{"pageNumber":"818","pageRowStart":"20425","pageSize":"25","recordCount":165485,"records":[{"id":70198034,"text":"70198034 - 2018 - A simple method for partitioning total solar radiation into diffuse/direct components in the United States","interactions":[],"lastModifiedDate":"2018-07-14T10:59:22","indexId":"70198034","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5719,"text":"International Journal of Green Energy","onlineIssn":"1543-5083","printIssn":"1543-5075","active":true,"publicationSubtype":{"id":10}},"title":"A simple method for partitioning total solar radiation into diffuse/direct components in the United States","docAbstract":"Solar radiation is a major sustainable and clean energy resource, and use of solar radiation is expected to increase. The utilization efficiency of solar energy varies with the relative proportions of the direct and diffuse components that compose total solar radiation and with the slope and aspect of the irradiated surface. The purpose of this paper is to develop a simple method for estimating diffuse and direct solar radiation at sites with observation of only total solar radiation. An existing model for estimating diffuse radiation, i.e., a linear relationship between the diffuse fraction (the ratio of diffuse radiation to total solar radiation) and the clearness index (the ratio of total solar radiation to extraterrestrial radiation), is applied to 7 sites across the continental United States with observations of diffuse and total radiation. The linear model shows good monthly performance. The model parameters (slope and interception) show a strong seasonal pattern that exhibits small variation across the 7 sites; therefore, the average values of the two monthly parameters may be used for estimating diffuse radiation for other locations with observations of total radiation.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15435075.2018.1484357","usgsCitation":"Fan, J., Huang, Q., Sumner, D.M., and Wang, D., 2018, A simple method for partitioning total solar radiation into diffuse/direct components in the United States: International Journal of Green Energy, v. 15, no. 9, p. 497-506, https://doi.org/10.1080/15435075.2018.1484357.","productDescription":"10 p.","startPage":"497","endPage":"506","ipdsId":"IP-066829","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":501656,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://stars.library.ucf.edu/scopus2015/10188","text":"External Repository"},{"id":355565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"15","issue":"9","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-28","publicationStatus":"PW","scienceBaseUri":"5b46e540e4b060350a15d05f","contributors":{"authors":[{"text":"Fan, Jingjing","contributorId":206181,"corporation":false,"usgs":false,"family":"Fan","given":"Jingjing","email":"","affiliations":[{"id":37274,"text":"Xian University of Technology","active":true,"usgs":false}],"preferred":false,"id":739728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Qiang","contributorId":206182,"corporation":false,"usgs":false,"family":"Huang","given":"Qiang","email":"","affiliations":[{"id":37274,"text":"Xian University of Technology","active":true,"usgs":false}],"preferred":false,"id":739729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sumner, David M. 0000-0002-2144-9304 dmsumner@usgs.gov","orcid":"https://orcid.org/0000-0002-2144-9304","contributorId":1362,"corporation":false,"usgs":true,"family":"Sumner","given":"David","email":"dmsumner@usgs.gov","middleInitial":"M.","affiliations":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true},{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":true,"id":739727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Dingbao","contributorId":166993,"corporation":false,"usgs":false,"family":"Wang","given":"Dingbao","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":739730,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198039,"text":"70198039 - 2018 - A novel technique for precision geometric correction of jitter distortion for the Europa Imaging System and other rolling shutter cameras","interactions":[],"lastModifiedDate":"2018-07-16T10:47:32","indexId":"70198039","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesTitle":{"id":5650,"text":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","onlineIssn":"2194-9034","printIssn":"1682-1750","active":true,"publicationSubtype":{"id":19}},"title":"A novel technique for precision geometric correction of jitter distortion for the Europa Imaging System and other rolling shutter cameras","docAbstract":"<p><span class=\"pb_abstract\">We use simulated images to demonstrate a novel technique for mitigating geometric distortions caused by platform motion (“jitter”) as two-dimensional image sensors are exposed and read out line by line (“rolling shutter”). The results indicate that the Europa Imaging System (EIS) on NASA’s Europa Clipper can likely meet its scientific goals requiring 0.1-pixel precision. We are therefore adapting the software used to demonstrate and test rolling shutter jitter correction to become part of the standard processing pipeline for EIS. The correction method will also apply to other rolling-shutter cameras, provided they have the operational flexibility to read out selected “check lines” at chosen times during the systematic readout of the frame area</span>  </p>","conferenceTitle":"2018 ISPRS TC III Mid-term Symposium “Developments, Technologies and Applications in Remote Sensing”","conferenceDate":"May 7-10, 2018","conferenceLocation":"Beijing, China","language":"English","publisher":"International Society for Photogrammetry & Remote Sensing","doi":"10.5194/isprs-archives-XLII-3-735-2018","usgsCitation":"Kirk, R.L., Shepherd, M., and Sides, S., 2018, A novel technique for precision geometric correction of jitter distortion for the Europa Imaging System and other rolling shutter cameras, 2018 ISPRS TC III Mid-term Symposium “Developments, Technologies and Applications in Remote Sensing”, v. XLII, no. 3, Beijing, China, May 7-10, 2018, p. 735-739, https://doi.org/10.5194/isprs-archives-XLII-3-735-2018.","productDescription":"4 p.","startPage":"735","endPage":"739","ipdsId":"IP-095328","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/isprs-archives-xlii-3-735-2018","text":"Publisher Index Page"},{"id":355567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"XLII","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-30","publicationStatus":"PW","scienceBaseUri":"5b46e540e4b060350a15d05b","contributors":{"authors":[{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shepherd, Makayla 0000-0002-4101-9977","orcid":"https://orcid.org/0000-0002-4101-9977","contributorId":206191,"corporation":false,"usgs":true,"family":"Shepherd","given":"Makayla","email":"","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sides, Stuart 0000-0002-7705-0677 ssides@usgs.gov","orcid":"https://orcid.org/0000-0002-7705-0677","contributorId":206192,"corporation":false,"usgs":true,"family":"Sides","given":"Stuart","email":"ssides@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":739750,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70198008,"text":"70198008 - 2018 - “Asian carp” is societally and scientifically problematic. Let's replace it","interactions":[],"lastModifiedDate":"2018-08-03T16:10:27","indexId":"70198008","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"“Asian carp” is societally and scientifically problematic. Let's replace it","docAbstract":"<p><span>Bighead Carp&nbsp;</span><i>Hypophthalmichthys nobilis</i><span>, Black Carp<span>&nbsp;</span></span><i>Mylopharyngodon piceus</i><span>, Grass Carp<span>&nbsp;</span></span><i>Ctenopharyngodon idella</i><span>, and Silver Carp<span>&nbsp;</span></span><i>H. molitrix</i><span><span>&nbsp;</span>are considered invasive species in North America and Europe. In North America, they are typically referred to collectively as “Asian carp”, a reference to their native range. The category “Asian carp” fails to acknowledge the cultural value and the ecological differences of these fishes, causes confusion when translated into Chinese, and frequently causes problems of communication with the public and occasionally among professionals when some species are intentionally or inadvertently in‐ or excluded when referred to collectively. Herein we review the long history of aquaculture of these species in China, their human cultural significance, the origin of the category “Asian carp”, and the problems the term “Asian carp” might cause when used in cross‐cultural communication. We recommend discontinuing use of the term Asian carp and replacing it with individual species names. When a group term is required, there are several more favorable alternatives, including existing Chinese terms that have been used for centuries.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/fsh.10087","usgsCitation":"Kocovsky, P., Chapman, D., and Qian, S.S., 2018, “Asian carp” is societally and scientifically problematic. Let's replace it: Fisheries, v. 43, no. 7, p. 311-316, https://doi.org/10.1002/fsh.10087.","productDescription":"6 p.","startPage":"311","endPage":"316","ipdsId":"IP-086982","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":355528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"7","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-27","publicationStatus":"PW","scienceBaseUri":"5b46e542e4b060350a15d06d","contributors":{"authors":[{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":739577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":739578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qian, Song S.","contributorId":198934,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":739579,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70197579,"text":"sim3410 - 2018 - Map of recently active traces of the Rodgers Creek Fault, Sonoma County, California","interactions":[],"lastModifiedDate":"2018-07-16T13:25:56","indexId":"sim3410","displayToPublicDate":"2018-07-06T00:00:00","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":"3410","title":"Map of recently active traces of the Rodgers Creek Fault, Sonoma County, California","docAbstract":"<p>The accompanying map and digital data identify recently active strands of the Rodgers Creek Fault in Sonoma County, California, interpreted primarily from the geomorphic expression of recent faulting on aerial photography and hillshade imagery derived from airborne lidar data. A recently active fault strand is defined here as having evidence consistent with slip during the Holocene epoch (approximately the past 11,700 years). The purpose of the map is to update the fundamental fault dataset for characterizing surface-rupture hazard, siting slip-rate and paleoseismic studies, and studying the geometry and evolution of slip. To serve a range of users, the map is presented in several formats: as an image map, as a digital database for use within GIS, and as a KML file for visualizing the fault using virtual globe software.</p><p>Important outcomes of this mapping revision include the following: (1) a northward 17-km increase in the known length of Holocene-active faulting to include most of the Healdsburg Fault, a structural continuation of the Rodgers Creek Fault northwest of a bend in the fault at Santa Rosa; (2) first-time identification of fault strands across the Santa Rosa Creek floodplain in central Santa Rosa; (3) increases in the known width and complexity of faulting; and (4) identification of fault splays that project toward the Bennett Valley-Maacama Fault system to the east and toward a recently mapped active extension of the Hayward Fault to the south beneath San Pablo Bay.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3410","usgsCitation":"Hecker, S., and Randolph Loar, C.E., 2018, Map of recently active traces of the Rodgers Creek Fault, Sonoma County, California: U.S. Geological Survey Scientific Investigations Map 3410, 7 p., 1 sheet, https://doi.org/10.3133/sim3410.","productDescription":"Sheet: 39.85 x 40.25 inches; Pamphlet: iii, 7 p.; Metadata; Spatial data; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-094680","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":355540,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_mapsheet.pdf","text":"Map sheet","size":"17.