{"pageNumber":"683","pageRowStart":"17050","pageSize":"25","recordCount":40797,"records":[{"id":70042211,"text":"70042211 - 2012 - Long-term impacts of invasive species on a native top predator in a large lake system","interactions":[],"lastModifiedDate":"2012-12-31T12:11:20","indexId":"70042211","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Long-term impacts of invasive species on a native top predator in a large lake system","docAbstract":"1. Declining abundances of forage fish and the introduction and establishment of non-indigenous species have the potential to substantially alter resource and habitat exploitation by top predators in large lakes. 2. We measured stable isotopes of carbon (δ<sup>13</sup>C) and nitrogen (δ<sup>15</sup>N) in field-collected and archived samples of Lake Ontario lake trout (<i>Salvelinus namaycush</i>) and five species of prey fish and compared current trophic relationships of this top predator with historical samples. 3. Relationships between δ<sup>15</sup>N and lake trout age were temporally consistent throughout Lake Ontario and confirmed the role of lake trout as a top predator in this food web. However, δ<sup>13</sup>C values for age classes of lake trout collected in 2008 ranged from 1.0 to 3.9‰ higher than those reported for the population sampled in 1992. 4. Isotope mixing models predicted that these changes in resource assimilation were owing to the replacement of rainbow smelt (<i>Osmerus mordax</i>) by round goby (<i>Neogobius melanostomus</i>) in lake trout diet and increased reliance on carbon resources derived from nearshore production. This contrasts with the historical situation in Lake Ontario where δ<sup>13</sup>C values of the lake trout population were dominated by a reliance on offshore carbon production. 5. These results indicate a reduced capacity of the Lake Ontario offshore food web to support the energetic requirements of lake trout and that this top predator has become increasingly reliant on prey resources that are derived from nearshore carbon pathways.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Blackwell Publishing Ltd.","publisherLocation":"Oxford, UK","doi":"10.1111/fwb.12014","usgsCitation":"Rush, S.A., Paterson, G., Johnson, T., Drouillard, K.G., Haffner, G.D., Hebert, C.E., Arts, M., McGoldrick, D.J., Backus, S., Lantry, B.F., Lantry, J.R., Schaner, T., and Fisk, A., 2012, Long-term impacts of invasive species on a native top predator in a large lake system: Freshwater Biology, v. 57, no. 11, p. 2342-2355, https://doi.org/10.1111/fwb.12014.","productDescription":"14 p.","startPage":"2342","endPage":"2355","ipdsId":"IP-040527","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":264963,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/fwb.12014"},{"id":264964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"11","noUsgsAuthors":false,"publicationDate":"2012-09-11","publicationStatus":"PW","scienceBaseUri":"50e5d010e4b0a4aa5bb0af4d","contributors":{"authors":[{"text":"Rush, Scott A.","contributorId":92139,"corporation":false,"usgs":true,"family":"Rush","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paterson, Gordon","contributorId":12755,"corporation":false,"usgs":true,"family":"Paterson","given":"Gordon","email":"","affiliations":[],"preferred":false,"id":470997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Tim B.","contributorId":14277,"corporation":false,"usgs":true,"family":"Johnson","given":"Tim B.","affiliations":[],"preferred":false,"id":470998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drouillard, Ken G.","contributorId":36436,"corporation":false,"usgs":true,"family":"Drouillard","given":"Ken","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":471002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haffner, Gordon D.","contributorId":17501,"corporation":false,"usgs":true,"family":"Haffner","given":"Gordon","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":470999,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hebert, Craig E.","contributorId":11041,"corporation":false,"usgs":false,"family":"Hebert","given":"Craig","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":470996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arts, Michael T.","contributorId":77781,"corporation":false,"usgs":false,"family":"Arts","given":"Michael T.","affiliations":[],"preferred":false,"id":471006,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McGoldrick, Daryl J.","contributorId":56517,"corporation":false,"usgs":false,"family":"McGoldrick","given":"Daryl","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":471004,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Backus, Sean M.","contributorId":31335,"corporation":false,"usgs":true,"family":"Backus","given":"Sean M.","affiliations":[],"preferred":false,"id":471001,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470995,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lantry, Jana R.","contributorId":28495,"corporation":false,"usgs":false,"family":"Lantry","given":"Jana","email":"","middleInitial":"R.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":471000,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Schaner, Ted","contributorId":69939,"corporation":false,"usgs":true,"family":"Schaner","given":"Ted","email":"","affiliations":[],"preferred":false,"id":471005,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Fisk, Aaron T.","contributorId":51604,"corporation":false,"usgs":false,"family":"Fisk","given":"Aaron T.","affiliations":[],"preferred":false,"id":471003,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70040182,"text":"70040182 - 2012 - Loss and modification of habitat","interactions":[],"lastModifiedDate":"2022-12-20T17:01:04.013581","indexId":"70040182","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Loss and modification of habitat","docAbstract":"Amphibians live in a wide variety of habitats around the world, many of which have been modified or destroyed by human activities. Most species have unique life history characteristics adapted to specific climates, habitats (e.g., lentic, lotic, terrestrial, arboreal, fossorial, amphibious), and local conditions that provide suitable areas for reproduction, development and growth, shelter from environmental extremes, and predation, as well as connectivity to other populations or habitats. Although some species are entirely aquatic or terrestrial, most amphibians, as their name implies, lead a dual life and require a mosaic of habitats in both aquatic and terrestrial ecosystems. With over 6 billion people on Earth, most species are now persisting in habitats that have been directly or indirectly influenced by human activities. Some species have disappeared where their habitats have been completely destroyed, reduced, or rendered unsuitable. Habitat loss and degradation are widely considered by most researchers as the most important causes of amphibian population decline globally (Barinaga 1990; Wake and Morowitz 1991; Alford and Richards 1999). In this chapter, a background on the diverse habitat requirements of amphibians is provided, followed by a discussion of the effects of urbanization, agriculture, livestock grazing, timber production and harvesting, fire and hazardous fuel management, and roads on amphibians and their habitats. Also briefly discussed is the influence on amphibian habitats of natural disturbances, such as extreme weather events and climate change, given the potential for human activities to impact climate in the longer term. For amphibians in general, microhabitats are of greater importance than for other vertebrates. As ectotherms with a skin that is permeable to water and with naked gelatinous eggs, amphibians are physiologically constrained to be active during environmental conditions that provide appropriate body temperatures and adequate water balance (Thorson and Svihla 1943; Brattstrom 1963; Tracy 1976). Hence, individuals require and seek specific microhabitats that maintain their preferred body temperature while at the same time reducing water loss or allowing individuals to re-hydrate. Amphibians also possess relatively few physical attributes that protect them from predators. Although they may avoid predators behaviourally or deter them by skin toxins, amphibians lack defensive shells or hardened cuticles, do not have protective teeth or claws, and most are insufficiently fast to escape predators. Hence, they are relatively dependent on sites that conceal or protect them from predation. Most amphibians also differ significantly from other vertebrates in possessing a complex two-phase life cycle: the pre-metamorphic larval (tadpole) stage and the post-metamorphic juvenile and adult stage (Wilbur 1980, 1984). Most amphibian species have two distinct econes (Heatwole 1989), each with different habitat requirements, the larvae being aquatic and the post-metamorphic animals more terrestrial. The habitats required by the two phases can differ greatly, but both are essential to the survival of a species. However, amphibian diversity is great and exceptions to this general pattern exist. For example, some species have direct development without going through a larval stage and are fully terrestrial, whereas the larvae of other species can reach sexual maturity without going through metamorphosis (i.e., neoteny) and are fully aquatic.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Conservation and decline of amphibians: Ecological aspects, effect of humans, and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Surrey Beatty & Sons","usgsCitation":"Lemckert, F., Hecnar, S., and Pilliod, D., 2012, Loss and modification of habitat, chap. 1 <i>of</i> Conservation and decline of amphibians: Ecological aspects, effect of humans, and management, v. 10, 52 p.","productDescription":"52 p.","ipdsId":"IP-040483","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":349743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61053fe4b06e28e9c2552c","contributors":{"authors":[{"text":"Lemckert, Francis","contributorId":147197,"corporation":false,"usgs":false,"family":"Lemckert","given":"Francis","email":"","affiliations":[],"preferred":false,"id":724509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hecnar, Stephen","contributorId":147198,"corporation":false,"usgs":false,"family":"Hecnar","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":724510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":147050,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":724511,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042000,"text":"70042000 - 2012 - Subsidy or subtraction: how do terrestrial inputs influence consumer production in lakes?","interactions":[],"lastModifiedDate":"2012-12-31T12:15:11","indexId":"70042000","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1698,"text":"Freshwater Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Subsidy or subtraction: how do terrestrial inputs influence consumer production in lakes?","docAbstract":"Cross-ecosystem fluxes are ubiquitous in food webs and are generally thought of as subsidies to consumer populations. Yet external or allochthonous inputs may in fact have complex and habitat-specific effects on recipient ecosystems. In lakes, terrestrial inputs of organic carbon contribute to basal resource availability, but can also reduce resource availability via shading effects on phytoplankton and periphyton. Terrestrial inputs might therefore either subsidise or subtract from consumer production. We developed and parameterised a simple model to explore this idea. The model estimates basal resource supply and consumer production given lake-level characteristics including total phosphorus (TP) and dissolved organic carbon (DOC) concentration, and consumer-level characteristics including resource preferences and growth efficiencies. Terrestrial inputs diminished primary production and total basal resource supply at the whole-lake level, except in ultra-oligotrophic systems. However, this system-level generalisation masked complex habitat-specific effects. In the pelagic zone, dissolved and particulate terrestrial carbon inputs were available to zooplankton via several food web pathways. Consequently, zooplankton production usually increased with terrestrial inputs, even as total whole-lake resource availability decreased. In contrast, in the benthic zone the dominant, dissolved portion of the terrestrial carbon load had predominantly negative effects on resource availability via shading of periphyton. Consequently, terrestrial inputs always decreased zoobenthic production except under extreme and unrealistic parameterisations of the model. Appreciating the complex and habitat-specific effects of allochthonous inputs may be essential for resolving the effects of cross-habitat fluxes on consumers in lakes and other food webs.