{"pageNumber":"850","pageRowStart":"21225","pageSize":"25","recordCount":184617,"records":[{"id":70197725,"text":"70197725 - 2018 - Sampling strategies to improve passive optical remote sensing of river bathymetry","interactions":[],"lastModifiedDate":"2018-06-19T11:36:18","indexId":"70197725","displayToPublicDate":"2018-06-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Sampling strategies to improve passive optical remote sensing of river bathymetry","docAbstract":"Passive optical remote sensing of river bathymetry involves establishing a relation between depth and reflectance that can be applied throughout an image to produce a depth map.  Building upon the Optimal Band Ratio Analysis (OBRA) framework, we introduce sampling strategies for constructing calibration data sets that lead to strong relationships between an image-derived quantity and depth across a range of depths.  Progressively excluding observations that exceed a series of cutoff depths from the calibration process improved the accuracy of depth estimates and allowed the maximum detectable depth ($d_{max}$) to be inferred directly from an image.  Depth retrieval in two distinct rivers also was enhanced by a stratified version of OBRA that partitions field measurements into a series of depth bins to avoid biases associated with under-representation of shallow areas in typical field data sets.  In the shallower, clearer of the two rivers, including the deepest field observations in the calibration data set did not compromise depth retrieval accuracy, suggesting that $d_{max}$ was not exceeded and the reach could be mapped without gaps.  Conversely, in the deeper and more turbid stream, progressive truncation of input depths yielded a plausible estimate of $d_{max}$ consistent with theoretical calculations based on field measurements of light attenuation by the water column.  This result implied that the entire channel, including pools, could not be mapped remotely.  However, truncation improved the accuracy of depth estimates in areas shallower than $d_{max}$, which comprise the majority of the channel and are of primary interest for many habitat-oriented applications.","language":"English","publisher":"MDPI","doi":"10.3390/rs10060935","usgsCitation":"Legleiter, C.J., Overstreet, B., and Kinzel, P.J., 2018, Sampling strategies to improve passive optical remote sensing of river bathymetry: Remote Sensing, v. 10, no. 6, e935; 24 p., https://doi.org/10.3390/rs10060935.","productDescription":"e935; 24 p.","ipdsId":"IP-092922","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":468649,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10060935","text":"Publisher Index Page"},{"id":437856,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7D50KX6","text":"USGS data release","linkHelpText":"Hyperspectral image data and field measurements used for bathymetric mapping of the Snake River in Grand Teton National Park, WY"},{"id":437855,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HT2N96","text":"USGS data release","linkHelpText":"Hyperspectral image data and field measurements used for bathymetric mapping of the Deschutes River near Bend, OR"},{"id":355153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5b46e559e4b060350a15d105","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":738300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Overstreet, Brandon 0000-0001-7845-6671 boverstreet@usgs.gov","orcid":"https://orcid.org/0000-0001-7845-6671","contributorId":169201,"corporation":false,"usgs":true,"family":"Overstreet","given":"Brandon","email":"boverstreet@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":738302,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70197625,"text":"sim3409 - 2018 - Bathymetric contour map, surface area and capacity table, and bathymetric difference map for Clearwater Lake near Piedmont, Missouri, 2017","interactions":[],"lastModifiedDate":"2018-09-25T08:04:18","indexId":"sim3409","displayToPublicDate":"2018-06-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3409","title":"Bathymetric contour map, surface area and capacity table, and bathymetric difference map for Clearwater Lake near Piedmont, Missouri, 2017","docAbstract":"Clearwater Lake, on the Black River near Piedmont in Reynolds County, Missouri, was constructed in 1948 and is operated by the U.S. Army Corps of Engineers for flood-risk reduction, recreation, and fish and wildlife habitat. The lake area is about 1,800 acres with about 34 miles of shoreline at the conservation pool elevation of 498 feet. Since the completion of the lake in 1948, sedimentation likely has caused the storage capacity of the lake to decrease gradually. The loss of storage capacity can decrease the effectiveness of the lake to mitigate flooding, and excessive sediment accumulation also can reduce aquatic habitat in some areas of the lake. Many lakes operated by the U.S. Army Corps of Engineers have periodic bathymetric and sediment surveys to monitor the status of the lake. The U.S. Geological Survey completed one such survey of Clearwater Lake in 2008 during a period of high lake level using bathymetric surveying equipment consisting of a multibeam echosounder, a singlebeam echosounder, 1/3 arc-second National Elevation Dataset data (used outside the multibeam echosounder survey extent), and the waterline derived from 2008 aerial light detection and ranging (lidar) data. In May 2017, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, surveyed the bathymetry of Clearwater Lake to prepare an updated bathymetric map and a surface area and capacity table. The 2008 survey was contrasted with the 2017 survey to document the changes in the bathymetric surface of the lake.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3409","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Richards, J.M., and Huizinga, R.J., 2018, Bathymetric contour map, surface area and capacity table, and bathymetric difference map for Clearwater Lake near Piedmont, Missouri, 2017: U.S. Geological Survey Scientific Investigations Map 3409, 1 sheet, https://doi.org/10.3133/sim3409.","productDescription":"Sheet: 36.0 x 36.0 inches; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095869","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":355036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3409/coverthb2.jpg"},{"id":355141,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3409/sim3409.pdf","text":"Map","size":"9.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3409"},{"id":355142,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DN44BJ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Bathymetric data for Clearwater Lake near Piedmont, Missouri, 2017"}],"country":"United States","state":"Missouri","city":"Piedmont","otherGeospatial":"Clearwater Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.9,\n              37.33\n            ],\n            [\n              -90.67,\n              37.33\n            ],\n            [\n              -90.67,\n              37.0833\n            ],\n            [\n              -90.9,\n              37.0833\n            ],\n            [\n              -90.9,\n              37.33\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto: dc_mo@usgs.gov\" data-mce-href=\"mailto: dc_mo@usgs.gov\">Director</a>, Central Midwest Water Science Center,&nbsp;<a href=\"https://mo.water.usgs.gov\" data-mce-href=\"https://mo.water.usgs.gov\">Missouri Office</a><br>U.S. Geological Survey<br>400 Independence Road <br>Rolla, MO 65401<br></p>","tableOfContents":"<ul><li>Introduction<br></li><li>Methods<br></li><li>Bathymetric Data Collection Quality Assurance<br></li><li>Bathymetric Surface and Contour Map Quality Assurance<br></li><li>Bathymetry, Capacity, and Bathymetric Change<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-06-19","noUsgsAuthors":false,"publicationDate":"2018-06-19","publicationStatus":"PW","scienceBaseUri":"5b46e559e4b060350a15d109","contributors":{"authors":[{"text":"Richards, Joseph M. 0000-0002-9822-2706 richards@usgs.gov","orcid":"https://orcid.org/0000-0002-9822-2706","contributorId":2370,"corporation":false,"usgs":true,"family":"Richards","given":"Joseph","email":"richards@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737970,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70197722,"text":"70197722 - 2018 - Evolution of the 2015 Cotopaxi eruption revealed by combined geochemical & seismic observations","interactions":[],"lastModifiedDate":"2018-08-31T10:55:21","indexId":"70197722","displayToPublicDate":"2018-06-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Evolution of the 2015 Cotopaxi eruption revealed by combined geochemical & seismic observations","docAbstract":"<p>Through integration of multiple data streams to monitor volcanic unrest scientists are able to make more robust eruption forecast and to obtain a more holistic interpretation of volcanic systems. We examined gas emission and gas geochemistry, seismic and petrologic data recorded during the 2015 unrest of Cotopaxi (Ecuador) in order to decipher the origin and temporal evolution of this eruption. Identification of families of similar seismic events and the use of seismic amplitude ratios reveals temporal changes in volcanic processes. SO2 (300 to 24000 t/d), BrO/SO2 (5-10 x10-5), SO2/HCl (5.8 ± 4.8 and 6.6 ± 3.0) and CO2/SO2 (0.6 to 2.1) measured throughout the eruption indicate a shallow magmatic source. Bulk ash and glass chemistry indicate a homogenous andesitic (SiO2 wt%=56.94 ± 0.25) magma having undergone extensive S-exsolution and degassing during ascent. These data lead us to interpret this eruption as a magma intrusion and ascend to shallow levels. The intrusion progressively interacted with the hydrothermal system, boiled off water, and produced hydromagmatic explosions. A small volume of this intrusion continued to fragment and produced episodic ash emissions until it was sufficiently degassed and rheologically stiff. Based on the 470 kt of measured SO2 we estimate that ~ 65.3 x106 m3 of magma were required to supply the emitted gases. This volume exceeds the volume of erupted juvenile material by a factor of 50. This result emphasizes the importance of careful monitoring of Cotopaxi to identify the intrusion of a new batch of magma, which could rejuvenate the non-erupted material.</p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GC007514","usgsCitation":"Hidalgo, S., Battaglia, J., Arellano, S., Sierra, D., Bernard, B., Parra, R., Kelly, P.J., Dinger, F., Barrington, C., and Samaniego, P., 2018, Evolution of the 2015 Cotopaxi eruption revealed by combined geochemical & seismic observations: Geochemistry, Geophysics, Geosystems, v. 19, no. 7, p. 2087-2108, https://doi.org/10.1029/2018GC007514.","productDescription":"22 p.","startPage":"2087","endPage":"2108","ipdsId":"IP-077610","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468647,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2018gc007514","text":"External Repository"},{"id":355148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-16","publicationStatus":"PW","scienceBaseUri":"5b46e559e4b060350a15d107","contributors":{"authors":[{"text":"Hidalgo, Silvana","contributorId":205717,"corporation":false,"usgs":false,"family":"Hidalgo","given":"Silvana","email":"","affiliations":[{"id":37151,"text":"Instituto Geofísico – Escuela Politécnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":738285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Battaglia, Jean","contributorId":205718,"corporation":false,"usgs":false,"family":"Battaglia","given":"Jean","email":"","affiliations":[{"id":37152,"text":"Laboratoire Magmas et Volcans, Université Blaise Pascal - CNRS - IRD, OPGC, Clermont Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":738286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arellano, Santiago","contributorId":205719,"corporation":false,"usgs":false,"family":"Arellano","given":"Santiago","affiliations":[{"id":37153,"text":"Department of Earth and Space Sciences – Chalmers University of Technology, Göteborg, Sweden","active":true,"usgs":false}],"preferred":false,"id":738287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sierra, Daniel","contributorId":205720,"corporation":false,"usgs":false,"family":"Sierra","given":"Daniel","email":"","affiliations":[{"id":37151,"text":"Instituto Geofísico – Escuela Politécnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":738288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernard, Benjamin","contributorId":178529,"corporation":false,"usgs":false,"family":"Bernard","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":738290,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parra, Rene","contributorId":205721,"corporation":false,"usgs":false,"family":"Parra","given":"Rene","email":"","affiliations":[{"id":37154,"text":"Instituto de Simulación Computacional, Colegio de Ciencias e Ingenierías - Universidad San Francisco de Quito, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":738289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":738284,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dinger, Florian","contributorId":205723,"corporation":false,"usgs":false,"family":"Dinger","given":"Florian","email":"","affiliations":[{"id":37156,"text":"Max-Planck Institut for Chemistry, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738292,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barrington, Charlotte","contributorId":205722,"corporation":false,"usgs":false,"family":"Barrington","given":"Charlotte","email":"","affiliations":[{"id":37155,"text":"Earth Observatory of Singapore, Nanyang Technological University, Singapore 639798","active":true,"usgs":false}],"preferred":false,"id":738291,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Samaniego, Pablo","contributorId":205724,"corporation":false,"usgs":false,"family":"Samaniego","given":"Pablo","email":"","affiliations":[{"id":37157,"text":"Université Clermont Auvergne, CNRS, IRD, OPGC, Laboratoire Magmas et Volcans, F-63000 Clermont-Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":738293,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70200630,"text":"70200630 - 2018 - A method to value nature-related webcam viewing: The value of virtual use with application to brown bear webcam viewing","interactions":[],"lastModifiedDate":"2018-10-26T09:47:55","indexId":"70200630","displayToPublicDate":"2018-06-18T12:37:08","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5771,"text":"Journal of Environmental Economics and Policy","active":true,"publicationSubtype":{"id":10}},"title":"A method to value nature-related webcam viewing: The value of virtual use with application to brown bear webcam viewing","docAbstract":"<p><span>There are an estimated 16,000 nature related remote web cameras that provide users around the world with an opportunity to view wildlife. Because there is no monetary price to view the webcams, we utilise variations in the viewers’ opportunity cost of time to estimate consumer surplus. We apply this model to a large sample (</span><i>n</i><span> = 2649) of the more than 10 million viewers of Alaska's Katmai National Park and Preserve brown bear webcams. The resulting consumer surplus is around \\$11 per hour of viewing. When applied to the 2.42 million viewer hours, this yields a benefit of \\$27 million annually. Since there are limits on the number of visitors as well as high costs of visiting this remote site, the aggregate webcam viewing value is more than twice the aggregate on-site viewing value. With minimal survey data required to apply this model, we believe it has broad applicability to other nature-related webcams around the world.