{"pageNumber":"93","pageRowStart":"2300","pageSize":"25","recordCount":10450,"records":[{"id":70198105,"text":"70198105 - 2018 - Value of sample information in dynamic, structurally uncertain resource systems","interactions":[],"lastModifiedDate":"2018-07-16T11:02:00","indexId":"70198105","displayToPublicDate":"2018-07-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Value of sample information in dynamic, structurally uncertain resource systems","docAbstract":"Few if any natural resource systems are completely understood and fully observed. Instead, there almost always is uncertainty about the way a system works and its status at any given time, which can limit effective management. A natural approach to uncertainty is to allocate time and effort to the collection of additional data, on the reasonable assumption that more information will facilitate better understanding and lead to better management. But the collection of more data, either through observation or investigation, requires time and effort that often can be put to other conservation activities. An important question is whether the use of limited resources to improve understanding is justified by the resulting potential for improved management. In this paper we address directly a change in value from new information collected through investigation. We frame the value of information in terms of learning through the management process itself, as well as learning through investigations that are external to the management process but add to our base of understanding. We provide a conceptual framework and metrics for this issue, and illustrate them with examples involving Florida scrub-jays (Aphelocoma coerulescens).","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0199326","usgsCitation":"Williams, B.K., and Johnson, F.A., 2018, Value of sample information in dynamic, structurally uncertain resource systems: PLoS ONE, v. 13, no. 6, e0199326; 16 p., https://doi.org/10.1371/journal.pone.0199326.","productDescription":"e0199326; 16 p.","ipdsId":"IP-093487","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468589,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0199326","text":"Publisher Index Page"},{"id":355688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-29","publicationStatus":"PW","scienceBaseUri":"5b6fc413e4b0f5d57878e9c9","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":740038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@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},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":740037,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198082,"text":"70198082 - 2018 - Post-spring migration colony-site prospecting by Roseate Terns (Sterna dougallii)","interactions":[],"lastModifiedDate":"2018-07-16T10:44:23","indexId":"70198082","displayToPublicDate":"2018-07-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2881,"text":"North American Bird Bander","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Post-spring migration colony-site prospecting by Roseate Terns (<i>Sterna dougallii</i>)","title":"Post-spring migration colony-site prospecting by Roseate Terns (Sterna dougallii)","docAbstract":"We recorded banded Roseate Terns (Sterna dougallii) and unbanded individuals mated to banded individuals in May and the first third of June in 2001 and 2002 to quantify post spring migration prospecting by this species at Falkner Island, Connecticut, USA. In 2001, more than one quarter: 34/125 (27.2%) of those observed by 19 May and 38/150 (25.3%) of those observed by 25 May did not remain at this colony site and went elsewhere to attempt breeding. In 2002, fewer terns were observed by 19 May, but an even higher percentage: 11/28 (39.3%) of those seen by 19 May and 58/151 (38.4%) of those seen by 25 May did not stay and nest. Our results demonstrate that a substantial proportion of the earliest arriving individuals at this site are prospecting and gathering information about local conditions before making a decision about going elsewhere to nest.","language":"English","usgsCitation":"Spendelow, J.A., and Eichenwald, A.J., 2018, Post-spring migration colony-site prospecting by Roseate Terns (Sterna dougallii): North American Bird Bander, v. 43, no. 1, p. 1-6.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-074482","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":355681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc414e4b0f5d57878e9cd","contributors":{"authors":[{"text":"Spendelow, Jeffrey A. 0000-0001-8167-0898 jspendelow@usgs.gov","orcid":"https://orcid.org/0000-0001-8167-0898","contributorId":4355,"corporation":false,"usgs":true,"family":"Spendelow","given":"Jeffrey","email":"jspendelow@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eichenwald, Adam J.","contributorId":205977,"corporation":false,"usgs":false,"family":"Eichenwald","given":"Adam","email":"","middleInitial":"J.","affiliations":[{"id":37202,"text":"School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA","active":true,"usgs":false}],"preferred":false,"id":739934,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70202307,"text":"70202307 - 2018 - Rapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry","interactions":[],"lastModifiedDate":"2019-02-21T12:57:44","indexId":"70202307","displayToPublicDate":"2018-07-12T12:57:34","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Rapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry","docAbstract":"<p><span>Timely assessment of coastal landforms and structures after storms is important for evaluating storm impacts, aiding emergency response and restoration, and initializing and assessing morphological models. Four-dimensional multiview photogrammetry, also known as structure from motion (4D SfM), provides a method for generating three-dimensional reconstructions of landscapes at two times (before and after events) using only photos and existing information for ground control points. Here, these techniques were applied using National Oceanic and Atmospheric Administration (NOAA)-obtained oblique aerial photos taken before (2015) and immediately after Hurricane Matthew (2016) to assess coastal changes near Matanzas, Florida. This work demonstrated that 3D digital elevation models can be constructed within 48 hours of postevent photo collection without on-site ground control measurements. One advantage of timely SfM elevation-change assessments is that they avoid confusion of storm impacts with changes that occur after the event but before LIDAR surveys can be performed. The accuracy and precision of the 4D SfM maps were assessed&nbsp;</span><i>a posteriori</i><span>&nbsp;using the first-available LIDAR data, which were collected more than a month after the hurricane, and 11 independent ground-truth survey points measured a week after the hurricane. Horizontal coordinates of the 4D SfM reconstruction were biased by an average of 0.79 m (0.83 m root-mean-square difference; RMSD) compared with the ground-truth points, but vertical elevations were more accurate. They were biased from the LIDAR by −0.09 to −0.25 m, with ∼0.20 m RMSD from both the LIDAR data and five ground-truth points with good vertical positioning and 0.25 m RMSD from LIDAR data along a 60-m stretch of pavement. This level of precision was sufficient to quantify geomorphological change that was often in excess of 1 m. The methodology is conducive for rapid assessment of changes along short stretches (tens of kilometers) of coast with modest resources and could be scaled up for larger regions.