{"pageNumber":"654","pageRowStart":"16325","pageSize":"25","recordCount":46883,"records":[{"id":70142796,"text":"70142796 - 2012 - Great lakes prey fish populations: a cross-basin overview of status and trends based on bottom trawl surveys, 1978-2012","interactions":[],"lastModifiedDate":"2018-03-23T14:41:05","indexId":"70142796","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Great lakes prey fish populations: a cross-basin overview of status and trends based on bottom trawl surveys, 1978-2012","docAbstract":"<p><span>The assessment of prey fish stocks in the Great Lakes have been conducted annually with bottom trawls since the 1970s by the Great Lakes Science Center, sometimes assisted by partner agencies. These stock assessments provide data on the status and trends of prey fish that are consumed by important commercial and recreational fishes. Although all these annual surveys are conducted using bottom trawls, they differ among the lakes in the proportion of the lake covered, seasonal timing, bottom trawl gear used, and the manner in which the trawl is towed (across or along bottom contours). Because each assessment is unique in one or more important aspects, direct comparison of prey fish catches among lakes is not straightforward. However, all of the assessments produce indices of abundance or biomass that can be standardized to facilitate comparisons of status and trends across all the Great Lakes. In this report, population indices were standardized to the highest value for a time series within each lake for the following principal prey species: cisco (</span><i>Coregonus artedi</i><span>), bloater (</span><i>C. hoyi</i><span>), rainbow smelt (</span><i>Osmerus mordax</i><span>), and alewife (</span><i>Alosa pseudoharengus</i><span>). Indices were also provided for round goby (</span><i>Neogobius melanostomus</i><span>), an invasive fish that has proliferated throughout the basin over the past 18 years. These standardized indices represent the best available long-term indices of relative abundance for these fishes across all of the Great Lakes. In this report, standardized indices are presented in graphical form along with synopses to provide a short, informal cross-basin summary of the status and trends of principal prey fishes. In keeping with this intent, tables, references, and a detailed discussion were omitted.</span></p>","language":"English","publisher":"U.S. Geological Survey - Great Lakes Science Center","usgsCitation":"Gorman, O.T., 2012, Great lakes prey fish populations: a cross-basin overview of status and trends based on bottom trawl surveys, 1978-2012, 9 p.","productDescription":"9 p.","startPage":"1","endPage":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044799","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":312030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312029,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.glsc.usgs.gov/products/reports/624961862"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      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,{"id":70148283,"text":"70148283 - 2012 - Slip rate on the San Diego trough fault zone, inner California Borderland, and the 1986 Oceanside earthquake swarm revisited","interactions":[],"lastModifiedDate":"2015-05-27T10:20:09","indexId":"70148283","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Slip rate on the San Diego trough fault zone, inner California Borderland, and the 1986 Oceanside earthquake swarm revisited","docAbstract":"<p>The San Diego trough fault zone (SDTFZ) is part of a 90-km-wide zone of faults within the inner California Borderland that accommodates motion between the Pacific and North American plates. Along with most faults offshore southern California, the slip rate and paleoseismic history of the SDTFZ are unknown. We present new seismic reflection data that show that the fault zone steps across a 5-km-wide stepover to continue for an additional 60 km north of its previously mapped extent. The 1986 Oceanside earthquake swarm is located within the 20-km-long restraining stepover. Farther north, at the latitude of Santa Catalina Island, the SDTFZ bends 20&deg; to the west and may be linked via a complex zone of folds with the San Pedro basin fault zone (SPBFZ). In a cooperative program between the U.S. Geological Survey (USGS) and the Monterey Bay Aquarium Research Institute (MBARI), we measure and date the coseismic offset of a submarine channel that intersects the fault zone near the SDTFZ&ndash;SPBFZ junction. We estimate a horizontal slip rate of about 1:5 \u0001 0:3 mm=yr over the past 12,270 yr.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120110317","usgsCitation":"Ryan, H., Conrad, J.E., Paull, C.K., and McGann, M., 2012, Slip rate on the San Diego trough fault zone, inner California Borderland, and the 1986 Oceanside earthquake swarm revisited: Bulletin of the Seismological Society of America, v. 102, no. 6, p. 2300-2312, https://doi.org/10.1785/0120110317.","productDescription":"13 p.","startPage":"2300","endPage":"2312","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-036085","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":300839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Diego trough fault zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.7237548828125,\n              32.579220642875676\n            ],\n            [\n              -118.7237548828125,\n              33.578014746143985\n            ],\n            [\n              -117.7239990234375,\n              33.578014746143985\n            ],\n            [\n              -117.7239990234375,\n              32.579220642875676\n            ],\n            [\n              -118.7237548828125,\n              32.579220642875676\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"102","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-12-01","publicationStatus":"PW","scienceBaseUri":"5566eae2e4b0d9246a9ec2fd","contributors":{"authors":[{"text":"Ryan, Holly F. hryan@usgs.gov","contributorId":140746,"corporation":false,"usgs":true,"family":"Ryan","given":"Holly F.","email":"hryan@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":547656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":547657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paull, C. 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,{"id":70141428,"text":"70141428 - 2012 - Validation of a coupled wave-flow model in a high-energy setting: the mouth of the Columbia River","interactions":[],"lastModifiedDate":"2017-03-06T12:54:47","indexId":"70141428","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Validation of a coupled wave-flow model in a high-energy setting: the mouth of the Columbia River","docAbstract":"<p><span>&nbsp;A monthlong time series of wave, current, salinity, and suspended-sediment measurements was made at five sites on a transect across the Mouth of Columbia River (MCR). These data were used to calibrate and evaluate the performance of a coupled hydrodynamic and wave model for the MCR based on the Delft3D modeling system. The MCR is a dynamic estuary inlet in which tidal currents, river discharge, and wave-driven currents are all important. Model tuning consisted primarily of spatial adjustments to bottom drag coefficients. In combination with (near-) default parameter settings, the MCR model application is able to simulate the dominant features in the tidal flow, salinity and wavefields observed in field measurements. The wave-orbital averaged method for representing the current velocity profile in the wave model is considered the most realistic for the MCR. The hydrodynamic model is particularly effective in reproducing the observed vertical residual and temporal variations in current structure. Density gradients introduce the observed and modeled reversal of the mean flow at the bed and augment mean and peak flow in the upper half of the water column. This implies that sediment transport during calmer summer conditions is controlled by density stratification and is likely net landward due to the reversal of flow near the bed. The correspondence between observed and modeled hydrodynamics makes this application a tool to investigate hydrodynamics and associated sediment transport.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2012JC008105","usgsCitation":"Elias, E.P., Gelfenbaum, G.R., and van der Westhuysen, A.J., 2012, Validation of a coupled wave-flow model in a high-energy setting: the mouth of the Columbia River: Journal of Geophysical Research C: Oceans, v. 117, no. C9, 21 p., https://doi.org/10.1029/2012JC008105.","productDescription":"21 p.","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042897","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474646,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2012jc008105","text":"Publisher Index Page"},{"id":298050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Columbia River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.07958984375001,\n              46.06560846138691\n            ],\n            [\n              -124.07958984375001,\n              46.3810438458062\n            ],\n            [\n              -122.8216552734375,\n              46.3810438458062\n            ],\n            [\n              -122.8216552734375,\n              46.06560846138691\n            ],\n            [\n              -124.07958984375001,\n              46.06560846138691\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"117","issue":"C9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-09-11","publicationStatus":"PW","scienceBaseUri":"54e7173ce4b02d776a66a01d","contributors":{"authors":[{"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":540763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gelfenbaum, Guy R. 0000-0003-1291-6107 ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":540764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van der Westhuysen, Andre J.","contributorId":139312,"corporation":false,"usgs":false,"family":"van der Westhuysen","given":"Andre","email":"","middleInitial":"J.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. 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,{"id":70185340,"text":"70185340 - 2012 - Factors associated with the severity of interacting fires in Yosemite National Park","interactions":[],"lastModifiedDate":"2017-03-21T13:02:01","indexId":"70185340","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Factors associated with the severity of interacting fires in Yosemite National Park","docAbstract":"In 1972, Yosemite National Park established a wilderness fire zone in which lightning fires were allowed to run their courses under prescribed conditions.  This zone was expanded in 1973 to include the 16 209 ha Illilouette Creek basin, just to the southeast of Yosemite Valley.  From 1973 through 2011, there have been 157 fires in the basin.  Fire severity data were collected on all 28 of those fires that were larger than 40 ha.  The proportion burned in each fire severity class was not significantly associated with fire return interval departure class.  When areas were reburned, the proportion of unchanged severity fire decreased while the proportion of high severity fire increased.  The proportion of fire severity of the subsequent fires was associated with the number of years since last burned, the burning index, and the severity of the previous fires.  The main effects were significant for unchanged severity and low severity, and the interaction between return interval class and burning index class was significant for high severity.  Most vegetation types remained the same when burned with unchanged, low, or moderate severity, while high severity often resulted in conversion to montane chaparral.  