{"pageNumber":"646","pageRowStart":"16125","pageSize":"25","recordCount":184884,"records":[{"id":70228374,"text":"70228374 - 2020 - The geometry of reaction norms yields insights on classical fitness functions for Great Lakes salmon","interactions":[],"lastModifiedDate":"2022-02-09T16:51:48.728377","indexId":"70228374","displayToPublicDate":"2020-03-16T10:42:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The geometry of reaction norms yields insights on classical fitness functions for Great Lakes salmon","docAbstract":"<p>Life history theory examines how characteristics of organisms, such as age and size at maturity, may vary through natural selection as evolutionary responses that optimize fitness. Here we ask how predictions of age and size at maturity differ for the three classical fitness functions–intrinsic rate of natural increase<span>&nbsp;</span><i>r</i>, net reproductive rate<span>&nbsp;</span><i>R</i><sub>0</sub>, and reproductive value<span>&nbsp;</span><i>V</i><sub><i>x</i></sub>−for semelparous species. We show that different choices of fitness functions can lead to very different predictions of species behavior. In one’s efforts to understand an organism’s behavior and to develop effective conservation and management policies, the choice of fitness function matters. The central ingredient of our approach is the maturation reaction norm (MRN), which describes how optimal age and size at maturation vary with growth rate or mortality rate. We develop a practical geometric construction of MRNs that allows us to include different growth functions (linear growth and nonlinear von Bertalanffy growth in length) and develop two-dimensional MRNs useful for quantifying growth-mortality trade-offs. We relate our approach to Beverton-Holt life history invariants and to the Stearns-Koella categorization of MRNs. We conclude with a detailed discussion of life history parameters for Great Lakes Chinook Salmon and demonstrate that age and size at maturity are consistent with predictions using<span>&nbsp;</span><i>R</i><sub>0</sub><span>&nbsp;</span>(but not<span>&nbsp;</span><i>r</i><span>&nbsp;</span>or<span>&nbsp;</span><i>V</i><sub><i>x</i></sub>) as the underlying fitness function.</p>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0228990","usgsCitation":"Breck, J.E., Simon, C.P., Rutherford, E.S., Low, B.S., Lamberson, P.J., and Rogers, M.W., 2020, The geometry of reaction norms yields insights on classical fitness functions for Great Lakes salmon: PLoS ONE, v. 15, no. 3, p. 1-35, https://doi.org/10.1371/journal.pone.0228990.","productDescription":"e0228990, 35 p.","startPage":"1","endPage":"35","ipdsId":"IP-111222","costCenters":[{"id":198,"text":"Coop Res Unit 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S.","contributorId":189289,"corporation":false,"usgs":false,"family":"Low","given":"Bobbi","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":834014,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lamberson, P. J.","contributorId":275342,"corporation":false,"usgs":false,"family":"Lamberson","given":"P.","email":"","middleInitial":"J.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":834015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rogers, Mark W. 0000-0001-7205-5623","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":245525,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834016,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70212618,"text":"70212618 - 2020 - Pavement alters delivery of sediment and fallout radionuclides to urbanstreams","interactions":[],"lastModifiedDate":"2020-08-24T15:59:04.913792","indexId":"70212618","displayToPublicDate":"2020-03-16T09:48:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Pavement alters delivery of sediment and fallout radionuclides to urbanstreams","docAbstract":"<div id=\"ab015\" class=\"abstract author\" lang=\"en\"><div id=\"as015\"><p id=\"sp0015\"><span>Sediment from urban impervious surfaces has the potential to be an important vector for contaminants, particularly where stormwater culverts and other buried channels draining large impervious areas exit from underground pipes into open channels. To better understand urban sediment sources and their relation to fallout radionuclides, we collected samples of rainfall, urban sediment (pavement sediment, topsoil), streambank sediment, and fluvial sediment (suspended sediment and bed sediment) for&nbsp;</span><sup>7</sup><span>Be,&nbsp;</span><sup>210</sup><span>Pb</span><sub>ex</sub><span>, and&nbsp;</span><sup>137</sup><span>Cs analysis. The results indicate that each rainfall event tags pavement sediment with elevated activities of&nbsp;</span><sup>7</sup><span>Be and&nbsp;</span><sup>210</sup><span>Pb</span><sub>ex</sub><span>&nbsp;such that runoff from impervious surfaces in the buried channel part of the stream network contains the highest activities. Pavement sediment, because it is characteristically a thin veneer, has a small mass to rainwater ratio resulting in a greater tagging of&nbsp;</span><sup>7</sup><span>Be and&nbsp;</span><sup>210</sup><span>Pb</span><sub>ex</sub><span>&nbsp;activity than does topsoil on a per gram basis. An unmixing model indicated that suspended-sediment samples collected at the culvert outlet from the buried-channel network are from pavement sediment sources (45&nbsp;±&nbsp;25%) with a smaller component of topsoil (22&nbsp;±&nbsp;19%), and a component from streambanks (32&nbsp;±&nbsp;35%) that we infer to be older channel material and subsoil eroded from within the culvert system. Downstream from the culvert, suspended sediment collected from the open-channel parts of the stream had&nbsp;</span><sup>7</sup><span>Be and&nbsp;</span><sup>210</sup><span>Pb</span><sub>ex</sub><span>&nbsp;activities that were substantially reduced by the contribution of sediment from streambanks (57&nbsp;±&nbsp;15%), with pavement contributions decreasing to 15 (±9%) and topsoil contributing 28 (±7%). The results highlight the utility of&nbsp;</span><sup>7</sup><span>Be,&nbsp;</span><sup>210</sup><span>Pb</span><sub>ex</sub><span>, and&nbsp;</span><sup>137</sup><span>Cs as tracers of urban sediment sources, resulting in a unique radionuclide signature for urban watersheds compared to other sediment-source settings.</span></p></div></div><div id=\"ab005\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.124855","usgsCitation":"Gellis, A.C., Fuller, C.C., Van Metre, P.C., Mahler, B., Welty, C., Miller, A., Nibert, L.A., Clifton, Z.J., Malen, J., and Kemper, J., 2020, Pavement alters delivery of sediment and fallout radionuclides to urbanstreams: Journal of Hydrology, v. 588, 124855, 13 p., https://doi.org/10.1016/j.jhydrol.2020.124855.","productDescription":"124855, 13 p.","ipdsId":"IP-114470","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":457362,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2020.124855","text":"Publisher Index Page"},{"id":377799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","city":"Baltimore","otherGeospatial":"Dead Run","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.7164134979248,\n              39.30043202393245\n            ],\n            [\n              -76.70843124389647,\n              39.30043202393245\n            ],\n            [\n              -76.70843124389647,\n              39.309929271979534\n            ],\n            [\n              -76.7164134979248,\n              39.309929271979534\n            ],\n            [\n              -76.7164134979248,\n              39.30043202393245\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"588","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":797118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":797119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welty, C.","contributorId":82506,"corporation":false,"usgs":true,"family":"Welty","given":"C.","email":"","affiliations":[],"preferred":false,"id":797121,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Andrew","contributorId":200717,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew","affiliations":[],"preferred":false,"id":797122,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nibert, Lucas A 0000-0003-3542-1596","orcid":"https://orcid.org/0000-0003-3542-1596","contributorId":223438,"corporation":false,"usgs":false,"family":"Nibert","given":"Lucas","email":"","middleInitial":"A","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":797123,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clifton, Zachary J. 0000-0002-8148-5454","orcid":"https://orcid.org/0000-0002-8148-5454","contributorId":220551,"corporation":false,"usgs":true,"family":"Clifton","given":"Zachary","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797124,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Malen, Jeremy 0000-0001-9455-0182","orcid":"https://orcid.org/0000-0001-9455-0182","contributorId":223437,"corporation":false,"usgs":true,"family":"Malen","given":"Jeremy","email":"","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797125,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kemper, J.T.","contributorId":239541,"corporation":false,"usgs":false,"family":"Kemper","given":"J.T.","affiliations":[{"id":47904,"text":"Colorado State University, Warner College of Natural Resources, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":797126,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70210825,"text":"70210825 - 2020 - Ecology of influenza A viruses in wild birds and wetlands of Alaska","interactions":[],"lastModifiedDate":"2020-06-29T13:21:04.561218","indexId":"70210825","displayToPublicDate":"2020-03-16T09:41:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":948,"text":"Avian Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Ecology of influenza A viruses in wild birds and wetlands of Alaska","docAbstract":"Alaska represents a globally important region for the ecology of avian-origin influenza A viruses (IAVs) given expansive wetlands in this region which serve as habitat for numerous hosts of IAVs that disperse among four continents during the annual cycle.  Extensive sampling of wild birds for IAVs in Alaska since 1991 has greatly extended inference regarding intercontinental viral exchange between North America and East Asia and the importance of Beringian endemic species to IAV ecology within this region.  Data on IAVs in aquatic birds inhabiting Alaska has also been useful for helping to establish global patterns of prevalence in wild birds and viral dispersal across the landscape.  In this review, we summarize main findings from investigations of IAVs in wild birds and wetlands of Alaska with the aim of providing readers with an understanding of viral ecology within this region.  More specifically, we review viral detections, evidence of IAV exposure, and genetic characterization of isolates derived from wild bird samples collected in Alaska by host taxonomy.  Additionally, we provide a short overview of wetland complexes within Alaska that may be important to IAV ecology at the continental scale.","language":"English","publisher":"BioOne","doi":"10.1637/0005-2086-64.2.109","usgsCitation":"Ramey, A.M., and Reeves, A.B., 2020, Ecology of influenza A viruses in wild birds and wetlands of Alaska: Avian Diseases, v. 64, no. 2, p. 109-122, https://doi.org/10.1637/0005-2086-64.2.109.","productDescription":"14 p.","startPage":"109","endPage":"122","ipdsId":"IP-114972","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":375950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -147.568359375,\n              65.05360170595502\n            ],\n            [\n              -164.1796875,\n              64.16810689799152\n            ],\n            [\n              -167.4755859375,\n              60.1524422143808\n            ],\n            [\n              -164.794921875,\n              54.41892996865827\n            ],\n            [\n              -154.0283203125,\n              56.559482483762245\n            ],\n            [\n              -143.8330078125,\n              60.108670463036\n            ],\n            [\n              -147.568359375,\n              65.05360170595502\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"64","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":791604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":791605,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209125,"text":"70209125 - 2020 - Methylmercury-Total mercury ratios in predator and primary consumer insects from Adirondack streams (New York, USA)","interactions":[],"lastModifiedDate":"2020-11-13T15:38:58.090262","indexId":"70209125","displayToPublicDate":"2020-03-16T07:08:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Methylmercury-Total mercury ratios in predator and primary consumer insects from Adirondack streams (New York, USA)","docAbstract":"<p><span>Mercury (Hg) is a global pollutant that affects biota in remote settings due to atmospheric deposition of inorganic Hg, and its conversion to methylmercury (MeHg), the bioaccumulating and toxic form. Characterizing biotic MeHg is important for evaluating aquatic ecosystem responses to changes in Hg inputs. Aquatic insects possess many qualities desired for MeHg biomonitoring, but are not widely used, largely because of limited information regarding percentages of total mercury (THg) composed of MeHg (i.e., MeHg%) in various taxa. Here, we examine taxonomic, spatial, and seasonal variation in MeHg% of stream-dwelling predator and primary-consumer insects from nine streams in the Adirondack region (NY, USA). Predator MeHg% was high (median 94%) and did not differ significantly among five taxa. MeHg% in selected dragonflies (the most abundant predators, Odonata: Aeshnidae and Libellulidae) exhibited little seasonal and spatial variation, and THg concentration was strongly correlated with aqueous (filtered) MeHg (FMeHg; r</span><sub>s</sub><span> = 0.76). In contrast, MeHg% in primary consumers—shredders (northern caddisflies [Trichoptera: Limnephilidae]) and scrapers (flathead mayflies [Ephemeroptera: Heptageniidae]), were lower (medians 52% and 35%, respectively), and differed significantly between taxa, among sites, and seasonally. Correlations of THg with FMeHg were weak (shredders, r</span><sub>s</sub><span> = 0.45, p = 0.09) or not significant (scrapers, p = 0.89). The higher MeHg% of predators corresponded with their higher trophic positions (indicated by nitrogen stable isotopes). Results suggest obligate predators hold the most promise for the use of THg as a surrogate for MeHg biomonitoring with aquatic insects within the Adirondack region.