</span></p>","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-18-00016.1","usgsCitation":"Sherwood, C.R., Warrick, J.A., Hill, A.D., Ritchie, A.C., Andrews, B.D., and Plant, N.G., 2018, Rapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry: Journal of Coastal Research, v. 34, no. 6, p. 1303-1316, https://doi.org/10.2112/JCOASTRES-D-18-00016.1.","productDescription":"14 p.","startPage":"1303","endPage":"1316","ipdsId":"IP-094558","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468591,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2112/jcoastres-d-18-00016.1","text":"Publisher Index Page"},{"id":361409,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.23505592346191,\n              29.655164600486\n            ],\n            [\n              -81.20484352111816,\n              29.655164600486\n            ],\n            [\n              -81.20484352111816,\n              29.70676659773517\n            ],\n            [\n              -81.23505592346191,\n              29.70676659773517\n            ],\n            [\n              -81.23505592346191,\n              29.655164600486\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"6","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hill, Andrew D.","contributorId":213440,"corporation":false,"usgs":false,"family":"Hill","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":757730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ritchie, Andrew C. 0000-0002-5906-1014 aritchie@usgs.gov","orcid":"https://orcid.org/0000-0002-5906-1014","contributorId":213438,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andrews, Brian D. 0000-0003-1024-9400 bandrews@usgs.gov","orcid":"https://orcid.org/0000-0003-1024-9400","contributorId":201662,"corporation":false,"usgs":true,"family":"Andrews","given":"Brian","email":"bandrews@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757728,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757729,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70198053,"text":"70198053 - 2018 - An update on Toxoplasma gondii infections in northern sea otters (Enhydra lutris kenyoni) from Washington State, USA","interactions":[],"lastModifiedDate":"2018-07-12T22:20:58","indexId":"70198053","displayToPublicDate":"2018-07-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3686,"text":"Veterinary Parasitology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"An update on Toxoplasma gondii infections in northern sea otters <i>(Enhydra lutris kenyoni) </i> from Washington State, USA","title":"An update on Toxoplasma gondii infections in northern sea otters (Enhydra lutris kenyoni) from Washington State, USA","docAbstract":"<p>Toxoplasmosis in marine mammals is epidemiologically and clinically important. <i>Toxoplasma gondii</i> antibodies (by modified agglutination test, cut-off ≥1:25) were detected in serum of 65 of 70 (92.9%) northern sea otters (<i>Enhydra lutris kenyoni</i>) from Washington State, USA. Brains and/or muscles of 44 sea otters were bioassayed in mice (INF-γ knock-out [KO], Swiss Webster outbred [SW]) and viable <i>T. gondii</i> was isolated from 22 of 44 (50%); <i>T. gondii</i> strains were lethal to KO mice but not SW mice. These <i>T. gondii</i> isolates were further propagated in cell culture. Multi-locus PCR-RFLP genotyping of cell culture-derived tachyzoites revealed four different genotypes among 22 isolates including ToxoDB PCR-RFLP genotype #5 (14 isolates), #1 (three isolates), #3 (four isolates), and #167 (one isolate). PCR-DNA sequencing based genotyping using polymorphic gene GRA6 revealed one of four different alleles. Among the 14 RFLP genotype #5 strains, 10 have GRA6 sequences that match with the Type A, one match with the Type X, two strains did not generate sequence data, and one strain had double peaks at known polymorphic sites indicating a mixed infection. The seven strains belong to genotypes #1 and #3, all have identical sequences to <i>T. gondii</i> Type II reference isolate ME49. Genotype #167 strain has identical sequence to Type I reference strain. In summary, we observed high seroprevalence, and high rate of isolation of <i>T. gondii</i> from northern sea otters and predominant genotype #5 that has been previously reported a dominant and widespread strain among terrestrial wildlife in North America. GRA6 sequence analysis of the genotype #5 isolates indicated the dominance of Type A lineage in sea otters in Washington State.</p>","language":"English","publisher":"Wildlife Disease Association","doi":"10.1016/j.vetpar.2018.05.011","usgsCitation":"Verma, S.K., Knowles, S., Cerqueira-Cezar, C.K., Kwok, O.C., Jiang, T., Su, C., and Dubey, J.P., 2018, An update on Toxoplasma gondii infections in northern sea otters (Enhydra lutris kenyoni) from Washington State, USA: Veterinary Parasitology, v. 258, p. 133-137, https://doi.org/10.1016/j.vetpar.2018.05.011.","productDescription":"5 p.","startPage":"133","endPage":"137","ipdsId":"IP-095836","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":355625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","volume":"258","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e538e4b060350a15d049","contributors":{"authors":[{"text":"Verma, Shiv K.","contributorId":167589,"corporation":false,"usgs":false,"family":"Verma","given":"Shiv","email":"","middleInitial":"K.","affiliations":[{"id":24764,"text":"US Department of Agriculture, Agricultural Research Service, Animal Parasitic Diseases Laboratory, Beltsville, MD, 20705-2350","active":true,"usgs":false}],"preferred":false,"id":739790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knowles, Susan 0000-0002-0254-6491 sknowles@usgs.gov","orcid":"https://orcid.org/0000-0002-0254-6491","contributorId":5254,"corporation":false,"usgs":true,"family":"Knowles","given":"Susan","email":"sknowles@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":739788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cerqueira-Cezar, Camila K.","contributorId":206207,"corporation":false,"usgs":false,"family":"Cerqueira-Cezar","given":"Camila","email":"","middleInitial":"K.","affiliations":[{"id":37284,"text":"United States Department of Agriculture, Agricultural Research Service, Beltsville Agricultural Research Center, Animal Parasitic Diseases Laboratory, Building 1001, Beltsville, MD, 20705-2350, USA","active":true,"usgs":false}],"preferred":false,"id":739791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kwok, Oliver C.","contributorId":167593,"corporation":false,"usgs":false,"family":"Kwok","given":"Oliver","email":"","middleInitial":"C.","affiliations":[{"id":24764,"text":"US Department of Agriculture, Agricultural Research Service, Animal Parasitic Diseases Laboratory, Beltsville, MD, 20705-2350","active":true,"usgs":false}],"preferred":false,"id":739792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jiang, Tiantian","contributorId":206208,"corporation":false,"usgs":false,"family":"Jiang","given":"Tiantian","email":"","affiliations":[{"id":37286,"text":"16\tDepartment of Microbiology, University of Tennessee, Knoxville, TN 37996-0845,","active":true,"usgs":false}],"preferred":false,"id":739793,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Su, Chunlei","contributorId":167590,"corporation":false,"usgs":false,"family":"Su","given":"Chunlei","email":"","affiliations":[{"id":24765,"text":"University of Tennessee, Department of Microbiology, Knoxville, TN 37996-0845","active":true,"usgs":false}],"preferred":false,"id":739794,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dubey, Jitender P.","contributorId":206206,"corporation":false,"usgs":false,"family":"Dubey","given":"Jitender","email":"","middleInitial":"P.","affiliations":[{"id":37284,"text":"United States Department of Agriculture, Agricultural Research Service, Beltsville Agricultural Research Center, Animal Parasitic