</span></p>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/21606544.2018.1483842","usgsCitation":"Loomis, J.B., Richardson, L., Huber, C., Skibins, J., and Sharp, R., 2018, A method to value nature-related webcam viewing: The value of virtual use with application to brown bear webcam viewing: Journal of Environmental Economics and Policy, v. 7, no. 4, p. 452-462, https://doi.org/10.1080/21606544.2018.1483842.","productDescription":"11 p.","startPage":"452","endPage":"462","ipdsId":"IP-090967","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":358820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-18","publicationStatus":"PW","scienceBaseUri":"5c10a99ae4b034bf6a7e5359","contributors":{"authors":[{"text":"Loomis, John B.","contributorId":197268,"corporation":false,"usgs":false,"family":"Loomis","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":749758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, Leslie","contributorId":197525,"corporation":false,"usgs":false,"family":"Richardson","given":"Leslie","affiliations":[],"preferred":false,"id":749759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":749757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skibins, Jeffrey","contributorId":210077,"corporation":false,"usgs":false,"family":"Skibins","given":"Jeffrey","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":749760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sharp, Ryan","contributorId":168598,"corporation":false,"usgs":false,"family":"Sharp","given":"Ryan","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":749761,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70202676,"text":"70202676 - 2018 - Exposure to synthetic hydraulic fracturing waste influences the mucosal bacterial community structure of the brook trout (Salvelinus fontinalis) epidermis","interactions":[],"lastModifiedDate":"2019-03-18T10:10:27","indexId":"70202676","displayToPublicDate":"2018-06-18T09:59:01","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5818,"text":"AIMS Microbiology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Exposure to synthetic hydraulic fracturing waste influences the mucosal bacterial community structure of the brook trout (<i>Salvelinus fontinalis</i>)  epidermis","title":"Exposure to synthetic hydraulic fracturing waste influences the mucosal bacterial community structure of the brook trout (Salvelinus fontinalis) epidermis","docAbstract":"<p><span>Production of natural gas using unconventional technologies has risen as demand for alternative fuels has increased. Impacts on the environment from waste generated from these processes are largely unexplored. In particular, the outcomes of organismal exposure to hydraulic fracturing waste have not been rigorously evaluated. We evaluated the effects of exposure to surrogate hydraulic fracturing waste (HF waste) on mucosal bacterial community structure of the brook trout (</span><i>Salvelinus fontinalis</i><span>) epidermis. Brook trout are fish native to streams at risk to HF waste exposure. Here, fish were exposed to four treatments (control, 0.00%; low, 0.01%; medium, 0.10%; and high, 1.0% concentrations) of surrogate HF waste synthesized to mimic concentrations documented in the field. Epidermal mucus samples were collected and assessed 15 days post-exposure to determine if the associated bacterial community varied among treatments. We observed differences in epidermal mucosal bacterial community composition at multiple taxonomic scales among treatments. These community changes reflected compositional differences in taxa dominance and community similarity rather than losses or gains in taxonomic richness. The dominant bacterial genus that explained the greatest variation in community structure between exposed and unexposed fish was&nbsp;</span><i>Flavobacterium</i><span>. Two genera associated with salmonid diseases,&nbsp;</span><i>Flavobacterium</i><span>&nbsp;and&nbsp;</span><i>Pseudomonas</i><span>, were statistically more abundant in high treatments than controls. These results suggest that exposure to low levels of HF waste influences bacterial colonization and may lead to a disruption that favors bacterial populations associated with fish disease.</span></p>","language":"English","publisher":"AIMS Press","doi":"10.3934/microbiol.2018.3.413","usgsCitation":"Galbraith, H.S., Iwanowicz, D.D., Spooner, D.E., Iwanowicz, L.R., Keller, D., Zelanko, P.M., and Adams, C.R., 2018, Exposure to synthetic hydraulic fracturing waste influences the mucosal bacterial community structure of the brook trout (Salvelinus fontinalis) epidermis: AIMS Microbiology, v. 4, no. 3, p. 413-427, https://doi.org/10.3934/microbiol.2018.3.413.","productDescription":"15 p.","startPage":"413","endPage":"427","ipdsId":"IP-068278","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468650,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3934/microbiol.2018.3.413","text":"Publisher Index Page"},{"id":362130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","volume":"4","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Galbraith, Heather S. 0000-0003-3704-3517 hgalbraith@usgs.gov","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":4519,"corporation":false,"usgs":true,"family":"Galbraith","given":"Heather","email":"hgalbraith@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":759443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":759444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spooner, Daniel E. 0000-0002-5408-4364 dspooner@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-4364","contributorId":4603,"corporation":false,"usgs":true,"family":"Spooner","given":"Daniel","email":"dspooner@usgs.gov","middleInitial":"E.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":759445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":190787,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":759446,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keller, David","contributorId":214247,"corporation":false,"usgs":false,"family":"Keller","given":"David","affiliations":[],"preferred":false,"id":759447,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zelanko, Paula M.","contributorId":210768,"corporation":false,"usgs":false,"family":"Zelanko","given":"Paula","email":"","middleInitial":"M.","affiliations":[{"id":38143,"text":"The Academy of Natural Sciences of Drexel University","active":true,"usgs":false}],"preferred":false,"id":759448,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Adams, Cynthia R. 0000-0003-4383-530X cradams@usgs.gov","orcid":"https://orcid.org/0000-0003-4383-530X","contributorId":176965,"corporation":false,"usgs":true,"family":"Adams","given":"Cynthia","email":"cradams@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":759449,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70204848,"text":"70204848 - 2018 - A framework for identifying and characterising coral reef “oases” against a backdrop of degradation","interactions":[],"lastModifiedDate":"2020-09-01T14:08:16.952561","indexId":"70204848","displayToPublicDate":"2018-06-18T08:10:12","publicationYear":"2018","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":"A framework for identifying and characterising coral reef “oases” against a backdrop of degradation","docAbstract":"<ol class=\"\"><li>Human activities have led to widespread ecological decline; however, the severity of degradation is spatially heterogeneous due to some locations resisting, escaping, or rebounding from disturbances.</li><li>We developed a framework for identifying oases within coral reef regions using long‐term monitoring data. We calculated standardised estimates of coral cover (<i>z</i>‐scores) to distinguish sites that deviated positively from regional means. We also used the coefficient of variation (CV) of coral cover to quantify how oases varied temporally, and to distinguish among types of oases. We estimated “coral calcification capacity” (CCC), a measure of the coral community's ability to produce calcium carbonate structures and tested for an association between this metric and<span>&nbsp;</span><i>z</i>‐scores of coral cover.</li><li>We illustrated our<span>&nbsp;</span><i>z</i>‐score approach within a modelling framework by extracting<span>&nbsp;</span><i>z</i>‐scores and CVs from simulated data based on four generalized trajectories of coral cover. We then applied the approach to time‐series data from long‐term reef monitoring programmes in four focal regions in the Pacific (the main Hawaiian Islands and Mo'orea, French Polynesia) and western Atlantic (the Florida Keys and St. John, US Virgin Islands). Among the 123 sites analysed, 38 had positive<span>&nbsp;</span><i>z</i>‐scores for median coral cover and were categorised as oases.</li><li><i>Synthesis and applications</i>. Our framework provides ecosystem managers with a valuable tool for conservation by identifying “oases” within degraded areas. By evaluating trajectories of change in state (e.g., coral cover) among oases, our approach may help in identifying the mechanisms responsible for spatial variability in ecosystem condition. Increased mechanistic understanding can guide whether management of a particular location should emphasise protection, mitigation or restoration. Analysis of the empirical data suggest that the majority of our coral reef oases originated by either escaping or resisting disturbances, although some sites showed a high capacity for recovery, while others were candidates for restoration. Finally, our measure of reef condition (i.e., median<span>&nbsp;</span><i>z</i>‐scores of coral cover) correlated positively with coral calcification capacity suggesting that our approach identified oases that are also exceptional for one critical component of ecological function.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13179","usgsCitation":"Guest, J.R., Edmunds, P.J., Gates, R.D., Kuffner, I.B., Andersson, A.J., Barnes, B.B., Chollett, I., Courtney, T.A., Elahi, R., Gross, K., Lenz, E.A., Mitarai, S., Mumby, P.J., Nelson, H.R., Parker, B.A., Putnam, H.M., Rogers, C.S., and Toth, L., 2018, A framework for identifying and characterising coral reef “oases” against a backdrop of degradation: Journal of Applied Ecology, v. 55, no. 6, p. 2865-2875, https://doi.org/10.1111/1365-2664.13179.","productDescription":"11 p.","startPage":"2865","endPage":"2875","ipdsId":"IP-088135","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13179","text":"Publisher Index Page"},{"id":366671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"French Polynesia, United States, US Virgin Islands","state":"Florida, Hawaii","otherGeospatial":"Florida Keys","volume":"55","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Guest, James R.","contributorId":204566,"corporation":false,"usgs":false,"family":"Guest","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":768732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edmunds, Peter J.","contributorId":204567,"corporation":false,"usgs":false,"family":"Edmunds","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":36956,"text":"California State University","active":true,"usgs":false}],"preferred":false,"id":768733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gates, Ruth D.","contributorId":167853,"corporation":false,"usgs":false,"family":"Gates","given":"Ruth","email":"","middleInitial":"D.","affiliations":[{"id":24839,"text":"Hawai'i Institute of Marine Biology, Hawaii","active":true,"usgs":false}],"preferred":false,"id":768734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 ikuffner@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7847","contributorId":3105,"corporation":false,"usgs":true,"family":"Kuffner","given":"Ilsa","email":"ikuffner@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andersson, Andreas J","contributorId":141142,"corporation":false,"usgs":false,"family":"Andersson","given":"Andreas","email":"","middleInitial":"J","affiliations":[{"id":12888,"text":"Scripps Institution of Oceanography, Univ of California","active":true,"usgs":false}],"preferred":false,"id":768736,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnes, Brian B.","contributorId":218223,"corporation":false,"usgs":false,"family":"Barnes","given":"Brian","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":768737,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chollett, Iliana","contributorId":218224,"corporation":false,"usgs":false,"family":"Chollett","given":"Iliana","email":"","affiliations":[],"preferred":false,"id":768738,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Courtney, Travis A.","contributorId":218225,"corporation":false,"usgs":false,"family":"Courtney","given":"Travis","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":768739,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Elahi, Robin","contributorId":218226,"corporation":false,"usgs":false,"family":"Elahi","given":"Robin","email":"","affiliations":[],"preferred":false,"id":768740,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gross, Kevin","contributorId":71483,"corporation":false,"usgs":true,"family":"Gross","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":768741,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lenz, Elizabeth