{"pageNumber":"663","pageRowStart":"16550","pageSize":"25","recordCount":40804,"records":[{"id":70148142,"text":"70148142 - 2013 - Factors influencing survival and mark retention in postmetamorphic boreal chorus frogs","interactions":[],"lastModifiedDate":"2015-05-27T13:58:03","indexId":"70148142","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1337,"text":"Copeia","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing survival and mark retention in postmetamorphic boreal chorus frogs","docAbstract":"<p><span>The ability to track individual animals is crucial in many field studies and often requires applying marks to captured individuals. Toe clipping has historically been a standard marking method for wild amphibian populations, but more recent marking methods include visual implant elastomer and photo identification. Unfortunately, few studies have investigated the influence and effectiveness of marking methods for recently metamorphosed individuals and as a result little is known about this life-history phase for most amphibians. Our focus was to explore survival probabilities, mark retention, and mark migration in postmetamorphic Boreal Chorus Frogs (</span><i>Psuedacris maculata</i><span>) in a laboratory setting. One hundred forty-seven individuals were assigned randomly to two treatment groups or a control group. Frogs in the first treatment group were marked with visual implant elastomer, while frogs in the second treatment group were toe clipped. Growth and mortality were recorded for one year and resulting data were analyzed using known-fate models in Program MARK. Model selection results suggested that survival probabilities of frogs varied with time and showed some variation among marking treatments. We found that frogs with multiple toes clipped on the same foot had lower survival probabilities than individuals in other treatments, but individuals can be marked by clipping a single toe on two different feet without any mark loss or negative survival effects. Individuals treated with visual implant elastomer had a mark migration rate of 4% and mark loss rate of 6%, and also showed very little negative survival impacts relative to control individuals.</span></p>","language":"English","publisher":"The American Society of Ichthyologists and Herpetologists","doi":"10.1643/CH-12-129","usgsCitation":"Swanson, J.E., Bailey, L., Muths, E.L., and Funk, W.C., 2013, Factors influencing survival and mark retention in postmetamorphic boreal chorus frogs: Copeia, v. 2013, no. 4, p. 670-675, https://doi.org/10.1643/CH-12-129.","productDescription":"6 p.","startPage":"670","endPage":"675","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045724","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":300866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2013","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5566eac7e4b0d9246a9ec2e1","contributors":{"authors":[{"text":"Swanson, Jennifer E.","contributorId":140894,"corporation":false,"usgs":false,"family":"Swanson","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":547478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L.","contributorId":93183,"corporation":false,"usgs":true,"family":"Bailey","given":"Larissa L.","affiliations":[],"preferred":false,"id":547477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":547476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, W. Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":97589,"corporation":false,"usgs":false,"family":"Funk","given":"W.","email":"","middleInitial":"Chris","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":547479,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193319,"text":"70193319 - 2013 - Effects of plant phenology and vertical height on accuracy of radio-telemetry locations","interactions":[],"lastModifiedDate":"2024-06-18T14:12:16.547785","indexId":"70193319","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3766,"text":"Wildlife Biology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of plant phenology and vertical height on accuracy of radio-telemetry locations","docAbstract":"<p><span>The use of very high frequency (VHF) radio-telemetry remains wide-spread in studies of wildlife ecology and management. However, few studies have evaluated the influence of vegetative obstruction on accuracy in differing habitats with varying transmitter types and heights. Using adult and fawn collars at varying heights above the ground (0, 33, 66 and 100 cm) to simulate activities (bedded, feeding and standing) and ages (neonate, juvenile and adult) of deer&nbsp;</span><i><i>Odocoileus</i></i><span><span>&nbsp;</span>spp., we collected 5,767 bearings and estimated 1,424 locations (28-30 for each of 48 subsamples) in three habitat types (pasture, grassland and forest), during two stages of vegetative growth (spring and late summer). Bearing error was approximately twice as large at a distance of 900 m for fawn (9.9°) than for adult deer collars (4.9°). Of 12 models developed to explain the variation in location error, the analysis of covariance model (HT*D + C*D + HT*TBA + C*TBA) containing interactions of height of collar above ground (HT), collar type (C), vertical height of understory vegetation (D) and tree basal area (TBA) was the best model (w</span><sub>i</sub><span><span>&nbsp;</span>= 0.92) and explained ∼ 71% of the variation in location error. Location error was greater for both collar types at 0 and 33 cm above the ground compared to 66 and 100 cm above the ground; however, location error was less for adult than fawn collars. Vegetation metrics influenced location error, which increased with greater vertical height of understory vegetation and tree basal area. Further, interaction of vegetation metrics and categorical variables indicated significant effects on location error. Our results indicate that researchers need to consider study objectives, life history of the study animal, signal strength of collar (collar type), distance from transmitter to receiver, topographical changes in elevation, habitat composition and season when designing telemetry protocols. Bearing distances in forested habitat should be decreased (approximately 23% in our study) compared to bearing distances in open habitat to maintain a consistent bearing error across habitats. Additionally, we believe that field biologists monitoring neonate ungulates for habitat selection should rely on visual locations rather than using VHF-collars and triangulation.</span></p>","language":"English","publisher":"Nordic Board for Wildlife Research","doi":"10.2981/11-044","usgsCitation":"Grovenburg, T.W., Jacques, C.N., Klaver, R.W., DePerno, C.S., Lehman, C.P., Brinkman, T.J., Robling, K.A., Rupp, S.P., and Jenks, J., 2013, Effects of plant phenology and vertical height on accuracy of radio-telemetry locations: Wildlife Biology, v. 19, no. 1, p. 30-40, https://doi.org/10.2981/11-044.","productDescription":"11 p.","startPage":"30","endPage":"40","ipdsId":"IP-029734","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473933,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/210","text":"External Repository"},{"id":348601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","county":"Edmunds County, Faulk County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.7096,45.5953],[-99.3464,45.5941],[-98.73,45.5911],[-98.7242,45.5905],[-98.7254,45.4963],[-98.7246,45.33],[-98.7249,45.2459],[-98.7184,45.2449],[-98.7209,45.1024],[-98.7186,44.8965],[-99.3132,44.8976],[-99.3287,44.8986],[-99.5728,44.8983],[-99.5743,45.0722],[-99.5719,45.1019],[-99.5751,45.2458],[-99.6962,45.2465],[-99.7111,45.2462],[-99.7096,45.5953]]]},\"properties\":{\"name\":\"Edmunds\",\"state\":\"SD\"}}]}","volume":"19","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8d6e4b09af898c8617d","contributors":{"authors":[{"text":"Grovenburg, Troy W.","contributorId":57712,"corporation":false,"usgs":true,"family":"Grovenburg","given":"Troy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":721662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacques, Christopher N.","contributorId":15521,"corporation":false,"usgs":true,"family":"Jacques","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":721663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":718687,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DePerno, Christopher S.","contributorId":10327,"corporation":false,"usgs":true,"family":"DePerno","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":721664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lehman, Chad P.","contributorId":200257,"corporation":false,"usgs":false,"family":"Lehman","given":"Chad","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":721665,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brinkman, Todd J.","contributorId":39696,"corporation":false,"usgs":true,"family":"Brinkman","given":"Todd","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721666,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robling, Kevin A.","contributorId":200258,"corporation":false,"usgs":false,"family":"Robling","given":"Kevin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":721667,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rupp, Susan P.","contributorId":200259,"corporation":false,"usgs":false,"family":"Rupp","given":"Susan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":721668,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jenks, Jonathan A.","contributorId":51591,"corporation":false,"usgs":true,"family":"Jenks","given":"Jonathan A.","affiliations":[],"preferred":false,"id":721669,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70044266,"text":"sir20125257 - 2013 - Arsenic concentrations, related environmental factors, and the predicted probability of elevated arsenic in groundwater in Pennsylvania","interactions":[],"lastModifiedDate":"2016-08-10T21:22:56","indexId":"sir20125257","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","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":"2012-5257","title":"Arsenic concentrations, related environmental factors, and the predicted probability of elevated arsenic in groundwater in Pennsylvania","docAbstract":"<p>Analytical results for arsenic in water samples from 5,023 wells obtained during 1969&ndash;2007 across Pennsylvania were compiled and related to other associated groundwater-quality and environmental factors and used to predict the probability of elevated arsenic concentrations, defined as greater than or equal to 4.0&nbsp;micrograms per liter (&micro;g/L), in groundwater. Arsenic concentrations of 4.0&nbsp;&micro;g/L or greater (elevated concentrations) were detected in 18 percent of samples across Pennsylvania; 8&nbsp;percent of samples had concentrations that equaled or exceeded the U.S. Environmental Protection Agency&rsquo;s drinking-water maximum contaminant level of 10.0&nbsp;&micro;g/L. The highest arsenic concentration was&nbsp;490.0&nbsp;&micro;g/L.