Diseases Laboratory, Building 1001, Beltsville, MD, 20705-2350, USA","active":true,"usgs":false}],"preferred":false,"id":739789,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70198028,"text":"70198028 - 2018 - On the reliability of N‐mixture models for count data","interactions":[],"lastModifiedDate":"2018-07-09T21:49:17","indexId":"70198028","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1039,"text":"Biometrics","active":true,"publicationSubtype":{"id":10}},"title":"On the reliability of N‐mixture models for count data","docAbstract":"<p>N‐mixture models describe count data replicated in time and across sites in terms of abundance <i>N</i> and detectability <i>p</i>. They are popular because they allow inference about <i>N</i> while controlling for factors that influence <i>p</i> without the need for marking animals. Using a capture–recapture perspective, we show that the loss of information that results from not marking animals is critical, making reliable statistical modeling of <i>N</i> and <i>p</i> problematic using just count data. One cannot reliably fit a model in which the detection probabilities are distinct among repeat visits as this model is overspecified. This makes uncontrolled variation in <i>p</i> problematic. By counter example, we show that even if <i>p</i> is constant after adjusting for covariate effects (the “constant <i>p</i>” assumption) scientifically plausible alternative models in which <i>N</i> (or its expectation) is non‐identifiable or does not even exist as a parameter, lead to data that are practically indistinguishable from data generated under an N‐mixture model. This is particularly the case for sparse data as is commonly seen in applications. We conclude that under the constant <i>p</i> assumption reliable inference is only possible for relative abundance in the absence of questionable and/or untestable assumptions or with better quality data than seen in typical applications. Relative abundance models for counts can be readily fitted using Poisson regression in standard software such as R and are sufficiently flexible to allow controlling for <i>p</i> through the use covariates while simultaneously modeling variation in relative abundance. If users require estimates of absolute abundance, they should collect auxiliary data that help with estimation of <i>p</i>.</p>","language":"English","publisher":"Wiley","doi":"10.1111/biom.12734","usgsCitation":"Barker, R.J., Schofield, M., Link, W.A., and Sauer, J.R., 2018, On the reliability of N‐mixture models for count data: Biometrics, v. 74, no. 1, p. 369-377, https://doi.org/10.1111/biom.12734.","productDescription":"9 p.","startPage":"369","endPage":"377","ipdsId":"IP-075479","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460879,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/biom.12734","text":"Publisher Index Page"},{"id":355564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-03","publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d063","contributors":{"authors":[{"text":"Barker, Richard J.","contributorId":206174,"corporation":false,"usgs":false,"family":"Barker","given":"Richard","email":"","middleInitial":"J.","affiliations":[{"id":37272,"text":"University of Otago; Dunedin, New Zealand","active":true,"usgs":false}],"preferred":false,"id":739705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schofield, Matthew J.","contributorId":206175,"corporation":false,"usgs":false,"family":"Schofield","given":"Matthew J.","affiliations":[{"id":37272,"text":"University of Otago; Dunedin, New Zealand","active":true,"usgs":false}],"preferred":false,"id":739706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739707,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198033,"text":"70198033 - 2018 - Candidate products for operational earthquake forecasting illustrated using the HayWired planning scenario, including one very quick (and not‐so‐dirty) hazard‐map option","interactions":[],"lastModifiedDate":"2020-09-01T14:08:49.812533","indexId":"70198033","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Candidate products for operational earthquake forecasting illustrated using the HayWired planning scenario, including one very quick (and not‐so‐dirty) hazard‐map option","docAbstract":"<p>In an effort to help address debates on the usefulness of operational earthquake forecasting (OEF), we illustrate a number of OEF products that could be automatically generated in near‐real time. To exemplify, we use an <i><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;><mi xmlns=&quot;&quot;>M</mi></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mi\">M</span></span></span></span></span></span></i> 7.1 mainshock on the Hayward fault, which is very similar to the U.S. Geological Survey (USGS) HayWired earthquake planning scenario. Given that there is always some background level of hazard or risk, we emphasize that probability gains (the ratio of short‐term to long‐term‐average estimates) might be of particular interest to users. We also illustrate how such gains are highly sensitive to forecast duration and latency, with the latter representing how long it takes to generate the forecast and/or to take action. The influence of fault‐based information, which has traditionally been ignored in OEF, is also evaluated using the newly developed the third Uniform California Earthquake Rupture Forecast epidemic‐type aftershock sequence (UCERF3‐ETAS) model. We find that the inclusion of faults only makes a difference for hazard and risk metrics that are dominated by large‐event likelihoods. We also show how the ShakeMap of a mainshock represents a decent estimate of the ground motions that have a 6% chance of being exceeded due to aftershocks in the week that follows. The ultimate value of these types of OEF products can only be determined in the context of specific uses, and because these vary widely, institutions responsible for providing OEF products will depend heavily on user feedback, especially when making resource‐allocation decisions.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170241","usgsCitation":"Field, E., and Milner, K.R., 2018, Candidate products for operational earthquake forecasting illustrated using the HayWired planning scenario, including one very quick (and not‐so‐dirty) hazard‐map option: Seismological Research Letters, v. 89, no. 4, p. 1420-1434, https://doi.org/10.1785/0220170241.","productDescription":"15 p.","startPage":"1420","endPage":"1434","ipdsId":"IP-095951","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":355563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-18","publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d061","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":739725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milner, Kevin R.","contributorId":63494,"corporation":false,"usgs":true,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":739726,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198015,"text":"70198015 - 2018 - An updated method for estimating landslide‐event magnitude","interactions":[],"lastModifiedDate":"2018-07-13T14:28:34","indexId":"70198015","displayToPublicDate":"2018-07-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"An updated method for estimating landslide‐event magnitude","docAbstract":"<p><span>Summary statistics derived from the frequency–area distribution (FAD) of inventories of triggered landslides allows for direct comparison of landslides triggered by one event (e.g. earthquake, rainstorm) with another. Such comparisons are vital to understand links between the landslide‐event and the environmental characteristics of the area affected. This could lead to methods