{"pageNumber":"599","pageRowStart":"14950","pageSize":"25","recordCount":40829,"records":[{"id":70102827,"text":"ofr20141083 - 2014 - Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States","interactions":[],"lastModifiedDate":"2014-06-06T15:53:08","indexId":"ofr20141083","displayToPublicDate":"2014-06-06T15:50:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1083","title":"Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States","docAbstract":"Sea-level rise is an ongoing phenomenon that is expected to continue and is projected to have a wide range of effects on coastal environments and infrastructure during the 21st century and beyond. Consequently, there is a need to assemble relevant datasets and to develop modeling or other analytical approaches to evaluate the likelihood of particular sea-level rise impacts, such as coastal erosion, and to inform coastal management decisions with this information. This report builds on previous work that compiled oceanographic and geomorphic data as part of the U.S. Geological Survey’s Coastal Vulnerability Index (CVI) for the U.S. Atlantic coast, and developed a Bayesian Network to predict shoreline-change rates based on sea-level rise plus variables that describe the hydrodynamic and geologic setting. This report extends the previous analysis to include the Gulf and Pacific coasts of the continental United States and Alaska and Hawaii, which required using methods applied to the USGS CVI dataset to extract data for these regions. The Bayesian Network converts inputs that include observations of local rates of relative sea-level change, mean wave height, mean tide range, a geomorphic classification, coastal slope, and observed shoreline-change rates to calculate the probability of the shoreline-erosion rate exceeding a threshold level of 1 meter per year for the coasts of the United States. The calculated probabilities were compared to the historical observations of shoreline change to evaluate the hindcast success rate of the most likely probability of shoreline change. Highest accuracy was determined for the coast of Hawaii (98 percent success rate) and lowest accuracy was determined for the Gulf of Mexico (34 percent success rate). The minimum success rate rose to nearly 80 percent (Atlantic and Gulf coasts) when success included shoreline-change outcomes that were adjacent to the most likely outcome. Additionally, the probabilistic approach determines the confidence in calculated outcomes as the probability of the most likely outcome. The confidence was highest along the Pacific coast and it was lowest along the Alaskan coast.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141083","issn":"2331-1258","usgsCitation":"Gutierrez, B.T., Plant, N.G., Pendleton, E., and Thieler, E.R., 2014, Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States: U.S. Geological Survey Open-File Report 2014-1083, v, 26 p., https://doi.org/10.3133/ofr20141083.","productDescription":"v, 26 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-053816","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141083.jpg"},{"id":288158,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1083/"},{"id":288159,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1083/pdf/ofr2014-1083.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130.0,20.0 ], [ -130.0,50.0 ], [ -60.0,50.0 ], [ -60.0,20.0 ], [ -130.0,20.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae789ce4b0abf75cf2da90","contributors":{"authors":[{"text":"Gutierrez, Benjamin T.","contributorId":58670,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":493044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":493043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pendleton, Elizabeth A.","contributorId":101312,"corporation":false,"usgs":true,"family":"Pendleton","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":493045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493042,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70112937,"text":"70112937 - 2014 - Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA","interactions":[],"lastModifiedDate":"2018-01-02T12:28:30","indexId":"70112937","displayToPublicDate":"2014-06-06T14:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA","docAbstract":"<p>1.  Analyses of flower-visitor interaction networks allow application of community-level information to conservation problems, but management recommendations that ensue from such analyses are not well characterized. Results of modularity analyses, which detect groups of species (modules) that interact more with each other than with species outside their module, may be particularly applicable to management concerns.</p>\n<br>\n<p>2.  We conducted modularity analyses of networks surrounding a rare endemic annual plant, <i>Eriogonum visheri</i>, at Badlands National Park, USA, in 2010 and 2011. Plant species visited were determined by pollen on insect bodies and by flower species upon which insects were captured. Roles within modules (network hub, module hub, connector and peripheral, in decreasing order of network structural importance) were determined for each species.</p>\n<br>\n<p>3.  Relationships demonstrated by the modularity analysis, in concert with knowledge of pollen species carried by insects, allowed us to infer effects of two invasive species on <i>E. visheri</i>. Sharing a module increased risk of interspecific pollen transfer to <i>E. visheri</i>. Control of invasive <i>Salsola tragus</i>, which shared a module with <i>E. visheri</i>, is therefore a prudent management objective, but lack of control of invasive <i>Melilotus officinalis</i>, which occupied a different module, is unlikely to negatively affect pollination of <i>E. visheri</i>. <i>Eriogonum pauciflorum</i> may occupy a key position in this network, supporting insects from the <i>E. visheri</i> module when <i>E. visheri</i> is less abundant.</p>\n<br>\n<p>4.  Year-to-year variation in species' roles suggests management decisions must be based on observations over several years. Information on pollen deposition on stigmas would greatly strengthen inferences made from the modularity analysis.</p>\n<br>\n<p>5.  Synthesis and applications: Assessing the consequences of pollination, whether at the community or individual level, is inherently time-consuming. A trade-off exists: rather than an estimate of fitness effects, the network approach provides a broad understanding of the relationships among insect visitors and other plant species that may affect the focal rare plant. Knowledge of such relationships allows managers to detect, target and prioritize control of only the important subset of invasive species present and identify other species that may augment a rare species' population stability, such as <i>E. pauciflorum</i> in our study.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.12273","usgsCitation":"Larson, D.L., Droege, S., Rabie, P.A., Larson, J.L., Devalez, J., Haar, M., and McDermott-Kubeczko, M., 2014, Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA: Journal of Applied Ecology, v. 51, no. 4, p. 1024-1032, https://doi.org/10.1111/1365-2664.12273.","productDescription":"9 p.","startPage":"1024","endPage":"1032","ipdsId":"IP-052981","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12273","text":"Publisher Index Page"},{"id":288828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288827,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2664.12273"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -102.9,43.48 ], [ -102.9,43.92 ], [ -101.89,43.92 ], [ -101.89,43.48 ], [ -102.9,43.48 ] ] ] } } ] }","volume":"51","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"53ae789de4b0abf75cf2daa8","chorus":{"doi":"10.1111/1365-2664.12273","url":"http://dx.doi.org/10.1111/1365-2664.12273","publisher":"Wiley-Blackwell","authors":"Larson Diane L., Droege Sam, Rabie Paul A., Larson Jennifer L., Devalez Jelle, Haar Milton, McDermott-Kubeczko Margaret","journalName":"Journal of Applied Ecology","publicationDate":"6/6/2014"},"contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":494950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Droege, Sam sdroege@usgs.gov","contributorId":3464,"corporation":false,"usgs":true,"family":"Droege","given":"Sam","email":"sdroege@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":494951,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rabie, Paul A. 0000-0003-4364-2268","orcid":"https://orcid.org/0000-0003-4364-2268","contributorId":74328,"corporation":false,"usgs":true,"family":"Rabie","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":true,"id":494955,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, Jennifer L. 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":68144,"corporation":false,"usgs":true,"family":"Larson","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":494954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Devalez, Jelle","contributorId":24690,"corporation":false,"usgs":true,"family":"Devalez","given":"Jelle","email":"","affiliations":[],"preferred":false,"id":494953,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haar, Milton","contributorId":14302,"corporation":false,"usgs":true,"family":"Haar","given":"Milton","email":"","affiliations":[],"preferred":false,"id":494952,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McDermott-Kubeczko, Margaret","contributorId":91024,"corporation":false,"usgs":true,"family":"McDermott-Kubeczko","given":"Margaret","affiliations":[],"preferred":false,"id":494956,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70111688,"text":"70111688 - 2014 - Natural uranium and strontium isotope tracers of water sources and surface water-groundwater interactions in arid wetlands: Pahranagat Valley, Nevada, USA","interactions":[],"lastModifiedDate":"2014-06-06T11:53:25","indexId":"70111688","displayToPublicDate":"2014-06-06T11:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Natural uranium and strontium isotope tracers of water sources and surface water-groundwater interactions in arid wetlands: Pahranagat Valley, Nevada, USA","docAbstract":"Near-surface physical and chemical process can strongly affect dissolved-ion concentrations and stable isotope compositions of water in wetland settings, especially under arid climate conditions.  In contrast, heavy radiogenic isotopes of strontium (<sup>87</sup>Sr/<sup>86</sup>Sr) and uranium (<sup>234</sup>U/<sup>238</sup>U) remain largely unaffected and can be used to help identify unique signatures from different sources and quantify end-member mixing that would otherwise be difficult to determine.  The utility of combined Sr and U isotopes are demonstrated in this study of wetland habitats on the Pahranagat National Wildlife Refuge, which depend on supply from large-volume springs north of the Refuge, and from small-volume springs and seeps within the Refuge.  Water budgets from these sources have not been quantified previously.  Evaporation, transpiration, seasonally variable surface flow, and water management practices complicate the use of conventional methods for determining source contributions and mixing relations.  In contrast, <sup>87</sup>Sr/<sup>86</sup>Sr and <sup>234</sup>U/<sup>238</sup>U remain unfractionated under these conditions, and compositions at a given site remain constant.  Differences in Sr- and U-isotopic signatures between individual sites can be related by simple two- or three-component mixing models.  Results indicate that surface flow constituting the Refuge’s irrigation source consists of a 65:25:10 mixture of water from two distinct regionally sourced carbonate aquifer springs, and groundwater from locally sourced volcanic aquifers.  Within the Refuge, contributions from the irrigation source and local groundwater are readily determined and depend on proximity to those sources as well as water management practices.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.05.011","usgsCitation":"Paces, J.B., and Wurster, F.C., 2014, Natural uranium and strontium isotope tracers of water sources and surface water-groundwater interactions in arid wetlands: Pahranagat Valley, Nevada, USA: Journal of Hydrology, v. 517, p. 213-225, https://doi.org/10.1016/j.jhydrol.2014.05.011.","productDescription":"13 p.","startPage":"213","endPage":"225","numberOfPages":"13","ipdsId":"IP-049329","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":288145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288135,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2014.05.011"}],"country":"United States","state":"Nevada","otherGeospatial":"Pahranagat Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115.313393,37.187186 ], [ -115.313393,37.618914 ], [ -115.025947,37.618914 ], [ -115.025947,37.187186 ], [ -115.313393,37.187186 ] ] ] } } ] }","volume":"517","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7782e4b0abf75cf2c161","contributors":{"authors":[{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":494438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wurster, Frederic C. 0000-0002-5393-2878 fred_wurster@fws.gov","orcid":"https://orcid.org/0000-0002-5393-2878","contributorId":74301,"corporation":false,"usgs":true,"family":"Wurster","given":"Frederic","email":"fred_wurster@fws.gov","middleInitial":"C.","affiliations":[],"preferred":false,"id":494439,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70173453,"text":"70173453 - 2014 - Comparative bioenergetics modeling of two Lake Trout morphotypes","interactions":[],"lastModifiedDate":"2016-06-20T12:20:20","indexId":"70173453","displayToPublicDate":"2014-06-06T06:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Comparative bioenergetics modeling of two Lake Trout morphotypes","docAbstract":"<p><span>Efforts to restore Lake Trout&nbsp;</span><i>Salvelinus namaycush</i><span>&nbsp;in the Laurentian Great Lakes have been hampered for decades by several factors, including overfishing and invasive species (e.g., parasitism by Sea Lampreys&nbsp;</span><i>Petromyzon marinus</i><span>&nbsp;and reproductive deficiencies associated with consumption of Alewives&nbsp;</span><i>Alosa pseudoharengus</i><span>). Restoration efforts are complicated by the presence of multiple body forms (i.e., morphotypes) of Lake Trout that differ in habitat utilization, prey consumption, lipid storage, and spawning preferences. Bioenergetics models constitute one tool that is used to help inform management and restoration decisions; however, bioenergetic differences among morphotypes have not been evaluated. The goal of this research was to investigate bioenergetic differences between two actively stocked morphotypes: lean and humper Lake Trout. We measured consumption and respiration rates across a wide range of temperatures (4&ndash;22&deg;C) and size-classes (5&ndash;100&nbsp;g) to develop bioenergetics models for juvenile Lake Trout. Bayesian estimation was used so that uncertainty could be propagated through final growth predictions. Differences between morphotypes were minimal, but when present, the differences were temperature and weight dependent. Basal respiration did not differ between morphotypes at any temperature or size-class. When growth and consumption differed between morphotypes, the differences were not consistent across the size ranges tested. Management scenarios utilizing the temperatures presently found in the Great Lakes (e.g., predicted growth at an average temperature of 11.7&deg;C and 14.4&deg;C during a 30-d period) demonstrated no difference in growth between the two morphotypes. Due to a lack of consistent differences between lean and humper Lake Trout, we developed a model that combined data from both morphotypes. The combined model yielded results similar to those of the morphotype-specific models, suggesting that accounting for morphotype differences may not be necessary in bioenergetics modeling of lean and humper Lake Trout.