A.","contributorId":218227,"corporation":false,"usgs":false,"family":"Lenz","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":768742,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mitarai, Satoshi","contributorId":218228,"corporation":false,"usgs":false,"family":"Mitarai","given":"Satoshi","email":"","affiliations":[],"preferred":false,"id":768743,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mumby, Peter J.","contributorId":175366,"corporation":false,"usgs":false,"family":"Mumby","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":768744,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Nelson, Hannah R.","contributorId":218229,"corporation":false,"usgs":false,"family":"Nelson","given":"Hannah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":768745,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Parker, Britt A.","contributorId":218230,"corporation":false,"usgs":false,"family":"Parker","given":"Britt","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":768746,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Putnam, Hollie M.","contributorId":218231,"corporation":false,"usgs":false,"family":"Putnam","given":"Hollie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":768747,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rogers, Caroline S. 0000-0001-9056-6961 caroline_rogers@usgs.gov","orcid":"https://orcid.org/0000-0001-9056-6961","contributorId":3126,"corporation":false,"usgs":true,"family":"Rogers","given":"Caroline","email":"caroline_rogers@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":768748,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768749,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70197677,"text":"70197677 - 2018 - Characterizing the sponge grounds of Grays Canyon, Washington, USA","interactions":[],"lastModifiedDate":"2018-06-18T11:02:29","indexId":"70197677","displayToPublicDate":"2018-06-18T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5536,"text":"Deep Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing the sponge grounds of Grays Canyon, Washington, USA","docAbstract":"Deep-sea sponge grounds are relatively understudied ecosystems that may provide key habitats for a large number of fish and invertebrates including commercial species. Glass sponge grounds have been discovered from the tropics to polar regions but there are only a few places with high densities of dictyonine sponges. Dictyonine glass sponges have a fused skeleton, which stays intact when they die and in some areas the accumulation of successive generations of sponges leads to the formation of reefs. In 2010 and 2016, we surveyed an area near Grays Canyon in Washington, USA, where dense aggregations of glass sponges and potential sponge reefs were discovered in 2007. Our primary aims were to make a preliminary assessment of whether the glass sponges form reefs at this location, characterize the sponge assemblage present at this site and examine associations between the sponges and commercially important species. Multibeam mapping and sub-bottom profiling indicate that the glass sponges at this site do not form reefs and are mostly attached to hard substrates. Analysis of photographs collected by an autonomous underwater vehicle and samples collected by a remotely operated vehicle guided by telepresence revealed the presence of two abundant dictyonine sponge species at this site, Heterochone calyx and Aphrocallistes vastus (mean densities = 1.43 ± 0.057 per 10 m2, max = 24 per 10 m2). We also observed a large number of non-reef-building glass sponges and various demosponges including a potentially new species in the genus Acarnus. A diverse fish assemblage was recorded at this site including eight species of rockfish. Rockfish abundance was positively related to sponge abundance. Spot prawns (Pandalus platyceros) were also abundant and were strongly associated with sponges. Despite not finding sponge reefs, this is an ecologically significant area. Further research is necessary to determine the environmental factors that give rise to the abundance of large dictyonine sponges at this location and also to determine if other similar sponge grounds exist along the west coast of the United States.","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2018.01.004","usgsCitation":"Powell, A., Clarke, M., Fruh, E., Chaytor, J., Reiswig, H.M., and Whitmire, C.E., 2018, Characterizing the sponge grounds of Grays Canyon, Washington, USA: Deep Sea Research Part II: Topical Studies in Oceanography, v. 150, p. 146-155, https://doi.org/10.1016/j.dsr2.2018.01.004.","productDescription":"10 p.","startPage":"146","endPage":"155","ipdsId":"IP-086610","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468653,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr2.2018.01.004","text":"Publisher Index Page"},{"id":355102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Grays Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -126,\n              46\n            ],\n            [\n              -124,\n              46\n            ],\n            [\n              -124,\n              48\n            ],\n            [\n              -126,\n              48\n            ],\n            [\n              -126,\n              46\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"150","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e55ae4b060350a15d10d","contributors":{"authors":[{"text":"Powell, Abby N. abby_powell@usgs.gov","contributorId":2534,"corporation":false,"usgs":false,"family":"Powell","given":"Abby N.","email":"abby_powell@usgs.gov","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":738158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clarke, M. Elizabeth","contributorId":205699,"corporation":false,"usgs":false,"family":"Clarke","given":"M. Elizabeth","affiliations":[{"id":37147,"text":"Office of the Science Director, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration. Montlake Blvd E., Seattle, WA 98112, USA.","active":true,"usgs":false}],"preferred":false,"id":738159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fruh, Erica","contributorId":205700,"corporation":false,"usgs":false,"family":"Fruh","given":"Erica","email":"","affiliations":[{"id":37147,"text":"Office of the Science Director, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration. Montlake Blvd E., Seattle, WA 98112, USA.","active":true,"usgs":false}],"preferred":false,"id":738160,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":738157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reiswig, Henry M.","contributorId":205701,"corporation":false,"usgs":false,"family":"Reiswig","given":"Henry","email":"","middleInitial":"M.","affiliations":[{"id":37148,"text":"University of Victoria and Royal British Columbia Museum, Victoria, Canada.","active":true,"usgs":false}],"preferred":false,"id":738161,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitmire, Curt E.","contributorId":205702,"corporation":false,"usgs":false,"family":"Whitmire","given":"Curt","email":"","middleInitial":"E.","affiliations":[{"id":37149,"text":"Fishery Resource Analysis and Monitoring Division, Northwest Fisheries Science Center, National Oceanic and Atmospheric Administration, 99 Pacific Street, Bldg. 255-A, Monterey, California, 97365,","active":true,"usgs":false}],"preferred":false,"id":738162,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197675,"text":"70197675 - 2018 - Book review: A new view on the species abundance distribution Stochastic communities: A mathematical theory of biodiversity","interactions":[],"lastModifiedDate":"2018-08-10T13:37:07","indexId":"70197675","displayToPublicDate":"2018-06-18T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Book review: A new view on the species abundance distribution Stochastic communities: A mathematical theory of biodiversity","docAbstract":"The sampled relative abundances of species of a taxonomic group, whether birds, trees, or moths, in a natural community at a particular place vary in a way that suggests a consistent underlying pattern, referred to as the species abundance distribution (SAD). Preston [1] conjectured that the numbers of species, plotted as a histogram of logarithmic abundance classes called octaves, seemed to fit a lognormal distribution; that is, the histograms look like normal distributions, although truncated on the left-hand, or low-species-abundance, end. Although other specific curves for the SAD have been proposed in the literature, Preston’s lognormal distribution is widely cited in textbooks and has stimulated attempts at explanation. An important aspect of Preston’s lognormal distribution is the ‘veil line’, a vertical line drawn exactly at the point of the left-hand truncation in the distribution, to the left of which would be species missing from the sample.\n\nDewdney rejects the lognormal conjecture. Instead, starting with the long-recognized fact that the number of species sampled from a community, when plotted as histograms against population abundance, resembles an inverted J, he presents a mathematical description of an alternative that he calls the ‘J distribution’, a hyperbolic density function truncated at both ends. When multiplied by species richness, R, it becomes the SAD of the sample.","language":"English","publisher":"Elsevier","doi":"10.1016/j.tree.2018.05.002","usgsCitation":"DeAngelis, D.L., 2018, Book review: A new view on the species abundance distribution Stochastic communities: A mathematical theory of biodiversity: Trends in Ecology and Evolution, v. 33, no. 8, p. 572-574, https://doi.org/10.1016/j.tree.2018.05.002.","productDescription":"3 p.","startPage":"572","endPage":"574","ipdsId":"IP-096315","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":355103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e55ae4b060350a15d10f","contributors":{"authors":[{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":738152,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70197705,"text":"70197705 - 2018 - Adaptation with climate uncertainty: An examination of agricultural land use in the United States","interactions":[],"lastModifiedDate":"2018-06-19T11:41:57","indexId":"70197705","displayToPublicDate":"2018-06-18T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2599,"text":"Land Use Policy","active":true,"publicationSubtype":{"id":10}},"title":"Adaptation with climate uncertainty: An examination of agricultural land use in the United States","docAbstract":"<p><span>This paper examines adaptation responses to climate change through adjustment of agricultural land use. The climate drivers we examine are changes in long-term climate normals (e.g., 10-year moving averages) and changes in inter-annual climate variability. Using US county level data over 1982 to 2012 from Census of Agriculture, we find that impacts of long-term climate normals are as important as that of inter-annual climate variability. Projecting into the future, we find projected climate change will lead to an expansion in crop land share across the northern and interior western United States with decreases in the south. We also find that grazing land share increases in southern regions and Inland Pacific Northwest and declines in the northern areas. However, the extent to which the adaptation potential would be is dependent on the climate model, emission scenario and time horizon under consideration.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.landusepol.2018.05.057","usgsCitation":"Mu, J.E., McCarl, B.A., Sleeter, B.M., Abatzoglou, J.T., and Zhang, H., 2018, Adaptation with climate uncertainty: An examination of agricultural land use in the United States: Land Use Policy, v. 77, p. 392-401, https://doi.org/10.1016/j.landusepol.2018.05.057.","productDescription":"10 p.","startPage":"392","endPage":"401","ipdsId":"IP-076144","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468652,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.landusepol.2018.05.057","text":"Publisher Index Page"},{"id":355131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e559e4b060350a15d10b","contributors":{"authors":[{"text":"Mu, Jianhong E.","contributorId":75840,"corporation":false,"usgs":true,"family":"Mu","given":"Jianhong","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":738230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarl, Bruce A.","contributorId":58173,"corporation":false,"usgs":true,"family":"McCarl","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":738228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":738226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abatzoglou, John T.","contributorId":191729,"corporation":false,"usgs":false,"family":"Abatzoglou","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":33345,"text":" University of Idaho","active":true,"usgs":false}],"preferred":false,"id":738227,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Hongliang","contributorId":205709,"corporation":false,"usgs":false,"family":"Zhang","given":"Hongliang","email":"","affiliations":[{"id":37150,"text":"University of Neuchâtel","active":true,"usgs":false}],"preferred":false,"id":738229,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70221454,"text":"70221454 - 2018 - Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model","interactions":[],"lastModifiedDate":"2021-06-16T14:14:34.261411","indexId":"70221454","displayToPublicDate":"2018-06-16T08:52:24","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7168,"text":"Journal of the American Water Resources Association (JAWRA)","active":true,"publicationSubtype":{"id":10}},"title":"Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model","docAbstract":"We test the use of a mixed-effects model for estimating lag to peak for small basins in Maine (drainage areas from 0.8 to 78 km2). Lag to peak is defined as the time between the center of volume of the excess rainfall during a storm event and the resulting peak streamflow. A mixed-effects model allows for multiple observations at sites without violating model assumptions inherent in traditional ordinary least squares models, which assume each observation is independent. The mixed model includes basin drainage area and maximum 15-min rainfall depth for individual storms as explanatory features. Based on a remove-one-site cross-validation analysis, the prediction errors of this model ranged from 42% to +73%. The mixed model substantially outperformed three published models for lag to peak and one published model for centroid lag for estimating lag to peak for small basins in Maine. Lag to peak estimates are a key input to rainfallrunoff models used to design