{"pageNumber":"1315","pageRowStart":"32850","pageSize":"25","recordCount":165312,"records":[{"id":70128991,"text":"70128991 - 2014 - Hierarchical spatial genetic structure in a distinct population segment of greater sage-grouse","interactions":[],"lastModifiedDate":"2016-12-14T12:11:21","indexId":"70128991","displayToPublicDate":"2014-06-07T09:51:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical spatial genetic structure in a distinct population segment of greater sage-grouse","docAbstract":"<p>Greater sage-grouse (<em>Centrocercus urophasianus</em>) within the Bi-State Management Zone (area along the border between Nevada and California) are geographically isolated on the southwestern edge of the species&rsquo; range. Previous research demonstrated that this population is genetically unique, with a high proportion of unique mitochondrial DNA (mtDNA) haplotypes and with significant differences in microsatellite allele frequencies compared to populations across the species&rsquo; range. As a result, this population was considered a distinct population segment (DPS) and was recently proposed for listing as threatened under the U.S. Endangered Species Act. A more comprehensive understanding of the boundaries of this genetically unique population (where the Bi-State population begins) and an examination of genetic structure within the Bi-State is needed to help guide effective management decisions. We collected DNA from eight sampling locales within the Bi-State (N = 181) and compared those samples to previously collected DNA from the two most proximal populations outside of the Bi-State DPS, generating mtDNA sequence data and amplifying 15 nuclear microsatellites. Both mtDNA and microsatellite analyses support the idea that the Bi-State DPS represents a genetically unique population, which has likely been separated for thousands of years. Seven mtDNA haplotypes were found exclusively in the Bi-State population and represented 73 % of individuals, while three haplotypes were shared with neighboring populations. In the microsatellite analyses both STRUCTURE and FCA separate the Bi-State from the neighboring populations. We also found genetic structure within the Bi-State as both types of data revealed differences between the northern and southern part of the Bi-State and there was evidence of isolation-by-distance. STRUCTURE revealed three subpopulations within the Bi-State consisting of the northern Pine Nut Mountains (PNa), mid Bi-State, and White Mountains (WM) following a north&ndash;south gradient. This genetic subdivision within the Bi-State is likely the result of habitat loss and fragmentation that has been exacerbated by recent human activities and the encroachment of singleleaf pinyon (<em>Pinus monophylla</em>) and juniper (<em>Juniperus</em> spp.) trees. While genetic concerns may be only one of many priorities for the conservation and management of the Bi-State greater sage-grouse, we believe that they warrant attention along with other issues (e.g., quality of sagebrush habitat, preventing future loss of habitat). Management actions that promote genetic connectivity, especially with respect to WM and PNa, may be critical to the long-term viability of the Bi-State DPS.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10592-014-0618-8","usgsCitation":"Oyler-McCance, S.J., Casazza, M.L., Fike, J.A., and Coates, P.S., 2014, Hierarchical spatial genetic structure in a distinct population segment of greater sage-grouse: Conservation Genetics, v. 15, no. 6, p. 1299-1311, https://doi.org/10.1007/s10592-014-0618-8.","productDescription":"13 p.","startPage":"1299","endPage":"1311","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052505","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":295364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295348,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10592-014-0618-8"}],"country":"United States","state":"California, Nevada","volume":"15","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-07","publicationStatus":"PW","scienceBaseUri":"5440de2de4b0b0a643c732db","contributors":{"authors":[{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":503267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. fikej@usgs.gov","contributorId":4564,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer","email":"fikej@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":503269,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":503268,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"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":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":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":70098476,"text":"ofr20141060 - 2014 - Quality-assurance and data management plan for groundwater activities by the U.S. Geological Survey in Kansas, 2014","interactions":[],"lastModifiedDate":"2014-06-06T15:10:05","indexId":"ofr20141060","displayToPublicDate":"2014-06-06T15:07:00","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":"2014-1060","title":"Quality-assurance and data management plan for groundwater activities by the U.S. Geological Survey in Kansas, 2014","docAbstract":"<p>As the Nation’s principle earth-science information agency, the U.S. Geological Survey (USGS) is depended on to collect data of the highest quality. This document is a quality-assurance plan for groundwater activities (GWQAP) of the Kansas Water Science Center. The purpose of this GWQAP is to establish a minimum set of guidelines and practices to be used by the Kansas Water Science Center to ensure quality in groundwater activities. Included within these practices are the assignment of responsibilities for implementing quality-assurance activities in the Kansas Water Science Center and establishment of review procedures needed to ensure the technical quality and reliability of the groundwater products. In addition, this GWQAP is intended to complement quality-assurance plans for surface-water and water-quality activities and similar plans for the Kansas Water Science Center and general project activities throughout the USGS.