{"pageNumber":"877","pageRowStart":"21900","pageSize":"25","recordCount":184904,"records":[{"id":70205206,"text":"70205206 - 2018 - Reproductive frequency and size-dependence of fecundity in the Giant Gartersnake (Thamnophis gigas)","interactions":[],"lastModifiedDate":"2019-09-06T10:21:06","indexId":"70205206","displayToPublicDate":"2018-04-30T10:19:21","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Reproductive frequency and size-dependence of fecundity in the Giant Gartersnake (<i>Thamnophis gigas</i>)","title":"Reproductive frequency and size-dependence of fecundity in the Giant Gartersnake (Thamnophis gigas)","docAbstract":"<p>How reproductive output changes with age or size is a key life-history trait that can affect which&nbsp;demographic rates most influence population growth. Although many studies have investigated the reproductive&nbsp;ecology of gartersnakes, we know little about reproduction in the threatened Giant Gartersnake, <i>Thamnophis&nbsp;gigas</i>. We used X-radiography to determine reproductive status and estimated fecundity for 73 female <i>T. gigas</i>&nbsp;collected from several regions within the range of this species in the Sacramento Valley of California, USA, and&nbsp;synthesize these data with data from litters born in captivity to improve our understanding of reproduction in this&nbsp;species. Average total litter size determined from X-rays (15.9) and captive-born litters (15.5) are within the ranges&nbsp;reported from other gartersnakes, but captive-born litters had high rates of stillbirth. Only 154 of 202 neonates&nbsp;from captive snakes were born alive, and seven of 13 litters contained at least one stillborn neonate. We found&nbsp;that fecundity was positively related to maternal snout-vent length, and some evidence that larger litters contained&nbsp;smaller neonates. The proportion of X-rayed females that were gravid was 0.50 in 2014, 0.47 in and 2015, and&nbsp;0.64 in 2016. Central California experienced an exceptional drought from 2012–2015, which may have affected&nbsp;the reproductive output and frequency of <i>T.&nbsp; gigas</i>. Our estimates of reproductive frequency and size-dependent&nbsp;fecundity in <i>T. gigas</i> provide valuable information that can be used in demographic models of this threatened&nbsp;species. Our results demonstrate that X-radiography is a useful, minimally invasive means to study fecundity in&nbsp;wild populations of snakes.</p>","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Rose, J.P., Ersan, J., Wylie, G., Casazza, M.L., and Halstead, B., 2018, Reproductive frequency and size-dependence of fecundity in the Giant Gartersnake (Thamnophis gigas): Herpetological Conservation and Biology, v. 13, no. 1, p. 80-90.","productDescription":"11 p.","startPage":"80","endPage":"90","ipdsId":"IP-087900","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":367252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367242,"type":{"id":15,"text":"Index Page"},"url":"https://herpconbio.org/contents_vol13_issue1.html"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.354736328125,\n              38.37611542403604\n            ],\n            [\n              -120.69580078125001,\n              38.37611542403604\n            ],\n            [\n              -120.69580078125001,\n              39.85072092501597\n            ],\n            [\n              -122.354736328125,\n              39.85072092501597\n            ],\n            [\n              -122.354736328125,\n              38.37611542403604\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":770354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ersan, Julia 0000-0002-1549-7561","orcid":"https://orcid.org/0000-0002-1549-7561","contributorId":218034,"corporation":false,"usgs":true,"family":"Ersan","given":"Julia","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":770355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Glenn D. 0000-0002-7061-6658","orcid":"https://orcid.org/0000-0002-7061-6658","contributorId":207594,"corporation":false,"usgs":false,"family":"Wylie","given":"Glenn D.","affiliations":[],"preferred":false,"id":770357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":770356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":770353,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196760,"text":"70196760 - 2018 - Associations between urban sprawl and life expectancy in the United States","interactions":[],"lastModifiedDate":"2018-04-30T13:10:32","indexId":"70196760","displayToPublicDate":"2018-04-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2041,"text":"International Journal of Environmental Research and Public Health","active":true,"publicationSubtype":{"id":10}},"title":"Associations between urban sprawl and life expectancy in the United States","docAbstract":"<p><span>In recent years, the United States has had a relatively poor performance with respect to life expectancy compared to the other developed nations. Urban sprawl is one of the potential causes of the high rate of mortality in the United States. This study investigated cross-sectional associations between sprawl and life expectancy for metropolitan counties in the United States in 2010. In this study, the measure of life expectancy in 2010 came from a recently released dataset of life expectancies by county. This study modeled average life expectancy with a structural equation model that included five mediators: annual vehicle miles traveled (VMT) per household, average body mass index, crime rate, and air quality index as mediators of sprawl, as well as percentage of smokers as a mediator of socioeconomic status. After controlling for sociodemographic characteristics, this study found that life expectancy was significantly higher in compact counties than in sprawling counties. Compactness affects mortality directly, but the causal mechanism is unclear. For example, it may be that sprawling areas have higher traffic speeds and longer emergency response times, lower quality and less accessible health care facilities, or less availability of healthy foods. Compactness affects mortality indirectly through vehicle miles traveled, which is a contributor to traffic fatalities, and through body mass index, which is a contributor to many chronic diseases. This study identified significant direct and indirect associations between urban sprawl and life expectancy. These findings support further research and practice aimed at identifying and implementing changes to urban planning designed to support health and healthy behaviors.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/ijerph15050861","usgsCitation":"Hamidi, S., Ewing, R., Tatalovich, Z., Grace, J.B., and Berrigan, D., 2018, Associations between urban sprawl and life expectancy in the United States: International Journal of Environmental Research and Public Health, v. 15, no. 5, p. 1-11, https://doi.org/10.3390/ijerph15050861.","productDescription":"Article 861; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-056461","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468802,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ijerph15050861","text":"Publisher Index Page"},{"id":353857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-26","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe24","contributors":{"authors":[{"text":"Hamidi, Shima","contributorId":204538,"corporation":false,"usgs":false,"family":"Hamidi","given":"Shima","email":"","affiliations":[{"id":12734,"text":"University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":734278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ewing, Reid","contributorId":204537,"corporation":false,"usgs":false,"family":"Ewing","given":"Reid","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":734277,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tatalovich, Zaria","contributorId":204539,"corporation":false,"usgs":false,"family":"Tatalovich","given":"Zaria","email":"","affiliations":[{"id":36952,"text":"National Cancer Institute, NIH","active":true,"usgs":false}],"preferred":false,"id":734279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":734276,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berrigan, David","contributorId":204540,"corporation":false,"usgs":false,"family":"Berrigan","given":"David","email":"","affiliations":[{"id":36952,"text":"National Cancer Institute, NIH","active":true,"usgs":false}],"preferred":false,"id":734280,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70197481,"text":"70197481 - 2018 - Biology and impacts of Pacific Islands invasive species. 14. Sus scrofa the feral pig (Artiodactyla: Suidae)","interactions":[],"lastModifiedDate":"2018-06-06T16:21:37","indexId":"70197481","displayToPublicDate":"2018-04-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2990,"text":"Pacific Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Biology and impacts of Pacific Islands invasive species. 14. <i>Sus scrofa</i> the feral pig (Artiodactyla: Suidae)","title":"Biology and impacts of Pacific Islands invasive species. 14. Sus scrofa the feral pig (Artiodactyla: Suidae)","docAbstract":"<p><span>Feral pigs (</span><i>Sus scrofa</i><span><span>&nbsp;</span>L.) are perhaps the most abundant, widespread, and economically significant large introduced vertebrate across the Pacific island region. Unlike many other nonnative invasive species, feral pigs have both cultural and recreational importance in the region, complicating their management. Today, Pacific island feral pigs are a mixture of several strains of domestic swine, Asiatic wild boar, and European wild boar. Due to their generalist diet and rooting behavior, feral pigs alter soils and watersheds and negatively impact native and nonnative flora and fauna. As a result, feral pigs have played a role in the extinction of several species of plants and animals on Pacific islands and have negative effects on both ecotourism and agricultural industries in the region. Despite numerous published studies on feral pigs in the Pacific island region, of which the majority include systematic analyses of original empirical data, some fundamental aspects of feral pig ecology remain poorly characterized, at least partly due to the remote and inaccessible environments that they often inhabit. To address these knowledge gaps, effort should be made to integrate research conducted outside the Pacific island region into local management strategies. This review summarizes the origins, history, ecology, environmental effects, and current management of feral pigs in the Pacific island region; integrates regional scientific findings with those of other insular and continental systems; and identifies current knowledge gaps requiring further research to inform the ecology and management of this impactful invasive species.</span></p>","language":"English ","publisher":"University of Hawai'i Press","doi":"10.2984/72.2.1","usgsCitation":"Wehr, N., Hess, S.C., and Litton, C.M., 2018, Biology and impacts of Pacific Islands invasive species. 14. Sus scrofa the feral pig (Artiodactyla: Suidae): Pacific Science, v. 72, no. 2, p. 177-198, https://doi.org/10.2984/72.2.1.","productDescription":"22 p.","startPage":"177","endPage":"198","numberOfPages":"22","ipdsId":"IP-080121","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":354773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Pacific Islands","volume":"72","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e58ee4b060350a15d1da","contributors":{"authors":[{"text":"Wehr, Nathaniel H. ","contributorId":205455,"corporation":false,"usgs":false,"family":"Wehr","given":"Nathaniel H. ","affiliations":[{"id":33542,"text":"Department of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":737354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hess, Steven C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":3156,"corporation":false,"usgs":true,"family":"Hess","given":"Steven","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":737352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Litton, Creighton M.","contributorId":58534,"corporation":false,"usgs":true,"family":"Litton","given":"Creighton","email":"","middleInitial":"M.","affiliations":[{"id":34391,"text":"Department of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, Hawaii 96822","active":true,"usgs":false}],"preferred":false,"id":737353,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70197755,"text":"70197755 - 2018 - The widespread influence of Great Lakes microseisms across the United States revealed by the 2014 polar vortex","interactions":[],"lastModifiedDate":"2018-06-19T16:38:07","indexId":"70197755","displayToPublicDate":"2018-04-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The widespread influence of Great Lakes microseisms across the United States revealed by the 2014 polar vortex","docAbstract":"<p><span>During the winter of 2014, a weak polar vortex brought record cold temperatures to the north‐central (“Midwest”) United States, and the Great Lakes reached the highest extent of ice coverage (92.5%) since 1979. This event shut down the generation of seismic signals caused by wind‐driven wave action within the lakes (termed “lake microseisms”), giving an unprecedented opportunity to isolate and characterize these novel signals through comparison with nonfrozen time periods. Using seismic records at 72 broadband stations, we observe Great Lakes microseism signals at distances &gt;300&nbsp;km from the lakes. In contrast to conventional oceanic microseisms, there is no clear relationship between the frequency content of the seismic signals (observed from ~0.5–5‐s period) and the dominant swell period or resonance periods of the lakes based on their bathymetric profiles. Thus, the exact generation mechanism is not readily explained by conventional microseism theory and warrants further investigation.