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3410"},{"id":355541,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_rcf_hfsec.shp.xml","text":"Northern section","size":"40 KB xml","description":"SIM 3410","linkHelpText":" - Healdsburg Fault section of the Rodgers Creek Fault "},{"id":355542,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_rcf_rcfsec.shp.xml","text":"Southern section","size":"40 KB xml","description":"SIM 3410","linkHelpText":" - Rodgers Creek Fault section of the Rodgers Creek Fault"},{"id":355543,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_data.zip","text":"Database","size":"1 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3410"},{"id":355544,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_rodgerscreekfault.kmz","text":"KMZ file","size":"450 KB kmz","description":"SIM 3410"},{"id":355545,"rank":8,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_readme.txt","text":"Read Me","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3410"},{"id":355538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3410/coverthb.jpg"},{"id":355539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3410/sim3410_pamphlet.pdf","text":"Pamphlet","size":"350 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3410"}],"country":"United States","state":"California","otherGeospatial":"Rodgers Creek Fault","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.4167,\n              38.16667\n            ],\n            [\n              -122.4833,\n              38.16667\n            ],\n            [\n              -122.9833,\n              38.68333\n            ],\n            [\n              -122.8667,\n              38.68333\n            ],\n            [\n              -122.4167,\n              38.16667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://earthquake.usgs.gov/contactus/menlo/\" target=\"_blank\" data-mce-href=\"https://earthquake.usgs.gov/contactus/menlo/\">Contact Information</a><br><a href=\"https://earthquake.usgs.gov/\" target=\"_blank\" data-mce-href=\"https://earthquake.usgs.gov/\">Earthquake Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>345 Middlefield Road, MS 977<br>Menlo Park, CA 94025<br></p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-07-06","noUsgsAuthors":false,"publicationDate":"2018-07-06","publicationStatus":"PW","scienceBaseUri":"5b46e543e4b060350a15d071","contributors":{"authors":[{"text":"Hecker, Suzanne 0000-0002-5054-372X","orcid":"https://orcid.org/0000-0002-5054-372X","contributorId":205568,"corporation":false,"usgs":true,"family":"Hecker","given":"Suzanne","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":737818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Randolph Loar, Carolyn E.","contributorId":205569,"corporation":false,"usgs":false,"family":"Randolph Loar","given":"Carolyn","email":"","middleInitial":"E.","affiliations":[{"id":37115,"text":"Stantec Consulting Services Inc","active":true,"usgs":false}],"preferred":false,"id":737819,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198011,"text":"70198011 - 2018 - Using cluster analysis to compartmentalize a large managed wetland based on physical, biological, and climatic geospatial attributes","interactions":[],"lastModifiedDate":"2018-09-10T10:59:41","indexId":"70198011","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Using cluster analysis to compartmentalize a large managed wetland based on physical, biological, and climatic geospatial attributes","docAbstract":"<p><span>Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward’s linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00267-018-1050-5","usgsCitation":"Hahus, I., Migliaccio, K., Douglas-Mankin, K.R., Klarenberg, G., and Muñoz-Carpena, R., 2018, Using cluster analysis to compartmentalize a large managed wetland based on physical, biological, and climatic geospatial attributes: Environmental Management, v. 62, no. 3, p. 571-583, https://doi.org/10.1007/s00267-018-1050-5.","productDescription":"13 p.","startPage":"571","endPage":"583","ipdsId":"IP-094746","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":355526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.446,\n              26.356\n            ],\n            [\n              -80.222,\n              26.356\n            ],\n            [\n              -80.222,\n              26.683\n            ],\n            [\n              -80.446,\n              26.683\n            ],\n            [\n              -80.446,\n              26.356\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"62","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-27","publicationStatus":"PW","scienceBaseUri":"5b46e542e4b060350a15d06b","contributors":{"authors":[{"text":"Hahus, Ian","contributorId":206143,"corporation":false,"usgs":false,"family":"Hahus","given":"Ian","email":"","affiliations":[{"id":37258,"text":"Department of Agricultural and Biological Engineering, University of Florida","active":true,"usgs":false}],"preferred":false,"id":739586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Migliaccio, Kati","contributorId":111526,"corporation":false,"usgs":true,"family":"Migliaccio","given":"Kati","affiliations":[],"preferred":false,"id":739587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas-Mankin, Kyle R. 0000-0002-3155-3666","orcid":"https://orcid.org/0000-0002-3155-3666","contributorId":203927,"corporation":false,"usgs":true,"family":"Douglas-Mankin","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klarenberg, Geraldine","contributorId":206145,"corporation":false,"usgs":false,"family":"Klarenberg","given":"Geraldine","email":"","affiliations":[{"id":37258,"text":"Department of Agricultural and Biological Engineering, University of Florida","active":true,"usgs":false}],"preferred":false,"id":739588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muñoz-Carpena, Rafael","contributorId":206146,"corporation":false,"usgs":false,"family":"Muñoz-Carpena","given":"Rafael","affiliations":[{"id":37258,"text":"Department of Agricultural and Biological Engineering, University of Florida","active":true,"usgs":false}],"preferred":false,"id":739589,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70198012,"text":"70198012 - 2018 - Frictional properties and 3-D stress analysis of the southern Alpine Fault, New Zealand","interactions":[],"lastModifiedDate":"2018-07-06T13:09:35","indexId":"70198012","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2468,"text":"Journal of Structural Geology","active":true,"publicationSubtype":{"id":10}},"title":"Frictional properties and 3-D stress analysis of the southern Alpine Fault, New Zealand","docAbstract":"<p><span>New Zealand's Alpine Fault (AF) ruptures quasi-periodically in large-magnitude earthquakes. Paleoseismological evidence suggests that about half of all recognized AF earthquakes terminated at the boundary between the Central and South Westland sections of the fault. There, fault geometry&nbsp;and the polarity of uplift change. The South Westland AF exhibits oblique-normal fault motion on a structure oriented 052°/82°SE that, for at least 35 km along strike, contains saponite-rich principal slip zone gouges. New hydrothermal friction experiments reveal that the saponite&nbsp;fault gouge is frictionally weak, exhibiting friction coefficients&nbsp;between&nbsp;</span><i>μ</i><span> = 0.12 and<span>&nbsp;</span></span><i>μ</i><span> = 0.16 for a range of temperatures (</span><i>T</i><span> = 25–210 °C) and effective normal stresses (</span><i>σ</i><sub><i>n</i></sub><span>' = 31.2–93.6 MPa). The saponite gouge is rate-strengthening in all velocity steps performed at velocities between 0.01 and 3.0 μm/s, behavior conducive to aseismic creep. A three-dimensional<span> stress analysis</span><span><span>&nbsp;</span>shows that the South Westland AF is favorably oriented with respect to the regional<span> stress field</span><span>&nbsp;</span>for slip within the frictionally weak saponite fault gouge. Geometrically, the fault is severely misoriented for slip in any fault-forming materials with friction coefficients exceeding<span>&nbsp;</span></span></span><i>μ</i><span><span>∼0.5. The combination of weak gouges prone to aseismic creep, strong<span> asperities</span><span>, and low resolved<span> shear stress</span><span>&nbsp;</span>may impede<span> earthquake rupture</span></span></span><span>&nbsp;</span>propagation along the South Westland Alpine Fault.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jsg.2018.06.003","usgsCitation":"Boulton, C., Barth, N.C., Moore, D.E., Lockner, D.A., Townend, J., and Faulkner, D.R., 2018, Frictional properties and 3-D stress analysis of the southern Alpine Fault, New Zealand: Journal of Structural Geology, v. 114, p. 43-54, https://doi.org/10.1016/j.jsg.2018.06.003.","productDescription":"12 p.","startPage":"43","endPage":"54","ipdsId":"IP-094797","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468600,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jsg.2018.06.003","text":"Publisher Index Page"},{"id":355524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              165.8056640625,\n              -47.5172006978394\n            ],\n            [\n              176.77001953125,\n              -47.5172006978394\n            ],\n            [\n              176.77001953125,\n              -39.65645604812829\n            ],\n            [\n              165.8056640625,\n              -39.65645604812829\n            ],\n            [\n              165.8056640625,\n              -47.5172006978394\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"114","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d069","contributors":{"authors":[{"text":"Boulton, Carolyn","contributorId":195077,"corporation":false,"usgs":false,"family":"Boulton","given":"Carolyn","email":"","affiliations":[],"preferred":false,"id":739591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Nicolas C.","contributorId":206132,"corporation":false,"usgs":false,"family":"Barth","given":"Nicolas","email":"","middleInitial":"C.","affiliations":[{"id":37254,"text":"University of California, Riverside, CA","active":true,"usgs":false}],"preferred":false,"id":739592,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Diane E. 0000-0002-8641-1075 dmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-8641-1075","contributorId":2704,"corporation":false,"usgs":true,"family":"Moore","given":"Diane","email":"dmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":739590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":739593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Townend, John","contributorId":206133,"corporation":false,"usgs":false,"family":"Townend","given":"John","email":"","affiliations":[{"id":34132,"text":"Victoria University of Wellington, NZ","active":true,"usgs":false}],"preferred":false,"id":739594,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Faulkner, Daniel R.","contributorId":206134,"corporation":false,"usgs":false,"family":"Faulkner","given":"Daniel","email":"","middleInitial":"R.","affiliations":[{"id":37255,"text":"University of Liverpool, UK","active":true,"usgs":false}],"preferred":false,"id":739595,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70198015,"text":"70198015 - 2018 - An updated method for estimating landslide‐event magnitude","interactions":[],"lastModifiedDate":"2018-07-13T14:28:34","indexId":"70198015","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"An updated method for estimating landslide‐event magnitude","docAbstract":"<p><span>Summary statistics derived from the frequency–area distribution (FAD) of inventories of triggered landslides allows for direct comparison of landslides triggered by one event (e.g. earthquake, rainstorm) with another. Such comparisons are vital to understand links between the landslide‐event and the environmental characteristics of the area affected. This could lead to methods for rapid estimation of landslide‐event magnitude, which in turn could lead to estimates of the total triggered landslide area. Previous studies proposed that the FAD of landslides follows an inverse power‐law, which provides the basis to model the size distribution of landslides and to estimate landslide‐event magnitude (</span><i>mLS</i><span>), which quantifies the severity of the event. In this study, we use a much larger collection of earthquake‐induced landslide (EQIL) inventories (</span><i>n</i><span>=45) than previous studies to show that size distributions are much more variable than previously assumed. We present an updated model and propose a method for estimating<span>&nbsp;</span></span><i>mLS</i><span><span>&nbsp;</span>and its uncertainty that better fits the observations and is more reproducible, robust, and consistent than existing methods. We validate our model by computing<span>&nbsp;</span></span><i>mLS</i><span><span>&nbsp;</span>for all of the inventories in our dataset and comparing that with the total landslide areas of the inventories. We show that our method is able to estimate the total landslide area of the events in this larger inventory dataset more successfully than the existing methods.