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10646-020-02191-7","usgsCitation":"Riva-Murray, K., Bradley, P., and Brigham, M.E., 2020, Methylmercury-Total mercury ratios in predator and primary consumer insects from Adirondack streams (New York, USA): Ecotoxicology, v. 29, https://doi.org/10.1007/s10646-020-02191-7.","productDescription":"15 p.","startPage":"1658","ipdsId":"IP-086907","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":373331,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Adirondack Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.35498046875,\n              42.827638636242284\n            ],\n            [\n              -73.2568359375,\n              42.827638636242284\n            ],\n            [\n              -73.2568359375,\n              45.24395342262324\n            ],\n            [\n              -76.35498046875,\n              45.24395342262324\n            ],\n            [\n              -76.35498046875,\n              42.827638636242284\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"29","edition":"1644","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":168876,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785017,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70228662,"text":"70228662 - 2020 - The effects of swimming exercise and dissolved oxygen on growth performance, fin condition and survival of rainbow trout Oncorhynchus mykiss","interactions":[],"lastModifiedDate":"2022-03-11T16:34:08.740184","indexId":"70228662","displayToPublicDate":"2020-03-15T11:24:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":857,"text":"Aquaculture Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The effects of swimming exercise and dissolved oxygen on growth performance, fin condition and survival of rainbow trout <i>Oncorhynchus mykiss</i>","title":"The effects of swimming exercise and dissolved oxygen on growth performance, fin condition and survival of rainbow trout Oncorhynchus mykiss","docAbstract":"<p><span>Swimming exercise and dissolved oxygen (DO) are important parameters to consider when operating intensive salmonid aquaculture facilities. While previous research has focused on each of these two variables in rainbow trout&nbsp;</span><i>Oncorhynchus mykiss</i><span>, studies examining both variables in combination, and their potential interaction, are absent from the scientific literature. Both swimming exercise (usually measured in body lengths per second, or BL/s) and DO can be readily controlled in modern aquaculture systems; therefore, we sought to evaluate the effects of these variables, separately and combined, on several outcomes in rainbow trout including growth performance, fin health and survival. Rainbow trout fry (18&nbsp;g) were stocked into 12 circular 0.5&nbsp;m</span><sup>3</sup><span>&nbsp;tanks, provided with either high (1.5–2&nbsp;BL/s) or low (approximately 0.5&nbsp;BL/s) swimming exercise and high (100% saturation) or low (70% saturation) DO, and grown to approximately 1&nbsp;kg. By the conclusion of the study, higher DO was independently associated with significantly (</span><i>p</i><span>&nbsp;&lt;&nbsp;.05) increased growth performance. Significant differences were not noted in other outcomes, namely feed conversion, condition factor and mortality, although caudal and right pectoral fin damage was associated with low oxygen and low swimming exercise treatments respectively. Cardiosomatic index was significantly higher among exercised fish. These results suggest that swimming exercise and DO at saturation during the culture of rainbow trout can be beneficial to producers through improved growth performance and cardiac health.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/are.14600","usgsCitation":"Waldrop, T., Summerfelt, S., Mazik, P.M., Kenney, P.B., and Good, C., 2020, The effects of swimming exercise and dissolved oxygen on growth performance, fin condition and survival of rainbow trout Oncorhynchus mykiss: Aquaculture Research, v. 51, no. 6, p. 2582-2589, https://doi.org/10.1111/are.14600.","productDescription":"8 p.","startPage":"2582","endPage":"2589","ipdsId":"IP-113465","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":457365,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/are.14600","text":"Publisher Index Page"},{"id":397025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Waldrop, Thomas","contributorId":279449,"corporation":false,"usgs":false,"family":"Waldrop","given":"Thomas","affiliations":[{"id":33606,"text":"The Conservation Fund Freshwater Institute","active":true,"usgs":false}],"preferred":false,"id":834953,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Summerfelt, Steven","contributorId":279450,"corporation":false,"usgs":false,"family":"Summerfelt","given":"Steven","affiliations":[{"id":33606,"text":"The Conservation Fund Freshwater Institute","active":true,"usgs":false}],"preferred":false,"id":834954,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834952,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kenney, P. Brett","contributorId":279452,"corporation":false,"usgs":false,"family":"Kenney","given":"P.","email":"","middleInitial":"Brett","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":834955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Good, Christopher","contributorId":279454,"corporation":false,"usgs":false,"family":"Good","given":"Christopher","affiliations":[{"id":33606,"text":"The Conservation Fund Freshwater Institute","active":true,"usgs":false}],"preferred":false,"id":834956,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70210136,"text":"70210136 - 2020 - North Carolina State climate report","interactions":[],"lastModifiedDate":"2020-05-15T14:30:20.518142","indexId":"70210136","displayToPublicDate":"2020-03-15T09:27:17","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"North Carolina State climate report","docAbstract":"Our scientific understanding of the climate system strongly supports the conclusion that North Carolina’s climate has changed in recent decades and the expectation that large changes—much larger than at any time in the state’s history—will occur if current trends in greenhouse gas concentrations continue. Even under a scenario where emissions peak around 2050 and decline thereafter, North Carolina will experience substantial changes in climate. The projected changes with the highest level of scientific confidence include increases in temperature, increases in summer absolute humidity, increases in sea level, and increases in extreme precipitation. It is also likely that there will be increases in the intensity of the strongest hurricanes. \nA full appreciation for past and future changes in North Carolina’s climate requires a global perspective. Earth’s climate has warmed substantially since the late 19th century, with most of that warming occurring in the last 50 years. This warming trend is clear from global temperature records and many other indicators, including rising global sea levels and rapid decreases in arctic sea ice cover. Scientists have very high confidence that this warming is largely due to human activities that have significantly increased atmospheric concentrations of carbon dioxide (CO2) and other greenhouse gases. Exhaustive research has examined other potential causes of this warming, and the increase in greenhouse gas concentrations is the only plausible cause that is consistent with the observed data and the physics that governs the climate system.","language":"English","publisher":"NCICS","collaboration":"North Carolina State University, NC Department of Environmental Quality","usgsCitation":"Kunkel, K.E., Easterling, D.R., Ballinger, A., Bililign, S., Champion, S., Corbett, D.R., Dello, K., Dissen, J., Kossin, J.P., Lackmann, G., Luettich, R., Perry, B., Robinson, W., Stevens, L.E., Stewart, B.C., and Terando, A., 2020, North Carolina State climate report, 236 p,.","productDescription":"236 p,","ipdsId":"IP-115496","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":374872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":374858,"type":{"id":15,"text":"Index 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Edinburgh","active":true,"usgs":false}],"preferred":false,"id":789253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bililign, Solomon","contributorId":224721,"corporation":false,"usgs":false,"family":"Bililign","given":"Solomon","affiliations":[{"id":40925,"text":"North Carolina A&T University","active":true,"usgs":false}],"preferred":false,"id":789254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Champion, Sarah M","contributorId":224722,"corporation":false,"usgs":false,"family":"Champion","given":"Sarah M","affiliations":[{"id":25510,"text":"NC State University","active":true,"usgs":false}],"preferred":false,"id":789255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corbett, D Reide 0000-0001-9205-8362","orcid":"https://orcid.org/0000-0001-9205-8362","contributorId":218739,"corporation":false,"usgs":false,"family":"Corbett","given":"D","email":"","middleInitial":"Reide","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":789256,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dello, Kathie","contributorId":224723,"corporation":false,"usgs":false,"family":"Dello","given":"Kathie","email":"","affiliations":[{"id":25510,"text":"NC State University","active":true,"usgs":false}],"preferred":false,"id":789257,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dissen, Jenny","contributorId":224724,"corporation":false,"usgs":false,"family":"Dissen","given":"Jenny","email":"","affiliations":[{"id":25510,"text":"NC State University","active":true,"usgs":false}],"preferred":false,"id":789258,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kossin, James P. 0000-0003-0461-9794","orcid":"https://orcid.org/0000-0003-0461-9794","contributorId":212208,"corporation":false,"usgs":false,"family":"Kossin","given":"James","email":"","middleInitial":"P.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric 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University","active":true,"usgs":false}],"preferred":false,"id":789262,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Robinson, Walter","contributorId":224728,"corporation":false,"usgs":false,"family":"Robinson","given":"Walter","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":789263,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stevens, Laura E. 0000-0002-8842-702X","orcid":"https://orcid.org/0000-0002-8842-702X","contributorId":205981,"corporation":false,"usgs":false,"family":"Stevens","given":"Laura","email":"","middleInitial":"E.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":789264,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Stewart, Brooke C.","contributorId":195288,"corporation":false,"usgs":false,"family":"Stewart","given":"Brooke","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":789265,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Terando, Adam 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":205908,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":789266,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70228573,"text":"70228573 - 2020 - Investigation of bed and den site selection by American black bears (Ursus americanus) in a landscape impacted by forest restoration treatments and wildfires","interactions":[],"lastModifiedDate":"2022-02-14T15:33:01.949286","indexId":"70228573","displayToPublicDate":"2020-03-15T09:19:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Investigation of bed and den site selection by American black bears (<i>Ursus americanus</i>) in a landscape impacted by forest restoration treatments and wildfires","title":"Investigation of bed and den site selection by American black bears (Ursus americanus) in a landscape impacted by forest restoration treatments and wildfires","docAbstract":"<p id=\"sp0010\">The combined effects of long-term fire suppression, logging, and overgrazing have negatively impacted many southwestern U.S. forests, resulting in decreased habitat quality for wildlife, and more frequent and severe wildfires. In response, land management agencies are implementing large-scale forest restoration treatments, but data on how wildlife respond to restoration treatments and wildfires are often limited. We investigated bed and den site selection of American black bears (<i>Ursus americanus</i>) using GPS location data and a use/available study design to assess the influence of habitat characteristics, including wildfires, prescribed burns, and thinning treatments on bed and den site selection in the Jemez Mountains, New Mexico. The most supported models suggested that black bears were more likely to select bed sites with a combination of low horizontal visibility (<i>β</i>&nbsp;=&nbsp;−0.007, SE&nbsp;=&nbsp;0.002;<span>&nbsp;</span><i>P</i>&nbsp;=&nbsp;0.002) and high stand basal area (<i>β</i>&nbsp;=&nbsp;0.013, SE&nbsp;=&nbsp;0.005;<span>&nbsp;</span><i>P</i>&nbsp;=&nbsp;0.004). The highest-ranking model for den site selection indicated that black bears were more likely to select den sites with low horizontal visibility (<i>β</i>&nbsp;=&nbsp;−0.0102, SE&nbsp;=&nbsp;0.004;<span>&nbsp;</span><i>P</i>&nbsp;=&nbsp;0.006). Black bears used all disturbed sites to varying degrees (45% of study area), although 48% of bed sites were located in undisturbed habitat (55% of study area) while only 11% and 2% of bed sites were located in thinned and prescribed burn sites, respectively. Thirty-nine percent of bed sites were located in previous wildfire locations; however, 67% of these sites were in areas with low burn severity. Thirty-eight percent of den sites were located in previously disturbed habitat, 8 of these sites were burned by wildfires. In order to develop effective management plans for black bears, it is essential to understand responses to landscape-scale habitat disturbances due to wildfires and restoration activities, all of which are becoming more prevalent and widespread across southwestern forests. Accounting for the timing, size, and proximity of future restoration efforts would aid in mitigating potential short-term negative effects on black bears.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2020.117904","usgsCitation":"Bard, S.M., and Cain, J.W., 2020, Investigation of bed and den site selection by American black bears (Ursus americanus) in a landscape impacted by forest restoration treatments and wildfires: Forest Ecology and Management, v. 460, p. 1-11, https://doi.org/10.1016/j.foreco.2020.117904.","productDescription":"117904, 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-112372","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457367,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1595500","text":"Publisher Index Page"},{"id":395886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Collaborative Forest Landscape Restoration Program area, Jemez Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.67587280273438,\n              35.65004306288284\n            ],\n            [\n              -106.67587280273438,\n              35.622698214535184\n            ],\n            [\n              -106.62506103515625,\n              35.623256366178964\n            ],\n            [\n              -106.42936706542969,\n              35.85455268869835\n            ],\n            [\n              -106.39503479003906,\n              35.85343961959182\n            ],\n            [\n              -106.39022827148438,\n              36.00800626603582\n            ],\n            [\n              -106.62368774414062,\n              36.00911716117325\n            ],\n            [\n              -106.68960571289062,\n              35.884043325566886\n            ],\n            [\n              -106.86882019042969,\n              35.879592612012026\n            ],\n            [\n              -106.86744689941405,\n              35.821153818963175\n            ],\n            [\n              -106.85714721679688,\n              35.8217105820067\n            ],\n            [\n              -106.85302734374999,\n              35.649485098277204\n            ],\n            [\n              -106.67587280273438,\n              35.65004306288284\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"460","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bard, Susan M.","contributorId":264967,"corporation":false,"usgs":false,"family":"Bard","given":"Susan","email":"","middleInitial":"M.","affiliations":[{"id":27575,"text":"NMSU","active":true,"usgs":false}],"preferred":false,"id":834645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834644,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209101,"text":"70209101 - 2020 - Methodology for estimating the prospective CO2 storage resource of residual oil zones at the national and regional scale","interactions":[],"lastModifiedDate":"2020-03-16T16:52:49","indexId":"70209101","displayToPublicDate":"2020-03-14T16:47:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2049,"text":"International Journal of Greenhouse Gas Control","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Methodology for estimating the prospective CO<sub>2</sub> storage resource of residual oil zones at the national and regional scale","title":"Methodology for estimating the prospective CO2 storage resource of residual oil zones at the national and regional scale","docAbstract":"<p><span>Residual oil zones (ROZs) are increasingly gaining interest as potential reservoirs for carbon dioxide (CO</span><sub>2</sub><span>) storage. Here, we present a national- and regional-scale methodology for estimating prospective CO</span><sub>2</sub><span>&nbsp;storage resources in residual oil zones. This methodology uses a volumetric equation that accounts for CO</span><sub>2</sub><span>&nbsp;storage as a free phase in pore space and as a dissolved phase in oil and does not assume any oil production associated with CO</span><sub>2</sub><span>&nbsp;storage. Reservoir modeling and the CO</span><sub>2</sub><span>-SCREEN tool are used to demonstrate that CO</span><sub>2</sub><span>&nbsp;storage in residual oil zones will predominantly take place in the free phase (approximately 92–97%) with some storage as dissolution in oil (approximately 3–8 %). Based on this preliminary demonstration, the CO</span><sub>2</sub><span>&nbsp;storage efficiency for ROZs using this national- and regional-scale method ranges from 0.61 to 7.1 %. This range indicates ROZs have a similar efficiency potential for storing CO</span><sub>2</sub><span>&nbsp;as deep saline formations (0.51–5.4 %).