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL076690","usgsCitation":"Anthony, R.E., Ringler, A.T., and Wilson, D.C., 2018, The widespread influence of Great Lakes microseisms across the United States revealed by the 2014 polar vortex: Geophysical Research Letters, v. 45, no. 8, p. 3436-3444, https://doi.org/10.1002/2017GL076690.","productDescription":"9 p.","startPage":"3436","endPage":"3444","ipdsId":"IP-095199","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468803,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gl076690","text":"Publisher Index Page"},{"id":355175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Great Lakes","volume":"45","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-20","publicationStatus":"PW","scienceBaseUri":"5b46e58fe4b060350a15d1dc","contributors":{"authors":[{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738395,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70195291,"text":"ofr20181010 - 2018 - Laboratory observations of artificial sand and oil agglomerates","interactions":[],"lastModifiedDate":"2018-04-30T10:54:20","indexId":"ofr20181010","displayToPublicDate":"2018-04-27T15:45:00","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":"2018-1010","title":"Laboratory observations of artificial sand and oil agglomerates","docAbstract":"<p><span>Sand and oil agglomerates (SOAs) form when weathered oil reaches the surf zone and combines with suspended sediments. The presence of large SOAs in the form of thick mats (up to 10 centimeters [cm] in height and up to 10 square meters [m</span><sup>2</sup><span>] in area) and smaller SOAs, sometimes referred to as surface residual balls (SRBs), may lead to the re-oiling of beaches previously affected by an oil spill. A limited number of numerical modeling and field studies exist on the transport and dynamics of centimeter-scale SOAs and their interaction with the sea floor. Numerical models used to study SOAs have relied on shear-stress formulations to predict incipient motion. However, uncertainty exists as to the accuracy of applying these formulations, originally developed for sand grains in a uniformly sorted sediment bed, to larger, nonspherical SOAs. In the current effort, artificial sand and oil agglomerates (aSOAs) created with the size, density, and shape characteristics of SOAs were studied in a small-oscillatory flow tunnel. These experiments expanded the available data on SOA motion and interaction with the sea floor and were used to examine the applicability of shear-stress formulations to predict SOA mobility. Data collected during these two sets of experiments, including photographs, video, and flow velocity, are presented in this report, along with an analysis of shear-stress-based formulations for incipient motion. The results showed that shear-stress thresholds for typical quartz sand predicted the incipient motion of aSOAs with 0.5–1.0-cm diameters, but were inaccurate for aSOAs with larger diameters (&gt;2.5 cm). This finding implies that modified parameterizations of incipient motion may be necessary under certain combinations of aSOA characteristics and environmental conditions.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181010","usgsCitation":"Jenkins, R.L., Dalyander, P.S., Penko, Allison, and Long, J.W., 2018, Laboratory observations of artificial sand and oil agglomerates: U.S. Geological Survey Open-File Report 2018&ndash;1010, https://doi.org/10.3133/ofr20181010.","productDescription":"HTML","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079703","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353721,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1010","text":"Report HTML"},{"id":353720,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1010/coverthb2.jpg"}],"contact":"<p>Director, <a href=\"https://coastal.er.usgs.gov\" data-mce-href=\"https://coastal.er.usgs.gov\">St. Petersburg Coastal and Marine Science Center</a><br> U.S. Geological Survey<br> 600 4th Street South<br> St. Petersburg, FL 33701</p>","tableOfContents":"<ul><li>Abstract</li><li>List of Figures</li><li>List of Tables</li><li>Supplemental Information</li><li>Abbreviations</li><li>Introduction</li><li>Experimental Setup</li><li>Data Processing</li><li>Data Catalog</li><li>Results</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2018-04-27","noUsgsAuthors":false,"publicationDate":"2018-04-27","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe26","contributors":{"authors":[{"text":"Jenkins, Robert L. III 0000-0003-2078-4618","orcid":"https://orcid.org/0000-0003-2078-4618","contributorId":202181,"corporation":false,"usgs":true,"family":"Jenkins","given":"Robert L.","suffix":"III","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":727763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":141015,"corporation":false,"usgs":true,"family":"Dalyander","given":"P.","email":"sdalyander@usgs.gov","middleInitial":"Soupy","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":727764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Penko, Allison","contributorId":191932,"corporation":false,"usgs":false,"family":"Penko","given":"Allison","affiliations":[],"preferred":false,"id":727766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Long, Joseph W. 0000-0003-2912-1992","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":202183,"corporation":false,"usgs":true,"family":"Long","given":"Joseph W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":727765,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196038,"text":"sir20185042 - 2018 - A metabolism-based whole lake eutrophication model to estimate the magnitude and time scales of the effects of restoration in Upper Klamath Lake, south-central Oregon","interactions":[],"lastModifiedDate":"2018-04-30T11:11:57","indexId":"sir20185042","displayToPublicDate":"2018-04-27T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5042","title":"A metabolism-based whole lake eutrophication model to estimate the magnitude and time scales of the effects of restoration in Upper Klamath Lake, south-central Oregon","docAbstract":"<p class=\"p1\">A whole lake eutrophication (WLE) model approach for phosphorus and cyanobacterial biomass in Upper Klamath Lake, south-central Oregon, is presented here. The model is a successor to a previous model developed to inform a Total Maximum Daily Load (TMDL) for phosphorus in the lake, but is based on net primary production (NPP), which can be calculated from dissolved oxygen, rather than scaling up a small-scale description of cyanobacterial growth and respiration rates. This phase 3 WLE model is a refinement of the proof-of-concept developed in phase 2, which was the first attempt to use NPP to simulate cyanobacteria in the TMDL model. The calibration of the calculated NPP WLE model was successful, with performance metrics indicating a good fit to calibration data, and the calculated NPP WLE model was able to simulate mid-season bloom decreases, a feature that previous models could not reproduce.</p><p class=\"p1\">In order to use the model to simulate future scenarios based on phosphorus load reduction, a multivariate regression model was created to simulate NPP as a function of the model state variables (phosphorus and chlorophyll <i>a</i>) and measured meteorological and temperature model inputs. The NPP time series was split into a low- and high-frequency component using wavelet analysis, and regression models were fit to the components separately, with moderate success.</p><p class=\"p1\">The regression models for NPP were incorporated in the WLE model, referred to as the “scenario” WLE (SWLE), and the fit statistics for phosphorus during the calibration period were mostly unchanged. The fit statistics for chlorophyll <i>a</i>, however, were degraded. These statistics are still an improvement over prior models, and indicate that the SWLE is appropriate for long-term predictions even though it misses some of the seasonal variations in chlorophyll <i>a</i>.</p><p class=\"p1\">The complete whole lake SWLE model, with multivariate regression to predict NPP, was used to make long-term simulations of the response to 10-, 20-, and 40-percent reductions in tributary nutrient loads. The long-term mean water column concentration of total phosphorus was reduced by 9, 18, and 36 percent, respectively, in response to these load reductions. The long-term water column chlorophyll <i>a </i>concentration was reduced by 4, 13, and 44 percent, respectively. The adjustment to a new equilibrium between the water column and sediments occurred over about 30 years.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185042","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Wherry, S.A., and Wood, T.M., 2018, A metabolism-based whole lake eutrophication model to estimate the magnitude and time scales of the effects of restoration in Upper Klamath Lake, south-central Oregon: U.S. Geological Survey Scientific Investigations Report 2018–5042, 43 p., https:/doi.org/10.3133/sir20185042.","productDescription":"vii, 43 p.","onlineOnly":"Y","ipdsId":"IP-081297","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":353789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5042/coverthb.jpg"},{"id":353790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5042/sir20185042.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5042"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.10273742675781,\n              42.22750046697999\n            ],\n            [\n              -121.79374694824219,\n              42.22750046697999\n            ],\n            [\n              -121.79374694824219,\n              42.595554553719204\n            ],\n            [\n              -122.10273742675781,\n              42.595554553719204\n            ],\n            [\n              -122.10273742675781,\n              42.22750046697999\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/or-water\" target=\"blank\" data-mce-href=\"https://www.usgs.gov/centers/or-water\">Oregon Water Science Center</a><br> U.S. Geological Survey<br> 2130 SW 5th Avenue<br> Portland, Oregon 97201</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Significant Findings<br></li><li>Introduction<br></li><li>Datasets<br></li><li>Whole Lake Eutrophication Model for Simulating Historical Conditions<br></li><li>Multivariate Regression Model of Net Primary Production<br></li><li>Whole Lake Eutrophication Model for Simulating Future Conditions<br></li><li>Implications of Model Results for Restoration<br></li><li>Summary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-04-27","noUsgsAuthors":false,"publicationDate":"2018-04-27","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe2e","contributors":{"authors":[{"text":"Wherry, Susan A. 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":4952,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":731093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Tamara M. 0000-0001-6057-8080 tmwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6057-8080","contributorId":1164,"corporation":false,"usgs":true,"family":"Wood","given":"Tamara","email":"tmwood@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731094,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196723,"text":"70196723 - 2018 - Modeling and simulation of emergent behavior in transportation infrastructure restoration","interactions":[],"lastModifiedDate":"2018-04-27T13:58:56","indexId":"70196723","displayToPublicDate":"2018-04-27T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Modeling and simulation of emergent behavior in transportation infrastructure restoration","docAbstract":"<p><span>The objective of this chapter is to create a methodology to model the emergent behavior during a disruption in the transportation system and that calculates economic losses due to such a disruption, and to understand how an extreme event affects the road transportation network. The chapter discusses a system dynamics approach which is used to model the transportation road infrastructure system to evaluate the different factors that render road segments inoperable and calculate economic consequences of such inoperability. System dynamics models have been integrated with business process simulation model to evaluate, design, and optimize the business process. The chapter also explains how different factors affect the road capacity. After identifying the various factors affecting the available road capacity, a causal loop diagram (CLD) is created to visually represent the causes leading to a change in the available road capacity and the effects on travel costs when the available road capacity changes.