<span>&nbsp;</span></span></p>","language":"English","publisher":"Wiley","doi":"10.1002/esp.4359","usgsCitation":"Tanyas, H., Allstadt, K.E., and van Weston, C.J., 2018, An updated method for estimating landslide‐event magnitude: Earth Surface Processes and Landforms, v. 43, no. 9, p. 1836-1847, https://doi.org/10.1002/esp.4359.","productDescription":"12 p.","startPage":"1836","endPage":"1847","ipdsId":"IP-090008","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468601,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.4359","text":"Publisher Index Page"},{"id":437830,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79022QD","text":"USGS data release","linkHelpText":"landslides-mLS"},{"id":355523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d067","contributors":{"authors":[{"text":"Tanyas, Hakan","contributorId":198731,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","affiliations":[],"preferred":false,"id":739604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":739603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Weston, Cees J.","contributorId":206153,"corporation":false,"usgs":false,"family":"van Weston","given":"Cees","email":"","middleInitial":"J.","affiliations":[{"id":37261,"text":"University of Twente, Netherlands","active":true,"usgs":false}],"preferred":false,"id":739605,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70198005,"text":"70198005 - 2018 - Variation in inbreeding rates across the range of Northern Spotted Owls (Strix occidentalis caurina): Insights from over 30 years of monitoring data","interactions":[],"lastModifiedDate":"2018-07-06T13:28:28","indexId":"70198005","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Variation in inbreeding rates across the range of Northern Spotted Owls (Strix occidentalis caurina): Insights from over 30 years of monitoring data","docAbstract":"<p><span>Inbreeding has been difficult to quantify in wild populations because of incomplete parentage information. We applied and extended a recently developed framework for addressing this problem to infer inbreeding rates in Northern Spotted Owls (</span><i>Strix occidentalis caurina</i><span>) across the Pacific Northwest, USA. Using pedigrees from 14,187 Northern Spotted Owls, we inferred inbreeding rates for 14 types of matings among relatives that produce pedigree inbreeding coefficients of<span>&nbsp;</span></span><i>F</i><span><span>&nbsp;</span>= 0.25 or<span>&nbsp;</span></span><i>F</i><span><span>&nbsp;</span>= 0.125. Inbreeding was most common in the Washington Cascades, where an estimated 15% of individuals are inbred. Inbreeding was lowest in western Oregon (3.5%) and northern California (2.7%), and intermediate for the Olympic Peninsula of Washington (6.1%). Estimates from the Olympic Peninsula were likely underestimates because of small sample sizes and the presence of few pedigrees capable of resolving inbreeding events. Most inbreeding resulted from matings between full siblings or half siblings, although a high rate of inbreeding from mother–son pairs was identified in the Olympic Peninsula. Geographic variation in inbreeding rates may reflect population declines and bottlenecks that have been detected in prior investigations. We show that there is strong selection against inbred birds. Only 3 of 44 inbred birds were later identified as parents (6.8%), whereas 2,823 of 10,380 birds that represented a comparable cross section of the data were later seen as reproducing parents (27.2%). Habitat loss and competition with Barred Owls (</span><i>S. varia</i><span>) remain primary threats to Northern Spotted Owls. However, given the negative consequences of inbreeding, Spotted Owl populations in Washington with suitable habitat and manageable numbers of Barred Owls may benefit from translocations of individuals from Oregon and California to introduce new genetic variation and reduce future inbreeding events.</span></p>","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-18-1.1","usgsCitation":"Miller, M.P., Haig, S.M., Forsman, E.D., Anthony, R., Diller, L., Dugger, K.M., Franklin, A.B., Fleming, T.L., Gremel, S., Lesmeister, D.B., Higley, M., Herter, D.R., and Sovern, S.G., 2018, Variation in inbreeding rates across the range of Northern Spotted Owls (Strix occidentalis caurina): Insights from over 30 years of monitoring data: The Auk, v. 135, no. 4, p. 821-833, https://doi.org/10.1642/AUK-18-1.1.","productDescription":"13 p.","startPage":"821","endPage":"833","ipdsId":"IP-096546","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468599,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1642/auk-18-1.1","text":"Publisher Index Page"},{"id":355529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -125.13427734374999,\n              37.64903402157866\n            ],\n            [\n              -119.5751953125,\n              37.64903402157866\n            ],\n            [\n              -119.5751953125,\n              49.03786794532644\n            ],\n            [\n              -125.13427734374999,\n              49.03786794532644\n            ],\n            [\n              -125.13427734374999,\n              37.64903402157866\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"135","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e543e4b060350a15d06f","contributors":{"authors":[{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":739563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":739564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forsman, Eric D.","contributorId":96792,"corporation":false,"usgs":false,"family":"Forsman","given":"Eric","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":739565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anthony, Robert G.","contributorId":61324,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert G.","affiliations":[],"preferred":false,"id":739566,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diller, Lowell","contributorId":206137,"corporation":false,"usgs":false,"family":"Diller","given":"Lowell","affiliations":[{"id":24606,"text":"Green Diamond Resource Company","active":true,"usgs":false}],"preferred":false,"id":739567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dugger, Katie M. 0000-0002-4148-246X","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":36037,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"","middleInitial":"M.","affiliations":[{"id":517,"text":"Oregon Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":739568,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Franklin, Alan B.","contributorId":101999,"corporation":false,"usgs":false,"family":"Franklin","given":"Alan","email":"","middleInitial":"B.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":739569,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fleming, Tracy L.","contributorId":96199,"corporation":false,"usgs":true,"family":"Fleming","given":"Tracy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":739638,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gremel, Scott","contributorId":206139,"corporation":false,"usgs":false,"family":"Gremel","given":"Scott","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":739570,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lesmeister, Damon B. 0000-0003-1102-0122","orcid":"https://orcid.org/0000-0003-1102-0122","contributorId":205006,"corporation":false,"usgs":false,"family":"Lesmeister","given":"Damon","email":"","middleInitial":"B.","affiliations":[{"id":37019,"text":"USDA Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":739571,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Higley, Mark","contributorId":206140,"corporation":false,"usgs":false,"family":"Higley","given":"Mark","email":"","affiliations":[{"id":37256,"text":"Hoopa Valley Tribal Forestry","active":true,"usgs":false}],"preferred":false,"id":739572,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Herter, Dale R.","contributorId":206141,"corporation":false,"usgs":false,"family":"Herter","given":"Dale","email":"","middleInitial":"R.","affiliations":[{"id":37257,"text":"Raedeke Associates, Inc","active":true,"usgs":false}],"preferred":false,"id":739573,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sovern, Stan G","contributorId":206142,"corporation":false,"usgs":false,"family":"Sovern","given":"Stan","email":"","middleInitial":"G","affiliations":[{"id":27990,"text":"Deceased","active":true,"usgs":false}],"preferred":false,"id":739574,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70197568,"text":"ofr20181096 - 2018 - Procedures for using the Horiba Scientific Aqualog<sup>®</sup> fluorometer to measure absorbance and fluorescence from dissolved organic matter","interactions":[],"lastModifiedDate":"2018-07-11T10:42:39","indexId":"ofr20181096","displayToPublicDate":"2018-07-05T00:00:00","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":"2018-1096","title":"Procedures for using the Horiba Scientific Aqualog<sup>®</sup> fluorometer to measure absorbance and fluorescence from dissolved organic matter","docAbstract":"<p>Advances in spectroscopic techniques have led to an increase in the use of optical measurements (absorbance and fluorescence) to assess dissolved organic matter composition and infer sources and processing. Although optical measurements are easy to make, they can be affected by many variables rendering them less comparable, including by inconsistencies in sample collection (for example, filter pore size, preservation), the application of corrections for interferences (for example, inner-filtering corrections), differences in holding times, and instrument drift (for example, lamp intensity). A documented, standardized procedure to address these variables ensures that the optical (absorbance and fluorescence) measurements collected by U.S. Geological Survey researchers are useful and widely comparable.</p><p>Rigorous and quantifiable quality assurance and quality control are essential for making these data comparable, particularly because there is no published guideline for the measurement of dissolved organic matter absorbance and fluorescence, and especially because there is no National Institute of Standards and Technology standard for dissolved organic matter. Validation and quality-control samples are analyzed on a monthly basis to determine laboratory and instrument precision and daily (that is, each day samples are run) to ensure repeatability. Data are not considered acceptable unless they meet laboratory criteria: All standards should be within 10 percent of the target value, laboratory replicates should be within 5 percent relative percent difference, and laboratory blanks (that is, laboratory reagent-grade water) should be less than one-tenth of the long-term method detection limit.</p><p>Finally, for data to be useful, they must be accessible to users in a format that can be easily analyzed and interpreted. The Organic Matter Research Laboratory staff has developed a processing routine that extracts a subset of the data, which is made available to the public through the USGS National Water Quality Information System (<a href=\"http://nwis.waterdata.usgs.gov/usa/nwis/qwdata\" target=\"_blank\" data-mce-href=\"http://nwis.waterdata.usgs.gov/usa/nwis/qwdata\">http://nwis.waterdata.usgs.gov/usa/nwis/qwdata</a>), and organizes the full datasets (that is, complete absorbance spectra and fluorescence excitation-emission matrices) in different forms that allow for these data to be analyzed using multi-parameter and multi-way statistical approaches.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181096","usgsCitation":"Hansen, A.M., Fleck, J.A., Kraus, T.E.C., Downing, B.D., von Dessonneck, T., and Bergamaschi, B.A., 2018, Procedures for using the Horiba Scientific Aqualog<sup>®</sup> fluorometer to measure absorbance and fluorescence from dissolved organic matter: U.S. Geological Survey Open-File Report 2018–1096, 31 p., https://doi.org/10.3133/ofr20181096.","productDescription":"Report: vi, 31 p.; 3 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082063","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355505,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1096/coverthb.jpg"},{"id":355506,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1096/ofr2018.1096.pdf","text":"Report","size":"5.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1096"},{"id":355509,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1096/ofr20181096_appendix3.xlsx","text":"Appendix 3","size":"12.8 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2018-1096 Appendix 3"},{"id":355507,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1096/ofr20181096_appendix1.pdf","text":"Appendix 1","size":"450 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1096 Appendix 1"},{"id":355508,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1096/ofr20181096_appendix2.xlsx","text":"Appendix 2","size":"350 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2018-1096 Appendix 2"}],"contact":"<div><a href=\"mailto:dc_ca@usgs.gov\" target=\"_blank\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,</div><div><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a></div><div><a href=\"https://usgs.gov/\" target=\"_blank\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a></div><div>6000 J Street, Placer Hall</div><div>Sacramento, California 95819</div>","tableOfContents":"<ul><li>Abstract<br></li><li>Purpose and Scope<br></li><li>Background<br></li><li>Sample Collection and Handling<br></li><li>Analytical Method<br></li><li>Data Processing and Corrections<br></li><li>Data Storage<br></li><li>Data Analysis<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix 1.  Aqualog® Standard Operating Procedure Walkthrough<br></li><li>Appendix 2.  Processed Summary Report for Absorbance Data<br></li><li>Appendix 3.  Processed Summary Report for Fluorescence Data<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2018-07-05","noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d079","contributors":{"authors":[{"text":"Hansen, Angela M. 0000-0003-0938-7611","orcid":"https://orcid.org/0000-0003-0938-7611","contributorId":204702,"corporation":false,"usgs":true,"family":"Hansen","given":"Angela M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737700,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"von Dessonneck, Travis","contributorId":178352,"corporation":false,"usgs":false,"family":"von Dessonneck","given":"Travis","email":"","affiliations":[],"preferred":false,"id":737698,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737699,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197997,"text":"70197997 - 2018 - Transient coastal landscapes: Rising sea level threatens salt marshes","interactions":[],"lastModifiedDate":"2018-07-05T10:20:30","indexId":"70197997","displayToPublicDate":"2018-07-05T00:00:00","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":"Transient coastal landscapes: Rising sea level threatens salt marshes","docAbstract":"<p><span>Salt marshes are important coastal environments that provide key ecological services. As sea level rise has accelerated globally, concerns about the ability of salt marshes to survive submergence are increasing. Previous estimates of likely survival of salt marshes were based on ratios of sea level rise to marsh platform accretion</span><span><span><span>. Here we took advantage of an unusual, long-term (1979–2015), spatially detailed comparison of changes in a representative New England salt marsh to provide an empirical estimate of<span> habitat losses&nbsp;</span>based on actual measurements. We show prominent changes in<span> habitat mosaic</span></span><span>&nbsp;</span>within the marsh, consistent and coincident with increased submergence and<span> coastal erosion</span></span><span>. Model results suggest that at current rates of sea level rise, marsh platform accretion, habitat loss, and with the limitation of the widespread “coastal squeeze”, the entire ecosystem might disappear by the beginning of the next century, a fate that might be likely for many salt marshes elsewhere.