{"pageNumber":"395","pageRowStart":"9850","pageSize":"25","recordCount":40805,"records":[{"id":70196295,"text":"70196295 - 2018 - Morphological indicators of a mascon beneath Ceres' largest crater, Kerwan","interactions":[],"lastModifiedDate":"2018-04-02T10:41:05","indexId":"70196295","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Morphological indicators of a mascon beneath Ceres' largest crater, Kerwan","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Gravity data of Ceres returned by the National Aeronautics and Space Administration's Dawn spacecraft is consistent with a lower density crust of variable thickness overlying a higher density mantle. Crustal thickness variations can affect the long‐term, postimpact modification of impact craters on Ceres. Here we show that the unusual morphology of the 280&nbsp;km diameter crater Kerwan may result from viscous relaxation in an outer layer that thins substantially beneath the crater floor. We propose that such a structure is consistent with either impact‐induced uplift of the high‐density mantle beneath the crater or from volatile loss during the impact event. In either case, the subsurface structure inferred from the crater morphology is superisostatic, and the mass excess would result in a positive Bouguer anomaly beneath the crater, consistent with the highest‐degree gravity data from Dawn. Ceres joins the Moon, Mars, and Mercury in having basin‐associated gravity anomalies, although their origin may differ substantially.</p></div></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL075526","usgsCitation":"Bland, M.T., Ermakov, A., Raymond, C.A., Williams, D., Bowling, T.J., Preusker, F., Park, R., Marchi, S., Castillo-Rogez, J.C., Fu, R., and Russell, C.T., 2018, Morphological indicators of a mascon beneath Ceres' largest crater, Kerwan: Geophysical Research Letters, v. 45, no. 3, p. 1297-1304, https://doi.org/10.1002/2017GL075526.","productDescription":"8 p.","startPage":"1297","endPage":"1304","ipdsId":"IP-090456","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":499997,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/f89798f4b4fc45c7bdd7716972754263","text":"External Repository"},{"id":353026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-12","publicationStatus":"PW","scienceBaseUri":"5afee741e4b0da30c1bfc1e3","contributors":{"authors":[{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":732204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ermakov, Anton","contributorId":189478,"corporation":false,"usgs":false,"family":"Ermakov","given":"Anton","email":"","affiliations":[],"preferred":false,"id":732205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raymond, Carol A.","contributorId":200798,"corporation":false,"usgs":false,"family":"Raymond","given":"Carol","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":732206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, David A.","contributorId":84604,"corporation":false,"usgs":true,"family":"Williams","given":"David A.","affiliations":[],"preferred":false,"id":732207,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowling, Tim J.","contributorId":203743,"corporation":false,"usgs":false,"family":"Bowling","given":"Tim","email":"","middleInitial":"J.","affiliations":[{"id":36705,"text":"University of Chicago","active":true,"usgs":false}],"preferred":false,"id":732208,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Preusker, F.","contributorId":39659,"corporation":false,"usgs":true,"family":"Preusker","given":"F.","affiliations":[],"preferred":false,"id":732209,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Park, Ryan S.","contributorId":200803,"corporation":false,"usgs":false,"family":"Park","given":"Ryan S.","affiliations":[],"preferred":false,"id":732210,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marchi, Simone","contributorId":192193,"corporation":false,"usgs":false,"family":"Marchi","given":"Simone","affiliations":[],"preferred":false,"id":732211,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Castillo-Rogez, Julie C.","contributorId":201111,"corporation":false,"usgs":false,"family":"Castillo-Rogez","given":"Julie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":732212,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fu, R.R.","contributorId":173388,"corporation":false,"usgs":false,"family":"Fu","given":"R.R.","email":"","affiliations":[{"id":27078,"text":"Columbia University, New York","active":true,"usgs":false}],"preferred":false,"id":732213,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Russell, Christopher T.","contributorId":69451,"corporation":false,"usgs":true,"family":"Russell","given":"Christopher","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":732214,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70197893,"text":"70197893 - 2018 - Seismic hazard, risk, and design for South America","interactions":[],"lastModifiedDate":"2018-10-04T13:27:16","indexId":"70197893","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Seismic hazard, risk, and design for South America","docAbstract":"<p><span>We calculate seismic hazard, risk, and design criteria across South America using the latest data, models, and methods to support public officials, scientists, and engineers in earthquake risk mitigation efforts. Updated continental scale seismic hazard models are based on a new seismicity catalog, seismicity rate models, evaluation of earthquake sizes, fault geometry and rate parameters, and ground‐motion models. Resulting probabilistic seismic hazard maps show peak ground acceleration, modified Mercalli intensity, and spectral accelerations at 0.2 and 1&nbsp;s periods for 2%, 10%, and 50% probabilities of exceedance in 50 yrs. Ground shaking soil amplification at each site is calculated by considering uniform soil that is applied in modern building codes or by applying site‐specific factors based on&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>V</mi><mrow><mi>S</mi><mn>30</mn></mrow></msub></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msub\"><span><span><span id=\"MathJax-Span-4\" class=\"mi\">V</span></span><sub><span><span id=\"MathJax-Span-5\" class=\"mrow\"><span id=\"MathJax-Span-6\" class=\"mi\">S</span><span id=\"MathJax-Span-7\" class=\"mn\">30</span></span></span></sub></span></span></span></span></span></span></span></span><span><span>&nbsp;</span>shear‐wave velocities determined through a simple topographic proxy technique. We use these hazard models in conjunction with the Prompt Assessment of Global Earthquakes for Response (PAGER) model to calculate economic and casualty risk. Risk is computed by incorporating the new hazard values amplified by soil, PAGER fragility/vulnerability equations, and LandScan 2012 estimates of population exposure. We also calculate building design values using the guidelines established in the building code provisions. Resulting hazard and associated risk is high along the northern and western coasts of South America, reaching damaging levels of ground shaking in Chile, western Argentina, western Bolivia, Peru, Ecuador, Colombia, Venezuela, and in localized areas distributed across the rest of the continent where historical earthquakes have occurred. Constructing buildings and other structures to account for strong shaking in these regions of high hazard and risk should mitigate losses and reduce casualties from effects of future earthquake strong ground shaking. National models should be developed by scientists and engineers in each country using the best available science.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170002","usgsCitation":"Petersen, M.D., Harmsen, S., Jaiswal, K.S., Rukstales, K.S., Luco, N., Haller, K., Mueller, C., and Shumway, A., 2018, Seismic hazard, risk, and design for South America: Bulletin of the Seismological Society of America, v. 108, no. 2, p. 781-800, https://doi.org/10.1785/0120170002.","productDescription":"20 p.","startPage":"781","endPage":"800","ipdsId":"IP-088385","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":438040,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WM1BK1","text":"USGS data release","linkHelpText":"Seismic Hazard, Risk, and Design for South America"},{"id":355335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"South America","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.3203125,\n              -56.75272287205735\n            ],\n            [\n              -33.92578125,\n              -56.75272287205735\n            ],\n            [\n              -33.92578125,\n              14.604847155053898\n            ],\n            [\n              -83.3203125,\n              14.604847155053898\n            ],\n            [\n              -83.3203125,\n              -56.75272287205735\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"108","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-16","publicationStatus":"PW","scienceBaseUri":"5b46e5d2e4b060350a15d21a","contributors":{"authors":[{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":738964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harmsen, Stephen 0000-0003-1759-5154 harmsen@usgs.gov","orcid":"https://orcid.org/0000-0003-1759-5154","contributorId":205962,"corporation":false,"usgs":true,"family":"Harmsen","given":"Stephen","email":"harmsen@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rukstales, Kenneth S. 0000-0003-2818-078X rukstales@usgs.gov","orcid":"https://orcid.org/0000-0003-2818-078X","contributorId":775,"corporation":false,"usgs":true,"family":"Rukstales","given":"Kenneth","email":"rukstales@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haller, Kathleen 0000-0001-8847-7302 haller@usgs.gov","orcid":"https://orcid.org/0000-0001-8847-7302","contributorId":172556,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":738970,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shumway, Allison 0000-0003-1142-7141 ashumway@usgs.gov","orcid":"https://orcid.org/0000-0003-1142-7141","contributorId":147862,"corporation":false,"usgs":true,"family":"Shumway","given":"Allison","email":"ashumway@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738971,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70197434,"text":"70197434 - 2018 - Deciphering the link between doubly uniparental inheritance of mtDNA and sex determination in bivalves: Clues from comparative transcriptomics","interactions":[],"lastModifiedDate":"2018-06-05T09:48:37","indexId":"70197434","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3832,"text":"Genome Biology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Deciphering the link between doubly uniparental inheritance of mtDNA and sex determination in bivalves: Clues from comparative transcriptomics","docAbstract":"<p><span>Bivalves exhibit an astonishing diversity of sexual systems and sex-determining mechanisms. They can be gonochoric, hermaphroditic or androgenetic, with both genetic and environmental factors known to determine or influence sex. One unique sex-determining system involving the mitochondrial genome has also been hypothesized to exist in bivalves with doubly uniparental inheritance (DUI) of mtDNA. However, the link between DUI and sex determination remains obscure. In this study, we performed a comparative gonad transcriptomics analysis for two DUI-possessing freshwater mussel species to better understand the mechanisms underlying sex determination and DUI in these bivalves. We used a BLAST reciprocal analysis to identify orthologs between&nbsp;</span><i>Venustaconcha ellipsiformis</i><span><span>&nbsp;</span>and<span>&nbsp;</span></span><i>Utterbackia peninsularis</i><span><span>&nbsp;</span>and compared our results with previously published sex-specific bivalve transcriptomes to identify conserved sex-determining genes. We also compared our data with other DUI species to identify candidate genes possibly involved in the regulation of DUI. A total of ∼12,000 orthologous relationships were found, with 2,583 genes differentially expressed in both species. Among these genes, key sex-determining factors previously reported in vertebrates and in bivalves (e.g.,<span>&nbsp;</span></span><i>Sry, Dmrt1, Foxl2</i><span>) were identified, suggesting that some steps of the sex-determination pathway may be deeply conserved in metazoans. Our results also support the hypothesis that a modified ubiquitination mechanism could be responsible for the retention of the paternal mtDNA in male bivalves, and revealed that DNA methylation could also be involved in the regulation of DUI. Globally, our results suggest that sets of genes associated with sex determination and DUI are similar in distantly-related DUI species.