</p>\n<br>\n<p>This document provides the framework for collecting, analyzing, and reporting groundwater data that are quality assured and quality controlled. This GWQAP presents policies directing the collection, processing, analysis, storage, review, and publication of groundwater data. In addition, policies related to organizational responsibilities, training, project planning, and safety are presented. These policies and practices pertain to all groundwater activities conducted by the Kansas Water Science Center, including data-collection programs, interpretive and research projects. This report also includes the data management plan that describes the progression of data management from data collection to archiving and publication.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141060","issn":"2331-1258","usgsCitation":"Putnam, J.E., and Hansen, C.V., 2014, Quality-assurance and data management plan for groundwater activities by the U.S. Geological Survey in Kansas, 2014: U.S. Geological Survey Open-File Report 2014-1060, v, 37 p., https://doi.org/10.3133/ofr20141060.","productDescription":"v, 37 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-051485","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":288156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141060.jpg"},{"id":288154,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1060/"},{"id":288155,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1060/pdf/ofr2014-1060.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae77f9e4b0abf75cf2c668","contributors":{"authors":[{"text":"Putnam, James E. jputnam@usgs.gov","contributorId":2021,"corporation":false,"usgs":true,"family":"Putnam","given":"James","email":"jputnam@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":491730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Cristi V. chansen@usgs.gov","contributorId":435,"corporation":false,"usgs":true,"family":"Hansen","given":"Cristi","email":"chansen@usgs.gov","middleInitial":"V.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":491729,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70111698,"text":"ds856 - 2014 - Archive of digital chirp subbottom profile data collected during USGS cruise 12BIM03 offshore of the Chandeleur Islands, Louisiana, July 2012","interactions":[],"lastModifiedDate":"2023-01-04T21:51:19.731225","indexId":"ds856","displayToPublicDate":"2014-06-06T14:19:00","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":"856","title":"Archive of digital chirp subbottom profile data collected during USGS cruise 12BIM03 offshore of the Chandeleur Islands, Louisiana, July 2012","docAbstract":"<p>From July 23 - 31, 2012, the U.S. Geological Survey conducted geophysical surveys to investigate the geologic controls on barrier island framework and long-term sediment transport along the oil spill mitigation sand berm constructed at the north end and just offshore of the Chandeleur Islands, La. (figure 1). This effort is part of a broader USGS study, which seeks to better understand barrier island evolution over medium time scales (months to years). This report serves as an archive of unprocessed digital chirp subbottom data, trackline maps, navigation files, Geographic Information System (GIS) files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Gained (showing a relative increase in signal amplitude) digital images of the seismic profiles are also provided. Refer to the Abbreviations page for expansions of acronyms and abbreviations used in this report.</p>\n\n<br>\n\n<p>The USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 12BIM03 tells us the data were collected in 2012 during the third field activity for that project in that calendar year and BIM is a generic code, which represents efforts related to Barrier Island Mapping. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID.</p>\n\n<br>\n\n<p>All chirp systems use a signal of continuously varying frequency; the EdgeTech SB-424 system used during this survey produces high-resolution, shallow-penetration (typically less than 50 milliseconds (ms)) profile images of sub-seafloor stratigraphy. The towfish contains a transducer that transmits and receives acoustic energy and is typically towed 1 - 2 m below the sea surface. As transmitted acoustic energy intersects density boundaries, such as the seafloor or sub-surface sediment layers, energy is reflected back toward the transducer, received, and recorded by a PC-based seismic acquisition system. This process is repeated at regular time intervals (for example, 0.125 seconds (s)) and returned energy is recorded for a specific duration (for example, 50 ms). In this way, a two-dimensional (2-D) vertical image of the shallow geologic structure beneath the ship track is produced. Figure 2 displays the acquisition geometry. Refer to table 1 for a summary of acquisition parameters and table 2 for trackline statistics.</p>\n\n<br>\n\n<p>The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG Y rev. 0 format (Barry and others, 1975); the first 3,200 bytes of the card image header are in ASCII format instead of EBCDIC format. The SEG Y files may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU) (Cohen and Stockwell, 2010). See the How To Download SEG Y Data page for download instructions. The web version of this archive does not contain the SEG Y trace files. These files are very large and would require extremely long download times. To obtain the complete DVD archive, contact USGS Information Services at 1-888-ASK-USGS or infoservices@usgs.gov. The printable profiles provided here are GIF images that were processed and gained using SU software and can be viewed from the Profiles page or from links located on the trackline maps; refer to the Software page for links to example SU processing scripts. The SEG Y files are available on the DVD version of this report or on the Web, downloadable via the USGS Coastal and Marine Geoscience Data System (http://cmgds.marine.usgs.gov). The data are also available for viewing using GeoMapApp (http://www.geomapapp.org) and Virtual Ocean (http://www.virtualocean.org) multi-platform open source software.</p>\n\n<br>\n\n<p>Detailed information about the navigation system used can be found in table 1 and the Field Activity Collection System (FACS) logs. To view the trackline maps and navigation files, and for more information about these items, see the Navigation page.