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Reviews","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Freshwater Biological Association","publisherLocation":"Cumbria, U.K.","doi":"10.1608/FRJ-5.1.475","usgsCitation":"Jones, S., Solomon, C.T., and Weidel, B., 2012, Subsidy or subtraction: how do terrestrial inputs influence consumer production in lakes?: Freshwater Reviews, v. 5, no. 1, p. 37-49, https://doi.org/10.1608/FRJ-5.1.475.","productDescription":"13 p.","startPage":"37","endPage":"49","ipdsId":"IP-028158","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":264962,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1608/FRJ-5.1.475"},{"id":264965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4df8ce4b0e8fec6ce494d","contributors":{"authors":[{"text":"Jones, Stuart E.","contributorId":22222,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart E.","affiliations":[{"id":6966,"text":"Department of Biological Sciences, University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":470573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":470574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470572,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041931,"text":"70041931 - 2012 - Significant motions between GPS sites in the New Madrid region: implications for seismic hazard","interactions":[],"lastModifiedDate":"2012-12-31T14:16:23","indexId":"70041931","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Significant motions between GPS sites in the New Madrid region: implications for seismic hazard","docAbstract":"Position time series from Global Positioning System (GPS) stations in the New Madrid region were differenced to determine the relative motions between stations. Uncertainties in rates were estimated using a three‐component noise model consisting of white, flicker, and random walk noise, following the methodology of Langbein, 2004. Significant motions of 0.37±0.07 (one standard error) mm/yr were found between sites PTGV and STLE, for which the baseline crosses the inferred deep portion of the Reelfoot fault. Baselines between STLE and three other sites also show significant motion. Site MCTY (adjacent to STLE) also exhibits significant motion with respect to PTGV. These motions are consistent with a model of interseismic slip of about 4  mm/yr on the Reelfoot fault at depths between 12 and 20 km. If constant over time, this rate of slip produces sufficient slip for an <i>M</i> 7.3 earthquake on the shallow portion of the Reelfoot fault, using the geologically derived recurrence time of 500 years. This model assumes that the shallow portion of the fault has been previously loaded by the intraplate stress. A GPS site near Little Rock, Arkansas, shows significant southward motion of 0.3–0.4  mm/yr (±0.08  mm/yr) relative to three sites to the north, indicating strain consistent with focal mechanisms of earthquake swarms in northern Arkansas.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/0120100219","usgsCitation":"Frankel, A., Smalley, R., and Paul, J., 2012, Significant motions between GPS sites in the New Madrid region: implications for seismic hazard: Bulletin of the Seismological Society of America, v. 102, no. 2, p. 479-489, https://doi.org/10.1785/0120100219.","productDescription":"11 p.","startPage":"479","endPage":"489","ipdsId":"IP-024949","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":264985,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120100219"},{"id":264986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","volume":"102","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-03-29","publicationStatus":"PW","scienceBaseUri":"50e4c530e4b0e8fec6ce0c31","contributors":{"authors":[{"text":"Frankel, Arthur","contributorId":103761,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","affiliations":[],"preferred":false,"id":470409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smalley, Robert","contributorId":39670,"corporation":false,"usgs":true,"family":"Smalley","given":"Robert","affiliations":[],"preferred":false,"id":470408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paul, J.","contributorId":7024,"corporation":false,"usgs":true,"family":"Paul","given":"J.","email":"","affiliations":[],"preferred":false,"id":470407,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041972,"text":"70041972 - 2012 - Sources of shaking and flooding during the Tohoku-Oki earthquake: a mixture of rupture styles","interactions":[],"lastModifiedDate":"2013-03-13T15:45:07","indexId":"70041972","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Sources of shaking and flooding during the Tohoku-Oki earthquake: a mixture of rupture styles","docAbstract":"Modeling strong ground motions from great subduction zone earthquakes is one of the great challenges of computational seismology. To separate the rupture characteristics from complexities caused by 3D sub-surface geology requires an extraordinary data set such as provided by the recent Mw9.0 Tohoku-Oki earthquake. Here we combine deterministic inversion and dynamically guided forward simulation methods to model over one thousand high-rate GPS and strong motion observations from 0 to 0.25 Hz across the entire Honshu Island. Our results display distinct styles of rupture with a deeper generic interplate event (~Mw8.5) transitioning to a shallow tsunamigenic earthquake (~Mw9.0) at about 25 km depth in a process driven by a strong dynamic weakening mechanism, possibly thermal pressurization. This source model predicts many important features of the broad set of seismic, geodetic and seafloor observations providing a major advance in our understanding of such great natural hazards.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth and Planetary Science Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.epsl.2012.04.006","usgsCitation":"Wei, S., Graves, R., Helmberger, D., Avouac, J., and Jiang, J., 2012, Sources of shaking and flooding during the Tohoku-Oki earthquake: a mixture of rupture styles: Earth and Planetary Science Letters, v. 333-334, p. 91-100, https://doi.org/10.1016/j.epsl.2012.04.006.","startPage":"91","endPage":"100","numberOfPages":"10","ipdsId":"IP-036931","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":474187,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.caltech.edu/CaltechAUTHORS:20120827-114719257","text":"External Repository"},{"id":264979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264977,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.epsl.2012.04.006"}],"country":"Japan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 122.7,20.2 ], [ 122.7,45.7 ], [ 154.2,45.7 ], [ 154.2,20.2 ], [ 122.7,20.2 ] ] ] } } ] }","volume":"333-334","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4ccd1e4b0e8fec6ce1f73","contributors":{"authors":[{"text":"Wei, Shengji","contributorId":31652,"corporation":false,"usgs":true,"family":"Wei","given":"Shengji","affiliations":[],"preferred":false,"id":470506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Robert","contributorId":78406,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","affiliations":[],"preferred":false,"id":470508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Helmberger, Don","contributorId":75410,"corporation":false,"usgs":true,"family":"Helmberger","given":"Don","affiliations":[],"preferred":false,"id":470507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Avouac, Jean-Philippe","contributorId":98195,"corporation":false,"usgs":true,"family":"Avouac","given":"Jean-Philippe","email":"","affiliations":[],"preferred":false,"id":470510,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jiang, Junle","contributorId":88632,"corporation":false,"usgs":true,"family":"Jiang","given":"Junle","affiliations":[],"preferred":false,"id":470509,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70159493,"text":"70159493 - 2012 - A program for handling map projections of small-scale geospatial raster data","interactions":[],"lastModifiedDate":"2017-04-06T15:11:27","indexId":"70159493","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1188,"text":"Cartographic Perspectives","active":true,"publicationSubtype":{"id":10}},"title":"A program for handling map projections of small-scale geospatial raster data","docAbstract":"<p><span>Scientists routinely accomplish small-scale geospatial modeling using raster datasets of global extent. Such use often requires the projection of global raster datasets onto a map or the reprojection from a given map projection associated with a dataset. The distortion characteristics of these projection transformations can have significant effects on modeling results. Distortions associated with the reprojection of global data are generally greater than distortions associated with reprojections of larger-scale, localized areas. The accuracy of areas in projected raster datasets of global extent is dependent on spatial resolution. To address these problems of projection and the associated resampling that accompanies it, methods for framing the transformation space, direct point-to-point transformations rather than gridded transformation spaces, a solution to the wrap-around problem, and an approach to alternative resampling methods are presented. The implementations of these methods are provided in an open-source software package called MapImage (or&nbsp;</span><i>mapIMG</i><span>, for short), which is designed to function on a variety of computer architectures.</span></p>","language":"English","publisher":"NACIS","doi":"10.14714/CP71.61","usgsCitation":"Finn, M.P., Steinwand, D.R., Trent, J.R., Buehler, R.A., Mattli, D.M., and Yamamoto, K.H., 2012, A program for handling map projections of small-scale geospatial raster data: Cartographic Perspectives, v. 71, p. 53-67, https://doi.org/10.14714/CP71.61.","productDescription":"15 p.","startPage":"53","endPage":"67","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040817","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"links":[{"id":474185,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14714/cp71.61","text":"Publisher Index Page"},{"id":311162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"71","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-09-24","publicationStatus":"PW","scienceBaseUri":"56432339e4b0aafbcd017fc4","contributors":{"authors":[{"text":"Finn, Michael P. 0000-0003-0415-2194 mfinn@usgs.gov","orcid":"https://orcid.org/0000-0003-0415-2194","contributorId":2657,"corporation":false,"usgs":true,"family":"Finn","given":"Michael","email":"mfinn@usgs.gov","middleInitial":"P.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":579215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steinwand, Daniel R. steinwand@usgs.gov","contributorId":3224,"corporation":false,"usgs":true,"family":"Steinwand","given":"Daniel","email":"steinwand@usgs.gov","middleInitial":"R.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":579216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trent, Jason R.","contributorId":81187,"corporation":false,"usgs":true,"family":"Trent","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":579605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buehler, Robert A.","contributorId":92369,"corporation":false,"usgs":true,"family":"Buehler","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":579606,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mattli, David M. dmattli@usgs.gov","contributorId":5606,"corporation":false,"usgs":true,"family":"Mattli","given":"David","email":"dmattli@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":579607,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yamamoto, Kristina H. khyamamoto@usgs.gov","contributorId":4490,"corporation":false,"usgs":true,"family":"Yamamoto","given":"Kristina","email":"khyamamoto@usgs.gov","middleInitial":"H.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":579608,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192104,"text":"70192104 - 2012 - Basin thickness variations at the Junction of the Eastern California Shear Zone and the San Bernardino Mountains, California:  How thick could the Pliocene sections be?","interactions":[],"lastModifiedDate":"2017-11-16T10:38:47","indexId":"70192104","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Basin thickness variations at the Junction of the Eastern California Shear Zone and the San Bernardino Mountains, California:  How thick could the Pliocene sections be?","docAbstract":"We estimate the thickness of Neogene basin fill along the junction of the Eastern\nCalifornia Shear Zone and the North Frontal thrust system of the San Bernardino Mountains\nusing gravity data with geologic and well log constraints. The geometry of the basin fill is of\ninterest for groundwater assessment and location of potential faults, as well as providing an upper\nbound on the thickness of any potential, buried Pliocene sediments. Nearly one thousand new\ngravity measurements were collected along the North Frontal thrust system from Hesperia to\nJohnson Valley. Three-dimensional inverse modeling of the new and existing gravity data shows\nthat Neogene deposits are segmented into basins along the range front of the San Bernardino\nMountains. The Helendale fault, a dextral fault in the Eastern California Shear Zone, separates\nshallower basement (approximately 300 m depth) beneath Lucerne Valley east of the fault from\ndeeper basement (approximately 550 m or more) west of the fault. The thickest part of the basin\nfill is generally located near the San Bernardino Mountains and the basin shallows northward.\nThe amount of throw on the North Frontal thrust appears to decrease eastward, as the gravity\ngradient associated with the fault diminishes in amplitude. The thickness of basin fill away from\nthe North Frontal system and east of the Helendale fault is less than 100 to 200 m, except for local\npockets generally developed along strike-slip faults of the Eastern California Shear Zone and local\neast-west oriented depressions associated with folding of the basin fill.