hydraulic infrastructure. The improved accuracy and consistency with model assumptions indicates that mixed models may provide increased data utilization that could enhance models and estimates of lag to peak in other regions.","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12653","usgsCitation":"Lombard, P.J., and Holtschlag, D., 2018, Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model: Journal of the American Water Resources Association (JAWRA), v. 54, no. 4, p. 949-961, https://doi.org/10.1111/1752-1688.12653.","productDescription":"13 p.","startPage":"949","endPage":"961","ipdsId":"IP-089128","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":437859,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PK0F3D","text":"USGS data release","linkHelpText":"Precipitation and streamflow data for computing lag to peak at selected stations in Maine"},{"id":386535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Maine","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -69.08203125,\n              47.517200697839414\n            ],\n            [\n              -70.0048828125,\n              46.558860303117164\n            ],\n            [\n              -70.9716796875,\n              45.27488643704891\n            ],\n            [\n              -70.751953125,\n              43.100982876188546\n            ],\n            [\n              -66.8408203125,\n              44.84029065139799\n            ],\n            [\n              -67.3681640625,\n              45.82879925192134\n            ],\n            [\n              -67.9833984375,\n              47.368594345213374\n            ],\n            [\n              -69.08203125,\n              47.517200697839414\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"54","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":205225,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holtschlag, David 0000-0001-5185-4928","orcid":"https://orcid.org/0000-0001-5185-4928","contributorId":215360,"corporation":false,"usgs":true,"family":"Holtschlag","given":"David","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817755,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70221449,"text":"70221449 - 2018 - Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015","interactions":[],"lastModifiedDate":"2021-06-17T10:29:24.325243","indexId":"70221449","displayToPublicDate":"2018-06-16T07:48:30","publicationYear":"2018","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":"Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">The Weighted Regressions on Time, Discharge, and Season (WRTDS) model was used to derive estimates of suspended-sediment concentration (SSC) and suspended-sediment load (SSL), their dependence on discharge, and their trends with confidence intervals, for one site each on the lowermost Mississippi and Atchafalaya Rivers. The WRTDS model reduces uncertainty in SSCs related to variable streamflow conditions. Flow-normalized SSCs in each river were similar, and decreased from about 260 mg/L to 130 mg/L from 1980 through 2015; combined annual SSL in the two rivers decreased from about 200 Megatons per year (MT/y) to about 100 MT/y. Declines in SSC and SSL were more gradual from 2005 through 2015 and show signs of stabilizing. Our estimates of SSL in 2015 differ markedly from several recently published estimates of current and projected future Mississippi River SSLs, which were generally around 200 MT/y. However, these values came mostly from a different site upstream on the Mississippi River. The relationship between SSC and streamflow differed in an important way between the two rivers. SSC increased as streamflow increased for the entire range of observed streamflow in the Atchafalaya River. In the Mississippi River, SSC followed the same pattern during low and moderate streamflow but decreased at the highest streamflow that tended to occur between January and July. Since much of the water flowing in the Atchafalaya originates from the Mississippi River, the difference suggests a within-basin source of suspended sediment for the Atchafalaya River that is absent in the lower Mississippi River. These findings have important implications for the restoration of deltaic wetlands in coastal Louisiana. Accurate estimates of the SSL available in each river are crucial for understanding how effective diversions of river water into adjacent estuaries will be in sustaining these wetlands. Our study demonstrates that there might be far less sediment available than previously reported. Further, the difference in the relationship between SSC and streamflow in the two rivers is highly relevant to the ongoing discussion of coastal restoration strategies because the delta building that is occurring at the mouth of the Atchafalaya River is frequently used as a model of what could be expected with controlled diversions in the lower Mississippi River delta. The differences in the SSC behavior with changes in streamflow between the two rivers needs to be considered when results from the Atchafalaya River system are projected to those of the Mississippi River.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2018.05.068","usgsCitation":"Mize, S., Murphy, J.C., Diehl, T.H., and Demcheck, D.K., 2018, Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015: Journal of Hydrology, v. 564, p. 1-11, https://doi.org/10.1016/j.jhydrol.2018.05.068.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-079997","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":386526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Mississippi River, Lower Atchafalaya River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.60400390625,\n              30.996445897426373\n            ],\n            [\n              -91.5106201171875,\n              31.043521630684204\n            ],\n            [\n              -91.527099609375,\n              31.194007509998823\n            ],\n            [\n              -91.746826171875,\n              31.17050982470345\n            ],\n            [\n              -91.82922363281249,\n              31.123496964067325\n            ],\n            [\n              -91.86767578124999,\n              30.97289931126414\n            ],\n            [\n              -91.8511962890625,\n              30.543338954230222\n            ],\n            [\n              -91.71936035156249,\n              30.140376821599734\n            ],\n            [\n              -91.6094970703125,\n              29.702368038541767\n            ],\n            [\n              -91.4996337890625,\n              29.44916482692468\n            ],\n            [\n              -91.131591796875,\n              29.35345166863502\n            ],\n            [\n              -91.03271484375,\n              29.578234494739206\n            ],\n            [\n              -91.021728515625,\n              29.954934549656144\n            ],\n            [\n              -90.6976318359375,\n              29.835878945929952\n            ],\n            [\n              -90.054931640625,\n              29.702368038541767\n            ],\n            [\n              -89.7967529296875,\n              29.67850809103362\n            ],\n            [\n              -89.84619140625,\n              29.950175057288813\n            ],\n            [\n              -90.3350830078125,\n              30.059585699708215\n            ],\n            [\n              -90.8734130859375,\n              30.183121842195515\n            ],\n            [\n              -91.23596191406249,\n              30.694611546632277\n            ],\n            [\n              -91.60400390625,\n              30.996445897426373\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"564","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mize, Scott 0000-0001-6751-5568","orcid":"https://orcid.org/0000-0001-6751-5568","contributorId":218508,"corporation":false,"usgs":true,"family":"Mize","given":"Scott","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":167405,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":817746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Demcheck, Dennis K. 0000-0003-2981-078X","orcid":"https://orcid.org/0000-0003-2981-078X","contributorId":210305,"corporation":false,"usgs":true,"family":"Demcheck","given":"Dennis","email":"","middleInitial":"K.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817748,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227826,"text":"70227826 - 2018 - Combined effects of temperature and salinity on the physiology of two geographically-distant eastern oyster populations","interactions":[],"lastModifiedDate":"2022-02-01T19:59:06.916219","indexId":"70227826","displayToPublicDate":"2018-06-15T14:58:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2277,"text":"Journal of Experimental Marine Biology and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Combined effects of temperature and salinity on the physiology of two geographically-distant eastern oyster populations","docAbstract":"<p>Understanding why a species occupies a certain geographic range and predicting how they will be affected by climate change require characterizing physiological traits in geographically-distant populations. The objective of this study was to perform a direct comparison of two eastern oyster (<i>Crassostrea virginica</i>) populations that occupy contrasting temperature and salinity habitats, New Brunswick, Canada (47°N – Gulf of St. Lawrence) and Louisiana, USA (29°N – Gulf of Mexico). Specifically, clearance rate, valve opening, and oxygen consumption rate were measured in oysters of both populations following a full factorial design with three temperatures (10, 20, 30 °C) and two salinities (15, 25). New Brunswick oysters had a greater gill area, shell gape angle, and oxygen consumption rate. Temperature was the main driver of clearance rate, valve opening duration and oxygen consumption rate. Clearance rate at 20 °C and 30 °C was significantly higher than at 10 °C, and oysters at 20 °C had their valves opened for a greater percentage of time compared to oysters at 10 °C and 30 °C. Oxygen consumption rate increased gradually from 10 °C to 30 °C and similarly for both populations, with no indications of a thermal breakpoint at 30 °C. Temperature coefficients for the oxygen consumption rate (Q<sub>10</sub>) were within the normal ecological range for both populations. No physiological differences were observed between salinity treatments in both populations. No latitudinal compensation in the physiological rates was found. Overall, results showed that <i>C. virginica</i> is tolerant to a broad range of temperatures and salinities. Such physiological plasticity is consistent with the species' extended geographical range.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jembe.2018.06.001","usgsCitation":"Casas, S.M., Filgueira, R., Lavaud, R., Comeau, L.A., La Peyre, M., and La Peyre, J.F., 2018, Combined effects of temperature and salinity on the physiology of two geographically-distant eastern oyster populations: Journal of Experimental Marine Biology and Ecology, v. 506, p. 82-90, https://doi.org/10.1016/j.jembe.2018.06.001.","productDescription":"9 p.","startPage":"82","endPage":"90","ipdsId":"IP-092992","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"506","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Casas, S. M.","contributorId":272906,"corporation":false,"usgs":false,"family":"Casas","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":832379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Filgueira, R.","contributorId":204578,"corporation":false,"usgs":false,"family":"Filgueira","given":"R.","email":"","affiliations":[],"preferred":false,"id":832380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lavaud, R.","contributorId":273051,"corporation":false,"usgs":false,"family":"Lavaud","given":"R.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":832534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Comeau, L. A.","contributorId":272908,"corporation":false,"usgs":false,"family":"Comeau","given":"L.","email":"","middleInitial":"A.","affiliations":[{"id":56406,"text":"Fisheries  and  Oceans  Canada","active":true,"usgs":false}],"preferred":false,"id":832381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Megan 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":79375,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan","email":"mlapeyre@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832382,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"La Peyre, J. F.","contributorId":273052,"corporation":false,"usgs":false,"family":"La Peyre","given":"J.","email":"","middleInitial":"F.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":832383,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70198775,"text":"70198775 - 2018 - Variation in home range size and patterns in adult female American crocodiles Crocodylus acutus","interactions":[],"lastModifiedDate":"2021-04-06T15:19:07.060998","indexId":"70198775","displayToPublicDate":"2018-06-15T09:32:44","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Variation in home range size and patterns in adult female American crocodiles <i>Crocodylus acutus</i>","title":"Variation in home range size and patterns in adult female American crocodiles Crocodylus acutus","docAbstract":"<p><span>The American crocodile&nbsp;</span><i>Crocodylus acutus</i><span>&nbsp;is a threatened species that uses relatively deep, open-water habitats with low salinity. Adult female American crocodiles nest on sandy coastal beaches, islands or human-made berms, assist in the hatching process, and can travel long distances to nesting habitat. We satellite-tracked 15 adult female American crocodiles in 2 hydrologically distinct areas in Everglades National Park, Florida, USA, to quantify the home range sizes, test for intraspecific differences in home range and core area size and structure, and identify important crocodile high-use areas. Overall home ranges (95% kernel density estimate; KDE) for adult female crocodiles in South Florida ranged from 30.0 to 141.9 km</span><sup>2</sup><span>&nbsp;(mean ± SD, 84.4 ± 32.3 km</span><sup>2</sup><span>), and core areas (50% KDE) ranged from 4.7 to 27.4 km</span><sup>2</sup><span>(17.8 ± 7.3 km</span><sup>2</sup><span>). We identified patterns in home range and core area overlap, seasonally shifting patterns in core area use, and the Fox Lake complex as an important crocodile high-use area. As the population of American crocodiles continues to grow and expand into new areas, it is important for conservation managers to understand individual crocodile habitat-use patterns and spatial resource requirements.