</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijggc.2020.103006","usgsCitation":"Sanguinito, S., Singh, H., Myshakin, E.M., Goodman, A.L., Dilmore, R.M., Grant, T.C., Morgan, D., Bromhal, G., Warwick, P., Brennan, S.T., Freeman, P., Karacan, C.O., Gorecki, C., Peck, W., Burton-Kelly, M., Dotzenrod, N., Frailey, S., and Pawar, R., 2020, Methodology for estimating the prospective CO2 storage resource of residual oil zones at the national and regional scale: International Journal of Greenhouse Gas Control, v. 96, 103006, 8 p., https://doi.org/10.1016/j.ijggc.2020.103006.","productDescription":"103006, 8 p.","ipdsId":"IP-108213","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":457370,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1780239","text":"Publisher Index Page"},{"id":373301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sanguinito, Sean 0000-0001-8096-4288","orcid":"https://orcid.org/0000-0001-8096-4288","contributorId":223389,"corporation":false,"usgs":false,"family":"Sanguinito","given":"Sean","email":"","affiliations":[{"id":40707,"text":"Leidos Research Support Team, United States Department of Energy, National Energy Technology Laboratory","active":true,"usgs":false}],"preferred":false,"id":784928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Singh, Harpreet","contributorId":223390,"corporation":false,"usgs":false,"family":"Singh","given":"Harpreet","email":"","affiliations":[{"id":40708,"text":"United States Department of Energy, National Energy Technology Laboratory","active":true,"usgs":false}],"preferred":false,"id":784929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Myshakin, Evgeniy M.","contributorId":220813,"corporation":false,"usgs":false,"family":"Myshakin","given":"Evgeniy","email":"","middleInitial":"M.","affiliations":[{"id":40277,"text":"U.S. Department of Energy","active":true,"usgs":false}],"preferred":false,"id":784930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goodman, Angela L.","contributorId":223391,"corporation":false,"usgs":false,"family":"Goodman","given":"Angela","email":"","middleInitial":"L.","affiliations":[{"id":40708,"text":"United States Department of Energy, National Energy Technology Laboratory","active":true,"usgs":false}],"preferred":false,"id":784931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dilmore, Robert M.","contributorId":223392,"corporation":false,"usgs":false,"family":"Dilmore","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":40708,"text":"United States Department of Energy, National Energy Technology Laboratory","active":true,"usgs":false}],"preferred":false,"id":784932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grant, Timothy C.","contributorId":223393,"corporation":false,"usgs":false,"family":"Grant","given":"Timothy","email":"","middleInitial":"C.","affiliations":[{"id":40708,"text":"United States Department of Energy, National Energy Technology Laboratory","active":true,"usgs":false}],"preferred":false,"id":784933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morgan, David","contributorId":223394,"corporation":false,"usgs":false,"family":"Morgan","given":"David","affiliations":[{"id":40708,"text":"United States Department of Energy, National Energy Technology 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Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":208012,"corporation":false,"usgs":false,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[],"preferred":false,"id":784938,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Gorecki, Charles","contributorId":223395,"corporation":false,"usgs":false,"family":"Gorecki","given":"Charles","email":"","affiliations":[{"id":40709,"text":"Energy & Environmental Research Center, University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":784939,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Peck, Wesley","contributorId":223396,"corporation":false,"usgs":false,"family":"Peck","given":"Wesley","email":"","affiliations":[{"id":40709,"text":"Energy & Environmental Research Center, University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":784940,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Burton-Kelly, Matthew","contributorId":223397,"corporation":false,"usgs":false,"family":"Burton-Kelly","given":"Matthew","email":"","affiliations":[{"id":40709,"text":"Energy & Environmental Research Center, University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":784941,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Dotzenrod, Neil","contributorId":223398,"corporation":false,"usgs":false,"family":"Dotzenrod","given":"Neil","email":"","affiliations":[{"id":40709,"text":"Energy & Environmental Research Center, University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":784942,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Frailey, Scott","contributorId":177268,"corporation":false,"usgs":false,"family":"Frailey","given":"Scott","email":"","affiliations":[],"preferred":false,"id":784943,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Pawar, Rajesh 0000-0003-1422-7532","orcid":"https://orcid.org/0000-0003-1422-7532","contributorId":223399,"corporation":false,"usgs":false,"family":"Pawar","given":"Rajesh","email":"","affiliations":[{"id":37625,"text":"Earth and Environmental Sciences Division, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":784944,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70209447,"text":"70209447 - 2020 - Validation of a screening method for the detection of colistin-resistant E. coli containing mcr-1 in feral swine feces","interactions":[],"lastModifiedDate":"2020-05-05T17:21:58.161449","indexId":"70209447","displayToPublicDate":"2020-03-14T07:28:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2390,"text":"Journal of Microbiological Methods","active":true,"publicationSubtype":{"id":10}},"title":"Validation of a screening method for the detection of colistin-resistant E. coli containing mcr-1 in feral swine feces","docAbstract":"A method was developed and validated for the detection of colistin-resistant Escherichia coli containing mcr-1 in the feces of feral swine. Following optimization of an enrichment method using EC broth supplemented with colistin (1 µg/mL) and vancomycin (8 µg/mL), aliquots derived from 100 feral swine fecal samples were spiked with of one of five different mcr-1 positive E. coli strains (between 100 and 104 CFU/g), for a total of 1,110 samples tested. Enrichments were then screened using a simple boil-prep and a previously developed real-time PCR assay for mcr-1 detection. The sensitivity of the method was determined in swine feces, with mcr-1 E. coli inoculums of 0.1-9.99 CFU/g (n = 340), 10-49.99 CFU/g (n = 170), 50-99 CFU/g (n = 255), 100-149 CFU/g (n = 60), and 200-2,200 CFU/g (n = 175), which were detected with 32%, 72%, 88%, 95%, and 98% accuracy, respectively. Uninoculated controls (n = 100) were negative for mcr-1 following enrichment.","language":"English","publisher":"Elsevier ","doi":"10.1016/j.mimet.2020.105892","collaboration":"","usgsCitation":"Chandler, J.C., Franklin, A.B., Bevins, S.N., Bentler, K.T., Bonnedahl, J., Ahlstrom, C., Bisha, B., and Shriner, S.A., 2020, Validation of a screening method for the detection of colistin-resistant E. coli containing mcr-1 in feral swine feces: Journal of Microbiological Methods, v. 172, 105892, 5 p., https://doi.org/10.1016/j.mimet.2020.105892.","productDescription":"105892, 5 p.","ipdsId":"IP-114741","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":457373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.mimet.2020.105892","text":"Publisher Index Page"},{"id":373833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"172","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chandler, Jeffrey C","contributorId":223870,"corporation":false,"usgs":false,"family":"Chandler","given":"Jeffrey","email":"","middleInitial":"C","affiliations":[{"id":40781,"text":"USDA/APHIS/WS, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":786508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Franklin, Alan B.","contributorId":101999,"corporation":false,"usgs":false,"family":"Franklin","given":"Alan","email":"","middleInitial":"B.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":786509,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bevins, Sarah N.","contributorId":212845,"corporation":false,"usgs":false,"family":"Bevins","given":"Sarah","email":"","middleInitial":"N.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":786510,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bentler, Kevin T","contributorId":223871,"corporation":false,"usgs":false,"family":"Bentler","given":"Kevin","email":"","middleInitial":"T","affiliations":[{"id":40781,"text":"USDA/APHIS/WS, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":786511,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonnedahl, Jonas","contributorId":181800,"corporation":false,"usgs":false,"family":"Bonnedahl","given":"Jonas","email":"","affiliations":[],"preferred":false,"id":786512,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahlstrom, Christina 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":214540,"corporation":false,"usgs":true,"family":"Ahlstrom","given":"Christina","email":"","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":786513,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bisha, Bledar","contributorId":223872,"corporation":false,"usgs":false,"family":"Bisha","given":"Bledar","email":"","affiliations":[{"id":40782,"text":"Department of Animal Science, University of Wyoming,","active":true,"usgs":false}],"preferred":false,"id":786514,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shriner, Susan A.","contributorId":168690,"corporation":false,"usgs":false,"family":"Shriner","given":"Susan","email":"","middleInitial":"A.","affiliations":[{"id":13407,"text":"Colorado State Univ.","active":true,"usgs":false}],"preferred":false,"id":786515,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70209158,"text":"70209158 - 2020 - A 'weight of evidence' approach to evaluating structural equation models","interactions":[],"lastModifiedDate":"2020-03-19T19:09:47","indexId":"70209158","displayToPublicDate":"2020-03-13T19:08:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5943,"text":"One Ecosystem","active":true,"publicationSubtype":{"id":10}},"title":"A 'weight of evidence' approach to evaluating structural equation models","docAbstract":"It is possible that model selection has been the most researched and most discussed topic in the history of both statistics and structural equation modeling (SEM). The reason for this is because selecting one model for interpretive use from amongst many possible models is both essential and difficult. The published protocols and advice for model evaluation and selection in SEM studies are complex and difficult to integrate with current approaches used in biology. Opposition to the use of p-values and decision thresholds has been voiced by the statistics community, yet certain phases of model evaluation have been historically tied to reliance on p-values. In this paper, I outline an approach to model evaluation, comparison and selection based on a weight-of-evidence paradigm. The details and proposed sequence of steps are illustrated using a real-world example. At the end of the paper, I briefly discuss the current state of knowledge and a possible direction for future studies.","language":"English","publisher":"Pensoft Publisher","doi":"10.3897/oneeco.5.e50452","usgsCitation":"Grace, J., 2020, A 'weight of evidence' approach to evaluating structural equation models: One Ecosystem, v. 5, e50452, https://doi.org/10.3897/oneeco.5.e50452.","productDescription":"e50452","ipdsId":"IP-115758","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":457375,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/oneeco.5.e50452","text":"Publisher Index Page"},{"id":373395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Grace, James 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":219648,"corporation":false,"usgs":true,"family":"Grace","given":"James","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":785160,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70228651,"text":"70228651 - 2020 - Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty","interactions":[],"lastModifiedDate":"2022-02-16T18:02:33.912037","indexId":"70228651","displayToPublicDate":"2020-03-13T11:56:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty","docAbstract":"<p><span>Populations of invasive species often spread heterogeneously across a landscape, consisting of local populations that cluster in space but are connected by dispersal. A fundamental dilemma for invasive species control is how to optimally allocate limited fiscal resources across local populations. Theoretical work based on perfect knowledge of demographic connectivity suggests that targeting local populations from which migrants originate (sources) can be optimal. However, demographic processes such as abundance and dispersal can be highly uncertain, and the relationship between local population density and damage costs (damage function) is rarely known. We used a metapopulation model to understand how budget and uncertainty in abundance, connectivity, and the damage function, together impact return on investment (ROI) for optimal control strategies. Budget, observational uncertainty, and the damage function had strong effects on the optimal resource allocation strategy. Uncertainty in dispersal probability was the least important determinant of ROI. The damage function determined which resource prioritization strategy was optimal when connectivity was symmetric but not when it was asymmetric. When connectivity was asymmetric, prioritizing source populations had a higher ROI than allocating effort equally across local populations, regardless of the damage function, but uncertainty in connectivity structure and abundance reduced ROI of the optimal prioritization strategy by 57% on average depending on the control budget. With low budgets (monthly removal rate of 6.7% of population), there was little advantage to prioritizing resources, especially when connectivity was high or symmetric, and observational uncertainty had only minor effects on ROI. Allotting funding for improved monitoring appeared to be most important when budgets were moderate (monthly removal of 13–20% of the population). Our result showed that multiple sources of observational uncertainty should be considered concurrently for optimizing ROI. Accurate estimates of connectivity direction and abundance were more important than accurate estimates of dispersal rates. Developing cost-effective surveillance methods to reduce observational uncertainties, and quantitative frameworks for determining how resources should be spatially apportioned to multiple monitoring and control activities are important and challenging future directions for optimizing ROI for invasive species control programs.