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/gbe/evy019","usgsCitation":"Capt, C., Renaut, S., Ghiselli, F., Milani, L., Johnson, N.A., Sietman, B.E., Stewart, D., and Breton, S., 2018, Deciphering the link between doubly uniparental inheritance of mtDNA and sex determination in bivalves: Clues from comparative transcriptomics: Genome Biology and Evolution, v. 10, no. 2, p. 577-590, https://doi.org/10.1093/gbe/evy019.","productDescription":"14 p.","startPage":"577","endPage":"590","ipdsId":"IP-092196","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469078,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gbe/evy019","text":"Publisher Index Page"},{"id":354709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-19","publicationStatus":"PW","scienceBaseUri":"5b46e5d4e4b060350a15d226","contributors":{"authors":[{"text":"Capt, Charlotte","contributorId":205385,"corporation":false,"usgs":false,"family":"Capt","given":"Charlotte","email":"","affiliations":[{"id":37091,"text":"Université de Montréal","active":true,"usgs":false}],"preferred":false,"id":737135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Renaut, Sébastien","contributorId":205386,"corporation":false,"usgs":false,"family":"Renaut","given":"Sébastien","affiliations":[{"id":37091,"text":"Université de Montréal","active":true,"usgs":false}],"preferred":false,"id":737136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ghiselli, Fabrizio","contributorId":205387,"corporation":false,"usgs":false,"family":"Ghiselli","given":"Fabrizio","email":"","affiliations":[{"id":37091,"text":"Université de Montréal","active":true,"usgs":false}],"preferred":false,"id":737137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Milani, Liliana","contributorId":205388,"corporation":false,"usgs":false,"family":"Milani","given":"Liliana","email":"","affiliations":[{"id":37091,"text":"Université de Montréal","active":true,"usgs":false}],"preferred":false,"id":737138,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Nathan A. 0000-0001-5167-1988 najohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":4175,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","email":"najohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":737134,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sietman, Bernard E.","contributorId":196565,"corporation":false,"usgs":false,"family":"Sietman","given":"Bernard","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":737139,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stewart, Donald","contributorId":205389,"corporation":false,"usgs":false,"family":"Stewart","given":"Donald","affiliations":[{"id":37092,"text":"Acadia University","active":true,"usgs":false}],"preferred":false,"id":737140,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Breton, Sophie 0000-0002-8286-486X","orcid":"https://orcid.org/0000-0002-8286-486X","contributorId":196560,"corporation":false,"usgs":false,"family":"Breton","given":"Sophie","email":"","affiliations":[],"preferred":false,"id":737141,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70197414,"text":"70197414 - 2018 - Assessing the influence of multiple stressors on stream diatom metrics in the upper Midwest, USA","interactions":[],"lastModifiedDate":"2018-06-01T13:10:02","indexId":"70197414","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the influence of multiple stressors on stream diatom metrics in the upper Midwest, USA","docAbstract":"<p>Water resource managers face increasing challenges in identifying what physical and chemical stressors are responsible for the alteration of biological conditions in streams. The objective of this study was to assess the comparative influence of multiple stressors on benthic diatoms at 98 sites that spanned a range of stressors in an agriculturally dominated region in the upper Midwest, USA. The primary stressors of interest included: nutrients, herbicides and fungicides, sediment, and streamflow; although the influence of physical habitat was incorporated in the assessment. Boosted Regression Tree was used to examine both the sensitivity of various diatom metrics and the relative importance of the primary stressors. Percent Sensitive Taxa, percent Highly Motile Taxa, and percent High Phosphorus Taxa had the strongest response to stressors. Habitat and total phosphorous were the most common discriminators of diatom metrics, with herbicides as secondary factors. A Classification and Regression Tree (CART) model was used to examine conditional relations among stressors and indicated that fine-grain streams had a lower percentage of Sensitive Taxa than coarse-grain streams, with Sensitive Taxa decreasing further with increased water temperature (&gt;30 °C) and triazine concentrations (&gt;1500 ng/L). In contrast, streams dominated by coarse-grain substrate contained a higher percentage of Sensitive Taxa, with relative abundance increasing with lower water temperatures (&lt;29 °C) and shallower water depth (&lt;0.3 m). Quantile regression indicated that maximum water temperature appears to be a major limiting factor in Midwest streams; whereas both total phosphorus and percent fines showed a slight subsidy-stress response. While using benthic algae for assessing stream quality can be challenging, field-based studies can elucidate stressor effects and interactions when the response variables are appropriate, sufficient stressor resolution is achieved, and the number and type of sites represent a gradient of stressor conditions and at least a quasi-factorial design.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2017.09.005","usgsCitation":"Munn, M., Waite, I.R., and Konrad, C.P., 2018, Assessing the influence of multiple stressors on stream diatom metrics in the upper Midwest, USA: Ecological Indicators, v. 85, p. 1239-1248, https://doi.org/10.1016/j.ecolind.2017.09.005.","productDescription":"10 p.","startPage":"1239","endPage":"1248","ipdsId":"IP-081927","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":469080,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2017.09.005","text":"Publisher Index Page"},{"id":438041,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7513X35","text":"USGS data release","linkHelpText":"Data on Midwest stream diatom and stressors, 2013"},{"id":354670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100,\n              36.5\n            ],\n            [\n              -81,\n              36.5\n            ],\n            [\n              -81,\n              45\n            ],\n            [\n              -100,\n              45\n            ],\n            [\n              -100,\n              36.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"85","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155dade4b092d9651e1b7b","contributors":{"authors":[{"text":"Munn, Mark D. 0000-0002-7154-7252","orcid":"https://orcid.org/0000-0002-7154-7252","contributorId":205360,"corporation":false,"usgs":true,"family":"Munn","given":"Mark D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737084,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70197955,"text":"70197955 - 2018 - Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager","interactions":[],"lastModifiedDate":"2018-06-28T11:55:53","indexId":"70197955","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager","docAbstract":"<p><span>In this study, we demonstrated that the Landsat-8 Operational Land Imager (OLI) sensor is a powerful tool that can provide periodic and system-wide information on the condition of drinking water reservoirs. The OLI is a multispectral radiometer (30&nbsp;m spatial resolution) that allows ecosystem observations at spatial and temporal scales that allow the environmental community and water managers another means to monitor changes in water quality not feasible with field-based monitoring. Using the provisional Land Surface Reflectance product and field-collected chlorophyll-</span><i>a</i><span><span>&nbsp;</span>(chl-</span><i>a</i><span>) concentrations from drinking water monitoring programs in North Carolina and Rhode Island, we compared five established approaches for estimating chl-</span><i>a</i><span>concentrations using spectral data. We found that using the three band reflectance approach with a combination of OLI spectral bands 1, 3, and 5 produced the most promising results for accurately estimating chl-</span><i>a</i><span><span>&nbsp;</span>concentrations in lakes (</span><i>R</i><sup>2</sup><span><span>&nbsp;</span>value of 0.66; root mean square error value of 8.9&nbsp;µg l</span><sup>−1</sup><span>). Using this model, we forecast the spatial and temporal variability of chl-</span><i>a</i><span><span>&nbsp;</span>for Jordan Lake, a recreational and drinking water source in piedmont North Carolina and several small ponds that supply drinking water in southeastern Rhode Island.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2018.1430912","usgsCitation":"Keith, D., Rover, J., Green, J., Zalewsky, B., Charpentier, M., Hursby, G., and Bishop, J., 2018, Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager: International Journal of Remote Sensing, v. 39, no. 9, p. 2818-2846, https://doi.org/10.1080/01431161.2018.1430912.","productDescription":"29 p.","startPage":"2818","endPage":"2846","ipdsId":"IP-096964","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469076,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6020680","text":"External Repository"},{"id":355407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.2,\n              35.6333\n            ],\n            [\n              -78.8333,\n              35.6333\n            ],\n            [\n              -78.8333,\n              35.8833\n            ],\n            [\n              -79.2,\n              35.8833\n            ],\n            [\n              -79.2,\n              35.6333\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"39","issue":"9","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-29","publicationStatus":"PW","scienceBaseUri":"5b46e5d2e4b060350a15d218","contributors":{"authors":[{"text":"Keith, Darryl","contributorId":206068,"corporation":false,"usgs":false,"family":"Keith","given":"Darryl","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":739317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rover, Jennifer 0000-0002-3437-4030","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":26162,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":739316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Green, Jason","contributorId":206069,"corporation":false,"usgs":false,"family":"Green","given":"Jason","email":"","affiliations":[{"id":37231,"text":"NC DENR","active":true,"usgs":false}],"preferred":false,"id":739318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zalewsky, Brian","contributorId":206070,"corporation":false,"usgs":false,"family":"Zalewsky","given":"Brian","email":"","affiliations":[{"id":37232,"text":"RI DEMP","active":true,"usgs":false}],"preferred":false,"id":739319,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Charpentier, Mike","contributorId":206071,"corporation":false,"usgs":false,"family":"Charpentier","given":"Mike","email":"","affiliations":[{"id":37233,"text":"Raytheon Company","active":true,"usgs":false}],"preferred":false,"id":739320,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hursby, Glen","contributorId":206072,"corporation":false,"usgs":false,"family":"Hursby","given":"Glen","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":739321,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bishop, Joseph","contributorId":206073,"corporation":false,"usgs":false,"family":"Bishop","given":"Joseph","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":739322,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70197972,"text":"70197972 - 2018 - Preparing for an uncertain future: Migrating shorebird response to past climatic fluctuations in the Prairie Potholes","interactions":[],"lastModifiedDate":"2018-07-02T11:09:44","indexId":"70197972","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Preparing for an uncertain future: Migrating shorebird response to past climatic fluctuations in the Prairie Potholes","docAbstract":"<p><span>The Prairie Pothole Region, situated in the northern Great Plains, provides important stopover habitat for migratory shorebirds. During spring migration in the U.S. Prairie Potholes, 7.3&nbsp;million shorebirds refuel in the region's myriad small, freshwater wetlands. Shorebirds use mudflats, shorelines, and ephemeral wetlands that are far more abundant in wet years than dry years. Generally, climate change is expected to bring warmer temperatures, seasonality shifts, more extreme events, and changes to precipitation. The impacts to wetland habitats are uncertain. In the Prairie Potholes, earlier spring onset and warmer temperatures may advance drying of wetlands or, alternately, increased spring precipitation may produce abundant shallow‐water habitats. To look at the availability of habitats for migratory shorebirds under different climate regimes, we compared habitat selection between a historic wet year and a dry year using binomial random‐effects models to describe local and landscape patterns. We found that in the dry year shorebirds were distributed more northerly and among more permanent wetlands, whereas in the wet year shorebirds were distributed more southerly and among more temporary wetlands. However, landscape‐scale variation played a larger role in the dry year. At the local wetland scale, shorebirds selected similarly between years—for shallower wetlands and wetlands in croplands. Overall, while shorebirds were sensitive to local habitat conditions, they exhibited a degree of adaptive capacity to climate change impacts by their ability to shift on the landscape. This indicates an avenue through which management decisions can enhance climate change resilience for these species given an uncertain future—by preserving shallow‐water wetlands in croplands throughout the landscape.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2095","usgsCitation":"Steen, V., Skagen, S., and Noon, B.R., 2018, Preparing for an uncertain future: Migrating shorebird response to past climatic fluctuations in the Prairie Potholes: Ecosphere, v. 9, no. 2, p. 1-12, https://doi.org/10.1002/ecs2.2095.","productDescription":"e02095; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-088903","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469077,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2095","text":"Publisher Index Page"},{"id":438042,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7W37VJW","text":"USGS data release","linkHelpText":"Data for shorebird migration across the prairie potholes in 2002 and 2011"},{"id":355444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104,\n              42.5\n            ],\n            [\n              -93,\n              42.5\n            ],\n            [\n              -93,\n              49\n            ],\n            [\n              -104,\n              49\n            ],\n            [\n              -104,\n              42.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-27","publicationStatus":"PW","scienceBaseUri":"5b46e5d2e4b060350a15d216","contributors":{"authors":[{"text":"Steen, Valerie A. 0000-0002-1417-8139","orcid":"https://orcid.org/0000-0002-1417-8139","contributorId":205994,"corporation":false,"usgs":false,"family":"Steen","given":"Valerie A.