</p>\n<p>Comparison of arsenic concentrations in Pennsylvania groundwater by physiographic province indicates that the Central Lowland physiographic province had the highest median arsenic concentration (4.5&nbsp;&micro;g/L) and the highest percentage of sample records with arsenic concentrations greater than or equal to 4.0&nbsp;&micro;g/L (59&nbsp;percent) and greater than or equal to 10.0&nbsp;&micro;g/L (43 percent). Evaluation of four major aquifer types (carbonate, crystalline, siliciclastic, and surficial) in Pennsylvania showed that all types had median arsenic concentrations less than 4.0&nbsp;&micro;g/L, and the highest arsenic concentration (490.0&nbsp;&micro;g/L) was in a siliciclastic aquifer. The siliciclastic and surficial aquifers had the highest percentage of sample records with arsenic concentrations greater than or equal to 4.0&nbsp;&micro;g/L and 10.0&nbsp;&micro;g/L. Elevated arsenic concentrations were associated with low pH (less than or equal to 4.0), high pH (greater than or equal to 8.0), or reducing conditions. For waters classified as anoxic (405 samples), 20&nbsp;percent of sampled wells contained water with elevated concentrations of arsenic; for waters classified as oxic (1,530&nbsp;samples) only 10 percent of sampled wells contained water with elevated arsenic concentrations. Nevertheless, regardless of the reduction-oxidation classification, 54&nbsp;percent of samples with low pH (13 of 24&nbsp;samples) and 25&nbsp;percent of samples with high pH (57 of 230&nbsp;samples) had elevated arsenic&nbsp;concentrations.</p>\n<p>Arsenic concentrations in groundwater in Pennsylvania were correlated with concentrations of several chemical constituents or properties, including (1) constituents associated with redox processes, (2) constituents that may have a similar origin or be mobilized under similar chemical conditions as arsenic, and (3) anions or oxyanions that have similar sorption behavior or compete for sorption sites on iron&nbsp;oxides.</p>\n<p>Logistic regression models were created to predict and map the probability of elevated arsenic concentrations in groundwater statewide in Pennsylvania and in three intrastate regions to further improve predictions for those three regions (glacial aquifer system, Gettysburg Basin, Newark Basin). Although the Pennsylvania and regional predictive models retained some different variables, they have common characteristics that can be grouped by (1) geologic and soils variables describing arsenic sources and mobilizers, (2) geochemical variables describing the geochemical environment of the groundwater, and (3) locally specific variables that are unique to each of the three regions studied and not applicable to statewide analysis. Maps of Pennsylvania and the three intrastate regions were produced that illustrate that areas most at risk are those with geology and soils capable of functioning as an arsenic source or mobilizer and geochemical groundwater conditions able to facilitate redox reactions. The models have limitations because they may not characterize areas that have localized controls on arsenic mobility. The probability maps associated with this report are intended for regional-scale use and may not be accurate for use at the field scale or when considering individual&nbsp;wells.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125257","collaboration":"Prepared in cooperation with the Pennsylvania Department of Health and the Pennsylvania Department of Environmental Protection","usgsCitation":"Gross, E.L., and Low, D.J., 2013, Arsenic concentrations, related environmental factors, and the predicted probability of elevated arsenic in groundwater in Pennsylvania: U.S. Geological Survey Scientific Investigations Report 2012-5257, viii, 48 p., https://doi.org/10.3133/sir20125257.","productDescription":"viii, 48 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":532,"text":"Pennsylvania Water Science 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,{"id":70156344,"text":"70156344 - 2013 - Tidally influenced alongshore circulation at an inlet-adjacent shoreline","interactions":[],"lastModifiedDate":"2015-08-20T13:09:15","indexId":"70156344","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Tidally influenced alongshore circulation at an inlet-adjacent shoreline","docAbstract":"<p>The contribution of tidal forcing to alongshore circulation inside the surfzone is investigated at a 7 km long sandy beach adjacent to a large tidal inlet. Ocean Beach in San Francisco, CA (USA) is onshore of a &sim;150 km2 ebb-tidal delta and directly south of the Golden Gate, the sole entrance to San Francisco Bay. Using a coupled flow-wave numerical model, we find that the tides modulate, and in some cases can reverse the direction of, surfzone alongshore flows through two separate mechanisms. First, tidal flow through the inlet results in a barotropic tidal pressure gradient that, when integrated across the surfzone, represents an important contribution to the surfzone alongshore force balance. Even during energetic wave conditions, the tidal pressure gradient can account for more than 30% of the total alongshore pressure gradient (wave and tidal components) and up to 55% during small waves. The wave driven component of the alongshore pressure gradient results from alongshore wave height and corresponding setup gradients induced by refraction over the ebb-tidal delta. Second, wave refraction patterns over the inner shelf are tidally modulated as a result of both tidal water depth changes and strong tidal flows (&sim;1 m/s), with the effect from currents being larger. These tidally induced changes in wave refraction result in corresponding variability of the alongshore radiation stress and pressure gradients within the surfzone. Our results indicate that tidal contributions to the surfzone force balance can be significant and important in determining the direction and magnitude of alongshore flow.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2013.01.017","usgsCitation":"Hansen, J., Elias, E.P., List, J.H., Erikson, L., and Barnard, P.L., 2013, Tidally influenced alongshore circulation at an inlet-adjacent shoreline: Continental Shelf Research, v. 56, p. 26-38, https://doi.org/10.1016/j.csr.2013.01.017.","productDescription":"13 p.","startPage":"26","endPage":"38","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032119","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438793,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DN4330","text":"USGS data release","linkHelpText":"San Francisco Bay Basic Tide Model"},{"id":307028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"San Francisco","otherGeospatial":"Ocean Beach","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.51953124999999,\n              37.729724141962045\n            ],\n            [\n              -122.51953124999999,\n              37.78781006166099\n            ],\n            [\n              -122.5037384033203,\n              37.78781006166099\n            ],\n            [\n              -122.5037384033203,\n              37.729724141962045\n            ],\n            [\n              -122.51953124999999,\n              37.729724141962045\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"56","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d6fa38e4b0518e3546bc5c","contributors":{"authors":[{"text":"Hansen, Jeff E.","contributorId":60339,"corporation":false,"usgs":true,"family":"Hansen","given":"Jeff E.","affiliations":[],"preferred":false,"id":568791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elias, Edwin P.L.","contributorId":47295,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","email":"","middleInitial":"P.L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":568790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"List, Jeffrey H. jlist@usgs.gov","contributorId":140039,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":568792,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erikson, Li H. lerikson@usgs.gov","contributorId":145944,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":568793,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":568794,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70157244,"text":"70157244 - 2013 - Tamarisk: Ecohydrology of a successful plant","interactions":[],"lastModifiedDate":"2025-12-31T16:48:33.87161","indexId":"70157244","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Tamarisk: Ecohydrology of a successful plant","docAbstract":"<p><span>This chapter explores the ecohydrology of tamarisk, with particular emphasis on water use, salt tolerance, potential for salinizing flood plains, drought tolerance and rooting depths, and ecological interactions with native plants on western rivers. It presents the working hypothesis that tamarisk is adapted to water stress, with low to moderate water use that tends to replace mesic vegetation when conditions on flow-regulated rivers become unsuitable for those species, rather than as an invasive species that displaces and out-competes native species under all conditions. It includes data on the annualized rates of evapotranspiration, transpiration, and stomatal conductance by tamarisk stands on western US rivers. It also cites the lack of evidence that simply removing tamarisk from a riverbank will improve salinity or allow native mesic vegetation to return.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tamarix: A case study of ecological change in the American West","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Oxford University Press","publisherLocation":"New York, NY","doi":"10.1093/acprof:osobl/9780199898206.003.0005","usgsCitation":"Nagler, P.L., and Quigley, M.F., 2013, Tamarisk: Ecohydrology of a successful plant, chap. <i>of</i> Tamarix: A case study of ecological change in the American West, p. 63-84, https://doi.org/10.1093/acprof:osobl/9780199898206.003.0005.","productDescription":"22 p.","startPage":"63","endPage":"84","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026847","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":308133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55f94142e4b05d6c4e5013ad","contributors":{"editors":[{"text":"Sher, Anna","contributorId":112677,"corporation":false,"usgs":true,"family":"Sher","given":"Anna","affiliations":[],"preferred":false,"id":953196,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Quigley, Martin F.","contributorId":112538,"corporation":false,"usgs":true,"family":"Quigley","given":"Martin","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":953197,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":572389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quigley, Martin F.","contributorId":112538,"corporation":false,"usgs":true,"family":"Quigley","given":"Martin","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":572390,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191526,"text":"70191526 - 2013 - Implications of the Mw9.0 Tohoku-Oki earthquake for ground motion scaling with source, path, and site parameters","interactions":[],"lastModifiedDate":"2017-10-17T11:44:12","indexId":"70191526","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Implications of the M<sub>w</sub>9.0 Tohoku-Oki earthquake for ground motion scaling with source, path, and site parameters","title":"Implications of the Mw9.0 Tohoku-Oki earthquake for ground motion scaling with source, path, and site parameters","docAbstract":"<p><span>The M</span><sub>w</sub><span>9.0 Tohoku-oki Japan earthquake produced approximately 2,000 ground motion recordings. We consider 1,238 three-component accelerograms corrected with component-specific low-cut filters. The recordings have rupture distances between 44 km and 1,000 km, time-averaged shear wave velocities of<span>&nbsp;</span></span><i>V<sub>S</sub></i><sub>30</sub><span><span>&nbsp;</span>= 90 m/s to 1,900 m/s, and usable response spectral periods of 0.01 sec to &gt;10 sec. The data support the notion that the increase of ground motions with magnitude saturates at large magnitudes. High-frequency ground motions demonstrate faster attenuation with distance in backarc than in forearc regions, which is only captured by one of the four considered ground motion prediction equations for subduction earthquakes. Recordings within 100 km of the fault are used to estimate event terms, which are generally positive (indicating model underprediction) at short periods and zero or negative (overprediction) at long periods. We find site amplification to scale minimally with<span>&nbsp;</span></span><i>V<sub>S</sub></i><sub>30</sub><span><span>&nbsp;</span>at high frequencies, in contrast with other active tectonic regions, but to scale strongly with<span>&nbsp;</span></span><i>V<sub>S</sub></i><sub>30</sub><span><span>&nbsp;</span>at low frequencies.