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Searching for the Pliocene: southern exposures, Annual Desert Symposium Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"The 2012 Desert Research Symposium","conferenceDate":"October 2012","conferenceLocation":"Redlands, CA","language":"English","publisher":"California State University Desert Studies Center","usgsCitation":"Langenheim, V., Surko, T.L., Armstrong, P.A., and Matti, J.C., 2012, Basin thickness variations at the Junction of the Eastern California Shear Zone and the San Bernardino Mountains, California:  How thick could the Pliocene sections be?, <i>in</i> Searching for the Pliocene: southern exposures, Annual Desert Symposium Proceedings, Redlands, CA, October 2012, p. 31-37.","productDescription":"7 p.","startPage":"31","endPage":"37","ipdsId":"IP-035779","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":348878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61053fe4b06e28e9c25524","contributors":{"authors":[{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":151042,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Surko, Tammy L.","contributorId":197760,"corporation":false,"usgs":false,"family":"Surko","given":"Tammy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":714246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Armstrong, Phillip A.","contributorId":197761,"corporation":false,"usgs":false,"family":"Armstrong","given":"Phillip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":714247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matti, Jonathan C. 0000-0001-5961-9869 jmatti@usgs.gov","orcid":"https://orcid.org/0000-0001-5961-9869","contributorId":167192,"corporation":false,"usgs":true,"family":"Matti","given":"Jonathan","email":"jmatti@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189076,"text":"70189076 - 2012 - Pyrite–sulfosalt reactions and semimetal fractionation in the Chinkuashih, Taiwan, copper–gold deposit: A 1 Ma paleo-fumarole","interactions":[],"lastModifiedDate":"2019-12-21T07:34:49","indexId":"70189076","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1765,"text":"Geofluids","active":true,"publicationSubtype":{"id":10}},"title":"Pyrite–sulfosalt reactions and semimetal fractionation in the Chinkuashih, Taiwan, copper–gold deposit: A 1 Ma paleo-fumarole","docAbstract":"<p><span>The mineralized fracture system that underlay paleo-fumarole field at Chinkuashih, Taiwan has been exposed by copper–gold mining to depths of about 550&nbsp;m below the paleo-surface. Its mineralogy and systematic variations in metal and semimetal (Fe, Cu, As, Sb, Bi, Hg, Cd, Sn, Zn, Pb, Se, Te, Au, Ag) concentrations provide insights into the chemical responses of a magmatic-vapor phase as it expands through fracture arrays to the surface and discharges as fumaroles associated with more extensive solfatara. At Chinkuashih, following initial sealing of the fractures by silica-alunite alteration, brittle failure reestablished discharge from an underlying reservoir of magmatic vapor. Crystalline pyrite was deposited first in the fractures and was succeeded and replaced by ‘enargite’ (Cu</span><sub>3</sub><span>(As,Sb)S</span><sub>4</sub><span>) as sulfosalt encrustations (‘sublimate’) on fracture surfaces and in extensional cracks. Subsequent recrystallization resulted in complex exsolution intergrowths with antimony fractionation to the evolving crystal–vapor interface. Heavy metal fractionation between sulfosalt and vapor enriched the vapor phase in heavy metals that subsequently precipitated as complex Bi–Hg–Sn sulfosalts in discrete areas (paleo-fumaroles) close to the paleo-surface in a manner analogous to modern-day fumaroles on active volcanoes such as Vulcano, Italy. As in similar paleo-fumaroles (e.g., El Indio, Chile and Lepanto, Philippines), the most characteristic reaction sequence is the partial replacement of the early pyrite by enargite and Fe-tennantite. It is proposed that this reaction tracks the decrease in the pressure of the underlying magmatic-vapor reservoir because of the sustained discharge of vapor to the surface.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1111/j.1468-8123.2012.00367.x","usgsCitation":"Henley, R., and Berger, B.R., 2012, Pyrite–sulfosalt reactions and semimetal fractionation in the Chinkuashih, Taiwan, copper–gold deposit: A 1 Ma paleo-fumarole: Geofluids, v. 12, no. 3, p. 245-260, https://doi.org/10.1111/j.1468-8123.2012.00367.x.","productDescription":"16 p.","startPage":"245","endPage":"260","ipdsId":"IP-037251","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Taiwan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              120.904541015625,\n              21.87169463514272\n            ],\n            [\n              121.058349609375,\n              22.63429269379353\n            ],\n            [\n              121.26708984374999,\n              22.755920681486405\n            ],\n            [\n              121.56372070312499,\n              23.41284706430993\n            ],\n            [\n              121.871337890625,\n              24.287026865376436\n            ],\n            [\n              122.00317382812499,\n              24.70691524106633\n            ],\n            [\n              121.915283203125,\n              24.806681353851964\n            ],\n            [\n              122.23388671874999,\n              25.145284610685064\n            ],\n            [\n              121.805419921875,\n              25.284437746983055\n            ],\n            [\n              121.57470703125,\n              25.37380917154398\n            ],\n            [\n              121.36596679687499,\n              25.37380917154398\n            ],\n            [\n              121.13525390625,\n              25.284437746983055\n            ],\n            [\n              120.673828125,\n              24.926294766395593\n            ],\n            [\n              120.30029296875,\n              24.246964554300924\n            ],\n            [\n              120.02563476562501,\n              23.52370005882413\n            ],\n            [\n              119.84985351562499,\n              22.806567100271522\n            ],\n            [\n              120.201416015625,\n              22.553147478403194\n            ],\n            [\n              120.41015624999999,\n              22.339914425562032\n            ],\n            [\n              120.55297851562499,\n              22.055096050575845\n            ],\n            [\n              120.728759765625,\n              21.841104749065032\n            ],\n            [\n              120.904541015625,\n              21.87169463514272\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-05-23","publicationStatus":"PW","scienceBaseUri":"595611c6e4b0d1f9f05067da","contributors":{"authors":[{"text":"Henley, R.W.","contributorId":52810,"corporation":false,"usgs":true,"family":"Henley","given":"R.W.","email":"","affiliations":[],"preferred":false,"id":702969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berger, Byron R. bberger@usgs.gov","contributorId":1490,"corporation":false,"usgs":true,"family":"Berger","given":"Byron","email":"bberger@usgs.gov","middleInitial":"R.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702785,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193111,"text":"70193111 - 2012 - New Zealand’s deadliest quake sounds alarm for cities on fault lines","interactions":[],"lastModifiedDate":"2017-10-31T11:38:54","indexId":"70193111","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5467,"text":"Natural Hazards Observer","active":true,"publicationSubtype":{"id":10}},"title":"New Zealand’s deadliest quake sounds alarm for cities on fault lines","docAbstract":"<p>The catastrophic Christ Church Earthquake is a strong reminder to engineers and scientists of the hazards pose by fault lines, both mapped and unknown, near major cities. In February 2011, the relatively moderate earthquake that struck the cities of Christchurch and Lyttleton in the Canterbury region of New Zealand's South Island surprised many with its destructive power. The magnitude 6.2 temblor killed 181 people, 118 of whom were killed in the collapse of a single building in the city center. The quake damaged or destroyed more than 100,000 buildings.<br></p><p>It was the deadliest quake to strike the nation in 80 years-since the 1931 earthquake that struck the Napier and Hastings area of the North Island. The Christchurch quake was part of the aftershock sequence following the September 2010 magnitude 7.1 earthquake near Darfield, 40 kilometers west of the city. The Darfield earthquake was in a sparsely populated area, causing to loss of life. By contrast, the Christchurch earthquake was generated on a fault in close proximity to the city.<br></p>","language":"English","publisher":"Natural Hazards Center","usgsCitation":"Kalkan, E., 2012, New Zealand’s deadliest quake sounds alarm for cities on fault lines: Natural Hazards Observer, v. 36, no. 3, p. 1-4.","productDescription":"4 p.","startPage":"1","endPage":"4","ipdsId":"IP-035486","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347761,"type":{"id":15,"text":"Index Page"},"url":"https://erolkalkan.com/Pubs/77.pdf"}],"country":"New Zealand","city":"Christchurch","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              171.650390625,\n              -44.31598790519689\n            ],\n            [\n              173.551025390625,\n              -44.31598790519689\n            ],\n            [\n              173.551025390625,\n              -42.98053954751642\n            ],\n            [\n              171.650390625,\n              -42.98053954751642\n            ],\n            [\n              171.650390625,\n              -44.31598790519689\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98bbfe4b0531197afa04a","contributors":{"authors":[{"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":718014,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70192488,"text":"70192488 - 2012 - Sexual selection and mating chronology of Lesser Prairie-Chickens","interactions":[],"lastModifiedDate":"2017-11-16T10:45:26","indexId":"70192488","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Sexual selection and mating chronology of Lesser Prairie-Chickens","docAbstract":"Little is known about mate selection and lek dynamics of Lesser Prairie-Chickens (Tympanuchus pallidicinctus). We collected data on male territory size and location on leks, behavior, and morphological characteristics and assessed the importance of these variables on male Lesser Prairie-Chicken mating success during spring 2008 and 2009 in the Texas Southern High Plains. We used discrete choice models and found that males that were less idle were chosen more often for mating. Our results also suggest that males with smaller territories obtained more copulations. Morphological characteristics were weaker predictors of male mating success. Peak female attendance at leks occurred during the 1-week interval starting 13 April during both years of study. Male prairie-chickens appear to make exploratory movements to, and from, leks early in the lekking season; 13 of 19 males banded early (23 Feb–13 Mar) in the lekking season departed the lek of capture and were not reobserved (11 yearlings, 2 adults). Thirty-three percent (range  =  26–51%) of males on a lek mated (yearlings  =  44%, adults  =  20%) and males that were more active experienced greater mating success.","language":"English","publisher":"The Wilson Ornithological Society","doi":"10.1676/11-079.1","usgsCitation":"Behney, A.C., Grisham, B.A., Boal, C.W., Whitlaw, H.A., and Haukos, D.A., 2012, Sexual selection and mating chronology of Lesser Prairie-Chickens: Wilson Journal of Ornithology, v. 124, no. 1, p. 96-105, https://doi.org/10.1676/11-079.1.","productDescription":"10 p.","startPage":"96","endPage":"105","ipdsId":"IP-026272","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61053fe4b06e28e9c25522","contributors":{"authors":[{"text":"Behney, Adam C.","contributorId":171686,"corporation":false,"usgs":false,"family":"Behney","given":"Adam","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":722167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grisham, Blake A.","contributorId":75419,"corporation":false,"usgs":true,"family":"Grisham","given":"Blake","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":722168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitlaw, Heather A.","contributorId":13026,"corporation":false,"usgs":true,"family":"Whitlaw","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":722169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":722170,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70190486,"text":"70190486 - 2012 - Concurrent speciation in the eastern woodland salamanders (Genus Plethodon):DNA sequences of the complete albumin nuclear and partialmitochondrial 12s genes","interactions":[],"lastModifiedDate":"2017-09-05T08:59:05","indexId":"70190486","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2779,"text":"Molecular Phylogenetics and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Concurrent speciation in the eastern woodland salamanders (Genus <i>Plethodon</i>):DNA sequences of the complete albumin nuclear and partialmitochondrial 12s genes","title":"Concurrent speciation in the eastern woodland salamanders (Genus Plethodon):DNA sequences of the complete albumin nuclear and partialmitochondrial 12s genes","docAbstract":"Salamanders of the North American plethodontid genus Plethodon are important model organisms in a variety of studies that depend on a phylogenetic framework (e.g., chemical communication, ecological competition, life histories, hybridization, and speciation), and consequently their systematics has been intensively investigated over several decades. Nevertheless, we lack a synthesis of relationships among the species. In the analyses reported here we use new DNA sequence data from the complete nuclear albumin gene (1818 bp) and the 12s mitochondrial gene (355 bp), as well as published data for four other genes (Wiens et al., 2006), up to a total of 6989 bp, to infer relationships. We relate these results to past systematic work based on morphology, allozymes, and DNA sequences. Although basal relationships show a strong consensus across studies, many terminal relationships remain in flux despite substantial sequencing and other molecular and morphological studies. This systematic instability appears to be a consequence of contemporaneous bursts of speciation in the late Miocene and Pliocene, yielding many closely related extant species in each of the four eastern species groups. Therefore we conclude that many relationships are likely to remain poorly resolved in the face of additional sequencing efforts. On the other hand, the current classification of the 45 eastern species into four species groups is supported. The Plethodon cinereus group (10 species) is the sister group to the clade comprising the other three groups, but these latter groups (Plethodon glutinosus [28 species], Plethodon welleri [5 species], and Plethodon wehrlei [2 species]) probably diverged from each other at approximately the same time.