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds856","usgsCitation":"Forde, A.S., Miselis, J.L., and Wiese, D.S., 2014, Archive of digital chirp subbottom profile data collected during USGS cruise 12BIM03 offshore of the Chandeleur Islands, Louisiana, July 2012: U.S. Geological Survey Data Series 856, HTML Document, https://doi.org/10.3133/ds856.","productDescription":"HTML Document","onlineOnly":"Y","ipdsId":"IP-054768","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288153,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds856.jpg"},{"id":288152,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/856/html/ds856_home.html"},{"id":288151,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/856/"}],"country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.916378,\n              29.951025\n            ],\n            [\n              -88.916378,\n              30.094522\n            ],\n            [\n              -88.797183,\n              30.094522\n            ],\n            [\n              -88.797183,\n              29.951025\n            ],\n            [\n              -88.916378,\n              29.951025\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5396d760e4b0f7580bc0a8d0","contributors":{"authors":[{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiese, Dana S. dwiese@usgs.gov","contributorId":2476,"corporation":false,"usgs":true,"family":"Wiese","given":"Dana","email":"dwiese@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494441,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"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":70103029,"text":"sir20145064 - 2014 - Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12","interactions":[],"lastModifiedDate":"2017-10-12T20:13:26","indexId":"sir20145064","displayToPublicDate":"2014-06-05T12:51:00","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":"2014-5064","title":"Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12","docAbstract":"<p>The Red River of the North (hereafter referred to as “Red River”) Basin is an important hydrologic region where water is a valuable resource for the region’s economy. Continuous water-quality monitors have been operated by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health, Minnesota Pollution Control Agency, City of Fargo, City of Moorhead, City of Grand Forks, and City of East Grand Forks at the Red River at Fargo, North Dakota, from 2003 through 2012 and at Grand Forks, N.Dak., from 2007 through 2012. The purpose of the monitoring was to provide a better understanding of the water-quality dynamics of the Red River and provide a way to track changes in water quality. Regression equations were developed that can be used to estimate concentrations and loads for dissolved solids, sulfate, chloride, nitrate plus nitrite, total phosphorus, and suspended sediment using explanatory variables such as streamflow, specific conductance, and turbidity.</p>\n<br/>\n<p>Specific conductance was determined to be a significant explanatory variable for estimating dissolved solids concentrations at the Red River at Fargo and Grand Forks. The regression equations provided good relations between dissolved solid concentrations and specific conductance for the Red River at Fargo and at Grand Forks, with adjusted coefficients of determination of 0.99 and 0.98, respectively. Specific conductance, log-transformed streamflow, and a seasonal component were statistically significant explanatory variables for estimating sulfate in the Red River at Fargo and Grand Forks. Regression equations provided good relations between sulfate concentrations and the explanatory variables, with adjusted coefficients of determination of 0.94 and 0.89, respectively.</p>\n<br/>\n<p>For the Red River at Fargo and Grand Forks, specific conductance, streamflow, and a seasonal component were statistically significant explanatory variables for estimating chloride. For the Red River at Grand Forks, a time component also was a statistically significant explanatory variable for estimating chloride. The regression equations for chloride at the Red River at Fargo provided a fair relation between chloride concentrations and the explanatory variables, with an adjusted coefficient of determination of 0.66 and the equation for the Red River at Grand Forks provided a relatively good relation between chloride concentrations and the explanatory variables, with an adjusted coefficient of determination of 0.77.</p>\n<br/>\n<p>Turbidity and streamflow were statistically significant explanatory variables for estimating nitrate plus nitrite concentrations at the Red River at Fargo and turbidity was the only statistically significant explanatory variable for estimating nitrate plus nitrite concentrations at Grand Forks. The regression equation for the Red River at Fargo provided a relatively poor relation between nitrate plus nitrite concentrations, turbidity, and streamflow, with an adjusted coefficient of determination of 0.46. The regression equation for the Red River at Grand Forks provided a fair relation between nitrate plus nitrite concentrations and turbidity, with an adjusted coefficient of determination of 0.73. Some of the variability that was not explained by the equations might be attributed to different sources contributing nitrates to the stream at different times. Turbidity, streamflow, and a seasonal component were statistically significant explanatory variables for estimating total phosphorus at the Red River at Fargo and Grand Forks. The regression equation for the Red River at Fargo provided a relatively fair relation between total phosphorus concentrations, turbidity, streamflow, and season, with an adjusted coefficient of determination of 0.74. The regression equation for the Red River at Grand Forks provided a good relation between total phosphorus concentrations, turbidity, streamflow, and season, with an adjusted coefficient of determination of 0.87.