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Emergent behavior in complex systems engineering: A modeling and simulation approach","language":"English","publisher":"Wiley","doi":"10.1002/9781119378952.ch15","usgsCitation":"Ojha, A., Corns, S., Shoberg, T.G., Qin, R., and Long, S.K., 2018, Modeling and simulation of emergent behavior in transportation infrastructure restoration, chap. <i>of</i> Emergent behavior in complex systems engineering: A modeling and simulation approach, p. 249-368, https://doi.org/10.1002/9781119378952.ch15.","productDescription":"120 p.","startPage":"249","endPage":"368","ipdsId":"IP-087912","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":353780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-16","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe2a","contributors":{"authors":[{"text":"Ojha, Akhilesh","contributorId":204482,"corporation":false,"usgs":false,"family":"Ojha","given":"Akhilesh","email":"","affiliations":[{"id":36947,"text":"Department of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO, 65401","active":true,"usgs":false}],"preferred":false,"id":734135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corns, Steven","contributorId":146271,"corporation":false,"usgs":false,"family":"Corns","given":"Steven","affiliations":[{"id":16655,"text":"Dept. of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO","active":true,"usgs":false}],"preferred":false,"id":734136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shoberg, Thomas G. 0000-0003-0173-1246 tshoberg@usgs.gov","orcid":"https://orcid.org/0000-0003-0173-1246","contributorId":3764,"corporation":false,"usgs":true,"family":"Shoberg","given":"Thomas","email":"tshoberg@usgs.gov","middleInitial":"G.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":734134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Qin, Ruwen","contributorId":204483,"corporation":false,"usgs":false,"family":"Qin","given":"Ruwen","email":"","affiliations":[{"id":36947,"text":"Department of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO, 65401","active":true,"usgs":false}],"preferred":false,"id":734137,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Long, Suzanna K.","contributorId":146270,"corporation":false,"usgs":false,"family":"Long","given":"Suzanna","email":"","middleInitial":"K.","affiliations":[{"id":16655,"text":"Dept. of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO","active":true,"usgs":false}],"preferred":false,"id":734138,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196725,"text":"70196725 - 2018 - Factors influencing elk recruitment across ecotypes in the Western United States","interactions":[],"lastModifiedDate":"2018-09-10T15:10:53","indexId":"70196725","displayToPublicDate":"2018-04-27T00:00:00","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":"Factors influencing elk recruitment across ecotypes in the Western United States","docAbstract":"<p><span>Ungulates are key components in ecosystems and economically important for sport and subsistence harvest. Yet the relative importance of the effects of weather conditions, forage productivity, and carnivores on ungulates are not well understood. We examined changes in elk (</span><i>Cervus canadensis</i><span>) recruitment (indexed as age ratios) across 7 states and 3 ecotypes in the northwestern United States during 1989–2010, while considering the effects of predator richness, forage productivity, and precipitation. We found a broad‐scale, long‐term decrease in elk recruitment of 0.48 juveniles/100 adult females/year. Weather conditions (indexed as summer and winter precipitation) showed small, but measurable, influences on recruitment. Forage productivity on summer and winter ranges (indexed by normalized difference vegetation index [NDVI] metrics) had the strongest effect on elk recruitment relative to other factors. Relationships between forage productivity and recruitment varied seasonally and regionally. The productivity of winter habitat was more important in southern parts of the study area, whereas annual variation in productivity of summer habitat had more influence on recruitment in northern areas. Elk recruitment varied by up to 15 juveniles/100 adult females across the range of variation in forage productivity. Areas with more species of large carnivores had relatively low elk recruitment, presumably because of increased predation. Wolves (</span><i>Canis lupus</i><span>) were associated with a decrease of 5 juveniles/100 adult females, whereas grizzly bears (</span><i>Ursus arctos</i><span>) were associated with an additional decrease of 7 juveniles/100 adult females. Carnivore species can have a critical influence on ungulate recruitment because their influence rivals large ranges of variation in environmental conditions. A more pressing concern, however, stems from persistent broad‐scale decreases in recruitment across the distribution of elk in the northwestern United States, irrespective of carnivore richness. Our results suggest that wildlife managers interested in improving recruitment of elk consider the combined effects of habitat and predators. Efforts to manage summer and winter ranges to increase forage productivity may have a positive effect on recruitment.<span>&nbsp;</span></span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21438","usgsCitation":"Lukacs, P.M., Mitchell, M.S., Hebblewhite, M., Johnson, B.K., Johnson, H.E., Kauffman, M., Proffitt, K.M., Zager, P., Brodie, J., Hersey, K., Holland, A.A., Hurley, M., McCorquodale, S., Middleton, A., Nordhagen, M., Nowak, J.J., Walsh, D.P., and White, P., 2018, Factors influencing elk recruitment across ecotypes in the Western United States: Journal of Wildlife Management, v. 82, no. 4, p. 698-710, https://doi.org/10.1002/jwmg.21438.","productDescription":"13 p.","startPage":"698","endPage":"710","ipdsId":"IP-063346","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":353779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"82","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-08","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe28","contributors":{"authors":[{"text":"Lukacs, Paul M.","contributorId":101240,"corporation":false,"usgs":true,"family":"Lukacs","given":"Paul","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":734180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hebblewhite, Mark","contributorId":190188,"corporation":false,"usgs":false,"family":"Hebblewhite","given":"Mark","email":"","affiliations":[],"preferred":false,"id":734182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Bruce K.","contributorId":204502,"corporation":false,"usgs":false,"family":"Johnson","given":"Bruce","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":734183,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":189179,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":false,"id":734185,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Proffitt, Kelly M.","contributorId":106783,"corporation":false,"usgs":true,"family":"Proffitt","given":"Kelly","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":734186,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zager, Peter","contributorId":16737,"corporation":false,"usgs":true,"family":"Zager","given":"Peter","email":"","affiliations":[],"preferred":false,"id":734187,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Brodie, Jedediah","contributorId":63706,"corporation":false,"usgs":true,"family":"Brodie","given":"Jedediah","affiliations":[],"preferred":false,"id":734188,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hersey, Kent","contributorId":99873,"corporation":false,"usgs":false,"family":"Hersey","given":"Kent","affiliations":[{"id":6763,"text":"Utah Division of Wildlife Resources, Salt Lake City, Utah","active":true,"usgs":false}],"preferred":false,"id":734189,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Holland, A. Andrew","contributorId":171542,"corporation":false,"usgs":false,"family":"Holland","given":"A.","email":"","middleInitial":"Andrew","affiliations":[],"preferred":false,"id":734190,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hurley, Mark","contributorId":58174,"corporation":false,"usgs":true,"family":"Hurley","given":"Mark","affiliations":[],"preferred":false,"id":734191,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McCorquodale, Scott","contributorId":28515,"corporation":false,"usgs":true,"family":"McCorquodale","given":"Scott","affiliations":[],"preferred":false,"id":734192,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Middleton, Arthur","contributorId":39274,"corporation":false,"usgs":true,"family":"Middleton","given":"Arthur","affiliations":[],"preferred":false,"id":734193,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Nordhagen, Matthew","contributorId":189127,"corporation":false,"usgs":false,"family":"Nordhagen","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":734194,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Nowak, J. Joshua","contributorId":171707,"corporation":false,"usgs":false,"family":"Nowak","given":"J.","email":"","middleInitial":"Joshua","affiliations":[],"preferred":false,"id":734195,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Walsh, Daniel P. 0000-0002-7772-2445 dwalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":4758,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"dwalsh@usgs.gov","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":734196,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"White, P.J.","contributorId":91436,"corporation":false,"usgs":true,"family":"White","given":"P.J.","affiliations":[],"preferred":false,"id":734197,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70196456,"text":"ofr20181062 - 2018 - Measurements of erosion potential using Gust chamber in Yolo Bypass near Sacramento, California","interactions":[],"lastModifiedDate":"2018-10-17T09:39:35","indexId":"ofr20181062","displayToPublicDate":"2018-04-27T00:00:00","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":"2018-1062","title":"Measurements of erosion potential using Gust chamber in Yolo Bypass near Sacramento, California","docAbstract":"<div><div><span>This report describes work performed to quantify the&nbsp;</span><span>erodibility of surface soils in the Yolo Bypass (Bypass) near&nbsp;</span><span>Sacramento, California, for use in the California Department&nbsp;</span><span>of Water Resources (DWR) Yolo Bypass D-MCM mercury&nbsp;</span><span>model. The Bypass, when not serving as a floodway, is heavily&nbsp;</span><span>utilized for agriculture. During flood events, surface water&nbsp;</span><span>flows over the soil, resulting in the application of a shear stress&nbsp;</span><span>to the soil. The shear stress is a function of flow speed and&nbsp;</span><span>is often assumed to vary as the square of flow speed. Once&nbsp;</span><span>the shear stress reaches a critical value, erosion commences,&nbsp;</span><span>and the erosion rate typically increases with applied shear&nbsp;</span><span>stress. The goal of the work described here was to quantify&nbsp;</span><span>this process and how it varies throughout the major land uses&nbsp;</span><span>found in the Yolo Bypass.</span></div><div><span><br></span></div><div><span>Each of the major land uses found in the Bypass was&nbsp;</span><span>targeted for sediment coring and two side-by-side cores,&nbsp;</span><span>10 centimeters in diameter, were extracted at each site for&nbsp;</span><span>testing in a Gust erosion chamber. This device consists of a&nbsp;</span><span>cylinder with a piston and cap installed to contain a sediment&nbsp;</span><span>sample and overlying water. In most instances, coring was&nbsp;</span><span>done with the cylinder, the piston and cap were installed, and&nbsp;</span><span>testing commenced immediately. The cap at the top of the&nbsp;</span><span>cylinder contains vanes to induce rotation of the flow and is&nbsp;</span><span>driven by an electric motor, simulating the bed shear stress&nbsp;</span><span>experienced by the soil in a flood event. Ambient water is&nbsp;</span><span>introduced to the cylinder, passes through the device, and&nbsp;</span><span>carries eroded sediment out of the chamber. The exiting water&nbsp;</span><span>is tested for turbidity, and water samples obtained to relate&nbsp;</span><span>turbidity to suspended sediment concentration are used to&nbsp;</span><span>compute erosion rates for each of the applied shear stresses.</span></div><div><span><br></span></div><div><span>The result for each sediment core is (1) definition of the&nbsp;</span><span>critical shear stress required to initiate sediment erosion and&nbsp;</span><span>(2) estimation of coefficients required to relate erosion rate&nbsp;</span><span>to applied shear stress once this critical shear-stress threshold&nbsp;</span><span>has been exceeded. These quantities were computed for each&nbsp;</span><span>of the sites sampled. In total, 10 locations were sampled,&nbsp;</span><span>representing 10 land uses ranging from wild and white rice&nbsp;</span><span>fields to the flooded Liberty Island and the Toe Drain that&nbsp;</span><span>receives runoff from much of the cultivated land (table 1).</span></div><div><span><br></span></div><div><span>The Gust chamber test causes the erosion of a very small&nbsp;</span><span>layer of sediment, typically less than a millimeter thick. The&nbsp;</span><span>strength of the soil within this layer increases with depth,&nbsp;</span><span>typically, and this soil strength versus depth is measured in the&nbsp;</span><span>testing process.</span></div><div><span><br></span></div><div><span>Results for each land use type tested are presented as the&nbsp;</span><span>initial critical shear stress at which erosion began and the rate&nbsp;</span><span>at which erosion increases as shear stress increases (table 2).