</span></p>","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/1.4000115","usgsCitation":"Stewart, J.P., Midorikawa, S., Graves, R.W., Khodaverdi, K., Kishida, T., Miura, H., Bozorgnia, Y., and Campbell, K.W., 2013, Implications of the Mw9.0 Tohoku-Oki earthquake for ground motion scaling with source, path, and site parameters: Earthquake Spectra, v. 29, no. S1, p. S1-S21, https://doi.org/10.1193/1.4000115.","productDescription":"21 p.","startPage":"S1","endPage":"S21","ipdsId":"IP-042067","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":346689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"S1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-03-01","publicationStatus":"PW","scienceBaseUri":"59e71695e4b05fe04cd331f2","contributors":{"authors":[{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":712796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Midorikawa, Saburoh","contributorId":197120,"corporation":false,"usgs":false,"family":"Midorikawa","given":"Saburoh","email":"","affiliations":[],"preferred":false,"id":712797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Robert W. rwgraves@usgs.gov","contributorId":3149,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","middleInitial":"W.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":712798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Khodaverdi, Khatareh","contributorId":197119,"corporation":false,"usgs":false,"family":"Khodaverdi","given":"Khatareh","email":"","affiliations":[],"preferred":false,"id":712799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kishida, Tadahiro","contributorId":140538,"corporation":false,"usgs":false,"family":"Kishida","given":"Tadahiro","email":"","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":712800,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miura, Hiroyuki","contributorId":197118,"corporation":false,"usgs":false,"family":"Miura","given":"Hiroyuki","email":"","affiliations":[],"preferred":false,"id":712801,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bozorgnia, Yousef","contributorId":197121,"corporation":false,"usgs":false,"family":"Bozorgnia","given":"Yousef","email":"","affiliations":[],"preferred":false,"id":712802,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Campbell, Kenneth W.","contributorId":74391,"corporation":false,"usgs":false,"family":"Campbell","given":"Kenneth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":712803,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70169310,"text":"70169310 - 2013 - Predicted effect of landscape position on wildlife habitat value of Conservation Reserve Enhancement Program wetlands in a tile-drained agricultural region","interactions":[],"lastModifiedDate":"2016-03-24T10:03:05","indexId":"70169310","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Predicted effect of landscape position on wildlife habitat value of Conservation Reserve Enhancement Program wetlands in a tile-drained agricultural region","docAbstract":"<p>Justification for investment in restored or constructed wetland projects are often based on presumed net increases in ecosystem services. However, quantitative assessment of performance metrics is often difficult and restricted to a single objective. More comprehensive performance assessments could help inform decision-makers about trade-offs in services provided by alternative restoration program design attributes. The primary goal of the Iowa Conservation Reserve Enhancement Program is to establish wetlands that efficiently remove nitrates from tile-drained agricultural landscapes. A secondary objective is provision of wildlife habitat. We used existing wildlife habitat models to compare relative net change in potential wildlife habitat value for four alternative landscape positions of wetlands within the watershed. Predicted species richness and habitat value for birds, mammals, amphibians, and reptiles generally increased as the wetland position moved lower in the watershed. However, predicted average net increase between pre- and post-project value was dependent on taxonomic group. The increased average wetland area and changes in surrounding upland habitat composition among landscape positions were responsible for these differences. Net change in predicted densities of several grassland bird species at the four landscape positions was variable and species-dependent. Predicted waterfowl breeding activity was greater for lower drainage position wetlands. Although our models are simplistic and provide only a predictive index of potential habitat value, we believe such assessment exercises can provide a tool for coarse-level comparisons of alternative proposed project attributes and a basis for constructing informed hypotheses in auxiliary empirical field studies.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1526-100X.2012.00898.x","usgsCitation":"Otis, D.L., Crumpton, W.R., Green, D., Loan-Wilsey, A., Cooper, T., and Johnson, R.R., 2013, Predicted effect of landscape position on wildlife habitat value of Conservation Reserve Enhancement Program wetlands in a tile-drained agricultural region: Restoration Ecology, v. 21, no. 2, p. 276-284, https://doi.org/10.1111/j.1526-100X.2012.00898.x.","productDescription":"9 p.","startPage":"276","endPage":"284","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-029128","costCenters":[{"id":199,"text":"Coop Res Unit 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,{"id":70154883,"text":"70154883 - 2013 - Evaluating  methodological assumptions of a catch-curve survival estimation of unmarked precocial shorebird chickes","interactions":[],"lastModifiedDate":"2015-07-15T14:06:15","indexId":"70154883","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating  methodological assumptions of a catch-curve survival estimation of unmarked precocial shorebird chickes","docAbstract":"<p><span>Estimating productivity for precocial species can be difficult because young birds leave their nest within hours or days of hatching and detectability thereafter can be very low. Recently, a method for using a modified catch-curve to estimate precocial chick daily survival for age based count data was presented using Piping Plover (</span><i>Charadrius melodus</i><span>) data from the Missouri River. However, many of the assumptions of the catch-curve approach were not fully evaluated for precocial chicks. We developed a simulation model to mimic Piping Plovers, a fairly representative shorebird, and age-based count-data collection. Using the simulated data, we calculated daily survival estimates and compared them with the known daily survival rates from the simulation model. We conducted these comparisons under different sampling scenarios where the ecological and statistical assumptions had been violated. Overall, the daily survival estimates calculated from the simulated data corresponded well with true survival rates of the simulation. Violating the accurate aging and the independence assumptions did not result in biased daily survival estimates, whereas unequal detection for younger or older birds and violating the birth death equilibrium did result in estimator bias. Assuring that all ages are equally detectable and timing data collection to approximately meet the birth death equilibrium are key to the successful use of this method for precocial shorebirds.</span></p>","language":"English","publisher":"Waterbird Society","doi":"10.1675/063.036.0112","usgsCitation":"McGowan, C., and Gardner, B., 2013, Evaluating  methodological assumptions of a catch-curve survival estimation of unmarked precocial shorebird chickes: Waterbirds, v. 36, no. 1, p. 82-87, https://doi.org/10.1675/063.036.0112.","productDescription":"6 p.","startPage":"82","endPage":"87","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038383","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473938,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.036.0112","text":"Publisher Index Page"},{"id":305766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55a78436e4b0183d66e45e88","contributors":{"authors":[{"text":"McGowan, Conor P. cmcgowan@usgs.gov","contributorId":145496,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":564875,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193570,"text":"70193570 - 2013 - Faulting within the Mount St. Helens conduit and implications for volcanic earthquakes","interactions":[],"lastModifiedDate":"2017-11-02T10:44:27","indexId":"70193570","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Faulting within the Mount St. Helens conduit and implications for volcanic earthquakes","docAbstract":"<p id=\"p-1\">The 2004–2008 eruption of Mount St. Helens produced seven dacite spines mantled by cataclastic fault rocks, comprising an outer fault core and an inner damage zone. These fault rocks provide remarkable insights into the mechanical processes that accompany extrusion of degassed magma, insights that are useful in forecasting dome-forming eruptions. The outermost part of the fault core consists of finely comminuted fault gouge that is host to 1- to 3-mm-thick layers of extremely fine-grained slickenside-bearing ultracataclasite. Interior to the fault core, there is an ∼2-m-thick damage zone composed of cataclastic breccia and sheared dacite, and interior to the damage zone, there is massive to flow-banded dacite lava of the spine interior. Structures and microtextures indicate entirely brittle deformation, including rock breakage, tensional dilation, shearing, grain flow, and microfaulting, as well as gas and fluid migration through intergranular pores and fractures in the damage zone. Slickenside lineations and consistent orientations of Riedel shears indicate upward shear of the extruding spines against adjacent conduit wall rocks.</p><p id=\"p-2\">Paleomagnetic directions, demagnetization paths, oxide mineralogy, and petrology indicate that cataclasis took place within dacite in a solidified steeply dipping volcanic conduit at temperatures above 500 °C. Low water content of matrix glass is consistent with brittle behavior at these relatively high temperatures, and the presence of tridymite indicates solidification depths of &lt;1 km. Cataclasis was coincident with the eruption’s seismogenic zone at &lt;1.5 km.</p><p id=\"p-3\">More than a million small and low-frequency “drumbeat” earthquakes with coda magnitudes (M<sub>d</sub>) &lt;2.0 and frequencies &lt;5 Hz occurred during the 2004–2008 eruption. Our field data provide a means with which to estimate slip-patch dimensions for shear planes and to compare these with estimates of slip patches based on seismic moments and shear moduli for dacite rock and granular fault gouge. Based on these comparisons, we find that aseismic creep is achieved by micron-scale displacements on Riedel shears and by granular flow, whereas the drumbeat earthquakes require millimeter to centimeter displacements on relatively large (e.g., ∼1000 m<sup>2</sup>) slip patches, possibly along observed extensive principal shear zones within the fault core but probably not along the smaller Riedel shears. Although our field and structural data are compatible with stick-slip models, they do not rule out seismic and infrasound models that call on resonance of steam-filled fractures to generate the drumbeat earthquakes. We suggest that stick-slip and gas release processes may be coupled, and that regardless of the source mechanism, the distinctive drumbeat earthquakes are proving to be an effective precursor for dome-forming eruptions.