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2014.954051","usgsCitation":"Kepler, M.V., Wagner, T., and Sweka, J.A., 2014, Comparative bioenergetics modeling of two Lake Trout morphotypes: Transactions of the American Fisheries Society, v. 143, no. 6, p. 1592-1604, https://doi.org/10.1080/00028487.2014.954051.","productDescription":"13 p.","startPage":"1592","endPage":"1604","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052962","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":472948,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Comparative_Bioenergetics_Modeling_of_Two_Lake_Trout_Morphotypes/1246729","text":"External Repository"},{"id":323990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-30","publicationStatus":"PW","scienceBaseUri":"576913b4e4b07657d19fefed","contributors":{"authors":[{"text":"Kepler, Megan V.","contributorId":172106,"corporation":false,"usgs":false,"family":"Kepler","given":"Megan","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":639792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweka, John A.","contributorId":80945,"corporation":false,"usgs":true,"family":"Sweka","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639793,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70132329,"text":"70132329 - 2014 - A new clarification method to visualize biliary degeneration during liver metamorphosis in sea lamprey (<i>Petromyzon marinus</i>)","interactions":[],"lastModifiedDate":"2021-12-09T15:28:15.105111","indexId":"70132329","displayToPublicDate":"2014-06-06T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"title":"A new clarification method to visualize biliary degeneration during liver metamorphosis in sea lamprey (<i>Petromyzon marinus</i>)","docAbstract":"<p><span>Biliary atresia is a rare disease of infancy, with an estimated 1 in 15,000 frequency in the southeast United States, but more common in East Asian countries, with a reported frequency of 1 in 5,000 in Taiwan. Although much is known about the management of biliary atresia, its pathogenesis is still elusive. The sea lamprey (</span><i>Petromyzon marinus</i><span>) provides a unique opportunity to examine the mechanism and progression of biliary degeneration. Sea lamprey develop through three distinct life stages: larval, parasitic, and adult. During the transition from<span>&nbsp;</span></span>larvae<span><span>&nbsp;</span>to parasitic juvenile, sea lamprey undergo metamorphosis with dramatic reorganization and remodeling in external morphology and internal organs. In the liver, the entire biliary system is lost, including the gall bladder and the biliary tree. A newly-developed method called &ldquo;CLARITY&rdquo; was modified to clarify the entire liver and the junction with the intestine in metamorphic sea lamprey. The process of biliary degeneration was visualized and discerned during sea lamprey metamorphosis by using laser scanning confocal microscopy. This method provides a powerful tool to study biliary atresia in a unique animal model.</span></p>","language":"English","publisher":"JoVE","publisherLocation":"Cambridge, MA","doi":"10.3791/51648","usgsCitation":"Chung-Davidson, Y., Davidson, P.J., Scott, A.M., Walaszczyk, E.J., Brant, C.O., Buchinger, T., Johnson, N.S., and Li, W., 2014, A new clarification method to visualize biliary degeneration during liver metamorphosis in sea lamprey (<i>Petromyzon marinus</i>): Journal of Visualized Experiments, v. 88, e51648, https://doi.org/10.3791/51648.","productDescription":"e51648","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052484","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472949,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3791/51648","text":"External Repository"},{"id":297315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"54dd2b1ee4b08de9379b3255","contributors":{"authors":[{"text":"Chung-Davidson, Yu-Wen","contributorId":126742,"corporation":false,"usgs":false,"family":"Chung-Davidson","given":"Yu-Wen","email":"","affiliations":[{"id":6589,"text":"Department of Fisheries & Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davidson, Peter J.","contributorId":126743,"corporation":false,"usgs":false,"family":"Davidson","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scott, Anne M.","contributorId":126744,"corporation":false,"usgs":false,"family":"Scott","given":"Anne","email":"","middleInitial":"M.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walaszczyk, Erin J.","contributorId":126745,"corporation":false,"usgs":false,"family":"Walaszczyk","given":"Erin","email":"","middleInitial":"J.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brant, Cory O.","contributorId":126746,"corporation":false,"usgs":false,"family":"Brant","given":"Cory","email":"","middleInitial":"O.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522777,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buchinger, Tyler","contributorId":126747,"corporation":false,"usgs":false,"family":"Buchinger","given":"Tyler","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522778,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":522772,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Li, Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":522779,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70111602,"text":"sir20145072 - 2014 - Concentrations, loads, and yields of total nitrogen and total phosphorus in the Barnegat Bay-Little Egg Harbor watershed, New Jersey, 1989-2011, at multiple spatial scales","interactions":[],"lastModifiedDate":"2014-06-05T14:55:51","indexId":"sir20145072","displayToPublicDate":"2014-06-05T14:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5072","title":"Concentrations, loads, and yields of total nitrogen and total phosphorus in the Barnegat Bay-Little Egg Harbor watershed, New Jersey, 1989-2011, at multiple spatial scales","docAbstract":"<p>Concentrations, loads, and yields of nutrients (total nitrogen and total phosphorus) were calculated for the Barnegat Bay-Little Egg Harbor (BB-LEH) watershed for 1989–2011 at annual and seasonal (growing and nongrowing) time scales. Concentrations, loads, and yields were calculated at three spatial scales: for each of the 81 subbasins specified by 14-digit hydrologic unit codes (HUC-14s); for each of the three BB-LEH watershed segments, which coincide with segmentation of the BB-LEH estuary; and for the entire BB-LEH watershed. Base-flow and runoff values were calculated separately and were combined to provide total values.</p>\n<br/>\n<p>Available surface-water-quality data for all streams in the BB-LEH watershed for 1980–2011 were compiled from existing datasets and quality assured. Precipitation and streamflow data were used to distinguish between water-quality samples that were collected during base-flow conditions and those that were collected during runoff conditions. Base-flow separation of hydrographs of six streams in the BB-LEH watershed indicated that base flow accounts for about 72 to 94 percent of total flow in streams in the watershed.</p>\n<br/>\n<p>Base-flow mean concentrations (BMCs) of total nitrogen (TN) and total phosphorus (TP) for each HUC-14 subbasin were calculated from relations between land use and measured base-flow concentrations. These relations were developed from multiple linear regression models determined from water-quality data collected at sampling stations in the BB-LEH watershed under base-flow conditions and land-use percentages in the contributing drainage basins. The total watershed base-flow volume was estimated for each year and season from continuous streamflow records for 1989–2011 and relations between precipitation and streamflow during base-flow conditions. For each year and season, the base-flow load and yield were then calculated for each HUC-14 subbasin from the BMCs, total base-flow volume, and drainage area.</p>\n<br/>\n<p>The watershed-loading application PLOAD was used to calculate runoff concentrations, loads, and yields of TN and TP at the HUC-14 scale. Flow-weighted event-mean concentrations (EMCs) for runoff were developed for each major land-use type in the watershed using storm sampling data from four streams in the BB-LEH watershed and three streams outside the watershed. The EMCs were developed separately for the growing and nongrowing seasons, and were typically greater during the growing season. The EMCs, along with annual and seasonal precipitation amounts and percent imperviousness associated with land-use types, were used as inputs to PLOAD to calculate annual and seasonal runoff concentrations, loads, and yields at the HUC-14 scale.</p>\n<br/>\n<p>Over the period of study (1989–2011), total surface-water loads (base flow plus runoff) for the entire BB-LEH watershed for TN ranged from about 455,000 kilograms (kg) as N (1995) to 857,000 kg as N (2010). For TP, total loads for the watershed ranged from about 17,000 (1995) to 32,000 kg as P (2010). On average, the north segment accounted for about 66 percent of the annual TN load and 63 percent of the annual TP load, and the central and south segments each accounted for less than 20 percent of the nutrient loads. Loads and yields were strongly associated with precipitation patterns, ensuing hydrologic conditions, and land use. HUC-14 subbasins with the highest yields of nutrients are concentrated in the northern part of the watershed, and have the highest percentages of urban or agricultural land use. Subbasins with the lowest TN and TP yields are dominated by forest cover.</p>\n<br/>\n<p>Percentages of turf (lawn) cover and nonturf cover were estimated for the watershed. Of the developed land in the watershed, nearly one quarter (24.9 percent) was mapped as turf cover. Because there is a strong relation between percent turf and percent developed land, percent turf in the watershed typically increases with percent development, and the amount of development can be considered a reasonable predictor of the amount of turf cover in the watershed. In the BB-LEH watershed, calculated concentrations of TN and TP were greater for developed–turf areas than for developed–nonturf areas, which, in turn, were greater than those for undeveloped areas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145072","collaboration":"Prepared in cooperation with the New England Interstate Water Pollution Control Commission","usgsCitation":"Baker, R.J., Wieben, C.M., Lathrop, R.G., and Nicholson, R.S., 2014, Concentrations, loads, and yields of total nitrogen and total phosphorus in the Barnegat Bay-Little Egg Harbor watershed, New Jersey, 1989-2011, at multiple spatial scales: U.S. Geological Survey Scientific Investigations Report 2014-5072, Report: vii, 64 p.; Table 13, https://doi.org/10.3133/sir20145072.","productDescription":"Report: vii, 64 p.; Table 13","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1989-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-039063","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":288123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145072.jpg"},{"id":288120,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5072/"},{"id":288122,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5072/pdf/sir2014-5072.pdf"},{"id":288121,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5072/table/sir2014-5072_table13-loads-huc.xlsx"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay;Little Egg Harbor","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.6007,39.4669 ], [ -74.6007,40.2311 ], [ -73.9678,40.2311 ], [ -73.9678,39.4669 ], [ -74.6007,39.4669 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5391834fe4b06f80638265a0","contributors":{"authors":[{"text":"Baker, Ronald J. rbaker@usgs.gov","contributorId":1436,"corporation":false,"usgs":true,"family":"Baker","given":"Ronald","email":"rbaker@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wieben, Christine M. 0000-0001-5825-5119 cwieben@usgs.gov","orcid":"https://orcid.org/0000-0001-5825-5119","contributorId":4270,"corporation":false,"usgs":true,"family":"Wieben","given":"Christine","email":"cwieben@usgs.gov","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lathrop, Richard G.","contributorId":63727,"corporation":false,"usgs":true,"family":"Lathrop","given":"Richard","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":494377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nicholson, Robert S. rnichol@usgs.gov","contributorId":2283,"corporation":false,"usgs":true,"family":"Nicholson","given":"Robert","email":"rnichol@usgs.gov","middleInitial":"S.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494375,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70103475,"text":"sir20145083 - 2014 - Monitoring recharge in areas of seasonally frozen ground in the Columbia Plateau and Snake River Plain, Idaho, Oregon, and Washington","interactions":[],"lastModifiedDate":"2014-06-05T08:45:59","indexId":"sir20145083","displayToPublicDate":"2014-06-05T08:26:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5083","title":"Monitoring recharge in areas of seasonally frozen ground in the Columbia Plateau and Snake River Plain, Idaho, Oregon, and Washington","docAbstract":"<p>Seasonally frozen ground occurs over approximately one‑third of the contiguous United States, causing increased winter runoff. Frozen ground generally rejects potential groundwater recharge. Nearly all recharge from precipitation in semi-arid regions such as the Columbia Plateau and the Snake River Plain in Idaho, Oregon, and Washington, occurs between October and March, when precipitation is most abundant and seasonally frozen ground is commonplace. The temporal and spatial distribution of frozen ground is expected to change as the climate warms. It is difficult to predict the distribution of frozen ground, however, because of the complex ways ground freezes and the way that snow cover thermally insulates soil, by keeping it frozen longer than it would be if it was not snow covered or, more commonly, keeping the soil thawed during freezing weather.