<span> Meta-analysis</span><span>&nbsp;</span>of available data suggests that 40 to 95% of the world's salt marshes will be submerged, depending on whether sea level rise remains at current or reaches anticipated rates for the end of this century.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.05.235","usgsCitation":"Valiela, I., Lloret, J., Bowyer, T., Miner, S., Remsen, D.P., Elmstrom, E., Cogswell, C., and Thieler, E.R., 2018, Transient coastal landscapes: Rising sea level threatens salt marshes: Science of the Total Environment, v. 640-641, p. 1148-1156, https://doi.org/10.1016/j.scitotenv.2018.05.235.","productDescription":"9 p.","startPage":"1148","endPage":"1156","ipdsId":"IP-081985","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/1912/10488","text":"Publisher Index Page"},{"id":355497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"640-641","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d075","contributors":{"authors":[{"text":"Valiela, Ivan","contributorId":189387,"corporation":false,"usgs":false,"family":"Valiela","given":"Ivan","email":"","affiliations":[],"preferred":false,"id":739535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lloret, Javier","contributorId":206128,"corporation":false,"usgs":false,"family":"Lloret","given":"Javier","email":"","affiliations":[{"id":37252,"text":"Ecosystems Center, Marine Biological Laboratory, Woods Hole MA US 02543","active":true,"usgs":false}],"preferred":false,"id":739536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowyer, Tynan","contributorId":206129,"corporation":false,"usgs":false,"family":"Bowyer","given":"Tynan","email":"","affiliations":[{"id":37252,"text":"Ecosystems Center, Marine Biological Laboratory, Woods Hole MA US 02543","active":true,"usgs":false}],"preferred":false,"id":739537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miner, Simon","contributorId":196953,"corporation":false,"usgs":false,"family":"Miner","given":"Simon","affiliations":[],"preferred":false,"id":739538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Remsen, David P.","contributorId":196868,"corporation":false,"usgs":false,"family":"Remsen","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":739539,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elmstrom, Elizabeth","contributorId":206130,"corporation":false,"usgs":false,"family":"Elmstrom","given":"Elizabeth","email":"","affiliations":[{"id":37252,"text":"Ecosystems Center, Marine Biological Laboratory, Woods Hole MA US 02543","active":true,"usgs":false}],"preferred":false,"id":739540,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cogswell, Charlotte","contributorId":206131,"corporation":false,"usgs":false,"family":"Cogswell","given":"Charlotte","email":"","affiliations":[{"id":37253,"text":"CR Environmental, Inc. 639 Boxberry Hill Road, East Falmouth, MA US 02536","active":true,"usgs":false}],"preferred":false,"id":739541,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739534,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70198084,"text":"70198084 - 2018 - Modeling the distributions of tegu lizards in native and potential invasive ranges","interactions":[],"lastModifiedDate":"2018-07-13T10:13:21","indexId":"70198084","displayToPublicDate":"2018-07-05T00:00:00","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":"Modeling the distributions of tegu lizards in native and potential invasive ranges","docAbstract":"<p>Invasive reptilian predators can have substantial impacts on native species and ecosystems. Tegu lizards are widely distributed in South America east of the Andes, and are popular in the international live animal trade. Two species are established in Florida (U.S.A.) - <i>Salvator merianae</i> (Argentine black and white tegu) and <i>Tupinambis teguixin sensu lato</i> (gold tegu) – and a third has been recorded there—<i> S. rufescens</i> (red tegu). We built species distribution models (SDMs) using 5 approaches (logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy) based on data from the native ranges. We then projected these models to North America to develop hypotheses for potential tegu distributions. Our results suggest that much of the southern United States and northern México probably contains suitable habitat for one or more of these tegu species. <i>Salvator rufescens</i> had higher habitat suitability in semi-arid areas, whereas <i>S. merianae</i> and <i>T. teguixin</i> had higher habitat suitability in more mesic areas. We propose that Florida is not the only state where these taxa could become established, and that early detection and rapid response programs targeting tegu lizards in potentially suitable habitat elsewhere in North America could help prevent establishment and abate negative impacts on native ecosystems.</p>","language":"English","publisher":"Springer","doi":"10.1038/s41598-018-28468-w","usgsCitation":"Jarnevich, C.S., Hayes, M., Fitzgerald, L.A., Yackel, A., Falk, B., Collier, M., Bonewell, L., Klug, P., Naretto, S., and Reed, R., 2018, Modeling the distributions of tegu lizards in native and potential invasive ranges: Scientific Reports, v. 8, e10193; 12 p., https://doi.org/10.1038/s41598-018-28468-w.","productDescription":"e10193; 12 p.","ipdsId":"IP-090713","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468602,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-28468-w","text":"Publisher Index Page"},{"id":437831,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JZZE4W","text":"USGS data release","linkHelpText":"Data for modeling tegu lizard distributions in the Americas"},{"id":355667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"5b6fc418e4b0f5d57878e9e1","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science 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Center","active":true,"usgs":true}],"preferred":true,"id":739940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Falk, Bryan 0000-0002-9690-5626 bfalk@usgs.gov","orcid":"https://orcid.org/0000-0002-9690-5626","contributorId":150075,"corporation":false,"usgs":true,"family":"Falk","given":"Bryan","email":"bfalk@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collier, Michelle 0000-0001-5715-448X","orcid":"https://orcid.org/0000-0001-5715-448X","contributorId":206269,"corporation":false,"usgs":true,"family":"Collier","given":"Michelle","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonewell, Lea","contributorId":206270,"corporation":false,"usgs":true,"family":"Bonewell","given":"Lea","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739943,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Klug, Page 0000-0002-0836-3901","orcid":"https://orcid.org/0000-0002-0836-3901","contributorId":206271,"corporation":false,"usgs":false,"family":"Klug","given":"Page","affiliations":[{"id":37295,"text":"USDA APHIS","active":true,"usgs":false}],"preferred":false,"id":739944,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Naretto, Sergio","contributorId":206272,"corporation":false,"usgs":false,"family":"Naretto","given":"Sergio","email":"","affiliations":[{"id":37296,"text":"Instituto de Diversidad y Ecología Animal","active":true,"usgs":false}],"preferred":false,"id":739945,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739946,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70199208,"text":"70199208 - 2018 - Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim","interactions":[],"lastModifiedDate":"2018-09-10T13:50:22","indexId":"70199208","displayToPublicDate":"2018-07-04T13:50:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3908,"text":"Royal Society Open Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Defining the risk landscape in the context of pathogen pollution: <i>Toxoplasma gondii</i> in sea otters along the Pacific Rim","title":"Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim","docAbstract":"<p><span>Pathogens entering the marine environment as pollutants exhibit a spatial signature driven by their transport mechanisms. The sea otter (</span><i>Enhydra lutris</i><span>), a marine animal which lives much of its life within sight of land, presents a unique opportunity to understand land–sea pathogen transmission. Using a dataset on&nbsp;</span><i>Toxoplasma gondii</i><span>&nbsp;prevalence across sea otter range from Alaska to California, we found that the dominant drivers of infection risk vary depending upon the spatial scale of analysis. At the population level, regions with high&nbsp;</span><i>T. gondii</i><span>&nbsp;prevalence had higher human population density and a greater proportion of human-dominated land uses, suggesting a strong role for population density of the felid definitive host of this parasite. This relationship persisted when a subset of data were analysed at the individual level: large-scale patterns in sea otter&nbsp;</span><i>T. gondii</i><span>&nbsp;infection prevalence were largely explained by individual exposure to areas of high human housing unit density, and other landscape features associated with anthropogenic land use, such as impervious surfaces and cropping land. These results contrast with the small-scale, within-region analysis, in which age, sex and prey choice accounted for most of the variation in infection risk, and terrestrial environmental features provided little variation to help in explaining observed patterns. These results underscore the importance of spatial scale in study design when quantifying both individual-level risk factors and landscape-scale variation in infection risk.</span></p>","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsos.171178","usgsCitation":"Burgess, T.L., Tinker, M.T., Miller, M.A., Bodkin, J.L., Murray, M.J., Saarinen, J.A., Nichol, L.M., Larson, S.E., Conrad, P.A., and Johnson, C., 2018, Defining the risk landscape in the context of pathogen pollution: Toxoplasma gondii in sea otters along the Pacific Rim: Royal Society Open Science, v. 5, Article  171178; 11 p., https://doi.org/10.1098/rsos.171178.","productDescription":"Article  171178; 11 p.","ipdsId":"IP-091756","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468604,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsos.171178","text":"Publisher Index Page"},{"id":357204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.618408203125,\n              34.15272698011818\n            ],\n            [\n              -119.24560546875001,\n              34.15272698011818\n            ],\n            [\n              -119.24560546875001,\n              37.69251435532741\n            ],\n            [\n              -122.618408203125,\n              37.69251435532741\n            ],\n            [\n              -122.618408203125,\n              34.15272698011818\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-04","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f94","contributors":{"authors":[{"text":"Burgess, Tristan L.","contributorId":207772,"corporation":false,"usgs":false,"family":"Burgess","given":"Tristan","email":"","middleInitial":"L.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":744678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":744677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Melissa A.","contributorId":57701,"corporation":false,"usgs":false,"family":"Miller","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":39007,"text":"CA Dept of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":744679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bodkin, James L. 0000-0003-1641-4438 jbodkin@usgs.gov","orcid":"https://orcid.org/0000-0003-1641-4438","contributorId":748,"corporation":false,"usgs":true,"family":"Bodkin","given":"James","email":"jbodkin@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":744680,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, Michael J.","contributorId":206852,"corporation":false,"usgs":false,"family":"Murray","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":37418,"text":"Monterey Bay Aquarium, Monterey, CA","active":true,"usgs":false}],"preferred":false,"id":744681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Saarinen, Justin A.","contributorId":207774,"corporation":false,"usgs":false,"family":"Saarinen","given":"Justin","email":"","middleInitial":"A.","affiliations":[{"id":35150,"text":"New College of Florida","active":true,"usgs":false}],"preferred":false,"id":744682,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nichol, Linda M.","contributorId":207775,"corporation":false,"usgs":false,"family":"Nichol","given":"Linda","email":"","middleInitial":"M.