The factors that were associated with reburn severity worked in combination with each factor influencing some aspect of severity. Managers and scientists can use this information to better understand the role fire plays in these ecosystems and how to best manage this dynamic ecological process.","language":"English","publisher":"Association for Fire Ecology","doi":"10.4996/fireecology.0801011","collaboration":"NPS","usgsCitation":"van Wagtendonk, J., van Wagtendonk, K.A., and Thode, A.E., 2012, Factors associated with the severity of interacting fires in Yosemite National Park: Fire Ecology, v. 8, no. 1, p. 11-31, https://doi.org/10.4996/fireecology.0801011.","productDescription":"21 p. ","startPage":"11","endPage":"31","ipdsId":"IP-031682","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":474670,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4996/fireecology.0801011","text":"Publisher Index Page"},{"id":337939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":337884,"type":{"id":15,"text":"Index Page"},"url":"https://fireecologyjournal.org/docs/Journal/pdf/Volume08/Issue01/011.pdf"}],"country":"United States","state":"California","otherGeospatial":"Illilouette Creek ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.5580291748047,\n              37.72592253917786\n            ],\n            [\n              -119.5806884765625,\n              37.71967662525055\n            ],\n            [\n              -119.59030151367188,\n              37.70202228211617\n            ],\n            [\n              -119.58961486816408,\n              37.66507035959997\n            ],\n            [\n              -119.58240509033203,\n              37.586486421515175\n            ],\n            [\n              -119.4873046875,\n              37.58485404085001\n            ],\n            [\n              -119.43134307861328,\n              37.628643846637885\n            ],\n            [\n              -119.44061279296875,\n              37.664798586116596\n            ],\n            [\n              -119.46739196777344,\n              37.70120736474139\n            ],\n            [\n              -119.47185516357423,\n              37.71696084622755\n            ],\n            [\n              -119.55493927001953,\n              37.72592253917786\n            ],\n            [\n              -119.5580291748047,\n              37.72592253917786\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2012-04-01","publicationStatus":"PW","scienceBaseUri":"58d23b91e4b0236b68f828f2","contributors":{"authors":[{"text":"van Wagtendonk, Jan W.","contributorId":189573,"corporation":false,"usgs":false,"family":"van Wagtendonk","given":"Jan W.","affiliations":[],"preferred":false,"id":685231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Wagtendonk, Kent A.","contributorId":175027,"corporation":false,"usgs":false,"family":"van Wagtendonk","given":"Kent","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":685232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thode, Andrea E.","contributorId":189574,"corporation":false,"usgs":false,"family":"Thode","given":"Andrea","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":685233,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70176762,"text":"70176762 - 2012 - The FOBIMO (FOraminiferal BIo-MOnitoring) initiative—Towards a standardised protocol for soft-bottom benthic foraminiferal monitoring studies","interactions":[],"lastModifiedDate":"2017-04-27T10:48:28","indexId":"70176762","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2673,"text":"Marine Micropaleontology","active":true,"publicationSubtype":{"id":10}},"title":"The FOBIMO (FOraminiferal BIo-MOnitoring) initiative—Towards a standardised protocol for soft-bottom benthic foraminiferal monitoring studies","docAbstract":"<p><span>The European Community Marine Strategy Framework Directive (MSFD) was established to provide guidelines for monitoring the quality of marine ecosystems. Monitoring the status of marine environments is traditionally based on macrofauna surveys, for which standardised methods have been established. Benthic foraminifera are also good indicators of environmental status because of their fast turnover rates, high degree of specialisation, and the preservation of dead assemblages in the fossil record. In spite of the growing interest in foraminiferal bio-monitoring during the last decades, no standardised methodology has been proposed until today. The aim of the FOraminiferal BIo-MOnitoring (FOBIMO) expert workshop, held in June 2011 at Fribourg, Switzerland, which assembled 37 scientists from 24 research groups and 13 countries, was to develop a suite of standard methods. This paper presents the main outcome of the workshop, a list of motivated recommendations with respect to sampling devices, sample storage, treatment, faunal analysis and documentation. Our recommendations fulfil the criteria imposed both by scientific rigour and by the practical limitations of routine studies. Hence, our aim is to standardise methodologies used in bio-monitoring only and not to limit the use of different methods in pure scientific studies. Unless otherwise stated, all recommendations concern living (stained) benthic foraminiferal assemblages. We have chosen to propose two types of recommendations. </span><i>Mandatory recommendations</i><span> have to be followed if a study wants to qualify as sound and compatible to the norms. The most important of these recommendations are the interval from 0 to 1&nbsp;cm below the sediment surface has to be sampled, and an interface corer or box corer that keeps the sediment surface intact is to be used for offshore surveys. A grab sampler must not be deployed in soft sediments. Three replicate samples are to be taken and analysed separately. Samples are to be washed on a 63-μm screen, and the living benthic foraminiferal fauna of the &gt;&nbsp;125&nbsp;μm fraction is to be analysed. Splits are to be picked and counted entirely, and all counted foraminifera from at least one replicate per station have to be stored in micropalaeontological slides. Census data, supplementary laboratory data and microslides have to be archived. </span><i>Advisory recommendations</i><span> are to sample in autumn, to have a sample size of 50&nbsp;cm</span><sup>2</sup><span> or a tube of 8&nbsp;cm inner diameter, to use &gt;&nbsp;70% ethanol as a preservative, rose Bengal at a concentration of 2 grams per litre for staining, and a staining time of at least 14&nbsp;days. The split size should be defined by a target value of 300 specimens, heavy liquid separation should be avoided, and the 63–125&nbsp;μm fraction or deeper sediment levels may be considered in some environments. We are convinced that the application of this protocol by a large number of scientists is a necessary first step to a general acceptance of benthic foraminifera as a reliable tool in bio-monitoring studies.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marmicro.2012.06.001","usgsCitation":"Schoenfeld, J., Alve, E., Geslin, E., Jorissen, F., Korsun, S., Spezzaferri, S., Abramovich, S., Almogi-Labin, A., Armynot du Chatelet, E., Barras, C., Bergamin, L., Bicchi, E., Bouchet, V., Cearreta, A., Di Bella, L., Dijkstra, N., Trevisan Disaro, S., Ferraro, L., Frontalini, F., Gennari, G., Golikova, E., Haynert, K., Hess, S., Husum, K., Martins, V., McGann, M., Oron, S., Romano, E., Mello Sousa, S., and Tsujimoto, A., 2012, The FOBIMO (FOraminiferal BIo-MOnitoring) initiative—Towards a standardised protocol for soft-bottom benthic foraminiferal monitoring studies: Marine Micropaleontology, v. 94-95, p. 1-13, https://doi.org/10.1016/j.marmicro.2012.06.001.","productDescription":"13 p.","startPage":"1","endPage":"13","ipdsId":"IP-062675","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":329327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94-95","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f3b2e4b0bc0bec0a0b1b","contributors":{"authors":[{"text":"Schoenfeld, Joachim","contributorId":167478,"corporation":false,"usgs":false,"family":"Schoenfeld","given":"Joachim","email":"","affiliations":[{"id":24716,"text":"Helmholtz Centre for Ocean Research Kiel (GEOMAR)","active":true,"usgs":false}],"preferred":false,"id":650200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alve, Elisabeth","contributorId":167479,"corporation":false,"usgs":false,"family":"Alve","given":"Elisabeth","email":"","affiliations":[{"id":24717,"text":"University of Oslo, Norway","active":true,"usgs":false}],"preferred":false,"id":650201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geslin, Emmanuelle","contributorId":167480,"corporation":false,"usgs":false,"family":"Geslin","given":"Emmanuelle","email":"","affiliations":[{"id":24718,"text":"University of Angers, France","active":true,"usgs":false}],"preferred":false,"id":650202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jorissen, Frans","contributorId":167481,"corporation":false,"usgs":false,"family":"Jorissen","given":"Frans","email":"","affiliations":[{"id":24718,"text":"University of Angers, France","active":true,"usgs":false}],"preferred":false,"id":650203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Korsun, Sergei","contributorId":167482,"corporation":false,"usgs":false,"family":"Korsun","given":"Sergei","email":"","affiliations":[{"id":24719,"text":"St. Petersburg State University, Russia","active":true,"usgs":false}],"preferred":false,"id":650204,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spezzaferri, Silva","contributorId":167483,"corporation":false,"usgs":false,"family":"Spezzaferri","given":"Silva","affiliations":[{"id":24720,"text":"University of Fribourg, Switzerland","active":true,"usgs":false}],"preferred":false,"id":650205,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Abramovich, Sigal","contributorId":175127,"corporation":false,"usgs":false,"family":"Abramovich","given":"Sigal","email":"","affiliations":[],"preferred":false,"id":650207,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Almogi-Labin, Ahuva","contributorId":175129,"corporation":false,"usgs":false,"family":"Almogi-Labin","given":"Ahuva","email":"","affiliations":[],"preferred":false,"id":650208,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Armynot du Chatelet, Eric","contributorId":175130,"corporation":false,"usgs":false,"family":"Armynot du Chatelet","given":"Eric","email":"","affiliations":[],"preferred":false,"id":650209,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Barras, Christine","contributorId":175131,"corporation":false,"usgs":false,"family":"Barras","given":"Christine","email":"","affiliations":[],"preferred":false,"id":650210,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bergamin, Luisa","contributorId":175132,"corporation":false,"usgs":false,"family":"Bergamin","given":"Luisa","email":"","affiliations":[],"preferred":false,"id":650211,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bicchi, Erica","contributorId":175133,"corporation":false,"usgs":false,"family":"Bicchi","given":"Erica","email":"","affiliations":[],"preferred":false,"id":650212,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bouchet, 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Elena","contributorId":175142,"corporation":false,"usgs":false,"family":"Golikova","given":"Elena","email":"","affiliations":[],"preferred":false,"id":650228,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Haynert, Kristin","contributorId":175143,"corporation":false,"usgs":false,"family":"Haynert","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":650229,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Hess, Silvia","contributorId":175144,"corporation":false,"usgs":false,"family":"Hess","given":"Silvia","email":"","affiliations":[],"preferred":false,"id":650230,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Husum, Katrine","contributorId":175145,"corporation":false,"usgs":false,"family":"Husum","given":"Katrine","email":"","affiliations":[],"preferred":false,"id":650231,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Martins, Virginia","contributorId":175146,"corporation":false,"usgs":false,"family":"Martins","given":"Virginia","email":"","affiliations":[],"preferred":false,"id":650232,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":2849,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":650233,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Oron, Shai","contributorId":175147,"corporation":false,"usgs":false,"family":"Oron","given":"Shai","email":"","affiliations":[],"preferred":false,"id":650234,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Romano, Elena","contributorId":175148,"corporation":false,"usgs":false,"family":"Romano","given":"Elena","email":"","affiliations":[],"preferred":false,"id":650235,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Mello Sousa, Silvia","contributorId":175149,"corporation":false,"usgs":false,"family":"Mello Sousa","given":"Silvia","email":"","affiliations":[],"preferred":false,"id":650236,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Tsujimoto, Akira","contributorId":58448,"corporation":false,"usgs":true,"family":"Tsujimoto","given":"Akira","email":"","affiliations":[],"preferred":false,"id":650237,"contributorType":{"id":1,"text":"Authors"},"rank":30}]}}
,{"id":70169879,"text":"70169879 - 2012 - Timing of wet snow avalanche activity: An analysis from Glacier National Park, Montana, USA.","interactions":[],"lastModifiedDate":"2017-04-25T10:41:57","indexId":"70169879","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Timing of wet snow avalanche activity: An analysis from Glacier National Park, Montana, USA.","docAbstract":"<p><span>Wet snow avalanches pose a problem for annual spring road opening operations along the Going-to-the-Sun Road (GTSR) in Glacier National Park, Montana, USA. A suite of meteorological metrics and snow observations has been used to forecast for wet slab and glide avalanche activity. However, the timing of spring wet slab and glide avalanches is a difficult process to forecast and requires new capabilities. For the 2011 and 2012 spring seasons we tested a previously developed classification tree model which had been trained on data from 2003-2010. For 2011, this model yielded a 91% predictive rate for avalanche days. For 2012, the model failed to capture any of the avalanche days observed. We then investigated these misclassified avalanche days in the 2012 season by comparing them to the misclassified days from the original dataset from which the model was trained. Results showed no significant difference in air temperature variables between this year and the original training data set for these misclassified days. This indicates that 2012 was characterized by avalanche days most similar to those that the model struggled with in the original training data. The original classification tree model showed air temperature to be a significant variable in wet avalanche activity which implies that subsequent movement of meltwater through the snowpack is also important. To further understand the timing of water flow we installed two lysimeters in fall 2011 before snow accumulation. Water flow showed a moderate correlation with air temperature later in the season and no synchronous pattern associated with wet slab and glide avalanche activity. We also characterized snowpack structure as the snowpack transitioned from a dry to a wet snowpack throughout the spring. This helped to assess potential failure layers of wet snow avalanches and the timing of avalanches compared to water moving through the snowpack. These tools (classification tree model and lysimeter data), combined with standard meteorological and avalanche observations, proved useful to forecasters regarding the timing of wet snow avalanche activity along the GTSR.