</p>\n<br/>\n<p>A combination of satellite remote sensing and ground truth measurements was used with some success to investigate seasonally frozen ground at local to regional scales. The frozen-ground/snow-cover algorithm from the National Snow and Ice Data Center, combined with the 21-year record of passive microwave observations from the Special Sensor Microwave Imager onboard a Defense Meteorological Satellite Program satellite, provided a unique time series of frozen ground. Periodically repeating this methodology and analyzing for trends can be a means to monitor possible regional changes to frozen ground that could occur with a warming climate.</p>\n<br/>\n<p>The Precipitation-Runoff Modeling System watershed model constructed for the upper Crab Creek Basin in the Columbia Plateau and Reynolds Creek basin on the eastern side of the Snake River Plain simulated recharge and frozen ground for several future climate scenarios. Frozen ground was simulated with the Continuous Frozen Ground Index, which is influenced by air temperature and snow cover. Model simulation results showed a decreased occurrence of frozen ground that coincided with increased temperatures in the future climate scenarios. Snow cover decreased in the future climate scenarios coincident with the temperature increases. Although annual precipitation was greater in future climate scenarios, thereby increasing the amount of water available for recharge over current (baseline) simulations, actual evapotranspiration also increased and reduced the amount of water available for recharge over baseline simulations. The upper Crab Creek model shows no significant trend in the rates of recharge in future scenarios. In these scenarios, annual precipitation is greater than the baseline averages, offsetting the effects of greater evapotranspiration in future scenarios. In the Reynolds Creek Basin simulations, precipitation was held constant in future scenarios and recharge was reduced by 1.0 percent for simulations representing average conditions in 2040 and reduced by 4.3 percent for simulations representing average conditions in 2080. The focus of the results of future scenarios for the Reynolds Creek Basin was the spatial components of selected hydrologic variables for this 92 square mile mountainous basin with 3,600 feet of relief. Simulation results from the watershed model using the Continuous Frozen Ground Index provided a relative measure of change in frozen ground, but could not identify the within-soil processes that allow or reject available water to recharge aquifers. The model provided a means to estimate what might occur in the future under prescribed climate scenarios, but more detailed energy-balance models of frozen-ground hydrology are needed to accurately simulate recharge under seasonally frozen ground and provide a better understanding of how changes in climate may alter infiltration.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145083","collaboration":"Prepared in collaboration with the USGS Office of Groundwater","usgsCitation":"Mastin, M., and Josberger, E., 2014, Monitoring recharge in areas of seasonally frozen ground in the Columbia Plateau and Snake River Plain, Idaho, Oregon, and Washington: U.S. Geological Survey Scientific Investigations Report 2014-5083, vii, 63 p., https://doi.org/10.3133/sir20145083.","productDescription":"vii, 63 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-051060","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":288102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145083.jpg"},{"id":288098,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5083/"},{"id":288101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5083/pdf/sir20145083.pdf"}],"projection":"Universal Transverse Mercator projection, Zone 11","datum":"North American Datum of 1983","country":"United States","state":"Idaho;Oregon;Washington","otherGeospatial":"Columbia Plateau;Crab Creek Basin;Reynolds Creek Basin;Snake River Plain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.47,41.99 ], [ -122.47,49.0 ], [ -108.63,49.0 ], [ -108.63,41.99 ], [ -122.47,41.99 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53918351e4b06f80638265ac","contributors":{"authors":[{"text":"Mastin, Mark","contributorId":41312,"corporation":false,"usgs":true,"family":"Mastin","given":"Mark","affiliations":[],"preferred":false,"id":493341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Josberger, Edward","contributorId":30733,"corporation":false,"usgs":true,"family":"Josberger","given":"Edward","affiliations":[],"preferred":false,"id":493340,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70111382,"text":"ds839 - 2014 - Topographic lidar survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012","interactions":[],"lastModifiedDate":"2015-02-02T15:14:23","indexId":"ds839","displayToPublicDate":"2014-06-04T11:49:47","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"839","title":"Topographic lidar survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012","docAbstract":"<p>This Data Series Report contains lidar elevation data collected from September 5 to October 11, 2012, for the barrier islands of Alabama, Mississippi and southeast Louisiana, including the coast near Port Fourchon. Most of the data were collected September 5&ndash;10, 2012, with a reflight conducted on October 11, 2012, to increase point density in some areas. Point cloud data&mdash;data points described in three dimensions&mdash;in lidar data exchange format (LAS), and bare earth digital elevation models (DEMs) in ERDAS Imagine raster format (IMG), are available as downloadable files. The point cloud data were processed to extract bare earth data; therefore, the point cloud data are organized into four classes: 1-unclassified, 2-ground, 7-noise and 9-water. Aero-Metric, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process these data.</p>\n<p>&nbsp;</p>\n<p>The lidar data were acquired at a horizontal spacing (or nominal pulse spacing) of 1 meter (m) or less. The USGS conducted two ground surveys in a small area on Chandeleur Island on September 6, 2012, one on bare earth and the other in both bare earth and vegetated areas. The USGS calculated a vertical root mean square error (RMSEz) of 0.072 m and an offset of 0.007 m using interpolated 2-m by 2-m resolution grid surfaces made from the lidar bare-earth data and the combined USGS ground surveys. Aero-Metric, Inc., calculated an RMSEz of 0.025 m by comparing the USGS bare earth ground survey point data to the closest lidar points. The USGS also conducted a terrestrial lidar survey on Dauphin Island, Louisiana, on September 3, 2012. The USGS calculated a RMSEz of 0.32 m and an offset of 0.27 m, meaning the lidar data were 0.27 m higher than the ground truth (Guy and others, 2013), using interpolated 2-m by 2-m resolution grid surfaces from the airborne lidar bare-earth data and the terrestrial lidar survey.</p>\n<p>&nbsp;</p>\n<p>This lidar survey was acquired to document the changes of several different barrier island systems resulting from Hurricane Isaac (Guy and others, 2013). The survey supports detailed studies of Louisiana, Mississippi and Alabama barrier islands that resolve annual and episodic changes in beaches, berms and dunes associated with processes driven by storms, sea-level rise, and even human restoration activities.</p>\n<p>&nbsp;</p>\n<p>These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds839","usgsCitation":"Guy, K.K., Doran, K., Stockdon, H.F., and Plant, N.G., 2014, Topographic lidar survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012: U.S. Geological Survey Data Series 839, HTML Document, https://doi.org/10.3133/ds839.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052682","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds839.jpg"},{"id":288070,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0839/ds839title.html"},{"id":288059,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0839/"}],"country":"United States","state":"Alabama; Louisiana; Mississippi","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.131591796875,\n              28.695406284421967\n            ],\n            [\n              -91.131591796875,\n              30.467614102257855\n            ],\n            [\n              -87.967529296875,\n              30.467614102257855\n            ],\n            [\n              -87.967529296875,\n              28.695406284421967\n            ],\n            [\n              -91.131591796875,\n              28.695406284421967\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031d5e4b04eea98bf84cd","contributors":{"authors":[{"text":"Guy, Kristy K. kguy@usgs.gov","contributorId":45010,"corporation":false,"usgs":true,"family":"Guy","given":"Kristy","email":"kguy@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":494325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":2496,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","email":"kdoran@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":494323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494324,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70111383,"text":"ds840 - 2014 - Topographic lidar survey of the Chandeleur Islands, Louisiana, February 6, 2012","interactions":[],"lastModifiedDate":"2014-06-04T11:54:19","indexId":"ds840","displayToPublicDate":"2014-06-04T11:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"840","title":"Topographic lidar survey of the Chandeleur Islands, Louisiana, February 6, 2012","docAbstract":"<p>This Data Series Report contains lidar elevation data collected February 6, 2012, for Chandeleur Islands, Louisiana. Point cloud data in lidar data exchange format (LAS) and bare earth digital elevation models (DEMs) in ERDAS Imagine raster format (IMG) are available as downloadable files. The point cloud data—data points described in three dimensions—were processed to extract bare earth data; therefore, the point cloud data are organized into the following classes: 1– and 17–unclassified, 2–ground, 9–water, and 10–breakline proximity. Digital Aerial Solutions, LLC, (DAS) was contracted by the U.S. Geological Survey (USGS) to collect and process these data.</p>\n<br/>\n<p>The lidar data were acquired at a horizontal spacing (or nominal pulse spacing) of 0.5 meters (m) or less. The USGS conducted two ground surveys in small areas on the Chandeleur Islands on February 5, 2012. DAS calculated a root mean square error (RMSEz) of 0.034 m by comparing the USGS ground survey point data to triangulated irregular network (TIN) models built from the lidar elevation data.</p>\n<br/>\n<p>This lidar survey was conducted to document the topography and topographic change of the Chandeleur Islands. The survey supports detailed studies of Louisiana, Mississippi and Alabama barrier islands that resolve annual and episodic changes in beaches, berms and dunes associated with processes driven by storms, sea-level rise, and even human restoration activities. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds840","usgsCitation":"Guy, K.K., Plant, N.G., and Bonisteel-Cormier, J.M., 2014, Topographic lidar survey of the Chandeleur Islands, Louisiana, February 6, 2012: U.S. Geological Survey Data Series 840, HTML document, https://doi.org/10.3133/ds840.","productDescription":"HTML document","onlineOnly":"Y","ipdsId":"IP-052857","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds840.jpg"},{"id":288060,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0840/"},{"id":288068,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0840/ds840title.html"}],"projection":"Universal Transverse Mercator projection, zone 16N","datum":"North American Datum of 1983","country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.4946,29.1929 ], [ -89.4946,30.5019 ], [ -87.8975,30.5019 ], [ -87.8975,29.1929 ], [ -89.4946,29.1929 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031d5e4b04eea98bf84d1","contributors":{"authors":[{"text":"Guy, Kristy K. kguy@usgs.gov","contributorId":45010,"corporation":false,"usgs":true,"family":"Guy","given":"Kristy","email":"kguy@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":494328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonisteel-Cormier, Jamie M.","contributorId":18085,"corporation":false,"usgs":true,"family":"Bonisteel-Cormier","given":"Jamie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":494327,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70111381,"text":"ds838 - 2014 - Topographic lidar survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013","interactions":[],"lastModifiedDate":"2014-06-04T11:43:22","indexId":"ds838","displayToPublicDate":"2014-06-04T11:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"838","title":"Topographic lidar survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013","docAbstract":"<p>This Data Series Report contains lidar elevation data collected on July 12 and 14, 2013, for Dauphin Island, Alabama, and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana. Classified point cloud data—data points described in three dimensions—in lidar data exchange format (LAS) and bare earth digital elevation models (DEMs) in ERDAS Imagine raster format (IMG) are available as downloadable files. Photo Science, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process these data.</p>\n<br/>\n<p>The lidar data were acquired at a horizontal spacing (or nominal pulse spacing) of 1 meter (m) or less. The USGS surveyed points within the project area from July 14–23, 2013, for use in ground control and accuracy assessment. Photo Science, Inc., calculated a vertical root mean square error (RMSEz) of 0.012 m by comparing 10 surveyed points to an interpolated elevation surface of unclassified lidar data. The USGS also checked the data using 80 surveyed points and unclassified lidar point elevation data and found an RMSEz of 0.073 m. The project specified an RMSEz of 0.0925 m or less.