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/eap.2126","usgsCitation":"Pepin, K.M., Smyser, T.J., Davis, A., Miller, R., McKee, S., VerCauteren, K.C., Kendall, W.L., and Slootmaker, C., 2020, Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty: Ecological Applications, v. 30, no. 6, e02126, 15 p., https://doi.org/10.1002/eap.2126.","productDescription":"e02126, 15 p.","ipdsId":"IP-113401","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457377,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/812305","text":"External Repository"},{"id":396025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Pepin, Kim M.","contributorId":279406,"corporation":false,"usgs":false,"family":"Pepin","given":"Kim","email":"","middleInitial":"M.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smyser, Timothy J.","contributorId":279407,"corporation":false,"usgs":false,"family":"Smyser","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Amy J.","contributorId":279408,"corporation":false,"usgs":false,"family":"Davis","given":"Amy J.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ryan S.","contributorId":279409,"corporation":false,"usgs":false,"family":"Miller","given":"Ryan S.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKee, Sophie","contributorId":279410,"corporation":false,"usgs":false,"family":"McKee","given":"Sophie","email":"","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"VerCauteren, Kurt C.","contributorId":279413,"corporation":false,"usgs":false,"family":"VerCauteren","given":"Kurt","email":"","middleInitial":"C.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834938,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834932,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Slootmaker, Chris","contributorId":279414,"corporation":false,"usgs":false,"family":"Slootmaker","given":"Chris","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":834939,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70210755,"text":"70210755 - 2020 - Eradication of peste des petits ruminants and the wildlife-livestock interface","interactions":[],"lastModifiedDate":"2020-06-23T15:30:31.423094","indexId":"70210755","displayToPublicDate":"2020-03-13T10:24:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5720,"text":"Frontiers in Veterinary Science","onlineIssn":"2297-1769","active":true,"publicationSubtype":{"id":10}},"title":"Eradication of peste des petits ruminants and the wildlife-livestock interface","docAbstract":"<div class=\"JournalAbstract\"><p>Growing evidence suggests that multiple wildlife species can be infected with peste des petits ruminants virus (PPRV), with important consequences for the potential maintenance of PPRV in communities of susceptible hosts, and the threat that PPRV may pose to the conservation of wildlife populations and resilience of ecosystems. Significant knowledge gaps in the epidemiology of PPRV across the ruminant community (wildlife and domestic), and the understanding of infection in wildlife and other atypical host species groups (e.g., camelidae, suidae, and bovinae) hinder our ability to apply necessary integrated disease control and management interventions at the wildlife-livestock interface. Similarly, knowledge gaps limit the inclusion of wildlife in the FAO/OIE Global Strategy for the Control and Eradication of PPR, and the framework of activities in the PPR Global Eradication Programme that lays the foundation for eradicating PPR through national and regional efforts. This article reports on the first international meeting on, “Controlling PPR at the livestock-wildlife interface,” held in Rome, Italy, March 27–29, 2019. A large group representing national and international institutions discussed recent advances in our understanding of PPRV in wildlife, identified knowledge gaps and research priorities, and formulated recommendations. The need for a better understanding of PPRV epidemiology at the wildlife-livestock interface to support the integration of wildlife into PPR eradication efforts was highlighted by meeting participants along with the reminder that PPR eradication and wildlife conservation need not be viewed as competing priorities, but instead constitute two requisites of healthy socio-ecological systems.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fvets.2020.00050","usgsCitation":"Fine, A.E., Pruvot, M., Benfield, C., Caron, A., Cattoli, G., Chardonnet, P., Dioli, M., Dulu, T., Gilbert, M., Kock, R., Lubroth, J., Mariner, J., Ostrowski, S., Parida, S., Fereidouni, S., Shiilegdamba, E., Sleeman, J.M., Schultz, C., Soula, J., van der Stede, Y., Tekola, B.G., Walzer, C., Zuther, S., and Njeumi, F., 2020, Eradication of peste des petits ruminants and the wildlife-livestock interface: Frontiers in Veterinary Science, v. 7, 50, 8 p., https://doi.org/10.3389/fvets.2020.00050.","productDescription":"50, 8 p.","ipdsId":"IP-113135","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":457384,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fvets.2020.00050","text":"Publisher Index Page"},{"id":375816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2020-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Fine, Amanda E.","contributorId":225470,"corporation":false,"usgs":false,"family":"Fine","given":"Amanda","email":"","middleInitial":"E.","affiliations":[{"id":41133,"text":"1Wildlife Conservation Society, Health Program, Bronx, New York, USA","active":true,"usgs":false}],"preferred":false,"id":791273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pruvot, 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Maurizio","contributorId":225476,"corporation":false,"usgs":false,"family":"Dioli","given":"Maurizio","email":"","affiliations":[{"id":41136,"text":"Laboratory X , Institute X, Department X, Organization X, City X, State XX (only USA, Canada and Australia), Country","active":true,"usgs":false}],"preferred":false,"id":791279,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dulu, Thomas","contributorId":225477,"corporation":false,"usgs":false,"family":"Dulu","given":"Thomas","email":"","affiliations":[{"id":41137,"text":"Office International des Epizooties/World Animal Health Organization, Nairobi, Kenya","active":true,"usgs":false}],"preferred":false,"id":791280,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gilbert, Martin","contributorId":225478,"corporation":false,"usgs":false,"family":"Gilbert","given":"Martin","affiliations":[{"id":41138,"text":"College of Veterinary Medicine, Cornel University, Ithaca, NY, 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Jeffery","contributorId":225481,"corporation":false,"usgs":false,"family":"Mariner","given":"Jeffery","email":"","affiliations":[{"id":41140,"text":"Cummings School of Veterinary Medicine, Tufts University, Grafton, MA, USA","active":true,"usgs":false}],"preferred":false,"id":791284,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ostrowski, Stephane","contributorId":225482,"corporation":false,"usgs":false,"family":"Ostrowski","given":"Stephane","email":"","affiliations":[{"id":41133,"text":"1Wildlife Conservation Society, Health Program, Bronx, New York, USA","active":true,"usgs":false}],"preferred":false,"id":791285,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Parida, Satya","contributorId":225483,"corporation":false,"usgs":false,"family":"Parida","given":"Satya","email":"","affiliations":[{"id":41141,"text":"Pirbright Institute, Surrey, UK","active":true,"usgs":false}],"preferred":false,"id":791286,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Fereidouni, Sasan","contributorId":225484,"corporation":false,"usgs":false,"family":"Fereidouni","given":"Sasan","email":"","affiliations":[{"id":41142,"text":"Research Institute of Wildlife Ecology, University of Veterinary Medicine, Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":791287,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Shiilegdamba, Enkhtuvshin","contributorId":205122,"corporation":false,"usgs":false,"family":"Shiilegdamba","given":"Enkhtuvshin","email":"","affiliations":[],"preferred":false,"id":791288,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":791289,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Schultz, Claudia","contributorId":225485,"corporation":false,"usgs":false,"family":"Schultz","given":"Claudia","email":"","affiliations":[{"id":41143,"text":"Research Center for Emerging Infections and Zoonoses, University of Veterinary Medicine, Hannover, Germany","active":true,"usgs":false}],"preferred":false,"id":791290,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Soula, Jean-Jacques","contributorId":225486,"corporation":false,"usgs":false,"family":"Soula","given":"Jean-Jacques","email":"","affiliations":[{"id":41144,"text":"FAO-OIE PPR Secretariat, Food and Agriculture Organization of the United Nations, Rome, Italy","active":true,"usgs":false}],"preferred":false,"id":791291,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"van der Stede, Yves","contributorId":225487,"corporation":false,"usgs":false,"family":"van der Stede","given":"Yves","email":"","affiliations":[{"id":41145,"text":"European Food Safety Agency, Parma, Italy","active":true,"usgs":false}],"preferred":false,"id":791292,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Tekola, Berhe G.","contributorId":225488,"corporation":false,"usgs":false,"family":"Tekola","given":"Berhe","email":"","middleInitial":"G.","affiliations":[{"id":41146,"text":"Office of the Director, Animal Production and Health Division, Food and Agriculture Organization of the United Nations, Rome, Italy","active":true,"usgs":false}],"preferred":false,"id":791293,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Walzer, Chris","contributorId":225489,"corporation":false,"usgs":false,"family":"Walzer","given":"Chris","affiliations":[{"id":41133,"text":"1Wildlife Conservation Society, Health Program, Bronx, New York, USA","active":true,"usgs":false}],"preferred":false,"id":791294,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Zuther, Steffen","contributorId":225490,"corporation":false,"usgs":false,"family":"Zuther","given":"Steffen","email":"","affiliations":[{"id":41147,"text":"Association for the Conservation of Biodiversity of Kazakhstan, Almaty, Kazakhstan","active":true,"usgs":false}],"preferred":false,"id":791295,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Njeumi, Feliz","contributorId":225491,"corporation":false,"usgs":false,"family":"Njeumi","given":"Feliz","email":"","affiliations":[{"id":41143,"text":"Research Center for Emerging Infections and Zoonoses, University of Veterinary Medicine, Hannover, Germany","active":true,"usgs":false}],"preferred":false,"id":791296,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}}
,{"id":70209076,"text":"70209076 - 2020 - Colorado River flow dwindles as warming-driven loss of reflective snow energizes evaporation","interactions":[],"lastModifiedDate":"2020-03-20T11:05:00","indexId":"70209076","displayToPublicDate":"2020-03-13T10:11:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Colorado River flow dwindles as warming-driven loss of reflective snow energizes evaporation","docAbstract":"The sensitivity of river discharge to climate-system warming is highly uncertain, and the processes that govern river discharge are poorly understood, which impedes climate-change adaptation. A prominent exemplar is the Colorado River, where meteorological drought and warming are shrinking a water resource that supports more than 1 trillion dollars of economic activity per year. A Monte Carlo simulation with a radiation-aware hydrologic model resolves the longstanding, wide disparity in sensitivity estimates and reveals the controlling physical processes. We estimate that annual mean discharge has been decreasing by 9.3% per degree Celsius of warming because of increased evapotranspiration, mainly driven by snow loss and a consequent decrease in reflection of solar radiation. Projected precipitation increases likely will not suffice to fully counter the robust, thermodynamically induced drying. Thus, an increasing risk of severe water shortages is expected.","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.aay9187","usgsCitation":"Milly, P.C., and Dunne, K.A., 2020, Colorado River flow dwindles as warming-driven loss of reflective snow energizes evaporation: Science, v. 367, no. 6483, p. 1252-1255, https://doi.org/10.1126/science.aay9187.","productDescription":"4 p.","startPage":"1252","endPage":"1255","ipdsId":"IP-110304","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":457386,"rank":6,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/science.aay9187","text":"Publisher Index Page"},{"id":437055,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PEXXLB","text":"USGS data release","linkHelpText":"Model-Estimated, Spatially Distributed Monthly Water Balance of the Upper Colorado River Basin, Water Years 1913-2017"},{"id":373250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373383,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://science.sciencemag.org/cgi/content/full/science.aay9187?ijkey=xqtlOT7tqrPa.&keytype=ref&siteid=sci","text":"Publisher-provided full text access","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Web page"},{"id":373384,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://science.sciencemag.org/content/sci/367/6483/1252.full.pdf?ijkey=xqtlOT7tqrPa.&keytype=ref&siteid=sci","text":"Publisher-provided full text access","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"Reprint"},{"id":373410,"rank":4,"type":{"id":1,"text":"Abstract"},"url":"https://science.sciencemag.org/cgi/content/abstract/science.aay9187?ijkey=xqtlOT7tqrPa.&keytype=ref&siteid=sci","text":"Publisher-provided abstract","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Arizona, Colorado, Idaho, New Mexico, Utah, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.2,\n              35.75\n            ],\n            [\n              -105.9,\n              35.75\n            ],\n            [\n              -105.9,\n              42.5\n            ],\n            [\n              -112.2,\n              42.5\n            ],\n            [\n              -112.2,\n              35.75\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"367","issue":"6483","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":false,"id":784807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunne, Krista A. 0000-0002-1220-6140 kadunne@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-6140","contributorId":203816,"corporation":false,"usgs":true,"family":"Dunne","given":"Krista","email":"kadunne@usgs.gov","middleInitial":"A.