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":739401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skagen, Susan K. 0000-0002-6744-1244 skagens@usgs.gov","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":167829,"corporation":false,"usgs":true,"family":"Skagen","given":"Susan K.","email":"skagens@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":739400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Noon, Barry R.","contributorId":198981,"corporation":false,"usgs":false,"family":"Noon","given":"Barry","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":739402,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70195167,"text":"70195167 - 2018 - Assessing intrinsic and specific vulnerability models ability to indicate groundwater vulnerability to groups of similar pesticides: A comparative study","interactions":[],"lastModifiedDate":"2018-10-04T13:41:33","indexId":"70195167","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3059,"text":"Physical Geography","active":true,"publicationSubtype":{"id":10}},"title":"Assessing intrinsic and specific vulnerability models ability to indicate groundwater vulnerability to groups of similar pesticides: A comparative study","docAbstract":"<p><span>With continued population growth and increasing use of fresh groundwater resources, protection of this valuable resource is critical. A cost effective means to assess risk of groundwater contamination potential will provide a useful tool to protect these resources. Integrating geospatial methods offers a means to quantify the risk of contaminant potential in cost effective and spatially explicit ways. This research was designed to compare the ability of intrinsic (DRASTIC) and specific (Attenuation Factor; AF) vulnerability models to indicate groundwater vulnerability areas by comparing model results to the presence of pesticides from groundwater sample datasets. A logistic regression was used to assess the relationship between the environmental variables and the presence or absence of pesticides within regions of varying vulnerability. According to the DRASTIC model, more than 20% of the study area is very highly vulnerable. Approximately 30% is very highly vulnerable according to the AF model. When groundwater concentrations of individual pesticides were compared to model predictions, the results were mixed. Model predictability improved when concentrations of the group of similar pesticides were compared to model results. Compared to the DRASTIC model, the AF model more accurately predicts the distribution of the number of contaminated wells within each vulnerability class.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02723646.2017.1406300","usgsCitation":"Douglas, S.H., Dixon, B., and Griffin, D.W., 2018, Assessing intrinsic and specific vulnerability models ability to indicate groundwater vulnerability to groups of similar pesticides: A comparative study: Physical Geography, v. 39, no. 6, p. 487-505, https://doi.org/10.1080/02723646.2017.1406300.","productDescription":"19 p.","startPage":"487","endPage":"505","ipdsId":"IP-081836","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":351284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-08","publicationStatus":"PW","scienceBaseUri":"5a7c1e73e4b00f54eb2292e4","contributors":{"authors":[{"text":"Douglas, Steven H. 0000-0001-9078-538X sdouglas@usgs.gov","orcid":"https://orcid.org/0000-0001-9078-538X","contributorId":182361,"corporation":false,"usgs":true,"family":"Douglas","given":"Steven","email":"sdouglas@usgs.gov","middleInitial":"H.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":727277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dixon, Barnali","contributorId":201960,"corporation":false,"usgs":false,"family":"Dixon","given":"Barnali","email":"","affiliations":[{"id":36308,"text":"USFSP","active":true,"usgs":false}],"preferred":false,"id":727278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":727279,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194994,"text":"70194994 - 2018 - Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality","interactions":[],"lastModifiedDate":"2018-02-01T17:03:36","indexId":"70194994","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality","docAbstract":"<p><span>Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause-of-death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3701","usgsCitation":"Walsh, D.P., Norton, A.S., Storm, D.J., Van Deelen, T.R., and Heisy, D.M., 2018, Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality: Ecology and Evolution, v. 8, no. 1, p. 509-520, https://doi.org/10.1002/ece3.3701.","productDescription":"12 p.","startPage":"509","endPage":"520","ipdsId":"IP-090309","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":461055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3701","text":"Publisher Index Page"},{"id":350936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-30","publicationStatus":"PW","scienceBaseUri":"5a74357de4b0a9a2e9e25c72","contributors":{"authors":[{"text":"Walsh, Daniel P. 0000-0002-7772-2445 dwalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":4758,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"dwalsh@usgs.gov","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":726489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norton, Andrew S.","contributorId":171631,"corporation":false,"usgs":false,"family":"Norton","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":726490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storm, Daniel J.","contributorId":171373,"corporation":false,"usgs":false,"family":"Storm","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":24576,"text":"University of Wisconsin, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":726491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Deelen, Timothy R.","contributorId":145413,"corporation":false,"usgs":false,"family":"Van Deelen","given":"Timothy","email":"","middleInitial":"R.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":726492,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heisy, Dennis M.","contributorId":201572,"corporation":false,"usgs":false,"family":"Heisy","given":"Dennis","email":"","middleInitial":"M.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":726493,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196274,"text":"70196274 - 2018 - Long‐term trends in fall age ratios of black brant","interactions":[],"lastModifiedDate":"2018-03-30T10:50:59","indexId":"70196274","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Long‐term trends in fall age ratios of black brant","docAbstract":"<p><span>Accurate estimates of the age composition of populations can inform past reproductive success and future population trajectories. We examined fall age ratios (juveniles:total birds) of black brant (</span><i>Branta bernicla nigricans</i><span>; brant) staging at Izembek National Wildlife Refuge near the tip of the Alaska Peninsula, southwest Alaska, USA, 1963 to 2015. We also investigated variation in fall age ratios associated with sampling location, an index of flock size, survey effort, day of season, observer, survey platform (boat‐ or land‐based) and tide stage. We analyzed data using logistic regression models implemented in a Bayesian framework. Mean predicted fall age ratio controlling for survey effort, day of year, and temporal and spatial variation was 0.24 (95% CL = 0.23, 0.25). Overall trend in age ratios was −0.6% per year (95% CL = −1.3%, 0.2%), resulting in an approximate 26% decline in the proportion of juveniles over the study period. We found evidence for variation across a range of variables implying that juveniles are not randomly distributed in space and time within Izembek Lagoon. Age ratios varied by location within the study area and were highly variable among years. They decreased with the number of birds aged (an index of flock size) and increased throughout September before leveling off in early October and declining in late October. Age ratios were similar among tide stages and observers and were lower during boat‐based (offshore) than land‐based (nearshore) surveys. Our results indicate surveys should be conducted annually during early to mid‐October to ensure the entire population is present and available for sampling, and throughout Izembek Lagoon to account for spatiotemporal variation in age ratios. Sampling should include a wide range of flock sizes representative of their distribution and occur in flocks located near and off shore. Further research evaluating the cause of declining age ratios in the fall population is necessary to inform management and predict long‐term population dynamics of brant.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21388","usgsCitation":"Ward, D.H., Amundson, C.L., Stehn, R.A., and Dau, C.P., 2018, Long‐term trends in fall age ratios of black brant: Journal of Wildlife Management, v. 82, no. 2, p. 362-373, https://doi.org/10.1002/jwmg.21388.","productDescription":"12 p.","startPage":"362","endPage":"373","ipdsId":"IP-082174","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":461053,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21388","text":"Publisher Index Page"},{"id":438037,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13578ZF","text":"USGS data release","linkHelpText":"Brant Age Ratio Model"},{"id":438036,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QIJIU2","text":"USGS data release","linkHelpText":"Data and Model-based Estimates from Black Brant (Branta bernicla nigricans) Fall Age Ratio Surveys at Izembek Lagoon, Alaska"},{"id":352991,"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              -163.42987060546875,\n              55.02802211299252\n            ],\n            [\n              -162.46856689453125,\n              55.02802211299252\n            ],\n            [\n              -162.46856689453125,\n              55.51774716789874\n            ],\n            [\n              -163.42987060546875,\n              55.51774716789874\n            ],\n            [\n              -163.42987060546875,\n              55.02802211299252\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"82","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-27","publicationStatus":"PW","scienceBaseUri":"5afee741e4b0da30c1bfc1e7","contributors":{"authors":[{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","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":732022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amundson, Courtney L. 0000-0002-0166-7224 camundson@usgs.gov","orcid":"https://orcid.org/0000-0002-0166-7224","contributorId":4833,"corporation":false,"usgs":true,"family":"Amundson","given":"Courtney","email":"camundson@usgs.gov","middleInitial":"L.","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":732023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stehn, Robert A.","contributorId":83986,"corporation":false,"usgs":true,"family":"Stehn","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":732024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dau, Christian P.","contributorId":26185,"corporation":false,"usgs":true,"family":"Dau","given":"Christian","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":732025,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198104,"text":"70198104 - 2018 - Use of remote sensing to detect and predict aquatic nuisance vegetation growth in coastal Louisiana: Summary of findings","interactions":[],"lastModifiedDate":"2018-07-24T15:57:54","indexId":"70198104","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5722,"text":"ERDC Technical Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"ERDC/EL TR-18-3","title":"Use of remote sensing to detect and predict aquatic nuisance vegetation growth in coastal Louisiana: Summary of findings","docAbstract":"<p><span>On an annual basis, federal and state agencies are responsible for mapping and removing large expanses of aquatic nuisance vegetation from navigable waterways. This study set out to achieve four primary objectives: (1) utilize recent advancements in remote sensing techniques to classify the extent and distribution of aquatic vegetation in coastal ecosystems using satellite imagery, (2) assess primary aquatic vegetation growth and management efforts in coastal Louisiana, (3) statistically identify the ecological drivers that promote growth and infestation of aquatic nuisance vegetation, and (4) develop numerical models and a spatial tool to predict the probability of occurrence and growth of aquatic vegetation given ecological drivers. Moderate spatial resolution multispectral satellite imagery were used in conjunction with environmental variables from available data streams to generate regression models that predict aquatic vegetation occurrence in the eastern coastal region of south Louisiana. Geospatial tools were developed to execute the model logic using recent environmental conditions, thereby predicting aquatic vegetation occurrence and producing classified maps for end users. These products provide more efficient and enhanced capabilities for management of aquatic nuisance vegetation.</span></p>","language":"English","publisher":"Engineer Research and Development Center","doi":"10.21079/11681/26649","usgsCitation":"Suir, G.M., Suir, K.J., and Sapkota, S., 2018, Use of remote sensing to detect and predict aquatic nuisance vegetation growth in coastal Louisiana: Summary of findings: ERDC Technical Report ERDC/EL TR-18-3, xi, 87 p., https://doi.org/10.21079/11681/26649.","productDescription":"xi, 87 p.","ipdsId":"IP-079845","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":461061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21079/11681/26649","text":"Publisher Index Page"},{"id":355961,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.6968994140625,\n              28.86391842622456\n            ],\n            [\n              -88.9617919921875,\n              28.86391842622456\n            ],\n            [\n              -88.9617919921875,\n              30.538607878854556\n            ],\n            [\n              -93.6968994140625,\n              30.538607878854556\n            ],\n            [\n              -93.6968994140625,\n              28.86391842622456\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-10","publicationStatus":"PW","scienceBaseUri":"5b6fc4a7e4b0f5d57878eab5","contributors":{"authors":[{"text":"Suir, Glenn M.","contributorId":206307,"corporation":false,"usgs":false,"family":"Suir","given":"Glenn","email":"","middleInitial":"M.","affiliations":[{"id":37304,"text":"U.S. Army Engineer Research and Development Center","active":true,"usgs":false}],"preferred":false,"id":740035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Suir, Kevin J. 0000-0003-1570-9648 suirk@usgs.gov","orcid":"https://orcid.org/0000-0003-1570-9648","contributorId":4894,"corporation":false,"usgs":true,"family":"Suir","given":"Kevin","email":"suirk@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":740034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sapkota, Sijan","contributorId":206308,"corporation":false,"usgs":false,"family":"Sapkota","given":"Sijan","affiliations":[{"id":37305,"text":"U.S. Army Medical Department Center and School","active":true,"usgs":false}],"preferred":false,"id":740036,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196285,"text":"70196285 - 2018 - Image simulation and assessment of the colour and spatial capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter","interactions":[],"lastModifiedDate":"2018-03-30T11:11:48","indexId":"70196285","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3454,"text":"Space Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Image simulation and assessment of the colour and spatial capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter","docAbstract":"<p><span>This study aims to assess the spatial and visible/near-infrared (VNIR) colour/spectral capabilities of the 4-band Colour and Stereo Surface Imaging System (CaSSIS) aboard the ExoMars 2016 Trace Grace Orbiter (TGO). The instrument response functions for the CaSSIS imager was used to resample spectral libraries, modelled spectra and to construct spectrally (</span><i class=\"EmphasisTypeItalic \">i.e.