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ympev.2011.12.018","usgsCitation":"Highton, R., Hastings, A.P., Palmer, C., Watts, R., Hass, C.A., Culver, M., and Arnold, S., 2012, Concurrent speciation in the eastern woodland salamanders (Genus Plethodon):DNA sequences of the complete albumin nuclear and partialmitochondrial 12s genes: Molecular Phylogenetics and Evolution, v. 63, no. 2, p. 278-290, https://doi.org/10.1016/j.ympev.2011.12.018.","productDescription":"13 p.","startPage":"278","endPage":"290","ipdsId":"IP-056780","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":345450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59afb79fe4b0e9bde1351141","contributors":{"authors":[{"text":"Highton, Richard","contributorId":196137,"corporation":false,"usgs":false,"family":"Highton","given":"Richard","email":"","affiliations":[],"preferred":false,"id":709433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hastings, Amy Picard","contributorId":196138,"corporation":false,"usgs":false,"family":"Hastings","given":"Amy","email":"","middleInitial":"Picard","affiliations":[],"preferred":false,"id":709434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmer, Catherine","contributorId":196139,"corporation":false,"usgs":false,"family":"Palmer","given":"Catherine","email":"","affiliations":[],"preferred":false,"id":709435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watts, Richard","contributorId":196140,"corporation":false,"usgs":false,"family":"Watts","given":"Richard","email":"","affiliations":[],"preferred":false,"id":709436,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hass, Carla A.","contributorId":196141,"corporation":false,"usgs":false,"family":"Hass","given":"Carla","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":709437,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":4327,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":127,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":709432,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arnold, Stevan","contributorId":196142,"corporation":false,"usgs":false,"family":"Arnold","given":"Stevan","email":"","affiliations":[],"preferred":false,"id":709438,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70193242,"text":"70193242 - 2012 - Productivity and sedimentary δ15N variability for the last 17,000 years along the northern Gulf of Alaska continental slope","interactions":[],"lastModifiedDate":"2017-10-31T12:21:00","indexId":"70193242","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3002,"text":"Paleoceanography","active":true,"publicationSubtype":{"id":10}},"title":"Productivity and sedimentary δ15N variability for the last 17,000 years along the northern Gulf of Alaska continental slope","docAbstract":"<p><span>Biogenic opal, organic carbon, organic matter stable isotope, and trace metal data from a well-dated, high-resolution jumbo piston core (EW0408–85JC; 59° 33.3′N, 144° 9.21′W, 682 m water depth) recovered from the northern Gulf of Alaska continental slope reveal changes in productivity and nutrient utilization over the last 17,000 years. Maximum values of opal concentration (∼10%) occur during the deglacial Bølling-Allerød (B-A) interval and earliest Holocene (11.2 to 10.8 cal ka BP), moderate values (∼6%) occur during the Younger Dryas (13.0 to 11.2 cal ka BP) and Holocene, and minimum values (∼3.5%) occur during the Late Glacial Interval (LGI). When converted to opal mass accumulation rates, the highest values (∼5000 g cm</span><sup>−2</sup><span><span>&nbsp;</span>kyr</span><sup>−1</sup><span>) occur during the LGI prior to 16.7 cal ka BP, which points to a strong influence by LGI glacimarine sedimentation regimes. Similar patterns are also observed in total organic carbon and cadmium paleoproductivity proxies. Mid-Holocene peaks in the terrestrial organic matter fraction at 5.5, 4.7, 3.5, and 1.2 cal ka BP indicate periods of enhanced delivery of glaciomarine sediments by the Alaska Coastal Current. The B-A and earliest Holocene intervals are laminated, and enrichments of redox-sensitive elements suggest dysoxic-to-anoxic conditions in the water column. The laminations are also associated with mildly enriched sedimentary<span>&nbsp;</span></span><i>δ</i><sup>15</sup><span>N ratios, indicating a link between productivity, nitrogen cycle dynamics, and sedimentary anoxia. After applying a correction for terrestrial<span>&nbsp;</span></span><i>δ</i><sup>15</sup><span>N contributions based on end-member mixing models of terrestrial and marine organic matter, the resulting B-A marine<span>&nbsp;</span></span><i>δ</i><sup>15</sup><span>N (6.3 ± 0.4 ‰) ratios are consistent with either mild denitrification, or increased nitrate utilization. These findings can be explained by increased micronutrient (Fe) availability during episodes of rapid rising sea level that released iron from the previously subaerial coastal plain; iron input from enhanced terrestrial runoff; and/or the intermittent presence of seasonal sea ice resulting from altered ocean/atmospheric circulation during the B-A in the Gulf of Alaska.</span></p>","language":"English","publisher":"Wiley","doi":"10.1029/2011PA002161","usgsCitation":"Addison, J.A., Finney, B., Dean, W.E., Davies, M., Mix, A.C., and Jaeger, J.M., 2012, Productivity and sedimentary δ15N variability for the last 17,000 years along the northern Gulf of Alaska continental slope: Paleoceanography, v. 27, PA1206; 17 p., https://doi.org/10.1029/2011PA002161.","productDescription":"PA1206; 17 p.","ipdsId":"IP-029801","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":474183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011pa002161","text":"Publisher Index Page"},{"id":347853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -149,\n              57.76\n            ],\n            [\n              -136,\n              57.76\n            ],\n            [\n              -136,\n              63\n            ],\n            [\n              -149,\n              63\n            ],\n            [\n              -149,\n             57.76\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"27","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-02-09","publicationStatus":"PW","scienceBaseUri":"59f98bbee4b0531197afa045","contributors":{"authors":[{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":718342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finney, Bruce P.","contributorId":88074,"corporation":false,"usgs":true,"family":"Finney","given":"Bruce P.","affiliations":[],"preferred":false,"id":718344,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dean, Walter E. dean@usgs.gov","contributorId":1801,"corporation":false,"usgs":true,"family":"Dean","given":"Walter","email":"dean@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":718347,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Davies, Maureen H.","contributorId":91311,"corporation":false,"usgs":true,"family":"Davies","given":"Maureen H.","affiliations":[],"preferred":false,"id":718346,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mix, Alan C.","contributorId":83346,"corporation":false,"usgs":true,"family":"Mix","given":"Alan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":718343,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Jaeger, John M.","contributorId":11423,"corporation":false,"usgs":true,"family":"Jaeger","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":718345,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70189363,"text":"70189363 - 2012 - Using computational modeling of river flow with remotely sensed data to infer channel bathymetry","interactions":[],"lastModifiedDate":"2017-07-11T16:17:30","indexId":"70189363","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Using computational modeling of river flow with remotely sensed data to infer channel bathymetry","docAbstract":"<p><span>As part of an ongoing investigation into the use of computational river flow and morphodynamic models for the purpose of correcting and extending remotely sensed river datasets, a simple method for inferring channel bathymetry is developed and discussed. The method is based on an inversion of the equations expressing conservation of mass and momentum to develop equations that can be solved for depth given known values of vertically-averaged velocity and water-surface elevation. The ultimate goal of this work is to combine imperfect remotely sensed data on river planform, water-surface elevation and water-surface velocity in order to estimate depth and other physical parameters of river channels. In this paper, the technique is examined using synthetic data sets that are developed directly from the application of forward two-and three-dimensional flow models. These data sets are constrained to satisfy conservation of mass and momentum, unlike typical remotely sensed field data sets. This provides a better understanding of the process and also allows assessment of how simple inaccuracies in remotely sensed estimates might propagate into depth estimates. The technique is applied to three simple cases: First, depth is extracted from a synthetic dataset of vertically averaged velocity and water-surface elevation; second, depth is extracted from the same data set but with a normally-distributed random error added to the water-surface elevation; third, depth is extracted from a synthetic data set for the same river reach using computed water-surface velocities (in place of depth-integrated values) and water-surface elevations. In each case, the extracted depths are compared to the actual measured depths used to construct the synthetic data sets (with two- and three-dimensional flow models). Errors in water-surface elevation and velocity that are very small degrade depth estimates and cannot be recovered. Errors in depth estimates associated with assuming water-surface velocities equal to depth-integrated velocities are substantial, but can be reduced with simple corrections.</span></p>","largerWorkTitle":"IAHR Riverflow 2012 Conference Proceedings","conferenceTitle":"IAHR Riverflow 2012 Conference","language":"English","usgsCitation":"Nelson, J.M., McDonald, R.R., Kinzel, P.J., and Shimizu, Y., 2012, Using computational modeling of river flow with remotely sensed data to infer channel bathymetry, <i>in</i> IAHR Riverflow 2012 Conference Proceedings, p. 761-768.","productDescription":"8 p.","startPage":"761","endPage":"768","ipdsId":"IP-036984","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343612,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcnetbase.com/doi/abs/10.1201/b13250-115"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965babce4b0d1f9f05b38d3","contributors":{"authors":[{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":704373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":704375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shimizu, Y.","contributorId":88177,"corporation":false,"usgs":true,"family":"Shimizu","given":"Y.","affiliations":[],"preferred":false,"id":704376,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70193571,"text":"70193571 - 2012 - Digital elevation model generation from satellite interferometric synthetic aperture radar: Chapter 5","interactions":[],"lastModifiedDate":"2017-11-30T10:25:33","indexId":"70193571","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Digital elevation model generation from satellite interferometric synthetic aperture radar: Chapter 5","docAbstract":"<p>An accurate digital elevation model (DEM) is a critical data set for characterizing the natural landscape, monitoring natural hazards, and georeferencing satellite imagery. The ideal interferometric synthetic aperture radar (InSAR) configuration for DEM production is a single-pass two-antenna system. Repeat-pass single-antenna satellite InSAR imagery, however, also can be used to produce useful DEMs. DEM generation from InSAR is advantageous in remote areas where the photogrammetric approach to DEM generation is hindered by inclement weather conditions. There are many sources of errors in DEM generation from repeat-pass InSAR imagery, for example, inaccurate determination of the InSAR baseline, atmospheric delay anomalies, and possible surface deformation because of tectonic, volcanic, or other sources during the time interval spanned by the images. This chapter presents practical solutions to identify and remove various artifacts in repeat-pass satellite InSAR images to generate a high-quality DEM.