</span></p>","language":"English","publisher":"Inter-research","doi":"10.3354/esr00900","usgsCitation":"Hart, K.M., Beauchamp, J.S., Cherkiss, M.S., and Mazzotti, F., 2018, Variation in home range size and patterns in adult female American crocodiles Crocodylus acutus: Endangered Species Research, v. 36, p. 161-171, https://doi.org/10.3354/esr00900.","productDescription":"11 p.","startPage":"161","endPage":"171","ipdsId":"IP-093882     ","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468654,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00900","text":"Publisher Index Page"},{"id":356576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.83990478515625,\n              25.122905883812052\n            ],\n            [\n              -80.2606201171875,\n              25.122905883812052\n            ],\n            [\n              -80.2606201171875,\n              26.33280692289788\n            ],\n            [\n              -81.83990478515625,\n              26.33280692289788\n            ],\n            [\n              -81.83990478515625,\n              25.122905883812052\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2afe4b0702d0e842fb1","contributors":{"authors":[{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":742931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, Jeffrey S.","contributorId":138880,"corporation":false,"usgs":false,"family":"Beauchamp","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[{"id":12559,"text":"University of Florida, FLEC","active":true,"usgs":false}],"preferred":false,"id":742932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cherkiss, Michael S. 0000-0002-7802-6791 mcherkiss@usgs.gov","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":4571,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","email":"mcherkiss@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":742933,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazzotti, Frank","contributorId":138878,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":742934,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70197650,"text":"70197650 - 2018 - Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity","interactions":[],"lastModifiedDate":"2021-08-11T18:52:48.609974","indexId":"70197650","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Context</h3><p>High-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species’ potential to link patches or populations are of importance.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Objectives</h3><p>We introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories’ plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species’ range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Simulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corroborating previous findings for this species.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>We show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting migratory connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0637-9","usgsCitation":"van Toor, M.L., Kranstauber, B., Newman, S.H., Prosser, D.J., Takekawa, J., Technitis, G., Weibel, R., Wikelski, M., and Safi, K., 2018, Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity: Landscape Ecology, v. 33, no. 6, p. 879-893, https://doi.org/10.1007/s10980-018-0637-9.","productDescription":"15 p.","startPage":"879","endPage":"893","ipdsId":"IP-084732","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468656,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-018-0637-9","text":"Publisher Index Page"},{"id":355084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-26","publicationStatus":"PW","scienceBaseUri":"5b46e566e4b060350a15d117","contributors":{"authors":[{"text":"van Toor, Marielle L.","contributorId":205670,"corporation":false,"usgs":false,"family":"van Toor","given":"Marielle","email":"","middleInitial":"L.","affiliations":[{"id":37137,"text":"Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":738069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kranstauber, Bart","contributorId":205671,"corporation":false,"usgs":false,"family":"Kranstauber","given":"Bart","email":"","affiliations":[{"id":37138,"text":"Department of Evolutionary Biology and Environmental Studies, University of Zurich","active":true,"usgs":false}],"preferred":false,"id":738070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Newman, Scott H.","contributorId":199129,"corporation":false,"usgs":false,"family":"Newman","given":"Scott","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":738071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Takekawa, John Y. 0000-0003-0217-5907","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":203805,"corporation":false,"usgs":false,"family":"Takekawa","given":"John Y.","affiliations":[{"id":36724,"text":"Audubon California, Richardson Bay Audubon Center and Sanctuary, Tiburon, CA","active":true,"usgs":false}],"preferred":false,"id":738072,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Technitis, Georgios","contributorId":205672,"corporation":false,"usgs":false,"family":"Technitis","given":"Georgios","email":"","affiliations":[{"id":37139,"text":"Department of Geography, University of Zurich","active":true,"usgs":false}],"preferred":false,"id":738073,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weibel, Robert","contributorId":205673,"corporation":false,"usgs":false,"family":"Weibel","given":"Robert","email":"","affiliations":[{"id":37139,"text":"Department of Geography, University of Zurich","active":true,"usgs":false}],"preferred":false,"id":738074,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wikelski, Martin","contributorId":205674,"corporation":false,"usgs":false,"family":"Wikelski","given":"Martin","email":"","affiliations":[{"id":37137,"text":"Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":738075,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Safi, Kamran","contributorId":205675,"corporation":false,"usgs":false,"family":"Safi","given":"Kamran","email":"","affiliations":[{"id":37137,"text":"Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":738076,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70198068,"text":"70198068 - 2018 - Reductive dechlorination rates of 4,4′-DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene) in sediments of the Palos Verdes Shelf, CA","interactions":[],"lastModifiedDate":"2018-07-13T12:35:26","indexId":"70198068","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2662,"text":"Marine Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Reductive dechlorination rates of 4,4′-DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene) in sediments of the Palos Verdes Shelf, CA","docAbstract":"<p>Wastes from the world's largest manufacturer of DDT (1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene) were released into the Los Angeles County municipal sewer system from 1947 to 1971. Following primary treatment, the effluent was discharged through a submarine outfall system whereupon a portion of the DDT and associated degradation products were deposited in sediments of the Palos Verdes Shelf (PVS). Parent DDT is present only in trace amounts in the sediments today, the vast majority having been transformed to DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene) shortly following deposition. Previously believed to be inert, DDE is slowly being converted to DDMU (1-chloro-4-[2-chloro-1-(4-chlorophenyl)ethenyl]benzene) and DDMU to DDNU (1-chloro-4-[1-(4-chlorophenyl)ethenyl]benzene) via microbially-mediated reductive dechlorination (RDC). Kinetic and compositional data suggest that this process began sometime in the mid- to late 1970s. Rates of DDE RDC in shelf sediments are spatially variable and have proven difficult to determine accurately. This limits our ability to understand the factors controlling RDC rates and to predict the course of natural recovery. In the present study, concentrations of ten DDT compounds and twelve PCB (polychlorinated biphenyl) congeners were determined in cores collected at two locations on the PVS (stations 3C, 6C, ~7km and ~2km downcurrent from the outfalls, respectively). DDE inventories, normalized to those of non-degrading PCB congeners having similar physico-chemical properties, were modeled to yield first-order RDC rates for the period 1981–2010. Average rates at stations 3C and 6C were 0.044±0.004 and 0.008±0.002yr<sup>−1</sup>, respectively, with depth-dependent RDC rates at station 3C (1992–2003) ranging from 0.0025 to 0.102yr<sup>−1</sup>. Comparison of RDC and total loss (i.e., RDC+physical loss) rates suggests that the average per cent loss of DDE due to RDC is ~90% at station 3C (1981–2010) and ~57% at station 6C (1992–2010). Trajectories of adjusted molar inventories of DDE, DDMU, and DDNU were forecast using a first-order multi-step reaction series (M-SRS) model. The results for DDE are consistent with the normalization procedure; RDC rates at stations 3C and 6C were 0.036±0.002yr<sup>−1</sup> and 0.010±0.001yr<sup>−1</sup>, respectively. At station 6C, the DDE to DDMU transformation appears to be the rate limiting step in the reaction sequence, DDE <i>k</i><sub>1</sub>→ DDMU <i>k</i><sub>2</sub>→ DDNU <sub>k3</sub>→ unidentified compound(s), whereas at station 3C RDC rates for DDE and DDMU are roughly equivalent. At both locations the transformation rate of DDNU is 7–20 times that of the other steps. Estimated half-lives of DDE at stations 3C and 6C based on the M-SRS model results are ~19 and 72 years, respectively.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marchem.2017.12.005","usgsCitation":"Eganhouse, R.P., Sherwood, C.R., Pontolillo, J., Edwards, B., and Dickhudt, P., 2018, Reductive dechlorination rates of 4,4′-DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene) in sediments of the Palos Verdes Shelf, CA: Marine Chemistry, v. 203, p. 10-21, https://doi.org/10.1016/j.marchem.2017.12.005.","productDescription":"12 p.","startPage":"10","endPage":"21","ipdsId":"IP-088923","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460891,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marchem.2017.12.005","text":"Publisher Index Page"},{"id":355656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Palos Verde Shelf","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.35111111111111,33.66777777777777 ], [ -118.35111111111111,33.7175 ], [ -118.28444444444445,33.7175 ], [ -118.28444444444445,33.66777777777777 ], [ -118.35111111111111,33.66777777777777 ] ] ] } } ] }","volume":"203","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc431e4b0f5d57878ea15","contributors":{"authors":[{"text":"Eganhouse, Robert P. 0000-0002-2075-5908 eganhous@usgs.gov","orcid":"https://orcid.org/0000-0002-2075-5908","contributorId":206243,"corporation":false,"usgs":true,"family":"Eganhouse","given":"Robert","email":"eganhous@usgs.gov","middleInitial":"P.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":739872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":739873,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pontolillo, James 0000-0002-1075-1313 jpontoli@usgs.gov","orcid":"https://orcid.org/0000-0002-1075-1313","contributorId":206244,"corporation":false,"usgs":true,"family":"Pontolillo","given":"James","email":"jpontoli@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":739874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, Brian 0000-0002-4655-8208 bedwards@usgs.gov","orcid":"https://orcid.org/0000-0002-4655-8208","contributorId":206245,"corporation":false,"usgs":true,"family":"Edwards","given":"Brian","email":"bedwards@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739875,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickhudt, Patrick J. ","contributorId":169593,"corporation":false,"usgs":false,"family":"Dickhudt","given":"Patrick J. ","affiliations":[{"id":25562,"text":"(former) Woods Hole Coastal and Marine Science Center employee","active":true,"usgs":false}],"preferred":false,"id":739876,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70197656,"text":"70197656 - 2018 - Quantifying anthropogenic contributions to century-scale groundwater salinity changes, San Joaquin Valley, California, USA","interactions":[],"lastModifiedDate":"2018-06-18T11:04:24","indexId":"70197656","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying anthropogenic contributions to century-scale groundwater salinity changes, San Joaquin Valley, California, USA","docAbstract":"Total dissolved solids (TDS) concentrations in groundwater tapped for beneficial uses (drinking water, irrigation, freshwater industrial) have increased on average by about 100 mg/L over the last 100 years in the San Joaquin Valley, California (SJV). During this period land use in the SJV changed from natural vegetation and dryland agriculture to dominantly irrigated agriculture with growing urban areas. Century-scale salinity trends were evaluated by comparing TDS concentrations and major ion compositions of groundwater from wells sampled in 1910 (Historic) to data from wells sampled in 1993-2015 (Modern). TDS concentrations in subregions of the SJV, the southern (SSJV), western (WSJV), northeastern (NESJV), and southeastern (SESJV) were calculated using a cell-declustering method. TDS concentrations increased in all regions, with the greatest increases found in the SSJV and SESJV. Evaluation of the Modern data from the NESJV and SESJV found higher TDS concentrations in recently recharged (post-1950) groundwater from shallow (< 50 m) wells surrounded predominantly by agricultural land uses, while premodern (pre-1950) groundwater from deeper wells, and recently recharged groundwater from wells surrounded by mainly urban, natural, and mixed land uses had lower TDS concentrations, approaching the TDS concentrations in the Historic groundwater. For the NESJV and SESJV, inverse geochemical modeling with PHREEQC indicated that weathering of primary silicate minerals accounted for the majority of the increase in TDS concentrations, contributing more than nitrate from fertilizers and sulfate from soil amendments combined. Bicarbonate showed the greatest increase among major ions, resulting from enhanced silicate weathering due to recharge of irrigation water enriched in CO2 during the growing season. The results of this study demonstrate that large anthropogenic changes to the hydrologic regime, like massive development of irrigated agriculture in semi-arid areas like the SJV, can cause large changes in groundwater quality on a regional scale.