</i><span>, in I/F space) and spatially consistent simulated CaSSIS image cubes of various key sites of interest and for ongoing scientific investigations on Mars. Coordinated datasets from Mars Reconnaissance Orbiter (MRO) are ideal, and specifically used for simulating CaSSIS. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provides colour information, while the Context Imager (CTX), and in a few cases the High-Resolution Imaging Science Experiment (HiRISE), provides the complementary spatial information at the resampled CaSSIS unbinned/unsummed pixel resolution (4.6 m/pixel from a 400-km altitude). The methodology used herein employs a Gram-Schmidt spectral sharpening algorithm to combine the ∼18–36 m/pixel CRISM-derived CaSSIS colours with I/F images primarily derived from oversampled CTX images. One hundred and eighty-one simulated CaSSIS 4-colour image cubes (at 18–36 m/pixel) were generated (including one of Phobos) based on CRISM data. From these, thirty-three “fully”-simulated image cubes of thirty unique locations on Mars (</span><i class=\"EmphasisTypeItalic \">i.e.</i><span>, with 4 colour bands at 4.6 m/pixel) were made. All simulated image cubes were used to test both the colour capabilities of CaSSIS by producing standard colour RGB images, colour band ratio composites (CBRCs) and spectral parameters. Simulated CaSSIS CBRCs demonstrated that CaSSIS will be able to readily isolate signatures related to ferrous (Fe</span><sup>2+</sup><span>) iron- and ferric (Fe</span><sup>3+</sup><span>) iron-bearing deposits on the surface of Mars, ices and atmospheric phenomena. Despite the lower spatial resolution of CaSSIS when compared to HiRISE, the results of this work demonstrate that CaSSIS will not only compliment HiRISE-scale studies of various geological and seasonal phenomena, it will also enhance them by providing additional colour and geologic context through its wider and longer full-colour coverage (</span><span id=\"IEq1\" class=\"InlineEquation\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo>&amp;#x223C;</mo><mn>9.4</mn><mo>&amp;#x00D7;</mo><mn>50</mn></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mo\">∼</span><span id=\"MathJax-Span-4\" class=\"mn\">9.4</span><span id=\"MathJax-Span-5\" class=\"mo\">×</span><span id=\"MathJax-Span-6\" class=\"mn\">50</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">∼9.4×50</span></span></span><span><span>&nbsp;</span>km), and its increased sensitivity to iron-bearing materials from its two IR bands (RED and NIR). In a few examples, subtle surface changes that were not easily detected by HiRISE were identified in the simulated CaSSIS images. This study also demonstrates the utility of the Gram-Schmidt spectral pan-sharpening technique to extend VNIR colour/spectral capabilities from a lower spatial resolution colour/spectral dataset to a single-band or panchromatic image greyscale image with higher resolution. These higher resolution colour products (simulated CaSSIS or otherwise) are useful as means to extend both geologic context and mapping of datasets with coarser spatial resolutions. The results of this study indicate that the TGO mission objectives, as well as the instrument-specific mission objectives, will be achievable with CaSSIS.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11214-017-0436-7","usgsCitation":"Tornabene, L.L., Seelos, F.P., Pommerol, A., Thomas, N., Caudill, C.M., Becerra, P., Bridges, J.C., Byrne, S., Cardinale, M., Chojnacki, M., Conway, S.J., Cremonese, G., Dundas, C.M., El-Maarry, M.R., Fernando, J., Hansen, C.J., Hansen, K., Harrison, T.N., Henson, R., Marinangeli, L., McEwen, A.S., Pajola, M., Sutton, S.S., and Wray, J.J., 2018, Image simulation and assessment of the colour and spatial capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter: Space Science Reviews, v. 214, Article 18, https://doi.org/10.1007/s11214-017-0436-7.","productDescription":"Article 18","ipdsId":"IP-084888","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":469083,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-02270615","text":"External Repository"},{"id":352994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"214","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-13","publicationStatus":"PW","scienceBaseUri":"5afee741e4b0da30c1bfc1e5","contributors":{"authors":[{"text":"Tornabene, Livio L.","contributorId":203691,"corporation":false,"usgs":false,"family":"Tornabene","given":"Livio","email":"","middleInitial":"L.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":732112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seelos, Frank P.","contributorId":203692,"corporation":false,"usgs":false,"family":"Seelos","given":"Frank","email":"","middleInitial":"P.","affiliations":[{"id":36691,"text":"JHU APL","active":true,"usgs":false}],"preferred":false,"id":732113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pommerol, Antoine","contributorId":203693,"corporation":false,"usgs":false,"family":"Pommerol","given":"Antoine","email":"","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":732114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, Nicolas","contributorId":203694,"corporation":false,"usgs":false,"family":"Thomas","given":"Nicolas","email":"","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":732115,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caudill, Christy M.","contributorId":203695,"corporation":false,"usgs":false,"family":"Caudill","given":"Christy","email":"","middleInitial":"M.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":732116,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Becerra, Patricio","contributorId":173341,"corporation":false,"usgs":false,"family":"Becerra","given":"Patricio","email":"","affiliations":[],"preferred":false,"id":732117,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bridges, John C.","contributorId":173222,"corporation":false,"usgs":false,"family":"Bridges","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":27194,"text":"University of Leicester","active":true,"usgs":false}],"preferred":false,"id":732118,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Byrne, Shane","contributorId":192609,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","email":"","affiliations":[],"preferred":false,"id":732119,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cardinale, Marco","contributorId":203696,"corporation":false,"usgs":false,"family":"Cardinale","given":"Marco","email":"","affiliations":[{"id":36692,"text":"Universita G. D'Annunzio","active":true,"usgs":false}],"preferred":false,"id":732120,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chojnacki, Matthew","contributorId":201621,"corporation":false,"usgs":false,"family":"Chojnacki","given":"Matthew","affiliations":[{"id":27205,"text":"U. Arizona","active":true,"usgs":false}],"preferred":false,"id":732121,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Conway, Susan J.","contributorId":203697,"corporation":false,"usgs":false,"family":"Conway","given":"Susan","email":"","middleInitial":"J.","affiliations":[{"id":36693,"text":"University of Nantes","active":true,"usgs":false}],"preferred":false,"id":732122,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cremonese, Gabriele","contributorId":203698,"corporation":false,"usgs":false,"family":"Cremonese","given":"Gabriele","email":"","affiliations":[{"id":36694,"text":"INAF Osservatorio Astronomicodi Padova","active":true,"usgs":false}],"preferred":false,"id":732123,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":732111,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"El-Maarry, M. R.","contributorId":203699,"corporation":false,"usgs":false,"family":"El-Maarry","given":"M.","email":"","middleInitial":"R.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":732124,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Fernando, Jennifer","contributorId":203700,"corporation":false,"usgs":false,"family":"Fernando","given":"Jennifer","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":732125,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hansen, Candice J.","contributorId":70235,"corporation":false,"usgs":false,"family":"Hansen","given":"Candice","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":732126,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Hansen, Kayle","contributorId":203701,"corporation":false,"usgs":false,"family":"Hansen","given":"Kayle","email":"","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":732127,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Harrison, Tanya N.","contributorId":203702,"corporation":false,"usgs":false,"family":"Harrison","given":"Tanya","email":"","middleInitial":"N.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":732128,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Henson, Rachel","contributorId":203703,"corporation":false,"usgs":false,"family":"Henson","given":"Rachel","email":"","affiliations":[{"id":27194,"text":"University of Leicester","active":true,"usgs":false}],"preferred":false,"id":732129,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Marinangeli, Lucia","contributorId":203704,"corporation":false,"usgs":false,"family":"Marinangeli","given":"Lucia","email":"","affiliations":[{"id":36692,"text":"Universita G. D'Annunzio","active":true,"usgs":false}],"preferred":false,"id":732130,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":732131,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Pajola, Maurizio","contributorId":203705,"corporation":false,"usgs":false,"family":"Pajola","given":"Maurizio","email":"","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":732132,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Sutton, Sarah S.","contributorId":203706,"corporation":false,"usgs":false,"family":"Sutton","given":"Sarah","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":732133,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Wray, James J.","contributorId":81736,"corporation":false,"usgs":false,"family":"Wray","given":"James","email":"","middleInitial":"J.","affiliations":[{"id":7032,"text":"School of Earth and Atmospheric Sciences, Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":732134,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}}
,{"id":70197213,"text":"70197213 - 2018 - Sediment erosion and delivery from Toutle River basin after the 1980 eruption of Mount St. Helens: A 30-year perspective","interactions":[],"lastModifiedDate":"2018-06-12T14:09:56","indexId":"70197213","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Sediment erosion and delivery from Toutle River basin after the 1980 eruption of Mount St. Helens: A 30-year perspective","docAbstract":"<p><span>Exceptional sediment yields persist in Toutle River valley more than 30&nbsp;years after the major 1980 eruption of Mount St. Helens. Differencing of decadal-scale digital elevation models shows the elevated load comes largely from persistent lateral channel erosion across the debris-avalanche deposit. Since the mid-1980s, rates of channel-bed-elevation change have diminished, and magnitudes of lateral erosion have outpaced those of channel incision. A digital elevation model of difference from 1999 to 2009 shows erosion across the debris-avalanche deposit is more spatially distributed compared to a model from 1987 to 1999, in which erosion was strongly focused along specific reaches of the channel.