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":784808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208470,"text":"sir20205010 - 2020 - Bathymetry of Morris Lake (Newton Reservoir), New Jersey, 2018","interactions":[],"lastModifiedDate":"2022-04-25T21:35:14.628865","indexId":"sir20205010","displayToPublicDate":"2020-03-13T09:15:00","publicationYear":"2020","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":"2020-5010","displayTitle":"Bathymetry of Morris Lake (Newton Reservoir), New Jersey, 2018","title":"Bathymetry of Morris Lake (Newton Reservoir), New Jersey, 2018","docAbstract":"<p>Morris Lake, also known as Newton Reservoir, has been the source of drinking water for the Town of Newton, New Jersey, since the early 1900s. Although Morris Lake has been used as a source of drinking water for many years, its capacity was previously uncertain. In April 2018, the U.S. Geological Survey and the New Jersey Department of Environmental Protection conducted a bathymetric survey of Morris Lake using a multibeam echosounder to map the reservoir. The points measured with the multibeam echosounder were combined with light detection and ranging data above the water surface and processed to create a 3.3-foot (1 meter) raster grid of the bathymetric surface, bathymetric contours at 2-foot intervals of depth and elevation, and an elevation-area-capacity table.</p><p>The results of the bathymetric survey show that Morris Lake has a maximum depth of just over 119 feet with an average depth of 42 feet. Like the surrounding topography, parts of the reservoir are extremely steep. The capacity of the reservoir at full spillway level is 1,980 million gallons, with a corresponding surface area of 145 acres. The accuracy of the mapped multibeam echosounder bathymetric data was evaluated using a quality assurance dataset collected with a single-beam echosounder; 9,386 quality assurance points were spatially joined with the mapped raster surface to compute measurement errors. The calculated median point error for Morris Lake was 0.23 foot, the median absolute error was 0.35 foot, and the 95-percent accuracy was 2.68 feet. The largest errors occurred in the steepest areas of the reservoir and in unmeasured areas. Geospatial files of the bathymetry data, including the mapped bathymetric surface, contours, and capacity tables, quality assurance points, and associated metadata are available for download as part of an accompanying U.S. Geological Survey data release.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205010","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Nystrom, E.A., and Collenburg, J.V., 2020, Bathymetry of Morris Lake (Newton Reservoir), New Jersey, 2018: U.S. Geological Survey Scientific Investigations Report 2020–5010, 14 p., https://doi.org/10.3133/sir20205010.","productDescription":"Report: vii, 14 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103879","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":399631,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109786.htm"},{"id":373089,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P977GO3J","text":"USGS data release","linkHelpText":"Geospatial Bathymetry Dataset and Elevation-Area-Capacity Table for Morris Lake (Newton Reservoir), New Jersey"},{"id":373091,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5010/sir20205010.pdf","text":"Report","size":"4.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5010"},{"id":373090,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5010/coverthb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Morris Lake (Newton Reservoir)","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.62128639221191,\n              41.0387074972886\n            ],\n            [\n              -74.59296226501463,\n              41.0387074972886\n            ],\n            [\n              -74.59296226501463,\n              41.05366055046841\n            ],\n            [\n              -74.62128639221191,\n              41.05366055046841\n            ],\n            [\n              -74.62128639221191,\n              41.0387074972886\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ny@usgs.gov\" data-mce-href=\"mailto:dc_ny@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ny-water\" data-mce-href=\"https://www.usgs.gov/centers/ny-water\">New York Water Science Center</a><br>U.S. Geological Survey<br>425 Jordan Road<br>Troy, NY 12180–8349<br></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Bathymetric Survey and Processing Methods</li><li>Bathymetric Map Creation and Results</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-03-13","noUsgsAuthors":false,"publicationDate":"2020-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Nystrom, Elizabeth A. 0000-0002-0886-3439 nystrom@usgs.gov","orcid":"https://orcid.org/0000-0002-0886-3439","contributorId":1072,"corporation":false,"usgs":true,"family":"Nystrom","given":"Elizabeth","email":"nystrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collenburg, Jerilyn V. 0000-0002-3513-3116","orcid":"https://orcid.org/0000-0002-3513-3116","contributorId":222391,"corporation":false,"usgs":true,"family":"Collenburg","given":"Jerilyn","email":"","middleInitial":"V.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782037,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70210526,"text":"70210526 - 2020 - Sub-annual streamflow responses to rainfall and snowmelt inputs in snow-dominated watersheds of the western U.S.","interactions":[],"lastModifiedDate":"2020-06-09T12:42:32.961647","indexId":"70210526","displayToPublicDate":"2020-03-13T07:40:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Sub-annual streamflow responses to rainfall and snowmelt inputs in snow-dominated watersheds of the western U.S.","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Streamflow generation in mountain watersheds is strongly influenced by snow accumulation and melt, and multiple studies have found that snow loss leads to earlier snowmelt timing and declines in annual streamflow. However, hydrologic responses to snow loss are heterogeneous, and not all areas experience streamflow declines. This research examines whether streamflow generation is different for rainfall versus snowmelt inputs. We compiled a sample of 57 small U.S. Geological Survey watersheds in the western United States containing a Natural Resource Conservation Service Snow Telemetry site and having ratios of mean annual peak snow water equivalent to precipitation ratios &gt;0.25. Daily streamflow was separated into quickflow and baseflow using a digital filter, and quickflow was then divided into quickflow response intervals using thresholds in quickflow slope. Each quickflow response interval was categorized by its fraction of input from snowmelt. Most sites exhibited two streamflow generation peaks each year, with one peak in the winter when runoff efficiency is greatest, and the second in the spring during peak snowmelt input. On average, study watersheds were dominated by snowmelt inputs (70%), and snowmelt and mixed inputs usually generated greater streamflow than rainfall because of higher inputs and longer durations. However, rainfall produced high streamflow generation in winter, when watersheds have their highest runoff efficiency (81%) across all input types. We demonstrate that while snowmelt is important for streamflow generation due to high input over long periods, increases in rain and mixed input during wet winter periods can countervail tendencies for reduced streamflow with declining snowpacks.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1029/2019WR026132","usgsCitation":"Hammond, J., and Kampf, S.K., 2020, Sub-annual streamflow responses to rainfall and snowmelt inputs in snow-dominated watersheds of the western U.S.: Water Resources Research, v. 56, no. 4, e2019WR026132, 15 p., https://doi.org/10.1029/2019WR026132.","productDescription":"e2019WR026132, 15 p.","ipdsId":"IP-111502","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":375457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Western United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.541015625,\n              35.60371874069731\n            ],\n            [\n              -117.7734375,\n              31.952162238024975\n            ],\n            [\n              -102.91992187499999,\n              28.844673680771766\n            ],\n            [\n              -102.91992187499999,\n              48.80686346108517\n            ],\n            [\n              -125.68359374999999,\n              48.922499263758255\n            ],\n            [\n              -124.541015625,\n              35.60371874069731\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"56","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kampf, Stephanie K. 0000-0001-8991-2679","orcid":"https://orcid.org/0000-0001-8991-2679","contributorId":225146,"corporation":false,"usgs":false,"family":"Kampf","given":"Stephanie","email":"","middleInitial":"K.","affiliations":[{"id":41048,"text":"Associate Professor, Department of Ecosystem Science and Sustainability, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":790525,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209141,"text":"70209141 - 2020 - Organic compounds in produced waters from the Bakken Formation and Three Forks Formation in the Williston Basin, North Dakota","interactions":[],"lastModifiedDate":"2020-03-19T07:20:09","indexId":"70209141","displayToPublicDate":"2020-03-13T07:16:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5211,"text":"Heliyon","active":true,"publicationSubtype":{"id":10}},"title":"Organic compounds in produced waters from the Bakken Formation and Three Forks Formation in the Williston Basin, North Dakota","docAbstract":"The organic composition of produced waters (flowback and formation waters) from the middle member of the Bakken Formation and the Three Forks Formation in the Williston Basin, North Dakota were examined to aid in the remediation of surface contamination and help develop treatment methods for produced-water recycling. Twelve produced water samples were collected from the Bakken and Three Forks Formations and analyzed for non-purgeable dissolved organic carbon (NPDOC), acetate, and extractable hydrocarbons. NPDOC and acetate concentrations from sampled wells from ranged from 33-190 milligrams per liter (mg/L) and 16-40 mg/L, respectively. Concentrations of individual extractable hydrocarbon compounds ranged from less than 1 to greater than 400 micrograms per liter (µg/L), and included polycyclic aromatic hydrocarbons (PAHs), phenolic compounds, glycol ethers, and cyclic ketones. While the limited number of samples, varying well production age, and lack of knowledge of on-going well treatments complicate conclusions, this report aids adds to the limited knowledge of organics in produced waters from the Bakken and Three Forks Formations.","language":"English","publisher":"Elsevier","doi":"10.1016/j.heliyon.2020.e03590","usgsCitation":"Varonka, M., Gallegos, T., Bates, A.L., Doolan, C.A., and Orem, W.H., 2020, Organic compounds in produced waters from the Bakken Formation and Three Forks Formation in the Williston Basin, North Dakota: Heliyon, v. 6, no. 3, e03590, 8 p., https://doi.org/10.1016/j.heliyon.2020.e03590.","productDescription":"e03590, 8 p.","ipdsId":"IP-109331","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":457390,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.heliyon.2020.e03590","text":"Publisher Index 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,{"id":70238974,"text":"70238974 - 2020 - Building a landslide hazard indicator with machine learning and land surface models","interactions":[],"lastModifiedDate":"2022-12-20T13:20:18.345312","indexId":"70238974","displayToPublicDate":"2020-03-13T07:14:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"Building a landslide hazard indicator with machine learning and land surface models","docAbstract":"<p><span>The&nbsp;U.S. Pacific Northwest&nbsp;has a history of frequent and occasionally deadly landslides caused by various factors. Using a multivariate, machine-learning approach, we combined a Pacific Northwest Landslide Inventory with a 36-year gridded hydrologic dataset from the National Climate Assessment – Land&nbsp;Data Assimilation&nbsp;System to produce a landslide hazard indicator (LHI) on a daily 0.125-degree grid. The LHI identified where and when landslides were most probable over the years 1979–2016, addressing issues of bias and completeness that muddy the analysis of multi-decadal landslide inventories. The seasonal cycle was strong along the west coast, with a peak in the winter, but weaker east of the Cascade Range. This lagging indicator can fill gaps in the observational record to identify the&nbsp;</span>seasonality<span>&nbsp;of landslides over a large spatiotemporal domain and show how landslide hazard has responded to a changing climate.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2020.104692","usgsCitation":"Stanley, T.A., Kirschbaum, D.B., Sobieszczyk, S., Jasinski, M.F., Borak, J.S., and Slaughter, S.L., 2020, Building a landslide hazard indicator with machine learning and land surface models: Environmental Modelling & Software, v. 129, 104692, 15 p., https://doi.org/10.1016/j.envsoft.2020.104692.","productDescription":"104692, 15 p.","ipdsId":"IP-114297","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":457392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2020.104692","text":"Publisher Index 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F.","contributorId":300152,"corporation":false,"usgs":false,"family":"Jasinski","given":"M.","email":"","middleInitial":"F.","affiliations":[{"id":40052,"text":"NASA Goddard","active":true,"usgs":false}],"preferred":false,"id":859495,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Borak, J. S.","contributorId":300155,"corporation":false,"usgs":false,"family":"Borak","given":"J.","email":"","middleInitial":"S.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":859496,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Slaughter, Stephen L. 0000-0002-4322-3330","orcid":"https://orcid.org/0000-0002-4322-3330","contributorId":224686,"corporation":false,"usgs":true,"family":"Slaughter","given":"Stephen","email":"","middleInitial":"L.