</p>","largerWorkTitle":"Advances in mapping from remote sensor imagery","language":"English","publisher":"Taylor & Francis","doi":"10.1201/b13770-6","usgsCitation":"Lu, Z., Dzurisin, D., Jung, H., Zhang, L., Lee, W., and Lee, C., 2012, Digital elevation model generation from satellite interferometric synthetic aperture radar: Chapter 5, chap. <i>of</i> Advances in mapping from remote sensor imagery, 26 p., https://doi.org/10.1201/b13770-6.","productDescription":"26 p.","ipdsId":"IP-037018","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":349560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61053ee4b06e28e9c2551a","contributors":{"authors":[{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":719397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dzurisin, Daniel 0000-0002-0138-5067 dzurisin@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-5067","contributorId":538,"corporation":false,"usgs":true,"family":"Dzurisin","given":"Daniel","email":"dzurisin@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jung, Hyung-Sup","contributorId":58382,"corporation":false,"usgs":true,"family":"Jung","given":"Hyung-Sup","email":"","affiliations":[],"preferred":false,"id":719399,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zhang, Lei","contributorId":199545,"corporation":false,"usgs":false,"family":"Zhang","given":"Lei","email":"","affiliations":[],"preferred":false,"id":719400,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lee, Wonjin","contributorId":199546,"corporation":false,"usgs":false,"family":"Lee","given":"Wonjin","email":"","affiliations":[],"preferred":false,"id":719401,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lee, Chang-Wook","contributorId":15748,"corporation":false,"usgs":true,"family":"Lee","given":"Chang-Wook","email":"","affiliations":[],"preferred":false,"id":719398,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70193568,"text":"70193568 - 2012 - A Bayesian method to rank different model forecasts of the same volcanic ash cloud: Chapter 24","interactions":[],"lastModifiedDate":"2017-11-29T14:40:47","indexId":"70193568","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5371,"text":"Geophysical Monograph","active":true,"publicationSubtype":{"id":24}},"title":"A Bayesian method to rank different model forecasts of the same volcanic ash cloud: Chapter 24","docAbstract":"<p>Volcanic eruptions often spew fine ash high into the atmosphere, where it is carried downwind, forming long ash clouds that disrupt air traffic and pose a hazard to air travel. To mitigate such hazards, the community studying ash hazards must assess risk of ash ingestion for any flight path and provide robust and accurate forecasts of volcanic ash dispersal. We provide a quantitative and objective method to evaluate the efficacy of ash dispersal estimates from different models, using Bayes theorem to assess the predictions that each model makes about ash dispersal. We incorporate model and measurement uncertainty and produce a posterior probability for model input parameters. The integral of the posterior over all possible combinations of model inputs determines the evidence for each model and is used to compare models. We compare two different types of transport models, an Eulerian model (Ash3d) and a Langrangian model (PUFF), as applied to the 2010 eruptions of Eyjafjallajökull volcano in Iceland. The evidence for each model benefits from common physical characteristics of ash dispersal from an eruption column and provides a measure of how well each model forecasts cloud transport. Given the complexity of the wind fields, we find that the differences between these models depend upon the differences in the way the models disperse ash into the wind from the source plume. With continued observation, the accuracy of the estimates made by each model increases, increasing the efficacy of each model’s ability to simulate ash dispersal.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Lagrangian Modeling of the Atmosphere","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2012GM001249","usgsCitation":"Denlinger, R.P., Webley, P., Mastin, L.G., and Schwaiger, H.F., 2012, A Bayesian method to rank different model forecasts of the same volcanic ash cloud: Chapter 24, chap. <i>of</i> Lagrangian Modeling of the Atmosphere: Geophysical Monograph, p. 299-310, https://doi.org/10.1029/2012GM001249.","productDescription":"12 p.","startPage":"299","endPage":"310","ipdsId":"IP-036808","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":349562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-03-29","publicationStatus":"PW","scienceBaseUri":"5a61053ee4b06e28e9c2551c","contributors":{"authors":[{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":719387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webley, P.","contributorId":96915,"corporation":false,"usgs":false,"family":"Webley","given":"P.","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":719388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwaiger, Hans F. 0000-0001-7397-8833 hschwaiger@usgs.gov","orcid":"https://orcid.org/0000-0001-7397-8833","contributorId":4108,"corporation":false,"usgs":true,"family":"Schwaiger","given":"Hans","email":"hschwaiger@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719385,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042217,"text":"sir20125262 - 2012 - Assessing potential effects of changes in water use with a numerical groundwater-flow model of Carson Valley, Douglas County, Nevada, and Alpine County, California","interactions":[],"lastModifiedDate":"2012-12-28T13:48:13","indexId":"sir20125262","displayToPublicDate":"2012-12-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5262","title":"Assessing potential effects of changes in water use with a numerical groundwater-flow model of Carson Valley, Douglas County, Nevada, and Alpine County, California","docAbstract":"Rapid growth and development within Carson Valley in Douglas County, Nevada, and Alpine County, California, has caused concern over the continued availability of groundwater, and whether the increased municipal demand could either impact the availability of water or result in decreased flow in the Carson River. Annual pumpage of groundwater has increased from less than 10,000 acre feet per year (acre-ft/yr) in the 1970s to about 31,000 acre-ft/yr in 2004, with most of the water used in agriculture. Municipal use of groundwater totaled about 10,000 acre-feet in 2000. In comparison, average streamflow entering the valley from 1940 to 2006 was 344,100 acre-ft/yr, while average flow exiting the valley was 297,400 acre-ft/yr. Carson Valley is underlain by semi-consolidated Tertiary sediments that are exposed on the eastern side and dip westward. Quaternary fluvial and alluvial deposits overlie the Tertiary sediments in the center and western side of the valley. The hydrology of Carson Valley is dominated by the Carson River, which supplies irrigation water for about 39,000 acres of farmland and maintains the water table less than 5 feet (ft) beneath much of the valley floor. Perennial and ephemeral watersheds drain the Carson Range and the Pine Nut Mountains, and mountain-front recharge to the groundwater system from these watersheds is estimated to average 36,000 acre-ft/yr. Groundwater in Carson Valley flows toward the Carson River and north toward the outlet of the Carson Valley. An upward hydraulic gradient exists over much of the valley, and artesian wells flow at land surface in some areas. Water levels declined as much as 15 ft since 1980 in some areas on the eastern side of the valley. Median estimated transmissivities of Quaternary alluvial-fan and fluvial sediments, and Tertiary sediments are 316; 3,120; and 110 feet squared per day (ft<sup>2</sup>/d), respectively, with larger transmissivity values in the central part of the valley and smaller values near the valley margins. A groundwater-flow model of Quaternary and Tertiary sediments in Carson Valley was developed using MODFLOW and calibrated to simulate historical conditions from water years 1971 through 2005. The 35-year transient simulation represented quarterly changes in precipitation, streamflow, pumping and irrigation. Inflows to the groundwater system simulated in the model include mountain-front recharge from watersheds in the Carson Range and Pine Nut Mountains, valley recharge from precipitation and land application of wastewater, agricultural recharge from irrigation, and septic-tank discharge. Outflows from the groundwater system simulated in the model include evapotranspiration from the water table and groundwater withdrawals for municipal, domestic, irrigation and other water supplies. The exchange of water between groundwater, the Carson River, and the irrigation system was represented with a version of the Streamflow Routing (SFR) package that was modified to apply diversions from the irrigation network to irrigated areas as recharge. The groundwater-flow model was calibrated through nonlinear regression with UCODE to measured water levels and streamflow to estimate values of hydraulic conductivity, recharge and streambed hydraulic-conductivity that were represented by 18 optimized parameters. The aquifer system was simulated as confined to facilitate numerical convergence, and the hydraulic conductivity of the top active model layers that intersect the water table was multiplied by a factor to account for partial saturation. Storage values representative of specific yield were specified in parts of model layers where unconfined conditions are assumed to occur. The median transmissivity (<i>T</i>) values (11,000 and 800 ft<sup>2</sup>/d for the fluvial and alluvial-fan sediments, respectively) are both within the third quartile of <i>T</i> values estimated from specific-capacity data, but <i>T</i> values for Tertiary sediments are larger than the third quartile estimated from specific-capacity data. The estimated vertical anisotropy for the Quaternary fluvial sediments (9,000) is comparable to the value estimated for a previous model of Carson Valley. The estimated total volume of mountain-front recharge is equivalent to a previous estimate from the Precipitation-Runoff Modeling System (PRMS) watershed models, but less recharge is estimated for the Carson Range and more recharge is estimated for the Pine Nut Mountains than the previous estimate. Simulated flow paths indicate that groundwater flows faster through the center of Carson Valley and slower through the lower hydraulic-conductivity Tertiary sediments to the east. Shallow flow in the center of the valley is towards drainage channels, but deeper flow is generally directed toward the basin outlet to the north. The aquifer system is in a dynamic equilibrium with large inflows from storage in dry years and large outflows to storage in wet years. Pumping has historically been less than 10 percent of outflows from the groundwater system, and agricultural recharge has been less than 10 percent of inflows to the groundwater system. Three principal sources of uncertainty that affect model results are: (1) the hydraulic characteristics of the Tertiary sediments on the eastern side of the basin, (2) the composition of sediments beneath the alluvial fans and (3) the extent of the confining unit represented within fluvial sediments in the center of the basin. The groundwater-flow model was used in five 55-year predictive simulations to evaluate the long-term effects of different water-use scenarios on water-budget components, groundwater levels, and streamflow in the Carson River. The predictive simulations represented water years 2006 through 2060 using quarterly stress periods with boundary conditions that varied cyclically to represent the transition from wet to dry conditions observed from water years 1995 through 2004. The five scenarios included a base scenario with 2005 pumping rates held constant throughout the simulation period and four other scenarios using: (1) pumping rates increased by 70 percent, including an additional 1,340 domestic wells, (2A) pumping rates more than doubled with municipal pumping increased by a factor of four over the base scenario, (2B) pumping rates of 2A with 2,040 fewer domestic wells, and (3) pumping rates of 2A with 3,700 acres removed from irrigation. The 55-year predictive simulations indicate that increasing groundwater withdrawals under the scenarios considered would result in as much as 40 ft and 60 ft of water-table decline on the west and east sides of Carson Valley, respectively. The water table in the central part of the valley would remain essentially unchanged, but water-level declines of as much as 30 ft are predicted for the deeper, confined aquifer. The increased withdrawals would reduce the volume of groundwater storage and decrease the mean downstream flow in the Carson River by as much as 16,500 acre-ft/yr. If, in addition, 3,700 acres were removed from irrigation, the reduction in mean downstream flow in the Carson River would be only 6,500 acre-ft/yr. The actual amount of flow reduction is uncertain because of potential changes in irrigation practices that may not be accounted for in the model. The projections of the predictive simulations are sensitive to rates of mountain-front recharge specified for the Carson Range and the Pine Nut Mountains. The model provides a tool that can be used to aid water managers and planners in making informed decisions. A prudent management approach would include continued monitoring of water levels on both the east and west sides of Carson Valley to either verify the predictions of the groundwater-flow model or to provide additional data for recalibration of the model if the predictions prove inaccurate.