</p>\n<br/>\n<p>For the Red River at Fargo, turbidity and streamflow were statistically significant explanatory variables for estimating suspended-sediment concentrations. For the Red River at Grand Forks, turbidity was the only statistically significant explanatory variable for estimating suspended-sediment concentration. The regression equation at the Red River at Fargo provided a good relation between suspended-sediment concentration, turbidity, and streamflow, with an adjusted coefficient of determination of 0.95. The regression equation for the Red River at Grand Forks provided a good relation between suspended-sediment concentration and turbidity, with an adjusted coefficient of determination of 0.96.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145064","collaboration":"Prepared in cooperation with the North Dakota Department of Health, Minnesota Pollution Control Agency, City of Fargo, City of Moorhead, City of Grand Forks, and City of East Grand Forks","usgsCitation":"Galloway, J.M., 2014, Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12: U.S. Geological Survey Scientific Investigations Report 2014-5064, vi, 37 p., https://doi.org/10.3133/sir20145064.","productDescription":"vi, 37 p.","numberOfPages":"48","onlineOnly":"Y","temporalStart":"2003-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-054797","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":288108,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5064/"},{"id":288109,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5064/pdf/sir2014-5064.pdf"},{"id":288110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145064.jpg"}],"country":"United States","state":"North Dakota","city":"Grand Forks;Fargo","otherGeospatial":"Red River Of The North","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.9863,45.4996 ], [ -100.9863,49.0 ], [ -93.8342,49.0 ], [ -93.8342,45.4996 ], [ -100.9863,45.4996 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53918350e4b06f80638265a4","contributors":{"authors":[{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493093,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"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":70111384,"text":"ofr20141112 - 2014 - Investigation of methods for successful installation and operation of Juvenile Salmon Acoustic Telemetry System (JSATS) hydrophones in the Willamette River, Oregon, 2012","interactions":[],"lastModifiedDate":"2014-06-05T08:22:30","indexId":"ofr20141112","displayToPublicDate":"2014-06-05T08:17:00","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":"2014-1112","title":"Investigation of methods for successful installation and operation of Juvenile Salmon Acoustic Telemetry System (JSATS) hydrophones in the Willamette River, Oregon, 2012","docAbstract":"Acoustic telemetry equipment was installed at three sites in the Willamette River during October 2012 to test the effectiveness of using the Juvenile Salmon Acoustic Telemetry System to monitor the movements of fish in a high-flow, high-velocity riverine environment. Hydrophones installed on concrete blocks were placed on the bottom of the river, and data cables were run from the hydrophones to shore where they were attached to anchor points. Under relatively low-flow conditions (less than approximately 10,000 cubic feet per second) the monitoring system remained in place and could be used to detect tagged fish as they traveled downstream during their seaward migration. At river discharge over approximately 10,000 cubic feet per second, the hydrophones were damaged and cables were lost because of the large volume of woody debris in the river and the increase in water velocity. Damage at two of the sites was sufficient to prevent data collection. A limited amount of data was collected from the equipment at the third site. Site selection and deployment strategies were re-evaluated, and an alternate deployment methodology was designed for implementation in 2013.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141112","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Rutz, G.L., Sholtis, M., Adams, N.S., and Beeman, J.W., 2014, Investigation of methods for successful installation and operation of Juvenile Salmon Acoustic Telemetry System (JSATS) hydrophones in the Willamette River, Oregon, 2012: U.S. Geological Survey Open-File Report 2014-1112, iv, 18 p., https://doi.org/10.3133/ofr20141112.","productDescription":"iv, 18 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-055083","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":288100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141112.PNG"},{"id":288097,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1112/"},{"id":288099,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1112/pdf/ofr2014-1112.pdf"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.0024,43.3771 ], [ -125.0024,46.1342 ], [ -120.8002,46.1342 ], [ -120.8002,43.3771 ], [ -125.0024,43.3771 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53918350e4b06f80638265a8","contributors":{"authors":[{"text":"Rutz, Gary L. grutz@usgs.gov","contributorId":3886,"corporation":false,"usgs":true,"family":"Rutz","given":"Gary","email":"grutz@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":494331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sholtis, Matthew D.","contributorId":69481,"corporation":false,"usgs":true,"family":"Sholtis","given":"Matthew D.","affiliations":[],"preferred":false,"id":494332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":494330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":494329,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70111431,"text":"70111431 - 2014 - <i>Alexandrium fundyense</i> cysts in the Gulf of Maine: long-term time series of abundance and distribution, and linkages to past and future blooms","interactions":[],"lastModifiedDate":"2014-06-04T15:24:15","indexId":"70111431","displayToPublicDate":"2014-06-04T15:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1371,"text":"Deep-Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"<i>Alexandrium fundyense</i> cysts in the Gulf of Maine: long-term time series of abundance and distribution, and linkages to past and future blooms","docAbstract":"<p>Here we document <i>Alexandrium fundyense</i> cyst abundance and distribution patterns over nine years (1997 and 2004–2011) in the coastal waters of the Gulf of Maine (GOM) and identify linkages between those patterns and several metrics of the severity or magnitude of blooms occurring before and after each autumn cyst survey. We also explore the relative utility of two measures of cyst abundance and demonstrate that GOM cyst counts can be normalized to sediment volume, revealing meaningful patterns equivalent to those determined with dry weight normalization.