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":744683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Larson, Shawn E.","contributorId":149287,"corporation":false,"usgs":false,"family":"Larson","given":"Shawn","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":744684,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conrad, Patricia A.","contributorId":181937,"corporation":false,"usgs":false,"family":"Conrad","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":744685,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Christine K.","contributorId":23771,"corporation":false,"usgs":false,"family":"Johnson","given":"Christine K.","affiliations":[],"preferred":false,"id":744686,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70213052,"text":"70213052 - 2018 - Discussion of “Shallow water hydro-sediment-morphodynamic equations for fluvial processes” by Zhixian Cao, Chunchen Xia, Gareth Pender, and Qingquan Liu","interactions":[],"lastModifiedDate":"2020-09-08T16:25:27.151806","indexId":"70213052","displayToPublicDate":"2018-07-04T11:21:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2338,"text":"Journal of Hydraulic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Discussion of “Shallow water hydro-sediment-morphodynamic equations for fluvial processes” by Zhixian Cao, Chunchen Xia, Gareth Pender, and Qingquan Liu","docAbstract":"<div class=\"NLM_sec NLM_sec_level_1\"><p>The original paper concerns the formulation and use of depth-integrated equations of motion to model the dynamics of shallow flows that entrain or deposit bed material. A recurring theme of the original paper is the authors’ criticism of related theoretical results published by Iverson and Ouyang (<a class=\"ref showRefEvent\" href=\"https://ascelibrary.org/doi/10.1061/%28ASCE%29HY.1943-7900.0001519#\" data-rid=\"c5\" data-mce-href=\"https://ascelibrary.org/doi/10.1061/%28ASCE%29HY.1943-7900.0001519\">2015</a>). This discussion explains why that criticism is misguided.</p></div>","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)HY.1943-7900.0001519","usgsCitation":"Iverson, R.M., 2018, Discussion of “Shallow water hydro-sediment-morphodynamic equations for fluvial processes” by Zhixian Cao, Chunchen Xia, Gareth Pender, and Qingquan Liu: Journal of Hydraulic Engineering, 07018009, 3 p., https://doi.org/10.1061/(ASCE)HY.1943-7900.0001519.","productDescription":"07018009, 3 p.","ipdsId":"IP-084425","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":378199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":798081,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70198411,"text":"70198411 - 2018 - Survival and cause-specific mortality of translocated female mule deer in southern New Mexico, USA","interactions":[],"lastModifiedDate":"2018-08-03T13:42:31","indexId":"70198411","displayToPublicDate":"2018-07-03T13:42:20","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Survival and cause-specific mortality of translocated female mule deer in southern New Mexico, USA","docAbstract":"<p><strong>Context:<span>&nbsp;</span></strong>Many mule deer (<i>Odocoileus hemionus</i>) populations in New Mexico have failed to recover from previous population declines, while some populations near urban areas have increased, resulting in more frequent human–wildlife conflicts. Translocations were used in an effort to simultaneously reduce an urban mule deer population and augment two low-density populations in south-western New Mexico, USA.</p><p><strong>Aims:<span>&nbsp;</span></strong>Because of insufficient monitoring, the efficacy of many ungulate translocations is unknown. Our goal was to monitor cause-specific mortality and 1 year post-release survival of mule deer translocated during 2013 and 2014. We compared survival rates of mule deer released with a hard- versus soft-release during the 2014 translocation.</p><p><strong>Methods:<span>&nbsp;</span></strong>. We translocated 218 mule deer in 2013 and 2014 into the Peloncillo Mountains (PM) and San Francisco River Valley (SFRV); 106 adult female mule deer were fitted with telemetry collars to determine cause-specific mortality and estimate survival 1 year post-release. All deer were hard-released in 2013. In 2014, translocated mule deer were either held in a soft-release pen (0.81 ha) for approximately 3 weeks or hard-released into their new environment. We used a Kaplan–Meier approach to estimate survival of translocated mule deer at each release area and to compare survival of mule deer translocated using each release method (i.e. hard- versus soft-release).</p><p><strong>Key results:<span>&nbsp;</span></strong>In 2013–14, survival of hard-released deer in the PM was 0.627 (s.e. = 0.09), compared with 0.327 (s.e. = 0.10) in the SFRV. In 2014–15, survival of hard–released deer in the PM was 0.727 (s.e. = 0.13) and survival of soft-released deer was 0.786 (s.e. = 0.11). In the SFRV, survival of hard- and soft-released deer was 0.656 (s.e. = 0.14) and 0.50 (s.e. = 0.16), respectively. Causes of mortality were predation (51%), potential disease (9%; blue tongue or epizootic haemorrhagic disease), accident (5%), poaching (5%) and unknown (20%).</p><p><strong>Conclusions:<span>&nbsp;</span></strong>Translocations can be an effective management tool to augment populations of mule deer while reducing overabundant urban populations. Soft-released mule deer did not have higher survival than hard-released mule deer, although the length and conditions of the acclimation period were limited in our study.</p><p><strong>Implications:<span>&nbsp;</span></strong>Overabundant mule deer populations in urban areas may serve as sources of animals to bolster declining populations. Soft-release pens of smaller size and short period of acclimation did not influence survival.</p>","language":"English","publisher":"CSIRO","doi":"10.1071/WR17173","usgsCitation":"Cain, J.W., Ashling, J.B., and Liley, S., 2018, Survival and cause-specific mortality of translocated female mule deer in southern New Mexico, USA: Wildlife Research, v. 45, no. 4, p. 325-335, https://doi.org/10.1071/WR17173.","productDescription":"11 p.","startPage":"325","endPage":"335","ipdsId":"IP-077616","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","volume":"45","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc418e4b0f5d57878e9e3","contributors":{"authors":[{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":741364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashling, Jana B.","contributorId":206715,"corporation":false,"usgs":false,"family":"Ashling","given":"Jana","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":741542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liley, Stewart","contributorId":171908,"corporation":false,"usgs":false,"family":"Liley","given":"Stewart","affiliations":[],"preferred":false,"id":741543,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70210190,"text":"70210190 - 2018 - Distinguishing Southern Africa precipitation response by strength of El Niño events and implications for decision-making","interactions":[],"lastModifiedDate":"2020-05-20T12:53:17.304468","indexId":"70210190","displayToPublicDate":"2018-07-03T07:46:49","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Distinguishing Southern Africa precipitation response by strength of El Niño events and implications for decision-making","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>December–February precipitation in southern Africa during recent El Niño events is studied by distinguishing circulation and precipitation responses during strong and moderate-to-weak events. We find that while both strong and moderate-to-weak El Niño events tend to dry southern Africa, the pattern and magnitude of precipitation anomalies in the region are different, with strong El Niño events resulting in rainfall deficits often less than −0.88 standardized units and deficits of only about half that for the moderate-to-weak case. Additionally, the likelihood of southern Africa receiving less than climatologic precipitation is approximately 80% for strong El Niño events compared to just over 60% for moderate-to-weak El Niño. Strong El Niño events are found to substantially disrupt onshore moisture transports from the Indian Ocean and increase geopotential heights within the Angola Low. Since El Niño is the most predictable component of the climate system that influences southern Africa precipitation, the information provided by this assessment of the likelihood of dry conditions can serve to benefit early warning systems.</p></div>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/aacc4c","usgsCitation":"Pomposi, C., Funk, C., Shukla, S., and Magadzire, T., 2018, Distinguishing Southern Africa precipitation response by strength of El Niño events and implications for decision-making: Environmental Research Letters, v. 13, no. 7, 074015, 12 p., https://doi.org/10.1088/1748-9326/aacc4c.","productDescription":"074015, 12 p.","ipdsId":"IP-091549","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468605,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aacc4c","text":"Publisher Index Page"},{"id":374953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Southern Africa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              12.6123046875,\n              -35.13787911963418\n            ],\n            [\n              36.2109375,\n              -35.13787911963418\n            ],\n            [\n              36.2109375,\n              -22.471954507739213\n            ],\n            [\n              12.6123046875,\n              -22.471954507739213\n            ],\n            [\n              12.6123046875,\n              -35.13787911963418\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"7","noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Pomposi, Catherine","contributorId":195984,"corporation":false,"usgs":false,"family":"Pomposi","given":"Catherine","email":"","affiliations":[],"preferred":false,"id":789483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":789484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shukla, Shraddhanand","contributorId":224784,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":13549,"text":"UC Santa Barbara Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":789485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Magadzire, Tamuka","contributorId":145822,"corporation":false,"usgs":false,"family":"Magadzire","given":"Tamuka","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":789486,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198857,"text":"70198857 - 2018 - To catch a quake","interactions":[],"lastModifiedDate":"2018-08-24T11:58:34","indexId":"70198857","displayToPublicDate":"2018-07-03T07:34:20","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"To catch a quake","docAbstract":"A revolution in seismic detection technology is underway, capturing unprecedented observations of earthquakes and their impacts. These sensor innovations provide real-time ground shaking observations that could improve emergency response following damaging earthquakes and may advance our understanding of the physics of earthquake ruptures.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-018-04790-9","usgsCitation":"Cochran, E.S., 2018, To catch a quake: Nature Communications, v. 9, Article number: 2508; 4 p., https://doi.org/10.1038/s41467-018-04790-9.","productDescription":"Article number: 2508; 4 p.","ipdsId":"IP-097663","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468606,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-04790-9","text":"Publisher Index Page"},{"id":356677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f96","contributors":{"authors":[{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":743105,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70197980,"text":"fs20183037 - 2018 - Coastal National Elevation Database","interactions":[],"lastModifiedDate":"2018-07-03T12:42:37","indexId":"fs20183037","displayToPublicDate":"2018-07-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3037","title":"Coastal National Elevation Database","docAbstract":"<p>The Coastal National Elevation Database (CoNED) Applications Project develops enhanced topographic (land elevation) and bathymetric (water depth) datasets that serve as valuable resources for coastal hazards research (Danielson and others, 2016; Thatcher and others, 2016). These datasets are used widely for mapping inundation zones from riverine flood events, hurricanes, and sea-level rise and for other Earth science applications, such as sediment transport, erosion, and storm impact models. </p><p>CoNED is a U.S. Geological Survey (USGS) Coastal-Marine Hazards and Resources Program (formerly Coastal and Marine Geology Program) activity centered at the USGS Earth Resources Observation and Science Center and distributed at other USGS Science Centers. As part of the vision for a 3D Nation, the CoNED Project is working collaboratively with the USGS National Geospatial Program, the National Oceanic and Atmospheric Administration, and the U.S. Army Corps of Engineers through the Interagency Working Group on Ocean and Coastal Mapping to build integrated elevation models in the coastal zone by assimilating the land surface topography with littoral zone and continental shelf bathymetry. Several nongovernmental organizations and Federal agencies, including the Department of the Interior Pacific Islands Climate Adaptation Science Center, the National Park Service, the Nature Conservancy, the Louisiana Coastal Protection and Restoration Authority, and numerous academic institutions, partner to make CoNED a success.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183037","usgsCitation":"Danielson, J.J., Poppenga, S.K., Tyler, D.J., Palaseanu-Lovejoy, M., and Gesch, D.B., 2018, Coastal National Elevation Database: U.S. Geological Survey Fact Sheet 2018–3037, 2 p., https://doi.org/10.3133/2018.