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125262","collaboration":"Prepared in cooperation with the Carson Water Subconservancy District","usgsCitation":"Yager, R.M., Maurer, D.K., and Mayers, C., 2012, Assessing potential effects of changes in water use with a numerical groundwater-flow model of Carson Valley, Douglas County, Nevada, and Alpine County, California: U.S. Geological Survey Scientific Investigations Report 2012-5262, x,  84 p., https://doi.org/10.3133/sir20125262.","productDescription":"x,  84 p.","numberOfPages":"98","additionalOnlineFiles":"N","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":264890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5262.jpg"},{"id":264888,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5262/"},{"id":264889,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5262/pdf/sir2012-5262.pdf"}],"country":"United States","state":"California;Nevada","county":"Alpine;Churchill;Douglas;Storey;Washoe","otherGeospatial":"Carson River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.0,38.25 ], [ -120.0,40.5 ], [ -118.0,40.5 ], [ -118.0,38.25 ], [ -120.0,38.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cfe1e4b0a4aa5bb0ae7d","contributors":{"authors":[{"text":"Yager, Richard M. 0000-0001-7725-1148 ryager@usgs.gov","orcid":"https://orcid.org/0000-0001-7725-1148","contributorId":950,"corporation":false,"usgs":true,"family":"Yager","given":"Richard","email":"ryager@usgs.gov","middleInitial":"M.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maurer, Douglas K. dkmaurer@usgs.gov","contributorId":2308,"corporation":false,"usgs":true,"family":"Maurer","given":"Douglas","email":"dkmaurer@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":471009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mayers, C.J.","contributorId":17410,"corporation":false,"usgs":true,"family":"Mayers","given":"C.J.","email":"","affiliations":[],"preferred":false,"id":471010,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042219,"text":"sir20125283 - 2012 - Floods of June 2012 in northeastern Minnesota","interactions":[],"lastModifiedDate":"2012-12-28T14:06:05","indexId":"sir20125283","displayToPublicDate":"2012-12-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5283","title":"Floods of June 2012 in northeastern Minnesota","docAbstract":"During June 19–20, 2012, heavy rainfall, as much as 10 inches locally reported, caused severe flooding across northeastern Minnesota. The floods were exacerbated by wet antecedent conditions from a relatively rainy spring, with May 2012 as one of the wettest Mays on record in Duluth. The June 19–20, 2012, rainfall event set new records in Duluth, including greatest 2-day precipitation with 7.25 inches of rain. The heavy rains fell on three major watersheds: the Mississippi Headwaters; the St. Croix, which drains to the Mississippi River; and Western Lake Superior, which includes the St. Louis River and other tributaries to Lake Superior. Widespread flash and river flooding that resulted from the heavy rainfall caused evacuations of residents, and damages to residences, businesses, and infrastructure. In all, nine counties in northeastern Minnesota were declared Federal disaster areas as a result of the flooding. Peak-of-record streamflows were recorded at 13 U.S. Geological Survey streamgages as a result of the heavy rainfall. Flood-peak gage heights, peak streamflows, and annual exceedance probabilities were tabulated for 35 U.S. Geological Survey streamgages. Flood-peak streamflows in June 2012 had annual exceedance probabilities estimated to be less than 0.002 (0.2 percent; recurrence interval greater than 500 years) for five streamgages, and between 0.002 and 0.01 (1 percent; recurrence interval greater than 100 years) for four streamgages. High-water marks were identified and tabulated for the most severely affected communities of Barnum (Moose Horn River), Carlton (Otter Creek), Duluth Heights neighborhood of Duluth (Miller Creek), Fond du Lac neighborhood of Duluth (St. Louis River), Moose Lake (Moose Horn River and Moosehead Lake), and Thomson (Thomson Reservoir outflow near the St. Louis River). Flood-peak inundation maps and water-surface profiles were produced for these six severely affected communities. The inundation maps were constructed in a geographic information system by combining high-water-mark data with high-resolution digital elevation model data. The flood maps and profiles show the extent and depth of flooding through the communities and can be used for flood response and recovery efforts by local, county, State, and Federal agencies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125283","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency.  The Downloads Directory contains the 6 figures from Appendix 2.  For more information, see the \"View companion files\" link above.","usgsCitation":"Czuba, C.R., Fallon, J.D., and Kessler, E.W., 2012, Floods of June 2012 in northeastern Minnesota: U.S. Geological Survey Scientific Investigations Report 2012-5283, Report: vi, 42 p.; Downloads Directory, https://doi.org/10.3133/sir20125283.","productDescription":"Report: vi, 42 p.; Downloads Directory","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-06-19","temporalEnd":"2012-06-20","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":264894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5283.gif"},{"id":264893,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2012/5283/downloads/"},{"id":264891,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5283/"},{"id":264892,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5283/sir2012-5283.pdf"}],"projection":"Universal Transverse Mercator projection, Zone 15","country":"United States","state":"Minnesota","county":"Aitkin;Carlton;Cass;Cook;Crow Wing;Itasca;Lake;Pine;St. Louis","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.0,45.5 ], [ -95.0,48.75 ], [ -89.0,48.75 ], [ -89.0,45.5 ], [ -95.0,45.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cffde4b0a4aa5bb0aef9","contributors":{"authors":[{"text":"Czuba, Christiana R. cczuba@usgs.gov","contributorId":4555,"corporation":false,"usgs":true,"family":"Czuba","given":"Christiana","email":"cczuba@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":471015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fallon, James D. jfallon@usgs.gov","contributorId":3417,"corporation":false,"usgs":true,"family":"Fallon","given":"James","email":"jfallon@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":471014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kessler, Erich W. 0000-0002-0869-4743 ekessler@usgs.gov","orcid":"https://orcid.org/0000-0002-0869-4743","contributorId":2871,"corporation":false,"usgs":true,"family":"Kessler","given":"Erich","email":"ekessler@usgs.gov","middleInitial":"W.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042073,"text":"70042073 - 2012 - Using spatially detailed water-quality data and solute-transport modeling to improve support total maximum daily load development","interactions":[],"lastModifiedDate":"2017-01-17T10:35:43","indexId":"70042073","displayToPublicDate":"2012-12-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Using spatially detailed water-quality data and solute-transport modeling to improve support total maximum daily load development","docAbstract":"Spatially detailed mass-loading studies and solute-transport modeling using OTIS (One-dimensional Transport with Inflow and Storage) demonstrate how natural attenuation and loading from distinct and diffuse sources control stream water quality and affect load reductions predicted in total maximum daily loads (TMDLs). Mass-loading data collected during low-flow from Cement Creek (a low-pH, metal-rich stream because of natural and mining sources, and subject to TMDL requirements) were used to calibrate OTIS and showed spatially variable effects of natural attenuation (instream reactions) and loading from diffuse (groundwater) and distinct sources. OTIS simulations of the possible effects of TMDL-recommended remediation of mine sites showed less improvement to dissolved zinc load and concentration (14% decrease) than did the TMDL (53-63% decrease). The TMDL (1) assumed conservative transport, (2) accounted for loads removed by remediation by subtracting them from total load at the stream mouth, and (3) did not include diffuse-source loads. In OTIS, loads were reduced near their source; the resulting concentration was decreased by natural attenuation and increased by diffuse-source loads during downstream transport. Thus, by not including natural attenuation and loading from diffuse sources, the TMDL overestimated remediation effects at low flow. Use of the techniques presented herein could improve TMDLs by incorporating these processes during TMDL development.","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1752-1688.2012.00662.x","usgsCitation":"Walton-Day, K., Runkel, R.L., and Kimball, B.A., 2012, Using spatially detailed water-quality data and solute-transport modeling to improve support total maximum daily load development: Journal of the American Water Resources Association, v. 48, no. 5, p. 949-969, https://doi.org/10.1111/j.1752-1688.2012.00662.x.","productDescription":"21 p.","startPage":"949","endPage":"969","ipdsId":"IP-027724","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":264814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-05-31","publicationStatus":"PW","scienceBaseUri":"50e5650ce4b0a4aa5bb04b66","contributors":{"authors":[{"text":"Walton-Day, Katherine 0000-0002-9146-6193","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":68339,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","affiliations":[],"preferred":false,"id":470740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kimball, Briant A. bkimball@usgs.gov","contributorId":533,"corporation":false,"usgs":true,"family":"Kimball","given":"Briant","email":"bkimball@usgs.gov","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470738,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041940,"text":"70041940 - 2012 - Timing of large earthquakes during the past 500 years along the Santa Cruz Mountains segment of the San Andreas fault at Mill Canyon, near Watsonville, California","interactions":[],"lastModifiedDate":"2012-12-26T15:39:50","indexId":"70041940","displayToPublicDate":"2012-12-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Timing of large earthquakes during the past 500 years along the Santa Cruz Mountains segment of the San Andreas fault at Mill Canyon, near Watsonville, California","docAbstract":"A paleoseismic investigation across the Santa Cruz Mountains section of the San Andreas fault at Mill Canyon indicates that four surface‐rupturing earthquakes have occurred there during the past ~500  years. At this site, right‐lateral fault slip has moved a low shutter ridge across the mouth of the canyon, ponding latest Holocene sediments. These alluvial deposits are deformed along a narrow zone of faulting. There is excellent evidence for a 1906 (M 7.8) and three earlier earthquakes consisting of well‐developed fissures, scarps, and colluvial wedges. Deformation resulting from the earlier earthquakes is comparable to that from 1906, suggesting they also were large‐magnitude events. The earthquake prior to 1906 occurred either about A.D. 1750 (1711–1770) or A.D. 1855 (1789–1904), depending on assumptions incorporated into two alternative OxCal models. If the later age range is correct, then the earthquake may have been a historical early‐to‐mid‐nineteenth‐century earthquake, possibly the A.D. 1838 earthquake. Both models are viable, and there is no way to select one over the other with the available data. Two earlier earthquakes occurred about A.D. 1690 (1660–1720) and A.D. 1522 (1454–1605). Using OxCal, recalculation of the age of the reported penultimate earthquake reported from the Grizzly Flat site, located about 10 km northwest of Mill Canyon, indicates it occurred about A.D. 1105–1545, earlier than any of the past three earthquakes, and possibly correlates to the fourth earthquake at Mill Canyon.