</p>\n<br/>\n<p>Cyst concentrations were highly variable spatially. Two distinct seedbeds (defined here as accumulation zones with>300 cysts cm<sup>−3</sup>) are evident, one in the Bay of Fundy (BOF) and one in mid-coast Maine. Overall, seedbed locations remained relatively constant through time, but their area varied 3–4 fold, and total cyst abundance more than 10 fold among years. A major expansion of the mid-coast Maine seedbed occurred in 2009 following an unusually intense <i>A. fundyense</i> bloom with visible red-water conditions, but that feature disappeared by late 2010. The regional system thus has only two seedbeds with the bathymetry, sediment characteristics, currents, biology, and environmental conditions necessary to persist for decades or longer. Strong positive correlations were confirmed between the abundance of cysts in both the 0–1 and the 0–3 cm layers of sediments in autumn and geographic measures of the extent of the bloom that occurred the next year (i.e., cysts→blooms), such as the length of coastline closed due to shellfish toxicity or the southernmost latitude of shellfish closures. In general, these metrics of bloom geographic extent did not correlate with the number of cysts in sediments following the blooms (blooms→cysts). There are, however, significant positive correlations between 0–3 cm cyst abundances and metrics of the preceding bloom that are indicative of bloom intensity or vegetative cell abundance (e.g., cumulative shellfish toxicity, duration of detectable toxicity in shellfish, and bloom termination date). These data suggest that it may be possible to use cyst abundance to empirically forecast the geographic extent of the forthcoming bloom and, conversely, to use other metrics from bloom and toxicity events to forecast the size of the subsequent cyst population as the inoculum for the next year's bloom. This is an important step towards understanding the excystment/encystment cycle in <i>A. fundyense</i> bloom dynamics while also augmenting our predictive capability for this HAB-forming species in the GOM.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Deep-Sea Research Part II: Topical Studies in Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2013.10.002","usgsCitation":"Anderson, D.M., Keafer, B.A., Kleindinst, J.L., McGillicuddy, D.J., Martin, J.L., Norton, K., Pilskaln, C.H., Smith, J.L., Sherwood, C.R., and Butman, B., 2014, <i>Alexandrium fundyense</i> cysts in the Gulf of Maine: long-term time series of abundance and distribution, and linkages to past and future blooms: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 103, p. 6-26, https://doi.org/10.1016/j.dsr2.2013.10.002.","productDescription":"21 p.","startPage":"6","endPage":"26","numberOfPages":"21","ipdsId":"IP-049742","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472950,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4085992","text":"External Repository"},{"id":288095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288092,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.dsr2.2013.10.002"}],"country":"United States","state":"Maine","otherGeospatial":"Bay Of Fundy;Gulf Of Maine","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -72.0,40.0 ], [ -72.0,46.0 ], [ -65.0,46.0 ], [ -65.0,40.0 ], [ -72.0,40.0 ] ] ] } } ] }","volume":"103","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"539031cfe4b04eea98bf84b1","contributors":{"authors":[{"text":"Anderson, Donald M.","contributorId":79801,"corporation":false,"usgs":true,"family":"Anderson","given":"Donald","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":494358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keafer, Bruce A.","contributorId":102795,"corporation":false,"usgs":true,"family":"Keafer","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleindinst, Judith L.","contributorId":78251,"corporation":false,"usgs":true,"family":"Kleindinst","given":"Judith","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":494357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGillicuddy, Dennis J. Jr.","contributorId":13541,"corporation":false,"usgs":true,"family":"McGillicuddy","given":"Dennis","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":494354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Jennifer L. jlmartin@usgs.gov","contributorId":2658,"corporation":false,"usgs":true,"family":"Martin","given":"Jennifer","email":"jlmartin@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":494352,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Norton, Kerry","contributorId":22692,"corporation":false,"usgs":true,"family":"Norton","given":"Kerry","email":"","affiliations":[],"preferred":false,"id":494356,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pilskaln, Cynthia H.","contributorId":90818,"corporation":false,"usgs":true,"family":"Pilskaln","given":"Cynthia","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":494359,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smith, Juliette L.","contributorId":20258,"corporation":false,"usgs":true,"family":"Smith","given":"Juliette","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":494355,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494353,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Butman, Bradford 0000-0002-4174-2073 bbutman@usgs.gov","orcid":"https://orcid.org/0000-0002-4174-2073","contributorId":943,"corporation":false,"usgs":true,"family":"Butman","given":"Bradford","email":"bbutman@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":494351,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70104546,"text":"70104546 - 2014 - Controls of vegetation structure and net primary production in restored grasslands","interactions":[],"lastModifiedDate":"2014-07-28T08:42:18","indexId":"70104546","displayToPublicDate":"2014-06-04T13:31:00","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":"Controls of vegetation structure and net primary production in restored grasslands","docAbstract":"<p>1. Vegetation structure and net primary production (NPP) are fundamental properties of ecosystems. Understanding how restoration practices following disturbance interact with environmental factors to control these properties can provide insight on how ecosystems recover and guide management efforts.