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings, 2012 International Snow Science Workshop","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2012 International Snow Science Workshop","conferenceDate":"September 16-21, 2012","conferenceLocation":"Anchorage, AK","language":"English","publisher":"International Snow Science Workshop","usgsCitation":"Peitzsch, E.H., Hendrikx, J., and Fagre, D.B., 2012, Timing of wet snow avalanche activity: An analysis from Glacier National Park, Montana, USA., <i>in</i> Proceedings, 2012 International Snow Science Workshop, Anchorage, AK, September 16-21, 2012, p. 884-891.","productDescription":"8 p.","startPage":"884","endPage":"891","ipdsId":"IP-039562","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":340124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340123,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://arc.lib.montana.edu/snow-science/item/1664"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58fdbd19e4b007492829448b","contributors":{"authors":[{"text":"Peitzsch, Erich H. 0000-0001-7624-0455 epeitzsch@usgs.gov","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":3786,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","email":"epeitzsch@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":625435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hendrikx, Jordy","contributorId":166967,"corporation":false,"usgs":false,"family":"Hendrikx","given":"Jordy","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":625436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":625434,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70169878,"text":"70169878 - 2012 - Time lapse photography as an approach to understanding glide avalanche activity","interactions":[],"lastModifiedDate":"2017-04-25T10:44:45","indexId":"70169878","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Time lapse photography as an approach to understanding glide avalanche activity","docAbstract":"<p><span>Avalanches resulting from glide cracks are notoriously difficult to forecast, but are a recurring problem for numerous avalanche forecasting programs. In some cases glide cracks are observed to open and then melt away in situ. In other cases, they open and then fail catastrophically as large, full-depth avalanches. Our understanding and management of these phenomena are currently limited. It is thought that an increase in the rate of snow gliding occurs prior to full-depth avalanche activity so frequent observation of glide crack movement can provide an index of instability. During spring 2011 in Glacier National Park, Montana, USA, we began an approach to track glide crack avalanche activity using a time-lapse camera focused on a southwest facing glide crack. This crack melted in-situ without failing as a glide avalanche, while other nearby glide cracks on north through southeast aspects failed. In spring 2012, a camera was aimed at a large and productive glide crack adjacent to the Going to the Sun Road. We captured three unique glide events in the field of view. Unfortunately, all of them either failed very quickly, or during periods of obscured view, so measurements of glide rate could not be obtained. However, we compared the hourly meteorological variables during the period of glide activity to the same variables prior to glide activity. The variables air temperature, relative humidity, air pressure, incoming and reflected long wave radiation, SWE, total precipitation, and snow depth were found to be statistically different for our cases examined. We propose that these are some of the potential precursors for glide avalanche activity, but do urge caution in their use, due to the simple approach and small data set size. It is hoped that by introducing a workable method to easily record glide crack movement, combined with ongoing analysis of the associated meteorological data, we will improve our understanding of when, or if, glide avalanche activity will ensue.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings, 2012 International Snow Science Workshop","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2012 International Snow Science Workshop","conferenceDate":"September 16-21, 2012","conferenceLocation":"Anchorage, AK","language":"English","publisher":"International Snow Science Workshop","usgsCitation":"Hendrikx, J., Peitzsch, E.H., and Fagre, D.B., 2012, Time lapse photography as an approach to understanding glide avalanche activity, <i>in</i> Proceedings, 2012 International Snow Science Workshop, Anchorage, AK, September 16-21, 2012, p. 872-877.","productDescription":"6 p.","startPage":"872","endPage":"877","ipdsId":"IP-039714","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":340112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340111,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://arc.lib.montana.edu/snow-science/item/1662"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58fdbd1ae4b007492829448d","contributors":{"authors":[{"text":"Hendrikx, Jordy","contributorId":166967,"corporation":false,"usgs":false,"family":"Hendrikx","given":"Jordy","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":625433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peitzsch, Erich H. 0000-0001-7624-0455 epeitzsch@usgs.gov","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":3786,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","email":"epeitzsch@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":625432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":625431,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70173603,"text":"70173603 - 2012 - Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain","interactions":[],"lastModifiedDate":"2016-06-07T16:04:12","indexId":"70173603","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain","docAbstract":"<p><span>Alewife (</span><i>Alosa pseudoharengus</i><span>) recently became established in Lake Champlain and may compete with native rainbow smelt (</span><i>Osmerus mordax</i><span>) for food or consume larval rainbow smelt. The strength of this effect depends partly on the spatial and temporal overlap of different age groups of the two species; therefore, we need a better understanding of factors affecting alewife and rainbow smelt distributions in Lake Champlain. We used hydroacoustics, trawls, and gill nets to document vertical fish distribution, and recorded environmental data during 16&nbsp;day&ndash;night surveys over two years. Temperature, temperature change, and light were all predictors of adult and age-0 rainbow smelt distribution, and temperature and light were predictors of age-0 alewives' distribution (based on GAMM models evaluated with AIC). Adult alewives were 5&ndash;30&nbsp;m shallower and age-0 alewives were 2&ndash;15&nbsp;m shallower than their rainbow smelt counterparts. Adult rainbow smelt distribution overlapped with age-0 rainbow smelt and age-0 alewives near the thermocline (10&ndash;25&nbsp;m), whereas adult alewives were shallower (0&ndash;6&nbsp;m) and overlapped with age-0 alewives and rainbow smelt in the epilimnion. Adult rainbow smelt were in water &lt;&nbsp;10&ndash;12&nbsp;&deg;C, whereas age-0 rainbow smelt were in 10&ndash;20&nbsp;&deg;C, and adult and age-0 alewives were in 15&ndash;22&nbsp;&deg;C water. Predicting these species distributions is necessary for quantifying the strength of predatory and competitive interactions between alewife and rainbow smelt, as well as between alewife and other fish species in Lake Champlain.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2011.06.002","usgsCitation":"Parrish, D.L., Simonin, P.W., Rudstam, L.G., Sullivan, P., and Pientka, B., 2012, Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain: Journal of Great Lakes Research, v. 38, no. 1, p. 115-122, https://doi.org/10.1016/j.jglr.2011.06.002.","productDescription":"8 p.","startPage":"115","endPage":"122","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025329","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.22250366210938,\n              44.457309801319305\n            ],\n            [\n              -73.29391479492188,\n              44.46025037930627\n            ],\n            [\n              -73.33511352539062,\n              44.3670601700202\n            ],\n            [\n              -73.21563720703125,\n              44.37196862007497\n            ],\n            [\n              -73.21975708007812,\n              44.449467536006935\n            ],\n            [\n              -73.22250366210938,\n              44.457309801319305\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"38","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5757f062e4b04f417c24dcf6","contributors":{"authors":[{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simonin, Paul W.","contributorId":171499,"corporation":false,"usgs":false,"family":"Simonin","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":18160,"text":"Rubenstein School of Environment and Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":637741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":637742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Patrick J.","contributorId":97813,"corporation":false,"usgs":true,"family":"Sullivan","given":"Patrick J.","affiliations":[],"preferred":false,"id":637743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pientka, Bernard","contributorId":171500,"corporation":false,"usgs":false,"family":"Pientka","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":637744,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70174123,"text":"70174123 - 2012 - Expert knowledge as a foundation for the management of secretive species and their habitat","interactions":[],"lastModifiedDate":"2016-09-07T13:22:05","indexId":"70174123","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Expert knowledge as a foundation for the management of secretive species and their habitat","docAbstract":"<p><span>In this chapter, we share lessons learned during the elicitation and application of expert knowledge in the form of a belief network model for the habitat of a waterbird, the King Rail (</span><i class=\"EmphasisTypeItalic \">Rallus elegans</i><span>). A belief network is a statistical framework used to graphically represent and evaluate hypothesized cause and effect relationships among variables. Our model was a pilot project to explore the value of such a model as a tool to help the US Fish and Wildlife Service (USFWS) conserve species that lack sufficient empirical data to guide management decisions. Many factors limit the availability of empirical data that can support landscape-scale conservation planning. Globally, most species simply have not yet been subject to empirical study (Wilson 2000). Even for well-studied species, data are often restricted to specific geographic extents, to particular seasons, or to specific segments of a species’ life history. The USFWS mandates that the agency’s conservation actions (1) be coordinated across regional landscapes, (2) be founded on the best available science (with testable assumptions), and (3) support adaptive management through monitoring and assessment of action outcomes. Given limits on the available data, the concept of “best available science” in the context of conservation planning generally includes a mix of empirical data and expert knowledge (Sullivan et al. 2006).</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Expert knowledge and its application in landscape ecology","language":"English","publisher":"Springer New York","doi":"10.1007/978-1-4614-1034-8","usgsCitation":"Drew, C.A., and Collazo, J., 2012, Expert knowledge as a foundation for the management of secretive species and their habitat, chap. <i>of</i> Expert knowledge and its application in landscape ecology, p. 87-107, https://doi.org/10.1007/978-1-4614-1034-8.","productDescription":"21 p.","startPage":"87","endPage":"107","ipdsId":"IP-030006","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":328316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a3be4b0571647cf8dd4","contributors":{"authors":[{"text":"Drew, C. Ashton","contributorId":140953,"corporation":false,"usgs":false,"family":"Drew","given":"C.","email":"","middleInitial":"Ashton","affiliations":[],"preferred":false,"id":648213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collazo, Jaime jaime_collazo@usgs.gov","contributorId":2613,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":640966,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70175236,"text":"70175236 - 2012 - Power analysis and trend detection for water quality monitoring data. An application for the Greater Yellowstone Inventory and Monitoring Network","interactions":[],"lastModifiedDate":"2016-08-31T13:55:37","indexId":"70175236","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/GRYN/NRR-2012/556","title":"Power analysis and trend detection for water quality monitoring data. An application for the Greater Yellowstone Inventory and Monitoring Network","docAbstract":"<p>An important consideration for long term monitoring programs is determining the required sampling effort to detect trends in specific ecological indicators of interest. To enhance the Greater Yellowstone Inventory and Monitoring Network’s water resources protocol(s) (O’Ney 2006 and O’Ney et al. 2009 [under review]), we developed a set of tools to: (1) determine the statistical power for detecting trends of varying magnitude in a specified water quality parameter