&nbsp;</span><span>Of the land use types sampled, irrigated pasture displayed&nbsp;</span><span>the lowest critical shear stress, meaning that it required the&nbsp;</span><span>smallest flow speed to initiate erosion. But in this case, the&nbsp;</span><span>rate of increase of the subsequent erosion, given higher flow&nbsp;</span><span>speeds, was small. The wild rice field samples exhibited a&nbsp;</span><span>higher critical shear stress but also exhibited a much higher&nbsp;</span><span>erosion rate once the critical shear stress was exceeded. The&nbsp;</span><span>erosion rate for wild rice was about three times greater than&nbsp;</span><span>that for white rice. Bear in mind that these results are based on&nbsp;</span><span>only two cores tested per site, and variability between fields&nbsp;</span><span>with the same crop could be significant. Approved digital data&nbsp;</span><span>can be viewed and downloaded from ScienceBase, at&nbsp;</span><span><a href=\"https://doi.org/10.5066/F7BV7DQC\" target=\"_blank\" data-mce-href=\"https://doi.org/10.5066/F7BV7DQC\">https://doi.org/10.5066/F7BV7DQC</a>. These results are being&nbsp;</span><span>used to calculate erosion rates in the DWR Yolo Bypass&nbsp;</span><span>D-MCM mercury model.</span></div><div><span><br></span></div><div><span>The Toe Drain was very difficult to sample, owing to&nbsp;</span><span>hard, consolidated sediments on the channel bed. On the&nbsp;</span><span>first visit, two cores were obtained successfully, and testing&nbsp;</span><span>revealed very different results. A second visit was made, but&nbsp;</span><span>it was not possible to obtain cores suitable for testing with the&nbsp;</span><span>coring equipment used. The available results suggest that Toe&nbsp;</span><span>Drain soil is highly erodible (low critical shear stress and high&nbsp;</span><span>erosion rate once initiated) despite being difficult to sample.&nbsp;</span><span>As a collector of runoff, it also has the potential to accumulate&nbsp;</span><span>soils eroded from adjacent areas, subsequent to storm events,&nbsp;</span><span>as flows subside. This deposited material will typically be&nbsp;</span><span>more erodible than the material that it lands on. The deposition&nbsp;</span><span>and resuspension of material was not simulated in the testing&nbsp;</span><span>described here because the applied shear stress increases&nbsp;</span><span>monotonically during testing.</span></div></div><div><span><br></span></div><div><div><span>The spatial distribution of mean grain size, loss on&nbsp;</span><span>ignition, and percent fines of Yolo Bypass soils are also&nbsp;</span><span>presented. Sediment sampling for this effort was performed&nbsp;</span><span>by DWR; the U.S. Geological Survey (USGS) performed&nbsp;</span><span>the sample analysis. These data should thus be considered&nbsp;</span><span>provisional, but the remainder of the data presented here, and&nbsp;</span><span>this report, have been through the formal U.S. Geological&nbsp;</span><span>Survey review process.</span></div><div><span><br></span></div><div><span>A separate effort has been made by others to develop&nbsp;</span><span>numerical model results defining the spatially&nbsp; varying, time-dependent&nbsp;</span><span>hydrodynamics in the Yolo Bypass. These model&nbsp;</span><span>results are being used to quantify shear stress on the soil&nbsp;</span><span>surface, which together with the Gust chamber results shown&nbsp;</span><span>here, are used for the DWR Yolo Bypass D-MCM mercury&nbsp;</span><span>transport model to compute erosion rates for each time step.</span></div><div><span><br data-mce-bogus=\"1\"></span></div></div>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181062","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Work, P.A., and Schoellhamer, D.H., 2018, Measurements of erosion potential using Gust chamber in Yolo Bypass near Sacramento, California: U.S. Geological Survey Open-File Report 2018–1062, 17 p., https://doi.org/10.3133/ofr20181062.","productDescription":"Report: v, 17 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-088304","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":353704,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1062/ofr20181062.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1062"},{"id":353705,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BV7DQC","text":"Data Release","linkHelpText":"Gust Erosion Chamber Data, Yolo Bypass, CA (2015-16)"},{"id":353703,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1062/coverthb.jpg"}],"country":"United States","state":"California","city":"Sacramento","otherGeospatial":"Yolo Bypass","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.69692993164062,\n              38.23494411562881\n            ],\n            [\n              -121.54586791992188,\n              38.23494411562881\n            ],\n            [\n              -121.54586791992188,\n              38.78941577989049\n            ],\n            [\n              -121.69692993164062,\n              38.78941577989049\n            ],\n            [\n              -121.69692993164062,\n              38.23494411562881\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" target=\"_blank\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,&nbsp;<br><a href=\"https://ca.water.usgs.gov\" target=\"_blank\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov\" target=\"_blank\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, CA 95819</p>","tableOfContents":"<ul><li>Executive Summary<br></li><li>Introduction<br></li><li>Site Selection<br></li><li>Field Methods<br></li><li>Results<br></li><li>Analysis<br></li><li>Conclusions<br></li><li>Recommendations<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2018-04-27","noUsgsAuthors":false,"publicationDate":"2018-04-27","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe2c","contributors":{"authors":[{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":732976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":732977,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70203196,"text":"70203196 - 2018 - Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability","interactions":[],"lastModifiedDate":"2019-04-26T16:44:27","indexId":"70203196","displayToPublicDate":"2018-04-26T16:33:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability","docAbstract":"<ol><li>Streamflow is essential for maintaining healthy aquatic ecosystems and for supporting human water supply needs. Changes in climate, land use and water use practices may alter water availability. Understanding the potential effect of these changes on aquatic ecosystems is critical for long-term water management to maintain a balance between water for human consumption and ecosystem needs.</li><li>Fish species data and streamflow estimates from a rainfall-runoff and flow routing model were used to develop boosted regression tree models to predict the relationship between streamflow and fish species richness (FSR) under plausible scenarios of (1) water withdrawal, (2) climate change and (3) increases in impervious surfaces in the Piedmont ecoregion of North Carolina, U.S.A. Maximum monthly flow, the fraction of total flow originating from impervious surface runoff, coefficient of monthly streamflow variability, and the specific river basin accounted for 50% of the variability in FSR. This model was used to predict FSR values for all twelve-digit Hydrological Unit Code catchments (HUC-12s) in the North Carolina Piedmont under current flow conditions and under water withdrawal, climate change and impervious surface scenarios.</li><li>Flow–ecology modeling results indicate that predicted FSR declined significantly with increased water withdrawals. However, the magnitude of decline varied geographically. A “hot-spot” analysis was conducted based on predicted changes in FSR under each scenario to understand which HUC-12s were most likely to be affected by changes in water withdrawals, climate and impervious surfaces. Under the 20% withdrawal increase scenario, 413 of 886 (47%) HUC-12s in the study area were predicted to lose one or more species. HUC-12s in the Broad, Catawba, Yadkin and Cape Fear river basins were most susceptible to species loss.</li><li>These findings may help decision making efforts by identifying catchments most vulnerable to changing water availability. Additionally, FSR-discharge modeling results can assist resource agencies, water managers and stakeholders in assessing the effect of water withdrawals in catchments to better support the protection and long-term conservation of species.</li></ol>","language":"English","doi":"10.1111/fwb.13048","usgsCitation":"Hain;, E.F., Kennen, J., Caldwell, P.V., Nelson, S.A., Ge Sun, and McNulty, S.G., 2018, Using regional scale flow–ecology modeling to identify catchments where fish assemblages are most vulnerable to changes in water availability: Freshwater Biology, v. 63, p. 928-945, https://doi.org/10.1111/fwb.13048.","productDescription":"17 p.","startPage":"928","endPage":"945","ipdsId":"IP-084804","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":363277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.936279296875,\n              33.797408767572485\n            ],\n            [\n              -76.893310546875,\n              33.797408767572485\n            ],\n            [\n              -76.893310546875,\n              36.53612263184686\n            ],\n            [\n              -80.936279296875,\n              36.53612263184686\n            ],\n            [\n              -80.936279296875,\n              33.797408767572485\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"63","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Hain;, Ernie F.","contributorId":215083,"corporation":false,"usgs":false,"family":"Hain;","given":"Ernie","email":"","middleInitial":"F.","affiliations":[{"id":39171,"text":"Center for Geospatial Analytics, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, 27695, USA","active":true,"usgs":false}],"preferred":false,"id":761593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761592,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Peter V.","contributorId":215084,"corporation":false,"usgs":false,"family":"Caldwell","given":"Peter","email":"","middleInitial":"V.","affiliations":[{"id":39172,"text":"USDA Forest Service, Center for Forest Watershed Science, Coweeta Hydrologic Laboratory, Otto, NC, USA","active":true,"usgs":false}],"preferred":false,"id":761594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Stacy A.C.","contributorId":215085,"corporation":false,"usgs":false,"family":"Nelson","given":"Stacy","email":"","middleInitial":"A.C.","affiliations":[{"id":39171,"text":"Center for Geospatial Analytics, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, 27695, USA","active":true,"usgs":false}],"preferred":false,"id":761595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ge Sun","contributorId":215086,"corporation":false,"usgs":false,"family":"Ge Sun","affiliations":[{"id":39173,"text":"USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":761596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNulty, Steven G.","contributorId":215087,"corporation":false,"usgs":false,"family":"McNulty","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":39173,"text":"USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":761597,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70265444,"text":"70265444 - 2018 - Dissipation of polyoxyethylene tallow amine (POEA) and glyphosate in an agricultural field and their co-occurrence on streambed sediments","interactions":[],"lastModifiedDate":"2025-04-07T14:24:03.688416","indexId":"70265444","displayToPublicDate":"2018-04-26T09:19:57","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":"Dissipation of polyoxyethylene tallow amine (POEA) and glyphosate in an agricultural field and their co-occurrence on streambed sediments","docAbstract":"<p><span>The&nbsp;environmental fate&nbsp;of&nbsp;polyoxyethylene&nbsp;tallow&nbsp;amine (POEA), an additive in&nbsp;glyphosate&nbsp;herbicide formulations, has not been studied. This study examined the dissipation of POEA;&nbsp;glyphosate; and aminomethylphosphonic acid (AMPA), a&nbsp;</span>degradation product<span>&nbsp;of glyphosate, in the top 45 cm of soil from an agricultural field where glyphosate was applied. The concentration of these compounds was also analyzed in bed sediment samples from watersheds in agricultural and urban areas from six states (Georgia, Hawaii, Iowa, Mississippi, North Carolina, South Carolina). The field studies show that POEA, glyphosate, and AMPA persist on the soil from planting season to planting season but dissipate over time with little migration into deeper soil. POEA, glyphosate, and AMPA were found on the bed sediment samples in urban and&nbsp;agricultural watersheds.