</p> \n<br/>\n<p>2. We assessed the relative contribution of environmental and restoration factors in controlling vegetation structure, above- and below-ground investment in production across a chronosequence of semiarid Conservation Reserve Program (CRP) fields recovering from dryland wheat cropping relative to undisturbed grassland. Importantly, we determined the role of plant diversity and how seeding either native or introduced perennial grasses influenced the recovery of vegetation properties.</p> \n<br/>\n<p>3. Plant basal cover increased with field age and was highest in CRP fields seeded with native perennial grasses. In contrast, fields seeded with introduced perennial grasses had tall-growing plants with relatively low basal cover. These vegetation structural characteristics interacted with precipitation, but not soil characteristics, to influence above-ground NPP (ANPP). Fields enrolled in the CRP program for >7 years supported twice as much ANPP as undisturbed shortgrass steppe in the first wet year of the study, but all CRP fields converged on a common low amount of ANPP in the following dry year and invested less than half as much as the shortgrass steppe in below-ground biomass.</p> \n<br/>\n<p>4. ANPP in CRP fields seeded with native perennial grasses for more than 7 years was positively related to species richness, whereas ANPP in CRP fields seeded with introduced perennial grasses were controlled more by dominant species.</p>\n<br/>\n<p>5. Synthesis and applications. Seeding with introduced, instead of native, perennial grasses had a strong direct influence on vegetation structure, including species richness, which indirectly affected NPP through time. However, the effects of restoring either native or introduced grasses on NPP were secondary to low water availability. Therefore, restoration strategies that maximize basal cover and below-ground biomass, which promote water acquisition, may lead to high resilience in semiarid and arid regions.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Blackwell Scientific Publications","publisherLocation":"Oxford","doi":"10.1111/1365-2664.12283","usgsCitation":"Munson, S.M., and Lauenroth, W.K., 2014, Controls of vegetation structure and net primary production in restored grasslands: Journal of Applied Ecology, v. 51, no. 4, p. 988-996, https://doi.org/10.1111/1365-2664.12283.","productDescription":"9 p.","startPage":"988","endPage":"996","numberOfPages":"9","ipdsId":"IP-054719","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":472951,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12283","text":"Publisher Index Page"},{"id":288082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287149,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2664.12283"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.058136,40.381075 ], [ -105.058136,40.922852 ], [ -104.515686,40.922852 ], [ -104.515686,40.381075 ], [ -105.058136,40.381075 ] ] ] } } ] }","volume":"51","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-06-03","publicationStatus":"PW","scienceBaseUri":"539031d4e4b04eea98bf84c1","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":493726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":493727,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048867,"text":"70048867 - 2014 - Aggression and coexistence in female caribou","interactions":[],"lastModifiedDate":"2014-06-04T12:52:44","indexId":"70048867","displayToPublicDate":"2014-06-04T13:11:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":894,"text":"Arctic","active":true,"publicationSubtype":{"id":10}},"title":"Aggression and coexistence in female caribou","docAbstract":"Female caribou (<i>Rangifer tarandus</i>) are highly gregarious, yet there has been little study of the behavioral mechanisms that foster coexistence. Quantifying patterns of aggression between male and female, particularly in the only cervid taxa where both sexes grow antlers, should provide insight into these mechanisms. We asked if patterns of aggression by male and female caribou followed the pattern typically noted in other polygynous cervids, in which males display higher frequencies and intensity of aggression. From June to August in 2011 and 2012, we measured the frequency and intensity of aggression across a range of group sizes through focal animal sampling of 170 caribou (64 males and 106 females) on Adak Island in the Aleutian Archipelago, Alaska. Males in same-sex and mixed-sex groups and females in mixed-sex groups had higher frequencies of aggression than females in same-sex groups. Group size did not influence frequency of aggression. Males displayed more intense aggression than females. Frequent aggression in mixed-sex groups probably reflects lower tolerance of males for animals in close proximity. Female caribou were less aggressive and more gregarious than males, as in other polygynous cervid species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Arctic","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Arctic Institute of North America","publisherLocation":"Calgary","doi":"10.14430/arctic4380","usgsCitation":"Weckerly, F.W., and Ricca, M., 2014, Aggression and coexistence in female caribou: Arctic, v. 67, no. 2, p. 189-195, https://doi.org/10.14430/arctic4380.","productDescription":"7 p.","startPage":"189","endPage":"195","numberOfPages":"7","ipdsId":"IP-052539","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472952,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14430/arctic4380","text":"Publisher Index Page"},{"id":288075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288073,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.14430/arctic4380"}],"country":"United States","state":"Alaska","otherGeospatial":"Adak