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":859497,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209137,"text":"70209137 - 2020 - Landfill leachate contributes per-/poly-fluoroalkyl substances (PFAS) and pharmaceuticals to municipal wastewater","interactions":[],"lastModifiedDate":"2021-05-28T14:10:48.45113","indexId":"70209137","displayToPublicDate":"2020-03-13T07:10:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5112,"text":"Environmental Science: Water Research & Technology","active":true,"publicationSubtype":{"id":10}},"title":"Landfill leachate contributes per-/poly-fluoroalkyl substances (PFAS) and pharmaceuticals to municipal wastewater","docAbstract":"Widespread disposal of landfill leachate to municipal sewer infrastructure in the United States calls for an improved understanding of the relative organic-chemical contributions to the wastewater treatment plant (WWTP) waste stream and associated surface-water discharge to receptors in the environment. Landfill leachate, WWTP influent, and WWTP effluent samples were collected from three landfill-WWTP systems and compared with analogous influent and effluent samples from two WWTPs that did not receive leachate. Samples were analyzed for 73 per-/poly-fluoroalkyl substances (PFAS), 109 pharmaceuticals, and 21 hormones and related compounds. PFAS were detected more frequently in leachate (92%) than in influent (55%). Total PFAS concentrations in leachate (93,100 ng/L) were more than ten times higher than in influent (6,950 ng/L), and effluent samples (3,730 ng/L). Concentrations of bisphenol A; the nonprescription pharmaceuticals cotinine, lidocaine, nicotine; and the prescription pharmaceuticals amphetamine, carisoprodol, pentoxifylline, and thiabendazole were an order of magnitude higher in landfill leachate than WWTP influent. Leachate load contributions for PFAS (0.78 to 31 g/d), bisphenol A (0.97 to 8.3 g/d), and nonprescription (2.0 to 3.1 g/d) and prescription (0.48 to 2.5 g/d) pharmaceuticals to WWTP influent were generally low (<10 g/d) for most compounds because of  high influent-to-leachate volumetric ratios (0.983). No clear differences in concentrations were apparent between effluents from WWTPs receiving landfill leachate and those that did not receive landfill leachate.","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D0EW00045K","usgsCitation":"Masoner, J.R., Kolpin, D.W., Cozzarelli, I.M., Smalling, K.L., Bolyard, S., Field, J., Furlong, E.T., Gray, J.L., Lozinski, D., Reinhart, D., Rodowa, A., and Bradley, P.M., 2020, Landfill leachate contributes per-/poly-fluoroalkyl substances (PFAS) and pharmaceuticals to municipal wastewater: Environmental Science: Water Research & Technology, v. 6, p. 1300-1311, https://doi.org/10.1039/D0EW00045K.","productDescription":"12 p.","startPage":"1300","endPage":"1311","ipdsId":"IP-116926","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":457394,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1039/d0ew00045k","text":"Publisher Index Page"},{"id":437056,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97LMTKZ","text":"USGS data release","linkHelpText":"Target-Chemical Concentrations in Landfill Leachate and Wastewater Treatment Influent and Effluent"},{"id":373360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":785068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":785070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smalling, Kelly L. 0000-0002-1214-4920 ksmall@usgs.gov","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":190789,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","email":"ksmall@usgs.gov","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bolyard, Stephanie 0000-0001-5590-0776","orcid":"https://orcid.org/0000-0001-5590-0776","contributorId":223446,"corporation":false,"usgs":false,"family":"Bolyard","given":"Stephanie","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":785072,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Field, Jennifer 0000-0002-9346-4693","orcid":"https://orcid.org/0000-0002-9346-4693","contributorId":223447,"corporation":false,"usgs":false,"family":"Field","given":"Jennifer","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":785073,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@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":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":785074,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":785075,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lozinski, Duncan 0000-0001-7646-466X","orcid":"https://orcid.org/0000-0001-7646-466X","contributorId":223450,"corporation":false,"usgs":false,"family":"Lozinski","given":"Duncan","email":"","affiliations":[{"id":40716,"text":"Brown and Caldwell","active":true,"usgs":false}],"preferred":false,"id":785076,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reinhart, Debra","contributorId":223451,"corporation":false,"usgs":false,"family":"Reinhart","given":"Debra","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":785077,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rodowa, Alix 0000-0002-3990-2111","orcid":"https://orcid.org/0000-0002-3990-2111","contributorId":223452,"corporation":false,"usgs":false,"family":"Rodowa","given":"Alix","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":785078,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785079,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70209825,"text":"70209825 - 2020 - A post-eruption study of gases and thermal waters at Okmok Volcano, Alaska","interactions":[],"lastModifiedDate":"2020-04-30T12:12:19.796285","indexId":"70209825","displayToPublicDate":"2020-03-13T07:05:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"A post-eruption study of gases and thermal waters at Okmok Volcano, Alaska","docAbstract":"We report here on the first focused study of gas discharges and thermal spring waters at Okmok Volcano since the 2008 phreatomagmatic eruptions. Results include the first compositional gas data from Okmok with minimal air contamination and the first data on magmatic carbon in Okmok spring waters. Chemical and isotopic analyses of the waters and gases are used to assess the character of Okmok fluids eight years after the eruptions ceased. \n\nGases from vents on intracaldera Cone C have high concentrations of H2 and contain H2S rather than SO2, demonstrating the influence of a hydrothermal system, while isotope values of carbon ( 10.2 to  8.9‰) and helium (~8 RA) confirm the presence of magma-derived volatiles. Estimates of equilibrium temperatures for the Cone C gas are ~230 ± 30 ºC. A much cooler reservoir with a maximum temperature of ~55 ºC feeds the intracaldera warm springs. Based on discharge measurements of creeks draining the caldera, the total heat output of the warm springs is estimated to be about 32 MW.\n\nGas data from a single location of steaming ground at the Geyser Bight geothermal area southwest of the Okmok Caldera are given. The gas is typical of geothermal gases with high concentrations of H2S and an air-corrected helium isotope ratio of 7.15 RA.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2020.106853","collaboration":"","usgsCitation":"Bergfeld, D., Evans, W.C., Hunt, A., Lopez, T., and Schaefer, J., 2020, A post-eruption study of gases and thermal waters at Okmok Volcano, Alaska: Journal of Volcanology and Geothermal Research, v. 396, https://doi.org/10.1016/j.jvolgeores.2020.106853.","productDescription":"106853, 16 p.","startPage":"","ipdsId":"IP-115008","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":457400,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2020.106853","text":"Publisher Index Page"},{"id":374393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Okmok Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -168.5687255859375,\n              53.212612189941574\n            ],\n            [\n              -167.6898193359375,\n              53.212612189941574\n            ],\n            [\n              -167.6898193359375,\n              53.589244357588655\n            ],\n            [\n              -168.5687255859375,\n              53.589244357588655\n            ],\n            [\n              -168.5687255859375,\n              53.212612189941574\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"396","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bergfeld, Deborah 0000-0003-4570-7627 dbergfel@usgs.gov","orcid":"https://orcid.org/0000-0003-4570-7627","contributorId":152531,"corporation":false,"usgs":true,"family":"Bergfeld","given":"Deborah","email":"dbergfel@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":788182,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":788183,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Andrew G. 0000-0002-3810-8610","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":206197,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":788186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lopez, Taryn","contributorId":146828,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","affiliations":[{"id":16753,"text":"University of Alaska Geophysical Institute","active":true,"usgs":false}],"preferred":false,"id":788184,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schaefer, Janet","contributorId":199547,"corporation":false,"usgs":false,"family":"Schaefer","given":"Janet","affiliations":[],"preferred":false,"id":788185,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70210150,"text":"70210150 - 2020 - Temporal evolution of measured and simulated infiltration following wildfire in the Colorado Front Range, USA: Shifting thresholds of runoff generation and hydrologic hazards","interactions":[],"lastModifiedDate":"2020-05-18T12:08:31.572534","indexId":"70210150","displayToPublicDate":"2020-03-13T07:02:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Temporal evolution of measured and simulated infiltration following wildfire in the Colorado Front Range, USA: Shifting thresholds of runoff generation and hydrologic hazards","docAbstract":"Destructive flash floods and debris flows are a common menace following wildfire. The restoration of protection provided by forests from post-fire floods and debris flows depends on the recovery of infiltration and attendant reduction of infiltration-excess surface runoff generation. This work examines seven years of post-fire infiltration measurements and temporal relations fit to soil-hydraulic properties from the Colorado Front Range, USA to assess infiltration recovery with increasing time since fire. Point-scale Green-Ampt simulations of infiltration across a full spectrum of rainfall events are used to evaluate infiltration changes and shifts in surface runoff generation thresholds with post-fire temporal recovery. Measured and simulated infiltration generally recovered monotonically with increasing time since fire. This indicates a reduced vulnerability to infiltration-excess runoff generation as time elapses, with the greatest risk in the first two years after the fire. The threshold for infiltration-excess runoff advances with increasing time to rainfall events with higher intensity and greater return intervals; by the third year after wildfire only extreme events (30-100 year recurrence) generate surface runoff and by the fifth and seventh year even extreme rainfall events typically fail to generate surface runoff. Remotely-sensed vegetation indices suggest linked, or at least contemporaneous, recovery of understory vegetation and field-saturated hydraulic conductivity at this field site, suggesting coincident recovery of multiple hillslope properties impacting surface runoff generation. This work indicates that the closing of the window of disturbance after wildfire, relative to infiltration-excess runoff generation and corresponding flash flood and debris flow hazards, relies on coupled assessments of hillslope property recovery and stochasticity of high-intensity rainfall. Post-fire hazard assessments using static hillslope properties could fail to predict flash floods and debris flows associated with infrequent extreme rainfall events that strike during the post-fire recovery period when hillslope properties are partially recovered.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.124765","collaboration":"","usgsCitation":"Ebel, B., 2020, Temporal evolution of measured and simulated infiltration following wildfire in the Colorado Front Range, USA: Shifting thresholds of runoff generation and hydrologic hazards: Journal of Hydrology, v. 585, https://doi.org/10.1016/j.jhydrol.2020.124765.","productDescription":"124765, 16 p.","startPage":"124765","ipdsId":"IP-111116","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":457401,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2020.124765","text":"Publisher Index Page"},{"id":437057,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCNFD9","text":"USGS data release","linkHelpText":"Green-Ampt infiltration modeling following wildfire in the Colorado Front Range, USA"},{"id":374881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Colorado Front Range","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.270751953125,\n              39.52522954427751\n            ],\n            [\n              -104.52392578125,\n              39.52522954427751\n            ],\n            [\n              -104.52392578125,\n              40.901057866884024\n            ],\n            [\n              -106.270751953125,\n              40.901057866884024\n            ],\n            [\n              -106.270751953125,\n              39.52522954427751\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"585","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":789317,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70219483,"text":"70219483 - 2020 - Small-scale water deficits after wildfires create long-lasting ecological impacts","interactions":[],"lastModifiedDate":"2021-04-12T11:58:12.438476","indexId":"70219483","displayToPublicDate":"2020-03-13T07:01:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Small-scale water deficits after wildfires create long-lasting ecological impacts","docAbstract":"<p><span>Ecological droughts are deficits in soil–water availability that induce threshold-like ecosystem responses, such as causing altered or degraded plant-community conditions, which can be exceedingly difficult to reverse. However, 'ecological drought' can be difficult to define, let alone to quantify, especially at spatial and temporal scales relevant to land managers. This is despite a growing need to integrate drought-related factors into management decisions as climate changes result in precipitation instability in many semi-arid ecosystems. We asked whether success in restoration seedings of the foundational species big sagebrush (</span><i>Artemisia tridentata</i><span>) was related to estimated water deficit, using the SoilWat2 model and data from &gt;600 plots located in previously burned areas in the western United States. Water deficit was characterized by: (1) the standardized precipitation-evapotranspiration index (SPEI), a coarse-scale drought index, and (2) the number of days with wet and warm conditions in the near-surface soil, where seeds and seedlings germinate and emerge (i.e. days with 0–5 cm deep soil water potential &gt;−2.5 MPa and temperature above 0 °C). SPEI, a widely used drought index, was not predictive of whether sagebrush had reestablished. In contrast, wet-warm days elicited a critical drought threshold response, with successfully reestablished sites having experienced seven more wet-warm days than unsuccessful sites during the first March following summer wildfire and restoration. Thus, seemingly small-scale and short-term changes in water availability and temperature can contribute to major ecosystem shifts, as many of these sites remained shrubless two decades later. These findings help clarify the definition of ecological drought for a foundational species and its imperiled semi-arid ecosystem. Drought is well known to affect the occurrence of wildfires, but drought in the year(s) after fire can determine whether fire causes long-lasting, negative impacts on ecosystems.