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-093676","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":355477,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3037/coverthb.jpg"},{"id":355478,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3037/fs20183037.pdf","text":"Report","size":"617 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3037"}],"contact":"<p>Director, <a href=\"https://eros.usgs.gov/\" data-mce-href=\"https://eros.usgs.gov/\">Earth Resources Observation and Science Center</a> &nbsp;<br>U.S. Geological Survey <br>47914 252nd Street&nbsp; <br>Sioux Falls, SD 57198</p>","tableOfContents":"<ul><li>Introduction<br></li><li>Goals and Benefits<br></li><li>CoNED TBDEMs<br></li><li>CoNED Scientific Research<br></li><li>References<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-07-03","noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d07b","contributors":{"authors":[{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":739450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poppenga, Sandra K. 0000-0002-2846-6836 spoppenga@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-6836","contributorId":3327,"corporation":false,"usgs":true,"family":"Poppenga","given":"Sandra","email":"spoppenga@usgs.gov","middleInitial":"K.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":739451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tyler, Dean J. 0000-0002-1542-7539 dtyler@usgs.gov","orcid":"https://orcid.org/0000-0002-1542-7539","contributorId":177897,"corporation":false,"usgs":true,"family":"Tyler","given":"Dean","email":"dtyler@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":739452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":739453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739454,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196994,"text":"ds1087 - 2018 - Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014","interactions":[],"lastModifiedDate":"2018-07-03T12:45:49","indexId":"ds1087","displayToPublicDate":"2018-07-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1087","title":"Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014","docAbstract":"<p>Groundwater-quality data were collected from 502 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program and are included in this report. Most of the wells (500) were sampled from January through December 2015, and 2 of them were sampled in 2013. The data were collected from five types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; and vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic speciation, chromium [VI], and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release. Some data from environmental samples collected in 2013 and quality-control samples collected in 2014 also are included in the associated data release; these data are associated with networks described in this report and have not been published previously.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1087","usgsCitation":"Arnold, T.L., Bexfield, L.M., Musgrove, M., Stackelberg, P.E., Lindsey, B.D., Kingsbury, J.A., Kulongoski, J.T., and Belitz, K., 2018, Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014: U.S. Geological Survey Data Series 1087, 68 p., https://doi.org/10.3133/ds1087.","productDescription":"Report: ix, 67 p.; Data Release","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091701","costCenters":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":355481,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1087/coverthb.jpg"},{"id":355482,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1087/ds1087.pdf","text":"Report","size":"16.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1087"},{"id":355483,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XK8DHK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Datasets from Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January through December 2015 and Previously Unpublished Data from 2013–2014"}],"country":"United States","contact":"<p><a href=\"mailto: dc_il@usgs.gov\" data-mce-href=\"mailto: dc_il@usgs.gov\">Director</a>, <a href=\"https://il.water.usgs.gov\" data-mce-href=\"https://il.water.usgs.gov\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>405 N. Goodwin <br>Urbana, IL 61801<br></p>","tableOfContents":"<ul><li>Foreword<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Purpose and Scope<br></li><li>Groundwater Study Design<br></li><li>Sample Collection and Analysis<br></li><li>Data Reporting<br></li><li>Quality-Assurance and Quality-Control Methods<br></li><li>Groundwater-Quality Data<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix 1. Well Depth and Open Interval by Study Network<br></li><li>Appendix 2. High-Frequency Data from Enhanced Trends Networks<br></li><li>Appendix 3. Quality-Control Data and Analysis<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-07-03","noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d07d","contributors":{"authors":[{"text":"Arnold, Terri 0000-0003-1406-6054 tlarnold@usgs.gov","orcid":"https://orcid.org/0000-0003-1406-6054","contributorId":1598,"corporation":false,"usgs":false,"family":"Arnold","given":"Terri","email":"tlarnold@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":735215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":735216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":197013,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stackelberg, Paul E. 0000-0002-1818-355X pestack@usgs.gov","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":1069,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","email":"pestack@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":434,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce D.","email":"blindsey@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":156272,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739494,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":739495,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70196904,"text":"ofr20181081 - 2018 - U.S. Geological Survey Community for Data Integration 2017 Workshop Proceedings","interactions":[],"lastModifiedDate":"2018-10-24T14:43:27","indexId":"ofr20181081","displayToPublicDate":"2018-07-02T15:50:00","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":"2018-1081","title":"U.S. Geological Survey Community for Data Integration 2017 Workshop Proceedings","docAbstract":"<h1>Executive Summary</h1><p>The U.S. Geological Survey (USGS) Community for Data Integration (CDI) Workshop was held May 16–19, 2017 at the Denver Federal Center. There were 183 in-person attendees and 35 virtual attendees over four days. The theme of the workshop was “Enabling Integrated Science,” with the purpose of bringing together the community to discuss current topics, shared challenges, and steps forward to advance integrated science at the USGS.</p><p>The CDI welcomed several keynote speakers, including Bill Werkheiser, USGS Acting Director; Kevin T. Gallagher, USGS Associate Director of the Core Science Systems Mission Area; Bruce Caron, Earth Science Information Partners Community Architect; and Tim Quinn, Chief of the USGS Office of Enterprise Information. Their presentations focused on the importance of collaborative, cross-disciplinary, and open science and the role of the CDI in identifying and supporting new opportunities in these areas for the USGS and its partners.</p><p>In addition to the stated theme, the workshop agenda was driven by the needs of the CDI, with topics highlighting current resources and technologies that could help attendees in their daily work. Topical sessions were proposed by CDI members and included subjects such as data citation, information technology architecture, legacy data, real-time data, and many more. Plenary speakers from the community talked about USGS activities in data science, elevation and hydrography data integration, advanced scientific computing solutions, cloud computing, data-management training, and data-sharing agreements. Two panels addressed the role of the CDI in enabling integrated science and examples of CDI-supported projects in action.</p><p>Breakout discussions focused on the workshop theme of “Enabling Integrated Science” and covered five topics: Data and Data Integration, Modeling, Computing Capacity, Science Data Integration, and User Needs and Experience. Sessions on each topic identified actions that could bring the USGS and the broader Earth science community closer to the goal of making&nbsp;integrated science commonplace. The breakouts produced recommendations with the broad themes of improving communication&nbsp;and connections across the USGS, reducing duplication and increasing knowledge transfer, increasing training and testbed&nbsp;opportunities to learn and experiment, and creating community-supported standards to enable better integration and interoperability.</p><p>The DataBlast poster and live demonstration session showcased 36 projects from around the CDI and included recent CDI-funded projects as well as other USGS and partner initiatives that were related to data and software integration and discovery.</p><p>Importantly, the CDI workshop provided a forum for scientists, technologists, data and resource managers, program managers, and others to convene face to face to discuss common methods, interests, challenges, and solutions related to scientific data and technologies. As a result of this rare convergence, new connections were made across disciplines, backgrounds, and geographical locations, seeding future activities and collaborations. Sharing of ideas from all attendees was encouraged through the use of a mobile application to collect real-time questions and feedback from the audience</p><p>The primary outcomes of the workshop are the recommendations from the breakout sessions titled “Roadmap Discussions on Enabling Integrated Science” and from the topical sessions detailed in these proceedings. These sessions, as well as the plenary discussions, identified new areas of collaboration and learning that the CDI will facilitate, such as data science, software development, scientific modeling practices, and user needs and experience. The CDI will build on the results of the workshop to guide its future topics, events, and funding opportunities to support an integrated science capacity for the USGS.</p><p>&nbsp;<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181081","usgsCitation":"Hsu, L., Hutchison, V.B., Langseth, M.L., and Wheeler, B., 2018, U.S. Geological Survey Community for Data Integration 2017 Workshop Proceedings: U.S. Geological Survey Open-File Report 2018–1081, 56 p., https://doi.org/10.3133/ofr20181081.","productDescription":"viii, 56 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-092748","costCenters":[{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":355343,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1081/coverthb.jpg"},{"id":355344,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1081/ofr20181081.pdf","text":"Report","size":"5.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1081"}],"contact":"<p><a href=\"https://www.usgs.gov/core-science-systems/csasl?qt-programs_l2_landing_page=0#qt-programs_l2_landing_page\" data-mce-href=\"https://www.usgs.gov/core-science-systems/csasl?qt-programs_l2_landing_page=0#qt-programs_l2_landing_page\">Core Science Analytics, Synthesis, and Library</a><br>U.S. Geological Survey<br>108 National Center<br>12201 Sunrise Valley Drive,<br>Reston, VA 20192<br></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Agenda</li><li>Roadmap Discussions on Enabling Integrated Science</li><li>Presentations and Panels</li><li>Topical Sessions</li><li>Working Group Meetings</li><li>Selected Birds of a Feather Discussion</li><li>Open Lab</li><li>Trainings</li><li>DataBlast</li><li>Summary of Workshop Outcomes</li><li>Acknowledgments</li><li>References</li><li>Appendix 1. Interactive Session Questions and Comments</li><li>Appendix 2. Attendees</li><li>Appendix 3. Community for Data Integration Science Support Framework</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2018-07-02","noUsgsAuthors":false,"publicationDate":"2018-07-02","publicationStatus":"PW","scienceBaseUri":"5b46e545e4b060350a15d07f","contributors":{"authors":[{"text":"Hsu, Leslie 0000-0002-5353-807X lhsu@usgs.gov","orcid":"https://orcid.org/0000-0002-5353-807X","contributorId":191745,"corporation":false,"usgs":true,"family":"Hsu","given":"Leslie","email":"lhsu@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":734967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hutchison, Vivian B. 0000-0001-5301-3698 vhutchison@usgs.gov","orcid":"https://orcid.org/0000-0001-5301-3698","contributorId":5100,"corporation":false,"usgs":true,"family":"Hutchison","given":"Vivian B.","email":"vhutchison@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":734968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langseth, Madison L. 0000-0002-4472-9106 mlangseth@usgs.gov","orcid":"https://orcid.org/0000-0002-4472-9106","contributorId":147810,"corporation":false,"usgs":true,"family":"Langseth","given":"Madison","email":"mlangseth@usgs.gov","middleInitial":"L.