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological responses at Mount St. Helens: Revisited 35 years after the 1980 eruption","language":"English","publisher":"Springer","doi":"10.1007/978-1-4939-7451-1_2","usgsCitation":"Major, J.J., Mosbrucker, A.R., and Spicer, K.R., 2018, Sediment erosion and delivery from Toutle River basin after the 1980 eruption of Mount St. Helens: A 30-year perspective, chap. <i>of</i> Ecological responses at Mount St. Helens: Revisited 35 years after the 1980 eruption, p. 19-44, https://doi.org/10.1007/978-1-4939-7451-1_2.","productDescription":"26 p.","startPage":"19","endPage":"44","ipdsId":"IP-055009","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":354963,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mount St. Helens","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","scienceBaseUri":"5b46e5d4e4b060350a15d228","contributors":{"editors":[{"text":"Crisafulli, Charles","contributorId":89491,"corporation":false,"usgs":true,"family":"Crisafulli","given":"Charles","affiliations":[],"preferred":false,"id":737812,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Dale, V.","contributorId":205567,"corporation":false,"usgs":false,"family":"Dale","given":"V.","email":"","affiliations":[],"preferred":false,"id":737813,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Major, Jon J. 0000-0003-2449-4466 jjmajor@usgs.gov","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":439,"corporation":false,"usgs":true,"family":"Major","given":"Jon","email":"jjmajor@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":736245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324 amosbrucker@usgs.gov","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":4968,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam","email":"amosbrucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":736246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":736247,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196466,"text":"70196466 - 2018 - Groundwater connectivity of upland-embedded wetlands in the Prairie Pothole Region","interactions":[],"lastModifiedDate":"2018-04-10T10:41:52","indexId":"70196466","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater connectivity of upland-embedded wetlands in the Prairie Pothole Region","docAbstract":"<p><span>Groundwater connections from upland-embedded wetlands to downstream waterbodies remain poorly understood. In principle, water from upland-embedded wetlands situated high in a landscape should flow via groundwater to waterbodies situated lower in the landscape. However, the degree of groundwater connectivity varies across systems due to factors such as geologic setting, hydrologic conditions, and topography. We use numerical models to evaluate the conditions suitable for groundwater connectivity between upland-embedded wetlands and downstream waterbodies in the prairie pothole region of North Dakota (USA). Results show groundwater connectivity between upland-embedded wetlands and other waterbodies is restricted when these wetlands are surrounded by a mounding water table. However, connectivity exists among adjacent upland-embedded wetlands where water–table mounds do not form. In addition, the presence of sand layers greatly facilitates groundwater connectivity of upland-embedded wetlands. Anisotropy can facilitate connectivity via groundwater flow, but only if it becomes unrealistically large. These findings help consolidate previously divergent views on the significance of local and regional groundwater flow in the prairie pothole region.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s13157-017-0956-7","usgsCitation":"Neff, B., and Rosenberry, D.O., 2018, Groundwater connectivity of upland-embedded wetlands in the Prairie Pothole Region: Wetlands, v. 38, no. 1, p. 51-63, https://doi.org/10.1007/s13157-017-0956-7.","productDescription":"13 p.","startPage":"51","endPage":"63","ipdsId":"IP-080137","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":353281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","volume":"38","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-07","publicationStatus":"PW","scienceBaseUri":"5afee741e4b0da30c1bfc1e1","contributors":{"authors":[{"text":"Neff, Brian 0000-0003-3718-7350 bneff@usgs.gov","orcid":"https://orcid.org/0000-0003-3718-7350","contributorId":198885,"corporation":false,"usgs":true,"family":"Neff","given":"Brian","email":"bneff@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":733016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":733017,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70197460,"text":"70197460 - 2018 - Contaminants in tropical island streams and their biota","interactions":[],"lastModifiedDate":"2018-06-05T14:35:51","indexId":"70197460","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1561,"text":"Environmental Research","active":true,"publicationSubtype":{"id":10}},"title":"Contaminants in tropical island streams and their biota","docAbstract":"<p><span>Environmental contamination is problematic for tropical islands due to their typically dense human populations and competing land and water uses. The Caribbean island of Puerto Rico (USA) has a long history of anthropogenic chemical use, and its human population density is among the highest globally, providing a model environment to study contaminant impacts on tropical island stream ecosystems. Polycyclic Aromatic Hydrocarbons, historic-use chlorinated pesticides, current-use pesticides, Polychlorinated Biphenyls (PCBs), and metals (mercury, cadmium, copper, lead, nickel, zinc, and selenium) were&nbsp;quantified in the habitat and biota of Puerto Rico streams and assessed in relation to land-use patterns and toxicological thresholds. Water, sediment, and native fish and shrimp species were sampled in 13 rivers spanning broad watershed land-use characteristics during 2009–2010. Contrary to expectations, freshwater stream ecosystems in Puerto Rico were not severely polluted, likely due to frequent flushing flows and reduced deposition associated with recurring flood events. Notable exceptions of contamination were nickel in sediment within three agricultural watersheds (range 123–336</span><span>&nbsp;</span><span><span>ppm dry weight) and organic contaminants (PCBs, organochlorine pesticides) and mercury in urban landscapes. At an urban site, PCBs i</span><span>n several fish species (Mountain Mullet<span>&nbsp;</span></span></span><i>Agonostomus monticola</i><span><span>&nbsp;</span>[range 0.019–0.030</span><span>&nbsp;</span><span>ppm wet weight] and American Eel<span>&nbsp;</span></span><i>Anguilla rostrata</i><span><span>&nbsp;</span>[0.019–0.031</span><span>&nbsp;</span><span><span>ppm wet weight]) may pose human health hazards, with concentrations exceeding the U.S. Environmental Protection Agency (EPA) consumption limit for 1 meal/month. American Eel at the urban site also contained<span> dieldrin</span></span>&nbsp;(range &lt; detection-0.024</span><span>&nbsp;</span><span>ppm wet weight) that exceeded the EPA maximum allowable consumption limit. The Bigmouth Sleeper<span>&nbsp;</span></span><i>Gobiomorous dormitor</i><span>, an important piscivorus sport fish, accumulated low levels of organic contaminants in edible muscle tissue (due to its low lipid c<span>ontent) and may be most suitable for human consumption island-wide; only mercury at one site (an urban location) exceeded EPA's consumption limit of 3 meals/month for this species. These results comprise the first comprehensive island-wide contaminant assessment of Puerto Rico streams and biota and provide natural resource and public health agencies here and in similar tropical islands elsewhere with information needed to guide ecosystem and<span> fisheries</span>&nbsp;conservation and management and human health risk assessment.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envres.2017.11.053","usgsCitation":"Buttermore, E.N., Cope, W., Kwak, T.J., Cooney, P.B., Shea, D., and Lazaro, P.R., 2018, Contaminants in tropical island streams and their biota: Environmental Research, v. 161, p. 615-623, https://doi.org/10.1016/j.envres.2017.11.053.","productDescription":"9 p.","startPage":"615","endPage":"623","ipdsId":"IP-092384","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"161","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e5d4e4b060350a15d220","contributors":{"authors":[{"text":"Buttermore, Elissa N.","contributorId":84871,"corporation":false,"usgs":true,"family":"Buttermore","given":"Elissa","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":737243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":737244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":737242,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooney, Patrick B.","contributorId":141249,"corporation":false,"usgs":false,"family":"Cooney","given":"Patrick","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":737245,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shea, Damian","contributorId":145456,"corporation":false,"usgs":false,"family":"Shea","given":"Damian","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":737246,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lazaro, Peter R.","contributorId":205423,"corporation":false,"usgs":false,"family":"Lazaro","given":"Peter","email":"","middleInitial":"R.","affiliations":[{"id":37103,"text":"Department of Biological Sciences, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":737247,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197312,"text":"70197312 - 2018 - Estimating factors influencing the detection probability of semiaquatic freshwater snails using quadrat survey methods","interactions":[],"lastModifiedDate":"2018-05-29T15:17:38","indexId":"70197312","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Estimating factors influencing the detection probability of semiaquatic freshwater snails using quadrat survey methods","docAbstract":"<p><span>Developing effective monitoring methods for elusive, rare, or patchily distributed species requires extra considerations, such as imperfect detection. Although detection is frequently modeled, the opportunity to assess it empirically is rare, particularly for imperiled species. We used Pecos assiminea (</span><i class=\"EmphasisTypeItalic \">Assiminea pecos</i><span>), an endangered semiaquatic snail, as a case study to test detection and accuracy issues surrounding quadrat searches. Quadrats (9&nbsp;×&nbsp;20&nbsp;cm;<span>&nbsp;</span></span><i class=\"EmphasisTypeItalic \">n</i><span>&nbsp;=&nbsp;12) were placed in suitable Pecos assiminea habitat and randomly assigned a treatment, defined as the number of empty snail shells (0, 3, 6, or 9). Ten observers rotated through each quadrat, conducting 5-min visual searches for shells. The probability of detecting a shell when present was 67.4&nbsp;±&nbsp;3.0%, but it decreased with the increasing litter depth and fewer number of shells present. The mean (±&nbsp;SE) observer accuracy was 25.5&nbsp;±&nbsp;4.3%. Accuracy was positively correlated to the number of shells in the quadrat and negatively correlated to the number of times a quadrat was searched. The results indicate quadrat surveys likely underrepresent true abundance, but accurately determine the presence or absence. Understanding detection and accuracy of elusive, rare, or imperiled species improves density estimates and aids in monitoring and conservation efforts.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10750-017-3415-9","usgsCitation":"Roesler, E.L., and Grabowski, T.B., 2018, Estimating factors influencing the detection probability of semiaquatic freshwater snails using quadrat survey methods: Hydrobiologia, v. 808, no. 1, p. 153-161, https://doi.org/10.1007/s10750-017-3415-9.","productDescription":"9 p.","startPage":"153","endPage":"161","ipdsId":"IP-075954","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"808","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-20","publicationStatus":"PW","scienceBaseUri":"5b155db9e4b092d9651e1b7f","contributors":{"authors":[{"text":"Roesler, Elizabeth L.","contributorId":204877,"corporation":false,"usgs":false,"family":"Roesler","given":"Elizabeth","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":736676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":736618,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70195384,"text":"70195384 - 2018 - A molecular investigation of soil organic carbon composition across a subalpine catchment","interactions":[],"lastModifiedDate":"2018-02-13T12:32:30","indexId":"70195384","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5626,"text":"Soil Systems","active":true,"publicationSubtype":{"id":10}},"title":"A molecular investigation of soil organic carbon composition across a subalpine catchment","docAbstract":"<p><span>The dynamics of soil organic carbon (SOC) storage and turnover are a critical component of the global carbon cycle. Mechanistic models seeking to represent these complex dynamics require detailed SOC compositions, which are currently difficult to characterize quantitatively. Here, we address this challenge by using a novel approach that combines Fourier transform infrared spectroscopy (FT-IR) and bulk carbon X-ray absorption spectroscopy (XAS) to determine the abundance of SOC functional groups, using elemental analysis (EA) to constrain the total amount of SOC. We used this SOC functional group abundance (SOC-fga) method to compare variability in SOC compositions as a function of depth across a subalpine watershed (East River, Colorado, USA) and found a large degree of variability in SOC functional group abundances between sites at different elevations. Soils at a lower elevation are predominantly composed of polysaccharides, while soils at a higher elevation have more substantial portions of carbonyl, phenolic, or aromatic carbon. We discuss the potential drivers of differences in SOC composition between these sites, including vegetation inputs, internal processing and losses, and elevation-driven environmental factors. Although numerical models would facilitate the understanding and evaluation of the observed SOC distributions, quantitative and meaningful measurements of SOC molecular compositions are required to guide such models. Comparison among commonly used characterization techniques on shared reference materials is a critical next step for advancing our understanding of the complex processes controlling SOC compositions.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/soils2010006","usgsCitation":"Hsu, H., Lawrence, C.R., Winnick, M.J., Bargar, J.R., and Maher, K., 2018, A molecular investigation of soil organic carbon composition across a subalpine catchment: Soil Systems, v. 2, no. 1, p. 1-23, https://doi.org/10.3390/soils2010006.","productDescription":"Article 6; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-088725","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/soils2010006","text":"Publisher Index Page"},{"id":351525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-01","publicationStatus":"PW","scienceBaseUri":"5afee743e4b0da30c1bfc207","contributors":{"authors":[{"text":"Hsu, Hsiao-Tieh","contributorId":202391,"corporation":false,"usgs":false,"family":"Hsu","given":"Hsiao-Tieh","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":728306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Corey R. 