</p><p id=\"p-4\">Our data document a continuous cycle of deformation along the conduit margins beginning with episodes of fracture in the damage zone and followed by transfer of motion to the fault core. We illustrate the cycle of deformation using a hypothetical cross section of the Mount St. Helens conduit, extending from the surface to the depth of magmatic solidification.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B30716.1","usgsCitation":"Pallister, J.S., Cashman, K.V., Hagstrum, J.T., Beeler, N.M., Moran, S.C., and Denlinger, R.P., 2013, Faulting within the Mount St. Helens conduit and implications for volcanic earthquakes: GSA Bulletin, v. 125, no. 3-4, p. 359-376, https://doi.org/10.1130/B30716.1.","productDescription":"18 p.","startPage":"359","endPage":"376","ipdsId":"IP-037093","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","volume":"125","issue":"3-4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-11-21","publicationStatus":"PW","scienceBaseUri":"59fc2eade4b0531197b27fe0","contributors":{"authors":[{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":719391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Katharine V.","contributorId":199542,"corporation":false,"usgs":false,"family":"Cashman","given":"Katharine","email":"","middleInitial":"V.","affiliations":[{"id":13025,"text":"Department of Geological Sciences, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":719394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagstrum, Jonathan T. 0000-0002-0689-280X jhag@usgs.gov","orcid":"https://orcid.org/0000-0002-0689-280X","contributorId":3474,"corporation":false,"usgs":true,"family":"Hagstrum","given":"Jonathan","email":"jhag@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":719390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beeler, Nicholas M. 0000-0002-3397-8481 nbeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-3397-8481","contributorId":2682,"corporation":false,"usgs":true,"family":"Beeler","given":"Nicholas","email":"nbeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":719392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":719395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":719393,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70043581,"text":"70043581 - 2013 - Prolactin regulates transcription of the ion uptake Na+/Cl- cotransporter (ncc) gene in zebrafish gill","interactions":[],"lastModifiedDate":"2013-03-11T21:21:18","indexId":"70043581","displayToPublicDate":"2013-02-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2782,"text":"Molecular and Cellular Endocrinology","active":true,"publicationSubtype":{"id":10}},"title":"Prolactin regulates transcription of the ion uptake Na+/Cl- cotransporter (ncc) gene in zebrafish gill","docAbstract":"Prolactin (PRL) is a well-known regulator of ion and water transport within osmoregulatory tissues across vertebrate species, yet how PRL acts on some of its target tissues remains poorly understood. Using zebrafish as a model, we show that ionocytes in the gill directly respond to systemic PRL to regulate mechanisms of ion uptake. Ion-poor conditions led to increases in the expression of PRL receptor (prlra), Na+/Cl− cotransporter (ncc; slc12a10.2), Na+/H+ exchanger (nhe3b; slc9a3.2), and epithelial Ca2+ channel (ecac; trpv6) transcripts within the gill. Intraperitoneal injection of ovine PRL (oPRL) increased ncc and prlra transcripts, but did not affect nhe3b or ecac. Consistent with direct PRL action in the gill, addition of oPRL to cultured gill filaments stimulated ncc in a concentration-dependent manner, an effect blocked by a pure human PRL receptor antagonist (Δ1-9-G129R-hPRL). These results suggest that PRL signaling through PRL receptors in the gill regulates the expression of ncc, thereby linking this pituitary hormone with an effector of Cl− uptake in zebrafish for the first time.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Molecular and Cellular Endocrinology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.mce.2013.01.021","usgsCitation":"Breves, J.P., Serizier, S.B., Goffin, V., McCormick, S., and Karlstrom, R.O., 2013, Prolactin regulates transcription of the ion uptake Na+/Cl- cotransporter (ncc) gene in zebrafish gill: Molecular and Cellular Endocrinology, In Press, Corrected Proof, https://doi.org/10.1016/j.mce.2013.01.021.","productDescription":"In Press, Corrected Proof","ipdsId":"IP-042950","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":473940,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3664226","text":"External Repository"},{"id":269099,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.mce.2013.01.021"},{"id":269100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"513efcf9e4b0dcc7339693bf","contributors":{"authors":[{"text":"Breves, Jason P.","contributorId":6349,"corporation":false,"usgs":false,"family":"Breves","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":473887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Serizier, Sandy B.","contributorId":26597,"corporation":false,"usgs":true,"family":"Serizier","given":"Sandy","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":473889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goffin, Vincent","contributorId":25056,"corporation":false,"usgs":true,"family":"Goffin","given":"Vincent","email":"","affiliations":[],"preferred":false,"id":473888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":39666,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen D.","email":"smccormick@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":473890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karlstrom, Rolf O.","contributorId":42502,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Rolf","email":"","middleInitial":"O.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":473891,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70202065,"text":"70202065 - 2013 - U-Pb ages of detrital zircons from the Tertiary Mississippi River delta plain in central Louisiana:  Insights into sediment provenance","interactions":[],"lastModifiedDate":"2019-02-08T15:17:24","indexId":"70202065","displayToPublicDate":"2013-02-27T13:52:48","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"U-Pb ages of detrital zircons from the Tertiary Mississippi River delta plain in central Louisiana:  Insights into sediment provenance","docAbstract":"<p>The sources of the tremendous amount of Cenozoic siliciclastic sediment deposited in the Gulf of Mexico region remain debated because of a lack of definitive provenance-identifying characteristics. In an effort to build on prior provenance analysis, we present 101–160 single-grain detrital zircon U-Pb ages for each of 10 outcrop samples from Upper Paleocene to Upper Miocene sandstones from a ∼10,000 km2 swath of central Louisiana corresponding to the ancient Mississippi River Delta, the largest Cenozoic depocenter in the northern Gulf of Mexico region. Sample depositional age control is derived from biostratigraphy and/or regional lithostratigraphic correlation. U-Pb ages in each of the samples range from Cenozoic to Archean, and correspond to the ages of various geologic terranes that underlie the modern Mississippi River drainage basin. However, the prominence of various age distributions changes systematically through the Cenozoic stratigraphy, and pronounced shifts in the abundance of certain age distributions between stratal packages appear to be correlated to shifts in heavy mineral assemblages recorded across the northern Gulf of Mexico coastal plain. Comparison of coastal plain detrital zircon age distributions to age distributions from North American sedimentary cover and the ages of major North American crystalline basement rocks, aided by a sediment mixing model, illuminates the provenance of each of the stratal packages, and suggests that (1) the Mississippi River catchment has resembled its present configuration, at least in the east-west dimension, for much, if not all, of the Cenozoic, and (2) depositional episodes on the Louisiana coastal plain characterized by high sediment supply also corresponded to high proportions of sediment sourcing from the Sevier-Laramide region of the interior western United States. Sediment supply to the Louisiana coastal plain by the paleo–Mississippi River has generally been high during the Cenozoic, except for an anomalous low during the Middle Eocene, when the abundance of sediment derived from the Rocky Mountain region decreased dramatically relative to sediment derived from the Appalachian region.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES00917.1","usgsCitation":"Craddock, W.H., and Kylander-Clark, A.R., 2013, U-Pb ages of detrital zircons from the Tertiary Mississippi River delta plain in central Louisiana:  Insights into sediment provenance: Geosphere, v. 9, no. 6, p. 1832-1851, https://doi.org/10.1130/GES00917.1.","productDescription":"20 p.","startPage":"1832","endPage":"1851","ipdsId":"IP-044256","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":473942,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00917.1","text":"Publisher Index Page"},{"id":361097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River Delta ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.966667,\n              29.516667\n            ],\n            [\n              -89.966667,\n              29.408333\n            ],\n            [\n              -89.816667,\n              29.408333\n            ],\n            [\n              -89.816667,\n              29.516667\n            ],\n            [\n              -89.966667,\n              29.516667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-11-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":756813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kylander-Clark, Andrew R. C.","contributorId":212897,"corporation":false,"usgs":false,"family":"Kylander-Clark","given":"Andrew","email":"","middleInitial":"R. C.","affiliations":[],"preferred":false,"id":756814,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70044170,"text":"ds709R - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-02-27T16:10:20","indexId":"ds709R","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"R","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Dudkash) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Dudkash area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709R","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey; This report is Chapter R in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i> (DS 709-R)","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps; 16 Image Files; 16 Metadata Files; 1 Shapefile, https://doi.org/10.3133/ds709R.","productDescription":"HTML Document; Readme; 4 Index Maps; 16 Image Files; 16 Metadata Files; 1 Shapefile","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":268489,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/r/1_readme.txt"},{"id":268490,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/r/index_maps/index_maps.html"},{"id":268491,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/r/image_files/image_files.html"},{"id":268492,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/r/metadata/metadata.html"},{"id":268493,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/r/shapefiles/shapefiles.html"},{"id":268488,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/r/"},{"id":268494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_R.png"}],"country":"Afghanistan","otherGeospatial":"Dudkash Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 58.0,29.0 ], [ 58.0,40.0 ], [ 77.0,40.0 ], [ 77.0,29.0 ], [ 58.0,29.