Island;Aleutian Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -176.9927,51.5906 ], [ -176.9927,52.0019 ], [ -176.4196,52.0019 ], [ -176.4196,51.5906 ], [ -176.9927,51.5906 ] ] ] } } ] }","volume":"67","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-05-28","publicationStatus":"PW","scienceBaseUri":"539031d1e4b04eea98bf84b9","contributors":{"authors":[{"text":"Weckerly, Floyd W.","contributorId":10298,"corporation":false,"usgs":false,"family":"Weckerly","given":"Floyd","email":"","middleInitial":"W.","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":485775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ricca, Mark A.","contributorId":39736,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark A.","affiliations":[],"preferred":false,"id":485776,"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":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","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":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":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":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":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":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":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":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","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":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","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":70049024,"text":"ofr20131272 - 2014 - Compilation of gallium resource data for bauxite deposits","interactions":[],"lastModifiedDate":"2018-10-22T10:13:33","indexId":"ofr20131272","displayToPublicDate":"2014-06-03T15:29:00","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":"2013-1272","title":"Compilation of gallium resource data for bauxite deposits","docAbstract":"<p>Gallium (Ga) concentrations for bauxite deposits worldwide have been compiled from the literature to provide a basis for research regarding the occurrence and distribution of Ga worldwide, as well as between types of bauxite deposits. In addition, this report is an attempt to bring together reported Ga concentration data into one database to supplement ongoing U.S. Geological Survey studies of critical mineral resources.</p>\n<br>\n<p>The compilation of Ga data consists of location, deposit size, bauxite type and host rock, development status, major oxide data, trace element (Ga) data and analytical method(s) used to derive the data, and tonnage values for deposits within bauxite provinces and districts worldwide. The range in Ga concentrations for bauxite deposits worldwide is <10 to 812 parts per million (ppm), with an average of 57 ppm. Gallium concentrations in lateritic bauxites range from below detection (< 8 ppm) to 146 ppm; the average concentration is 57 ppm Ga. The average Ga concentration for karst bauxite deposits is 58 ppm with a range between <10 to 180 ppm Ga. As a result, there are no substantial differences in gallium concentrations between karst- and laterite-type bauxites. We calculate the range in geologically available Ga in bauxite deposits worldwide between 30 and 82,720 metric tons (t), with an average of 14,909 t.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131272","issn":"2331-1258","collaboration":"Mineral Resources Program","usgsCitation":"Schulte, R., and Foley, N.K., 2014, Compilation of gallium resource data for bauxite deposits: U.S. Geological Survey Open-File Report 2013-1272, Report: iv, 14 p.; Table: ZIP file, https://doi.org/10.3133/ofr20131272.","productDescription":"Report: iv, 14 p.; Table: ZIP file","numberOfPages":"21","onlineOnly":"Y","ipdsId":"IP-048881","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":288047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131272.jpg"},{"id":288044,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1272/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":288046,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1272/table/ofr2013-1272_tables.zip","linkFileType":{"id":6,"text":"zip"}},{"id":288045,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1272/pdf/ofr2013-1272.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"538ee050e4b0d497d49684bd","contributors":{"authors":[{"text":"Schulte, Ruth F.","contributorId":68604,"corporation":false,"usgs":true,"family":"Schulte","given":"Ruth F.","affiliations":[],"preferred":false,"id":486040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Nora K. 0000-0003-0124-3509 nfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-0124-3509","contributorId":4010,"corporation":false,"usgs":true,"family":"Foley","given":"Nora","email":"nfoley@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486039,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70104615,"text":"ofr20141088 - 2014 - Hurricane Sandy: observations and analysis of coastal change","interactions":[],"lastModifiedDate":"2014-06-03T14:23:10","indexId":"ofr20141088","displayToPublicDate":"2014-06-03T14:17:00","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":"2014-1088","title":"Hurricane Sandy: observations and analysis of coastal change","docAbstract":"Hurricane Sandy, the largest Atlantic hurricane on record, made landfall on October 29, 2012, and impacted a long swath of the U.S. Atlantic coastline. The barrier islands were breached in a number of places and beach and dune erosion occurred along most of the Mid-Atlantic coast. As a part of the National Assessment of Coastal Change Hazards project, the U.S. Geological Survey collected post-Hurricane Sandy oblique aerial photography and lidar topographic surveys to document the changes that occurred as a result of the storm. Comparisons of post-storm photographs to those collected prior to Sandy’s landfall were used to characterize the nature, magnitude, and spatial variability of hurricane-induced coastal changes. Analysis of pre- and post-storm lidar elevations was used to quantify magnitudes of change in shoreline position, dune elevation, and beach width. Erosion was observed along the coast from North Carolina to New York; however, as would be expected over such a large region, extensive spatial variability in storm response was observed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141088","issn":"2331-1258","usgsCitation":"Sopkin, K.L., Stockdon, H.F., Doran, K., Plant, N.G., Morgan, K., Guy, K.K., and Smith, K., 2014, Hurricane Sandy: observations and analysis of coastal change: U.S. Geological Survey Open-File Report 2014-1088, ix, 54 p., https://doi.org/10.3133/ofr20141088.","productDescription":"ix, 54 p.","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-045502","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141088.jpg"},{"id":288040,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1088/"},{"id":288041,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1088/pdf/ofr2014-1088.pdf"}],"datum":"World Geodetic System 1984","country":"Mexico;United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.0,20.0 ], [ -90.0,40.0 ], [ -60.0,40.0 ], [ -60.0,20.0 ], [ -90.0,20.