</span></p>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ab79e4","usgsCitation":"O’Connor, R., Germino, M., Barnard, D.M., Andrews, C.M., Bradford, J., Pilliod, D., Arkle, R.S., and Shriver, R.K., 2020, Small-scale water deficits after wildfires create long-lasting ecological impacts: Environmental Research Letters, v. 15, no. 4, 044001, 11 p., https://doi.org/10.1088/1748-9326/ab79e4.","productDescription":"044001, 11 p.","ipdsId":"IP-114720","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":457404,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ab79e4","text":"Publisher Index Page"},{"id":437058,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LDKQE2","text":"USGS data release","linkHelpText":"Ecological drought for sagebrush seedings in the Great Basin"},{"id":384960,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Oregon, Idaho, Nevada, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.0810546875,\n              40.84706035607122\n            ],\n            [\n              -113.0712890625,\n              40.84706035607122\n            ],\n            [\n              -113.0712890625,\n              43.32517767999296\n            ],\n            [\n              -118.0810546875,\n              43.32517767999296\n            ],\n            [\n              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Center","active":false,"usgs":true}],"preferred":true,"id":813765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, David M 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":222833,"corporation":false,"usgs":false,"family":"Barnard","given":"David","email":"","middleInitial":"M","affiliations":[{"id":18168,"text":"USDA ARS","active":true,"usgs":false}],"preferred":false,"id":813766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andrews, Caitlin M. 0000-0003-4593-1071 candrews@usgs.gov","orcid":"https://orcid.org/0000-0003-4593-1071","contributorId":192985,"corporation":false,"usgs":true,"family":"Andrews","given":"Caitlin","email":"candrews@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":813767,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":813768,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813769,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arkle, Robert S. 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":218006,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813770,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shriver, Robert K 0000-0002-4590-4834","orcid":"https://orcid.org/0000-0002-4590-4834","contributorId":222834,"corporation":false,"usgs":false,"family":"Shriver","given":"Robert","email":"","middleInitial":"K","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":813771,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70208384,"text":"fs20203006 - 2020 - Pooling resources across organizations — Multisource water-quality data for the Delaware River Basin","interactions":[],"lastModifiedDate":"2022-04-20T18:14:13.866211","indexId":"fs20203006","displayToPublicDate":"2020-03-12T16:33:50","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3006","displayTitle":"Pooling Resources Across Organizations — Multisource Water-Quality Data for the Delaware River Basin","title":"Pooling resources across organizations — Multisource water-quality data for the Delaware River Basin","docAbstract":"<p>The U.S. Geological Survey (USGS) recently launched a pilot Integrated Water Availability Assessment (IWAA) in the Delaware River Basin to explore, test, and refine systems and processes for assessing water availability for human and ecological uses based on water monitoring data. Water-quality monitoring provides citizens, managers, and scientists with the information needed to evaluate the health of aquatic ecosystems and the safety and availability of water for drinking, agriculture, recreation, and other uses. Many organizations collect water-quality data at various sites and sampling frequencies to meet their assessment needs. The result is multiple individual datasets suitable for the specific organization’s needs that also hold great potential if pooled into a much larger dataset sourced from multiple organizations (multisource data). A multisource dataset increases the value and power of multiple single datasets and expands the breadth and depth of available water-quality data to ultimately increase the number and types of questions that can be answered. This fact sheet describes the process of “harmonizing” water-quality data from multiple organizations and presents a recently developed dataset for surface-water quality in the Delaware River Basin. This harmonized multisource surface-water-quality dataset will serve as a resource for analysis and modeling of surface-water quality to support IWAA efforts in the basin. Furthermore, this harmonization process can be expanded and applied to other regional IWAA basins or applied nationally.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203006","collaboration":"Integrated Water Availability Assessments Program","usgsCitation":"Murphy, J.C., and Shoda, M.E., 2020, Pooling resources across organizations — Multisource water-quality data for the Delaware River Basin: U.S. Geological Survey Fact Sheet 2020–3006, 2 p., https://doi.org/10.3133/fs20203006.","productDescription":"Report: 2 p.; Data Release","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-113620","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":373170,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PX8LZO","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Multisource surface-water-quality data and U.S. Geological Survey streamgage match for the Delaware River Basin"},{"id":373169,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3006/fs20203006.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3006"},{"id":373168,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3006/coverthb.jpg"},{"id":399198,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109784.htm"}],"country":"United States","state":"Delaware, Maryland, New York, New Jersey, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.5,\n              38.6\n            ],\n            [\n              -74.333,\n              38.6\n            ],\n            [\n              -74.333,\n              42.5\n            ],\n            [\n              -76.5,\n              42.5\n            ],\n            [\n              -76.5,\n              38.6\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Program Coordinator,&nbsp;<a data-mce-href=\"https://www.usgs.gov/water-resources/water-availability-and-use-science-program\" href=\"https://www.usgs.gov/water-resources/water-availability-and-use-science-program\">Water Availability and Use Science Program</a><br>U.S. Geological Survey <br>Water Resources Mission Area<br></p><p>Email:&nbsp;<a href=\"mailto:wausp-info@usgs.gov\" data-mce-href=\"mailto:wausp-info@usgs.gov\">wausp-info@usgs.gov</a></p>","tableOfContents":"<ul><li>Data Harmonization</li><li>Metadata Issues</li><li>Harmonized Water-Quality Data for the Delaware River Basin</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-03-12","noUsgsAuthors":false,"publicationDate":"2020-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":167405,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":781677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781678,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208635,"text":"ds1123 - 2020 - Abundance and productivity of marbled murrelets (<i>Brachyramphus marmoratus</i>) off central California during the 2019 breeding season","interactions":[],"lastModifiedDate":"2020-03-16T13:50:45","indexId":"ds1123","displayToPublicDate":"2020-03-12T15:04:48","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1123","displayTitle":"Abundance and Productivity of Marbled Murrelets (<i>Brachyramphus marmoratus</i>) Off Central California During the 2019 Breeding Season","title":"Abundance and productivity of marbled murrelets (<i>Brachyramphus marmoratus</i>) off central California during the 2019 breeding season","docAbstract":"<p>Marbled murrelets (<i>Brachyramphus marmoratus</i>) have been listed as “endangered” by the State of California and “threatened” by the U.S. Fish and Wildlife Service since 1992 in California, Oregon, and Washington. Information regarding marbled murrelet abundance, distribution, population trends, and habitat associations is critical for risk assessment, effective management, evaluation of conservation efficacy, and ultimately, to meet Federal and State recovery efforts for this species. During June–August&nbsp;2019, the U.S.&nbsp;Geological Survey Western Ecological Research Center continued previously established, long-term (1996–2019), at-sea surveys to estimate abundance and productivity of marbled murrelets in U.S. Fish and Wildlife Service Conservation Zone 6 (San Francisco Bay to Point Sur in central California). Using conventional distance sampling methods, we estimated marbled murrelet abundance using 125&nbsp;detections of 216&nbsp;murrelets (mean group size, 1.72) observed on 8 surveys. The abundance estimated for the entire study area using all surveys in 2019 was 404 birds (95-percent confidence interval, 272–601 birds). Estimated abundance from 2019 is comparable to most prior years of study. In 2019, we estimated reproductive productivity (calculated as the hatch-year [HY] to after-hatch-year [AHY] ratio) using three detections of three HY murrelets observed on six surveys. After date-correcting HY and AHY counts to account for birds expected to be absent from the water while inland at nests, the date-corrected juvenile ratio was 0.025±0.020 standard error. We discuss changes in methodologies during 1996–2019 that could be addressed in re-analysis of this long-term dataset. We updated a synthesized database of all Zone 6 marbled murrelet survey data since 1999 with 2019 data to allow scientists and managers to evaluate established survey methods and assess trends in abundance and productivity estimates.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1123","usgsCitation":"Felis, J.J., Kelsey, E.C., Adams, J., Horton, C., and White, L., 2020, Abundance and productivity of marbled murrelets (<i>Brachyramphus marmoratus</i>) off central California during the 2019 breeding season: U.S. Geological Survey Data Series 1123, 13 p., https://doi.org/10.3133/ds 1123.","productDescription":"Report: vi, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-114914","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":373097,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1123/coverthb.jpg"},{"id":373098,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1123/ds1123.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Data Series 1123"},{"id":373220,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75B01RW","linkHelpText":"Annual Marbled Murrelet Abundance and Productivity Surveys Off Central California (Zone 6), 1999-2018 (ver. 2.0, March 2019)"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.991943359375,\n              36.89719446989036\n            ],\n            [\n              -121.92626953124999,\n              36.89719446989036\n            ],\n            [\n              -121.92626953124999,\n              37.68382032669382\n            ],\n            [\n              -122.991943359375,\n              37.68382032669382\n            ],\n            [\n              -122.991943359375,\n              36.89719446989036\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/werc/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc/connect\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<p></p><ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Marbled Murrelet Abundance and Productivity Results</li><li>Discussion</li><li>References Cited</li></ul><p></p>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-03-12","noUsgsAuthors":false,"publicationDate":"2020-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Felis, Jonathan J. 0000-0002-0608-8950 jfelis@usgs.gov","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":4825,"corporation":false,"usgs":true,"family":"Felis","given":"Jonathan","email":"jfelis@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":784534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelsey, Emily C. 0000-0002-0107-3530 ekelsey@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3530","contributorId":206505,"corporation":false,"usgs":true,"family":"Kelsey","given":"Emily","email":"ekelsey@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":784542,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Josh 0000-0003-3056-925X josh_adams@usgs.gov","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":2422,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","email":"josh_adams@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":784535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Horton, Cheryl 0000-0003-0471-8143 cahorton@usgs.gov","orcid":"https://orcid.org/0000-0003-0471-8143","contributorId":223207,"corporation":false,"usgs":true,"family":"Horton","given":"Cheryl","email":"cahorton@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":784536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Laura 0000-0002-3830-5921 lmwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-3830-5921","contributorId":223208,"corporation":false,"usgs":true,"family":"White","given":"Laura","email":"lmwhite@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":784537,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209046,"text":"70209046 - 2020 - Global plant trait relationships extend to the climatic extremes of the tundra biome","interactions":[],"lastModifiedDate":"2020-03-13T09:58:07","indexId":"70209046","displayToPublicDate":"2020-03-12T13:28:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Global plant trait relationships extend to the climatic extremes of the tundra biome","docAbstract":"The majority of variation in six traits critical to the growth, survival and reproduction of global plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.","language":"English","publisher":"Nature ","doi":"10.1038/s41467-020-15014-4","usgsCitation":"Thomas, H.J., Bjorkman, A.D., Myers-Smith, I., Elmendorf, S., Kattge, J., Diaz, S., Vellend, M., Blok, D., Cornelissen, J., Forbes, B.C., Henry, G.H., Hollister, R., Normand, S., Prevey, J.S., Rixen, C., Schaepman-Strub, G., Wilmking, M., Wipf, S., Cornwell, W., Beck, P., Georges, D., Goetz, S., Guay, K.C., Ruger, N., Soudzilovskaia, N., Spasojevic, M.J., Alatalo, J., Alexander, H.D., Anadon-Rosell, A., Angers-Blondin, S., teBeest, M., Berner, L.T., Bjork, R.G., Buchwal, A., Buras, A., Carbognani, M., Christie, K.S., Collier, L.S., Cooper, E.J., Elberling, B., Eskelinen, A., Frei, E.R., Grau, O., Grogan, P., Hallinger, M., Heijmans, M.M., Hermanutz, L., Hudson, J.M., Johnstone, J., Hulber, K., Iturrate-Garcia, M., Iversen, C.M., Jaroszynska, F., Kaarlejarvi, E., Kulonen, A., Lamarque, L.J., Lantz, T.C., Levesque, E., Little, C., Michelsen, A., Milbau, A., Nabe-Nielsen, J., Nielsen, S.S., Ninot, J.M., Oberbauer, S.F., Olofsson, J., Onipchenko, V., Petraglia, A., Rumpf, S.B., Shetti, R., Speed, J.D., Suding, K., Tape, K., Tomaselli, M., Trant, A., Treier, U.A., Tremblay, M., Venn, S.E., Vowles, T., Weijers, S., Wookey, P.A., Zamin, T.J., Bahn, M., Blonder, B., van Bodegom, P., Bond-Lamberty, B., Campetella, G., Cerabolini, B., Chapin, F.S., Craine, J.M., Dainese, M., Green, W.A., Jansen, S., Kleyer, M., Manning, P., Niinemets, U., Onoda, Y., Ozinga, W.A., Penuelas, J., Poschlod, P., Reich, P., Sandel, B., Schamp, B.S., Sheremetiev, S., and de Vries, F.T., 2020, Global plant trait relationships extend to the climatic extremes of the tundra biome: Nature Communications, v. 11, 1351, 12 p., https://doi.org/10.1038/s41467-020-15014-4.","productDescription":"1351, 12 p.","ipdsId":"IP-114996","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":457408,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-020-15014-4","text":"Publisher Index Page"},{"id":373244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, H. J. D.","contributorId":223283,"corporation":false,"usgs":false,"family":"Thomas","given":"H.","email":"","middleInitial":"J. D.","affiliations":[],"preferred":false,"id":784735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bjorkman, A. D.","contributorId":223284,"corporation":false,"usgs":false,"family":"Bjorkman","given":"A.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":784736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Myers-Smith, I. H.","contributorId":13738,"corporation":false,"usgs":true,"family":"Myers-Smith","given":"I. 