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f2afbe4b0cad81a732d7b","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":474970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":474971,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70044136,"text":"70044136 - 2013 - Applications of spectral band adjustment factors (SBAF) for cross-calibration","interactions":[],"lastModifiedDate":"2013-02-27T17:44:54","indexId":"70044136","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Applications of spectral band adjustment factors (SBAF) for cross-calibration","docAbstract":"To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earth's surface acquired from multiple spaceborne imaging sensors. However, an integrated global observation framework requires an understanding of how land surface processes are seen differently by various sensors. This is particularly true for sensors acquiring data in spectral bands whose relative spectral responses (RSRs) are not similar and thus may produce different results while observing the same target. The intrinsic offsets between two sensors caused by RSR mismatches can be compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of the two sensors. The motivation of this work comes from the need to compensate the spectral response differences of multispectral sensors in order to provide a more accurate cross-calibration between the sensors. In this paper, radiometric cross-calibration of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors was performed using near-simultaneous observations over the Libya 4 pseudoinvariant calibration site in the visible and near-infrared spectral range. The RSR differences of the analogous ETM+ and MODIS spectral bands provide the opportunity to explore, understand, quantify, and compensate for the measurement differences between these two sensors. The cross-calibration was initially performed by comparing the top-of-atmosphere (TOA) reflectances between the two sensors over their lifetimes. The average percent differences in the long-term trends ranged from $-$5% to $+$6%. The RSR compensated ETM+ TOA reflectance (ETM+$^{ast}$) measurements were then found to agree with MODIS TOA reflectance to within 5% for all bands when Earth Observing-1 Hy- erion hyperspectral data were used to produce the SBAFs. These differences were later reduced to within 1% for all bands (except band 2) by using Environmental Satellite Scanning Imaging Absorption Spectrometer for Atmospheric Cartography hyperspectral data to produce the SBAFs.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2012.2228007","usgsCitation":"Chander, G., 2013, Applications of spectral band adjustment factors (SBAF) for cross-calibration: IEEE Transactions on Geoscience and Remote Sensing, v. 51, no. 3, p. 1267-1281, https://doi.org/10.1109/TGRS.2012.2228007.","productDescription":"15 p.","startPage":"1267","endPage":"1281","ipdsId":"IP-037261","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268516,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2012.2228007"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f2adfe4b0cad81a732d73","contributors":{"authors":[{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":474863,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70044146,"text":"70044146 - 2013 - Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study","interactions":[],"lastModifiedDate":"2017-05-10T15:48:47","indexId":"70044146","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study","docAbstract":"Cross-calibration of satellite sensors permits the quantitative comparison of measurements obtained from different Earth Observing (EO) systems. Cross-calibration studies usually use simultaneous or near-simultaneous observations from several spaceborne sensors to develop band-by-band relationships through regression analysis. The investigation described in this paper focuses on evaluation of the uncertainties inherent in the cross-calibration process, including contributions due to different spectral responses, spectral resolution, spectral filter shift, geometric misregistrations, and spatial resolutions. The hyperspectral data from the Environmental Satellite SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY and the EO-1 Hyperion, along with the relative spectral responses (RSRs) from the Landsat 7 Enhanced Thematic Mapper (TM) Plus and the Terra Moderate Resolution Imaging Spectroradiometer sensors, were used for the spectral uncertainty study. The data from Landsat 5 TM over five representative land cover types (desert, rangeland, grassland, deciduous forest, and coniferous forest) were used for the geometric misregistrations and spatial-resolution study. The spectral resolution uncertainty was found to be within 0.25%, spectral filter shift within 2.5%, geometric misregistrations within 0.35%, and spatial-resolution effects within 0.1% for the Libya 4 site. The one-sigma uncertainties presented in this paper are uncorrelated, and therefore, the uncertainties can be summed orthogonally. Furthermore, an overall total uncertainty was developed. In general, the results suggested that the spectral uncertainty is more dominant compared to other uncertainties presented in this paper. Therefore, the effect of the sensor RSR differences needs to be quantified and compensated to avoid large uncertainties in cross-calibration results.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2012.2228008","usgsCitation":"Chander, G., Helder, D., Aaron, D., Mishra, N., and Shrestha, A., 2013, Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study: IEEE Transactions on Geoscience and Remote Sensing, v. 51, no. 3, p. 1282-1296, https://doi.org/10.1109/TGRS.2012.2228008.","productDescription":"15 p.","startPage":"1282","endPage":"1296","ipdsId":"IP-039167","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268519,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f2af9e4b0cad81a732d77","contributors":{"authors":[{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":474896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helder, D. L. 0000-0002-7379-4679","orcid":"https://orcid.org/0000-0002-7379-4679","contributorId":51496,"corporation":false,"usgs":true,"family":"Helder","given":"D. L.","affiliations":[],"preferred":false,"id":474897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aaron, David","contributorId":83809,"corporation":false,"usgs":false,"family":"Aaron","given":"David","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":474899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mishra, N.","contributorId":67379,"corporation":false,"usgs":true,"family":"Mishra","given":"N.","email":"","affiliations":[],"preferred":false,"id":474898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shrestha, A.K.","contributorId":104783,"corporation":false,"usgs":true,"family":"Shrestha","given":"A.K.","email":"","affiliations":[],"preferred":false,"id":474900,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044171,"text":"ds709S - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-02-27T16:24:33","indexId":"ds709S","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"S","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Kunduz) and the WGS84 datum. The final image mosaics were subdivided into five overlapping tiles or quadrants because of the large size of the target area. The five image tiles (or quadrants) for the Kunduz area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709-S)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709S","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey; Chapter S in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>: U.S. Geological Survey Data Series 709, HTML Document; Readme; 4 Index Maps; 16 Image Files; 16 Metadata Files; 1 Shapefile, https://doi.org/10.3133/ds709S.","productDescription":"HTML Document; Readme; 4 Index Maps; 16 Image Files; 16 Metadata Files; 1 Shapefile","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":268501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_S.png"},{"id":268498,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/s/image_files/image_files.html"},{"id":268499,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/s/metadata/metadata.html"},{"id":268500,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/s/shapefiles/shapefiles.html"},{"id":268495,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/s/"},{"id":268496,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/s/1_readme.txt"},{"id":268497,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/s/index_maps/index_maps.html"}],"country":"Afghanistan","otherGeospatial":"Kunduz Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 58.0,29.0 ], [ 58.0,40.0 ], [ 77.0,40.0 ], [ 77.0,29.0 ], [ 58.0,29.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f2afde4b0cad81a732d7f","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":474973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":474974,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70044294,"text":"sir20135016 - 2013 - Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon","interactions":[],"lastModifiedDate":"2013-03-01T14:08:40","indexId":"sir20135016","displayToPublicDate":"2013-02-27T00:00:00","publicationYear":"2013","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":"2013-5016","title":"Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon","docAbstract":"A hydrodynamic, water temperature, and water-quality model of the Link River to Keno Dam reach of the upper Klamath River was updated to account for macrophytes and enhanced pH buffering from dissolved organic matter, ammonia, and orthophosphorus. Macrophytes had been observed in this reach by field personnel, so macrophyte field data were collected in summer and fall (June-October) 2011 to provide a dataset to guide the inclusion of macrophytes in the model. Three types of macrophytes were most common: pondweed (Potamogeton species), coontail (Ceratophyllum demersum), and common waterweed (Elodea canadensis). Pondweed was found throughout the Link River to Keno Dam reach in early summer with densities declining by mid-summer and fall. Coontail and common waterweed were more common in the lower reach near Keno Dam and were at highest density in summer. All species were most dense in shallow water (less than 2 meters deep) near shore. The highest estimated dry weight biomass for any sample during the study was 202 grams per square meter for coontail in August. Guided by field results, three macrophyte groups were incorporated into the CE-QUAL-W2 model for calendar years 2006-09. The CE-QUAL-W2 model code was adjusted to allow the user to initialize macrophyte populations spatially across the model grid. The default CE-QUAL-W2 model includes pH buffering by carbonates, but does not include pH buffering by organic matter, ammonia, or orthophosphorus. These three constituents, especially dissolved organic matter, are present in the upper Klamath River at concentrations that provide substantial pH buffering capacity. In this study, CE-QUAL-W2 was updated to include this enhanced buffering capacity in the simulation of pH. Acid dissociation constants for ammonium and phosphoric acid were taken from the literature. For dissolved organic matter, the number of organic acid groups and each group's acid dissociation constant (K<sub>a</sub>) and site density (moles of sites per mole of carbon) were derived by fitting a theoretical buffering response to measured upper Klamath River alkalinity titration curves. The organic matter buffering in the Klamath River was modeled with two monoprotic organic acids: carboxylic acids with a mean pK<sub>a</sub> of 5.584 and site density of 0.1925, and phenolic organic acids with a mean pK<sub>a</sub> of 9.594 and site density of 0.6466. Total inorganic carbon concentrations in the model boundary inputs were recalculated based on the new buffering equations. CE-QUAL-W2 was also adjusted to allow the simulation of nonconservative alkalinity caused by nitrification, denitrification, photosynthesis, and respiration. The Klamath River model was recalibrated after the macrophyte and pH buffering updates producing improved predictions for pH, dissolved oxygen, and particulate carbon.