</p>\n<br/>\n<p>The lidar survey was acquired to document the short- and long-term changes of several different barrier island systems. Specifically, this survey supports detailed studies of Chandeleur and Dauphin Islands that resolve annual changes in beaches, berms and dunes associated with processes driven by storms, sea-level rise, and even human restoration activities.</p>\n<br/>\n<p>These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds838","usgsCitation":"Guy, K.K., and Plant, N.G., 2014, Topographic lidar survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013: U.S. Geological Survey Data Series 838, HTML document, https://doi.org/10.3133/ds838.","productDescription":"HTML document","onlineOnly":"Y","ipdsId":"IP-052146","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds838.jpg"},{"id":288066,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0838/ds838title.html"},{"id":288058,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0838/"}],"projection":"Universal Transverse Mercator projection, zone 16N","datum":"North American Datum of 1983","country":"United States","state":"Alabama;Louisiana","otherGeospatial":"Breton Island;Chandeleur Islands;Dauphin Island;Grand Gosier Island;Stake Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.4946,29.1929 ], [ -89.4946,30.5019 ], [ -87.8975,30.5019 ], [ -87.8975,29.1929 ], [ -89.4946,29.1929 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031d4e4b04eea98bf84c9","contributors":{"authors":[{"text":"Guy, Kristy K. kguy@usgs.gov","contributorId":45010,"corporation":false,"usgs":true,"family":"Guy","given":"Kristy","email":"kguy@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":494321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":494320,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70074260,"text":"sir20145017 - 2014 - Brine contamination to aquatic resources from oil and gas development in the Williston Basin, United States","interactions":[],"lastModifiedDate":"2022-04-22T20:32:36.016333","indexId":"sir20145017","displayToPublicDate":"2014-06-04T11:04:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5017","title":"Brine contamination to aquatic resources from oil and gas development in the Williston Basin, United States","docAbstract":"<p>The Williston Basin, which includes parts of Montana, North Dakota, and South Dakota in the United States and the provinces of Manitoba and Saskatchewan in Canada, has been a leading domestic oil and gas producing region for more than one-half a century. Currently, there are renewed efforts to develop oil and gas resources from deep geologic formations, spurred by advances in recovery technologies and economic incentives associated with the price of oil. Domestic oil and gas production has many economic benefits and provides a means for the United States to fulfill a part of domestic energy demands; however, environmental hazards can be associated with this type of energy production in the Williston Basin, particularly to aquatic resources (surface water and shallow groundwater) by extremely saline water, or brine, which is produced with oil and gas. The primary source of concern is the migration of brine from buried reserve pits that were used to store produced water during recovery operations; however, there also are considerable risks of brine release from pipeline failures, poor infrastructure construction, and flow-back water from hydraulic fracturing associated with modern oilfield operations.</p>\n<br/>\n<p>During 2008, a multidisciplinary (biology, geology, water) team of U.S. Geological Survey researchers was assembled to investigate potential energy production effects in the Williston Basin. Researchers from the U.S. Geological Survey participated in field tours and met with representatives from county, State, tribal, and Federal agencies to identify information needs and focus research objectives. Common questions from agency personnel, especially those from the U.S. Fish and Wildlife Service, were “are the brine plumes (plumes of brine-contaminated groundwater) from abandoned oil wells affecting wetlands on Waterfowl Production Areas and National Wildlife Refuges?” and “are newer wells related to Bakken and Three Forks development different than the older, abandoned wells (in terms of potential for affecting aquatic resources)?” Of special concern were the wetland habitats of the ecologically important Prairie Pothole Region, which overlays a part of the Williston Basin and is recognized for the production of a majority of North America’s migratory waterfowl.</p>\n<br/>\n<p>On the basis of the concerns raised by on-the-ground land managers, as well as findings from previous research, a comprehensive study was developed with the following goals: summarize existing information pertaining to oil and gas production and aquatic resources in the Williston Basin; assess brine plume migration from new and previously studied sites in the Prairie Pothole Region; perform a regional, spatial evaluation of oil and gas production activities and aquatic resources; assess the potential for brine contamination to wetlands and streams; and hold a decision analysis workshop with key stakeholders to discuss issues pertaining to oil and gas production and environmental effects and to identify information gaps and research needs.</p>\n<br/>\n<p>This report represents an initial, multidisciplinary evaluation of measured and potential environmental effects associated with oil and gas production in the Williston Basin and Prairie Pothole Region. Throughout this report there are reviews of current knowledge, and discussions relating to data gaps and research needs. On the basis of the information presented, future research needs include: regional geophysical and water-quality assessments to establish baselines for current conditions and estimate the extent of previous brine contamination, investigations into the direct effects of brine to biotic communities, and evaluations to identify the most effective techniques to mitigate brine contamination.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145017","usgsCitation":"Chesley-Preston, T.L., Coleman, J.L., Gleason, R.A., Haines, S.S., Jenni, K., Nieman, T.L., Peterman, Z., van der Burg, M.P., Preston, T.M., Smith, B.D., Tangen, B., and Thamke, J., 2014, Brine contamination to aquatic resources from oil and gas development in the Williston Basin, United States: U.S. Geological Survey Scientific Investigations Report 2014-5017, 140 p., https://doi.org/10.3133/sir20145017.","productDescription":"140 p.","onlineOnly":"N","ipdsId":"IP-044530","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":288063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145017.jpg"},{"id":288061,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5017/pdf/sir2014-5017.pdf"},{"id":288057,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5017/"},{"id":399525,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_100211.htm"}],"projection":"Albers Equal-Area Conic projection","country":"United States","state":"Montana, North Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.5126953125,\n              46.08847179577592\n            ],\n            [\n              -98.32763671875,\n              46.08847179577592\n            ],\n            [\n              -98.32763671875,\n              48.93693495409401\n            ],\n            [\n              -105.5126953125,\n              48.93693495409401\n            ],\n            [\n              -105.5126953125,\n              46.08847179577592\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031d1e4b04eea98bf84bd","contributors":{"editors":[{"text":"Gleason, Robert A. 0000-0001-5308-8657 rgleason@usgs.gov","orcid":"https://orcid.org/0000-0001-5308-8657","contributorId":2402,"corporation":false,"usgs":true,"family":"Gleason","given":"Robert","email":"rgleason@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":509774,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Tangen, Brian A.","contributorId":78419,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian A.","affiliations":[],"preferred":false,"id":509775,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Chesley-Preston, Tara L. tchesley-preston@usgs.gov","contributorId":5557,"corporation":false,"usgs":true,"family":"Chesley-Preston","given":"Tara","email":"tchesley-preston@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":489437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coleman, James L. jlcoleman@usgs.gov","contributorId":141060,"corporation":false,"usgs":true,"family":"Coleman","given":"James","email":"jlcoleman@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":489436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gleason, Robert A. 0000-0001-5308-8657 rgleason@usgs.gov","orcid":"https://orcid.org/0000-0001-5308-8657","contributorId":2402,"corporation":false,"usgs":true,"family":"Gleason","given":"Robert","email":"rgleason@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":489430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":489434,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jenni, Karen E.","contributorId":21256,"corporation":false,"usgs":true,"family":"Jenni","given":"Karen E.","affiliations":[],"preferred":false,"id":489438,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nieman, Timothy L.","contributorId":103967,"corporation":false,"usgs":true,"family":"Nieman","given":"Timothy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":489441,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Peterman, Zell E. 0000-0002-5694-8082 peterman@usgs.gov","orcid":"https://orcid.org/0000-0002-5694-8082","contributorId":620,"corporation":false,"usgs":true,"family":"Peterman","given":"Zell E.","email":"peterman@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":489431,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"van der Burg, Max Post","contributorId":92580,"corporation":false,"usgs":true,"family":"van der Burg","given":"Max","email":"","middleInitial":"Post","affiliations":[],"preferred":false,"id":489440,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Preston, Todd M. 0000-0002-8812-9233 tmpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":1664,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"tmpreston@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":489435,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smith, Bruce D. 0000-0002-1643-2997 bsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":845,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","email":"bsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":489432,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tangen, Brian A.","contributorId":78419,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian A.","affiliations":[],"preferred":false,"id":489439,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thamke, Joanna N. 0000-0002-6917-1946 jothamke@usgs.gov","orcid":"https://orcid.org/0000-0002-6917-1946","contributorId":1012,"corporation":false,"usgs":true,"family":"Thamke","given":"Joanna N.","email":"jothamke@usgs.gov","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489433,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70047731,"text":"70047731 - 2014 - Demography of a reintroduced population: moving toward management models for an endangered species, the whooping crane","interactions":[],"lastModifiedDate":"2016-09-22T13:06:59","indexId":"70047731","displayToPublicDate":"2014-06-04T09:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Demography of a reintroduced population: moving toward management models for an endangered species, the whooping crane","docAbstract":"The reintroduction of threatened and endangered species is now a common method for reestablishing populations. Typically, a fundamental objective of reintroduction is to establish a self-sustaining population. Estimation of demographic parameters in reintroduced populations is critical, as these estimates serve multiple purposes. First, they support evaluation of progress toward the fundamental objective via construction of population viability analyses (PVAs) to predict metrics such as probability of persistence. Second, PVAs can be expanded to support evaluation of management actions, via management modeling. Third, the estimates themselves can support evaluation of the demographic performance of the reintroduced population, e.g., via comparison with wild populations. For each of these purposes, thorough treatment of uncertainties in the estimates is critical. Recently developed statistical methods - namely, hierarchical Bayesian implementations of state-space models - allow for effective integration of different types of uncertainty in estimation. We undertook a demographic estimation effort for a reintroduced population of endangered whooping cranes with the purpose of ultimately developing a Bayesian PVA for determining progress toward establishing a self-sustaining population, and for evaluating potential management actions via a Bayesian PVA-based management model. We evaluated individual and temporal variation in demographic parameters based upon a multi-state mark-recapture model. We found that survival was relatively high across time and varied little by sex. There was some indication that survival varied by release method. Survival was similar to that observed in the wild population. Although overall reproduction in this reintroduced population is poor, birds formed social pairs when relatively young, and once a bird was in a social pair, it had a nearly 50% chance of nesting the following breeding season. Also, once a bird had nested, it had a high probability of nesting again. These results are encouraging considering that survival and reproduction have been major challenges in past reintroductions of this species. The demographic estimates developed will support construction of a management model designed to facilitate exploration of management actions of interest, and will provide critical guidance in future planning for this reintroduction. An approach similar to what we describe could be usefully applied to many reintroduced populations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/13-0559.1","usgsCitation":"Servanty, S., Converse, S.J., and Bailey, L., 2014, Demography of a reintroduced population: moving toward management models for an endangered species, the whooping crane: Ecological Applications, v. 24, no. 5, p. 927-937, https://doi.org/10.1890/13-0559.1.","productDescription":"11 