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/0120110161","usgsCitation":"Fumal, T.E., 2012, Timing of large earthquakes during the past 500 years along the Santa Cruz Mountains segment of the San Andreas fault at Mill Canyon, near Watsonville, California: Bulletin of the Seismological Society of America, v. 102, no. 3, p. 1099-1119, https://doi.org/10.1785/0120110161.","productDescription":"21 p.","startPage":"1099","endPage":"1119","ipdsId":"IP-026483","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":264801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264800,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120110161"}],"country":"United States","state":"California","city":"Watsonville","otherGeospatial":"Mill Canyon;San Andreas Fault","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.69,36.94 ], [ -121.69,36.96 ], [ -121.67,36.96 ], [ -121.67,36.94 ], [ -121.69,36.94 ] ] ] } } ] }","volume":"102","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-06-05","publicationStatus":"PW","scienceBaseUri":"50e55067e4b0a4aa5bb0195e","contributors":{"authors":[{"text":"Fumal, Thomas E.","contributorId":67882,"corporation":false,"usgs":true,"family":"Fumal","given":"Thomas","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":470419,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70041910,"text":"70041910 - 2012 - Wave-induced mass transport affects daily <i>Escherichia coli</i> fluctuations in nearshore water","interactions":[],"lastModifiedDate":"2012-12-27T12:11:22","indexId":"70041910","displayToPublicDate":"2012-12-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Wave-induced mass transport affects daily <i>Escherichia coli</i> fluctuations in nearshore water","docAbstract":"Characterization of diel variability of fecal indicator bacteria concentration in nearshore waters is of particular importance for development of water sampling standards and protection of public health. Significant nighttime increase in <i>Escherichia coli</i> (<i>E. coli</i>) concentration in beach water, previously observed at marine sites, has also been identified in summer 2000 from fixed locations in waist- and knee-deep waters at Chicago 63rd Street Beach, an embayed, tideless, freshwater beach with low currents at night (approximately 0.015 m s<sup>–1</sup>). A theoretical model using wave-induced mass transport velocity for advection was developed to assess the contribution of surface waves to the observed nighttime <i>E. coli</i> replenishment in the nearshore water. Using average wave conditions for the summer season of year 2000, the model predicted an amount of <i>E. coli</i> transported from water of intermediate depth, where sediment resuspension occurred intermittently, that would be sufficient to have elevated <i>E. coli</i> concentration in the surf and swash zones as observed. The nighttime replenishment of <i>E. coli</i> in the surf and swash zones revealed here is an important phase in the cycle of diel variations of <i>E. coli</i> concentration in nearshore water. According to previous findings in Ge et al. (Environ. Sci. Technol. 2010, 44, 6731–6737), enhanced current circulation in the embayment during the day tends to displace and deposit material offshore, which partially sets up the system by the early evening for a new period of nighttime onshore movement. This wave-induced mass transport effect, although facilitating a significant base supply of material shoreward, can be perturbed or significantly influenced by high currents (orders of magnitude larger than a typical wave-induced mass transport velocity), current-induced turbulence, and tidal forcing.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/es203847n","usgsCitation":"Ge, Z., Whitman, R.L., Nevers, M.B., and Phanikumar, M., 2012, Wave-induced mass transport affects daily <i>Escherichia coli</i> fluctuations in nearshore water: Environmental Science & Technology, v. 46, no. 4, p. 2204-2211, https://doi.org/10.1021/es203847n.","productDescription":"8 p.","startPage":"2204","endPage":"2211","ipdsId":"IP-034924","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":264829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264825,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es203847n"}],"country":"United States","state":"Illinois","city":"Chicago","otherGeospatial":"63rd Street Beach","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.5765811,41.781041 ], [ -87.5765811,41.7844751 ], [ -87.5686903,41.7844751 ], [ -87.5686903,41.781041 ], [ -87.5765811,41.781041 ] ] ] } } ] }","volume":"46","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-02-01","publicationStatus":"PW","scienceBaseUri":"50e583c9e4b0a4aa5bb096de","contributors":{"authors":[{"text":"Ge, Zhongfu","contributorId":29709,"corporation":false,"usgs":true,"family":"Ge","given":"Zhongfu","affiliations":[],"preferred":false,"id":470368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nevers, Meredith B.","contributorId":91803,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":470369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phanikumar, Mantha S.","contributorId":17888,"corporation":false,"usgs":true,"family":"Phanikumar","given":"Mantha S.","affiliations":[],"preferred":false,"id":470367,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042060,"text":"70042060 - 2012 - A vectorial capacity product to monitor changing malaria transmission potential in epidemic regions of Africa","interactions":[],"lastModifiedDate":"2012-12-25T12:40:33","indexId":"70042060","displayToPublicDate":"2012-12-25T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2488,"text":"Journal of Tropical Medicine","active":true,"publicationSubtype":{"id":10}},"title":"A vectorial capacity product to monitor changing malaria transmission potential in epidemic regions of Africa","docAbstract":"Rainfall and temperature are two of the major factors triggering malaria epidemics in warm semi-arid (desert-fringe) and high altitude (highland-fringe) epidemic risk areas. The ability of the mosquitoes to transmit <i>Plasmodium</i> spp. is dependent upon a series of biological features generally referred to as vectorial capacity. In this study, the vectorial capacity model (VCAP) was expanded to include the influence of rainfall and temperature variables on malaria transmission potential. Data from two remote sensing products were used to monitor rainfall and temperature and were integrated into the VCAP model. The expanded model was tested in Eritrea and Madagascar to check the viability of the approach. The analysis of VCAP in relation to rainfall, temperature and malaria incidence data in these regions shows that the expanded VCAP correctly tracks the risk of malaria both in regions where rainfall is the limiting factor and in regions where temperature is the limiting factor. The VCAP maps are currently offered as an experimental resource for testing within Malaria Early Warning applications in epidemic prone regions of sub-Saharan Africa. User feedback is currently being collected in preparation for further evaluation and refinement of the VCAP model.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Tropical Medicine","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Hindawi Publishing Corporation","publisherLocation":"Cairo, Egypt","doi":"10.1155/2012/595948","usgsCitation":"Ceccato, P., Vancutsem, C., Klaver, R., Rowland, J., and Connor, S.J., 2012, A vectorial capacity product to monitor changing malaria transmission potential in epidemic regions of Africa: Journal of Tropical Medicine, v. 2012, p. 1-6, https://doi.org/10.1155/2012/595948.","productDescription":"Article ID 595948: 6 p.","startPage":"1","endPage":"6","onlineOnly":"Y","ipdsId":"IP-033377","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474189,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/2012/595948","text":"Publisher Index Page"},{"id":264765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264763,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1155/2012/595948"},{"id":264764,"type":{"id":11,"text":"Document"},"url":"https://downloads.hindawi.com/journals/jtm/2012/595948.pdf"}],"otherGeospatial":"Africa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -26.6,37.5 ], [ -26.6,38.0 ], [ 60.6,38.0 ], [ 60.6,37.5 ], [ -26.6,37.5 ] ] ] } } ] }","volume":"2012","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cfd9e4b0a4aa5bb0ae58","contributors":{"authors":[{"text":"Ceccato, Pietro","contributorId":64126,"corporation":false,"usgs":true,"family":"Ceccato","given":"Pietro","email":"","affiliations":[],"preferred":false,"id":470700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vancutsem, Christelle","contributorId":71085,"corporation":false,"usgs":true,"family":"Vancutsem","given":"Christelle","email":"","affiliations":[],"preferred":false,"id":470702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert 0000-0002-3263-9701","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":66148,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"","affiliations":[],"preferred":false,"id":470701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowland, James 0000-0003-4837-3511 rowland@usgs.gov","orcid":"https://orcid.org/0000-0003-4837-3511","contributorId":3108,"corporation":false,"usgs":true,"family":"Rowland","given":"James","email":"rowland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":470699,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Connor, Stephen J.","contributorId":104370,"corporation":false,"usgs":true,"family":"Connor","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":470703,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70042069,"text":"70042069 - 2012 - Novel approach for computing photosynthetically active radiation for productivity modeling using remotely sensed images in the Great Plains, United States","interactions":[],"lastModifiedDate":"2012-12-23T17:11:14","indexId":"70042069","displayToPublicDate":"2012-12-23T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2172,"text":"Journal of Applied Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Novel approach for computing photosynthetically active radiation for productivity modeling using remotely sensed images in the Great Plains, United States","docAbstract":"Gross primary production (GPP) is a key indicator of ecosystem performance, and helps in many decision-making processes related to environment. We used the Eddy covariancelight use efficiency (EC-LUE) model for estimating GPP in the Great Plains, United States in order to evaluate the performance of this model. We developed a novel algorithm for computing the photosynthetically active radiation (PAR) based on net radiation. A strong correlation (<i>R</i><sup>2</sup>=0.94,<i>N</i>=24) was found between daily PAR and Landsat-based mid-day instantaneous net radiation. Though the Moderate Resolution Spectroradiometer (MODIS) based instantaneous net radiation was in better agreement (<i>R</i><sup>2</sup>=0.98,<i>N</i>=24) with the daily measured PAR, there was no statistical significant difference between Landsat based PAR and MODIS based PAR. The EC-LUE model validation also confirms the need to consider biological attributes (C<sup>3</sup> versus C<sup>4</sup> plants) for potential light use efficiency. A universal potential light use efficiency is unable to capture the spatial variation of GPP. It is necessary to use C<sup>3</sup> versus C<sup>4</sup> based land use/land cover map for using EC-LUE model for estimating spatiotemporal distribution of GPP.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SPIE","publisherLocation":"Bellingham, WA","doi":"10.1117/1.JRS.6.063522","usgsCitation":"Singh, R.K., Liu, S., Tieszen, L.L., Suyker, A.E., and Verma, S., 2012, Novel approach for computing photosynthetically active radiation for productivity modeling using remotely sensed images in the Great Plains, United States: Journal of Applied Remote Sensing, v. 6, no. 1, 063522, https://doi.org/10.1117/1.JRS.6.063522.","productDescription":"063522","ipdsId":"IP-029748","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":264754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264753,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1117/1.JRS.6.063522"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","volume":"6","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e0af02e4b0fec3206ef6a3","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":470731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shu-Guang sliu@usgs.gov","contributorId":984,"corporation":false,"usgs":true,"family":"Liu","given":"Shu-Guang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":470729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tieszen, Larry L. tieszen@usgs.gov","contributorId":2831,"corporation":false,"usgs":true,"family":"Tieszen","given":"Larry","email":"tieszen@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":470730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suyker, Andrew E.","contributorId":46857,"corporation":false,"usgs":true,"family":"Suyker","given":"Andrew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":470732,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verma, Shashi B.","contributorId":76202,"corporation":false,"usgs":true,"family":"Verma","given":"Shashi B.","affiliations":[],"preferred":false,"id":470733,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70042065,"text":"70042065 - 2012 - Estimating seasonal evapotranspiration from temporal satellite images","interactions":[],"lastModifiedDate":"2012-12-23T22:33:39","indexId":"70042065","displayToPublicDate":"2012-12-23T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2110,"text":"Irrigation Science","active":true,"publicationSubtype":{"id":10}},"title":"Estimating seasonal evapotranspiration from temporal satellite images","docAbstract":"Estimating seasonal evapotranspiration (ET) has many applications in water resources planning and management, including hydrological and ecological modeling. Availability of satellite remote sensing images is limited due to repeat cycle of satellite or cloud cover. This study was conducted to determine the suitability of different methods namely cubic spline, fixed, and linear for estimating seasonal ET from temporal remotely sensed images. Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model in conjunction with the wet METRIC (wMETRIC), a modified version of the METRIC model, was used to estimate ET on the days of satellite overpass using eight Landsat images during the 2001 crop growing season in Midwest USA. The model-estimated daily ET was in good agreement (<i>R</i><sup>2</sup> = 0.91) with the eddy covariance tower-measured daily ET. The standard error of daily ET was 0.6 mm (20%) at three validation sites in Nebraska, USA. There was no statistically significant difference (<i>P</i> > 0.05) among the cubic spline, fixed, and linear methods for computing seasonal (July–December) ET from temporal ET estimates. Overall, the cubic spline resulted in the lowest standard error of 6 mm (1.67%) for seasonal ET. However, further testing of this method for multiple years is necessary to determine its suitability.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Irrigation Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s00271-011-0287-z","usgsCitation":"Singh, R.K., Liu, S., Tieszen, L.L., Suyker, A.E., and Verma, S., 2012, Estimating seasonal evapotranspiration from temporal satellite images: Irrigation Science, v. 30, no. 4, p. 303-313, https://doi.org/10.1007/s00271-011-0287-z.","productDescription":"11 p.","startPage":"303","endPage":"313","ipdsId":"IP-021931","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":264760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264759,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00271-011-0287-z"}],"volume":"30","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-04-30","publicationStatus":"PW","scienceBaseUri":"50db870de4b061270600c358","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":470726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shu-Guang sliu@usgs.gov","contributorId":984,"corporation":false,"usgs":true,"family":"Liu","given":"Shu-Guang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":470724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tieszen, Larry L. tieszen@usgs.gov","contributorId":2831,"corporation":false,"usgs":true,"family":"Tieszen","given":"Larry","email":"tieszen@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":470725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suyker, Andrew E.","contributorId":46857,"corporation":false,"usgs":true,"family":"Suyker","given":"Andrew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":470727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verma, Shashi B.","contributorId":76202,"corporation":false,"usgs":true,"family":"Verma","given":"Shashi B.","affiliations":[],"preferred":false,"id":470728,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70042120,"text":"tm4F4 - 2012 - Advanced methods for modeling water-levels and estimating drawdowns with SeriesSEE, an Excel add-in","interactions":[],"lastModifiedDate":"2022-04-26T19:05:49.744279","indexId":"tm4F4","displayToPublicDate":"2012-12-23T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-F4","title":"Advanced methods for modeling water-levels and estimating drawdowns with SeriesSEE, an Excel add-in","docAbstract":"<p>Water-level modeling is used for multiple-well aquifer tests to reliably differentiate pumping responses from natural water-level changes in wells, or &ldquo;environmental fluctuations.&rdquo; Synthetic water levels are created during water-level modeling and represent the summation of multiple component fluctuations, including those caused by environmental forcing and pumping. Pumping signals are modeled by transforming step-wise pumping records into water-level changes by using superimposed Theis functions. Water-levels can be modeled robustly with this Theis-transform approach because environmental fluctuations and pumping signals are simulated simultaneously. Water-level modeling with Theis transforms has been implemented in the program SeriesSEE, which is a Microsoft&reg; Excel add-in. Moving average, Theis, pneumatic-lag, and gamma functions transform time series of measured values into water-level model components in SeriesSEE. Earth tides and step transforms are additional computed water-level model components. Water-level models are calibrated by minimizing a sum-of-squares objective function where singular value decomposition and Tikhonov regularization stabilize results. Drawdown estimates from a water-level model are the summation of all Theis transforms minus residual differences between synthetic and measured water levels. The accuracy of drawdown estimates is limited primarily by noise in the data sets, not the Theis-transform approach. Drawdowns much smaller than environmental fluctuations have been detected across major fault structures, at distances of more than 1 mile from the pumping well, and with limited pre-pumping and recovery data at sites across the United States. In addition to water-level modeling, utilities exist in SeriesSEE for viewing, cleaning, manipulating, and analyzing time-series data.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section F: Groundwater in Book 4:<i>Hydrologic Analysis and Interpretation</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4F4","collaboration":"U. S. Department of Energy, National Nuclear Security Administration, Environmental Restoration Program, Underground Test Area Project","usgsCitation":"Halford, K., Garcia, C.A., Fenelon, J., and Mirus, B., 2012, Advanced methods for modeling water-levels and estimating drawdowns with SeriesSEE, an Excel add-In, (ver. 1.1, July, 2016): U.S. Geological Survey Techniques and Methods 4–F4, 28 p., https://dx.doi.org/10.3133/tm4F4.","productDescription":"Report: viii, 29 p.; Report Package; 5 Appendixes","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":399696,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98010.htm"},{"id":264743,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/tm4-F4/pdf/AppendixE_PahuteMesaExample.zip","text":"Appendix E Pahute Mesa Example","size":"18.7","linkFileType":{"id":6,"text":"zip"}},{"id":264742,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/tm4-F4/pdf/AppendixD_HypotheticalAquifer.zip","text":"Appendix D Hypothetical Aquifer","size":"15.1","linkFileType":{"id":6,"text":"zip"}},{"id":264741,"rank":0,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/tm4-F4/pdf/AppendixC_Verification.zip","text":"Appendix C Verification","size":"3.2 MB","linkFileType":{"id":6,"text":"zip"}},{"id":325395,"rank":10,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/tm/tm4-F4/versionHist.txt"},{"id":264736,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm4-F4/"},{"id":264737,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/tm4-F4/pdf/tm4-F4.pdf","text":"Report PDF","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":264738,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/tm/tm4-F4/pdf/Release.v1.20_T+M_SeriesSEE_Appendixes.zip","text":"Complete Report Package","size":"83.1 MB","linkFileType":{"id":6,"text":"zip"}},{"id":264740,"rank":0,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/tm4-F4/pdf/AppendixB_Codes-SeriesSEE.v1.20.zip","text":"Appendix B Codes-Series SEE.v1.20","size":"8.1 MB","linkFileType":{"id":6,"text":"zip"}},{"id":264739,"rank":0,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/tm4-F4/pdf/AppendixA_SeriesSEE.v.1.20.zip","text":"Appendix A Series SEE.v.1.20","size":"30.9 MB","linkFileType":{"id":6,"text":"zip"}},{"id":264744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/tm4-F4/images/coverthb.jpg"}],"edition":"Version 1.0: Originally posted December 2012; Version 1.1: July 2016","publicComments":"This report is Chapter 4 of Section F: Groundwater in Book 4:<i>Hydrologic Analysis and Interpretation</i>.","contact":"<p><a href=\"mailto:dc_nv@usgs.gov\" data-mce-href=\"mailto:dc_nv@usgs.gov\">Director</a>, Nevada Water Science Center <br>U.S. Geological Survey<br>2730 N. Deer Run Road<br>Carson City, Nevada 89701<br><a href=\"http://nevada.usgs.gov/\" data-mce-href=\"http://nevada.usgs.gov/\">http://nevada.usgs.gov/</a></p>","tableOfContents":"<p>USGS Techniques and Methods 4-F4: Advanced Methods for Modeling Water-Levels and Estimating Drawdowns with SeriesSEE, an Excel Add-In<!-- Posting Metadata --><!-- End Posting Metadata --></p>\n<ul>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Purpose and Scope</li>\n<li>Environmental Fluctuations</li>\n<li>Water-Level Modeling</li>\n<li>SeriesSEE</li>\n<li>Applications of Water-Level Modeling</li>\n<li>Water-Level Modeling Strategies</li>\n<li>Summary and Conclusions</li>\n<li>References</li>\n</ul>\n<p>&nbsp;</p>","publishedDate":"2012-12-21","revisedDate":"2016-07-18","noUsgsAuthors":false,"publicationDate":"2012-12-21","publicationStatus":"PW","scienceBaseUri":"50e5cfdee4b0a4aa5bb0ae68","contributors":{"authors":[{"text":"Halford, Keith 0000-0002-7322-1846","orcid":"https://orcid.org/0000-0002-7322-1846","contributorId":74845,"corporation":false,"usgs":true,"family":"Halford","given":"Keith","affiliations":[],"preferred":false,"id":470799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, C. Amanda 0000-0003-3776-3565 cgarcia@usgs.gov","orcid":"https://orcid.org/0000-0003-3776-3565","contributorId":1899,"corporation":false,"usgs":true,"family":"Garcia","given":"C.","email":"cgarcia@usgs.gov","middleInitial":"Amanda","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fenelon, Joe","contributorId":70266,"corporation":false,"usgs":true,"family":"Fenelon","given":"Joe","email":"","affiliations":[],"preferred":false,"id":470798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mirus, Benjamin B.","contributorId":12348,"corporation":false,"usgs":false,"family":"Mirus","given":"Benjamin","email":"","middleInitial":"B.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":470797,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042022,"text":"70042022 - 2012 - Effects of activity and energy budget balancing algorithm on laboratory performance of a fish bioenergetics model","interactions":[],"lastModifiedDate":"2012-12-27T11:28:18","indexId":"70042022","displayToPublicDate":"2012-12-23T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Effects of activity and energy budget balancing algorithm on laboratory performance of a fish bioenergetics model","docAbstract":"We evaluated the performance of the Wisconsin bioenergetics model for lake trout <i>Salvelinus namaycush</i> that were fed ad libitum in laboratory tanks under regimes of low activity and high activity. In addition, we compared model performance under two different model algorithms: (1) balancing the lake trout energy budget on day t based on lake trout energy density on day t and (2) balancing the lake trout energy budget on day t based on lake trout energy density on day t + 1. Results indicated that the model significantly underestimated consumption for both inactive and active lake trout when algorithm 1 was used and that the degree of underestimation was similar for the two activity levels. In contrast, model performance substantially improved when using algorithm 2, as no detectable bias was found in model predictions of consumption for inactive fish and only a slight degree of overestimation was detected for active fish. The energy budget was accurately balanced by using algorithm 2 but not by using algorithm 1. Based on the results of this study, we recommend the use of algorithm 2 to estimate food consumption by fish in the field. Our study results highlight the importance of accurately accounting for changes in fish energy density when balancing the energy budget; furthermore, these results have implications for the science of evaluating fish bioenergetics model performance and for more accurate estimation of food consumption by fish in the field when fish energy density undergoes relatively rapid changes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/00028487.2012.692346","usgsCitation":"Madenjian, C.P., David, S.R., and Pothoven, S.A., 2012, Effects of activity and energy budget balancing algorithm on laboratory performance of a fish bioenergetics model: Transactions of the American Fisheries Society, v. 141, no. 5, p. 1328-1337, https://doi.org/10.1080/00028487.2012.692346.","productDescription":"10 p.","startPage":"1328","endPage":"1337","numberOfPages":"10","ipdsId":"IP-028753","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":474193,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/2027.42/141002","text":"External Repository"},{"id":264816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264815,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/00028487.2012.692346"}],"country":"United States","volume":"141","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-08-16","publicationStatus":"PW","scienceBaseUri":"50e5cff2e4b0a4aa5bb0aecb","contributors":{"authors":[{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"David, Solomon R. sdavid@usgs.gov","contributorId":92942,"corporation":false,"usgs":true,"family":"David","given":"Solomon","email":"sdavid@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":470623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":470624,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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