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135016","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., Rounds, S.A., Asbill-Case, J.R., and Deas, M., 2013, Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon: U.S. Geological Survey Scientific Investigations Report 2013-5016, viii, 54 p., https://doi.org/10.3133/sir20135016.","productDescription":"viii, 54 p.","numberOfPages":"64","onlineOnly":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":268629,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5016/pdf/sir20135016.pdf"},{"id":268628,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5016/index.html"},{"id":268630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2013_5016.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 122,42.03 ], [ 122,42.33 ], [ 121.75,42.33 ], [ 121.75,42.03 ], [ 122,42.03 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5131dc02e4b0140546f53bf9","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":56317,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett","email":"annett@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":475250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asbill-Case, Jessica R.","contributorId":32058,"corporation":false,"usgs":true,"family":"Asbill-Case","given":"Jessica","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":475249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deas, Michael L.","contributorId":98830,"corporation":false,"usgs":true,"family":"Deas","given":"Michael L.","affiliations":[],"preferred":false,"id":475251,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043719,"text":"70043719 - 2013 - A comprehensive change detection method for updating the National Land Cover Database to circa 2011","interactions":[],"lastModifiedDate":"2013-02-26T12:57:26","indexId":"70043719","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A comprehensive change detection method for updating the National Land Cover Database to circa 2011","docAbstract":"The importance of characterizing, quantifying, and monitoring land cover, land use, and their changes has been widely recognized by global and environmental change studies. Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on different landscapes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2013.01.012","usgsCitation":"Jin, S., Yang, L., Danielson, P., Homer, C.G., Fry, J., and Xian, G., 2013, A comprehensive change detection method for updating the National Land Cover Database to circa 2011: Remote Sensing of Environment, v. 132, p. 159-175, https://doi.org/10.1016/j.rse.2013.01.012.","productDescription":"17 p.","startPage":"159","endPage":"175","ipdsId":"IP-041925","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268380,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2013.01.012"}],"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":"132","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd49a9e4b0b290850ef516","chorus":{"doi":"10.1016/j.rse.2013.01.012","url":"http://dx.doi.org/10.1016/j.rse.2013.01.012","publisher":"Elsevier BV","authors":"Jin Suming, Yang Limin, Danielson Patrick, Homer Collin, Fry Joyce, Xian George","journalName":"Remote Sensing of Environment","publicationDate":"5/2013","auditedOn":"4/22/2016"},"contributors":{"authors":[{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":474161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474160,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Patrick 0000-0002-2990-2783 pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":474157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fry, Joyce 0000-0002-8466-9582 jfry@usgs.gov","orcid":"https://orcid.org/0000-0002-8466-9582","contributorId":3147,"corporation":false,"usgs":true,"family":"Fry","given":"Joyce","email":"jfry@usgs.gov","affiliations":[],"preferred":true,"id":474158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xian, George 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":76589,"corporation":false,"usgs":true,"family":"Xian","given":"George","affiliations":[],"preferred":false,"id":474162,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70044029,"text":"70044029 - 2013 - Anaerobic methane oxidation in low-organic content methane seep sediments","interactions":[],"lastModifiedDate":"2013-04-04T13:58:02","indexId":"70044029","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Anaerobic methane oxidation in low-organic content methane seep sediments","docAbstract":"Sulfate-dependent anaerobic oxidation of methane (AOM) is the key sedimentary microbial process limiting methane emissions from marine sediments and methane seeps. In this study, we investigate how the presence of low-organic content sediment influences the capacity and efficiency of AOM at Bullseye vent, a gas hydrate-bearing cold seep offshore of Vancouver Island, Canada. The upper 8 m of sediment contains < 0.4 wt% total organic carbon (OC) and primarily consists of glacially-derived material that was deposited 14,900 to 15,900 yrs BP during the retreat of the late Quaternary Cordilleran Ice Sheet. We hypothesize this aged and exceptionally low-OC content sedimentary OM is biologically refractory, thereby limiting degradation of non-methane OM by sulfate reduction and maximizing methane consumption by sulfate-dependent AOM. A radiocarbon-based dissolved inorganic carbon (DIC) isotope mass balance model demonstrates that respired DIC in sediment pore fluids is derived from a fossil carbon source that is devoid of <sup>14</sup>C. A fossil origin for the DIC precludes remineralization of non-fossil OM present within the sulfate zone as a significant contributor to pore water DIC, suggesting that nearly all sulfate is available for anaerobic oxidation of fossil seep methane. Methane flux from the SMT to the sediment water interface in a diffusion-dominated flux region of Bullseye vent was, on average, 96% less than at an OM-rich seep in the Gulf of Mexico with a similar methane flux regime. Evidence for enhanced methane oxidation capacity within OM-poor sediments has implications for assessing how climate-sensitive reservoirs of sedimentary methane (e.g., gas hydrate) will respond to ocean warming, particularly along glacially-influenced mid and high latitude continental margins.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochimica et Cosmochimica Acta","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.gca.2013.01.022","usgsCitation":"Pohlman, J., Riedel, M., Bauer, J., Canuel, E.A., Paull, C.K., Lapham, L., Grabowski, K.S., Coffin, R., and Spence, G.D., 2013, Anaerobic methane oxidation in low-organic content methane seep sediments: Geochimica et Cosmochimica Acta, v. 108, p. 184-201, https://doi.org/10.1016/j.gca.2013.01.022.","productDescription":"18 p.","startPage":"184","endPage":"201","ipdsId":"IP-042835","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473944,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/5947","text":"External Repository"},{"id":268294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268292,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.gca.2013.01.022"}],"volume":"108","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515ea0e5e4b088aa22580949","contributors":{"authors":[{"text":"Pohlman, John W.","contributorId":95288,"corporation":false,"usgs":true,"family":"Pohlman","given":"John W.","affiliations":[],"preferred":false,"id":474669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riedel, Michael","contributorId":7518,"corporation":false,"usgs":true,"family":"Riedel","given":"Michael","email":"","affiliations":[],"preferred":false,"id":474664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bauer, James E.","contributorId":100262,"corporation":false,"usgs":true,"family":"Bauer","given":"James E.","affiliations":[],"preferred":false,"id":474671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Canuel, Elizabeth A.","contributorId":98604,"corporation":false,"usgs":true,"family":"Canuel","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474670,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":474667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lapham, Laura","contributorId":100263,"corporation":false,"usgs":true,"family":"Lapham","given":"Laura","affiliations":[],"preferred":false,"id":474672,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grabowski, Kenneth S.","contributorId":79374,"corporation":false,"usgs":true,"family":"Grabowski","given":"Kenneth","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":474668,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coffin, Richard B.","contributorId":36027,"corporation":false,"usgs":true,"family":"Coffin","given":"Richard B.","affiliations":[],"preferred":false,"id":474665,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spence, George D.","contributorId":54066,"corporation":false,"usgs":true,"family":"Spence","given":"George","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":474666,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70042310,"text":"70042310 - 2013 - Global earthquake fatalities and population","interactions":[],"lastModifiedDate":"2013-02-26T09:14:23","indexId":"70042310","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Global earthquake fatalities and population","docAbstract":"Modern global earthquake fatalities can be separated into two components: (1) fatalities from an approximately constant annual background rate that is independent of world population growth and (2) fatalities caused by earthquakes with large human death tolls, the frequency of which is dependent on world population. Earthquakes with death tolls greater than 100,000 (and 50,000) have increased with world population and obey a nonstationary Poisson distribution with rate proportional to population. We predict that the number of earthquakes with death tolls greater than 100,000 (50,000) will increase in the 21st century to 8.7±3.3 (20.5±4.3) from 4 (7) observed in the 20th century if world population reaches 10.1 billion in 2100. Combining fatalities caused by the background rate with fatalities caused by catastrophic earthquakes (>100,000 fatalities) indicates global fatalities in the 21st century will be 2.57±0.64 million if the average post-1900 death toll for catastrophic earthquakes (193,000) is assumed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earthquake Spectra","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"EERI","publisherLocation":"Oakland, CA","doi":"10.1193/1.4000106","usgsCitation":"Holzer, T.L., and Savage, J.C., 2013, Global earthquake fatalities and population: Earthquake Spectra, v. 29, no. 1, p. 