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202390,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":728305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winnick, Matthew J.","contributorId":202392,"corporation":false,"usgs":false,"family":"Winnick","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":728307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bargar, John R.","contributorId":14970,"corporation":false,"usgs":true,"family":"Bargar","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":728308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maher, Katharine","contributorId":46004,"corporation":false,"usgs":true,"family":"Maher","given":"Katharine","email":"","affiliations":[],"preferred":false,"id":728309,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196739,"text":"70196739 - 2018 - Examining fluvial fish range loss with SDMs","interactions":[],"lastModifiedDate":"2018-04-27T13:24:42","indexId":"70196739","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Examining fluvial fish range loss with SDMs","docAbstract":"<p><span>Fluvial fishes face increased imperilment from anthropogenic activities, but the specific factors contributing most to range declines are often poorly understood. For example, the range of the fluvial‐specialist shoal bass (</span><i>Micropterus cataractae</i><span>) continues to decrease, yet how perceived threats have contributed to range loss is largely unknown. We used species distribution models to determine which factors contributed most to shoal bass range loss. We estimated a potential distribution based on natural abiotic factors and a series of currently occupied distributions that incorporated variables characterizing land cover, non‐native species, and river fragmentation intensity (no fragmentation, dams only, and dams and large impoundments). We allowed interspecific relationships between non‐native congeners and shoal bass to vary across fragmentation intensities. Results from the potential distribution model estimated shoal bass presence throughout much of their native basin, whereas models of currently occupied distribution showed that range loss increased as fragmentation intensified. Response curves from models of currently occupied distribution indicated a potential interaction between fragmentation intensity and the relationship between shoal bass and non‐native congeners, wherein non‐natives may be favored at the highest fragmentation intensity. Response curves also suggested that &gt;100 km of interconnected, free‐flowing stream fragments were necessary to support shoal bass presence. Model evaluation, including an independent validation, suggested that models had favorable predictive and discriminative abilities. Similar approaches that use readily available, diverse, geospatial data sets may deliver insights into the biology and conservation needs of other fluvial species facing similar threats.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/cobi.13024","usgsCitation":"Taylor, A.T., Papes, M., and Long, J.M., 2018, Examining fluvial fish range loss with SDMs: Conservation Biology, v. 32, no. 1, p. 171-182, https://doi.org/10.1111/cobi.13024.","productDescription":"12 p.","startPage":"171","endPage":"182","ipdsId":"IP-079935","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":353774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-29","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1d5","contributors":{"authors":[{"text":"Taylor, Andrew T.","contributorId":177197,"corporation":false,"usgs":false,"family":"Taylor","given":"Andrew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":734169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Papes, Monica","contributorId":204496,"corporation":false,"usgs":false,"family":"Papes","given":"Monica","email":"","affiliations":[],"preferred":false,"id":734170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734168,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70197788,"text":"70197788 - 2018 - Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States","interactions":[],"lastModifiedDate":"2018-06-20T10:54:13","indexId":"70197788","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States","docAbstract":"<p><span>Probabilistic seismic hazard analysis (PSHA) characterizes ground-motion hazard from earthquakes. Typically, the time horizon of a PSHA forecast is long, but in response to induced seismicity related to hydrocarbon development, the USGS developed one-year PSHA models. In this paper, we present a display of the variability in USGS hazard curves due to epistemic uncertainty in its informed submodel using a simple bootstrapping approach. We find that variability is highest in low-seismicity areas. On the other hand, areas of high seismic hazard, such as the New Madrid seismic zone or Oklahoma, exhibit relatively lower variability simply because of more available data and a better understanding of the seismicity. Comparing areas of high hazard, New Madrid, which has a history of large naturally occurring earthquakes, has lower forecast variability than Oklahoma, where the hazard is driven mainly by suspected induced earthquakes since 2009. Overall, the mean hazard obtained from bootstrapping is close to the published model, and variability increased in the 2017 one-year model relative to the 2016 model. Comparing the relative variations caused by individual logic-tree branches, we find that the highest hazard variation (as measured by the 95% confidence interval of bootstrapping samples) in the final model is associated with different ground-motion models and maximum magnitudes used in the logic tree, while the variability due to the smoothing distance is minimal. It should be pointed out that this study is not looking at the uncertainty in the hazard in general, but only as it is represented in the USGS one-year models.</span><span></span></p>","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/tle37020141a1.1","usgsCitation":"Mousavi, S.M., Beroza, G.C., and Hoover, S.M., 2018, Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States: The Leading Edge, v. 37, no. 2, p. 141a1-141a9, https://doi.org/10.1190/tle37020141a1.1.","productDescription":"9 p.","startPage":"141a1","endPage":"141a9","ipdsId":"IP-093220","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":355202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115,\n              25\n            ],\n            [\n              -65,\n              25\n            ],\n            [\n              -65,\n              50\n            ],\n            [\n              -115,\n              50\n            ],\n            [\n              -115,\n              25\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"37","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e5d3e4b060350a15d21c","contributors":{"authors":[{"text":"Mousavi, S. Mostafa","contributorId":205790,"corporation":false,"usgs":false,"family":"Mousavi","given":"S.","email":"","middleInitial":"Mostafa","affiliations":[{"id":37167,"text":"Department of Geophysics, Stanford University, Stanford, CA","active":true,"usgs":false}],"preferred":false,"id":738494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":738495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoover, Susan M. 0000-0002-8682-6668 shoover@usgs.gov","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":5715,"corporation":false,"usgs":true,"family":"Hoover","given":"Susan","email":"shoover@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70195346,"text":"70195346 - 2018 - Biomarker responses of Peromyscus leucopus exposed to lead and cadmium in the Southeast Missouri Lead Mining District","interactions":[],"lastModifiedDate":"2018-02-12T09:26:13","indexId":"70195346","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Biomarker responses of <i>Peromyscus leucopus</i> exposed to lead and cadmium in the Southeast Missouri Lead Mining District","title":"Biomarker responses of Peromyscus leucopus exposed to lead and cadmium in the Southeast Missouri Lead Mining District","docAbstract":"<p><span>Biomarker responses and histopathological lesions have been documented in laboratory mammals exposed to elevated concentrations of lead and cadmium. The exposure of white-footed mice (</span><i class=\"EmphasisTypeItalic \">Peromyscus leucopus</i><span>) to these metals and the potential associated toxic effects were examined at three contaminated sites in the Southeast Missouri Lead Mining District and at a reference site in MO, USA. Mice from the contaminated sites showed evidence of oxidative stress and reduced activity of red blood cell δ-aminolevulinic acid dehydratase (ALAD). Histological examinations of the liver and kidney, cytologic examination of blood smears, and biomarkers of lipid peroxidation and DNA damage failed to show indications of toxic effects from lead. The biomagnification factor of cadmium (hepatic concentration/soil concentration) at a site with a strongly acid soil was 44 times the average of the biomagnification factors at two sites with slightly alkaline soils. The elevated concentrations of cadmium in the mice did not cause observable toxicity, but were associated with about a 50% decrease in expected tissue lead concentrations and greater ALAD activity compared to the activity at the reference site. Lead was associated with a decrease in concentrations of hepatic glutathione and thiols, whereas cadmium was associated with an increase. In addition, to support risk assessment efforts, we developed linear regression models relating both tissue lead dosages (based on a previously published a laboratory study) and tissue lead concentrations in<span>&nbsp;</span></span><i class=\"EmphasisTypeItalic \">Peromyscus</i><span><span>&nbsp;</span>to soil lead concentrations.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10661-017-6442-0","usgsCitation":"Beyer, W.N., Casteel, S.W., Friedrichs, K.R., Gramlich, E., Houseright, R.A., Nichols, J.W., Karouna-Renier, N., Kim, D.Y., Rangen, K., Rattner, B.A., and Schultz, S.L., 2018, Biomarker responses of Peromyscus leucopus exposed to lead and cadmium in the Southeast Missouri Lead Mining District: Environmental Monitoring and Assessment, v. 190, p. 1-16, https://doi.org/10.1007/s10661-017-6442-0.","productDescription":"Article 104; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-087013","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":351428,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Southeast Missouri Lead Mining District","volume":"190","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-29","publicationStatus":"PW","scienceBaseUri":"5a7ec172e4b00f54eb25a75b","contributors":{"authors":[{"text":"Beyer, W. Nelson 0000-0002-8911-9141 nbeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8911-9141","contributorId":3301,"corporation":false,"usgs":true,"family":"Beyer","given":"W.","email":"nbeyer@usgs.gov","middleInitial":"Nelson","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":727966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casteel, Stan W.","contributorId":202227,"corporation":false,"usgs":false,"family":"Casteel","given":"Stan","email":"","middleInitial":"W.","affiliations":[{"id":36374,"text":"College of Veterinary Medicine, University of Missouri, Missouri, 65211, USA","active":true,"usgs":false}],"preferred":false,"id":727967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedrichs, Kristen R.","contributorId":202228,"corporation":false,"usgs":false,"family":"Friedrichs","given":"Kristen","email":"","middleInitial":"R.","affiliations":[{"id":36375,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin, 2015 Linden Dr., Madison, WI 53706-1100, USA","active":true,"usgs":false}],"preferred":false,"id":727968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gramlich, Eric","contributorId":202229,"corporation":false,"usgs":false,"family":"Gramlich","given":"Eric","email":"","affiliations":[{"id":36376,"text":"Missouri Department of Natural Resources,  P.O. Box 176 Jefferson City, MO 65102-0176, USA","active":true,"usgs":false}],"preferred":false,"id":727969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Houseright, Ruth A.","contributorId":202230,"corporation":false,"usgs":false,"family":"Houseright","given":"Ruth","email":"","middleInitial":"A.","affiliations":[{"id":36375,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin, 2015 Linden Dr., Madison, WI 53706-1100, USA","active":true,"usgs":false}],"preferred":false,"id":727970,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nichols, John W.","contributorId":175334,"corporation":false,"usgs":false,"family":"Nichols","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":727971,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":727972,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kim, Dae Young","contributorId":202231,"corporation":false,"usgs":false,"family":"Kim","given":"Dae","email":"","middleInitial":"Young","affiliations":[{"id":36374,"text":"College of Veterinary Medicine, University of Missouri, Missouri, 65211, USA","active":true,"usgs":false}],"preferred":false,"id":727973,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rangen, Kathleen","contributorId":202232,"corporation":false,"usgs":false,"family":"Rangen","given":"Kathleen","email":"","affiliations":[{"id":36376,"text":"Missouri Department of Natural Resources,  P.O. Box 176 Jefferson City, MO 65102-0176, USA","active":true,"usgs":false}],"preferred":false,"id":727974,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":727975,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schultz, Sandra L. 0000-0003-3394-2857 sschultz@usgs.gov","orcid":"https://orcid.org/0000-0003-3394-2857","contributorId":5966,"corporation":false,"usgs":true,"family":"Schultz","given":"Sandra","email":"sschultz@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":727976,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70195430,"text":"70195430 - 2018 - Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts","interactions":[],"lastModifiedDate":"2018-02-14T13:31:00","indexId":"70195430","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts","docAbstract":"<p><span>Many different factors influence animal activity. Often, the value of an environmental variable may influence significantly the upper or lower tails of the activity distribution. For describing relationships with heterogeneous boundaries, quantile regressions predict a quantile of the conditional distribution of the dependent variable. A quantile count model extends linear quantile regression methods to discrete response variables, and is useful if activity is quantified by trapping, where there may be many tied (equal) values in the activity distribution, over a small range of discrete values. Additionally, different environmental variables in combination may have synergistic or antagonistic effects on activity, so examining their effects together, in a modeling framework, is a useful approach. Thus, model selection on quantile counts can be used to determine the relative importance of different variables in determining activity, across the entire distribution of capture results. We conducted model selection on quantile count models to describe the factors affecting activity (numbers of captures) of cane toads (</span><i>Rhinella marina</i><span>) in response to several environmental variables (humidity, temperature, rainfall, wind speed, and moon luminosity) over eleven months of trapping. Environmental effects on activity are understudied in this pest animal. In the dry season, model selection on quantile count models suggested that rainfall positively affected activity, especially near the lower tails of the activity distribution. In the wet season, wind speed limited activity near the maximum of the distribution, while minimum activity increased with minimum temperature. This statistical methodology allowed us to explore, in depth, how environmental factors influenced activity across the entire distribution, and is applicable to any survey or trapping regime, in which environmental variables affect activity.