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.05.333","usgsCitation":"Hansen, J.A., Jurgens, B., and Fram, M.S., 2018, Quantifying anthropogenic contributions to century-scale groundwater salinity changes, San Joaquin Valley, California, USA: Science of the Total Environment, v. 642, p. 125-136, https://doi.org/10.1016/j.scitotenv.2018.05.333.","productDescription":"12 p.","startPage":"125","endPage":"136","ipdsId":"IP-083514","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":460889,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.05.333","text":"Publisher Index Page"},{"id":437861,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7319T3K","text":"USGS data release","linkHelpText":"Groundwater-quality data and ancillary data for selected wells in the San Joaquin Valley, California, 1900-2015"},{"id":355083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley, San Joaquin Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.71728515624999,\n              40.195659093364654\n            ],\n            [\n              -122.51953124999999,\n              39.791654835253425\n            ],\n            [\n              -122.3876953125,\n              39.487084981687495\n 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-121.59667968749999,\n              39.487084981687495\n            ],\n            [\n              -121.70654296874999,\n              39.85915479295669\n            ],\n            [\n              -121.83837890625,\n              40.245991504199026\n            ],\n            [\n              -122.25585937500001,\n              40.74725696280421\n            ],\n            [\n              -122.36572265625,\n              40.74725696280421\n            ],\n            [\n              -122.71728515624999,\n              40.44694705960048\n            ],\n            [\n              -122.84912109375,\n              40.3130432088809\n            ],\n            [\n              -122.71728515624999,\n              40.195659093364654\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"642","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e566e4b060350a15d115","contributors":{"authors":[{"text":"Hansen, Jeffrey A. 0000-0002-2185-1686","orcid":"https://orcid.org/0000-0002-2185-1686","contributorId":205441,"corporation":false,"usgs":true,"family":"Hansen","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738093,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70198069,"text":"70198069 - 2018 - DDT and related compounds in pore water of shallow sediments on the Palos Verdes Shelf, California, USA","interactions":[],"lastModifiedDate":"2018-07-16T11:06:02","indexId":"70198069","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2662,"text":"Marine Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"DDT and related compounds in pore water of shallow sediments on the Palos Verdes Shelf, California, USA","docAbstract":"<p>For nearly two and a half decades following World War II, production wastes from the world's largest manufacturer of technical DDT (1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene) were discharged into sewers of Los Angeles County. Following treatment, the wastes were released via a submarine outfall system to nearshore coastal waters where a portion accumulated in shallow sediments of the Palos Verdes Shelf (PVS). An investigation of the pore-water geochemistry of DDT-related compounds (DDX) was undertaken in an effort to understand factors controlling the rate of reductive dechlorination (RDC) of the major DDT degradate, 4,4′-DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene). Equilibrium matrix-solid phase microextraction (matrix-SPMEeq) combined with automated thermal desorption-gas chromatography/mass spectrometry (TDGC/MS) was used to determine freely dissolved concentrations of ten DDX analytes in sediment cores collected from three locations on the PVS (stations 3C, 6C, 8C, which are 7 km, 2 km, and 0 km, respectively, downcurrent from the outfall system). Pore-water concentrations (pM) of the principal DDX compounds involved in RDC were: 3C-DDE: 6.0–24, DDMU (1-chloro-4-[2-chloro-1-(4-chlorophenyl)ethenyl]benzene): 11–160, DDNU (1-chloro-4-[1-(4-chlorophenyl)ethenyl]benzene): 1.8–68; 6C-DDE: 5.6–170, DDMU: 5.6–177, DDNU: 1.7–87; 8CDDE: 27–212, DDMU: 31–403, DDNU: 5.5–89. Variations in the spatial distribution of DDX analytes in pore water reflect several factors including proximity to the outfalls, RDC reaction rates, and natural variability in sedimentation and post-depositional transport processes. A comparison of pore-water data produced using matrix-SPME<sub>eq</sub>/TD-GC/MS and whole-core squeezing/solvent extraction/liquid injection-GC/MS indicates that the majority of the DDE in the upper sediment column (≤about 10 cm) is associated with dissolved/colloidal organic matter. Below that depth, freely-dissolved DDE predominates. The principal organic geochemical phase controlling sorption of DDE in PVS sediments are residual hydrocarbons, the vast majority of which originated from petroleum refinery wastes. Organic carbon-normalized sediment-water distribution coefficients (KOC) were calculated from solid-phase and pore-water concentrations of DDX and organic carbon. Log K<sub>OC</sub> values (L/kg) were relatively invariant across the shelf and with depth in the sediment column. Shelf-wide compound-specific coefficients (log K<sub>OC</sub>) were: DDE: 7.5 ± 0.11, DDMU: 6.92 ± 0.13, DDNU: 6.37 ± 0.19. The spatial uniformity of K<sub>OC</sub> means that biological exposure and availability of the DDX compounds can, in principle, be estimated from solid-phase chemical measurements.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marchem.2018.05.003","usgsCitation":"Eganhouse, R.P., DiFilippo, E.L., Pontolillo, J., Orem, W.H., Hackley, P.C., and Edwards, B., 2018, DDT and related compounds in pore water of shallow sediments on the Palos Verdes Shelf, California, USA: Marine Chemistry, v. 203, p. 78-90, https://doi.org/10.1016/j.marchem.2018.05.003.","productDescription":"13 p.","startPage":"78","endPage":"90","ipdsId":"IP-088771","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468657,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marchem.2018.05.003","text":"Publisher Index Page"},{"id":355658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Palos Verdes Shelf","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.35111111111111,33.66777777777777 ], [ -118.35111111111111,33.7175 ], [ -118.28444444444445,33.7175 ], [ -118.28444444444445,33.66777777777777 ], [ -118.35111111111111,33.66777777777777 ] ] ] } } ] }","volume":"203","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc430e4b0f5d57878ea13","contributors":{"authors":[{"text":"Eganhouse, Robert P. 0000-0002-2075-5908 eganhous@usgs.gov","orcid":"https://orcid.org/0000-0002-2075-5908","contributorId":206243,"corporation":false,"usgs":true,"family":"Eganhouse","given":"Robert","email":"eganhous@usgs.gov","middleInitial":"P.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":739877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiFilippo, Erica L.","contributorId":90449,"corporation":false,"usgs":true,"family":"DiFilippo","given":"Erica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":739878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pontolillo, James 0000-0002-1075-1313 jpontoli@usgs.gov","orcid":"https://orcid.org/0000-0002-1075-1313","contributorId":206244,"corporation":false,"usgs":true,"family":"Pontolillo","given":"James","email":"jpontoli@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":739879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":739880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":739881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Edwards, Brian 0000-0002-4655-8208 bedwards@usgs.gov","orcid":"https://orcid.org/0000-0002-4655-8208","contributorId":206245,"corporation":false,"usgs":true,"family":"Edwards","given":"Brian","email":"bedwards@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739882,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70198024,"text":"70198024 - 2018 - Insular biogeographic origins and high phylogenetic distinctiveness for a recently depleted lizard fauna from Christmas Island, Australia","interactions":[],"lastModifiedDate":"2018-07-16T11:08:03","indexId":"70198024","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1028,"text":"Biology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Insular biogeographic origins and high phylogenetic distinctiveness for a recently depleted lizard fauna from Christmas Island, Australia","docAbstract":"<p><span>Striking faunal turnover across Asia and Australasia, most famously along the eastern edge of the Sunda Shelf or ‘Wallace's Line’, has been a focus of biogeographic research for over 150 years. Here, we investigate the origins of a highly threatened endemic lizard fauna (four species) on Christmas Island. Despite occurring less 350 km south of the Sunda Shelf, this fauna mostly comprises species from clades centred on the more distant regions of Wallacea, the Pacific and Australia (more than 1000 km east). The three most divergent lineages show Miocene (approx. 23–5 Ma) divergences from sampled relatives; and have recently become extinct or extinct in the wild, likely owing to the recent introduction of a southeast Asian snake (</span><i>Lycodon capucinus</i><span>). Insular distributions, deep phylogenetic divergence and recent decline suggest that rather than dispersal ability or recent origins, environmental and biotic barriers have impeded these lineages from diversifying on the continental Sunda Shelf, and thereby, reinforced faunal differentiation across Wallace's Line. Our new phylogenetically informed perspective further highlights the rapid loss of ancient lineages that has occurred on Christmas Island, and underlines how the evolutionary divergence and vulnerability of many island-associated lineages may continue to be underestimated.</span></p>","language":"English","publisher":"The Royal Society","doi":"10.1098/rsbl.2017.0696","usgsCitation":"Oliver, P.M., Blom, M., Cogger, H.G., Fisher, R.N., Richmond, J.Q., and Woinarski, J.C., 2018, Insular biogeographic origins and high phylogenetic distinctiveness for a recently depleted lizard fauna from Christmas Island, Australia: Biology Letters, v. 14, no. 6, p. 1-5, https://doi.org/10.1098/rsbl.2017.0696.","productDescription":"Article  20170696; 5 p.","startPage":"1","endPage":"5","ipdsId":"IP-093671","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsbl.2017.0696","text":"Publisher Index Page"},{"id":355548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Christmas Island","volume":"14","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5b46e566e4b060350a15d113","contributors":{"authors":[{"text":"Oliver, Paul M.","contributorId":178111,"corporation":false,"usgs":false,"family":"Oliver","given":"Paul","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":739683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blom, Mozes P. K.","contributorId":206162,"corporation":false,"usgs":false,"family":"Blom","given":"Mozes P. K.","affiliations":[{"id":37265,"text":"Naturhistoriska Riksmuseet, Sweden","active":true,"usgs":false}],"preferred":false,"id":739684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cogger, Harold G.","contributorId":206163,"corporation":false,"usgs":false,"family":"Cogger","given":"Harold","email":"","middleInitial":"G.","affiliations":[{"id":37266,"text":"The Australian Museum","active":true,"usgs":false}],"preferred":false,"id":739685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":739682,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":739686,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Woinarski, John C. Z.","contributorId":206164,"corporation":false,"usgs":false,"family":"Woinarski","given":"John","email":"","middleInitial":"C. Z.","affiliations":[{"id":37267,"text":"Charles Darwin University, Australia","active":true,"usgs":false}],"preferred":false,"id":739687,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70200470,"text":"70200470 - 2018 - Harnessing big data to rethink land heterogeneity in Earth system models","interactions":[],"lastModifiedDate":"2018-10-18T14:26:46","indexId":"70200470","displayToPublicDate":"2018-06-14T14:26:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Harnessing big data to rethink land heterogeneity in Earth system models","docAbstract":"<p><span>The continual growth in the availability, detail, and wealth of environmental data provides an invaluable asset to improve the characterization of land heterogeneity in Earth system models – a persistent challenge in macroscale models. However, due to the nature of these data (volume and complexity) and computational constraints, these data are underused for global applications. As a proof of concept, this study explores how to effectively and efficiently harness these data in Earth system models over a 1/4° ( ∼ </span><span>25</span><span>km) grid cell in the western foothills of the Sierra Nevada in central California. First, a novel hierarchical multivariate clustering approach (HMC) is introduced that summarizes the high-dimensional environmental data space into hydrologically interconnected representative clusters (i.e., tiles). These tiles and their associated properties are then used to parameterize the sub-grid heterogeneity of the Geophysical Fluid Dynamics Laboratory (GFDL) LM4-HB land model. To assess how this clustering approach impacts the simulated water, energy, and carbon cycles, model experiments are run using a series of different tile configurations assembled using HMC. The results over the test domain show that (1)&nbsp;the observed similarity over the landscape makes it possible to converge on the macroscale response of the fully distributed model with around 300 sub-grid land model tiles; (2)&nbsp;assembling the sub-grid tile configuration from available environmental data can have a large impact on the macroscale states and fluxes of the water, energy, and carbon cycles; for example, the defined subsurface connections between the tiles lead to a dampening of macroscale extremes; (3)&nbsp;connecting the fine-scale grid to the model tiles via HMC enables circumvention of the classic scale discrepancies between the macroscale and field-scale estimates; this has potentially significant implications for the evaluation and application of Earth system models.