155-175, https://doi.org/10.1193/1.4000106.","productDescription":"21 p.","startPage":"155","endPage":"175","ipdsId":"IP-029571","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":268280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268279,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1193/1.4000106"}],"volume":"29","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-02-01","publicationStatus":"PW","scienceBaseUri":"53cd5ef7e4b0b290850fc055","contributors":{"authors":[{"text":"Holzer, Thomas L. tholzer@usgs.gov","contributorId":2829,"corporation":false,"usgs":true,"family":"Holzer","given":"Thomas","email":"tholzer@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":471251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savage, James C. 0000-0002-5114-7673 jasavage@usgs.gov","orcid":"https://orcid.org/0000-0002-5114-7673","contributorId":2412,"corporation":false,"usgs":true,"family":"Savage","given":"James","email":"jasavage@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":471250,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70042510,"text":"70042510 - 2013 - A comment on \"Novel scavenger removal trials increase wind turbine-caused avian fatality estimates\"","interactions":[],"lastModifiedDate":"2018-03-29T15:16:16","indexId":"70042510","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"A comment on \"Novel scavenger removal trials increase wind turbine-caused avian fatality estimates\"","docAbstract":"<p><span>In a recent paper, Smallwood et al. (2010) conducted a study to compare their “novel” approach to conducting carcass removal trials with what they term the “conventional” approach and to evaluate the effects of the different methods on estimated avian fatality at a wind power facility in California. A quick glance at Table 3 that succinctly summarizes their results and provides estimated fatality rates and 80% confidence intervals calculated using the 2 methods reveals a surprising result. The confidence intervals of all of their estimates and most of the conventional estimates extend below 0. These results imply that wind turbines may have the capacity to create live birds. But a more likely interpretation is that a serious error occurred in the calculation of either the average fatality rate or its standard error or both. Further evaluation of their methods reveals that the scientific basis for concluding that “many estimates of scavenger removal rates prior to [their] study were likely biased low due to scavenger swamping” and “previously reported estimates of avian fatality rates … should be adjusted upwards” was not evident in their analysis and results. Their comparison to conventional approaches was not applicable, their statistical models were questionable, and the conclusions they drew were unsupported.</span></p>","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/jwmg.468","usgsCitation":"Huso, M., and Erickson, W.P., 2013, A comment on \"Novel scavenger removal trials increase wind turbine-caused avian fatality estimates\": Journal of Wildlife Management, v. 77, no. 2, p. 213-215, https://doi.org/10.1002/jwmg.468.","productDescription":"3 p.","startPage":"213","endPage":"215","ipdsId":"IP-031078","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":268315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268311,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.468"}],"volume":"77","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-01-07","publicationStatus":"PW","scienceBaseUri":"539a2a60e4b0a59b2649726f","contributors":{"authors":[{"text":"Huso, Manuela M.P.","contributorId":80566,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela M.P.","affiliations":[],"preferred":false,"id":471670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erickson, Wallace P.","contributorId":78627,"corporation":false,"usgs":true,"family":"Erickson","given":"Wallace","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":471669,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043595,"text":"70043595 - 2013 - A data-based conservation planning tool for Florida panthers","interactions":[],"lastModifiedDate":"2013-03-04T21:06:08","indexId":"70043595","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1550,"text":"Environmental Modeling & Assessment","onlineIssn":" 1573-296","printIssn":"1420-2026","active":true,"publicationSubtype":{"id":10}},"title":"A data-based conservation planning tool for Florida panthers","docAbstract":"Habitat loss and fragmentation are the greatest threats to the endangered Florida panther (<i>Puma concolor coryi</i>). We developed a data-based habitat model and user-friendly interface so that land managers can objectively evaluate Florida panther habitat. We used a geographic information system (GIS) and the Mahalanobis distance statistic (<i>D</i><sup>2</sup>) to develop a model based on broad-scale landscape characteristics associated with panther home ranges. Variables in our model were Euclidean distance to natural land cover, road density, distance to major roads, human density, amount of natural land cover, amount of semi-natural land cover, amount of permanent or semi-permanent flooded area–open water, and a cost–distance variable. We then developed a Florida Panther Habitat Estimator tool, which automates and replicates the GIS processes used to apply the statistical habitat model. The estimator can be used by persons with moderate GIS skills to quantify effects of land-use changes on panther habitat at local and landscape scales. Example applications of the tool are presented.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modeling and Assessment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10666-012-9336-0","usgsCitation":"Murrow, J.L., Thatcher, C., van Manen, F., and Clark, J.D., 2013, A data-based conservation planning tool for Florida panthers: Environmental Modeling & Assessment, v. 18, no. 2, p. 159-170, https://doi.org/10.1007/s10666-012-9336-0.","productDescription":"12 p.","startPage":"159","endPage":"170","ipdsId":"IP-040629","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":268388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268382,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10666-012-9336-0"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.63,24.52 ], [ -87.63,31.0 ], [ -80.0,31.0 ], [ -80.0,24.52 ], [ -87.63,24.52 ] ] ] } } ] }","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-09-09","publicationStatus":"PW","scienceBaseUri":"5135d072e4b03b8ec4025b38","contributors":{"authors":[{"text":"Murrow, Jennifer L.","contributorId":92945,"corporation":false,"usgs":true,"family":"Murrow","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":473934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thatcher, Cindy A.","contributorId":79604,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy A.","affiliations":[],"preferred":false,"id":473933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Manen, Frank T.","contributorId":51172,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank T.","affiliations":[],"preferred":false,"id":473932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":473931,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70044074,"text":"ofr20121113 - 2013 - Assessment of coal geology, resources, and reserves in the Montana Powder River Basin","interactions":[],"lastModifiedDate":"2013-02-26T12:38:21","indexId":"ofr20121113","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1113","title":"Assessment of coal geology, resources, and reserves in the Montana Powder River Basin","docAbstract":"The purpose of this report is to summarize geology, coal resources, and coal reserves in the Montana Powder River Basin assessment area in southeastern Montana. This report represents the fourth assessment area within the Powder River Basin to be evaluated in the continuing U.S. Geological Survey regional coal assessment program. There are four active coal mines in the Montana Powder River Basin assessment area: the Spring Creek and Decker Mines, both near Decker; the Rosebud Mine, near Colstrip; and the Absaloka Mine, west of Colstrip. During 2011, coal production from these four mines totaled approximately 36 million short tons. A fifth mine, the Big Sky, had significant production from 1969-2003; however, it is no longer in production and has since been reclaimed. Total coal production from all five mines in the Montana Powder River Basin assessment area from 1968 to 2011 was approximately 1.4 billion short tons. The Rosebud/Knobloch coal bed near Colstrip and the Anderson, Dietz 2, and Dietz 3 coal beds near Decker contain the largest deposits of surface minable, low-sulfur, subbituminous coal currently being mined in the assessment area. A total of 26 coal beds were identified during this assessment, 18 of which were modeled and evaluated to determine in-place coal resources. The total original coal resource in the Montana Powder River Basin assessment area for the 18 coal beds assessed was calculated to be 215 billion short tons. Available coal resources, which are part of the original coal resource remaining after subtracting restrictions and areas of burned coal, are about 162 billion short tons. Restrictions included railroads, Federal interstate highways, urban areas, alluvial valley floors, state parks, national forests, and mined-out areas. It was determined that 10 of the 18 coal beds had sufficient areal extent and thickness to be evaluated for recoverable surface resources ([Roland (Baker), Smith, Anderson, Dietz 2, Dietz 3, Canyon, Werner/Cook, Pawnee, Rosebud/Knobloch, and Flowers-Goodale]). These 10 coal beds total about 151 billion short tons of the 162 billion short tons of available resource; however, after applying a strip ratio of 10:1 or less, only 39 billion short tons remains of the 151 billion short tons. After mining and processing losses are subtracted from the 39 billion short tons, 35 billion short tons of coal were considered as a recoverable resource. Coal reserves (economically recoverable coal) are the portion of the recoverable coal resource that can be mined, processed, and marketed at a profit at the time of the economic evaluation. The surface coal reserve estimate for the 10 coal beds evaluated for the Montana Powder River assessment area is 13 billion short tons. It was also determined that about 42 billion short tons of underground coal resource exists in the Montana Powder River Basin assessment area; about 34 billion short tons (80 percent) are within 500-1,000 feet of the land surface and another 8 billion short tons are 1,000-2,000 feet beneath the land surface.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121113","usgsCitation":"Haacke, J., Scott, D.C., Osmonson, L.M., Luppens, J.A., Pierce, P.E., and Gunderson, J.A., 2013, Assessment of coal geology, resources, and reserves in the Montana Powder River Basin: U.S. Geological Survey Open-File Report 2012-1113, xi, 133 p., https://doi.org/10.3133/ofr20121113.","productDescription":"xi, 133 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":268375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1113.gif"},{"id":268374,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1113/OF12-1113.pdf"},{"id":268373,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1113/"}],"country":"United States","state":"Montana;Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.1714,42.6259 ], [ -108.1714,46.7850 ], [ -104.0076,46.7850 ], [ -104.0076,42.6259 ], [ -108.1714,42.6259 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4e2be4b0b290850f1ef4","contributors":{"authors":[{"text":"Haacke, Jon E.","contributorId":86054,"corporation":false,"usgs":true,"family":"Haacke","given":"Jon E.","affiliations":[],"preferred":false,"id":474781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, David C. 0000-0002-7925-7452 dscott@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-7452","contributorId":629,"corporation":false,"usgs":true,"family":"Scott","given":"David","email":"dscott@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":474778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osmonson, Lee M.","contributorId":33322,"corporation":false,"usgs":false,"family":"Osmonson","given":"Lee","email":"","middleInitial":"M.