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,{"id":70203860,"text":"sir20195059 - 2020 - Groundwater quality and geochemistry of West Virginia’s southern coal fields","interactions":[],"lastModifiedDate":"2023-03-03T15:42:41.455704","indexId":"sir20195059","displayToPublicDate":"2020-03-12T13:15:00","publicationYear":"2020","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":"2019-5059","displayTitle":"Groundwater Quality and Geochemistry of West Virginia’s Southern Coal Fields","title":"Groundwater quality and geochemistry of West Virginia’s southern coal fields","docAbstract":"<p>Coal mining has been the dominant industry and land use in West Virginia’s southern coal fields since the mid-1800s. Mortality rates for a variety of serious chronic conditions, such as diabetes, heart disease, and some forms of cancer in Appalachian coal mining regions, are higher than in areas lacking substantial coal mining activity within the Appalachian Region or elsewhere in the United States. Causes of the increased mortality and morbidity are not clear, but poor diet, high rates of smoking, socioeconomic factors, and the quality of groundwater used by area residents are all possible contributing factors. This study was conducted by the U.S. Geological Survey in cooperation with the West Virginia Department of Health and Human Resources and the West Virginia Department of Environmental Protection, with grant support from the Centers for Disease Control and Prevention (CDC) to assess the quality of groundwater in southern West Virginia. The data from this assessment of groundwater quality may be used by the CDC and other agencies to potentially investigate the role or lack thereof of groundwater quality with respect to mortality and morbidity rates in the region. The study was conducted in a region where a high density of current or past coal mining combined with a lack of advanced sewage treatment could affect concentrations of commonly occurring constituents plus contaminants, including nitrate, trace metals, major ions, indicator bacteria, radon, hydrogen sulfide, and dissolved hydrocarbons.</p><p>Because rural residential wells and mine outfalls are considered private sources of water in the region, and are therefore unregulated and unmonitored, water-quality data are sparse. To fill the data gap and assess the groundwater quality in the region, water-quality samples were collected from 60 sites in a 10-county area. The 60 sites sampled included 46 rural residential homeowner wells and 14 mine outfall discharges used for residential supply. For this study, all samples were collected prior to any filtration or other treatments, typically at the pressure tank, and are indicative of total and dissolved constituents in the untreated water.</p><p>Generally, data for the 60 sites indicate that most waters sampled do not exceed thresholds for most U.S. Environmental Protection Agency (EPA) drinking-water standards and U.S. Geological Survey (USGS) drinking-water screening criteria. However, there were several notable exceptions. Turbidity exceeded the 5-Nephelometric Turbidity Unit (NTU) EPA treatment technique (TT) drinking-water standard in 14 of 60 (23 percent) sites sampled and exceeded the 1-NTU TT standard in 51 of 60 (85 percent) sites sampled. Turbidity is common in many wells in southern West Virginia and may be attributed to iron oxyhydroxide precipitates, sediment carried into the aquifers from the shallow soil zone due to improperly constructed or cased wells or transported to the aquifer in shallow stress-relief fracture zones or through permeable bedding-plane partings. For the sites sampled, 31 of 60 (52 percent) had pH values at, above, or below the upper and lower range of the EPA Secondary Maximum Contaminant Level (SMCL, 6.5–8.5 standard units). Of those 31 sites, 28 (90 percent) were indicative of acidic corrosive water and 3 (10 percent) were indicative of alkaline water.</p><p>The Langelier Saturation Index (LSI), which is a measure of the corrosivity of the water, was computed for all sites sampled for the study. Eighty-two percent of the sites sampled had waters that were classified as corrosive, based on a LSI less than −0.5. Corrosive water has the potential to leach lead, copper, and other metals from lead, copper, galvanized, or lead-tin soldered connections in water lines. The chloride to sulfate mass ratio also was assessed with the alkalinity to indicate the potential to promote galvanic corrosion (PPGC) of water lines and plumbing fixtures. Only one of the sites (1.7 percent) classified as a corrosive water site, had a PPGC considered high; the remaining sites were classified as having either a moderate (53.3 percent) or low (45 percent) PPGC. Therefore, the type of plumbing systems sampled for this study may be affected by corrosive water, but the potential for leaching trace metals and other constituents from residential plumbing systems containing older galvanized pipes or lead-tin soldered copper pipes is moderate to low.</p><p>The indicator bacteria total coliform and <i>Escherichia coli</i> (<i>E. coli</i>) also were detected in groundwater samples to varying degrees. Total coliforms, which are a broad class of indicator bacteria, are common in groundwater in southern West Virginia and were detected in 39 of the 60 sites (65 percent) sampled. The presence of total coliform bacteria is a potential indicator of surface contamination, due to improperly constructed or cased wells, or infiltration of soil or other surface contaminants into the aquifer or well bore. <i>E. coli</i> bacteria, however, are much more indicative of fecal contamination of groundwater from either human or animal sources, and 14 of the 60 (23 percent) sites sampled had detections of <i>E. coli</i>. Although only a few strains of <i>E. coli</i> are known pathogens, their presence in groundwater may be an indicator of other related pathogens such as viruses and should be regarded as a serious potential issue. Water treatment such as chlorination, ozonation, or ultraviolet light may be appropriate to kill potential pathogenic bacteria or viruses in the source water.</p><p>Manganese and iron were prevalent contaminants in the groundwater samples collected for this study, with 30 of 60 (50 percent) sites analyzed for manganese and 25 of 60 (42 percent) sites analyzed for iron exceeding the proposed 50- and 300-micrograms per liter (µg/L) SMCL drinking-water standards, respectively, for aesthetic criteria such as taste, odor, or staining of plumbing fixtures. Fourteen of the 60 sites sampled (23 percent) had concentrations of manganese that exceeded the 300-µg/L USGS health-based screening level, and 1 site exceeded the 1,600-µg/L EPA drinking-water equivalent level, which is based on a lifetime exposure level. Sodium is another common constituent in groundwater within the study area. Sodium has an EPA health-based value (HBV) of 20 milligrams per liter (mg/L) for individuals who are on a sodium-restricted diet for blood pressure or other health reasons. Sodium concentrations exceeded the 20-mg/L EPA HBV in 27 of 60 (45 percent) samples.</p><p>Radon, a naturally occurring carcinogenic radioactive gas known to cause lung cancer, was detected at concentrations at or exceeding the proposed 300-picocuries per liter (pCi/L) EPA Maximum Contaminant Level (MCL) in 12 of the 60 (20 percent) sites sampled. Sites with radon gas concentrations exceeding the 300-pCi/L proposed MCL have the potential for airborne concentrations of radon to exceed the 4-pCi/L indoor air standard. Inhalation of radon can cause lung cancer, and the 4-pCi/L indoor air standard is based on an inhalation standard. Therefore, homeowners whose wells have radon gas concentrations exceeding 300 pCi/L may be advised to have their indoor air tested to determine if indoor air concentrations exceed the 4-pCi/L indoor air standard established by the EPA.</p><p>Various factors were analyzed statistically and graphically to determine whether they have an influence on groundwater quality within the study area, including topographic setting, well depth, type of mining (surface or underground), type of site (well or mine outfall), and geologic formation. Only geologic formation and the type of site sampled had strong statistical correlations with one or more of the constituents of concern for this study. The overall chemistry of outfalls (mine outfalls) and wells was significantly different, with a much higher dissolved oxygen content in outfalls than in wells. The dissolved oxygen content is the primary component driving the oxidation and reduction of minerals, and the precipitation of minerals that are saturated or super saturated with respect to various cations and anions. Median dissolved oxygen concentrations for the outfalls sampled was 8.75 mg/L, and only 0.4 mg/L for the wells sampled.</p><p>Median concentrations of sulfate and selenium were much higher in waters from the outfalls sampled, with median concentrations of 73.75 mg/L and 2.35 µg/L, respectively, compared to the wells sampled, which had median concentrations of 18.3 mg/L and less than (&lt;) the 0.05-µg/L method detection limit, respectively. The maximum selenium concentration was for a well, with a concentration of 16.6 µg/L. The geochemical processes that control sulfate and selenium concentrations in groundwater are similar and are the result of the oxidation of sulfide minerals such as pyrite and ferroselite. Iron and manganese concentrations were elevated in most of the wells sampled, with median concentrations of 269.5 and 124.5 µg/L, respectively, but were rarely detected in the outfalls sampled, with median concentrations of &lt; 4.0 and &lt; 0.4 µg/L, respectively. The difference in iron and manganese between wells and outfalls is indicative of the role of dissolved oxygen on processes controlling groundwater chemistry in the region.</p><p>Three principal geologic formations were assessed for the study, and the overall chemistry for the Pocahontas, New River, and Kanawha Formations varied substantially with respect to several constituents. Concentrations of calcium, magnesium, and total dissolved solids were highest for sites sampled in the Pocahontas Formation, with median concentrations of 41.9, 18.6, and 312 mg/L, respectively. For constituents that are commonly associated with mining activity, the highest concentrations were for sites sampled in the New River Formation, with median concentrations of iron and manganese of 2,450 µg/L and 482 µg/L, respectively, and a median pH of 6.35 standard units. Concentrations of barium also were elevated in samples collected from sites in the New River Formation, with a median barium concentration of 184 µg/L. The source of the barium is not fully known but may be associated with commingling of shallow groundwater with deeper brines or dissolution of the mineral barite. The highest median sulfate concentrations were from sites sampled in the Pocahontas Formation, with a median concentration of 64.0 mg/L. Of the 12 sites at or exceeding the 300-pCi/L proposed drinking-water standard for radon, 8 (67 percent of MCL exceedances) were for sites deriving water from the Kanawha Formation, 3 (25 percent of MCL exceedances) were for sites deriving water from the New River Formation, and only 1 site was for water from the Pocahontas Formation (8 percent of proposed MCL exceedances).</p><p>Dissolved hydrocarbons, including methane, ethane, propane, propene, <i>n</i>- and <i>i</i>-butane, 1-butene, <i>n</i>- and <i>i</i>-pentane, pentane, 2- and 3-ethyl pentane, hexane, and benzene were analyzed in samples collected from 59 of the 60 sites to assess the potential occurrence and sources of these trace gases in groundwater within the study area. Results of the analysis indicate that most of the gas is of shallow biogenic origin, possibly associated with coal-bed methane, but a subset of samples has a gas signature and a chloride to bromide ratio indicative of potential mixing with deeper thermogenic gases. Only 2 of the 59 (3.3 percent) sites sampled had concentrations of methane gas, which is a highly combustible and explosive gas, exceeding the 10 milligrams per kilogram level of concern established by the U.S. Office of Surface Mining Reclamation and Enforcement.</p><p>Principal components analysis was used to assess the primary geochemical processes occurring in the aquifers sampled. The first principal component had significant positive loadings for bromide, chloride, silica, ammonia, barium, iron, manganese, and arsenic, and significant negative loadings for dissolved oxygen, potassium, nitrate, and uranium, and reflects reduction and oxidation (redox) processes occurring in deeper anoxic groundwater or shallow oxic groundwater. The strong positive loadings for iron, manganese, barium, and arsenic are correlated with reducing conditions often found deeper in the aquifer. More oxic water is correlated with oxidation of nitrogen species to nitrate and environmental mobilization of uranium and sulfate in shallow wells and mine outfalls.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195059","collaboration":"Prepared in cooperation with the West Virginia Department of Health and Human Resources, Office of Environmental Health Services and the West Virginia Department of Environmental Protection, Division of Water and Waste Management","usgsCitation":"Kozar, M.D., McAdoo, M.A., and Haase, K.B., 2020, Groundwater quality and geochemistry of West Virginia’s southern coal fields (ver. 1.1, March 2020): U.S. Geological Survey Scientific Investigations Report 2019−5059, 78 p., https://doi.org/10.3133/sir20195059.","productDescription":"x, 78 p.","numberOfPages":"92","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-103597","costCenters":[{"id":37280,"text":"Virginia and West Virginia 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1.1: March 2020; Version 1.0: February 2020","contact":"<p><a href=\"mailto:dc_va@usgs.gov\" data-mce-href=\"mailto:dc_va@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/va-wv-water\" data-mce-href=\"https://www.usgs.gov/centers/va-wv-water\">Virginia/West Virginia Science Center</a><br>U.S. Geological Survey<br>11 Dunbar Street<br>Charleston, WV 25301</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods of Data Collection and Analysis</li><li>Groundwater Quality</li><li>Geochemistry</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Correlation matrix showing Spearman correlation coefficients of statistical significance at a confidence interval of 99.9 percent for 46 variables, including 41 chemical constituents and 5 principal component analysis scores</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2020-02-19","revisedDate":"2020-03-12","noUsgsAuthors":false,"publicationDate":"2020-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Kozar, Mark D. 0000-0001-7755-7657 mdkozar@usgs.gov","orcid":"https://orcid.org/0000-0001-7755-7657","contributorId":1963,"corporation":false,"usgs":true,"family":"Kozar","given":"Mark","email":"mdkozar@usgs.gov","middleInitial":"D.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":764486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAdoo, Mitchell A. 0000-0002-3895-0816 mmcadoo@usgs.gov","orcid":"https://orcid.org/0000-0002-3895-0816","contributorId":200287,"corporation":false,"usgs":true,"family":"McAdoo","given":"Mitchell","email":"mmcadoo@usgs.gov","middleInitial":"A.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":764487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haase, Karl B. 0000-0002-6897-6494","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":216317,"corporation":false,"usgs":true,"family":"Haase","given":"Karl B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":764488,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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