":[{"text":"Micacchion, Mick","contributorId":21511,"corporation":false,"usgs":true,"family":"Micacchion","given":"Mick","affiliations":[],"preferred":false,"id":545236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":545234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":545235,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148079,"text":"70148079 - 2015 - An open-population hierarchical distance sampling model","interactions":[],"lastModifiedDate":"2015-05-19T09:05:34","indexId":"70148079","displayToPublicDate":"2015-02-01T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"An open-population hierarchical distance sampling model","docAbstract":"Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Brooklyn, NY","doi":"10.1890/14-1625.1","usgsCitation":"Sollmann, R., Gardner, B., Chandler, R.B., Royle, J.A., and Sillett, T.S., 2015, An open-population hierarchical distance sampling model: Ecology, v. 96, no. 2, p. 325-331, https://doi.org/10.1890/14-1625.1.","productDescription":"7 p.","startPage":"325","endPage":"331","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060570","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472301,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/14-1625.1","text":"Publisher Index Page"},{"id":300528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555c5eb0e4b0a92fa7eacbf2","contributors":{"authors":[{"text":"Sollmann, Rachel","contributorId":11909,"corporation":false,"usgs":true,"family":"Sollmann","given":"Rachel","email":"","affiliations":[],"preferred":false,"id":547190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":140853,"corporation":false,"usgs":true,"family":"Gardner","given":"Beth","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":547191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, Richard B rchandler@usgs.gov","contributorId":140854,"corporation":false,"usgs":false,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B","affiliations":[{"id":13596,"text":"Univ. Georgia","active":true,"usgs":false}],"preferred":false,"id":547192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sillett, T Scott","contributorId":140855,"corporation":false,"usgs":false,"family":"Sillett","given":"T","email":"","middleInitial":"Scott","affiliations":[{"id":13597,"text":"Smithsonian Institude","active":true,"usgs":false}],"preferred":false,"id":547193,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193751,"text":"70193751 - 2015 - Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties","interactions":[],"lastModifiedDate":"2018-09-04T15:50:44","indexId":"70193751","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties","docAbstract":"The advection-dispersion equation (ADE) fails to describe commonly observed non-Fickian solute transport in saturated porous media, necessitating the use of other models such as the dual-domain mass-transfer (DDMT) model. DDMT model parameters are commonly calibrated via curve fitting, providing little insight into the relation between effective parameters and physical properties of the medium. There is a clear need for material characterization techniques that can provide insight into the geometry and connectedness of pore spaces related to transport model parameters. Here, we consider proton nuclear magnetic resonance (NMR), direct-current (DC) resistivity, and complex conductivity (CC) measurements for this purpose, and assess these methods using glass beads as a control and two different samples of the zeolite clinoptilolite, a material that demonstrates non-Fickian transport due to intragranular porosity. We estimate DDMT parameters via calibration of a transport model to column-scale solute tracer tests, and compare NMR, DC resistivity, CC results, which reveal that grain size alone does not control transport properties and measured geophysical parameters; rather, volume and arrangement of the pore space play important roles. NMR cannot provide estimates of more-mobile and less-mobile pore volumes in the absence of tracer tests because these estimates depend critically on the selection of a material-dependent and flow-dependent cutoff time. Increased electrical connectedness from DC resistivity measurements are associated with greater mobile pore space determined from transport model calibration. CC was hypothesized to be related to length scales of mass transfer, but the CC response is unrelated to DDMT.
","language":"English","publisher":"AGU","doi":"10.1002/2014WR015284","usgsCitation":"Swanson, R., Binley, A., Keating, K., France, S., Osterman, G., Day-Lewis, F.D., and Singha, K., 2015, Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties: Water Resources Research, v. 51, no. 2, p. 1264-1283, https://doi.org/10.1002/2014WR015284.","productDescription":"20 p.","startPage":"1264","endPage":"1283","ipdsId":"IP-057728","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472303,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr015284","text":"Publisher Index Page"},{"id":349126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-27","publicationStatus":"PW","scienceBaseUri":"5a60febde4b06e28e9c2533f","contributors":{"authors":[{"text":"Swanson, Ryan D","contributorId":199846,"corporation":false,"usgs":false,"family":"Swanson","given":"Ryan D","affiliations":[],"preferred":false,"id":720193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Binley, Andrew 0000-0002-0938-9070","orcid":"https://orcid.org/0000-0002-0938-9070","contributorId":192556,"corporation":false,"usgs":false,"family":"Binley","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":720194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keating, Kristina","contributorId":199847,"corporation":false,"usgs":false,"family":"Keating","given":"Kristina","email":"","affiliations":[],"preferred":false,"id":720195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"France, Samantha","contributorId":199848,"corporation":false,"usgs":false,"family":"France","given":"Samantha","email":"","affiliations":[],"preferred":false,"id":720196,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osterman, Gordon","contributorId":199849,"corporation":false,"usgs":false,"family":"Osterman","given":"Gordon","email":"","affiliations":[],"preferred":false,"id":720197,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":720192,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":720198,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70148424,"text":"70148424 - 2015 - Magmatic gas emissions at Holocene volcanic features near Mono Lake, California, and their relation to regional