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2067","usgsCitation":"Muller, B.J., Cade, B.S., and Schwarzkoph, L., 2018, Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts: Ecosphere, v. 9, no. 1, p. 1-14, https://doi.org/10.1002/ecs2.2067.","productDescription":"Article e02067; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-092621","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2067","text":"Publisher Index Page"},{"id":351611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-05","publicationStatus":"PW","scienceBaseUri":"5afee743e4b0da30c1bfc203","contributors":{"authors":[{"text":"Muller, Benjamin J.","contributorId":202492,"corporation":false,"usgs":false,"family":"Muller","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[{"id":36457,"text":"Centre for Tropical Biodiversity and Climate Change, James Cook University, Townsville, Quensland, Australia","active":true,"usgs":false}],"preferred":false,"id":728565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cade, Brian S. 0000-0001-9623-9849 cadeb@usgs.gov","orcid":"https://orcid.org/0000-0001-9623-9849","contributorId":1278,"corporation":false,"usgs":true,"family":"Cade","given":"Brian","email":"cadeb@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":728564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwarzkoph, Lin","contributorId":202493,"corporation":false,"usgs":false,"family":"Schwarzkoph","given":"Lin","email":"","affiliations":[{"id":36458,"text":"College of Science and Engineering, James Cook University, Townsville, Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":728566,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70195338,"text":"70195338 - 2018 - Spatial patterns in occupancy and reproduction of Golden Eagles during drought: Prospects for conservation in changing environments","interactions":[],"lastModifiedDate":"2018-02-08T14:22:33","indexId":"70195338","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Spatial patterns in occupancy and reproduction of Golden Eagles during drought: Prospects for conservation in changing environments","docAbstract":"<p><span>We used a broad-scale sampling design to investigate spatial patterns in occupancy and breeding success of territorial pairs of Golden Eagles (</span><i>Aquila chrysaetos</i><span>) in the Diablo Range, California, USA, during a period of exceptional drought (2014–2016). We surveyed 138 randomly selected sample sites over 4 occasions each year and identified 199 pairs of eagles, 100 of which were detected in focal sample sites. We then used dynamic multistate modeling to identify relationships between site occupancy and reproduction of Golden Eagles relative to spatial variability in landscape composition and drought conditions. We observed little variability among years in site occupancy (3-yr mean = 0.74), but the estimated annual probability of successful reproduction was relatively low during the study period and declined from 0.39 (± 0.08 SE) to 0.18 (± 0.07 SE). Probabilities of site occupancy and reproduction were substantially greater at sample sites that were occupied by successful breeders in the previous year, indicating the presence of sites that were consistently used by successfully reproducing eagles. We found strong evidence for nonrandom spatial distribution in both occupancy and reproduction: Sites with the greatest potential for occupancy were characterized by rugged terrain conditions with intermediate amounts of grassland interspersed with patches of oak woodland and coniferous forest, whereas successful reproduction was most strongly associated with the amount of precipitation that a site received during the nesting period. Our findings highlight the contribution of consistently occupied and productive breeding sites to overall productivity of the local breeding population, and show that both occupancy and reproduction at these sites were maintained even during a period of exceptional drought. Our approach to quantifying and mapping site quality should be especially useful for the spatial prioritization of compensation measures intended to help offset the impacts of increasing human land use and development on Golden Eagles and their habitats.</span></p>","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-96.1","usgsCitation":"Wiens, D., Kolar, P., Hunt, W.G., Hunt, T., Fuller, M.R., and Bell, D., 2018, Spatial patterns in occupancy and reproduction of Golden Eagles during drought: Prospects for conservation in changing environments: The Condor, v. 120, no. 1, p. 106-124, https://doi.org/10.1650/CONDOR-17-96.1.","productDescription":"19 p.","startPage":"106","endPage":"124","ipdsId":"IP-087249","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-17-96.1","text":"Publisher Index Page"},{"id":351376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.33,\n              37\n            ],\n            [\n              -121,\n              37\n            ],\n            [\n              -121,\n              38.05674222065296\n            ],\n            [\n              -122.33,\n              38.05674222065296\n            ],\n            [\n              -122.33,\n              37\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"120","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7d6ffce4b00f54eb244199","contributors":{"authors":[{"text":"Wiens, David 0000-0002-2020-038X jwiens@usgs.gov","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":167538,"corporation":false,"usgs":true,"family":"Wiens","given":"David","email":"jwiens@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolar, Patrick 0000-0002-0076-7565 pkolar@usgs.gov","orcid":"https://orcid.org/0000-0002-0076-7565","contributorId":189512,"corporation":false,"usgs":true,"family":"Kolar","given":"Patrick","email":"pkolar@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, W. Grainger","contributorId":139544,"corporation":false,"usgs":false,"family":"Hunt","given":"W.","email":"","middleInitial":"Grainger","affiliations":[{"id":12795,"text":"The Peregrine Fund, Inc.","active":true,"usgs":false}],"preferred":false,"id":727885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Teresa","contributorId":139545,"corporation":false,"usgs":false,"family":"Hunt","given":"Teresa","affiliations":[{"id":12795,"text":"The Peregrine Fund, Inc.","active":true,"usgs":false}],"preferred":false,"id":727886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Mark R. 0000-0001-7459-1729 mark_fuller@usgs.gov","orcid":"https://orcid.org/0000-0001-7459-1729","contributorId":2296,"corporation":false,"usgs":true,"family":"Fuller","given":"Mark","email":"mark_fuller@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727888,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bell, Douglas A.","contributorId":44427,"corporation":false,"usgs":true,"family":"Bell","given":"Douglas A.","affiliations":[],"preferred":false,"id":727889,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70195193,"text":"70195193 - 2018 - The suitability of using dissolved gases to determine groundwater discharge to high gradient streams","interactions":[],"lastModifiedDate":"2018-02-07T13:08:28","indexId":"70195193","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"The suitability of using dissolved gases to determine groundwater discharge to high gradient streams","docAbstract":"<p><span>Determining groundwater discharge to streams using dissolved gases is known to be useful over a wide range of streamflow rates but the suitability of dissolved gas methods to determine discharge rates in high gradient mountain streams has not been sufficiently tested, even though headwater streams are critical as ecological habitats and water resources. The aim of this study is to test the suitability of using dissolved gases to determine groundwater discharge rates to high gradient streams by field experiments in a well-characterized, high gradient mountain stream and a literature review. At a reach scale (550 m) we combined stream and groundwater radon activity measurements with an in-stream SF</span><sub>6</sub><span><span>&nbsp;</span>tracer test. By means of numerical modeling we determined gas exchange velocities and derived very low groundwater discharge rates (∼15% of streamflow). These groundwater discharge rates are below the uncertainty range of physical streamflow measurements and consistent with temperature, specific conductance and streamflow measured at multiple locations along the reach. At a watershed-scale (4 km), we measured CFC-12 and δ</span><sup>18</sup><span>O concentrations and determined gas exchange velocities and groundwater discharge rates with the same numerical model. The groundwater discharge rates along the 4 km stream reach were highly variable, but were consistent with the values derived in the detailed study reach. Additionally, we synthesized literature values of gas exchange velocities for different stream gradients which show an empirical relationship that will be valuable in planning future dissolved gas studies on streams with various gradients. In sum, we show that multiple dissolved gas tracers can be used to determine groundwater discharge to high gradient mountain streams from reach to watershed scales.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2017.12.022","usgsCitation":"Gleeson, T., Manning, A.H., Popp, A., Zane, M., and Clark, J.F., 2018, The suitability of using dissolved gases to determine groundwater discharge to high gradient streams: Journal of Hydrology, v. 557, p. 561-572, https://doi.org/10.1016/j.jhydrol.2017.12.022.","productDescription":"12 p.","startPage":"561","endPage":"572","ipdsId":"IP-071701","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":469056,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/82x8s2wg","text":"External Repository"},{"id":351246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.3167,\n              39.4\n            ],\n            [\n              -120.2167,\n              39.4\n            ],\n            [\n              -120.2167,\n              39.4667\n            ],\n            [\n              -120.3167,\n              39.4667\n            ],\n            [\n              -120.3167,\n              39.4\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"557","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e73e4b00f54eb2292dc","contributors":{"authors":[{"text":"Gleeson, Tom","contributorId":42694,"corporation":false,"usgs":false,"family":"Gleeson","given":"Tom","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":727373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":727372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Popp, Andrea","contributorId":202011,"corporation":false,"usgs":false,"family":"Popp","given":"Andrea","email":"","affiliations":[{"id":35133,"text":"University of Freiburg, Freiburg, Germany","active":true,"usgs":false}],"preferred":false,"id":727374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zane, Mathew","contributorId":202012,"corporation":false,"usgs":false,"family":"Zane","given":"Mathew","email":"","affiliations":[{"id":36321,"text":"Department of Geological Sciences, University of California, Santa Barbara, California","active":true,"usgs":false}],"preferred":false,"id":727375,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Jordan F.","contributorId":202013,"corporation":false,"usgs":false,"family":"Clark","given":"Jordan","email":"","middleInitial":"F.","affiliations":[{"id":36321,"text":"Department of Geological Sciences, University of California, Santa Barbara, California","active":true,"usgs":false}],"preferred":false,"id":727376,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196116,"text":"70196116 - 2018 - Radium mobility and the age of groundwater in public-drinking-water supplies from the Cambrian-Ordovician aquifer system, north-central USA","interactions":[],"lastModifiedDate":"2018-03-21T10:03:13","indexId":"70196116","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Radium mobility and the age of groundwater in public-drinking-water supplies from the Cambrian-Ordovician aquifer system, north-central USA","docAbstract":"<p><span>High radium (Ra) concentrations in potable portions of the Cambrian-Ordovician (C-O) aquifer system were investigated using water-quality data and environmental tracers (</span><sup>3</sup><span>H,<span>&nbsp;</span></span><sup>3</sup><span>He</span><sub>trit</sub><span>, SF</span><sub>6</sub><span>,<span>&nbsp;</span></span><sup>14</sup><span>C and<span>&nbsp;</span></span><sup>4</sup><span>He</span><sub>rad</sub><span>) of groundwater age from 80 public-supply wells (PSWs). Groundwater ages were estimated by calibration of tracers to lumped parameter models and ranged from modern (&lt;50&nbsp;yr) in upgradient, regionally unconfined areas to ancient (&gt;1 Myr) in the most downgradient, confined portions of the potable system. More than 80 and 40 percent of mean groundwater ages were older than 1000 and 50,000&nbsp;yr, respectively. Anoxic, Fe-reducing conditions and increased mineralization develop with time in the aquifer system and mobilize Ra into solution resulting in the frequent occurrence of combined Ra (Ra</span><sub>c</sub><span>&nbsp;=&nbsp;</span><sup>226</sup><span>Ra +<span>&nbsp;</span></span><sup>228</sup><span>Ra) at concentrations exceeding the USEPA MCL of 185 mBq/L (5&nbsp;pCi/L). The distribution of the three Ra isotopes comprising total Ra (Ra</span><sub>t</sub><span>&nbsp;=&nbsp;</span><sup>224</sup><span>Ra +<span>&nbsp;</span></span><sup>226</sup><span>Ra +<span>&nbsp;</span></span><sup>228</sup><span>Ra) differed across the aquifer system. The concentrations of<span>&nbsp;</span></span><sup>224</sup><span>Ra and<span>&nbsp;</span></span><sup>228</sup><span>Ra were strongly correlated and comprised a larger proportion of the Ra</span><sub>t</sub><span><span>&nbsp;</span>concentration in samples from the regionally unconfined area, where arkosic sandstones provide an enhanced source for progeny from the<span>&nbsp;</span></span><sup>232</sup><span>Th&nbsp;decay series.