over different lengths of sampling (years) and different within-year collection frequencies (monthly or seasonal sampling) at particular locations using historical data, and (2) perform periodic trend analyses for water quality parameters while addressing seasonality and flow weighting. </p><p>A power analysis for trend detection is a statistical procedure used to estimate the probability of rejecting the hypothesis of no trend when in fact there is a trend, within a specific modeling framework. In this report, we base our power estimates on using the seasonal Kendall test (Helsel and Hirsch 2002) for detecting trend in water quality parameters measured at fixed locations over multiple years. We also present procedures (R-scripts) for conducting a periodic trend analysis using the seasonal Kendall test with and without flow adjustment. This report provides the R-scripts developed for power and trend analysis, tutorials, and the associated tables and graphs. The purpose of this report is to provide practical information for monitoring network staff on how to use these statistical tools for water quality monitoring data sets. </p>","language":"English","publisher":"National Park Service","usgsCitation":"Irvine, K.M., Manlove, K., and Hollimon, C., 2012, Power analysis and trend detection for water quality monitoring data. An application for the Greater Yellowstone Inventory and Monitoring Network: Natural Resource Report NPS/GRYN/NRR-2012/556, ix, 65 p.","productDescription":"ix, 65 p.","numberOfPages":"75","ipdsId":"IP-037155","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":328141,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328140,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2187418"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7ffbde4b0f2f0cebfc323","contributors":{"authors":[{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manlove, Kezia","contributorId":68204,"corporation":false,"usgs":true,"family":"Manlove","given":"Kezia","affiliations":[],"preferred":false,"id":644469,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hollimon, Cynthia","contributorId":173384,"corporation":false,"usgs":false,"family":"Hollimon","given":"Cynthia","email":"","affiliations":[{"id":5120,"text":"Montana State University, Department of Mathematical Sciences, Bozeman, MT 59717","active":true,"usgs":false}],"preferred":false,"id":644468,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70173757,"text":"70173757 - 2012 - Spatio-temporal variation in male white-tailed deer harvest rates in Pennsylvania: Implications for estimating abundance","interactions":[],"lastModifiedDate":"2016-08-24T12:28:25","indexId":"70173757","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatio-temporal variation in male white-tailed deer harvest rates in Pennsylvania: Implications for estimating abundance","docAbstract":"<p><span>The performance of 2 popular methods that use age-at-harvest data to estimate abundance of white-tailed deer is contingent on assumptions about variation in estimates of subadult (1.5&thinsp;yr old) and adult (&ge;2.5&thinsp;yr old) male harvest rates. Auxiliary data (e.g., estimates of survival or harvest rates from radiocollared animals) can be used to relax some assumptions, but unless these population parameters exhibit limited temporal or spatial variation, these auxiliary data may not improve accuracy. Unfortunately maintaining sufficient sample sizes of radiocollared deer for parameter estimation in every wildlife management unit (WMU) is not feasible for most state agencies. We monitored the fates of 397 subadult and 225 adult male white-tailed deer across 4 WMUs from 2002 to 2008 using radio telemetry. We investigated spatial and temporal variation in harvest rates and investigated covariates related to the patterns observed. We found that most variation in harvest rates was explained spatially and that adult harvest rates (0.36&ndash;0.69) were more variable among study areas than subadult harvest rates (0.26&ndash;0.42). We found that hunter effort during the archery and firearms season best explained variation in harvest rates of adult males among WMUs, whereas hunter effort during only the firearms season best explained harvest rates for subadult males. From a population estimation perspective, it is advantageous that most variation was spatial and explained by a readily obtained covariate (hunter effort). However, harvest rates may vary if hunting regulations or hunter behavior change, requiring additional field studies to obtain accurate estimates of harvest rates.&nbsp;</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.249","usgsCitation":"Norton, A.S., Diefenbach, D.R., Wallingford, B.D., and Rosenberry, C.S., 2012, Spatio-temporal variation in male white-tailed deer harvest rates in Pennsylvania: Implications for estimating abundance: Journal of Wildlife Management, v. 76, no. 1, p. 136-143, https://doi.org/10.1002/jwmg.249.","productDescription":"8 p.","startPage":"136","endPage":"143","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025517","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Armstrong County, Centre County, 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PSC"},"noUsgsAuthors":false,"publicationDate":"2011-09-27","publicationStatus":"PW","scienceBaseUri":"57594233e4b04f417c256996","contributors":{"authors":[{"text":"Norton, Andrew S.","contributorId":171631,"corporation":false,"usgs":false,"family":"Norton","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":638130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":638069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallingford, Bret D.","contributorId":171632,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":638131,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberry, Christopher S.","contributorId":171633,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":638132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70173875,"text":"70173875 - 2012 - Lake sturgeon population attributes and reproductive structure in the Namakan Reservoir, Minnesota and Ontario","interactions":[],"lastModifiedDate":"2018-02-23T14:21:04","indexId":"70173875","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"title":"Lake sturgeon population attributes and reproductive structure in the Namakan Reservoir, Minnesota and Ontario","docAbstract":"<p><span>Quantified were the age, growth, mortality and reproductive structure of lake sturgeon (</span><i>Acipenser fulvescens</i><span>) collected in the US and Canadian waters of the Namakan Reservoir. The hypotheses were tested that (i) age and growth of lake sturgeon in the Namakan Reservoir would differ by sex and reproductive stage of maturity, and (ii) that the relative strength of year-classes of lake sturgeon in the reservoir would be affected by environmental variables. To quantify age, growth and mortality of the population, existing data was used from a multi-agency database containing information on all lake sturgeon sampled in the reservoir from 2004 to 2009. Lake sturgeon were sampled in the Minnesota and Ontario waters of the Namakan Reservoir using multi-filament gillnets 1.8&nbsp;m high and 30&ndash;100&nbsp;m long and varying in mesh size from 178 to 356&nbsp;mm stretch. Reproductive structure of the lake sturgeon was assessed only during spring 2008 and 2009 using plasma testosterone and estradiol-17&beta; concentrations. Ages of lake sturgeon &gt;75&nbsp;cm ranged from 9 to 86&nbsp;years (n&nbsp;=&nbsp;533, mean&nbsp;=&nbsp;36&nbsp;years). A catch-curve analysis using the 1981&ndash;1953&nbsp;year classes estimated total annual mortality of adults to be 4.8% and annual survival as 95.2%. Using logistic regression analysis, it was found that total annual precipitation was positively associated with lake sturgeon year-class strength in the Namakan Reservoir. A 10&nbsp;cm increase in total annual precipitation was associated with at least a 39% increase in the odds of occurrence of a strong year class of lake sturgeon in the reservoir. Plasma steroid analysis revealed a sex ratio of 2.4 females: 1 male and, on average, 10% of female and 30% of male lake sturgeon were reproductively mature each year (i.e. potential spawners). Moreover, there was evidence based on re-captured male fish of both periodic and annual spawning, as well as the ability of males to rapidly undergo gonadal maturation prior to spawning. Knowledge of lake sturgeon reproductive structure and factors influencing recruitment success contribute to the widespread conservation efforts for this threatened species.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1439-0426.2011.01927.x","usgsCitation":"Shaw, S.L., Chipps, S.R., Windels, S.K., Webb, M., McLeod, D.T., and Willis, D., 2012, Lake sturgeon population attributes and reproductive structure in the Namakan Reservoir, Minnesota and Ontario: Journal of Applied Ichthyology, v. 28, no. 2, p. 168-175, https://doi.org/10.1111/j.1439-0426.2011.01927.x.","productDescription":"8 p.","startPage":"168","endPage":"175","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-031252","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Minnesota, Ontario","otherGeospatial":"Namakan Reservoir","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.44696044921875,\n              48.25576986959547\n            ],\n            [\n              -93.44696044921875,\n              48.69821216562637\n            ],\n            [\n              -92.35931396484374,\n              48.69821216562637\n            ],\n            [\n              -92.35931396484374,\n              48.25576986959547\n            ],\n            [\n              -93.44696044921875,\n              48.25576986959547\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-02-06","publicationStatus":"PW","scienceBaseUri":"57627c34e4b07657d19a69fe","contributors":{"authors":[{"text":"Shaw, S. L.","contributorId":171918,"corporation":false,"usgs":false,"family":"Shaw","given":"S.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":639108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":638879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Windels, Steve K.","contributorId":182422,"corporation":false,"usgs":false,"family":"Windels","given":"Steve","email":"","middleInitial":"K.","affiliations":[{"id":18939,"text":"Voyageurs National Park","active":true,"usgs":false}],"preferred":false,"id":639109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, M.A.H.","contributorId":102241,"corporation":false,"usgs":true,"family":"Webb","given":"M.A.H.","affiliations":[],"preferred":false,"id":639110,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLeod, D. T.","contributorId":171920,"corporation":false,"usgs":false,"family":"McLeod","given":"D.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":639111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Willis, D.W.","contributorId":56179,"corporation":false,"usgs":true,"family":"Willis","given":"D.W.","email":"","affiliations":[],"preferred":false,"id":639112,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70173872,"text":"70173872 - 2012 - A generalized model for estimating the energy density of invertebrates","interactions":[],"lastModifiedDate":"2016-06-15T14:47:04","indexId":"70173872","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"A generalized model for estimating the energy density of invertebrates","docAbstract":"<p><span>Invertebrate energy density (ED) values are traditionally measured using bomb calorimetry. However, many researchers rely on a few published literature sources to obtain ED values because of time and sampling constraints on measuring ED with bomb calorimetry. Literature values often do not account for spatial or temporal variability associated with invertebrate ED. Thus, these values can be unreliable for use in models and other ecological applications. We evaluated the generality of the relationship between invertebrate ED and proportion of dry-to-wet mass (pDM). We then developed and tested a regression model to predict ED from pDM based on a taxonomically, spatially, and temporally diverse sample of invertebrates representing 28 orders in aquatic (freshwater, estuarine, and marine) and terrestrial (temperate and arid) habitats from 4 continents and 2 oceans. Samples included invertebrates collected in all seasons over the last 19&nbsp;y. Evaluation of these data revealed a significant relationship between ED and pDM (</span><i>r</i><span>2</span><span>&nbsp; =  0.96,&nbsp;</span><i>p</i><span>&nbsp;&lt; 0.0001), where ED (as J/g wet mass) was estimated from pDM as ED  =  22,960pDM &minus; 174.2. Model evaluation showed that nearly all (98.8%) of the variability between observed and predicted values for invertebrate ED could be attributed to residual error in the model. Regression of observed on predicted values revealed that the 97.5% joint confidence region included the intercept of 0 (&minus;103.0 &plusmn; 707.9) and slope of 1 (1.01 &plusmn; 0.12). Use of this model requires that only dry and wet mass measurements be obtained, resulting in significant time, sample size, and cost savings compared to traditional bomb calorimetry approaches. This model should prove useful for a wide range of ecological studies because it is unaffected by taxonomic, seasonal, or spatial variability.