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.04.246","usgsCitation":"Tush, D.L., Maksimowicz, M.M., and Meyer, M., 2018, Dissipation of polyoxyethylene tallow amine (POEA) and glyphosate in an agricultural field and their co-occurrence on streambed sediments: Science of the Total Environment, v. 636, p. 212-219, https://doi.org/10.1016/j.scitotenv.2018.04.246.","productDescription":"8 p.","startPage":"212","endPage":"219","ipdsId":"IP-079506","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":488908,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.04.246","text":"Publisher Index Page"},{"id":484240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"636","noUsgsAuthors":false,"publicationDate":"2018-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Tush, Daniel L. 0000-0003-0031-3501 dtush@usgs.gov","orcid":"https://orcid.org/0000-0003-0031-3501","contributorId":4538,"corporation":false,"usgs":true,"family":"Tush","given":"Daniel","email":"dtush@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":932737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maksimowicz, Megan M.","contributorId":146481,"corporation":false,"usgs":false,"family":"Maksimowicz","given":"Megan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":932738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meyer, Michael T. 0000-0001-6006-7985","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":205665,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":932739,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196718,"text":"70196718 - 2018 - Clusters of community exposure to coastal flooding hazards based on storm and sea level rise scenarios—implications for adaptation networks in the San Francisco Bay region","interactions":[],"lastModifiedDate":"2018-05-21T13:07:34","indexId":"70196718","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3242,"text":"Regional Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Clusters of community exposure to coastal flooding hazards based on storm and sea level rise scenarios—implications for adaptation networks in the San Francisco Bay region","docAbstract":"<p><span>Sea level is projected to rise over the coming decades, further increasing the extent of flooding hazards in coastal communities. Efforts to address potential impacts from climate-driven coastal hazards have called for collaboration among communities to strengthen the application of best practices. However, communities currently lack practical tools for identifying potential partner communities based on similar hazard exposure characteristics. This study uses statistical cluster analysis to identify similarities in community exposure to flooding hazards for a suite of sea level rise and storm scenarios. We demonstrate this approach using 63 jurisdictions in the San Francisco Bay region of California (USA) and compare 21 distinct exposure variables related to residents, employees, and structures for six hazard scenario combinations of sea level rise and storms. Results indicate that cluster analysis can provide an effective mechanism for identifying community groupings. Cluster compositions changed based on the selected societal variables and sea level rise scenarios, suggesting that a community could participate in multiple networks to target specific issues or policy interventions. The proposed clustering approach can serve as a data-driven foundation to help communities identify other communities with similar adaptation challenges and to enhance regional efforts that aim to facilitate adaptation planning and investment prioritization.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10113-017-1267-5","usgsCitation":"Hummel, M., Wood, N.J., Schweikert, A., Stacey, M., Jones, J., Barnard, P.L., and Erikson, L., 2018, Clusters of community exposure to coastal flooding hazards based on storm and sea level rise scenarios—implications for adaptation networks in the San Francisco Bay region: Regional Environmental Change, v. 18, no. 5, p. 1343-1355, https://doi.org/10.1007/s10113-017-1267-5.","productDescription":"13 p.","startPage":"1343","endPage":"1355","ipdsId":"IP-084260","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":353750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.61016845703124,\n              37.385435182627226\n            ],\n            [\n              -121.58569335937501,\n              37.385435182627226\n            ],\n            [\n              -121.58569335937501,\n              38.25974980039479\n            ],\n            [\n              -122.61016845703124,\n              38.25974980039479\n            ],\n            [\n              -122.61016845703124,\n              37.385435182627226\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-07","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe34","contributors":{"authors":[{"text":"Hummel, Michelle","contributorId":204476,"corporation":false,"usgs":false,"family":"Hummel","given":"Michelle","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":734104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":734105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schweikert, Amy","contributorId":204479,"corporation":false,"usgs":false,"family":"Schweikert","given":"Amy","email":"","affiliations":[],"preferred":false,"id":734106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stacey, Mark T.","contributorId":13367,"corporation":false,"usgs":true,"family":"Stacey","given":"Mark T.","affiliations":[],"preferred":false,"id":734107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Jeanne","contributorId":50444,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","affiliations":[],"preferred":false,"id":734108,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":2880,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":734109,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":147149,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":734110,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70196707,"text":"70196707 - 2018 - Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal","interactions":[],"lastModifiedDate":"2018-04-26T11:32:22","indexId":"70196707","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5679,"text":"Open Water Journal","active":true,"publicationSubtype":{"id":10}},"title":"Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal","docAbstract":"<p><span>The U.S. Geological Survey (USGS) is the primary U.S. Government agency for water data collection and dissemination. In this role, the USGS has recently created and deployed a National Water Census Data Portal (NWC-DP) which provides access to streamflow, evapotransporation, precipitation, aquatic biology and other data at the national level. Recognizing the value of these data sets for hydrologic science education, this paper presents an effort to bridge the gap between pencil–and-paper-based hydrology curriculum and the USGS NWC-DP resource. Specifically, we have developed an R package, National Water Census Education (NWCEd), and five associated laboratory exercises that integrate R- and web-services-based access to the NWC-DP data sets. Using custom functions built into the NWCEd, students are able to access unprecedented amounts of hydrologic data from the NWC-DP, which can be applied to current hydrology curriculum and analyzed using NWCEd and a number of other open-source R tools.</span></p>","language":"English","publisher":"BYU","usgsCitation":"Nelson, J., Ames, D.P., and Blodgett, D.L., 2018, Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal: Open Water Journal, v. 5, no. 1, p. 1-14.","productDescription":"Article 1; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-086854","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":353730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353724,"type":{"id":15,"text":"Index Page"},"url":"https://scholarsarchive.byu.edu/openwater/vol5/iss1/1/"}],"volume":"5","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cfe4b0da30c1bfbe42","contributors":{"authors":[{"text":"Nelson, Jake","contributorId":204467,"corporation":false,"usgs":false,"family":"Nelson","given":"Jake","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":734059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ames, Daniel P.","contributorId":204468,"corporation":false,"usgs":false,"family":"Ames","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":734060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":734058,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196703,"text":"70196703 - 2018 - Assessing the efficacy of corn-based bait containing antimycin-a to control common carp populations using laboratory and pond experiments","interactions":[],"lastModifiedDate":"2018-06-04T16:02:11","indexId":"70196703","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the efficacy of corn-based bait containing antimycin-a to control common carp populations using laboratory and pond experiments","docAbstract":"<p><span>Strategic use of oral toxicants could allow for practical and sustainable control schemes for the invasive common carp (</span><i class=\"EmphasisTypeItalic \">Cyprinus carpio,</i><span><span>&nbsp;</span>or ‘carp’) if a toxicant selectively targeted carp and not native species. In this study, we incorporated antimycin-a (ANT-A), a known fish toxicant, into a corn-based bait and conducted a series of experiments to determine its toxicity, leaching rate, and species-specificity. Our results showed that ANT-A was lethal to carp at doses ≥&nbsp;4&nbsp;mg/kg and that the amount of ANT-A that leached out of the bait in 72&nbsp;h was not lethal to carp or bluegill (</span><i class=\"EmphasisTypeItalic \">Lepomis macrochirus</i><span>). Species-specificity trials were conducted in 227 L tanks, in which carp were stocked with three native species representing families that occur sympatrically with carp in our study region: the fathead minnow (</span><i class=\"EmphasisTypeItalic \">Pimephales promelas</i><span>), yellow perch (</span><i class=\"EmphasisTypeItalic \">Perca flavescens</i><span>) and bluegill. These trials showed high mortality of carp (46%) and fathead minnows (76%) but no significant mortality of perch or bluegill. Finally, a pond study, which used the same species composition except for fathead minnows, resulted in 37% morality among adult carp and no mortality among perch or bluegill. Our results suggest that corn-based bait that contains ANT-A could be used to selectively control carp in ecosystems dominated by percids or centrarchids, such as lakes across the Great Plains ecoregion of North America, where carp are especially problematic.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1662-y","usgsCitation":"Poole, J.R., Sauey, B.W., Amberg, J., and Bajer, P.G., 2018, Assessing the efficacy of corn-based bait containing antimycin-a to control common carp populations using laboratory and pond experiments: Biological Invasions, v. 20, no. 7, p. 1809-1820, https://doi.org/10.1007/s10530-018-1662-y.","productDescription":"12 p.","startPage":"1809","endPage":"1820","ipdsId":"IP-085875","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":353729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"7","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-15","publicationStatus":"PW","scienceBaseUri":"5afee6cfe4b0da30c1bfbe44","contributors":{"authors":[{"text":"Poole, Joshua R.","contributorId":204465,"corporation":false,"usgs":false,"family":"Poole","given":"Joshua","email":"","middleInitial":"R.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":734050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauey, Blake W. 0000-0003-2819-0814 bsauey@usgs.gov","orcid":"https://orcid.org/0000-0003-2819-0814","contributorId":202175,"corporation":false,"usgs":true,"family":"Sauey","given":"Blake","email":"bsauey@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bajer, Przemyslaw G.","contributorId":204466,"corporation":false,"usgs":false,"family":"Bajer","given":"Przemyslaw","email":"","middleInitial":"G.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":734052,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196709,"text":"70196709 - 2018 - Mechanisms of wave‐driven water level variability on reef‐fringed coastlines","interactions":[],"lastModifiedDate":"2018-07-03T11:25:32","indexId":"70196709","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms of wave‐driven water level variability on reef‐fringed coastlines","docAbstract":"<p><span>Wave‐driven water level variability (and runup at the shoreline) is a significant cause of coastal flooding induced by storms. Wave runup is challenging to predict, particularly along tropical coral reef‐fringed coastlines due to the steep bathymetric profiles and large bottom roughness generated by reef organisms, which can violate assumptions in conventional models applied to open sandy coastlines. To investigate the mechanisms of wave‐driven water level variability on a reef‐fringed coastline, we performed a set of laboratory flume experiments on an along‐shore uniform bathymetric profile with and without bottom roughness. Wave setup and waves at frequencies lower than the incident sea‐swell forcing (infragravity waves) were found to be the dominant components of runup. These infragravity waves were positively correlated with offshore wave groups, signifying they were generated in the surf zone by the oscillation of the breakpoint. On the reef flat and at the shoreline, the low‐frequency waves formed a standing wave pattern with energy concentrated at the natural frequencies of the reef flat, indicating resonant amplification. Roughness elements used in the flume to mimic large reef bottom roughness reduced low frequency motions on the reef flat and reduced wave run up by 30% on average, compared to the runs over a smooth bed. These results provide insight into sea‐swell and infragravity wave transformation and wave setup dynamics on steep‐sloped coastlines, and the effect that future losses of reef bottom roughness may have on coastal flooding along reef‐fringed coasts.