for rapid estimation of landslide‐event magnitude, which in turn could lead to estimates of the total triggered landslide area. Previous studies proposed that the FAD of landslides follows an inverse power‐law, which provides the basis to model the size distribution of landslides and to estimate landslide‐event magnitude (</span><i>mLS</i><span>), which quantifies the severity of the event. In this study, we use a much larger collection of earthquake‐induced landslide (EQIL) inventories (</span><i>n</i><span>=45) than previous studies to show that size distributions are much more variable than previously assumed. We present an updated model and propose a method for estimating<span>&nbsp;</span></span><i>mLS</i><span><span>&nbsp;</span>and its uncertainty that better fits the observations and is more reproducible, robust, and consistent than existing methods. We validate our model by computing<span>&nbsp;</span></span><i>mLS</i><span><span>&nbsp;</span>for all of the inventories in our dataset and comparing that with the total landslide areas of the inventories. We show that our method is able to estimate the total landslide area of the events in this larger inventory dataset more successfully than the existing methods.<span>&nbsp;</span></span></p>","language":"English","publisher":"Wiley","doi":"10.1002/esp.4359","usgsCitation":"Tanyas, H., Allstadt, K.E., and van Weston, C.J., 2018, An updated method for estimating landslide‐event magnitude: Earth Surface Processes and Landforms, v. 43, no. 9, p. 1836-1847, https://doi.org/10.1002/esp.4359.","productDescription":"12 p.","startPage":"1836","endPage":"1847","ipdsId":"IP-090008","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468601,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.4359","text":"Publisher Index Page"},{"id":437830,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79022QD","text":"USGS data release","linkHelpText":"landslides-mLS"},{"id":355523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5b46e541e4b060350a15d067","contributors":{"authors":[{"text":"Tanyas, Hakan","contributorId":198731,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","affiliations":[],"preferred":false,"id":739604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":739603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Weston, Cees J.","contributorId":206153,"corporation":false,"usgs":false,"family":"van Weston","given":"Cees","email":"","middleInitial":"J.","affiliations":[{"id":37261,"text":"University of Twente, Netherlands","active":true,"usgs":false}],"preferred":false,"id":739605,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70198084,"text":"70198084 - 2018 - Modeling the distributions of tegu lizards in native and potential invasive ranges","interactions":[],"lastModifiedDate":"2018-07-13T10:13:21","indexId":"70198084","displayToPublicDate":"2018-07-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the distributions of tegu lizards in native and potential invasive ranges","docAbstract":"<p>Invasive reptilian predators can have substantial impacts on native species and ecosystems. Tegu lizards are widely distributed in South America east of the Andes, and are popular in the international live animal trade. Two species are established in Florida (U.S.A.) - <i>Salvator merianae</i> (Argentine black and white tegu) and <i>Tupinambis teguixin sensu lato</i> (gold tegu) – and a third has been recorded there—<i> S. rufescens</i> (red tegu). We built species distribution models (SDMs) using 5 approaches (logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy) based on data from the native ranges. We then projected these models to North America to develop hypotheses for potential tegu distributions. Our results suggest that much of the southern United States and northern México probably contains suitable habitat for one or more of these tegu species. <i>Salvator rufescens</i> had higher habitat suitability in semi-arid areas, whereas <i>S. merianae</i> and <i>T. teguixin</i> had higher habitat suitability in more mesic areas. We propose that Florida is not the only state where these taxa could become established, and that early detection and rapid response programs targeting tegu lizards in potentially suitable habitat elsewhere in North America could help prevent establishment and abate negative impacts on native ecosystems.</p>","language":"English","publisher":"Springer","doi":"10.1038/s41598-018-28468-w","usgsCitation":"Jarnevich, C.S., Hayes, M., Fitzgerald, L.A., Yackel, A., Falk, B., Collier, M., Bonewell, L., Klug, P., Naretto, S., and Reed, R., 2018, Modeling the distributions of tegu lizards in native and potential invasive ranges: Scientific Reports, v. 8, e10193; 12 p., https://doi.org/10.1038/s41598-018-28468-w.","productDescription":"e10193; 12 p.","ipdsId":"IP-090713","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468602,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-28468-w","text":"Publisher Index Page"},{"id":437831,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JZZE4W","text":"USGS data release","linkHelpText":"Data for modeling tegu lizard distributions in the Americas"},{"id":355667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"5b6fc418e4b0f5d57878e9e1","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Mark","contributorId":206268,"corporation":false,"usgs":false,"family":"Hayes","given":"Mark","affiliations":[],"preferred":false,"id":739938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzgerald, Lee A.","contributorId":141035,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":739939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yackel, Amy 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":152310,"corporation":false,"usgs":true,"family":"Yackel","given":"Amy","email":"yackela@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Falk, Bryan 0000-0002-9690-5626 bfalk@usgs.gov","orcid":"https://orcid.org/0000-0002-9690-5626","contributorId":150075,"corporation":false,"usgs":true,"family":"Falk","given":"Bryan","email":"bfalk@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collier, Michelle 0000-0001-5715-448X","orcid":"https://orcid.org/0000-0001-5715-448X","contributorId":206269,"corporation":false,"usgs":true,"family":"Collier","given":"Michelle","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonewell, Lea","contributorId":206270,"corporation":false,"usgs":true,"family":"Bonewell","given":"Lea","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739943,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Klug, Page 0000-0002-0836-3901","orcid":"https://orcid.org/0000-0002-0836-3901","contributorId":206271,"corporation":false,"usgs":false,"family":"Klug","given":"Page","affiliations":[{"id":37295,"text":"USDA APHIS","active":true,"usgs":false}],"preferred":false,"id":739944,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Naretto, Sergio","contributorId":206272,"corporation":false,"usgs":false,"family":"Naretto","given":"Sergio","email":"","affiliations":[{"id":37296,"text":"Instituto de Diversidad y Ecología Animal","active":true,"usgs":false}],"preferred":false,"id":739945,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":739946,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70198059,"text":"70198059 - 2018 - A semi-arid river in distress: Contributing factors and recovery solutions for three imperiled freshwater mussels (Family Unionidae) endemic to the Rio Grande basin in North America","interactions":[],"lastModifiedDate":"2018-07-12T22:23:57","indexId":"70198059","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A semi-arid river in distress: Contributing factors and recovery solutions for three imperiled