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":false,"id":474780,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luppens, James A. 0000-0001-7607-8750 jluppens@usgs.gov","orcid":"https://orcid.org/0000-0001-7607-8750","contributorId":550,"corporation":false,"usgs":true,"family":"Luppens","given":"James","email":"jluppens@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":474777,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pierce, Paul E. 0000-0001-9675-7320 ppierce@usgs.gov","orcid":"https://orcid.org/0000-0001-9675-7320","contributorId":3732,"corporation":false,"usgs":true,"family":"Pierce","given":"Paul","email":"ppierce@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":474779,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gunderson, Jay A.","contributorId":94566,"corporation":false,"usgs":true,"family":"Gunderson","given":"Jay","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474782,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70044056,"text":"70044056 - 2013 - The Malthusian-Darwinian dynamic and the trajectory of civilization","interactions":[],"lastModifiedDate":"2018-01-16T11:26:33","indexId":"70044056","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"The Malthusian-Darwinian dynamic and the trajectory of civilization","docAbstract":"Two interacting forces influence all populations: the Malthusian dynamic of exponential growth until resource limits are reached, and the Darwinian dynamic of innovation and adaptation to circumvent these limits through biological and/or cultural evolution. The specific manifestations of these forces in modern human society provide an important context for determining how humans can establish a sustainable relationship with the finite Earth.","language":"English","publisher":"Elsevier","doi":"10.1016/j.tree.2012.12.001","usgsCitation":"Nekola, J.C., Allen, C.D., Brown, J., Burger, J.R., Davidson, A., Fristoe, T.S., Hamilton, M.J., Hammond, S.T., Kodric-Brown, A., Mercado-Silva, N., and Okie, J.G., 2013, The Malthusian-Darwinian dynamic and the trajectory of civilization: Trends in Ecology and Evolution, v. 28, no. 3, p. 127-130, https://doi.org/10.1016/j.tree.2012.12.001.","productDescription":"4 p.","startPage":"127","endPage":"130","ipdsId":"IP-043895","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":268310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7703e4b0b2908510b49b","contributors":{"authors":[{"text":"Nekola, Jeffrey C.","contributorId":105958,"corporation":false,"usgs":true,"family":"Nekola","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":474734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":474724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, James H.","contributorId":20058,"corporation":false,"usgs":true,"family":"Brown","given":"James H.","affiliations":[],"preferred":false,"id":474727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burger, Joseph R.","contributorId":15875,"corporation":false,"usgs":true,"family":"Burger","given":"Joseph","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":474725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davidson, Ana D.","contributorId":93321,"corporation":false,"usgs":true,"family":"Davidson","given":"Ana D.","affiliations":[],"preferred":false,"id":474733,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fristoe, Trevor S.","contributorId":40464,"corporation":false,"usgs":true,"family":"Fristoe","given":"Trevor","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":474728,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hamilton, Marcus J.","contributorId":73452,"corporation":false,"usgs":true,"family":"Hamilton","given":"Marcus","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":474730,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hammond, Sean T.","contributorId":85483,"corporation":false,"usgs":true,"family":"Hammond","given":"Sean","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":474732,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kodric-Brown, Astrid","contributorId":82197,"corporation":false,"usgs":true,"family":"Kodric-Brown","given":"Astrid","email":"","affiliations":[],"preferred":false,"id":474731,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mercado-Silva, Norman","contributorId":18219,"corporation":false,"usgs":true,"family":"Mercado-Silva","given":"Norman","email":"","affiliations":[],"preferred":false,"id":474726,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Okie, Jordan G.","contributorId":69836,"corporation":false,"usgs":true,"family":"Okie","given":"Jordan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":474729,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70044100,"text":"70044100 - 2013 - Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example","interactions":[],"lastModifiedDate":"2013-02-26T17:59:42","indexId":"70044100","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example","docAbstract":"Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10980-012-9830-4","usgsCitation":"Cross, P.C., Caillaud, D., and Heisey, D.M., 2013, Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example: Landscape Ecology, v. 28, no. 2, p. 247-257, https://doi.org/10.1007/s10980-012-9830-4.","productDescription":"11 p.","startPage":"247","endPage":"257","ipdsId":"IP-034645","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":268415,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10980-012-9830-4"},{"id":268416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-11-30","publicationStatus":"PW","scienceBaseUri":"53cd7a2ae4b0b2908510d4ed","contributors":{"authors":[{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":474810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caillaud, Damien","contributorId":31650,"corporation":false,"usgs":true,"family":"Caillaud","given":"Damien","email":"","affiliations":[],"preferred":false,"id":474811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heisey, Dennis M. dheisey@usgs.gov","contributorId":2455,"corporation":false,"usgs":true,"family":"Heisey","given":"Dennis","email":"dheisey@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":474809,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70146651,"text":"70146651 - 2013 - Fens as whole-ecosystem gauges of groundwater recharge under climate change","interactions":[],"lastModifiedDate":"2015-04-20T09:17:35","indexId":"70146651","displayToPublicDate":"2013-02-25T10:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Fens as whole-ecosystem gauges of groundwater recharge under climate change","docAbstract":"<p>Currently, little is known about the impact of climate change on groundwater recharge in the Sierra Nevada and southern Cascade Range of California or other mountainous regions of the world. The purpose of this study was to determine whether small alpine peat lands called fens can be used as whole-ecosystem gauges of groundwater recharge through time. Fens are sustained by groundwater discharge and are highly sensitive to changes in groundwater flow due to hydrologic disturbance including climate change. Seven fens in the Sierra Nevada and southern Cascade Range were studied over a 50-80 year period using historic aerial photography. In each aerial photograph, fen areas were identified as open lawn and partially treed areas that exhibited (1) dark brownish-green coloring or various shades of gray and black in black and white imagery and (2) mottling of colors and clustering of vegetation, which signified a distinct moss canopy with overlying clumped sedge vegetation. In addition to the aerial photography study, a climate analysis for the study sites was carried out using both measured data (U.S. Department of Agriculture Natural Resources Conservation Service SNOwpack TELemetry system) and modeled data (a downscaled version of the Parameter-elevation Regressions on Independent Slopes Model) for the period from 1951 to 2010. Over the study period, the five fens in the Sierra Nevada were found to be decreasing between 10% and 16% in delineated area. The climate analysis revealed significant increases through time in annual mean minimum temperature (T<sub>min</sub>) between 1951-1980 and 1981-2010. In addition, April 1 snow water equivalent and snowpack longevity also decreased between 1951-1980 and 1981-2010. For the fens in the Cascade Range, there were no discernible changes in delineated area. At these sites, increases in T<sub>min</sub> occurred only within the past 20-25 years and decreases in snowpack longevity were more subtle. A conceptual model is presented, which illustrates that basic differences in hydrogeology of the Sierra Nevada vs. the Cascade Range may control the threshold at which changes in delineated fen areas are discernible. Overall, the results from this study show that fens in the Sierra Nevada have strong potential as whole ecosystem gauges for determining long-term changes in groundwater recharge under climate change. Due to either more moderate climate change and/or hydrogeological differences, fens in the southern Cascade Range currently do not appear to have the same utility. A greater sample size of fens in the Sierra Nevada is needed to confirm the general applicability of this method. In addition, future work needs to focus on integrating fen monitoring with geochemical and/or isotopic process-level studies in order to quantify changes in groundwater recharge identified using this new approach.</p>","language":"English","publisher":"European Geophysical Society","publisherLocation":"New York, NY","doi":"10.1016/j.jhydrol.2012.11.056","usgsCitation":"Drexler, J., Knifong, D.L., Tuil, J., Flint, L.E., and Flint, A.L., 2013, Fens as whole-ecosystem gauges of groundwater recharge under climate change: Journal of Hydrology, v. 481, p. 22-34, https://doi.org/10.1016/j.jhydrol.2012.11.056.","productDescription":"13 p.","startPage":"22","endPage":"34","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040704","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":299768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"481","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5536233ae4b0b22a15807a94","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":1659,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith Z.","email":"jdrexler@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":545228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knifong, Donna L. dknifong@usgs.gov","contributorId":1517,"corporation":false,"usgs":true,"family":"Knifong","given":"Donna","email":"dknifong@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":545227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tuil, JayLee","contributorId":140341,"corporation":false,"usgs":false,"family":"Tuil","given":"JayLee","email":"","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":545230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":545226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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