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-3311-2018","usgsCitation":"Chaney, N.W., Van Huijgevoort, M.H., Shevliakova, E., Malyshev, S., Milly, P.C., Gauthier, P., and Sulman, B.N., 2018, Harnessing big data to rethink land heterogeneity in Earth system models: Hydrology and Earth System Sciences, v. 22, p. 3311-3330, https://doi.org/10.5194/hess-22-3311-2018.","productDescription":"20 p.","startPage":"3311","endPage":"3330","ipdsId":"IP-090830","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-3311-2018","text":"Publisher Index Page"},{"id":358546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-14","publicationStatus":"PW","scienceBaseUri":"5c10a99ae4b034bf6a7e535d","contributors":{"authors":[{"text":"Chaney, Nathaniel W.","contributorId":169242,"corporation":false,"usgs":false,"family":"Chaney","given":"Nathaniel","email":"","middleInitial":"W.","affiliations":[{"id":25453,"text":"Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA","active":true,"usgs":false}],"preferred":false,"id":749025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Huijgevoort, Marjolein H. J.","contributorId":209888,"corporation":false,"usgs":false,"family":"Van Huijgevoort","given":"Marjolein","email":"","middleInitial":"H. J.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shevliakova, Elena","contributorId":201589,"corporation":false,"usgs":false,"family":"Shevliakova","given":"Elena","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":749027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malyshev, Sergey","contributorId":201588,"corporation":false,"usgs":false,"family":"Malyshev","given":"Sergey","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":749028,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":749024,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gauthier, Paul P. G.","contributorId":209889,"corporation":false,"usgs":false,"family":"Gauthier","given":"Paul P. G.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749029,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sulman, Benjamin N. 0000-0002-3265-6691","orcid":"https://orcid.org/0000-0002-3265-6691","contributorId":209890,"corporation":false,"usgs":false,"family":"Sulman","given":"Benjamin","email":"","middleInitial":"N.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749030,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70216335,"text":"70216335 - 2018 - Thresholds and hotspots for shrub restoration following a heterogeneous megafire","interactions":[],"lastModifiedDate":"2020-11-12T15:00:59.555625","indexId":"70216335","displayToPublicDate":"2018-06-14T08:54:45","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds and hotspots for shrub restoration following a heterogeneous megafire","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Context</h3><p>Reestablishing foundational plant species through aerial seeding is an essential yet challenging step for restoring the vast semiarid landscapes impacted by plant invasions and wildfire-regime shifts. A key component of the challenge stems from landscape variability and its effects on plant recovery.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Objectives</h3><p>We assessed landscape correlates, thresholds, and tipping points for sagebrush presence from fine-scale sampling across a large, heterogeneous area burned the previous year, where we were able to quantify soil surface features that are typically occluded yet can strongly affect recovery patterns.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>Hypothesis testing and binary-decision trees were used to evaluate factors affecting initial sagebrush establishment, using 2171 field plots (totaling ~ 2,000,000&nbsp;m<sup>2</sup><span>&nbsp;</span>sampled) over a 113,000-ha region.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Sagebrush established in 50% of plots where it was seeded, a &gt; 12-fold greater establishment frequency than in unseeded areas. Sagebrush establishment was enhanced in threshold-like ways by elevation (&gt; 1200&nbsp;m ASL), topographic features that alter heatload and soil water, and by soil-surface features such as “fertile islands” that bore the imprint of pre-fire sagebrush. Sagebrush occupancy had a negative, linear relationship with exotic-annual grass cover and parabolic relationship with perennial bunchgrasses (optimal at 40% cover).</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Our approach revealed interactive, ecological relationships such as novel soil-surface effects on first year establishment of sagebrush across the burned landscape, and identified “hot spots” for recovery. The approach could be expanded across sites and years to provide the information needed to explain past seeding successes or failures, and in designing treatments at the landscape scale.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0662-8","usgsCitation":"Germino, M., Barnard, D., Davidson, B., Arkle, R., Pilliod, D., Fisk, M., and Applestein, C., 2018, Thresholds and hotspots for shrub restoration following a heterogeneous megafire: Landscape Ecology, v. 33, p. 1177-1194, https://doi.org/10.1007/s10980-018-0662-8.","productDescription":"18 p.","startPage":"1177","endPage":"1194","ipdsId":"IP-090670","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":380454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.04833984375001,\n              43.197167282501276\n            ],\n            [\n              -116.1474609375,\n              43.197167282501276\n            ],\n            [\n              -116.1474609375,\n              44.008620115415354\n            ],\n            [\n              -117.04833984375001,\n              44.008620115415354\n            ],\n            [\n              -117.04833984375001,\n              43.197167282501276\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"33","noUsgsAuthors":false,"publicationDate":"2018-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Germino, Matthew 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":218007,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, David 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":218008,"corporation":false,"usgs":true,"family":"Barnard","given":"David","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davidson, Bill 0000-0003-1315-479X","orcid":"https://orcid.org/0000-0003-1315-479X","contributorId":218011,"corporation":false,"usgs":true,"family":"Davidson","given":"Bill","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804735,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arkle, Robert 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":216339,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804737,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisk, Matthew 0000-0002-2250-0116","orcid":"https://orcid.org/0000-0002-2250-0116","contributorId":205749,"corporation":false,"usgs":true,"family":"Fisk","given":"Matthew","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804738,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":205748,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804739,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70217156,"text":"70217156 - 2018 - Exposure to human-associated chemical markers of fecal contamination and self-reported illness among swimmers at recreational beaches","interactions":[],"lastModifiedDate":"2021-01-07T13:39:52.424305","indexId":"70217156","displayToPublicDate":"2018-06-14T07:34:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Exposure to human-associated chemical markers of fecal contamination and self-reported illness among swimmers at recreational beaches","docAbstract":"<div class=\"article_abstract\"><div class=\"container container_scaled-down\"><div class=\"row\"><div class=\"col-xs-12\"><div id=\"abstractBox\" class=\"article_abstract-content hlFld-Abstract\"><p class=\"articleBody_abstractText\">Anthropogenic chemicals have been proposed as potential markers of human fecal contamination in recreational water. However, to date, there are no published studies describing their relationships with illness risks. Using a cohort of swimmers at seven U.S. beaches, we examined potential associations between the presence of chemical markers of human fecal pollution and self-reported gastrointestinal (GI) illness, diarrhea, and respiratory illness. Swimmers were surveyed about their beach activities, water exposure, and baseline symptoms on the day of their beach visit, and about any illness experienced 10–12 days later. Risk differences were estimated using model-based standardization and adjusted for the swimmer’s age, beach site, sand contact, rainfall, and water temperature. Sixty-two chemical markers were analyzed from daily water samples at freshwater and marine beaches. Of those, 20 were found consistently. With the possible exception of bisphenol A and cholesterol, no chemicals were consistently associated with increased risks of illness. These two chemicals were suggestively associated with 2% and 1% increased risks of GI illness and diarrhea in both freshwater and marine beaches. Additional research using the more sensitive analytic methods currently available for a wider suite of analytes is needed to support the use of chemical biomarkers to quantify illness risk and identify fecal pollution sources.</p></div></div></div></div></div>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.8b00639","usgsCitation":"Napier, M.D., Poole, C., Stewart, J.R., Weber, D.J., Glassmeyer, S.T., Kolpin, D.W., Furlong, E., Dufour, A.P., and Wade, T.J., 2018, Exposure to human-associated chemical markers of fecal contamination and self-reported illness among swimmers at recreational beaches: Environmental Science & Technology, v. 52, no. 13, p. 7513-7523, https://doi.org/10.1021/acs.est.8b00639.","productDescription":"11 p.","startPage":"7513","endPage":"7523","ipdsId":"IP-097335","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468659,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://europepmc.org/articles/pmc6192706","text":"External Repository"},{"id":381997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Indiana, Michigan, Mississippi, Ohio, Rhode Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.3525390625,\n              42.68243539838623\n            ],\n            [\n              -86.748046875,\n              42.13082130188811\n            ],\n            [\n              -87.5830078125,\n              41.64007838467894\n            ],\n            [\n              -87.0556640625,\n              41.343824581185686\n            ],\n            [\n              -86.0888671875,\n              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University of North Carolina-Chapel Hill, Chapel Hill, NC","active":true,"usgs":false}],"preferred":false,"id":807746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Jill R","contributorId":247491,"corporation":false,"usgs":false,"family":"Stewart","given":"Jill","email":"","middleInitial":"R","affiliations":[{"id":49555,"text":"Department of Environmental Sciences and Engineering, University of North Carolina-Chapel Hill, Chapel Hill, NC","active":true,"usgs":false}],"preferred":false,"id":807747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, David J","contributorId":247492,"corporation":false,"usgs":false,"family":"Weber","given":"David","email":"","middleInitial":"J","affiliations":[{"id":49556,"text":"Division of Infectious Diseases, School of Medicine, University of North Carolina Health Care, Chapel Hill, NC","active":true,"usgs":false}],"preferred":false,"id":807748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glassmeyer, Susan T.","contributorId":184135,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":807749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807750,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Furlong, Edward 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":213730,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":807751,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dufour, Alfred P","contributorId":247494,"corporation":false,"usgs":false,"family":"Dufour","given":"Alfred","email":"","middleInitial":"P","affiliations":[{"id":49559,"text":"U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, Cincinnati, OH","active":true,"usgs":false}],"preferred":false,"id":807752,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wade, Timothy J. 0000-0002-7843-0997","orcid":"https://orcid.org/0000-0002-7843-0997","contributorId":247495,"corporation":false,"usgs":false,"family":"Wade","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":49553,"text":"U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Research Triangle Park, NC","active":true,"usgs":false}],"preferred":false,"id":807753,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70197646,"text":"70197646 - 2018 - Rapid crop cover mapping for the conterminous United States","interactions":[],"lastModifiedDate":"2018-06-14T15:57:50","indexId":"70197646","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","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":"Rapid crop cover mapping for the conterminous United States","docAbstract":"<p><span>Timely crop cover maps with sufficient resolution are important components to various environmental planning and research applications. Through the modification and use of a previously developed crop classification model (CCM), which was originally developed to generate historical annual crop cover maps, we hypothesized that such crop cover maps could be generated rapidly during the growing season. Through a process of incrementally removing weekly and monthly independent variables from the CCM and implementing a ‘two model mapping’ approach, we found it viable to generate conterminous United States-wide rapid crop cover maps at a resolution of 250 m for the current year by the month of September. In this approach, we divided the CCM model into one ‘crop type model’ to handle the classification of nine specific crops and a second, binary model to classify the presence or absence of ‘other’ crops. Under the two model mapping approach, the training errors were 0.8% and 1.5% for the crop type and binary model, respectively, while test errors were 5.5% and 6.4%, respectively. With spatial mapping accuracies for annual maps reaching upwards of 70%, this approach demonstrated a strong potential for generating rapid crop cover maps by the 1</span><sup>st</sup><span><span>&nbsp;</span>of September.