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":734969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wheeler, Benjamin 0000-0001-5875-1163 bwheeler@usgs.gov","orcid":"https://orcid.org/0000-0001-5875-1163","contributorId":5949,"corporation":false,"usgs":true,"family":"Wheeler","given":"Benjamin","email":"bwheeler@usgs.gov","affiliations":[],"preferred":true,"id":734970,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199039,"text":"70199039 - 2018 - Real-time nowcasting of microbiological water quality at recreational beaches: A wavelet and artificial neural network-based hybrid modeling approach","interactions":[],"lastModifiedDate":"2018-08-29T15:47:30","indexId":"70199039","displayToPublicDate":"2018-07-02T15:47:12","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":"Real-time nowcasting of microbiological water quality at recreational beaches: A wavelet and artificial neural network-based hybrid modeling approach","docAbstract":"<p><span>The number of beach closings caused by bacterial contamination has continued to rise in recent years, putting beachgoers at risk of exposure to contaminated water. Current approaches predict levels of indicator bacteria using regression models containing a number of explanatory variables. Data-based modeling approaches can supplement routine monitoring data and provide highly accurate short-term forecasts of beach water quality. In this paper, we apply the nonlinear autoregressive network with exogenous inputs (NARX) method with explanatory variables to predict&nbsp;</span><i>Escherichia coli</i><span>&nbsp;concentrations at four Lake Michigan beach sites. We also apply the nonlinear input–output network (NIO) and nonlinear autoregressive neural network (NAR) methods in addition to a hybrid wavelet-NAR (WA-NAR) model and demonstrate their application. All models were tested using 3 months of observed data. Results revealed that the NARX models provided the best performance and that the WA-NAR model, which requires no explanatory variables, outperformed the NIO and NAR models; therefore, the WA-NAR model is suitable for application to data scarce regions. The models proposed in this paper were evaluated using multiple performance metrics, including sensitivity and specificity measures, and produced results comparable or superior to those of previous mechanistic and statistical models developed for the same beach sites. The relatively high&nbsp;</span><i>R</i><sup>2</sup><span>&nbsp;values between data and the NARX models (</span><i>R</i><sup>2</sup><span>&nbsp;values of ∼0.8 for the beach sites and ∼0.9 for the river site) indicate that the new class of models shows promise for beach management.</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.8b01022","usgsCitation":"Zhang, J., Qiu, H., Li, X., Niu, J., Nevers, M., Hu, X., and Phanikumar, M.S., 2018, Real-time nowcasting of microbiological water quality at recreational beaches: A wavelet and artificial neural network-based hybrid modeling approach: Environmental Science & Technology, v. 52, no. 15, p. 8446-8455, https://doi.org/10.1021/acs.est.8b01022.","productDescription":"10 p.","startPage":"8446","endPage":"8455","ipdsId":"IP-094837","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":356935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"15","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-29","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f98","contributors":{"authors":[{"text":"Zhang, Juan","contributorId":207432,"corporation":false,"usgs":false,"family":"Zhang","given":"Juan","email":"","affiliations":[{"id":37539,"text":"Jinan University","active":true,"usgs":false}],"preferred":false,"id":743839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qiu, Han","contributorId":207433,"corporation":false,"usgs":false,"family":"Qiu","given":"Han","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":743840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Xiaoyu","contributorId":207434,"corporation":false,"usgs":false,"family":"Li","given":"Xiaoyu","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":743841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niu, Jie","contributorId":207435,"corporation":false,"usgs":false,"family":"Niu","given":"Jie","email":"","affiliations":[{"id":37539,"text":"Jinan University","active":true,"usgs":false}],"preferred":false,"id":743842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":743838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hu, Xiaonong","contributorId":207436,"corporation":false,"usgs":false,"family":"Hu","given":"Xiaonong","email":"","affiliations":[{"id":37539,"text":"Jinan University","active":true,"usgs":false}],"preferred":false,"id":743843,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Phanikumar, Mantha S.","contributorId":147924,"corporation":false,"usgs":false,"family":"Phanikumar","given":"Mantha","email":"","middleInitial":"S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":743844,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70201402,"text":"70201402 - 2018 - The foraminifera of Chincoteague Bay, Assateague Island, and the surrounding areas: A regional distribution study","interactions":[],"lastModifiedDate":"2025-05-13T18:36:32.220109","indexId":"70201402","displayToPublicDate":"2018-07-02T14:56:15","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2294,"text":"Journal of Foraminiferal Research","active":true,"publicationSubtype":{"id":10}},"title":"The foraminifera of Chincoteague Bay, Assateague Island, and the surrounding areas: A regional distribution study","docAbstract":"<p><span>Foraminiferal census data from Chincoteague Bay, Newport Bay, the salt marshes of Assateague Island, adjacent mainland salt marshes, and the inner-shelf, were assessed to determine the current assemblages in Chincoteague Bay, and how the different environments surrounding the bay, and the gradients within the bay, influence the microfossil distribution. Determining the current background distribution and its drivers allows for future comparisons to determine paleoenvironmental conditions, impacts from natural and anthropogenic pollution, and the influence of climate change. Foraminiferal census data were compared to sedimentological characteristics and environmental parameters, exhibiting strong correlations with salinity, sediment organic content, and grain-size. Foraminiferal distributions exhibited a gradient from an assemblage dominated by&nbsp;</span><i>Elphidium</i><span>&nbsp;cf.&nbsp;</span><i>E. excavatum</i><span>&nbsp;near Chincoteague inlet to an assemblage dominated by&nbsp;</span><i>Ammonia parkinsoniana</i><span>&nbsp;and&nbsp;</span><i>Ammobaculites</i><span>&nbsp;cf.&nbsp;</span><i>Ab. exiguus</i><span>&nbsp;in the more restricted central and northern portions of the bay. The sites closest to the mouth of Trappe Creek in Newport Bay, along the western side of Chincoteague Bay and in the central bay, had a greater relative abundance of dead agglutinated taxa compared with the majority of sites in Chincoteague Bay. Despite the overwhelming dominance of calcareous taxa throughout the bay, dissolution may affect the preservation potential of&nbsp;</span><i>Cribroelphidium poeyanum</i><span>&nbsp;and&nbsp;</span><i>Haynesina germanica</i><span>&nbsp;in the northern and central portions of Chincoteague Bay, as indicated by seasonal pH data. Similarly, the sandy back-barrier lagoonal sites exhibited relatively low densities, potentially a result of dissolution or mechanical destruction.</span></p>","language":"English","publisher":"Cushman Foundation for Foraminiferal Research","doi":"10.2113/gsjfr.48.3.223","usgsCitation":"Ellis, A.M., Shaw, J., Osterman, L.E., and Smith, C.G., 2018, The foraminifera of Chincoteague Bay, Assateague Island, and the surrounding areas: A regional distribution study: Journal of Foraminiferal Research, v. 48, no. 3, p. 223-240, https://doi.org/10.2113/gsjfr.48.3.223.","productDescription":"18 p.","startPage":"223","endPage":"240","ipdsId":"IP-089998","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":360253,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Assateague Island, Chincoteague Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.52825927734375,\n              37.84883250647402\n            ],\n            [\n              -75.07919311523438,\n              37.84883250647402\n            ],\n            [\n              -75.07919311523438,\n              38.31795595794451\n            ],\n            [\n              -75.52825927734375,\n              38.31795595794451\n            ],\n            [\n              -75.52825927734375,\n              37.84883250647402\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"48","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c137dd5e4b006c4f851489a","contributors":{"authors":[{"text":"Ellis, Alisha M. 0000-0002-1785-020X aellis@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-020X","contributorId":192957,"corporation":false,"usgs":true,"family":"Ellis","given":"Alisha","email":"aellis@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaw, Jaimie E.","contributorId":211432,"corporation":false,"usgs":false,"family":"Shaw","given":"Jaimie E.","affiliations":[{"id":25340,"text":"Cherokee Nation Technologies","active":true,"usgs":false}],"preferred":false,"id":754048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osterman, Lisa E. osterman@usgs.gov","contributorId":3058,"corporation":false,"usgs":true,"family":"Osterman","given":"Lisa","email":"osterman@usgs.gov","middleInitial":"E.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754192,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198662,"text":"70198662 - 2018 - On the robustness of N‐mixture models","interactions":[],"lastModifiedDate":"2018-08-14T14:01:30","indexId":"70198662","displayToPublicDate":"2018-07-02T14:01:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"On the robustness of N‐mixture models","docAbstract":"<p><i>N</i><span>‐mixture models provide an appealing alternative to mark–recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the&nbsp;</span><i>N</i><span>‐mixture models: inference is very sensitive to the model's assumptions. We consider the effects of three violations of assumptions that might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness‐of‐fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2362","usgsCitation":"Link, W.A., Schofield, M.R., Barker, R.J., and Sauer, J.R., 2018, On the robustness of N‐mixture models: Ecology, v. 99, no. 7, p. 1547-1551, https://doi.org/10.1002/ecy.2362.","productDescription":"5 p.","startPage":"1547","endPage":"1551","ipdsId":"IP-092400","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":356444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-06","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f9a","contributors":{"authors":[{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":742385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schofield, Matthew R.","contributorId":207010,"corporation":false,"usgs":false,"family":"Schofield","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":37428,"text":"Dept of Math/Stat, University of Otago, New Zealand","active":true,"usgs":false}],"preferred":false,"id":742386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barker, Richard J.","contributorId":207011,"corporation":false,"usgs":false,"family":"Barker","given":"Richard","email":"","middleInitial":"J.","affiliations":[{"id":37428,"text":"Dept of Math/Stat, University of Otago, New Zealand","active":true,"usgs":false}],"preferred":false,"id":742387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":742388,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199447,"text":"70199447 - 2018 - Inferring presence of the western toad (Anaxyrus boreas) species complex using environmental DNA","interactions":[],"lastModifiedDate":"2018-09-18T13:28:26","indexId":"70199447","displayToPublicDate":"2018-07-02T13:28:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Inferring presence of the western toad (<i>Anaxyrus boreas</i>) species complex using environmental DNA","title":"Inferring presence of the western toad (Anaxyrus boreas) species complex using environmental DNA","docAbstract":"<p><span>Western toads&nbsp;(species complex comprised of&nbsp;</span><i>Anaxyrus boreas</i><span>,&nbsp;</span><i>A. canorus</i><span>,&nbsp;</span><i>A. exsul</i><span>, and&nbsp;</span><span>A.&nbsp;<i>nelsoni</i></span><span>) are widely distributed in the western United States but are declining, particularly in the southeastern extent of their range. The&nbsp;subspecies&nbsp;</span><i>A. b. boreas</i><span>&nbsp;is listed as a Species of Greatest Conservation Need in New Mexico, Colorado, Utah, and Wyoming. Reliable and sensitive methods for delineating distributions of western toads are critical for monitoring the status of the species and prioritizing conservation efforts. We developed two qPCR assays for detecting western toad&nbsp;DNA&nbsp;in environmental DNA samples. Both markers efficiently and reliably detect low concentrations of western toad DNA across their range in the conterminous U. S. without detecting non-target, sympatric species. To determine the optimal annual sampling period, we then tested these markers using repeated sampling in ponds where western toads were known to be present. Quantities of collected eDNA varied widely across samples, but sample-level detections across sites exceeded 80% for June sampling. In the later summer, detection dropped off sharply with only a single detection in the ten samples collected throughout August.