</span></p>","language":"English","publisher":"Wiley","doi":"10.1029/2018JC013933","usgsCitation":"Buckley, M.L., Lowe, R.J., Hansen, J.E., van Dongeren, A.R., and Storlazzi, C.D., 2018, Mechanisms of wave‐driven water level variability on reef‐fringed coastlines: Journal of Geophysical Research C: Oceans, v. 123, no. 5, p. 3811-3831, https://doi.org/10.1029/2018JC013933.","productDescription":"21 p.","startPage":"3811","endPage":"3831","ipdsId":"IP-092740","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468807,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://admin.research-repository.uwa.edu.au/en/publications/db5339a2-0de9-4c15-9798-f5eaddf31687","text":"Publisher Index Page"},{"id":437931,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71V5D7J","text":"USGS data release","linkHelpText":"Water level and velocity measurements from the 2012 University of Western Australia Fringing Reef Experiment (UWAFRE)"},{"id":353758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-26","publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe3e","contributors":{"authors":[{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":734069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Jeff E.","contributorId":204340,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","email":"","middleInitial":"E.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":true,"id":734070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Dongeren, Ap R.","contributorId":203482,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","middleInitial":"R.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":734071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734072,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196708,"text":"70196708 - 2018 - Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters","interactions":[],"lastModifiedDate":"2021-05-28T14:06:57.742111","indexId":"70196708","displayToPublicDate":"2018-04-26T00:00:00","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":"Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters","docAbstract":"<p><span>Discharges from pharmaceutical manufacturing facilities (PMFs) previously have been identified as important sources of pharmaceuticals to the environment. Yet few studies are available to establish the influence of PMFs on the pharmaceutical source contribution to wastewater treatment plants (WWTPs) and waterways at the national scale. Consequently, a national network of 13 WWTPs receiving PMF discharges, six WWTPs with no PMF input, and one WWTP that transitioned through a PMF closure were selected from across the United States to assess the influence of PMF inputs on pharmaceutical loading to WWTPs. Effluent samples were analyzed for 120 pharmaceuticals and pharmaceutical degradates. Of these, 33 pharmaceuticals had concentrations substantially higher in PMF-influenced effluent (maximum 555,000 ng/L) compared to effluent from control sites (maximum 175 ng/L). Concentrations in WWTP receiving PMF input are variable, as discharges from PMFs are episodic, indicating that production activities can vary substantially over relatively short (several months) periods and have the potential to rapidly transition to other pharmaceutical products. Results show that PMFs are an important, national-scale source of pharmaceuticals to the environment.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.04.160","usgsCitation":"Scott, T., Phillips, P.J., Kolpin, D., Finkelstein, K.M., Furlong, E., Foreman, W.T., and Gray, J., 2018, Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters: Science of the Total Environment, v. 636, p. 69-79, https://doi.org/10.1016/j.scitotenv.2018.04.160.","productDescription":"11 p.","startPage":"69","endPage":"79","ipdsId":"IP-095342","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":468809,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.04.160","text":"Publisher Index Page"},{"id":353759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"636","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe40","contributors":{"authors":[{"text":"Scott, Tia-Marie 0000-0002-5677-0544 tia-mariescott@usgs.gov","orcid":"https://orcid.org/0000-0002-5677-0544","contributorId":5122,"corporation":false,"usgs":true,"family":"Scott","given":"Tia-Marie","email":"tia-mariescott@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finkelstein, Kaitlyn M. 0000-0003-1588-3312","orcid":"https://orcid.org/0000-0003-1588-3312","contributorId":202727,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Kaitlyn","email":"","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734067,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Furlong, Edward T. 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":204151,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":734064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":190786,"corporation":false,"usgs":true,"family":"Foreman","given":"William","email":"wforeman@usgs.gov","middleInitial":"T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":734065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gray, James L. 0000-0002-0807-5635","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":202726,"corporation":false,"usgs":true,"family":"Gray","given":"James L.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":734066,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70196702,"text":"70196702 - 2018 - Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern","interactions":[],"lastModifiedDate":"2018-04-26T11:21:22","indexId":"70196702","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Reproductive success and contaminant associations in tree swallows (<i>Tachycineta bicolor</i>) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern","title":"Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern","docAbstract":"During 2010-2014, tree swallow (Tachycineta bicolor) reproductive success was monitored at 68 sites across all 5 Great Lakes, including 58 sites located within Great Lakes Areas of Concern (AOCs) and 10 non-AOCs. Sample eggs were collected from tree swallow clutches and analyzed for contaminants including polychlorinated biphenyls (PCBs), dioxins and furans, polybrominated diphenyl ethers, and 34 other organic compounds. Contaminant data were available for 360 of the clutches monitored. Markov chain multistate modeling was used to assess the importance of 5 ecological variables and 11 of the dominant contaminants in explaining the pattern of egg and nestling failure rates. Four of 5 ecological variables (Female Age, Date within season, Year, and Site) were important explanatory variables. Of the 11 contaminants, only total dioxin and furan toxic equivalents (TEQs) explained a significant amount of the egg failure probabilities. Neither total PCBs nor PCB TEQs explained the variation in egg failure rates. In a separate analysis, polycyclic aromatic hydrocarbon exposure in nestling diet, used as a proxy for female diet during egg laying, was significantly correlated with the daily probability of egg failure. The 8 sites within AOCs which had poorer reproduction when compared to 10 non-AOC sites, the measure of impaired reproduction as defined by the Great Lakes Restoration Initiative, were associated with exposure to dioxins and furan TEQs, PAHs, or depredation. Only 2 sites had poorer reproduction than the poorest performing non-AOC. Using a classic (non-modeling) approach to estimating reproductive success, 82% of nests hatched at least 1 egg, and 75% of eggs laid, excluding those collected for contaminant analyses, hatched.","language":"English","publisher":"Springer","doi":"10.1007/s10646-018-1913-9","usgsCitation":"Custer, C.M., Custer, T.W., Etterson, M.A., Dummer, P.M., Goldberg, D., and Franson, J.C., 2018, Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern: Ecotoxicology, v. 27, no. 4, p. 457-476, https://doi.org/10.1007/s10646-018-1913-9.","productDescription":"20 p.","startPage":"457","endPage":"476","ipdsId":"IP-086919","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":353728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","volume":"27","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-09","publicationStatus":"PW","scienceBaseUri":"5afee6cfe4b0da30c1bfbe46","contributors":{"authors":[{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Custer, Thomas W. 0000-0003-3170-6519 tcuster@usgs.gov","orcid":"https://orcid.org/0000-0003-3170-6519","contributorId":2835,"corporation":false,"usgs":true,"family":"Custer","given":"Thomas","email":"tcuster@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734044,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Etterson, Matthew A.","contributorId":108012,"corporation":false,"usgs":false,"family":"Etterson","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":734045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dummer, Paul M. 0000-0002-2055-9480 pdummer@usgs.gov","orcid":"https://orcid.org/0000-0002-2055-9480","contributorId":3015,"corporation":false,"usgs":true,"family":"Dummer","given":"Paul","email":"pdummer@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734046,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldberg, Diana R. 0000-0001-8540-8512","orcid":"https://orcid.org/0000-0001-8540-8512","contributorId":82252,"corporation":false,"usgs":true,"family":"Goldberg","given":"Diana R.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":734047,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Franson, J. Christian 0000-0002-0251-4238 jfranson@usgs.gov","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":177499,"corporation":false,"usgs":true,"family":"Franson","given":"J.","email":"jfranson@usgs.gov","middleInitial":"Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":734048,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196714,"text":"70196714 - 2018 - Temperature-influenced energetics model for migrating waterfowl","interactions":[],"lastModifiedDate":"2018-04-26T16:18:45","indexId":"70196714","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Temperature-influenced energetics model for migrating waterfowl","docAbstract":"<p><span>Climate and weather affect avian migration by influencing when and where birds fly, the energy costs and risks of flight, and the ability to sense cues necessary for proper navigation. We review the literature of the physiology of avian migration and the influence of climate, specifically temperature, on avian migration dynamics. We use waterfowl as a model guild because of the ready availability of empirical physiological data and their enormous economic value, but our discussion and expectations are broadly generalizable to migratory birds in general. We detail potential consequences of an increasingly warm climate on avian migration, including the possibility of the cessation of migration by some populations and species. Our intent is to lay the groundwork for including temperature effects on energetic gains and losses of migratory birds with the expected consequences of increasing temperatures into a predictive modeling framework. To this end, we provide a simulation of migration progression exclusively focused on the influence of temperature on the physiological determinants of migration. This simulation produced comparable results to empirically derived and observed values for different migratory factors (e.g., body fat content, flight range, departure date). By merging knowledge from the arenas of avian physiology and migratory theory we have identified a clear need for research and have developed hypotheses for a path forward.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.04.001","usgsCitation":"Aagaard, K., Thogmartin, W.E., and Lonsdorg, E.V., 2018, Temperature-influenced energetics model for migrating waterfowl: Ecological Modelling, v. 378, p. 46-58, https://doi.org/10.1016/j.ecolmodel.2018.04.001.","productDescription":"13 p.","startPage":"46","endPage":"58","ipdsId":"IP-084841","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2018.04.001","text":"Publisher Index Page"},{"id":353754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"378","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe38","contributors":{"authors":[{"text":"Aagaard, Kevin 0000-0003-0756-2172 kaagaard@usgs.gov","orcid":"https://orcid.org/0000-0003-0756-2172","contributorId":147393,"corporation":false,"usgs":true,"family":"Aagaard","given":"Kevin","email":"kaagaard@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lonsdorg, Eric V.","contributorId":204474,"corporation":false,"usgs":false,"family":"Lonsdorg","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":734083,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196712,"text":"70196712 - 2018 - Introduction to “Global tsunami science: Past and future, Volume III”","interactions":[],"lastModifiedDate":"2018-04-26T16:50:23","indexId":"70196712","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Introduction to “Global tsunami science: Past and future, Volume III”","docAbstract":"<p><span>Twenty papers on the study of tsunamis are included in Volume III of the PAGEOPH topical issue “Global Tsunami Science: Past and Future”. Volume I of this topical issue was published as PAGEOPH, vol. 173, No. 12, 2016 and Volume II as PAGEOPH, vol. 174, No. 8, 2017. Two papers in Volume III focus on specific details of the 2009 Samoa and the 1923 northern Kamchatka tsunamis; they are followed by three papers related to tsunami hazard assessment for three different regions of the world oceans: South Africa, Pacific coast of Mexico and the northwestern part of the Indian Ocean. The next six papers are on various aspects of tsunami hydrodynamics and numerical modelling, including tsunami edge waves, resonant behaviour of compressible water layer during tsunamigenic earthquakes, dispersive properties of seismic and volcanically generated tsunami waves, tsunami runup on a vertical wall and influence of earthquake rupture velocity on maximum tsunami runup. Four papers discuss problems of tsunami warning and real-time forecasting for Central America, the Mediterranean coast of France, the coast of Peru, and some general problems regarding the optimum use of the DART buoy network for effective real-time tsunami warning in the Pacific Ocean. Two papers describe historical and paleotsunami studies in the Russian Far East. The final set of three papers importantly investigates tsunamis generated by non-seismic sources: asteroid airburst and meteorological disturbances. Collectively, this volume highlights contemporary trends in global tsunami research, both fundamental and applied toward hazard assessment and mitigation.