freshwater mussels (Family Unionidae) endemic to the Rio Grande basin in North America","docAbstract":"<p><span>Freshwater resources in arid and semi-arid regions are in extreme demand, which creates conflicts between needs of humans and aquatic ecosystems. The Rio Grande basin in the southwestern United States and northern Mexico exemplifies this issue, as much of its aquatic biodiversity is in peril as a result of human activities. Unionid mussels have been disproportionately impacted, though the specific factors responsible for their decline remain largely unknown. This is problematic because the Rio Grande basin harbors one federally endangered unionid mussel (</span><i>Popenaias popeii</i><span>, Texas Hornshell) plus two other mussel species (</span><i>Potamilus metnecktayi</i><span>, Salina Mucket; and<span>&nbsp;</span></span><i>Truncilla cognata</i><span>, Mexican Fawnsfoot), which are also being considered for listing under the U.S. Endangered Species Act. To date, surveys for these species have not corrected for variability in detection so current range estimates may be inaccurate. Using single occupancy-modeling to estimate detection and occupancy at 115 sites along ~800 river kilometers of the Rio Grande in Texas, we found that detection probabilities were relatively high, indicating that our survey design was efficient. In contrast, the estimated occupancy was low, indicating that our focal species were likely rare within the Rio Grande drainage. In general, the predicted occupancy of our focal species was low throughout their respective ranges, indicating possible range declines. A comparison of currently occupied ranges to presumptive ranges underscores this point. The best-approximating models indicated that occupancy was influenced by habitat, water quantity and quality, and proximity to large-scale human activities, such as dams and major urban centers. We also discuss a series of conservation options that may not only improve the long-term prognosis of our focal species but also other aquatic taxa.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.03.032","usgsCitation":"Randklev, C.R., Miller, T., Hart, M., Morton, J., Johnson, N.A., Skow, K., Inoue, K., Tsakiris, E., Oetker, S., Smith, R., Robertson, C., and Lopez, R., 2018, A semi-arid river in distress: Contributing factors and recovery solutions for three imperiled freshwater mussels (Family Unionidae) endemic to the Rio Grande basin in North America: Science of the Total Environment, v. 631-632, p. 733-744, https://doi.org/10.1016/j.scitotenv.2018.03.032.","productDescription":"12 p.","startPage":"733","endPage":"744","ipdsId":"IP-091761","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":355630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Rio Grande basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.5,34.25 ], [ -107.5,35.75 ], [ -106.0,35.75 ], [ -106.0,34.25 ], [ -107.5,34.25 ] ] ] } } ] }","volume":"631-632","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e545e4b060350a15d081","contributors":{"authors":[{"text":"Randklev, Charles R.","contributorId":202530,"corporation":false,"usgs":false,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":739813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Tom","contributorId":206211,"corporation":false,"usgs":false,"family":"Miller","given":"Tom","email":"","affiliations":[{"id":37287,"text":"Laredo Community College","active":true,"usgs":false}],"preferred":false,"id":739814,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Michael","contributorId":206212,"corporation":false,"usgs":false,"family":"Hart","given":"Michael","email":"","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":739815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morton, Jennifer","contributorId":206213,"corporation":false,"usgs":false,"family":"Morton","given":"Jennifer","email":"","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":739816,"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":739812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skow, Kevin","contributorId":206214,"corporation":false,"usgs":false,"family":"Skow","given":"Kevin","email":"","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":739817,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Inoue, Kentaro","contributorId":202526,"corporation":false,"usgs":false,"family":"Inoue","given":"Kentaro","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":739818,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tsakiris, Eric","contributorId":206215,"corporation":false,"usgs":false,"family":"Tsakiris","given":"Eric","email":"","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":739819,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Oetker, Susan","contributorId":206216,"corporation":false,"usgs":false,"family":"Oetker","given":"Susan","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":739820,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Ryan","contributorId":206257,"corporation":false,"usgs":false,"family":"Smith","given":"Ryan","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":739911,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Robertson, Clint","contributorId":206217,"corporation":false,"usgs":false,"family":"Robertson","given":"Clint","affiliations":[{"id":37288,"text":"Texas Parks and Wildife","active":true,"usgs":false}],"preferred":false,"id":739821,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lopez, Roel","contributorId":206218,"corporation":false,"usgs":false,"family":"Lopez","given":"Roel","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":739822,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70202687,"text":"70202687 - 2018 - Metamodeling for groundwater age forecasting in the Lake Michigan Basin","interactions":[],"lastModifiedDate":"2019-03-18T16:30:22","indexId":"70202687","displayToPublicDate":"2018-07-01T16:30:14","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Metamodeling for groundwater age forecasting in the Lake Michigan Basin","docAbstract":"<p><span>Groundwater age is an important indicator of groundwater susceptibility to anthropogenic contamination and a key input to statistical models for forecasting water quality. Numerical models can provide estimates of groundwater age, enabling interpretation of measured age tracers. However, to extend to national‐scale groundwater systems where numerical models are not routinely available, a more efficient metamodeling approach can provide a less precise but widely applicable estimate of groundwater age, trained to make forecasts based on predictor variables that can be measured independent of numerical models. We trained gradient‐boosted regression tree statistical metamodels to MODFLOW/MODPATH‐derived groundwater age estimates in five inset models in the Lake Michigan Basin, USA. Using high‐throughput computing, we explored an exhaustive range of tuning parameters and tested metamodels through cross validation, a 20% holdout, and a round robin approach among the five inset models withholding each inset model from training and testing on the held‐out inset model. Forecast skill—measured by Nash Sutcliffe efficiency—was high for age‐related responses in the 20% hold‐out case (ranging from 0.73 to 0.84). The round robin analysis provided the opportunity to explore extending to unmodeled areas and a greater range of skill indicated the need to evaluate when it is appropriate to apply a metamodel from one region to another. We further explored the ramifications of metamodel simplification achieved through removing predictor variables based on their estimated importance. We found that similar metamodel performance was achievable with a fraction of the candidate set of predictor variables with well construction variables being most important.