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"538ee05ae4b0d497d49684cd","contributors":{"authors":[{"text":"Sopkin, Kristin L. ksopkin@usgs.gov","contributorId":4437,"corporation":false,"usgs":true,"family":"Sopkin","given":"Kristin","email":"ksopkin@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":493751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":493749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doran, Kara S. 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":33010,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","affiliations":[],"preferred":false,"id":493753,"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":493750,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morgan, Karen L.M. 0000-0002-2994-5572","orcid":"https://orcid.org/0000-0002-2994-5572","contributorId":95553,"corporation":false,"usgs":true,"family":"Morgan","given":"Karen L.M.","affiliations":[],"preferred":false,"id":493755,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":493754,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Kathryn E. L.","contributorId":20860,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn E. L.","affiliations":[],"preferred":false,"id":493752,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70068743,"text":"sir20135241 - 2014 - Spatial and stratigraphic distribution of water in oil shale of the Green River Formation using Fischer assay, Piceance Basin, northwestern Colorado","interactions":[],"lastModifiedDate":"2014-06-03T14:13:22","indexId":"sir20135241","displayToPublicDate":"2014-06-03T14:07:00","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":"2013-5241","title":"Spatial and stratigraphic distribution of water in oil shale of the Green River Formation using Fischer assay, Piceance Basin, northwestern Colorado","docAbstract":"<p>The spatial and stratigraphic distribution of water in oil shale of the Eocene Green River Formation in the Piceance Basin of northwestern Colorado was studied in detail using some 321,000 Fischer assay analyses in the U.S. Geological Survey oil-shale database. The oil-shale section was subdivided into 17 roughly time-stratigraphic intervals, and the distribution of water in each interval was assessed separately. This study was conducted in part to determine whether water produced during retorting of oil shale could provide a significant amount of the water needed for an oil-shale industry. Recent estimates of water requirements vary from 1 to 10 barrels of water per barrel of oil produced, depending on the type of retort process used. Sources of water in Green River oil shale include (1) free water within clay minerals; (2) water from the hydrated minerals nahcolite (NaHCO<sub>3</sub>), dawsonite (NaAl(OH)<sub>2</sub>CO<sub>3</sub>), and analcime (NaAlSi<sub>2</sub>O<sub>6</sub>.H<sub>2</sub>0); and (3) minor water produced from the breakdown of organic matter in oil shale during retorting. The amounts represented by each of these sources vary both stratigraphically and areally within the basin. Clay is the most important source of water in the lower part of the oil-shale interval and in many basin-margin areas. Nahcolite and dawsonite are the dominant sources of water in the oil-shale and saline-mineral depocenter, and analcime is important in the upper part of the formation. Organic matter does not appear to be a major source of water. The ratio of water to oil generated with retorting is significantly less than 1:1 for most areas of the basin and for most stratigraphic intervals; thus water within oil shale can provide only a fraction of the water needed for an oil-shale industry.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135241","issn":"2328-0328","usgsCitation":"Johnson, R.C., Mercier, T.J., and Brownfield, M.E., 2014, Spatial and stratigraphic distribution of water in oil shale of the Green River Formation using Fischer assay, Piceance Basin, northwestern Colorado: U.S. Geological Survey Scientific Investigations Report 2013-5241, Report: vii, 108 p.; 1 Plate: 104.88 x 84.72 inches, https://doi.org/10.3133/sir20135241.","productDescription":"Report: vii, 108 p.; 1 Plate: 104.88 x 84.72 inches","onlineOnly":"Y","ipdsId":"IP-024872","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":288039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135241.jpg"},{"id":288036,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5241/"},{"id":288037,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5241/pdf/sir2013-5241.pdf"},{"id":288038,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5241/download/plate1.pdf"}],"country":"United States","state":"Colorado","otherGeospatial":"Green River Formation;Piceance Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,38.0 ], [ -109.0,41.0 ], [ -106.0,41.0 ], [ -106.0,38.0 ], [ -109.0,38.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"538ee05ce4b0d497d49684d9","contributors":{"authors":[{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":488095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":488096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":488094,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"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":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":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}]}}
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