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00024-018-1851-8","usgsCitation":"Rabinovich, A.B., Fritz, H.M., Tanioka, Y., and Geist, E.L., 2018, Introduction to “Global tsunami science: Past and future, Volume III”: Pure and Applied Geophysics, v. 175, no. 4, p. 1231-1237, https://doi.org/10.1007/s00024-018-1851-8.","productDescription":"7 p.","startPage":"1231","endPage":"1237","ipdsId":"IP-096461","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-19","publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe3c","contributors":{"authors":[{"text":"Rabinovich, Alexander B.","contributorId":177506,"corporation":false,"usgs":false,"family":"Rabinovich","given":"Alexander","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":734130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fritz, Hermann M.","contributorId":194830,"corporation":false,"usgs":false,"family":"Fritz","given":"Hermann","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":734131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tanioka, Yuichiro","contributorId":177507,"corporation":false,"usgs":false,"family":"Tanioka","given":"Yuichiro","email":"","affiliations":[],"preferred":false,"id":734132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":734133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196005,"text":"sir20185009 - 2018 - Public-supply water use and self-supplied industrial water use in Tennessee, 2010","interactions":[],"lastModifiedDate":"2018-09-25T05:58:29","indexId":"sir20185009","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5009","title":"Public-supply water use and self-supplied industrial water use in Tennessee, 2010","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the Tennessee Department of Environment and Conservation, Division of Water Resources, prepared this report and displayed and analyzed water use by self-supplied industrial and public-supply water systems in Tennessee for 2010. Public-supply water systems in Tennessee provide water for domestic, industrial, and commercial uses and for municipal services. In 2010, 474 public-supply water systems distributed 917 million gallons per day (Mgal/d) of surface water (67 percent, 617 Mgal/d) and groundwater (33 percent, 300 Mgal/d) to a population of 5.7 million in Tennessee. Gross per capita water use in Tennessee during 2010 was 162 gallons per day.</p><p>Since 1950, water withdrawals by public-supply water systems in Tennessee have increased from 160 Mgal/d to 917 Mgal/d in 2010. Each of the 95 counties in Tennessee was served by at least 1 public-supply water system in 2010. Tennessee public-supply water systems withdraw less groundwater than surface water, and surface-water use has increased at a faster rate than groundwater use. Since 2005, surface-water withdrawals have increased by 26 Mgal/d, and groundwater withdrawals have decreased by 29 Mgal/d, which is the first decrease in groundwater withdrawals since 1950; however, 29 systems reported increased groundwater withdrawals during 2010, and 12 of these 29 systems reported increases of 1 Mgal/d or more. Davidson County had the largest surface-water withdrawal rate (136 Mgal/d) in 2010. The largest groundwater withdrawal rate (151 Mgal/d) by a single public-supply water system was reported by Memphis Light, Gas and Water, which served more than 669,000 people in Shelby County in 2010.</p><p>Self-supplied industrial water use includes water for such purposes as fabrication, processing, washing, diluting, cooling, or transporting a product; incorporating water into a product; or for sanitation needs in facilities that manufacture various products. Water withdrawals for self-supplied industrial water use during 2010 were about 776 Mgal/d. This quantity represented a decrease of 7 Mgal/d since 2005. In Tennessee, self-supplied industrial water withdrawals were primarily for&nbsp;chemical and allied products (555 Mgal/d), paper and allied products (107 Mgal/d), aeronautical products (71.5 Mgal/d), concrete and glass products (9.74 Mgal/d), and primary metal products (4.49 Mgal/d); and these products accounted for 96 percent (747 Mgal/d) of the self-supplied industrial water withdrawals in 2010. Surface water supplied 94 percent of the water (728 Mgal/d) for self-supplied industrial purposes, and groundwater supplied 6 percent (47.6 Mgal/d). Self-supplied industrial water withdrawals in Sullivan County were 488 Mgal/d and accounted for 61 percent of the self-supplied industrial water withdrawals. The largest groundwater withdrawal, 14.9 Mgal/d, by a single self-supplied industry was in Memphis, Tennessee, for the production of chemicals and allied products.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185009","collaboration":"Prepared in cooperation with the Tennessee Department of Environment and Conservation, Division of Water Resources","usgsCitation":"Robinson, J.A., 2018, Public-supply water use and self-supplied industrial water use in Tennessee, 2010: U.S. Geological Survey Scientific Investigation Report 2018–5009, 30 p., https://doi.org/10.3133/sir20185009.","productDescription":"Report: v, 29 p.; 7 Appendixes; Data Release","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059935","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":353717,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5009/sir20185009_appendixes1-7.xlsx","text":"Appendixes 1 to 7","size":"162 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018–5009 Appendixes 1 to 7"},{"id":353715,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5009/coverthb2.jpg"},{"id":353718,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7V9868K","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water Use in Tennessee, 2010"},{"id":353716,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5009/sir20185009.pdf","text":"Report","size":"4.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5009"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"mailto: dc_tn@usgs.gov\" data-mce-href=\"mailto: dc_tn@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/lmg-water/\" data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi Gulf Water Science Center</a>, Tennessee Office <br>U.S. Geological Survey<br>640 Grassmere Park, Suite 100 <br>Nashville, TN 37211</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Approach and Methods<br></li><li>Public-Supply Water Use During 2010<br></li><li>Self-Supplied Industrial Water Use During 2010<br></li><li>Summary<br></li><li>References Cited<br></li><li>Glossary<br></li><li>Appendix 1. Public-Supply Water Systems and Associated Water Use in the Tennessee Hydrologic Region, 2010<br></li><li>Appendix 2. Public-Supply Water Systems and Associated Water Use in the Ohio Hydrologic Region, 2010<br></li><li>Appendix 3. Public-Supply Water Systems and Associated Water Use in the Lower-Mississippi Hydrologic Region, 2010<br></li><li>Appendix 4. Self-Supplied Industrial Water Use in the Tennessee Hydrologic Region, 2010<br></li><li>Appendix 5. Self-Supplied Industrial Water Use in the Ohio Hydrologic Region, 2010<br></li><li>Appendix 6. Self-Supplied Industrial Water Use in the Lower Mississippi Hydrologic Region, 2010<br></li><li>Appendix 7. Public-Supply Water Systems in Tennessee, 2010<br></li></ul>","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"publishedDate":"2018-04-26","noUsgsAuthors":false,"publicationDate":"2018-04-26","publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe4e","contributors":{"authors":[{"text":"Robinson, John A. 0000-0001-8002-4237 jarobin@usgs.gov","orcid":"https://orcid.org/0000-0001-8002-4237","contributorId":1105,"corporation":false,"usgs":true,"family":"Robinson","given":"John","email":"jarobin@usgs.gov","middleInitial":"A.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":730885,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70196713,"text":"70196713 - 2018 - Effect of dynamical phase on the resonant interaction among tsunami edge wave modes","interactions":[],"lastModifiedDate":"2018-04-26T16:21:37","indexId":"70196713","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Effect of dynamical phase on the resonant interaction among tsunami edge wave modes","docAbstract":"<p><span>Different modes of tsunami edge waves can interact through nonlinear resonance. During this process, edge waves that have very small initial amplitude can grow to be as large or larger than the initially dominant edge wave modes. In this study, the effects of dynamical phase are established for a single triad of edge waves that participate in resonant interactions. In previous studies, Jacobi elliptic functions were used to describe the slow variation in amplitude associated with the interaction. This analytical approach assumes that one of the edge waves in the triad has zero initial amplitude and that the combined phase of the three waves&nbsp;</span><i class=\"EmphasisTypeItalic \">φ</i><span>&nbsp;=&nbsp;</span><i class=\"EmphasisTypeItalic \">θ</i><sub>1</sub><span>&nbsp;+&nbsp;</span><i class=\"EmphasisTypeItalic \">θ</i><sub>2</sub><span>&nbsp;−&nbsp;</span><i class=\"EmphasisTypeItalic \">θ</i><sub>3</sub><span><span>&nbsp;</span>is constant at the value for maximum energy exchange (</span><i class=\"EmphasisTypeItalic \">φ</i><span>&nbsp;=&nbsp;0). To obtain a more general solution, dynamical phase effects and non-zero initial amplitudes for all three waves are incorporated using numerical methods for the governing differential equations. Results were obtained using initial conditions calculated from a subduction zone, inter-plate thrust fault geometry and a stochastic earthquake slip model. The effect of dynamical phase is most apparent when the initial amplitudes and frequencies of the three waves are within an order of magnitude. In this case, non-zero initial phase results in a marked decrease in energy exchange and a slight decrease in the period of the interaction. When there are large differences in frequency and/or initial amplitude, dynamical phase has less of an effect and typically one wave of the triad has very little energy exchange with the other two waves. Results from this study help elucidate under what conditions edge waves might be implicated in late, large-amplitude arrivals.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00024-018-1796-y","usgsCitation":"Geist, E.L., 2018, Effect of dynamical phase on the resonant interaction among tsunami edge wave modes: Pure and Applied Geophysics, v. 175, no. 4, p. 1341-1354, https://doi.org/10.1007/s00024-018-1796-y.","productDescription":"14 p.","startPage":"1341","endPage":"1354","ipdsId":"IP-093470","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-12","publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe3a","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":734080,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70196715,"text":"70196715 - 2018 - Pedestrian evacuation modeling to reduce vehicle use for distant tsunami evacuations in Hawaiʻi","interactions":[],"lastModifiedDate":"2018-04-26T16:17:10","indexId":"70196715","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Pedestrian evacuation modeling to reduce vehicle use for distant tsunami evacuations in Hawaiʻi","docAbstract":"<p><span>Tsunami waves that arrive hours after generation elsewhere pose logistical challenges to emergency managers due to the perceived abundance of time and inclination of evacuees to use vehicles. We use coastal communities on the island of Oʻahu (Hawaiʻi, USA) to demonstrate regional evacuation modeling that can identify where successful pedestrian-based evacuations are plausible and where vehicle use could be discouraged. The island of Oʻahu has two tsunami-evacuation zones (standard and extreme), which provides the opportunity to examine if recommended travel modes vary based on zone. Geospatial path distance models are applied to estimate population exposure a</span><span>s a function of pedestrian travel time and speed out of evacuation zones. The use of the extreme zone triples the number of residents, employees, and facilities serving at-risk populations that would be encouraged to evacuate and slightly reduces the percentage of residents (98–76%) that could evacuate in less than 15 min at a plausible speed (with similar percentages for employees). Areas with lengthy evacuations are concentrated in the North Shore region for the standard zone but found all around the Oʻahu coastline for the extreme zone. The use of the extreme zone results in a 26% increase in the number of hotel visitors that would be encouraged to evacuate, and a 76% increase in the number of them that may require more than 15 min. Modeling can identify where pedestrian evacuations are plausible; however, there are logistical and behavioral issues that warrant attention before localized evacuation procedures may be realistic.