magmatism","interactions":[],"lastModifiedDate":"2018-09-13T13:39:07","indexId":"70148424","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Magmatic gas emissions at Holocene volcanic features near Mono Lake, California, and their relation to regional magmatism","docAbstract":"Silicic lavas have erupted repeatedly in the Mono Basin over the past few thousand years, forming the massive domes and coulees of the Mono Craters chain and the smaller island vents in Mono Lake. We report here on the first systematic study of magmatic CO2 emissions from these features, conducted during 2007–2010. Most notably, a known locus of weak steam venting on the summit of North Coulee is actually enclosed in a large area (~ 0.25 km2) of diffuse gas discharge that emits 10–14 t/d of CO2, mostly at ambient temperature. Subsurface gases sampled here are heavily air-contaminated, but after standard corrections are applied, show average δ13C-CO2 of − 4.72‰, 3He/4He of 5.89RA, and CO2/3He of 0.77 × 1010, very similar to the values in fumarolic gas from Mammoth Mountain and the Long Valley Caldera immediately to the south of the basin. If these values also characterize the magmatic gas source at Mono Lake, where CO2 is captured by the alkaline lake water, a magmatic CO2 upflow beneath the lake of ~ 4 t/d can be inferred. Groundwater discharge from the Mono Craters area transports ~ 13 t/d of 14C-dead CO2 as free gas and dissolved carbonate species, and adding in this component brings the estimated total magmatic CO2 output to 29 t/d for the two silicic systems in the Mono Basin. If these emissions reflect intrusion and degassing of underlying basalt with 0.5 wt.% CO2, a modest intrusion rate of 0.00075 km3/yr is indicated. Much higher intrusion rates are required to account for CO2 emissions from Mammoth Mountain and the West Moat of the Long Valley Caldera.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2015.01.008","usgsCitation":"Bergfeld, D., Evans, W.C., Howle, J.F., and Hunt, A.G., 2015, Magmatic gas emissions at Holocene volcanic features near Mono Lake, California, and their relation to regional magmatism: Journal of Volcanology and Geothermal Research, v. 292, p. 70-83, https://doi.org/10.1016/j.jvolgeores.2015.01.008.","productDescription":"14 p.","startPage":"70","endPage":"83","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059936","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":301032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Long Valley Caldera, Mammoth Mountain, Mono Craters, Mono Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.06639099121094,\n 37.44106442458555\n ],\n [\n -119.06639099121094,\n 38.02862223458794\n ],\n [\n -118.76083374023436,\n 38.02862223458794\n ],\n [\n -118.76083374023436,\n 37.44106442458555\n ],\n [\n -119.06639099121094,\n 37.44106442458555\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"292","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"557176b5e4b077dba762a2c5","contributors":{"authors":[{"text":"Bergfeld, D. dbergfel@usgs.gov","contributorId":2069,"corporation":false,"usgs":true,"family":"Bergfeld","given":"D.","email":"dbergfel@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":548172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":548173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howle, James F. 0000-0003-0491-6203 jfhowle@usgs.gov","orcid":"https://orcid.org/0000-0003-0491-6203","contributorId":2225,"corporation":false,"usgs":true,"family":"Howle","given":"James","email":"jfhowle@usgs.gov","middleInitial":"F.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":548175,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193748,"text":"70193748 - 2015 - Development of a new semi-analytical model for cross-borehole flow experiments in fractured media","interactions":[],"lastModifiedDate":"2018-08-09T12:48:52","indexId":"70193748","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Development of a new semi-analytical model for cross-borehole flow experiments in fractured media","docAbstract":"Analysis of borehole flow logs is a valuable technique for identifying the presence of fractures in the subsurface and estimating properties such as fracture connectivity, transmissivity and storativity. However, such estimation requires the development of analytical and/or numerical modeling tools that are well adapted to the complexity of the problem. In this paper, we present a new semi-analytical formulation for cross-borehole flow in fractured media that links transient vertical-flow velocities measured in one or a series of observation wells during hydraulic forcing to the transmissivity and storativity of the fractures intersected by these wells. In comparison with existing models, our approach presents major improvements in terms of computational expense and potential adaptation to a variety of fracture and experimental configurations. After derivation of the formulation, we demonstrate its application in the context of sensitivity analysis for a relatively simple two-fracture synthetic problem, as well as for field-data analysis to investigate fracture connectivity and estimate fracture hydraulic properties. These applications provide important insights regarding (i) the strong sensitivity of fracture property estimates to the overall connectivity of the system; and (ii) the non-uniqueness of the corresponding inverse problem for realistic fracture configurations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2014.12.002","usgsCitation":"Roubinet, D., Irving, J., and Day-Lewis, F.D., 2015, Development of a new semi-analytical model for cross-borehole flow experiments in fractured media: Advances in Water Resources, v. 76, p. 97-108, https://doi.org/10.1016/j.advwatres.2014.12.002.","productDescription":"12 p.","startPage":"97","endPage":"108","ipdsId":"IP-061584","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472304,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://serval.unil.ch/notice/serval:BIB_547C366CAA45","text":"External Repository"},{"id":349128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60febde4b06e28e9c25341","contributors":{"authors":[{"text":"Roubinet, Delphine","contributorId":199840,"corporation":false,"usgs":false,"family":"Roubinet","given":"Delphine","email":"","affiliations":[],"preferred":false,"id":720181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irving, James","contributorId":199841,"corporation":false,"usgs":false,"family":"Irving","given":"James","email":"","affiliations":[],"preferred":false,"id":720182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":720180,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}