</span></p>","language":"English","publisher":"The University of Chicago Press","doi":"10.1899/11-057.1","usgsCitation":"James, D.A., Csargo, I.J., Von Eschen, A., Thul, M.D., Baker, J.M., Hayer, C., Howell, J., Krause, J., Letvin, A., and Chipps, S.R., 2012, A generalized model for estimating the energy density of invertebrates: Freshwater Science, v. 31, no. 1, p. 69-77, https://doi.org/10.1899/11-057.1.","productDescription":"9 p.","startPage":"69","endPage":"77","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032442","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57627c2be4b07657d19a69b3","contributors":{"authors":[{"text":"James, Daniel A.","contributorId":41737,"corporation":false,"usgs":true,"family":"James","given":"Daniel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Csargo, Isak J.","contributorId":171858,"corporation":false,"usgs":false,"family":"Csargo","given":"Isak","email":"","middleInitial":"J.","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":639116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Von Eschen, Aaron","contributorId":171921,"corporation":false,"usgs":false,"family":"Von Eschen","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":639117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thul, Megan D.","contributorId":171922,"corporation":false,"usgs":false,"family":"Thul","given":"Megan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":639118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baker, James M.","contributorId":171923,"corporation":false,"usgs":false,"family":"Baker","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":639119,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayer, Cari-Ann chayer@usgs.gov","contributorId":150040,"corporation":false,"usgs":true,"family":"Hayer","given":"Cari-Ann","email":"chayer@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":639120,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Howell, Jessica","contributorId":171924,"corporation":false,"usgs":false,"family":"Howell","given":"Jessica","email":"","affiliations":[],"preferred":false,"id":639121,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krause, Jacob","contributorId":171925,"corporation":false,"usgs":false,"family":"Krause","given":"Jacob","affiliations":[],"preferred":false,"id":639122,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Letvin, Alex","contributorId":171926,"corporation":false,"usgs":false,"family":"Letvin","given":"Alex","affiliations":[],"preferred":false,"id":639123,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":638876,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70005993,"text":"70005993 - 2012 - The impact of biotic/abiotic interfaces in mineral nutrient cycling: A study of soils of the Santa Cruz chronosequence, California","interactions":[],"lastModifiedDate":"2020-12-30T19:15:07.348439","indexId":"70005993","displayToPublicDate":"2011-12-25T13:43:00","publicationYear":"2012","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":"The impact of biotic/abiotic interfaces in mineral nutrient cycling: A study of soils of the Santa Cruz chronosequence, California","docAbstract":"<p id=\"sp005\">Biotic/abiotic interactions between soil mineral nutrients and annual grassland vegetation are characterized for five soils in a marine terrace chronosequence near Santa Cruz, California. A Mediterranean climate, with wet winters and dry summers, controls the annual cycle of plant growth and litter decomposition, resulting in net above-ground productivities of 280–600&nbsp;g&nbsp;m<sup>−2</sup>&nbsp;yr<sup>−1</sup>. The biotic/abiotic (A/B) interface separates seasonally reversible nutrient gradients, reflecting biological cycling in the shallower soils, from downward chemical weathering gradients in the deeper soils. The A/B interface is pedologically defined by argillic clay horizons centered at soil depths of about one meter which intensify with soil age. Below these horizons, elevated solute Na/Ca, Mg/Ca and Sr/Ca ratios reflect plagioclase and smectite weathering along pore water flow paths. Above the A/B interface, lower cation ratios denote temporal variability due to seasonal plant nutrient uptake and litter leaching. Potassium and Ca exhibit no seasonal variability beneath the A/B interface, indicating closed nutrient cycling within the root zone, whereas Mg variability below the A/B interface denotes downward leakage resulting from higher inputs of marine aerosols and lower plant nutrient requirements.</p><p id=\"sp010\">The fraction of a mineral nutrient annually cycled through the plants, compared to that lost from pore water discharge, is defined their respective fluxes<span>&nbsp;</span><i>F</i><sub>j,plants</sub>&nbsp;=&nbsp;<i>q</i><sub>j,plants</sub>/(<i>q</i><sub>j,plants</sub>&nbsp;+&nbsp;<i>q</i><sub>j,discharge</sub>) with average values for K and Ca (<i>F</i><sub>K,plants</sub>&nbsp;=&nbsp;0.99;<span>&nbsp;</span><i>F</i><sub>Ca,plants</sub>&nbsp;=&nbsp;0.93) much higher than for Mg and Na (<i>F</i><sub>Mg,plants</sub><span>&nbsp;</span>0.64;<span>&nbsp;</span><i>F</i><sub>Na,plants</sub>&nbsp;=&nbsp;0.28). The discrimination against Rb and Sr by plants is described by fractionation factors (<i>K</i><sub>Sr/Ca</sub>&nbsp;=&nbsp;0.86;<span>&nbsp;</span><i>K</i><sub>Rb/K</sub>&nbsp;=&nbsp;0.83) which are used in Rayleigh fractionation-mixing calculations to fit seasonal patterns in solute K and Ca cycling.<span>&nbsp;</span><i>K</i><sub>Rb/K</sub><span>&nbsp;</span>and<span>&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>K</mi></mrow><mrow is=&quot;true&quot;><msup is=&quot;true&quot;><mrow is=&quot;true&quot; /><mrow is=&quot;true&quot;><mn is=&quot;true&quot;>24</mn></mrow></msup><mtext is=&quot;true&quot;>Mg</mtext><mo is=&quot;true&quot;>/</mo><msup is=&quot;true&quot;><mrow is=&quot;true&quot; /><mrow is=&quot;true&quot;><mn is=&quot;true&quot;>22</mn></mrow></msup><mtext is=&quot;true&quot;>Mg</mtext></mrow></msub></mrow></math>\"><span class=\"MJX_Assistive_MathML\">K24Mg/22Mg</span></span></span><span>&nbsp;</span>values (derived from isotope data in the literature) fall within fractionation envelopes bounded by inputs from rainfall and mineral weathering.<span>&nbsp;</span><i>K</i><sub>Sr/Ca</sub><span>&nbsp;</span>and<span>&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mrow is=&quot;true&quot;><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>K</mi></mrow><mrow is=&quot;true&quot;><msup is=&quot;true&quot;><mrow is=&quot;true&quot; /><mrow is=&quot;true&quot;><mn is=&quot;true&quot;>44</mn></mrow></msup><mtext is=&quot;true&quot;>Ca</mtext><mo is=&quot;true&quot;>/</mo><msup is=&quot;true&quot;><mrow is=&quot;true&quot; /><mrow is=&quot;true&quot;><mn is=&quot;true&quot;>40</mn></mrow></msup><mtext is=&quot;true&quot;>Ca</mtext></mrow></msub></mrow></math>\"><span class=\"MJX_Assistive_MathML\">K44Ca/40Ca</span></span></span><span>&nbsp;</span>fractionation factors fall outside these envelopes indicating that Ca nutrient cycling is closed to these external inputs. Small net positive K and Ca fluxes (6–14&nbsp;mol&nbsp;m<sup>−2</sup>&nbsp;yr<sup>−1</sup>), based on annual mass balances, indicate that the soils are accumulating mineral nutrients, probably as a result of long-term environmental disequilibrium.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2011.10.029","usgsCitation":"White, A.F., Schulz, M., Vivit, D., Bullen, T.D., and Fitzpatrick, J.A., 2012, The impact of biotic/abiotic interfaces in mineral nutrient cycling: A study of soils of the Santa Cruz chronosequence, California: Geochimica et Cosmochimica Acta, v. 77, p. 62-85, https://doi.org/10.1016/j.gca.2011.10.029.","productDescription":"24 p.","startPage":"62","endPage":"85","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":381770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Cruz","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.18170166015625,\n              36.925743371044966\n            ],\n            [\n              -121.89605712890624,\n              36.925743371044966\n            ],\n            [\n              -121.89605712890624,\n              37.048601046408976\n            ],\n            [\n              -122.18170166015625,\n              37.048601046408976\n            ],\n            [\n              -122.18170166015625,\n              36.925743371044966\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"77","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bacdfe4b08c986b3237d8","contributors":{"authors":[{"text":"White, Art F.","contributorId":8607,"corporation":false,"usgs":true,"family":"White","given":"Art","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":353616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":353615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vivit, Davison V.","contributorId":79922,"corporation":false,"usgs":true,"family":"Vivit","given":"Davison V.","affiliations":[],"preferred":false,"id":353618,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bullen, Tomas D.","contributorId":64792,"corporation":false,"usgs":true,"family":"Bullen","given":"Tomas","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":353617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzpatrick, John A. 0000-0001-6738-7180 jfitzpat@usgs.gov","orcid":"https://orcid.org/0000-0001-6738-7180","contributorId":3719,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"John","email":"jfitzpat@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":353614,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70005978,"text":"70005978 - 2012 - Temporal trends in algae, benthic invertebrate, and fish assemblages in streams and rivers draining basins of varying land use in the south-central United States, 1993-2007","interactions":[],"lastModifiedDate":"2017-01-04T13:41:38","indexId":"70005978","displayToPublicDate":"2011-12-18T16:09:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Temporal trends in algae, benthic invertebrate, and fish assemblages in streams and rivers draining basins of varying land use in the south-central United States, 1993-2007","docAbstract":"<p><span>Site-specific temporal trends in algae, benthic invertebrate, and fish assemblages were investigated in 15 streams and rivers draining basins of varying land use in the south-central United States from 1993–2007. A multivariate approach was used to identify sites with statistically significant trends in aquatic assemblages which were then tested for correlations with assemblage metrics and abiotic environmental variables (climate, water quality, streamflow, and physical habitat). Significant temporal trends in one or more of the aquatic assemblages were identified at more than half (eight of 15) of the streams in the study. Assemblage metrics and abiotic environmental variables found to be significantly correlated with aquatic assemblages differed between land use categories. For example, algal assemblages at undeveloped sites were associated with physical habitat, while algal assemblages at more anthropogenically altered sites (agricultural and urban) were associated with nutrient and streamflow metrics. In urban stream sites results indicate that streamflow metrics may act as important controls on water quality conditions, as represented by aquatic assemblage metrics. The site-specific identification of biotic trends and abiotic–biotic relations presented here will provide valuable information that can inform interpretation of continued monitoring data and the design of future studies. In addition, the subsets of abiotic variables identified as potentially important drivers of change in aquatic assemblages provide policy makers and resource managers with information that will assist in the design and implementation of monitoring programs aimed at the protection of aquatic resources.</span></p>","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10750-011-0950-7","usgsCitation":"Miller, M.P., Kennen, J., Mabe, J.A., and Mize, S.V., 2012, Temporal trends in algae, benthic invertebrate, and fish assemblages in streams and rivers draining basins of varying land use in the south-central United States, 1993-2007: Hydrobiologia, v. 684, no. 1, p. 15-33, https://doi.org/10.1007/s10750-011-0950-7.","productDescription":"19 p.","startPage":"15","endPage":"33","temporalStart":"1993-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":257563,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Colorado, Kansas, Kentucky, Louisiana, Mississippi, Missouri, New Mexico, Oklahoma, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.09716796875,\n              25.958044673317843\n            ],\n            [\n              -97.40478515625,\n              25.878994400196202\n            ],\n            [\n              -97.84423828125,\n              26.05678288577881\n            ],\n            [\n              -98.45947265625,\n              26.13571361317392\n            ],\n            [\n              -98.98681640625,\n              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Center","active":true,"usgs":true}],"preferred":true,"id":353583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mabe, Jeffrey A.","contributorId":65565,"corporation":false,"usgs":true,"family":"Mabe","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":353586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mize, Scott V. 0000-0001-6751-5568 svmize@usgs.gov","orcid":"https://orcid.org/0000-0001-6751-5568","contributorId":2997,"corporation":false,"usgs":true,"family":"Mize","given":"Scott","email":"svmize@usgs.gov","middleInitial":"V.