p.","startPage":"927","endPage":"937","numberOfPages":"11","ipdsId":"IP-050859","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":288087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288086,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/13-0559.1"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.15,24.22 ], [ -93.15,47.11 ], [ -74.38,47.11 ], [ -74.38,24.22 ], [ -93.15,24.22 ] ] ] } } ] }","volume":"24","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031d4e4b04eea98bf84c5","contributors":{"authors":[{"text":"Servanty, Sabrina","contributorId":53296,"corporation":false,"usgs":true,"family":"Servanty","given":"Sabrina","affiliations":[],"preferred":false,"id":482841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":3513,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":482843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailey, Larissa L.","contributorId":93183,"corporation":false,"usgs":true,"family":"Bailey","given":"Larissa L.","affiliations":[],"preferred":false,"id":482842,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70094176,"text":"70094176 - 2014 - A screening tool for delineating subregions of steady recharge within groundwater models","interactions":[],"lastModifiedDate":"2018-04-02T15:20:49","indexId":"70094176","displayToPublicDate":"2014-06-04T09:22:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"A screening tool for delineating subregions of steady recharge within groundwater models","docAbstract":"We have developed a screening method for simplifying groundwater models by delineating areas within the domain that can be represented using steady-state groundwater recharge. The screening method is based on an analytical solution for the damping of sinusoidal infiltration variations in homogeneous soils in the vadose zone. The damping depth is defined as the depth at which the flux variation damps to 5% of the variation at the land surface. Groundwater recharge may be considered steady where the damping depth is above the depth of the water table. The analytical solution approximates the vadose zone diffusivity as constant, and we evaluated when this approximation is reasonable. We evaluated the analytical solution through comparison of the damping depth computed by the analytic solution with the damping depth simulated by a numerical model that allows variable diffusivity. This comparison showed that the screening method conservatively identifies areas of steady recharge and is more accurate when water content and diffusivity are nearly constant. Nomograms of the damping factor (the ratio of the flux amplitude at any depth to the amplitude at the land surface) and the damping depth were constructed for clay and sand for periodic variations between 1 and 365 d and flux means and amplitudes from nearly 0 to 1 × 10<sup>−3</sup> m d<sup>−1</sup>. We applied the screening tool to Central Valley, California, to identify areas of steady recharge. A MATLAB script was developed to compute the damping factor for any soil and any sinusoidal flux variation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Vadose Zone Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Soil Science Society of America","publisherLocation":"Madison, WI","doi":"10.2136/vzj2013.10.0184","usgsCitation":"Dickinson, J.E., Ferre, T., Bakker, M., and Crompton, B., 2014, A screening tool for delineating subregions of steady recharge within groundwater models: Vadose Zone Journal, v. 13, no. 6, 15 p., https://doi.org/10.2136/vzj2013.10.0184.","productDescription":"15 p.","numberOfPages":"15","ipdsId":"IP-045293","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":499879,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/3998685ffc7747f19af7502e880f5695","text":"External Repository"},{"id":288054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288053,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2136/vzj2013.10.0184"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.53,34.74 ], [ -123.53,41.48 ], [ -117.6,41.48 ], [ -117.6,34.74 ], [ -123.53,34.74 ] ] ] } } ] }","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-05-27","publicationStatus":"PW","scienceBaseUri":"539031d0e4b04eea98bf84b5","contributors":{"authors":[{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferre, T.P.A.","contributorId":196167,"corporation":false,"usgs":false,"family":"Ferre","given":"T.P.A.","email":"","affiliations":[],"preferred":false,"id":490537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bakker, Mark","contributorId":56137,"corporation":false,"usgs":true,"family":"Bakker","given":"Mark","email":"","affiliations":[],"preferred":false,"id":490538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crompton, Becky","contributorId":60544,"corporation":false,"usgs":true,"family":"Crompton","given":"Becky","email":"","affiliations":[],"preferred":false,"id":490539,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70111702,"text":"70111702 - 2014 - The carbon cycle and hurricanes in the United States between 1900 and 2011","interactions":[],"lastModifiedDate":"2014-06-06T13:40:00","indexId":"70111702","displayToPublicDate":"2014-06-03T13:35:34","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"The carbon cycle and hurricanes in the United States between 1900 and 2011","docAbstract":"Hurricanes cause severe impacts on forest ecosystems in the United States. These events can substantially alter the carbon biogeochemical cycle at local to regional scales. We selected all tropical storms and more severe events that made U.S. landfall between 1900 and 2011 and used hurricane best track database, a meteorological model (HURRECON), National Land Cover Database (NLCD), U. S. Department of Agirculture Forest Service biomass dataset, and pre- and post-MODIS data to quantify individual event and annual biomass mortality. Our estimates show an average of 18.2 TgC/yr of live biomass mortality for 1900–2011 in the US with strong spatial and inter-annual variability. Results show Hurricane Camille in 1969 caused the highest aboveground biomass mortality with 59.5 TgC. Similarly 1954 had the highest annual mortality with 68.4 TgC attributed to landfalling hurricanes. The results presented are deemed useful to further investigate historical events, and the methods outlined are potentially beneficial to quantify biomass loss in future events.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Scientific Reports","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Nature Publishing Group","doi":"10.1038/srep05197","usgsCitation":"Dahal, D., Liu, S., and Oeding, J., 2014, The carbon cycle and hurricanes in the United States between 1900 and 2011: Scientific Reports, v. 4, no. 5197, 10 p., https://doi.org/10.1038/srep05197.","productDescription":"10 p.","ipdsId":"IP-054728","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472953,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep05197","text":"Publisher Index Page"},{"id":288150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288146,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1038/srep05197"}],"country":"United States","volume":"4","issue":"5197","noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"53ae7863e4b0abf75cf2d3ee","contributors":{"authors":[{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":494445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shu-Guang sliu@usgs.gov","contributorId":984,"corporation":false,"usgs":true,"family":"Liu","given":"Shu-Guang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":494443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oeding, Jennifer joeding@usgs.gov","contributorId":4070,"corporation":false,"usgs":true,"family":"Oeding","given":"Jennifer","email":"joeding@usgs.gov","affiliations":[],"preferred":true,"id":494444,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70073693,"text":"sir20135235 - 2014 - Occurrence and hydrogeochemistry of radiochemical constituents in groundwater of Jefferson County and surrounding areas, southwestern Montana, 2007 through 2010","interactions":[],"lastModifiedDate":"2014-07-31T16:03:46","indexId":"sir20135235","displayToPublicDate":"2014-06-03T12:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5235","title":"Occurrence and hydrogeochemistry of radiochemical constituents in groundwater of Jefferson County and surrounding areas, southwestern Montana, 2007 through 2010","docAbstract":"<p>The U.S. Geological Survey, in cooperation with Jefferson County and the Jefferson Valley Conservation District, sampled groundwater in southwestern Montana to evaluate the occurrence and concentration of naturally-occurring radioactive constituents and to identify geologic settings and environmental conditions in which elevated concentrations occur. A total of 168 samples were collected from 128 wells within Broadwater, Deer Lodge, Jefferson, Lewis and Clark, Madison, Powell, and Silver Bow Counties from 2007 through 2010. Most wells were used for domestic purposes and were primary sources of drinking water for individual households. Water-quality samples were collected from wells completed within six generalized geologic units, and analyzed for constituents including uranium, radon, gross alpha-particle activity, and gross beta-particle activity. Thirty-eight wells with elevated concentrations or activities were sampled a second time to examine variability in water quality throughout time. These water-quality samples were analyzed for an expanded list of radioactive constituents including the following: three isotopes of uranium (uranium-234, uranium-235, and uranium-238), three isotopes of radium (radium-224, radium-226, and radium-228), and polonium-210. Existing U.S. Geological Survey and Montana Bureau of Mines and Geology uranium and radon water-quality data collected as part of other investigations through 2011 from wells within the study area were compiled as part of this investigation. Water-quality data from this study were compared to data collected nationwide by the U.S. Geological Survey through 2011.</p>\n<br>\n<p>Radionuclide samples for this study typically were analyzed within a few days after collection, and therefore data for this study may closely represent the concentrations and activities of water being consumed locally from domestic wells. Radioactive constituents were detected in water from every well sampled during this study regardless of location or geologic unit. Nearly 41 percent of sampled wells had at least one radioactive constituent concentration that exceeded U.S. Environmental Protection Agency drinking-water standards or screening levels. Uranium concentrations were higher than the U.S. Environmental Protection Agency maximum contaminant level (MCL) of 30 micrograms per liter in samples from 14 percent of the wells. Radon concentrations exceeded a proposed MCL of 4,000 picocuries per liter in 27 percent of the wells. Combined radium (radium-226 and radium-228) exceeded the MCL of 5 picocuries per liter in samples from 10 of 47 wells. About 40 percent (42 of 104 wells) of the wells had gross alpha-particle activities (72-hour count) at or greater than a screening level of 15 pCi/L. Gross beta-particle activity exceeded the U.S. Environmental Protection Agency 50 picocuries per liter screening level in samples from 5 of 104 wells. Maximum radium-224 and polonium-210 activities in study wells were 16.1 and 3.08 picocuries per liter, respectively; these isotopes are constituents of human-health concern, but the U.S. Environmental Protection Agency has not established MCLs for them.</p>\n<br>\n<p>Radioactive constituent concentrations or activities exceeded at least one established drinking-water standard, proposed drinking-water standard, or screening level in groundwater samples from five of six generalized geologic units assessed during this study. Radioactive constituent concentrations or activities were variable not only within each geologic unit, but also among wells that were completed in the same geologic unit and in close proximity to one another. Established or proposed drinking-water standards were exceeded most frequently in water from wells completed in the generalized geologic unit that includes rocks of the Boulder batholith and other Tertiary through Cretaceous igneous intrusive rocks (commonly described as granite). Specifically, of the wells completed in the Boulder batholith and related rocks sampled as part of this study, 24 percent exceeded the MCL of 30 micrograms per liter for uranium, 50 percent exceeded the proposed alternative MCL of 4,000 picocuries per liter for radon, and 27 percent exceeded the MCL of 5 micrograms per liter for combined radium-226 and radium-228.</p>\n<br>\n<p>Elevated radioactive constituent values were detected in samples representing a large range of field properties and water types. Correlations between radioactive constituents and pH, dissolved oxygen, and most major ions were not statistically significant (p-value > 0.05) or were weakly correlated with Spearman correlation coefficients (rho) ranging from -0.5 to 0.5. Moderate correlations did exist between gross beta-particle activity and potassium (rho = 0.72 to 0.82), likely because one potassium isotope (potassium-40) is a beta-particle emitter. Total dissolved solids and specific conductance also were moderately correlated (rho = 0.62 to 0.71) with gross alpha-particle and gross beta-particle activity, indicating that higher radioactivity values can be associated with higher total dissolved solids.</p>\n<br>\n<p>Correlations were evaluated among radioactive constituents. Moderate to strong correlations occurred between gross alpha-particle and beta-particle activities (rho = 0.77 to 0.96) and radium isotopes (rho = 0.78 to 0.92). Correlations between gross alpha-particle activity (72-hour count) and all analyzed radioactive constituents were statistically significant (p-value < 0.05), and therefore, gross alpha-particle activity likely may be used as a screening tool for determining the presence of radionuclides in area waters. In this study, gross alpha-particle activities of 7 picocuries per liter or greater were associated with all radioactive constituents whose concentrations exceeded drinking-water standards or screening levels.</p>\n<br>\n<p>Radiochemical results varied temporally in samples from several of the thirty-eight wells sampled at least twice during the study. The time between successive sampling events ranged from about 1 to 10 months for 29 wells to about 3 years for the other 9 wells. Radiochemical constituents that varied by greater than 30 percent between sampling events included uranium (29 percent of the resampled wells), and radon (11 percent of the resampled wells), gross alpha-particle activity (38 percent of the resampled wells), and gross beta-particle activity (15 percent of the resampled wells). Variability in uranium concentrations from two wells was sufficiently large that concentrations were less than the MCL in the first set of samples and greater than the MCL in the second.