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2017WR022387","usgsCitation":"Fienen, M.N., Nolan, B.T., Kauffman, L.J., and Feinstein, D.T., 2018, Metamodeling for groundwater age forecasting in the Lake Michigan Basin: Water Resources Research, v. 54, no. 7, p. 4750-4766, https://doi.org/10.1029/2017WR022387.","productDescription":"17 p.","startPage":"4750","endPage":"4766","ipdsId":"IP-096251","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468611,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr022387","text":"Publisher Index Page"},{"id":437832,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610ZMG","text":"USGS data release","linkHelpText":"Data and Scripts for Metamodeling for Groundwater Age Forecasting in the Lake Michigan Basin"},{"id":362158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Michigan Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89,\n              41.5\n            ],\n            [\n              -84,\n              41.5\n            ],\n            [\n              -84,\n              46.5\n            ],\n            [\n              -89,\n              46.5\n            ],\n            [\n              -89,\n              41.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"54","issue":"7","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":171511,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","middleInitial":"N.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nolan, B. Thomas 0000-0002-6945-9659","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":8905,"corporation":false,"usgs":true,"family":"Nolan","given":"B.","email":"","middleInitial":"Thomas","affiliations":[],"preferred":true,"id":759478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Leon J. 0000-0003-4564-0362 lkauff@usgs.gov","orcid":"https://orcid.org/0000-0003-4564-0362","contributorId":1094,"corporation":false,"usgs":true,"family":"Kauffman","given":"Leon","email":"lkauff@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530 dtfeinst@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":1907,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel","email":"dtfeinst@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759480,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70197865,"text":"70197865 - 2018 - Applying high-resolution imagery to evaluate restoration-induced changes in stream condition, Missouri River Headwaters Basin, Montana","interactions":[],"lastModifiedDate":"2018-08-07T12:15:35","indexId":"70197865","displayToPublicDate":"2018-07-01T12:15:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Applying high-resolution imagery to evaluate restoration-induced changes in stream condition, Missouri River Headwaters Basin, Montana","docAbstract":"<p><span>Degradation of streams and associated riparian habitat across the Missouri River Headwaters Basin has motivated several stream restoration projects across the watershed. Many of these projects install a series of beaver dam analogues (BDAs) to aggrade incised streams, elevate local water tables, and create natural surface water storage by reconnecting streams with their floodplains. Satellite imagery can provide a spatially continuous mechanism to monitor the effects of these in-stream structures on stream surface area. However, remote sensing-based approaches to map narrow (e.g., &lt;5 m wide) linear features such as streams have been under-developed relative to efforts to map other types of aquatic systems, such as wetlands or lakes. We mapped pre- and post-restoration (one to three years post-restoration) stream surface area and riparian greenness at four stream restoration sites using Worldview-2 and 3 images as well as a QuickBird-2 image. We found that panchromatic brightness and eCognition-based outputs (0.5 m resolution) provided high-accuracy maps of stream surface area (overall accuracy ranged from 91% to 99%) for streams as narrow as 1.5 m wide. Using image pairs, we were able to document increases in stream surface area immediately upstream of BDAs as well as increases in stream surface area along the restoration reach at Robb Creek, Alkali Creek and Long Creek (South). Although Long Creek (North) did not show a net increase in stream surface area along the restoration reach, we did observe an increase in riparian greenness, suggesting increased water retention adjacent to the stream. As high-resolution imagery becomes more widely collected and available, improvements in our ability to provide spatially continuous monitoring of stream systems can effectively complement more traditional field-based and gage-based datasets to inform watershed management.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs10060913","usgsCitation":"Vanderhoof, M.K., and Burt, C., 2018, Applying high-resolution imagery to evaluate restoration-induced changes in stream condition, Missouri River Headwaters Basin, Montana: Remote Sensing, v. 10, no. 6, p. 1-28, https://doi.org/10.3390/rs10060913.","productDescription":"Article 913; 28 p.","startPage":"1","endPage":"28","ipdsId":"IP-097220","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468616,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10060913","text":"Publisher Index Page"},{"id":437835,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F9618G","text":"USGS data release","linkHelpText":"Data release for Applying high-resolution imagery to evaluate restoration-induced changes in stream condition, Missouri River Headwaters Basin, Montana"},{"id":356280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Missouri River Headwaters Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.4167,\n              44.5\n            ],\n            [\n              -111.8333,\n              44.5\n            ],\n            [\n              -111.8333,\n              45.1667\n            ],\n            [\n              -112.4167,\n              45.1667\n            ],\n            [\n              -112.4167,\n              44.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-09","publicationStatus":"PW","scienceBaseUri":"5b6fc41be4b0f5d57878e9ef","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":738807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burt, Clifton 0000-0001-5213-800X","orcid":"https://orcid.org/0000-0001-5213-800X","contributorId":205903,"corporation":false,"usgs":false,"family":"Burt","given":"Clifton","affiliations":[],"preferred":false,"id":738808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70228296,"text":"70228296 - 2018 - Rearing performance of juvenile brown trout Salmo trutta fed a bioprocessed soybean meal diet with differing velocity regimes","interactions":[],"lastModifiedDate":"2022-02-08T14:58:58.91029","indexId":"70228296","displayToPublicDate":"2018-07-01T08:33:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10101,"text":"Open Journal of Animal Sciences","onlineIssn":"2161-762","printIssn":"2161-7597","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rearing performance of juvenile brown trout <i>Salmo trutta </i> fed a bioprocessed soybean meal diet with differing velocity regimes","title":"Rearing performance of juvenile brown trout Salmo trutta fed a bioprocessed soybean meal diet with differing velocity regimes","docAbstract":"This 121-day experiment evaluated the rearing performance of brown trout Salmo trutta fed one of two isonitrogenous and isocaloric diets (46% protein, 16% lipid) and reared at velocities of either 2.8 or 16.1 cm/s. Fishmeal was the primary protein source for the reference diet, which was compared to a bioprocessed soybean meal ingredient that replaced approximately 67% of the fishmeal in the experimental diet. At the end of the experiment, there were no significant differences in gain, percent gain, feed conversion rates, nor specific growth rates between the dietary treatments. There were also no significant differences in intestinal morphology, splenosomatic, hepatosomatic, and viscerosomatic indices related to diet composition. However, gain, percent gain, feed fed, and specific growth rate were all significantly greater in brown trout reared at the higher velocity. No significant differences in any of the other variables measured were observed between the velocity treatments. There were no significant interactions between diet and velocity in any of the variables. Based on the results of this study, bioprocessed soybean meal can replace at least 67% of the fish meal in brown trout diets, regardless of the rearing velocities used in this study. Higher rearing velocities are recommended to maximize juvenile brown trout growth rates.