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353584,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227333,"text":"70227333 - 2012 - Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment","interactions":[],"lastModifiedDate":"2022-01-10T15:36:27.174564","indexId":"70227333","displayToPublicDate":"2011-11-26T09:26:26","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2049,"text":"International Journal of Greenhouse Gas Control","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO<sub>2</sub> injection experiment","title":"Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment","docAbstract":"<div id=\"aep-abstract-id35\" class=\"abstract author\"><div id=\"aep-abstract-sec-id36\"><p id=\"spar0010\">A field experiment involving the release of carbon dioxide (CO<sub>2</sub>) into a shallow aquifer was conducted near Bozeman, Montana, during the summer of 2008, to investigate the potential groundwater quality impacts in the case of leakage of CO<sub>2</sub><span>&nbsp;</span>from deep geological storage. As an essential part of the Montana State University Zero Emission Research and Technology (MSU-ZERT) field program, food-grade CO<sub>2</sub><span>&nbsp;</span>was injected over a 30 day period into a horizontal perforated pipe a few feet below the water table of a shallow aquifer. The impact of elevated CO<sub>2</sub><span>&nbsp;</span>concentrations on groundwater quality was investigated by analyzing water samples taken before, during, and following CO<sub>2</sub><span>&nbsp;</span>injection, from observation wells located in the vicinity of the injection pipe, and from two distant monitoring wells. Field measurements and laboratory analyses showed rapid and systematic changes in pH, alkalinity, and conductance, as well as increases in the aqueous concentrations of naturally occurring major and trace element species.</p><p id=\"spar0015\">The geochemical data were evaluated using principal component analysis (PCA) to (1) understand potential correlations between aqueous species, and (2) to identify minerals controlling the chemical composition of the groundwater prior to CO<sub>2</sub><span>&nbsp;</span>injection. These evaluations were used to assess possible geochemical processes responsible for the observed increases in the concentrations of dissolved constituents, and to simulate these processes using a multicomponent reaction path model. Reasonable agreement between observed and modeled data suggests that (1) calcite dissolution was the primary pH buffer, yielding increased Ca<sup>+2</sup><span>&nbsp;</span>concentrations in the groundwater, (2) increases in the concentrations of most major and trace metal cations except Fe could be a result of Ca<sup>+2</sup>-driven exchange reactions, (3) the release of anions from adsorption sites due to competitive adsorption of carbonate could explain the observed trends of most anions, and (4) the dissolution of reactive Fe minerals (presumed ferrihydrite and fougerite, from thermodynamic analyses) could explain increases in total Fe concentration.</p></div></div><div id=\"aep-abstract-id33\" class=\"abstract graphical\"><div id=\"aep-abstract-sec-id34\"><h3 class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Highlights</h3><p id=\"spar0005\">► Because the possibility of CO<sub>2</sub><span>&nbsp;</span>leakage cannot be completely ruled out, the potential impact of CO<sub>2</sub><span>&nbsp;</span>intrusion on the quality of fresh water aquifers overlying CO<sub>2</sub><span>&nbsp;</span>storage sites needs to be investigated. ► Geochemical data from a field experiment involving the release of carbon dioxide (CO<sub>2</sub>) into a shallow aquifer were evaluated. ► Geochemical model used to assess possible geochemical processes responsible for the observed increases in the concentrations of dissolved constituents. ► Reasonable agreement between observed and modeled data suggests that increases in the concentrations of most major and trace metal cations except Fe could be a result of Ca<sup>+2</sup>-driven exchange reactions and the release of anions from adsorption sites due to competitive adsorption of carbonate could explain the observed trends of most anions.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijggc.2011.10.003","usgsCitation":"Zheng, L., Apps, J.A., Spycher, N., Birkholzer, J., Kharaka, Y.K., Thordsen, J., Beers, S.R., Herkelrath, W.N., Kakouros, E., and Trautz, R.C., 2012, Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment: International Journal of Greenhouse Gas Control, v. 7, p. 202-217, https://doi.org/10.1016/j.ijggc.2011.10.003.","productDescription":"16 p.","startPage":"202","endPage":"217","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":474694,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1210906","text":"External Repository"},{"id":394105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","city":"Bozeman","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.20292663574217,\n              45.58809518781759\n            ],\n            [\n              -110.95916748046875,\n              45.58809518781759\n            ],\n            [\n              -110.95916748046875,\n              45.670684230297006\n            ],\n            [\n              -111.20292663574217,\n              45.670684230297006\n            ],\n            [\n              -111.20292663574217,\n              45.58809518781759\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zheng, Liange","contributorId":209333,"corporation":false,"usgs":false,"family":"Zheng","given":"Liange","email":"","affiliations":[],"preferred":false,"id":830491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Apps, J. A.","contributorId":60386,"corporation":false,"usgs":false,"family":"Apps","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":830492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spycher, N.","contributorId":54424,"corporation":false,"usgs":true,"family":"Spycher","given":"N.","email":"","affiliations":[],"preferred":false,"id":830493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birkholzer, J.","contributorId":84590,"corporation":false,"usgs":true,"family":"Birkholzer","given":"J.","affiliations":[],"preferred":false,"id":830494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kharaka, Yousif K. 0000-0001-9861-8260 ykharaka@usgs.gov","orcid":"https://orcid.org/0000-0001-9861-8260","contributorId":1928,"corporation":false,"usgs":true,"family":"Kharaka","given":"Yousif","email":"ykharaka@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":830495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thordsen, James J. jthordsn@usgs.gov","contributorId":3329,"corporation":false,"usgs":true,"family":"Thordsen","given":"James J.","email":"jthordsn@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":830496,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beers, Sarah R.","contributorId":209331,"corporation":false,"usgs":false,"family":"Beers","given":"Sarah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":830497,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Herkelrath, William N. 0000-0002-6149-5524 wnherkel@usgs.gov","orcid":"https://orcid.org/0000-0002-6149-5524","contributorId":2612,"corporation":false,"usgs":true,"family":"Herkelrath","given":"William","email":"wnherkel@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":830498,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kakouros, Evangelos 0000-0002-4778-4039 kakouros@usgs.gov","orcid":"https://orcid.org/0000-0002-4778-4039","contributorId":2587,"corporation":false,"usgs":true,"family":"Kakouros","given":"Evangelos","email":"kakouros@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":830499,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Trautz, Robert C.","contributorId":171754,"corporation":false,"usgs":false,"family":"Trautz","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":26941,"text":"Electric Power Research Institute, Palo Alto, CA","active":true,"usgs":false}],"preferred":false,"id":830500,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70032532,"text":"70032532 - 2012 - Fitting a structured juvenile-adult model for green tree frogs to population estimates from capture-mark-recapture field data","interactions":[],"lastModifiedDate":"2021-02-04T19:41:57.048472","indexId":"70032532","displayToPublicDate":"2011-10-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1107,"text":"Bulletin of Mathematical Biology","active":true,"publicationSubtype":{"id":10}},"title":"Fitting a structured juvenile-adult model for green tree frogs to population estimates from capture-mark-recapture field data","docAbstract":"<p><span>We derive point and interval estimates for an urban population of green tree frogs (</span><i>Hyla cinerea</i><span>) from capture–mark–recapture field data obtained during the years 2006–2009. We present an infinite-dimensional least-squares approach which compares a mathematical population model to the statistical population estimates obtained from the field data. The model is composed of nonlinear first-order hyperbolic equations describing the dynamics of the amphibian population where individuals are divided into juveniles (tadpoles) and adults (frogs). To solve the least-squares problem, an explicit finite difference approximation is developed. Convergence results for the computed parameters are presented. Parameter estimates for the vital rates of juveniles and adults are obtained, and standard deviations for these estimates are computed. Numerical results for the model sensitivity with respect to these parameters are given. Finally, the above-mentioned parameter estimates are used to illustrate the long-time behavior of the population under investigation.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s11538-011-9682-0","usgsCitation":"Ackleh, A.S., Carter, J., Deng, K., Huang, Q., Pal, N., and Yang, X., 2012, Fitting a structured juvenile-adult model for green tree frogs to population estimates from capture-mark-recapture field data: Bulletin of Mathematical Biology, v. 74, no. 3, p. 641-665, https://doi.org/10.1007/s11538-011-9682-0.","productDescription":"25 p.","startPage":"641","endPage":"665","ipdsId":"IP-032520","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":241621,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-10-13","publicationStatus":"PW","scienceBaseUri":"505a10c6e4b0c8380cd53dd6","contributors":{"authors":[{"text":"Ackleh, Azmy S.","contributorId":119949,"corporation":false,"usgs":true,"family":"Ackleh","given":"Azmy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":436663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, J. 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":81839,"corporation":false,"usgs":true,"family":"Carter","given":"J.","email":"carterj@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":436668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deng, Keng","contributorId":119746,"corporation":false,"usgs":true,"family":"Deng","given":"Keng","email":"","affiliations":[],"preferred":false,"id":436665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huang, Qihua","contributorId":119159,"corporation":false,"usgs":true,"family":"Huang","given":"Qihua","email":"","affiliations":[],"preferred":false,"id":436664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pal, Nabendu","contributorId":119796,"corporation":false,"usgs":true,"family":"Pal","given":"Nabendu","email":"","affiliations":[],"preferred":false,"id":436667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yang, Xing","contributorId":116164,"corporation":false,"usgs":true,"family":"Yang","given":"Xing","email":"","affiliations":[],"preferred":false,"id":436666,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70004913,"text":"70004913 - 2012 - Development and use of a floristic quality index for coastal Louisiana marshes","interactions":[],"lastModifiedDate":"2019-08-27T11:34:45","indexId":"70004913","displayToPublicDate":"2011-06-10T11:30:03","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Development and use of a floristic quality index for coastal Louisiana marshes","docAbstract":"The Floristic Quality Index (FQI) has been used as a tool for assessing the integrity of plant communities and for assessing restoration projects in many regions of the USA. Here, we develop a modified FQI (FQImod) for coastal Louisiana wetlands and verify it using 12 years of monitoring data from a coastal restoration project. Plant species that occur in coastal Louisiana were assigned a coefficient of conservatism (CC) score by a local group with expertise in Louisiana coastal vegetation. Species percent cover and both native and non-native species were included in the FQImod which was scaled from 0?100. The FQImod scores from the long-term monitoring project demonstrated the utility of this index for assessing wetland condition over time, including its sensitivity to a hurricane. Ultimately, the FQI developed for coastal Louisiana will be used in conjunction with other wetland indices (e.g., hydrology and soils) to assess wetland condition coastwide and these indices will aid managers in coastal restoration and management decisions.","language":"English","publisher":"Springer","doi":"10.1007/s10661-011-2125-4","usgsCitation":"Visser, M.J., Cretini, K., Krauss, K.W., and Steyer, G.D., 2012, Development and use of a floristic quality index for coastal Louisiana marshes: Environmental Monitoring and Assessment, v. 184, no. 4, p. 2389-2403, https://doi.org/10.1007/s10661-011-2125-4.","productDescription":"15 p.","startPage":"2389","endPage":"2403","ipdsId":"IP-020272","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":366962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": 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   ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"184","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Visser, M Jenneke Jenneke","contributorId":119531,"corporation":false,"usgs":true,"family":"Visser","given":"M","suffix":"Jenneke","email":"","middleInitial":"Jenneke","affiliations":[],"preferred":false,"id":513238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cretini, Kari 0000-0003-0419-0748","orcid":"https://orcid.org/0000-0003-0419-0748","contributorId":207226,"corporation":false,"usgs":true,"family":"Cretini","given":"Kari","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":769362,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70118981,"text":"70118981 - 2012 - MODFLOW-style parameters in underdetermined parameter estimation","interactions":[],"lastModifiedDate":"2024-04-24T16:19:51.813673","indexId":"70118981","displayToPublicDate":"2011-02-25T09:11:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"MODFLOW-style parameters in underdetermined parameter estimation","docAbstract":"<p><span>In this article, we discuss the use of MODFLOW-Style&nbsp;</span><i>parameters</i><span>&nbsp;in the numerical codes MODFLOW_2005 and MODFLOW_2005-Adjoint for the definition of variables in the Layer Property Flow package.