<span>&nbsp;</span></span><sup>226</sup><span>Ra comprised a larger proportion of the Ra</span><sub>t</sub><span>concentration in samples from downgradient confined regions. Concentrations of Ra</span><sub>t</sub><span><span>&nbsp;</span>were significantly greater in samples from the regionally confined area of the aquifer system because of the increase in<span>&nbsp;</span></span><sup>226</sup><span>Ra concentrations there as compared to the regionally unconfined area.<span>&nbsp;</span></span><sup>226</sup><span>Ra distribution coefficients decreased substantially with anoxic conditions and increasing ionic strength of groundwater (mineralization), indicating that Ra is mobilized to solution from solid phases of the aquifer as adsorption capacity is diminished. The amount of<span>&nbsp;</span></span><sup>226</sup><span>Ra released from solid phases by alpha-recoil mechanisms and retained in solution increases relative to the amount of Ra sequestered by adsorption processes or co-precipitation with barite as adsorption capacity and the concentration of Ba decreases. Although<span>&nbsp;</span></span><sup>226</sup><span>Ra occurred at concentrations greater than<span>&nbsp;</span></span><sup>224</sup><span>Ra or<span>&nbsp;</span></span><sup>228</sup><span>Ra, the ingestion exposure risk was greater for<span>&nbsp;</span></span><sup>228</sup><span>Ra owing to its greater toxicity. In addition,<span>&nbsp;</span></span><sup>224</sup><span>Ra added substantial alpha-particle radioactivity to potable samples from the C-O aquifer system. Thus, monitoring for Ra isotopes and gross-alpha-activity (GAA) is important in upgradient, regionally unconfined areas as downgradient, and GAA measurements made within 72&nbsp;h of sample collection would best capture alpha-particle radiation from the short-lived<span>&nbsp;</span></span><sup>224</sup><span>Ra.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2017.11.002","usgsCitation":"Stackelberg, P.E., Szabo, Z., and Jurgens, B., 2018, Radium mobility and the age of groundwater in public-drinking-water supplies from the Cambrian-Ordovician aquifer system, north-central USA: Applied Geochemistry, v. 89, p. 34-48, https://doi.org/10.1016/j.apgeochem.2017.11.002.","productDescription":"15 p.","startPage":"34","endPage":"48","ipdsId":"IP-084578","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":469075,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2017.11.002","text":"Publisher Index Page"},{"id":438031,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BR8QP0","text":"USGS data release","linkHelpText":"Data for Radium Mobility and the Age of Groundwater in Public-drinking-water Supplies from the Cambrian-Ordovician Aquifer System, North-Central USA"},{"id":352683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.82275390625,\n              38.54816542304656\n            ],\n            [\n              -84.462890625,\n              38.54816542304656\n            ],\n            [\n              -84.462890625,\n              46.66451741754235\n            ],\n            [\n              -95.82275390625,\n              46.66451741754235\n            ],\n            [\n              -95.82275390625,\n              38.54816542304656\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"89","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee742e4b0da30c1bfc1ef","contributors":{"authors":[{"text":"Stackelberg, Paul E. 0000-0002-1818-355X pestack@usgs.gov","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":1069,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","email":"pestack@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":2240,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":731427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":1503,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant C.","email":"bjurgens@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":731428,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194989,"text":"70194989 - 2018 - Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model","interactions":[],"lastModifiedDate":"2018-02-02T10:29:37","indexId":"70194989","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model","docAbstract":"<p><span>Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO</span><sub>2</sub><span>concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO</span><sub>2</sub><span>, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO</span><sub>2</sub><span><span>&nbsp;</span>concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO</span><sub>2</sub><span><span>&nbsp;</span>concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of  ∼  70 % relative to the baseline scenario, due to elevated CO</span><sub>2</sub><span><span>&nbsp;</span>concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha</span><sup>−1</sup><span><span>&nbsp;</span>in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-689-2018","usgsCitation":"Lee, S., Yeo, I., Sadeghi, A.M., McCarty, G.W., Hively, W., Lang, M.W., and Sharifi, A., 2018, Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model: Hydrology and Earth System Sciences, v. 22, p. 689-708, https://doi.org/10.5194/hess-22-689-2018.","productDescription":"10 p.","startPage":"689","endPage":"708","ipdsId":"IP-090233","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-689-2018","text":"Publisher Index Page"},{"id":350956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Greensboro Watershed, Tuckahoe Creek Watershed","volume":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-25","publicationStatus":"PW","scienceBaseUri":"5a7586d6e4b00f54eb1d81d4","contributors":{"authors":[{"text":"Lee, Sangchul","contributorId":201237,"corporation":false,"usgs":false,"family":"Lee","given":"Sangchul","email":"","affiliations":[],"preferred":false,"id":726400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeo, In-Young","contributorId":131145,"corporation":false,"usgs":false,"family":"Yeo","given":"In-Young","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":726402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sadeghi, Ali M.","contributorId":131147,"corporation":false,"usgs":false,"family":"Sadeghi","given":"Ali","email":"","middleInitial":"M.","affiliations":[{"id":7262,"text":"USDA-ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":726401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":726403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hively, Wells whively@usgs.gov","contributorId":201563,"corporation":false,"usgs":true,"family":"Hively","given":"Wells","email":"whively@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":726399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":726404,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sharifi, Amir","contributorId":201564,"corporation":false,"usgs":false,"family":"Sharifi","given":"Amir","email":"","affiliations":[{"id":18168,"text":"USDA ARS","active":true,"usgs":false}],"preferred":false,"id":726405,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194987,"text":"70194987 - 2018 - Determinants of Pseudogymnoascus destructans within bat hibernacula: Implications for surveillance and management of white-nose syndrome","interactions":[],"lastModifiedDate":"2023-06-30T14:48:58.619547","indexId":"70194987","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Determinants of <i>Pseudogymnoascus destructans</i> within bat hibernacula: Implications for surveillance and management of white-nose syndrome","title":"Determinants of Pseudogymnoascus destructans within bat hibernacula: Implications for surveillance and management of white-nose syndrome","docAbstract":"<ol id=\"jpe13070-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>Fungal diseases are an emerging global problem affecting human health, food security and biodiversity. Ability of many fungal pathogens to persist within environmental reservoirs can increase extinction risks for host species and presents challenges for disease control. Understanding factors that regulate pathogen spread and persistence in these reservoirs is critical for effective disease management.</li><li>White-nose syndrome (WNS) is a disease of hibernating bats caused by<span>&nbsp;</span><i>Pseudogymnoascus destructans</i><span>&nbsp;</span>(<i>Pd</i>), a fungus that establishes persistent environmental reservoirs within bat hibernacula, which contribute to seasonal disease transmission dynamics in bats. However, host and environmental factors influencing distribution of<span>&nbsp;</span><i>Pd</i>within these reservoirs are unknown.</li><li>We used model selection on longitudinally collected field data to test multiple hypotheses describing presence–absence and abundance of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>in environmental substrates and on bats within hibernacula at different stages of WNS.</li><li>First detection of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>in the environment lagged up to 1&nbsp;year after first detection on bats within that hibernaculum. Once detected, the probability of detecting<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>within environmental samples from a hibernaculum increased over time and was higher in sediment compared to wall surfaces. Temperature had marginal effects on the distribution of<span>&nbsp;</span><i>Pd</i>. For bats, prevalence and abundance of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>were highest on<span>&nbsp;</span><i>Myotis lucifugus</i><span>&nbsp;</span>and on bats with visible signs of WNS.</li><li><i>Synthesis and applications</i>. Our results indicate that distribution of<span>&nbsp;</span><i>Pseudogymnoascus destructans</i><span>&nbsp;</span>(<i>Pd</i>) within a hibernaculum is driven primarily by bats with delayed establishment of environmental reservoirs. Thus, collection of samples from<span>&nbsp;</span><i>Myotis lucifugus</i>, or from sediment if bats cannot be sampled, should be prioritized to improve detection probabilities for<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>surveillance. Long-term persistence of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>in sediment suggests that disease management for white-nose syndrome should address risks of sustained transmission from environmental reservoirs.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13070","usgsCitation":"Verant, M.L., Bohuski, E.A., Richgels, K.L., Olival, K.J., Epstein, J.H., and Blehert, D.S., 2018, Determinants of Pseudogymnoascus destructans within bat hibernacula: Implications for surveillance and management of white-nose syndrome: Journal of Applied Ecology, v. 55, no. 2, p. 820-829, https://doi.org/10.1111/1365-2664.13070.","productDescription":"10 p.","startPage":"820","endPage":"829","ipdsId":"IP-078933","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":469050,"rank":3,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5877478","text":"External Repository"},{"id":350885,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418657,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77D2SP5","text":"USGS data release","description":"USGS data release","linkHelpText":"Determinants of Pseudogymnoascus destructans within bat hibernacula: data"}],"volume":"55","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-15","publicationStatus":"PW","scienceBaseUri":"5a74357fe4b0a9a2e9e25c7d","contributors":{"authors":[{"text":"Verant, Michelle L.","contributorId":201556,"corporation":false,"usgs":false,"family":"Verant","given":"Michelle","email":"","middleInitial":"L.","affiliations":[{"id":36202,"text":"School of Veterinary Medicine, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":726377,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohuski, Elizabeth A. 0000-0001-8061-2151 ebohuski@usgs.gov","orcid":"https://orcid.org/0000-0001-8061-2151","contributorId":5890,"corporation":false,"usgs":true,"family":"Bohuski","given":"Elizabeth","email":"ebohuski@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":726378,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richgels, Katherine L. D. 0000-0003-2834-9477 krichgels@usgs.gov","orcid":"https://orcid.org/0000-0003-2834-9477","contributorId":151205,"corporation":false,"usgs":true,"family":"Richgels","given":"Katherine","email":"krichgels@usgs.gov","middleInitial":"L. D.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":726379,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olival, Kevin J.","contributorId":143712,"corporation":false,"usgs":false,"family":"Olival","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":7118,"text":"EcoHealth Alliance","active":true,"usgs":false}],"preferred":false,"id":726380,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Epstein, Jonathan H.","contributorId":201557,"corporation":false,"usgs":false,"family":"Epstein","given":"Jonathan","email":"","middleInitial":"H.","affiliations":[{"id":36203,"text":"Ecohealth Alliamce","active":true,"usgs":false}],"preferred":false,"id":726381,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140397,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":726376,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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