</p>\n<br>\n<p>Sample holding times affect analytical results in this study. Gross alpha-particle and gross beta-particle activities were measured twice, 72 hours and 30 days after sample collection. Gross alpha-particle activity decreased an average of 37 percent between measurements, indicating the presence of short-lived alpha-emitting radionuclides in these samples. Gross beta-particle activity increased an average of 31 percent between measurements, indicating ingrowth of longer-lived beta-emitting radionuclides.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135235","issn":"2328-0328","collaboration":"Prepared in cooperation with Jefferson County and the Jefferson Valley Conservation District, Montana","usgsCitation":"Caldwell, R.R., Nimick, D.A., and DeVaney, R.M., 2014, Occurrence and hydrogeochemistry of radiochemical constituents in groundwater of Jefferson County and surrounding areas, southwestern Montana, 2007 through 2010: U.S. Geological Survey Scientific Investigations Report 2013-5235, Report: x, 61 p.; Downloads directory, https://doi.org/10.3133/sir20135235.","productDescription":"Report: x, 61 p.; Downloads directory","numberOfPages":"76","onlineOnly":"N","temporalStart":"2007-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-042934","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":287984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135235.jpg"},{"id":287981,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5235/"},{"id":287982,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5235/pdf/sir2013-5235.pdf"},{"id":287983,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5235/downloads/Appendix%20.xlsx"}],"scale":"100000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1927","country":"United States","state":"Montana","county":"Jefferson County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.0,45.5 ], [ -113.0,47.0 ], [ -111.5,47.0 ], [ -111.5,45.5 ], [ -113.0,45.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"538ee05be4b0d497d49684d5","contributors":{"authors":[{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":489047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nimick, David A. dnimick@usgs.gov","contributorId":421,"corporation":false,"usgs":true,"family":"Nimick","given":"David","email":"dnimick@usgs.gov","middleInitial":"A.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true}],"preferred":true,"id":489046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeVaney, Rainie M.","contributorId":84668,"corporation":false,"usgs":true,"family":"DeVaney","given":"Rainie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":489048,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70103906,"text":"sir20145091 - 2014 - Evaluation of seepage and discharge uncertainty in the middle Snake River, southwestern Idaho","interactions":[],"lastModifiedDate":"2014-06-03T11:36:57","indexId":"sir20145091","displayToPublicDate":"2014-06-03T11:31:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5091","title":"Evaluation of seepage and discharge uncertainty in the middle Snake River, southwestern Idaho","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the State of Idaho, Idaho Power Company, and the Idaho Department of Water Resources, evaluated seasonal seepage gains and losses in selected reaches of the middle Snake River, Idaho, during November 2012 and July 2013, and uncertainty in measured and computed discharge at four Idaho Power Company streamgages. Results from this investigation will be used by resource managers in developing a protocol to calculate and report Adjusted Average Daily Flow at the Idaho Power Company streamgage on the Snake River below Swan Falls Dam, near Murphy, Idaho, which is the measurement point for distributing water to owners of hydropower and minimum flow water rights in the middle Snake River. The evaluated reaches of the Snake River were from King Hill to Murphy, Idaho, for the seepage studies and downstream of Lower Salmon Falls Dam to Murphy, Idaho, for evaluations of discharge uncertainty.</p>\n<br>\n<p>Computed seepage was greater than cumulative measurement uncertainty for subreaches along the middle Snake River during November 2012, the non-irrigation season, but not during July 2013, the irrigation season. During the November 2012 seepage study, the subreach between King Hill and C J Strike Dam had a meaningful (greater than cumulative measurement uncertainty) seepage gain of 415 cubic feet per second (ft<sup>3</sup>/s), and the subreach between Loveridge Bridge and C J Strike Dam had a meaningful seepage gain of 217 ft<sup>3</sup>/s. The meaningful seepage gain measured in the November 2012 seepage study was expected on the basis of several small seeps and springs present along the subreach, regional groundwater table contour maps, and results of regional groundwater flow model simulations. Computed seepage along the subreach from C J Strike Dam to Murphy was less than cumulative measurement uncertainty during November 2012 and July 2013; therefore, seepage cannot be quantified with certainty along this subreach.</p>\n<br>\n<p>For the uncertainty evaluation, average uncertainty in discharge measurements at the four Idaho Power Company streamgages in the study reach ranged from 4.3 percent (Snake River below Lower Salmon Falls Dam) to 7.8 percent (Snake River below C J Strike Dam) for discharges less than 7,000 ft3/s in water years 2007–11. This range in uncertainty constituted most of the total quantifiable uncertainty in computed discharge, represented by prediction intervals calculated from the discharge rating of each streamgage. Uncertainty in computed discharge in the Snake River below Swan Falls Dam near Murphy was 10.1 and 6.0 percent at the Adjusted Average Daily Flow thresholds of 3,900 and 5,600 ft3/s, respectively. All discharge measurements and records computed at streamgages have some level of uncertainty that cannot be entirely eliminated. Knowledge of uncertainty at the Adjusted Average Daily Flow thresholds is useful for developing a measurement and reporting protocol for purposes of distributing water to hydropower and minimum flow water rights in the middle Snake River.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145091","issn":"2328-0328","collaboration":"Prepared in cooperation with the State of Idaho, Idaho Power Company, and the Idaho Department of Water Resources","usgsCitation":"Wood, M.S., Williams, M.L., Evetts, D.M., and Vidmar, P.J., 2014, Evaluation of seepage and discharge uncertainty in the middle Snake River, southwestern Idaho: U.S. Geological Survey Scientific Investigations Report 2014-5091, v, 34 p., https://doi.org/10.3133/sir20145091.","productDescription":"v, 34 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-043282","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":287980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145091.jpg"},{"id":287979,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5091/pdf/sir20145091.pdf"},{"id":287978,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5091/"}],"projection":"Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Idaho","otherGeospatial":"Snake River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.5,42.75 ], [ -116.5,43.5 ], [ -115.0,43.5 ], [ -115.0,42.75 ], [ -116.5,42.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"538ee057e4b0d497d49684c5","contributors":{"authors":[{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":493533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Marshall L. mlwilliams@usgs.gov","contributorId":1444,"corporation":false,"usgs":true,"family":"Williams","given":"Marshall","email":"mlwilliams@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evetts, David M. devetts@usgs.gov","contributorId":5097,"corporation":false,"usgs":true,"family":"Evetts","given":"David","email":"devetts@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":493535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vidmar, Peter J.","contributorId":65008,"corporation":false,"usgs":true,"family":"Vidmar","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":493536,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70111094,"text":"70111094 - 2014 - Soil, plant, and terrain effects on natural perchlorate distribution in a desert landscape","interactions":[],"lastModifiedDate":"2018-09-04T16:50:35","indexId":"70111094","displayToPublicDate":"2014-06-02T16:20:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Soil, plant, and terrain effects on natural perchlorate distribution in a desert landscape","docAbstract":"Perchlorate (ClO<sub>4</sub><sup>−</sup>) is a contaminant that occurs naturally throughout the world, but little is known about its distribution and interactions in terrestrial ecosystems. The objectives of this Amargosa Desert, Nevada study were to determine (i) the local-scale distribution of shallow-soil (0–30 cm) ClO<sub>4</sub><sup>−</sup> with respect to shrub proximity (far and near) in three geomorphic settings (shoulder slope, footslope, and valley floor); (ii) the importance of soil, plant, and terrain variables on the hillslope-distribution of shallow-soil and creosote bush [<i>Larrea tridentata</i> (Sessé & Moc. ex DC.) Coville] ClO<sub>4</sub><sup>−</sup>; and (iii) atmospheric (wet plus dry, including dust) deposition of ClO<sub>4</sub><sup>−</sup> in relation to soil and plant reservoirs and cycling. Soil ClO<sub>4</sub><sup>−</sup> ranged from 0.3 to 5.0 μg kg<sup>−1</sup>. Within settings, valley floor ClO<sub>4</sub><sup>−</sup> was 17× less near shrubs due in part to enhanced leaching, whereas shoulder and footslope values were ∼2× greater near shrubs. Hillslope regression models (soil, R<sup>2</sup> = 0.42; leaf, R<sup>2</sup> = 0.74) identified topographic and soil effects on ClO<sub>4</sub><sup>−</sup> deposition, transport, and cycling. Selective plant uptake, bioaccumulation, and soil enrichment were evidenced by leaf ClO<sub>4</sub><sup>−</sup> concentrations and Cl<sup>−</sup>/ClO<sub>4</sub><sup>−</sup> molar ratios that were ∼8000× greater and 40× less, respectively, than soil values. Atmospheric deposition ClO<sub>4</sub><sup>−</sup> flux was 343 mg ha<sup>−1</sup> yr<sup>−1</sup>, ∼10× that for published southwestern wet-deposition fluxes. Creosote bush canopy ClO<sub>4</sub><sup>−</sup> (1310 mg ha−1) was identified as a previously unrecognized but important and active reservoir. Nitrate δ<sup>18</sup>O analyses of atmospheric deposition and soil supported the leaf-cycled–ClO<sub>4</sub><sup>−</sup> input hypothesis. This study provides basic data on ClO<sub>4</sub><sup>−</sup> distribution and cycling that are pertinent to the assessment of environmental impacts in desert ecosystems and broadly transferable to anthropogenically contaminated systems.","language":"English","publisher":"ASCESS","doi":"10.2134/jeq2013.11.0453","usgsCitation":"Andraski, B.J., Jackson, W., Welborn, T.L., Böhlke, J., Sevanthi, R., and Stonestrom, D.A., 2014, Soil, plant, and terrain effects on natural perchlorate distribution in a desert landscape: Journal of Environmental Quality, v. 43, no. 3, p. 980-994, https://doi.org/10.2134/jeq2013.11.0453.","productDescription":"15 p.","startPage":"980","endPage":"994","ipdsId":"IP-052625","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472955,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2013.11.0453","text":"Publisher Index Page"},{"id":287969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.1582,35.9936 ], [ -117.1582,37.1034 ], [ -115.9415,37.1034 ], [ -115.9415,35.9936 ], [ -117.1582,35.9936 ] ] ] } } ] }","volume":"43","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-05-01","publicationStatus":"PW","scienceBaseUri":"53ae782ee4b0abf75cf2ccdf","contributors":{"authors":[{"text":"Andraski, Brian J. 0000-0002-2086-0417 andraski@usgs.gov","orcid":"https://orcid.org/0000-0002-2086-0417","contributorId":168800,"corporation":false,"usgs":true,"family":"Andraski","given":"Brian","email":"andraski@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":494247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, W.A.","contributorId":15549,"corporation":false,"usgs":true,"family":"Jackson","given":"W.A.","email":"","affiliations":[],"preferred":false,"id":494251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welborn, Toby L. 0000-0003-4839-2405 tlwelbor@usgs.gov","orcid":"https://orcid.org/0000-0003-4839-2405","contributorId":2295,"corporation":false,"usgs":true,"family":"Welborn","given":"Toby","email":"tlwelbor@usgs.gov","middleInitial":"L.