&nbsp;</span><i>Parameters</i><span>&nbsp;are a useful tool to represent aquifer properties in both codes and are the only option available in the adjoint version. Moreover, for overdetermined parameter estimation problems, the&nbsp;</span><i>parameter</i><span>&nbsp;approach for model input can make data input easier. We found that if each estimable parameter is defined by one&nbsp;</span><i>parameter</i><span>, the codes require a large computational effort and substantial gains in efficiency are achieved by removing logical comparison of character strings that represent the names and types of the&nbsp;</span><i>parameters.</i><span>&nbsp;An alternative formulation already available in the current implementation of the code can also alleviate the efficiency degradation due to character comparisons in the special case of&nbsp;</span><i>distributed parameters</i><span>&nbsp;defined through multiplication matrices. The authors also hope that lessons learned in analyzing the performance of the MODFLOW family codes will be enlightening to developers of other Fortran implementations of numerical codes.</span></p>","language":"English","publisher":"National Groundwater Association","doi":"10.1111/j.1745-6584.2011.00803.x","usgsCitation":"D’Oria, M.D., and Fienen, M., 2012, MODFLOW-style parameters in underdetermined parameter estimation: Groundwater, v. 50, no. 1, p. 149-153, https://doi.org/10.1111/j.1745-6584.2011.00803.x.","productDescription":"5 p.","startPage":"149","endPage":"153","ipdsId":"IP-016755","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":291560,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-02-25","publicationStatus":"PW","scienceBaseUri":"53e09e5be4b0beb42bdca469","contributors":{"authors":[{"text":"D’Oria, Marco D.","contributorId":22258,"corporation":false,"usgs":true,"family":"D’Oria","given":"Marco","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":497550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":497549,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70036375,"text":"70036375 - 2012 - Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal","interactions":[],"lastModifiedDate":"2017-04-06T14:20:32","indexId":"70036375","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal","docAbstract":"<p><span>Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km</span><sup>2</sup><span> in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/bg-9-631-2012","issn":"18106277","usgsCitation":"Dieye, A., Roy, D.P., Hanan, N., Liu, S., Hansen, M., and Toure, A., 2012, Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal: Biogeosciences, v. 9, p. 631-648, https://doi.org/10.5194/bg-9-631-2012.","productDescription":"18 p.","startPage":"631","endPage":"648","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474697,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-9-631-2012","text":"Publisher Index Page"},{"id":246158,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2012-02-03","publicationStatus":"PW","scienceBaseUri":"505b8d24e4b08c986b318292","contributors":{"authors":[{"text":"Dieye, A.M.","contributorId":35988,"corporation":false,"usgs":true,"family":"Dieye","given":"A.M.","email":"","affiliations":[],"preferred":false,"id":455789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, David P.","contributorId":54761,"corporation":false,"usgs":false,"family":"Roy","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false},{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false},{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":455790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanan, N.P.","contributorId":82123,"corporation":false,"usgs":true,"family":"Hanan","given":"N.P.","affiliations":[],"preferred":false,"id":455791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, S.","contributorId":93170,"corporation":false,"usgs":true,"family":"Liu","given":"S.","affiliations":[],"preferred":false,"id":455792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, M.","contributorId":34670,"corporation":false,"usgs":true,"family":"Hansen","given":"M.","affiliations":[],"preferred":false,"id":455788,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Toure, A.","contributorId":98920,"corporation":false,"usgs":true,"family":"Toure","given":"A.","email":"","affiliations":[],"preferred":false,"id":455793,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70237802,"text":"70237802 - 2012 - Numerical simulations examining the possible role of anthropogenic and volcanic emissions during the 1997 Indonesian fires","interactions":[],"lastModifiedDate":"2022-10-25T10:58:15.17341","indexId":"70237802","displayToPublicDate":"2010-12-02T09:01:03","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12793,"text":"Air Quality, Atmosphere & Health","active":true,"publicationSubtype":{"id":10}},"title":"Numerical simulations examining the possible role of anthropogenic and volcanic emissions during the 1997 Indonesian fires","docAbstract":"<p><span>The regional atmospheric chemistry and climate model REMOTE has been used to conduct numerical simulations of the atmosphere during the catastrophic Indonesian fires of 1997. These simulations represent one possible scenario of the event, utilizing the RETRO wildland fire emission database. Emissions from the fires dominate the atmospheric concentrations of O</span><sub>3</sub><span>, CO, NO</span><sub>2</sub><span>, and SO</span><sub>2</sub><span>&nbsp;creating many possible exceedances of the Indonesian air quality standards. The scenario described here suggests that urban anthropogenic emissions contributed to the poor air quality due primarily to the fires. The urban air pollution may have increased the total number of people exposed to exceedances of the O</span><sub>3</sub><span>&nbsp;1-h standard by 17%. Secondary O</span><sub>3</sub><span>&nbsp;from anthropogenic emissions enhanced the conversion of SO</span><sub>2</sub><span>&nbsp;released by the fires to&nbsp;</span><span class=\"mathjax-tex\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msubsup><mrow class=&quot;MJX-TeXAtom-ORD&quot;><mrow class=&quot;MJX-TeXAtom-ORD&quot;><mi mathvariant=&quot;normal&quot;>S</mi><mi mathvariant=&quot;normal&quot;>O</mi></mrow></mrow><mn>4</mn><mrow class=&quot;MJX-TeXAtom-ORD&quot;><mn>2</mn><mo>&amp;#x2212;</mo></mrow></msubsup></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msubsup\"><span id=\"MathJax-Span-4\" class=\"texatom\"><span id=\"MathJax-Span-5\" class=\"mrow\"><span id=\"MathJax-Span-6\" class=\"texatom\"><span id=\"MathJax-Span-7\" class=\"mrow\"><span id=\"MathJax-Span-8\" class=\"mi\">S</span><span id=\"MathJax-Span-9\" class=\"mi\">O</span></span></span></span></span><sup><span id=\"MathJax-Span-10\" class=\"texatom\"><span id=\"MathJax-Span-11\" class=\"mrow\"><span id=\"MathJax-Span-12\" class=\"mn\">2</span><span id=\"MathJax-Span-13\" class=\"mo\">−</span></span></span></sup><sub><span id=\"MathJax-Span-14\" class=\"mn\">4</span></sub></span></span></span></span></span></span><span>, demonstrating that the urban pollution actively altered the atmospheric behavior and lifetime of the fire emissions. Under the conditions present during the fires, volcanic SO</span><sub>2</sub><span>&nbsp;emissions had a negligible influence on surface pollution.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s11869-010-0105-4","usgsCitation":"Pfeffer, M.A., Langmann, B., Heil, A., and Graf, H., 2012, Numerical simulations examining the possible role of anthropogenic and volcanic emissions during the 1997 Indonesian fires: Air Quality, Atmosphere & Health, v. 5, p. 277-292, https://doi.org/10.1007/s11869-010-0105-4.","productDescription":"16 p.","startPage":"277","endPage":"292","ipdsId":"IP-015123","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":474698,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11869-010-0105-4","text":"Publisher Index Page"},{"id":408657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, Indonesia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              117.5924087688469,\n              -22.044190232100448\n            ],\n            [\n              147.41177478692185,\n              -21.240008281154616\n            ],\n            [\n              143.1536814245564,\n              -10.581228199188786\n            ],\n            [\n              122.95751134770723,\n              3.5612064227482705\n            ],\n            [\n              115.25784717158785,\n              4.500549743223559\n            ],\n            [\n              114.82526028667945,\n              0.8421315654653654\n            ],\n            [\n              112.53337407375636,\n              1.3178108731174376\n            ],\n            [\n              109.22250289407305,\n              1.9046429719454494\n            ],\n            [\n              105.20040890559852,\n              -6.922567902936095\n            ],\n            [\n              117.5924087688469,\n              -22.044190232100448\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2010-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Pfeffer, Melissa A.","contributorId":298479,"corporation":false,"usgs":false,"family":"Pfeffer","given":"Melissa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":855683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langmann, Barbel","contributorId":298485,"corporation":false,"usgs":false,"family":"Langmann","given":"Barbel","email":"","affiliations":[],"preferred":false,"id":855712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heil, Angelika","contributorId":213987,"corporation":false,"usgs":false,"family":"Heil","given":"Angelika","email":"","affiliations":[{"id":38956,"text":"Max Planck Institute for Meteorology, Environmental Modeling, Hamburg, Germany","active":true,"usgs":false}],"preferred":false,"id":855713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graf, Hans-F.","contributorId":298486,"corporation":false,"usgs":false,"family":"Graf","given":"Hans-F.","email":"","affiliations":[],"preferred":false,"id":855714,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70156573,"text":"70156573 - 2012 - Canadian SAR remote sensing for the Terrestrial Wetland Global Change Research Network (TWGCRN)","interactions":[],"lastModifiedDate":"2022-04-13T14:56:01.266436","indexId":"70156573","displayToPublicDate":"2010-09-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Canadian SAR remote sensing for the Terrestrial Wetland Global Change Research Network (TWGCRN)","docAbstract":"<p><span>The Canada Centre for Remote Sensing (CCRS) has more than 30 years of experience investigating the use of SAR remote sensing for many applications related to terrestrial water resources. Recently, CCRS scientists began contributing to the Terrestrial Wetland Global Change Research Network (TWGCRN), a bi-national research network dedicated to assessing impacts of global change on interconnected wetland-upland landscapes across a vital portion of North America. CCRS scientists are applying SAR remote sensing to characterize wetland components of these landscapes in three ways. First, they are using a comprehensive set of RADARSAT-2 SAR data collected during April to September 2009 to extract multi-temporal surface water information for key TWGCRN study landscapes in North America. Second, they are analyzing polarimetric RADARSAT-2 data to determine areas where double-bounce represents the primary scattering mechanism and is indicative of flooded vegetation in these landscapes. Third, they are testing advanced interferometric SAR techniques to estimate water levels with RADARSAT-2 Fine Quad polarimetric image pairs. The combined information from these three SAR analysis activities will provide TWGCRN scientists with an integrated view and monitoring capability for these dynamic wetland-upland landscapes. These data are being used in conjunction with other remote sensing and field data to study interactions between landscape and animal (birds and amphibians) responses to climate/global change.