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-26284-w","usgsCitation":"Dahal, D., Wylie, B.K., and Howard, D., 2018, Rapid crop cover mapping for the conterminous United States: Scientific Reports, v. 8, Article number: 8631; 12 p., https://doi.org/10.1038/s41598-018-26284-w.","productDescription":"Article number: 8631; 12 p.","ipdsId":"IP-089563","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-26284-w","text":"Publisher Index 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,{"id":70197626,"text":"70197626 - 2018 - Seagrass impact on sediment exchange between tidal flats and salt Marsh, and the sediment budget of shallow bays","interactions":[],"lastModifiedDate":"2018-07-03T11:04:21","indexId":"70197626","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Seagrass impact on sediment exchange between tidal flats and salt Marsh, and the sediment budget of shallow bays","docAbstract":"Seagrasses are marine flowering plants that strongly impact their physical and biological\nsurroundings and are therefore frequently referred to as ecological engineers. The effect of seagrasses on coastal bay resilience and sediment transport dynamics is understudied. Here we use six historical maps of seagrass distribution in Barnegat Bay, USA, to investigate the role of these vegetated surfaces on the sediment storage capacity of shallow bays. Analyses are carried out by means of the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) numerical modeling framework. Results show that a decline in the extent of seagrass meadows reduces the sediment mass potentially stored within bay systems. The presence of seagrass reduces shear stress values across the entire bay, including unvegetated areas, and promotes sediment deposition on tidal flats. On the other hand, the presence of seagrasses decreases suspended sediment concentrations, which in turn reduces the delivery of sediment to marsh platforms. Results highlight the relevance of seagrasses for the long-term survival of coastal ecosystems, and the complex dynamics regulating the interaction between subtidal and intertidal landscapes.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GL078056","usgsCitation":"Donatelli, C., Ganju, N.K., Fagherazzi, S., and Leonardi, N., 2018, Seagrass impact on sediment exchange between tidal flats and salt Marsh, and the sediment budget of shallow bays: Geophysical Research Letters, v. 45, no. 10, p. 4933-4943, https://doi.org/10.1029/2018GL078056.","productDescription":"11 p.","startPage":"4933","endPage":"4943","ipdsId":"IP-093431","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460893,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gl078056","text":"Publisher Index Page"},{"id":355044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.25178527832031,\n              39.67759833072648\n            ],\n            [\n              -74.07840728759766,\n              39.67759833072648\n            ],\n            [\n              -74.07840728759766,\n              39.87048617098581\n            ],\n            [\n              -74.25178527832031,\n              39.87048617098581\n            ],\n            [\n              -74.25178527832031,\n              39.67759833072648\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"45","issue":"10","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-20","publicationStatus":"PW","scienceBaseUri":"5b46e567e4b060350a15d11f","contributors":{"authors":[{"text":"Donatelli, Carmine","contributorId":202870,"corporation":false,"usgs":false,"family":"Donatelli","given":"Carmine","affiliations":[{"id":36541,"text":"University of Liverpool, Department of Geography and Planning, 74 Bedford St S.","active":true,"usgs":false}],"preferred":false,"id":737973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil Kamal 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":192273,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil","email":"nganju@usgs.gov","middleInitial":"Kamal","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":737972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagherazzi, Sergio","contributorId":89282,"corporation":false,"usgs":true,"family":"Fagherazzi","given":"Sergio","affiliations":[],"preferred":false,"id":737974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leonardi, Nicoletta","contributorId":202868,"corporation":false,"usgs":false,"family":"Leonardi","given":"Nicoletta","email":"","affiliations":[{"id":36541,"text":"University of Liverpool, Department of Geography and Planning, 74 Bedford St S.","active":true,"usgs":false}],"preferred":false,"id":737975,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196548,"text":"ofr20181068 - 2018 - A guide to processing bat acoustic data for the North American Bat Monitoring Program (NABat)","interactions":[],"lastModifiedDate":"2018-09-25T07:59:14","indexId":"ofr20181068","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","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":"2018-1068","title":"A guide to processing bat acoustic data for the North American Bat Monitoring Program (NABat)","docAbstract":"<p>The North American Bat Monitoring Program (NABat) aims to improve the state of conservation science for all species of bats shared by the United States, Canada, and Mexico. To accomplish this goal, NABat offers guidance and standardized protocols for acoustic monitoring of bats. In this document, “A Guide to Processing Bat Acoustic Data for the North American Bat Monitoring Program (NABat),” we provide general recommendations and specific workflows for the process of identifying bat species from acoustic files recorded using the NABat stationary point and mobile transect acoustic monitoring protocols.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181068","collaboration":"Prepared in cooperation with Wildlife Conservation Society Canada, USDA Forest Service, US Army Corps of Engineers, Illinois Natural History Survey, New York State Department of Environmental Conservation, Colorado Natural Heritage Program, Montana Natural Heritage Program, National Park Service, and Bat Call Identification, Inc.","usgsCitation":"Reichert, B., and Lausen, C., Loeb, S., Weller, T.,  Allen, R., Britzke, E., Hohoff, T., Siemers, J., Burkholder, B., Herzog, C., and Verant, M., 2018, A guide to processing bat acoustic data for the North American Bat Monitoring Program (NABat): U.S. Geological Survey Open-File Report 2018–1068, 33 p., https://doi.org/10.3133/ofr20181068.","productDescription":"vi, 33 p.","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-092559","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":353437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1068/coverthb2.jpg"},{"id":354992,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1068/ofr20181068.pdf","text":"Report","size":"3.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1068"}],"contact":"<p>Center Director, <a href=\"https://www.fort.usgs.gov/\" data-mce-href=\"https://www.fort.usgs.gov/\">Fort Collins Science Center</a><br>U.S. Geological Survey<br>2150 Centre Ave., Bldg. C<br>Fort Collins, CO 80526-8118</p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Introduction<br></li><li>Step 1. Attribute Acoustic Files<br></li><li>Step 2. Noise Scrubbing<br></li><li>Step 3. Auto ID<br></li><li>Step 4. Manual Vetting<br></li><li>Step 5. Submit to NABat<br></li><li>Chapter 1. Processing Acoustic Data Using Kaleidoscope Pro Version 4.3.2<br></li><li>Chapter 2. Processing Full Spectrum Acoustic Data Using SonoBat 4.2.1<br></li><li>Chapter 3. Processing Acoustic Data Using Bat Call Identification ver. 2.7d (BCID)<br></li><li>Chapter 4. Processing Zero-Cross Acoustic Data Using EchoClass v 3.1<br></li><li>Chapter 5. Processing Zero-Cross Acoustic Data Using AnaLookW 4.2n<br></li><li>References<br></li><li>Appendix A. Case Study—Using Rule Sets to Process Acoustic Data for USDA Forest Service Lands in Northern California<br></li><li>Appendix B. Additional Guidance for AnaLookW<br></li><li>Appendix C. Bat Auto ID Species Confusion Matrix<br></li></ul><p><br data-mce-bogus=\"1\"></p>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2018-06-14","noUsgsAuthors":false,"publicationDate":"2018-06-14","publicationStatus":"PW","scienceBaseUri":"5b46e568e4b060350a15d123","contributors":{"authors":[{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":204260,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":733536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lausen, Cori","contributorId":204261,"corporation":false,"usgs":false,"family":"Lausen","given":"Cori","affiliations":[{"id":36893,"text":"Wildlife Conservation Society Canada","active":true,"usgs":false}],"preferred":false,"id":733537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loeb, Susan","contributorId":204263,"corporation":false,"usgs":false,"family":"Loeb","given":"Susan","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":733539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weller, Ted 0000-0002-2914-5225","orcid":"https://orcid.org/0000-0002-2914-5225","contributorId":204262,"corporation":false,"usgs":false,"family":"Weller","given":"Ted","email":"","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":733538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Ryan","contributorId":204270,"corporation":false,"usgs":false,"family":"Allen","given":"Ryan","email":"","affiliations":[{"id":36896,"text":"Bat Call Identification, Inc.","active":true,"usgs":false}],"preferred":false,"id":733546,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Britzke, Eric","contributorId":204264,"corporation":false,"usgs":false,"family":"Britzke","given":"Eric","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":733540,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hohoff, Tara","contributorId":204265,"corporation":false,"usgs":false,"family":"Hohoff","given":"Tara","email":"","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":733541,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siemers, Jeremy","contributorId":204266,"corporation":false,"usgs":false,"family":"Siemers","given":"Jeremy","affiliations":[{"id":27518,"text":"Colorado Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":733542,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burkholder, Braden","contributorId":204267,"corporation":false,"usgs":false,"family":"Burkholder","given":"Braden","email":"","affiliations":[{"id":36895,"text":"Montana Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":733543,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Herzog, Carl","contributorId":204268,"corporation":false,"usgs":false,"family":"Herzog","given":"Carl","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":733544,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Verant, Michelle 0000-0001-6994-6257","orcid":"https://orcid.org/0000-0001-6994-6257","contributorId":204269,"corporation":false,"usgs":false,"family":"Verant","given":"Michelle","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":733545,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70197648,"text":"70197648 - 2018 - Diurnal patterns of methane flux from a seasonal wetland: mechanisms and methodology","interactions":[],"lastModifiedDate":"2018-06-19T11:02:54","indexId":"70197648","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Diurnal patterns of methane flux from a seasonal wetland: mechanisms and methodology","docAbstract":"<p><span>Methane emissions from wetlands are temporally dynamic. Few chamber-based studies have explored diurnal variation in methane flux with high temporal replication. Using an automated sampling system, we measured methane flux every 2.5 to 4&nbsp;h for 205 diel cycles during three growing seasons (2013–2015) from a seasonal wetland in the Prairie Pothole Region of North America. During ponded conditions, fluxes were generally positive (i.e., methanogenesis dominant, 10.1 ± 0.8&nbsp;mg&nbsp;m</span><sup>−2</sup><span>&nbsp;h</span><sup>−1</sup><span>), had extreme range of variation (from −1 to 70&nbsp;mg&nbsp;m</span><sup>−2</sup><span>&nbsp;h</span><sup>−1</sup><span>), and were highest during late day. In contrast, during dry conditions fluxes were very low and primarily negative (i.e., oxidation dominant, −0.05 ± 0.002&nbsp;mg&nbsp;m</span><sup>−2</sup><span>&nbsp;h</span><sup>−1</sup><span>), with the highest (least negative) fluxes occurring at pre-dawn. During semi-saturated conditions, methane fluxes also were very low, oscillated between positive and negative values (i.e., balanced between methanogenesis and methane oxidation), and exhibited no diel pattern. Methane flux was positively correlated with air temperature during ponded conditions (</span><i class=\"EmphasisTypeItalic \">r</i><span> = 0.57) and negatively during dry conditions (</span><i class=\"EmphasisTypeItalic \">r</i><span> = −0.42). Multiple regression analyses showed that temperature, light and water-filled pore space explained 72% of variation in methane flux. Methane fluxes are highly temporally dynamic and follow contrasting diel patterns that are dependent on dominant microbial processes influenced by saturation state.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s13157-018-1042-5","usgsCitation":"Bansal, S., Tangen, B., and Finocchiaro, R., 2018, Diurnal patterns of methane flux from a seasonal wetland: mechanisms and methodology: Wetlands, v. 45, no. 10, p. 4933-4943, https://doi.org/10.1007/s13157-018-1042-5.","productDescription":"11 p.","startPage":"4933","endPage":"4943","ipdsId":"IP-091017","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":437862,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7348JB2","text":"USGS data release","linkHelpText":"Diurnal patterns of methane flux from a depressional, seasonal wetland"},{"id":355062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-22","publicationStatus":"PW","scienceBaseUri":"5b46e567e4b060350a15d119","contributors":{"authors":[{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finocchiaro, Raymond 0000-0002-5514-8729 rfinocchiaro@usgs.gov","orcid":"https://orcid.org/0000-0002-5514-8729","contributorId":167278,"corporation":false,"usgs":true,"family":"Finocchiaro","given":"Raymond","email":"rfinocchiaro@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738042,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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