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2018.e00438","usgsCitation":"Franklin, T.W., Dysthe, J.C., Golden, M., McKelvey, K.S., Hossack, B.R., Carim, K.J., Tait, C., Young, M.K., and Schwartz, M.K., 2018, Inferring presence of the western toad (Anaxyrus boreas) species complex using environmental DNA: Global Ecology and Conservation, v. 15, p. 1-9, https://doi.org/10.1016/j.gecco.2018.e00438.","productDescription":"e00438; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-096364","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2018.e00438","text":"Publisher Index Page"},{"id":357435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02fd7e4b0fc368eb5398d","contributors":{"authors":[{"text":"Franklin, Thomas W.","contributorId":207966,"corporation":false,"usgs":false,"family":"Franklin","given":"Thomas","email":"","middleInitial":"W.","affiliations":[{"id":37672,"text":"1United States Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, 800 East Beckwith Ave., Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":745359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dysthe, Joseph C.","contributorId":207967,"corporation":false,"usgs":false,"family":"Dysthe","given":"Joseph","email":"","middleInitial":"C.","affiliations":[{"id":37672,"text":"1United States Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, 800 East Beckwith Ave., Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":745360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golden, Michael","contributorId":207968,"corporation":false,"usgs":false,"family":"Golden","given":"Michael","email":"","affiliations":[{"id":37673,"text":"United States Department of Agriculture, Forest Service, Dixie National Forest, 1789 N Wedgewood Ln, Cedar City UT","active":true,"usgs":false}],"preferred":false,"id":745361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKelvey, Kevin S.","contributorId":207969,"corporation":false,"usgs":false,"family":"McKelvey","given":"Kevin","email":"","middleInitial":"S.","affiliations":[{"id":37674,"text":"United States Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, 800 East Beckwith Ave., Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":745362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":745358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carim, Kellie J.","contributorId":207971,"corporation":false,"usgs":false,"family":"Carim","given":"Kellie","email":"","middleInitial":"J.","affiliations":[{"id":37672,"text":"1United States Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, 800 East Beckwith Ave., Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":745365,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tait, Cynthia","contributorId":207970,"corporation":false,"usgs":false,"family":"Tait","given":"Cynthia","email":"","affiliations":[{"id":37675,"text":"4United States Department of Agriculture, Forest Service, Intermountain Region, 324 25th Street, Ogden, UT","active":true,"usgs":false}],"preferred":false,"id":745364,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Young, Michael K.","contributorId":177836,"corporation":false,"usgs":false,"family":"Young","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":745363,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schwartz, Michael K.","contributorId":199035,"corporation":false,"usgs":false,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":745366,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70198336,"text":"70198336 - 2018 - Duck nest depredation, predator behavior, and female response using video","interactions":[],"lastModifiedDate":"2018-07-31T08:58:55","indexId":"70198336","displayToPublicDate":"2018-07-02T08:58:49","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Duck nest depredation, predator behavior, and female response using video","docAbstract":"<p><span>Depredation plays an important role in determining duck nest success and predator and female duck behavior during nest depredation can influence nest fate. We examined depredation of mallard (</span><i>Anas platyrhynchos</i><span>) and gadwall (</span><i>A. strepera</i><span>) nests in Suisun Marsh, California, USA, in 2015–2016 with continuous infrared video monitoring to identify nest predators and characterize predator and female duck behavior during depredation events. We recorded predators at 44% of 147 nests monitored. Raccoons (</span><i>Procyon lotor</i><span>) were the most frequent predator observed at nests (40% of nests visited and 53% of depredated eggs) followed by striped skunks (</span><i>Mephitis mephitis</i><span>; 27% and 27%), coyotes (</span><i>Canis latrans</i><span>; 4% and 9%), common ravens (</span><i>Corvus corax</i><span>; 4% and 9%), gopher snakes (</span><i>Pituophis catenifer catenifer</i><span>; 19% and 0%), and western yellow‐bellied racers (</span><i>Coluber constrictor mormon</i><span>; 1% and 0%). The number of eggs depredated per depredation bout varied among predators (raccoons: 7.3 eggs; skunks: 2.5; coyotes: 7.4; ravens: 7.7; and snakes: 0.0). Mammal depredation occurred between 1600 and 0400, whereas snakes and ravens were observed at nests during the day (snakes: 1000–2100; ravens: 1700). Females flushed from nests immediately before predator arrival (</span><img class=\"section_image\" src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/8d5db5c1-f39d-4217-8898-1b8d1b4b51f9/jwmg21444-math-0001.png\" alt=\"urn:x-wiley:14381656:media:jwmg21444:jwmg21444-math-0001\" data-mce-src=\"https://wol-prod-cdn.literatumonline.com/cms/attachment/8d5db5c1-f39d-4217-8898-1b8d1b4b51f9/jwmg21444-math-0001.png\"><span> = 29.0 ± 16.6 [SD] sec), and this timing did not vary among predators. However, the length of nest depredation bouts varied among predators. Nest visits by gopher snakes were longer (18.6 ± 19.4 min) than depredation bouts by other predators (12.3 ± 10.7 min), but snakes did not successfully consume any eggs. Females took more time to return to nests when nests were depredated by raccoons (239 ± 137 min), whereas females returned more quickly when nests were visited by skunks (81 ± 163 min) or gopher snakes (15 ± 128 min). Partial clutch depredation occurred at 15% of depredated nests, but only 23% of partially depredated nests successfully hatched ≥1 egg. Our results indicate that predator type and behavior can influence female behavior and nest fate, and that management actions that reduce the effectiveness of raccoons and skunks encountering waterfowl nests may benefit these nesting populations.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21444","usgsCitation":"Croston, R., Ackerman, J., Herzog, M.P., Kohl, J.D., Hartman, C.A., Peterson, S.H., Overton, C.T., Feldheim, C.L., and Casazza, M.L., 2018, Duck nest depredation, predator behavior, and female response using video: Journal of Wildlife Management, v. 82, no. 5, p. 1014-1025, https://doi.org/10.1002/jwmg.21444.","productDescription":"12 p.","startPage":"1014","endPage":"1025","ipdsId":"IP-088484","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":356018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-08","publicationStatus":"PW","scienceBaseUri":"5b6fc418e4b0f5d57878e9e5","contributors":{"authors":[{"text":"Croston, Rebecca 0000-0003-4696-0878","orcid":"https://orcid.org/0000-0003-4696-0878","contributorId":206560,"corporation":false,"usgs":true,"family":"Croston","given":"Rebecca","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":741092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kohl, Jeffrey D. 0000-0003-0921-7460","orcid":"https://orcid.org/0000-0003-0921-7460","contributorId":206562,"corporation":false,"usgs":true,"family":"Kohl","given":"Jeffrey","email":"","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131109,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":741097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741098,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741099,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Feldheim, Cliff L.","contributorId":206561,"corporation":false,"usgs":false,"family":"Feldheim","given":"Cliff","email":"","middleInitial":"L.","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":741095,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741100,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70259745,"text":"70259745 - 2018 - Alaska Volcano Observatory alert and forecasting timeliness: 1989–2017","interactions":[],"lastModifiedDate":"2024-10-23T11:37:30.603843","indexId":"70259745","displayToPublicDate":"2018-07-02T06:34:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17169,"text":"Frontiers in Earth Science - Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Alaska Volcano Observatory alert and forecasting timeliness: 1989–2017","docAbstract":"<div class=\"JournalAbstract\"><p>The Alaska Volcano Observatory (AVO) monitors volcanoes in Alaska and issues notifications and warnings of volcanic unrest and eruption. We evaluate the timeliness and accuracy of eruption forecasts for 53 eruptions at 20 volcanoes, beginning with Mount Redoubt's 1989–1990 eruption. Successful forecasts are defined as those where AVO issued a formal warning before eruption onset. These warning notifications are now part of AVO's Aviation Color Code and Volcanic Alert Level. This analysis considers only the start of an eruption, although many eruptions have multiple phases of activity. For the 21 eruptions at volcanoes with functioning local seismic networks, AVO has high forecasting success at volcanoes with: &gt;15 years repose intervals and magmatic eruptions (4 out of 4, 100%); or larger eruptions (Volcanic Explosivity Index (VEI) 3 or greater; 6 out of 10, 60%). Therefore, AVO successfully forecast all four monitored, longer-repose period, VEI 3+ eruptions: Redoubt 1989–1990 and 2009, Spurr 1992, and Augustine 2005–2006. For volcanoes with functioning seismic monitoring networks, success rates are lower for: volcanoes with shorter repose periods (3 out of 16, 19%); more mafic compositions (3 out of 18, 17%); or smaller eruption size (VEI 2 or less, 1 out of 11, 9%). These eruptions (Okmok, Pavlof, Veniaminof, and Shishaldin) often lack detectable precursory signals. For 32 eruptions at volcanoes without functioning local seismic networks, the forecasting success rate is much lower (2, 6%; Kasatochi 2008 and Shishaldin 2014). For remote volcanoes where the main hazard is to aviation, rapid detection is a goal in the absence of<span>&nbsp;</span><i>in situ</i><span>&nbsp;</span>monitoring. Eruption detection has improved in recent years, shown by a decrease in the time between eruption onset and notification. Even limited seismic monitoring can detect precursory activity at volcanoes with certain characteristics (intermediate composition, longer repose times, larger eruptions), but difficulty persists in detecting subtle precursory activity at frequently active volcanoes with more mafic compositions. This suggests that volcano-specific characteristics should be considered when designing monitoring programs and evaluating forecasting success. More proximally-located sensors and data types are likely needed to forecast eruptive activity at frequently-active, more mafic volcanoes that generally produce smaller eruptions.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2018.00086","usgsCitation":"Cameron, C., Prejean, S., Coombs, M.L., Wallace, K.L., Power, J., and Roman, D., 2018, Alaska Volcano Observatory alert and forecasting timeliness: 1989–2017: Frontiers in Earth Science - Volcanology, v. 6, 86, 16 p., https://doi.org/10.3389/feart.2018.00086.","productDescription":"86, 16 p.","ipdsId":"IP-095805","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468608,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2018.00086","text":"Publisher Index Page"},{"id":463113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -179.0050499667423,\n              50.8246967104881\n            ],\n            [\n              -160.54801871674235,\n              53.62315970952906\n            ],\n            [\n              -146.83708121674246,\n              59.69382332205734\n            ],\n            [\n              -148.50700309174243,\n              62.16910742042111\n            ],\n            [\n              -153.25309684174235,\n              61.714365562658\n            ],\n            [\n              -159.22965934174232,\n              58.79497961948812\n            ],\n            [\n              -162.0421593417424,\n              57.21189226650853\n            ],\n            [\n              -172.0616905917424,\n              54.50005217383722\n            ],\n            [\n              -179.53239371674232,\n              53.30923541769238\n            ],\n            [\n              -183.48747184174235,\n              52.674403054105795\n            ],\n            [\n              -183.48747184174235,\n              51.70458578993842\n            ],\n            [\n              -182.2570030917423,\n              51.04624916082764\n            ],\n            [\n              -179.0050499667423,\n              50.8246967104881\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Cameron, Cheryl","contributorId":345428,"corporation":false,"usgs":false,"family":"Cameron","given":"Cheryl","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":916578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prejean, Stephanie G. 0000-0003-0510-1989 sprejean@usgs.gov","orcid":"https://orcid.org/0000-0003-0510-1989","contributorId":172404,"corporation":false,"usgs":true,"family":"Prejean","given":"Stephanie","email":"sprejean@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916581,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Power, John 0000-0002-7233-4398","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":215240,"corporation":false,"usgs":true,"family":"Power","given":"John","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916582,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roman, Diana C.","contributorId":345429,"corporation":false,"usgs":false,"family":"Roman","given":"Diana C.","affiliations":[{"id":30217,"text":"Carnegie Institution for Science","active":true,"usgs":false}],"preferred":false,"id":916583,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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