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2018.03.009","usgsCitation":"Wood, N.J., Jones, J., Peters, J., and Richards, K., 2018, Pedestrian evacuation modeling to reduce vehicle use for distant tsunami evacuations in Hawaiʻi: International Journal of Disaster Risk Reduction, v. 28, p. 271-283, https://doi.org/10.1016/j.ijdrr.2018.03.009.","productDescription":"13 p.","startPage":"271","endPage":"283","ipdsId":"IP-092793","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468805,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2018.03.009","text":"Publisher Index Page"},{"id":437932,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7862FNT","text":"USGS data release","linkHelpText":"Pedestrian tsunami evacuation results for two tsunami-evacuation zones (standard and extreme) and three travel speeds (impaired, slow, and fast walk) for O'ahu, HI"},{"id":353753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -158.31573486328125,\n              21.235622362422877\n            ],\n            [\n              -157.6153564453125,\n              21.235622362422877\n            ],\n            [\n              -157.6153564453125,\n              21.73717777095988\n            ],\n            [\n              -158.31573486328125,\n              21.73717777095988\n            ],\n            [\n              -158.31573486328125,\n              21.235622362422877\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe36","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":734084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Jamie 0000-0002-9967-3314","orcid":"https://orcid.org/0000-0002-9967-3314","contributorId":204480,"corporation":false,"usgs":true,"family":"Jones","given":"Jamie","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":734085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":734086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richards, Kevin krichard@usgs.gov","contributorId":204475,"corporation":false,"usgs":false,"family":"Richards","given":"Kevin","email":"krichard@usgs.gov","affiliations":[{"id":36945,"text":"Hawaii Emergency Management Agency","active":true,"usgs":false}],"preferred":false,"id":734087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196719,"text":"70196719 - 2018 - Profiles of digestive enzymes of two competing planktivores, silver carp and gizzard shad, differ","interactions":[],"lastModifiedDate":"2018-04-26T16:23:33","indexId":"70196719","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5680,"text":"Ichthyological Research","active":true,"publicationSubtype":{"id":10}},"title":"Profiles of digestive enzymes of two competing planktivores, silver carp and gizzard shad, differ","docAbstract":"<p><span>Typically, studies in digestive physiology in fish focus on a few enzymes and provide insight into the specific processes of the enzyme in a targeted species. Comparative studies assessing a wide number of digestive enzymes on fishes that compete for food resources are lacking, especially in the context of an introduced species. It is generally thought that the invasive silver carp (SVC;&nbsp;</span><i class=\"EmphasisTypeItalic \">Hypophthalmichthys molitrix</i><span>) directly compete for food resources with the native gizzard shad (GZS;<span>&nbsp;</span></span><i class=\"EmphasisTypeItalic \">Dorosoma cepedianum</i><span>) in waters where they coexist. We compared 19 digestive enzymes between SVC and GZS throughout a year and in two rivers in the Midwestern United States: Illinois River and Wabash River. All digestive enzymes analyzed were detected in both SVC and GZS in both rivers. However, the profiles of the digestive enzymes varied by species. Alkaline phosphatase, valine arylamidase, acid phosphatase, naphthol-AS-BI-phosphohydrolase and N-acetyl-β-glucosaminidase were all much higher in SVC than in GZS. Differences between digestive enzyme profiles were also observed between rivers and months. This study demonstrates the utility of using an ecological approach to compare physiological features in fishes.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10228-018-0615-x","usgsCitation":"Amberg, J., Jensen, N., Erickson, R.A., Sauey, B.W., and Jackson, C., 2018, Profiles of digestive enzymes of two competing planktivores, silver carp and gizzard shad, differ: Ichthyological Research, v. 65, no. 2, p. 245-251, https://doi.org/10.1007/s10228-018-0615-x.","productDescription":"7 p.","startPage":"245","endPage":"251","ipdsId":"IP-076712","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":353749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-01","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe32","contributors":{"authors":[{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jensen, Nathan R.","contributorId":201065,"corporation":false,"usgs":false,"family":"Jensen","given":"Nathan R.","affiliations":[],"preferred":false,"id":734092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sauey, Blake W. 0000-0003-2819-0814 bsauey@usgs.gov","orcid":"https://orcid.org/0000-0003-2819-0814","contributorId":202175,"corporation":false,"usgs":true,"family":"Sauey","given":"Blake","email":"bsauey@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Craig 0000-0003-4023-0276 cjackson@usgs.gov","orcid":"https://orcid.org/0000-0003-4023-0276","contributorId":192276,"corporation":false,"usgs":true,"family":"Jackson","given":"Craig","email":"cjackson@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734095,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196699,"text":"70196699 - 2018 - Most atolls will be uninhabitable by the mid-21st century because of sea-level rise exacerbating wave-driven flooding","interactions":[],"lastModifiedDate":"2018-04-26T11:08:10","indexId":"70196699","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Most atolls will be uninhabitable by the mid-21st century because of sea-level rise exacerbating wave-driven flooding","docAbstract":"<p><span>Sea levels are rising, with the highest rates in the tropics, where thousands of low-lying coral atoll islands are located. Most studies on the resilience of these islands to sea-level rise have projected that they will experience minimal inundation impacts until at least the end of the 21st century. However, these have not taken into account the additional hazard of wave-driven overwash or its impact on freshwater availability. We project the impact of sea-level rise and wave-driven flooding on atoll infrastructure and freshwater availability under a variety of climate change scenarios. We show that, on the basis of current greenhouse gas emission rates, the nonlinear interactions between sea-level rise and wave dynamics over reefs will lead to the annual wave-driven overwash of most atoll islands by the mid-21st century. This annual flooding will result in the islands becoming uninhabitable because of frequent damage to infrastructure and the inability of their freshwater aquifers to recover between overwash events. This study provides critical information for understanding the timing and magnitude of climate change impacts on atoll islands that will result in significant, unavoidable geopolitical issues if it becomes necessary to abandon and relocate low-lying island states.</span></p>","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aap9741","usgsCitation":"Storlazzi, C.D., Gingerich, S.B., van Dongeren, A., Cheriton, O.M., Swarzenski, P.W., Quataert, E., Voss, C.I., Field, D.W., Annamalai, H., Piniak, G.A., and McCall, R.T., 2018, Most atolls will be uninhabitable by the mid-21st century because of sea-level rise exacerbating wave-driven flooding: Science Advances, v. 4, no. 4, p. 1-9, https://doi.org/10.1126/sciadv.aap9741.","productDescription":"eaap9741; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-091317","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468808,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aap9741","text":"Publisher Index Page"},{"id":437933,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VD6XDB","text":"USGS data release","linkHelpText":"Projected flood water depths on Roi-Namur, Kwajalein Atoll, Republic of the Marshall Islands"},{"id":353726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe4a","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gingerich, Stephen B. 0000-0002-4381-0746 sbginger@usgs.gov","orcid":"https://orcid.org/0000-0002-4381-0746","contributorId":1426,"corporation":false,"usgs":true,"family":"Gingerich","given":"Stephen","email":"sbginger@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Dongeren, Ap","contributorId":149002,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":734023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":189823,"corporation":false,"usgs":false,"family":"Swarzenski","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":734025,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quataert, Ellen","contributorId":193834,"corporation":false,"usgs":false,"family":"Quataert","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":734026,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":734027,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Field, Donald W.","contributorId":204460,"corporation":false,"usgs":false,"family":"Field","given":"Donald","email":"","middleInitial":"W.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":734028,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Annamalai, Hariharasubramanian","contributorId":204461,"corporation":false,"usgs":false,"family":"Annamalai","given":"Hariharasubramanian","email":"","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":734029,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Piniak, Greg A.","contributorId":204462,"corporation":false,"usgs":false,"family":"Piniak","given":"Greg","email":"","middleInitial":"A.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":734030,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McCall, Robert T.","contributorId":148986,"corporation":false,"usgs":false,"family":"McCall","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":734031,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70196701,"text":"70196701 - 2018 - Slow and steady wins the race? Future climate and land use change leaves the imperiled Blanding's turtle (Emydoidea blandingii) behind","interactions":[],"lastModifiedDate":"2018-04-26T11:15:01","indexId":"70196701","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Slow and steady wins the race? Future climate and land use change leaves the imperiled Blanding's turtle (<i>Emydoidea blandingii</i>) behind","title":"Slow and steady wins the race? Future climate and land use change leaves the imperiled Blanding's turtle (Emydoidea blandingii) behind","docAbstract":"<p><span>Climate change is accompanied by shifts in species distributions, as portions of current ranges become less suitable. Maintaining or improving landscape connectivity to facilitate species movements is a primary approach to mitigate the effects of climate change on biodiversity. However, it is not clear how ongoing changes in land use and climate may affect the existing connectivity of landscapes. We evaluated shifts in habitat suitability and connectivity for the imperiled Blanding's turtle (</span><i>Emydoidea blandingii</i><span>) in Wisconsin using species distribution modeling in combination with different future scenarios of both<span> land use change</span><span>&nbsp;</span>and climate change for the 2050s. We found that climate change had significant effects on both habitat suitability and connectivity, however, there was little difference in the magnitude of effects among different economic scenarios. Under both our low- and high-CO</span><sub>2</sub><span><span><span>&nbsp;</span>emissions scenarios, suitable habitat for the Blanding's turtle shifted northward. In the high-emissions scenario, almost no suitable habitat remained for Blanding's turtle in Wisconsin by the 2050s and there was up to a 100,000-fold increase in landscape resistance to turtle movement, suggesting the landscape essentially becomes impassable.<span> Habitat loss</span><span>&nbsp;</span>and landscape resistance were exponentially greater in southern versus northern Wisconsin, indicating a strong<span> trailing edge</span></span><span>&nbsp;</span>effect. Thus, populations at the southern edge of the range are likely to “fall behind” shifts in suitable habitat faster than northern populations. Given its limited dispersal capability, loss of suitable habitat may occur at a rate far faster than the Blanding's turtle can adjust to changing conditions via shifts in range.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.03.026","usgsCitation":"Hamilton, C.M., Bateman, B.L., Gorzo, J.M., Reid, B., Thogmartin, W.E., Peery, M.Z., Heglund, P.J., Radeloff, V.C., and Pidgeon, A.M., 2018, Slow and steady wins the race? Future climate and land use change leaves the imperiled Blanding's turtle (Emydoidea blandingii) behind: Biological Conservation, v. 222, p. 75-85, https://doi.org/10.1016/j.biocon.2018.03.026.","productDescription":"11 p.","startPage":"75","endPage":"85","ipdsId":"IP-088117","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2018.03.026","text":"Publisher Index Page"},{"id":353727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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