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Remote Sensing and Hydrology (Proceedings of a symposium held at Jackson Hole, Wyoming, USA, September 2010) (IAHS Publ. 352, 2012)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Remote Sensing and Hydrology 2010 Symposium","conferenceDate":"September 27-30, 2010","conferenceLocation":"Jackson Hole, Wyoming","language":"English","publisher":"IAHS","usgsCitation":"Kaya, S., Brisco, B., Cull, A., Gallant, A.L., Sadinski, W.J., and Thompson, D., 2012, Canadian SAR remote sensing for the Terrestrial Wetland Global Change Research Network (TWGCRN), <i>in</i> Remote Sensing and Hydrology (Proceedings of a symposium held at Jackson Hole, Wyoming, USA, September 2010) (IAHS Publ. 352, 2012), Jackson Hole, Wyoming, September 27-30, 2010, p. 380-383.","productDescription":"4 p.","startPage":"380","endPage":"383","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-023892","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":307330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe821de4b0824b2d148459","contributors":{"authors":[{"text":"Kaya, Shannon","contributorId":119420,"corporation":false,"usgs":true,"family":"Kaya","given":"Shannon","affiliations":[],"preferred":false,"id":569543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brisco, Brian","contributorId":37665,"corporation":false,"usgs":true,"family":"Brisco","given":"Brian","email":"","affiliations":[],"preferred":false,"id":569544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cull, Andrew","contributorId":117263,"corporation":false,"usgs":true,"family":"Cull","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":569545,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","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":569546,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sadinski, Walter J. wsadinski@usgs.gov","contributorId":3287,"corporation":false,"usgs":true,"family":"Sadinski","given":"Walter","email":"wsadinski@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":569547,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Dean","contributorId":120162,"corporation":false,"usgs":true,"family":"Thompson","given":"Dean","email":"","affiliations":[],"preferred":false,"id":569548,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":58155,"text":"ofr20041344 - 2012 - Version 3.0 of EMINERS - Economic Mineral Resource Simulator","interactions":[{"subject":{"id":50697,"text":"ofr02380 - 2002 - EMINERS -- An Economic Mineral Resource Simulator","indexId":"ofr02380","publicationYear":"2002","noYear":false,"title":"EMINERS -- An Economic Mineral Resource Simulator"},"predicate":"SUPERSEDED_BY","object":{"id":58155,"text":"ofr20041344 - 2012 - Version 3.0 of EMINERS - Economic Mineral Resource Simulator","indexId":"ofr20041344","publicationYear":"2012","noYear":false,"title":"Version 3.0 of EMINERS - Economic Mineral Resource Simulator"},"id":1}],"lastModifiedDate":"2012-07-03T17:03:08","indexId":"ofr20041344","displayToPublicDate":"2004-11-01T02:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2004-1344","title":"Version 3.0 of EMINERS - Economic Mineral Resource Simulator","docAbstract":"Quantitative mineral resource assessment, as developed by the U.S. Geological Survey (USGS), consists of three parts: (1) development of grade and tonnage mineral deposit models; (2) delineation of tracts permissive for each deposit type; and (3) probabilistic estimation of the numbers of undiscovered deposits for each deposit type. The estimate of the number of undiscovered deposits at different levels of probability is the input to the EMINERS (Economic Mineral Resource Simulator) program. EMINERS uses a Monte Carlo statistical process to combine probabilistic estimates of undiscovered mineral deposits with models of mineral deposit grade and tonnage to estimate mineral resources. Version 3.0 of the EMINERS program is available as this USGS Open-File Report 2004-1344. Changes from version 2.0 include updating 87 grade and tonnage models, designing new templates to produce graphs showing cumulative distribution and summary tables, and disabling economic filters. The economic filters were disabled because embedded data for costs of labor and materials, mining techniques, and beneficiation methods are out of date. However, the cost algorithms used in the disabled economic filters are still in the program and available for reference for mining methods and milling techniques. The release notes included with this report give more details on changes in EMINERS over the years. EMINERS is written in C++ and depends upon the Microsoft Visual C++ 6.0 programming environment. The code depends heavily on the use of Microsoft Foundation Classes (MFC) for implementation of the Windows interface. The program works only on Microsoft Windows XP or newer personal computers. It does not work on Macintosh computers. For help in using the program in this report, see the \"Quick-Start Guide for Version 3.0 of EMINERS-Economic Mineral Resource Simulator\" (W.J. Bawiec and G.T. Spanski, 2012, USGS Open-File Report 2009-1057, linked at right). It demonstrates how to execute EMINERS software using default settings and existing deposit models.","language":"English","publisher":"U.S. Gelogical Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20041344","collaboration":"Version 3.0 is an update to USGS Open-File Report 2004-1344, which originally was version 2.0 of EMINERS by J.S. Duval","usgsCitation":"Duval, J.S., 2012, Version 3.0 of EMINERS - Economic Mineral Resource Simulator (Version 3.0 of EMINERS updates version 2.0; Version 2.0 supersedes Open-File Report 2002-0380): U.S. Geological Survey Open-File Report 2004-1344, Readme: 4 p.; EMINERS Verison 3.0 Zip;  Release Notes: 4 p., https://doi.org/10.3133/ofr20041344.","productDescription":"Readme: 4 p.; EMINERS Verison 3.0 Zip;  Release Notes: 4 p.","onlineOnly":"Y","costCenters":[{"id":410,"text":"National Center","active":false,"usgs":true}],"links":[{"id":185448,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2004_1344.jpg"},{"id":5769,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2004/1344/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 3.0 of EMINERS updates version 2.0; Version 2.0 supersedes Open-File Report 2002-0380","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4affe4b07f02db697c48","contributors":{"authors":[{"text":"Duval, Joseph S.","contributorId":22314,"corporation":false,"usgs":true,"family":"Duval","given":"Joseph","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":258411,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":39853,"text":"twri09A6.6 - 2012 - Chapter A6. Section 6.6. Alkalinity and acid neutralizing capacity","interactions":[],"lastModifiedDate":"2019-05-28T12:21:40","indexId":"twri09A6.6","displayToPublicDate":"1999-01-10T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":336,"text":"Techniques of Water-Resources Investigations","code":"TWRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"09-A6.6","title":"Chapter A6. Section 6.6. Alkalinity and acid neutralizing capacity","docAbstract":"<p>Alkalinity (determined on a filtered sample) and Acid Neutralizing Capacity (ANC) (determined on a whole-water sample) are measures of the ability of a water sample to neutralize strong acid. Alkalinity and ANC provide information on the suitability of water for uses such as irrigation, determining the efficiency of wastewater processes, determining the presence of contamination by anthropogenic wastes, and maintaining ecosystem health. In addition, alkalinity is used to gain insights on the chemical evolution of an aqueous system. This section of the National Field Manual (NFM) describes the USGS field protocols for alkalinity/ANC determination using either the inflection-point or Gran function plot methods, including calculation of carbonate species, and provides guidance on equipment selection. Newly published and revised chapters will be announced on the USGS Home Page on the World Wide Web under 'New Publications of the U.S. Geological Survey.'</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"National Field Manual for the Collection of Water-Quality Data. U.S. Geological Survey Techniques of Water-Resources Investigations, Book 9","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/twri09A6.6","usgsCitation":"Rounds, S.A., and Wilde, F.D., 2012, Chapter A6. Section 6.6. Alkalinity and acid neutralizing capacity (Version 3, Revised Jul 2006): U.S. Geological Survey Techniques of Water-Resources Investigations 09-A6.6, 53 p., https://doi.org/10.3133/twri09A6.6.","productDescription":"53 p.","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":172683,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":363018,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/twri/twri9a6/twri9a66/twri9a_chapter6.6_9-2001.pdf","text":"Report September 2001","size":"692 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Second Edition (without comments)"},{"id":363017,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/twri/twri9a6/twri9a66/twri9a_Section6.6_4-98.pdf","text":"Report April 1998","size":"131 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Original Report"},{"id":363697,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm9A0","text":"Techniques and Methods 9-AO","linkHelpText":"- General Introduction for the “National Field Manual for the Collection of Water-Quality Data”"},{"id":363019,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/twri/twri9a6/twri9a66/twri9a_chapter6.6.pdf","text":"Report September 2001","size":"3.95 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Second Edition (with comment updates)"},{"id":363020,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/twri/twri9a6/twri9a66/twri9a_chapter6.6._v3.pdf","text":"Report July 2006","size":"414 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Third Edition"},{"id":3567,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/twri/twri9a6/twri9a66/twri9a_6.6.pdf","text":"Report","size":"648 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TWRI 9a6.6"}],"edition":"Version 3, Revised Jul 2006","contact":"<p><a href=\"https://www.usgs.gov/mission-areas/water-resources?qt-mission_areas_l2_landing_page_ta=0#qt-mission_areas_l2_landing_page_ta\" data-mce-href=\"https://www.usgs.gov/mission-areas/water-resources?qt-mission_areas_l2_landing_page_ta=0#qt-mission_areas_l2_landing_page_ta\">Water Mission Area</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:nfm@usgs.gov\" data-mce-href=\"mailto:nfm@usgs.gov\">nfm@usgs.gov</a></p>","tableOfContents":"<ul><li>6.6 Alkalinity and Acid Neutralizing Capacity</li><li>6.6.1 Equipment and Supplies</li><li>6.6.2 Calibration and Standardization</li><li>6.6.3 Collection and Processing</li><li>6.6.4 Measurement</li><li>6.6.5 Calculations</li><li>6.6.6 Troubleshooting</li><li>6.6.7 Reporting</li><li>Selected References</li><li>Acknowledgments</li></ul>","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49dfe4b07f02db5e36d8","contributors":{"authors":[{"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":222430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilde, Franceska D. fwilde@usgs.gov","contributorId":92240,"corporation":false,"usgs":true,"family":"Wilde","given":"Franceska","email":"fwilde@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":false,"id":222431,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005585,"text":"ofr20111258 - 2011 - Notes on interpretation of geophysical data over areas of mineralization in Afghanistan","interactions":[],"lastModifiedDate":"2020-01-15T09:44:52","indexId":"ofr20111258","displayToPublicDate":"2020-01-15T10:50:00","publicationYear":"2011","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":"2011-1258","displayTitle":"Notes on Interpretation of Geophysical Data Over Areas of Mineralization in Afghanistan","title":"Notes on interpretation of geophysical data over areas of mineralization in Afghanistan","docAbstract":"<p>Afghanistan has the potential to contain substantial metallic mineral resources. Although valuable mineral deposits have been identified, much of the country’s potential remains unknown. Geophysical surveys, particularly those conducted from airborne platforms, are a well-accepted and cost-effective method for obtaining information on the geological setting of a given area. This report summarizes interpretive findings from various geophysical surveys over selected mineral targets in Afghanistan, highlighting what existing data tell us. These interpretations are mainly qualitative in nature, because of the low resolution of available geophysical data.</p><p>Geophysical data and simple interpretations are included for these six areas and deposit types: (1) Aynak: Sedimentary-hosted copper; (2) Zarkashan: Porphyry copper; (3) Kundalan: Porphyry copper; (4) Dusar Shaida: Volcanic-hosted massive sulphide; (5) Khanneshin: Carbonatite-hosted rare earth element; and (6) Chagai Hills: Porphyry copper.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111258","usgsCitation":"Drenth, B.J., 2011, Notes on interpretation of geophysical data over areas of mineralization in Afghanistan: U.S. Geological Survey Open-File Report 2011–1258, 13 p.","productDescription":"iv, 13 p.","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":371064,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2011/1258/ofr20111258.pdf","text":"Report","size":"9.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2011-1258"},{"id":371063,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2011/1258/coverthb4.jpg"}],"country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60,29 ], [ 60,38 ], [ 75,38 ], [ 75,29 ], [ 60,29 ] ] ] } } ] }","contact":"<p><a href=\"https://www.usgs.gov/centers/gggsc\" data-mce-href=\"https://www.usgs.gov/centers/gggsc\">Crustal Geophysics and Geochemistry Science Center</a><br>Box 25046, Mail Stop 964<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Introduction</li><li>Aynak</li><li>Zarkashan</li><li>Kundalan</li><li>Dusar-Shaida</li><li>Khanneshin</li><li>Chagai Hills</li><li>Conclusions</li><li>References Cited</li></ul>","publishedDate":"2011-09-29","noUsgsAuthors":false,"publicationDate":"2011-09-29","publicationStatus":"PW","scienceBaseUri":"4f4e4afde4b07f02db696b70","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":352874,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
]}