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Böhlke, John Karl 0000-0001-5693-6455","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":22843,"corporation":false,"usgs":true,"family":"Böhlke","given":"John Karl","affiliations":[],"preferred":false,"id":494252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sevanthi, Ritesh","contributorId":14301,"corporation":false,"usgs":true,"family":"Sevanthi","given":"Ritesh","affiliations":[],"preferred":false,"id":494250,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stonestrom, David A. 0000-0001-7883-3385 dastones@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-3385","contributorId":2280,"corporation":false,"usgs":true,"family":"Stonestrom","given":"David","email":"dastones@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":494248,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70102823,"text":"ofr20141020 - 2014 - Transmissivity and storage coefficient estimates from slug tests, Naval Air Warfare Center, West Trenton, New Jersey","interactions":[],"lastModifiedDate":"2020-05-28T20:11:46.424521","indexId":"ofr20141020","displayToPublicDate":"2014-06-02T10:28:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1020","title":"Transmissivity and storage coefficient estimates from slug tests, Naval Air Warfare Center, West Trenton, New Jersey","docAbstract":"Slug tests were conducted on 56 observation wells open to bedrock at the former Naval Air Warfare Center (NAWC) in West Trenton, New Jersey. Aquifer transmissivity (T) and storage coefficient (S) values for most wells were estimated from slug-test data using the Cooper-Bredehoeft-Papadopulos method. Test data from three wells exhibited fast, underdamped water-level responses and were analyzed with the Butler high-K method. The range of T at NAWC was approximately 0.07 to 10,000 square feet per day. At 11 wells, water levels did not change measurably after 20 minutes following slug insertion; transmissivity at these 11 wells was estimated to be less than 0.07 square feet per day. The range of S was approximately 10<sup>-10</sup> to 0.01, the mode being 10<sup>-10</sup>. Water-level responses for tests at three wells fit poorly to the type curves of both methods, indicating that these methods were not appropriate for adequately estimating T and S from those data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141020","collaboration":"Toxic Substances Hydrology Program. Prepared in cooperation with U.S. Department of the Navy","usgsCitation":"Fiore, A.R., 2014, Transmissivity and storage coefficient estimates from slug tests, Naval Air Warfare Center, West Trenton, New Jersey: U.S. Geological Survey Open-File Report 2014-1020, Report: HTML document; Table 1, https://doi.org/10.3133/ofr20141020.","productDescription":"Report: HTML document; Table 1","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049724","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":287950,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1020/report/table/table1.xlsx"},{"id":287949,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1020/report/title.html"},{"id":287948,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1020/"},{"id":375134,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2014/1020/images/coverthb.jpg"}],"country":"United States","state":"New Jersey","city":"West Trenton","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.819974,40.264976 ], [ -74.819974,40.275041 ], [ -74.804359,40.275041 ], [ -74.804359,40.264976 ], [ -74.819974,40.264976 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae787ae4b0abf75cf2d6b7","contributors":{"authors":[{"text":"Fiore, Alex R. 0000-0002-0986-5225 afiore@usgs.gov","orcid":"https://orcid.org/0000-0002-0986-5225","contributorId":4977,"corporation":false,"usgs":true,"family":"Fiore","given":"Alex","email":"afiore@usgs.gov","middleInitial":"R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493028,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70110938,"text":"70110938 - 2014 - Ecohydrology of adjacent sagebrush and lodgepole pine ecosystems: the consequences of climate change and disturbance","interactions":[],"lastModifiedDate":"2014-06-02T09:37:06","indexId":"70110938","displayToPublicDate":"2014-06-02T09:31:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Ecohydrology of adjacent sagebrush and lodgepole pine ecosystems: the consequences of climate change and disturbance","docAbstract":"Sagebrush steppe and lodgepole pine forests are two of the most widespread vegetation types in the western United States and they play crucial roles in the hydrologic cycle of these water-limited regions. We used a process-based ecosystem water model to characterize the potential impact of climate change and disturbance (wildfire and beetle mortality) on water cycling in adjacent sagebrush and lodgepole pine ecosystems. Despite similar climatic and topographic conditions between these ecosystems at the sites examined, lodgepole pine, and sagebrush exhibited consistent differences in water balance, notably more evaporation and drier summer soils in the sagebrush and greater transpiration and less water yield in lodgepole pine. Canopy disturbances (either fire or beetle) have dramatic impacts on water balance and availability: reducing transpiration while increasing evaporation and water yield. Results suggest that climate change may reduce snowpack, increase evaporation and transpiration, and lengthen the duration of dry soil conditions in the summer, but may have uncertain effects on drainage. Changes in the distribution of sagebrush and lodgepole pine ecosystems as a consequence of climate change and/or altered disturbance regimes will likely alter ecosystem water balance.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosystems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10021-013-9745-1","usgsCitation":"Bradford, J.B., Schlaepfer, D., and Lauenroth, W.K., 2014, Ecohydrology of adjacent sagebrush and lodgepole pine ecosystems: the consequences of climate change and disturbance: Ecosystems, v. 17, no. 4, p. 590-605, https://doi.org/10.1007/s10021-013-9745-1.","productDescription":"16 p.","startPage":"590","endPage":"605","numberOfPages":"16","ipdsId":"IP-038315","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":287941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287905,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10021-013-9745-1"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.1592,36.8093 ], [ -113.1592,42.033 ], [ -103.9526,42.033 ], [ -103.9526,36.8093 ], [ -113.1592,36.8093 ] ] ] } } ] }","volume":"17","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-01-14","publicationStatus":"PW","scienceBaseUri":"53ae7692e4b0abf75cf2bfa6","contributors":{"authors":[{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":494203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":494205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":494204,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70104569,"text":"70104569 - 2014 - Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin","interactions":[],"lastModifiedDate":"2018-01-12T17:20:31","indexId":"70104569","displayToPublicDate":"2014-06-01T15:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin","docAbstract":"<p>The distribution of permafrost is important to understand because of permafrost's influence on high-latitude ecosystem structure and functions. Moreover, near-surface (defined here as within 1&thinsp;m of the Earth's surface) permafrost is particularly susceptible to a warming climate and is generally poorly mapped at regional scales. Subsequently, our objectives were to (1) develop the first-known binary and probabilistic maps of near-surface permafrost distributions at a 30 m resolution in the Alaskan Yukon River Basin by employing decision tree models, field measurements, and remotely sensed and mapped biophysical data; (2) evaluate the relative contribution of 39 biophysical variables used in the models; and (3) assess the landscape-scale factors controlling spatial variations in permafrost extent. Areas estimated to be present and absent of near-surface permafrost occupy approximately 46% and 45% of the Alaskan Yukon River Basin, respectively; masked areas (e.g., water and developed) account for the remaining 9% of the landscape. Strong predictors of near-surface permafrost include climatic indices, land cover, topography, and Landsat 7 Enhanced Thematic Mapper Plus spectral information. Our quantitative modeling approach enabled us to generate regional near-surface permafrost maps and provide essential information for resource managers and modelers to better understand near-surface permafrost distribution and how it relates to environmental factors and conditions.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research: Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/2013JG002594","usgsCitation":"Pastick, N.J., Jorgenson, M., Wylie, B.K., Rose, J.R., Rigge, M., and Walvoord, M.A., 2014, Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin: Journal of Geophysical Research: Biogeosciences, v. 119, no. 6, p. 1244-1265, https://doi.org/10.1002/2013JG002594.","productDescription":"22 p.","startPage":"1244","endPage":"1265","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056842","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jg002594","text":"Publisher Index Page"},{"id":294946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294945,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013JG002594"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaskan Yukon River Basin","volume":"119","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-30","publicationStatus":"PW","scienceBaseUri":"542fbaaee4b092f17df61dfa","contributors":{"authors":[{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":493735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgenson, M. Torre","contributorId":34848,"corporation":false,"usgs":true,"family":"Jorgenson","given":"M. Torre","affiliations":[],"preferred":false,"id":493738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":493734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rose, Joshua R.","contributorId":12395,"corporation":false,"usgs":true,"family":"Rose","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":493736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rigge, Matthew 0000-0003-4471-8009","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":18295,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","affiliations":[],"preferred":false,"id":493737,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walvoord, Michelle Ann 0000-0003-4269-8366 walvoord@usgs.gov","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":147211,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"walvoord@usgs.gov","middleInitial":"Ann","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":493739,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70103152,"text":"70103152 - 2014 - Estimating sample size for landscape-scale mark-recapture studies of North American migratory tree bats","interactions":[],"lastModifiedDate":"2014-10-01T15:17:53","indexId":"70103152","displayToPublicDate":"2014-06-01T15:13:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":629,"text":"Acta Chiropterologica","active":true,"publicationSubtype":{"id":10}},"title":"Estimating sample size for landscape-scale mark-recapture studies of North American migratory tree bats","docAbstract":"Concern for migratory tree-roosting bats in North America has grown because of possible population declines from wind energy development. This concern has driven interest in estimating population-level changes. Mark-recapture methodology is one possible analytical framework for assessing bat population changes, but sample size requirements to produce reliable estimates have not been estimated. To illustrate the sample sizes necessary for a mark-recapture-based monitoring program we conducted power analyses using a statistical model that allows reencounters of live and dead marked individuals. We ran 1,000 simulations for each of five broad sample size categories in a Burnham joint model, and then compared the proportion of simulations in which 95% confidence intervals overlapped between and among years for a 4-year study. Additionally, we conducted sensitivity analyses of sample size to various capture probabilities and recovery probabilities. More than 50,000 individuals per year would need to be captured and released to accurately determine 10% and 15% declines in annual survival. To detect more dramatic declines of 33% or 50% survival over four years, then sample sizes of 25,000 or 10,000 per year, respectively, would be sufficient. Sensitivity analyses reveal that increasing recovery of dead marked individuals may be more valuable than increasing capture probability of marked individuals. Because of the extraordinary effort that would be required, we advise caution should such a mark-recapture effort be initiated because of the difficulty in attaining reliable estimates. We make recommendations for what techniques show the most promise for mark-recapture studies of bats because some techniques violate the assumptions of mark-recapture methodology when used to mark bats.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Acta Chiropterologica","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Museum and Institute of Zoology, Polish Academy of Sciences","doi":"10.3161/150811014X683426","usgsCitation":"Ellison, L.E., and Lukacs, P., 2014, Estimating sample size for landscape-scale mark-recapture studies of North American migratory tree bats: Acta Chiropterologica, v. 16, no. 1, p. 231-239, https://doi.org/10.3161/150811014X683426.","productDescription":"9 p.","startPage":"231","endPage":"239","ipdsId":"IP-056218","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":294737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294736,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3161/150811014X683426"}],"otherGeospatial":"North America","volume":"16","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542d179ae4b092f17defc5a7","contributors":{"authors":[{"text":"Ellison, Laura E. ellisonl@usgs.gov","contributorId":3220,"corporation":false,"usgs":true,"family":"Ellison","given":"Laura","email":"ellisonl@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":493164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lukacs, Paul M.","contributorId":43285,"corporation":false,"usgs":true,"family":"Lukacs","given":"Paul M.","affiliations":[],"preferred":false,"id":493165,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70119245,"text":"70119245 - 2014 - Isotopically modified silver nanoparticles to assess nanosilver bioavailability and toxicity at environmentally relevant exposures","interactions":[],"lastModifiedDate":"2018-09-18T16:41:14","indexId":"70119245","displayToPublicDate":"2014-06-01T14:13:27","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1529,"text":"Environmental Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Isotopically modified silver nanoparticles to assess nanosilver bioavailability and toxicity at environmentally relevant exposures","docAbstract":"A major challenge in understanding the environmental implications of nanotechnology lies in studying nanoparticle uptake in organisms at environmentally realistic exposure concentrations. Typically, high exposure concentrations are needed to trigger measurable effects and to detect accumulation above background. But application of tracer techniques can overcome these limitations. Here we synthesised, for the first time, citrate-coated Ag nanoparticles using Ag that was 99.7 % <sup>109</sup>Ag. In addition to conducting reactivity and dissolution studies, we assessed the bioavailability and toxicity of these isotopically modified Ag nanoparticles (<sup>109</sup>Ag NPs) to a freshwater snail under conditions typical of nature. We showed that accumulation of <sup>109</sup>Ag from <sup>109</sup>Ag NPs is detectable in the tissues of <i>Lymnaea stagnalis</i> after 24-h exposure to aqueous concentrations as low as 6 ng L<sup>–1</sup> as well as after 3 h of dietary exposure to concentrations as low as 0.07 μg g<sup>–1</sup>. Silver uptake from unlabelled Ag NPs would not have been detected under similar exposure conditions. Uptake rates of <sup>109</sup>Ag from <sup>109</sup>Ag NPs mixed with food or dispersed in water were largely linear over a wide range of concentrations. Particle dissolution was most important at low waterborne concentrations. We estimated that 70 % of the bioaccumulated <sup>109</sup>Ag concentration in <i>L. stagnalis</i> at exposures <0.1 µg L<sup>–1</sup> originated from the newly solubilised Ag. Above this concentration, we predicted that 80 % of the bioaccumulated <sup>109</sup>Ag concentration originated from the <sup>109</sup>Ag NPs. It was not clear if agglomeration had a major influence on uptake rates.","language":"English","publisher":"CSIRO Publishing","publisherLocation":"Collingwood, Australia","doi":"10.1071/EN13141","usgsCitation":"Croteau, M., Dybowska, A.D., Luoma, S.N., Misra, S.K., and Valsami-Jones, E., 2014, Isotopically modified silver nanoparticles to assess nanosilver bioavailability and toxicity at environmentally relevant exposures: Environmental Chemistry, v. 11, no. 3, p. 247-256, https://doi.org/10.1071/EN13141.","productDescription":"10 p.","startPage":"247","endPage":"256","numberOfPages":"10","ipdsId":"IP-052049","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472958,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/en13141","text":"Publisher Index Page"},{"id":291719,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1071/EN13141"},{"id":291720,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e1efcfe4b0fe532be2de39","contributors":{"authors":[{"text":"Croteau, Marie-Noële","contributorId":22863,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie-Noële","affiliations":[],"preferred":false,"id":497617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dybowska, Agnieszka D.","contributorId":101201,"corporation":false,"usgs":true,"family":"Dybowska","given":"Agnieszka","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":497620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":497616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Misra, Superb K.","contributorId":91231,"corporation":false,"usgs":true,"family":"Misra","given":"Superb","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":497619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Valsami-Jones, Eugenia","contributorId":26057,"corporation":false,"usgs":true,"family":"Valsami-Jones","given":"Eugenia","email":"","affiliations":[],"preferred":false,"id":497618,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70124277,"text":"70124277 - 2014 - Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI","interactions":[],"lastModifiedDate":"2014-09-11T13:56:39","indexId":"70124277","displayToPublicDate":"2014-06-01T13:46:29","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI","docAbstract":"Agricultural production capacity contributes to food security in Afghanistan and is largely dependent on irrigated farming, mostly utilizing surface water fed by snowmelt. Because of the high contribution of irrigated crops (> 80%) to total agricultural production, knowing the spatial distribution and year-to-year variability in irrigated areas is imperative to monitoring food security for the country. We used 16-day composites of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to create 23-point time series for each year from 2000 through 2013. Seasonal peak values and time series were used in a threshold-dependent decision tree algorithm to map irrigated areas in Afghanistan for the last 14 years. In the absence of ground reference irrigated area information, we evaluated these maps with the irrigated areas classified from multiple snapshots of the landscape during the growing season from Landsat 5 optical and thermal sensor images. We were able to identify irrigated areas using Landsat imagery by selecting as irrigated those areas with Landsat-derived NDVI greater than 0.30–0.45, depending on the date of the Landsat image and surface temperature less than or equal to 310 Kelvin (36.9 ° C). Due to the availability of Landsat images, we were able to compare with the MODIS-derived maps for four years: 2000, 2009, 2010, and 2011. The irrigated areas derived from Landsat agreed well r<sup>2</sup> = 0.91 with the irrigated areas derived from MODIS, providing confidence in the MODIS NDVI threshold approach. The maps portrayed a highly dynamic irrigated agriculture practice in Afghanistan, where the amount of irrigated area was largely determined by the availability of surface water, especially snowmelt, and varied by as much as 30% between water surplus and water deficit years. During the past 14 years, 2001, 2004, and 2008 showed the lowest levels of irrigated area (~ 1.5 million hectares), attesting to the severe drought conditions in those years, whereas 2009, 2012 and 2013 registered the largest irrigated area (~ 2.5 million hectares) due to record snowpack and snowmelt in the region. The model holds promise the ability to provide near-real-time (by the end of the growing seasons) estimates of irrigated area, which are beneficial for food security monitoring as well as subsequent decision making for the country. While the model is developed for Afghanistan, it can be adopted with appropriate adjustments in the derived threshold values to map irrigated areas elsewhere.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2014.04.008","usgsCitation":"Pervez, M., Budde, M., and Rowland, J., 2014, Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI: Remote Sensing of Environment, v. 149, p. 155-165, https://doi.org/10.1016/j.rse.2014.04.008.","productDescription":"11 p.","startPage":"155","endPage":"165","numberOfPages":"11","ipdsId":"IP-049479","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":293759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293755,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2014.04.008"}],"country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.52,29.38 ], [ 60.52,38.49 ], [ 74.89,38.49 ], [ 74.89,29.38 ], [ 60.52,29.38 ] ] ] } } ] }","volume":"149","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5412b9b1e4b0239f1986baa5","contributors":{"authors":[{"text":"Pervez, Md Shahriar 0000-0003-3417-1871 shahriar.pervez.ctr@usgs.gov","orcid":"https://orcid.org/0000-0003-3417-1871","contributorId":74230,"corporation":false,"usgs":true,"family":"Pervez","given":"Md Shahriar","email":"shahriar.pervez.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":500640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budde, Michael 0000-0002-9098-2751","orcid":"https://orcid.org/0000-0002-9098-2751","contributorId":36867,"corporation":false,"usgs":true,"family":"Budde","given":"Michael","affiliations":[],"preferred":false,"id":500639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rowland, James 0000-0003-4837-3511 rowland@usgs.gov","orcid":"https://orcid.org/0000-0003-4837-3511","contributorId":3108,"corporation":false,"usgs":true,"family":"Rowland","given":"James","email":"rowland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":500638,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70160698,"text":"70160698 - 2014 - Examination of the influence of juvenile Atlantic salmon on the feeding mode of juvenile steelhead in Lake Ontario tributaries","interactions":[],"lastModifiedDate":"2015-12-30T12:29:43","indexId":"70160698","displayToPublicDate":"2014-06-01T13:30:00","publicationYear":"2014","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":"Examination of the influence of juvenile Atlantic salmon on the feeding mode of juvenile steelhead in Lake Ontario tributaries","docAbstract":"<p>We examined diets of 1204 allopatric and sympatric juvenile Atlantic salmon (<i>Salmo salar</i>) and steelhead (<i>Oncorhynchus mykiss</i>) in three tributaries of Lake Ontario. The diet composition of both species consisted primarily of ephemeropterans, trichopterans, and chironomids, although juvenile steelhead consumed more terrestrial invertebrates, especially at the sympatric sites. Subyearlings of both species consumed small prey (i.e. chironomids) whereas large prey (i.e. perlids) made up a higher percentage of the diet of yearlings. The diet of juvenile steelhead at the allopatric sites was more closely associated with the composition of the benthos than with the drift, but was about equally associated with the benthos and drift at the sympatric sites. The diet of both subyearling and yearling Atlantic salmon was more closely associated with the benthos than the drift at the sympatric sites. The evidence suggests that juvenile steelhead may subtly alter their feeding behavior in sympatry with Atlantic salmon. This behavioral adaptation may reduce competitive interactions between these species.</p>","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Toronto","doi":"10.1016/j.jglr.2014.03.005","usgsCitation":"Johnson, J.H., and Waldt, E.M., 2014, Examination of the influence of juvenile Atlantic salmon on the feeding mode of juvenile steelhead in Lake Ontario tributaries: Journal of Great Lakes Research, v. 40, no. 2, p. 370-376, https://doi.org/10.1016/j.jglr.2014.03.005.","productDescription":"7 p.","startPage":"370","endPage":"376","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051104","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Little Sandy Creek, Orwell Brook, Trout Brook","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.25747680664062,\n              43.489295765452496\n            ],\n            [\n              -76.25747680664062,\n              43.74728909225906\n            ],\n            [\n              -75.816650390625,\n              43.74728909225906\n            ],\n            [\n              -75.816650390625,\n              43.489295765452496\n            ],\n            [\n              -76.25747680664062,\n              43.489295765452496\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"40","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56850e91e4b0a04ef4933902","contributors":{"authors":[{"text":"Johnson, James H. 0000-0002-5619-3871 jhjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5619-3871","contributorId":389,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"jhjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waldt, Emily M. ewaldt@usgs.gov","contributorId":4358,"corporation":false,"usgs":true,"family":"Waldt","given":"Emily","email":"ewaldt@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583605,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70127897,"text":"70127897 - 2014 - Comparing simulated carbon budget of a Lei bamboo forest with flux tower data","interactions":[],"lastModifiedDate":"2014-10-02T12:48:48","indexId":"70127897","displayToPublicDate":"2014-06-01T12:46:53","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3532,"text":"Terrestrial, Atmospheric and Oceanic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Comparing simulated carbon budget of a Lei bamboo forest with flux tower data","docAbstract":"Bamboo forest ecosystem is the part of the forest ecosystem. The distribution area of bamboo forest is limited, but in somewhere, like south China, it has been cultivate for a long time with human management. As the climate change has been take great effect on forest carbon budget, many researchers pay attention to the carbon budget in bamboo forest. Moreover cultivative management had a significant impact on the bamboo forest carbon budget. In this study, we modified a terrestrial ecosystem model named Integrated Biosphere Simulator (IBIS) according the management of Lei bamboo forest. Some management, like fertilization, shoots harvesting and organic mulching in winter, had been incorporated into model. Then we had compared model results with the observation data from a Lei bamboo flux tower. The simulated and observed results had achieved good consistency. Our simulated Lei bamboo forest yearly net ecosystem productivity (NEP) was 0.41 kgC a<sup>-1</sup> of carbon, which is very close to the observation data 0.45 kgC a<sup>-1</sup> of carbon. And the monthly simulated results can take the change of carbon budget in each month, similar to the data we got from flux tower. It reflects that the modified IBIS model can characterize the growth of bamboo forest and perform the simulation well. And then two groups of simulations were set to evaluate effects of cultivative managements on Lei bamboo forests carbon budget. And results showed that both fertilization and organic mulching had taken positive effects on Lei bamboo forests carbon sequestration.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Terrestrial, Atmospheric and Oceanic Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Chinese Geoscience Union","publisherLocation":"Taipei, Taiwan","doi":"10.3319/TAO.2014.01.13.01(TT)","usgsCitation":"Li, X., Jiang, H., Liu, J., Sun, C., Wang, Y., and Jin, J., 2014, Comparing simulated carbon budget of a Lei bamboo forest with flux tower data: Terrestrial, Atmospheric and Oceanic Sciences, v. 25, no. 3, p. 359-368, https://doi.org/10.3319/TAO.2014.01.13.01(TT).","productDescription":"10 p.","startPage":"359","endPage":"368","numberOfPages":"10","ipdsId":"IP-060183","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":472959,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3319/tao.2014.01.13.01(tt)","text":"Publisher Index Page"},{"id":294821,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294801,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3319/TAO.2014.01.13.01(TT)"}],"volume":"25","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e6947e4b092f17df5a786","contributors":{"authors":[{"text":"Li, Xuehe","contributorId":95819,"corporation":false,"usgs":true,"family":"Li","given":"Xuehe","email":"","affiliations":[],"preferred":false,"id":502632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jiang, Hong","contributorId":108417,"corporation":false,"usgs":true,"family":"Jiang","given":"Hong","affiliations":[],"preferred":false,"id":502633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":502628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sun, Cheng","contributorId":18287,"corporation":false,"usgs":true,"family":"Sun","given":"Cheng","email":"","affiliations":[],"preferred":false,"id":502630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Ying","contributorId":76237,"corporation":false,"usgs":true,"family":"Wang","given":"Ying","email":"","affiliations":[],"preferred":false,"id":502631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jin, Jiaxin","contributorId":13561,"corporation":false,"usgs":true,"family":"Jin","given":"Jiaxin","affiliations":[],"preferred":false,"id":502629,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
]}