\n ","language":"English","publisher":"Scientific Research","doi":"10.4236/ojas.2018.83023","usgsCitation":"Voorhees, J.M., Barnes, M., Chipps, S.R., and Browne, M., 2018, Rearing performance of juvenile brown trout Salmo trutta fed a bioprocessed soybean meal diet with differing velocity regimes: Open Journal of Animal Sciences, v. 8, no. 3, p. 303-328, https://doi.org/10.4236/ojas.2018.83023.","productDescription":"26 p.","startPage":"303","endPage":"328","ipdsId":"IP-097693","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468619,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/ojas.2018.83023","text":"Publisher Index Page"},{"id":395612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Voorhees, Jill M.","contributorId":275085,"corporation":false,"usgs":false,"family":"Voorhees","given":"Jill","email":"","middleInitial":"M.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":833628,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnes, Michael","contributorId":275086,"corporation":false,"usgs":false,"family":"Barnes","given":"Michael","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":833629,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833627,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Browne, Michael","contributorId":178752,"corporation":false,"usgs":false,"family":"Browne","given":"Michael","email":"","affiliations":[],"preferred":false,"id":833630,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70205969,"text":"70205969 - 2018 - A multiscale natural community and species-level vulnerability assessment of the Gulf Coast, USA","interactions":[],"lastModifiedDate":"2019-10-11T17:30:54","indexId":"70205969","displayToPublicDate":"2018-06-29T17:22:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A multiscale natural community and species-level vulnerability assessment of the Gulf Coast, USA","docAbstract":"<p><span>Vulnerability assessments combine quantitative and qualitative evaluations of the exposure, sensitivity, and adaptive capacity of species or natural communities to current and future threats. When combined with the economic, ecological or evolutionary value of the species, vulnerability assessments quantify the relative risk to regional species and natural communities and can enable informed prioritization of conservation efforts. Vulnerability assessments are common practice in conservation biology, including the potential impacts of future climate scenarios. However, geographic variation in scenarios and vulnerabilities is rarely quantified. This gap is particularly limiting for informing ecosystem management given that conservation practices typically vary by sociopolitical boundaries rather than by ecological boundaries. To support prioritization of conservation actions across a range of spatial scales, we conducted the Gulf Coast Vulnerability Assessment (GCVA) for four natural communities and eleven focal species around the Gulf of Mexico based on current and future threats from climate change and land-use practices out to 2060. We used the Standardized Index of Vulnerability and Value (SIVVA) tool to assess both natural community and species vulnerabilities. We observed greater variation across ecologically delineated subregions within the Gulf Coast of the U.S. than across climate scenarios. This novel finding suggests that future vulnerability assessments incorporate regional variation and that conservation prioritization may vary across ecological subregions. Across subregions and climate scenarios the most prominent threats were legacy effects, primarily from habitat loss and degradation, that compromised the adaptive capacity of species and natural communities. The second most important threats were future threats from sea-level rise. Our results suggest that the substantial threats species and natural communities face from climate change and sea-level rise would be within their adaptive capacity were it not for historic habitat loss, fragmentation, and degradation.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0199844","usgsCitation":"Reece, J.S., Watson, A., Dalyander, P., Edwards, C., Geselbracht, L., LaPeyre, M.K., Tirpak, B., Tirpak, J., and Woodrey, M., 2018, A multiscale natural community and species-level vulnerability assessment of the Gulf Coast, USA: PLoS ONE, v. 13, no. 6, e0199844, 23 p., https://doi.org/10.1371/journal.pone.0199844.","productDescription":"e0199844, 23 p.","ipdsId":"IP-089364","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0199844","text":"Publisher Index Page"},{"id":368287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia, Louisiana, Mississippi, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.86962890625,\n              30.44867367928756\n            ],\n            [\n              -91.60400390625,\n              31.16580958786196\n            ],\n            [\n              -95.0537109375,\n              30.391830328088137\n            ],\n            [\n              -98.28369140625,\n              28.188243641850313\n            ],\n            [\n              -99.052734375,\n              26.62781822639305\n     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University","active":true,"usgs":false}],"preferred":false,"id":773108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dalyander, Patricia (Soupy) 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":191931,"corporation":false,"usgs":true,"family":"Dalyander","given":"Patricia (Soupy)","email":"sdalyander@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":773109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, C.","contributorId":80335,"corporation":false,"usgs":true,"family":"Edwards","given":"C.","affiliations":[],"preferred":false,"id":773110,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Geselbracht, Laura","contributorId":149889,"corporation":false,"usgs":false,"family":"Geselbracht","given":"Laura","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":773111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":773112,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tirpak, Blair 0000-0002-2679-8378 btirpak@usgs.gov","orcid":"https://orcid.org/0000-0002-2679-8378","contributorId":149886,"corporation":false,"usgs":true,"family":"Tirpak","given":"Blair","email":"btirpak@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":773113,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tirpak, John M.","contributorId":197496,"corporation":false,"usgs":false,"family":"Tirpak","given":"John M.","affiliations":[],"preferred":false,"id":773114,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Woodrey, Mark","contributorId":149890,"corporation":false,"usgs":false,"family":"Woodrey","given":"Mark","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":773115,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70197952,"text":"70197952 - 2018 - Pharmaceuticals, hormones, pesticides, and other bioactive contaminants in water, sediment, and tissue from Rocky Mountain National Park, 2012–2013","interactions":[],"lastModifiedDate":"2018-06-28T12:04:10","indexId":"70197952","displayToPublicDate":"2018-06-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Pharmaceuticals, hormones, pesticides, and other bioactive contaminants in water, sediment, and tissue from Rocky Mountain National Park, 2012–2013","docAbstract":"<p><span>Pharmaceuticals, hormones, pesticides, and other bioactive contaminants (BCs) are commonly detected in surface water and bed sediment in urban and suburban areas, but these contaminants are understudied in remote locations. In Rocky Mountain National Park (RMNP), Colorado, USA, BCs may threaten the reproductive success and survival of native aquatic species, benthic communities, and pelagic food webs. In 2012–2013, 67 water, 57 sediment, 63 fish, 10 frog, and 12 quality-control samples (8 water and 4 sediment) were collected from 20 sites in RMNP. Samples were analyzed for 369 parameters including 149 pharmaceuticals, 22 hormones, 137 pesticides, and 61 other chemicals or conditions to provide a representative assessment of BC occurrence within RMNP. Results indicate that BCs were detected in water and/or sediment from both remote and more accessible locations in RMNP. The most commonly detected BCs in water were caffeine, camphor, para-cresol, and DEET; and the most commonly detected BCs in sediment were indole, 3-methyl-1H-indole, para-cresol, and 2,6-dimethyl-naphthalene. Some detected contaminants, including carbaryl, caffeine, and oxycodone, are clearly attributable to direct local human input, whereas others may be transported into the park atmospherically (e.g., atrazine) or have local natural sources (e.g., para-cresol). One or more pharmaceuticals were detected in at least 1 sample from 15 of 20 sites. Most of the 29 detected pharmaceuticals are excreted primarily in human urine, not feces. Elevated net estrogenicity was observed in 18% of water samples, and elevated vitellogenin in blood was observed in 12% of male trout, both evidence of potential endocrine disruption. Hormone concentrations in sediment tended to be greater than concentrations in water. Most BCs were observed at concentrations below those not expected to pose adverse effects to aquatic life. Results indicate that even in remote locations aquatic wildlife can be exposed to pharmaceuticals, hormones, pesticides, and other bioactive contaminants.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.06.150","usgsCitation":"Battaglin, W., Bradley, P.M., Iwanowicz, L.R., Journey, C.A., Walsh, H., and Blazer, V., 2018, Pharmaceuticals, hormones, pesticides, and other bioactive contaminants in water, sediment, and tissue from Rocky Mountain National Park, 2012–2013: Science of the Total Environment, v. 643, p. 651-673, https://doi.org/10.1016/j.scitotenv.2018.06.150.","productDescription":"23 p.","startPage":"651","endPage":"673","ipdsId":"IP-093530","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":460883,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.06.150","text":"Publisher Index Page"},{"id":437843,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XUYMQT","text":"USGS data release","linkHelpText":"Occurrence data for organic compounds and bioactive chemicals in water, sediment and tissue from Rocky Mountain National Park, 2012-13"},{"id":355409,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.8333,\n              40.1667\n            ],\n            [\n              -105.5,\n              40.1667\n            ],\n            [\n              -105.5,\n              40.5833\n            ],\n            [\n              -105.8333,\n              40.5833\n            ],\n            [\n              -105.8333,\n              40.1667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"643","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e54be4b060350a15d0ad","contributors":{"authors":[{"text":"Battaglin, William A. 0000-0001-7287-7096","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":204638,"corporation":false,"usgs":true,"family":"Battaglin","given":"William A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":190787,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":739303,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":189681,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739304,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Heather L. 0000-0001-6392-4604","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":203238,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":739306,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":739305,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197930,"text":"70197930 - 2018 - Cinnamon gulch revisited: Another look at separating natural and mining-impacted contributions to instream metal load","interactions":[],"lastModifiedDate":"2018-06-27T09:47:23","indexId":"70197930","displayToPublicDate":"2018-06-27T00:00:00","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":"Cinnamon gulch revisited: Another look at separating natural and mining-impacted contributions to instream metal load","docAbstract":"Baseline, premining data for streams draining abandoned mine lands is virtually non existent, and indirect methods for estimating premining conditions are needed to establish realistic, cost effective cleanup goals. One such indirect method is the proximal analog approach, in which premining conditions are estimated using data from nearby mineralized areas that are unaffected by mining. In this paper, we combine the proximal analog approach with a quantitative mass balance framework using data from a spatially-detailed synoptic sampling campaign. The combined approach is applied to Cinnamon Gulch, a headwater stream with numerous draining adits. Synoptic sampling results indicate that three of the top five metal sources are affected by mining activities, and stream segments draining these sources account for a large percentage of overall metal loading within the study reach. These initial calculations overestimate the effects of mining, as the affected stream segments were likely acidic and metal rich prior to mining. Premining loads and concentrations were therefore determined through a replacement approach in which the chemistry of each mining-affected stream segment is revised based on proximal analog concentrations. The revised loading profiles indicate that 15–17% of the Al, Cd, Cu, Mn, Ni, and Zn loads are attributable to mining, whereas the mining contribution for Pb is 40%. Premining concentrations of Al, Cd, Cu, Mn, and Zn are estimated to be in excess of aquatic life standards over the length of the study reach.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2018.04.010","usgsCitation":"Runkel, R.L., Verplanck, P., Kimball, B., and Walton-Day, K., 2018, Cinnamon gulch revisited: Another look at separating natural and mining-impacted contributions to instream metal load: Applied Geochemistry, v. 95, p. 206-217, https://doi.org/10.1016/j.apgeochem.2018.04.010.","productDescription":"12 p.","startPage":"206","endPage":"217","ipdsId":"IP-093823","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":355388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Cinnamon Gulch","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.171875,\n              39.27053717095511\n            ],\n            [\n              -105.40008544921875,\n              39.27053717095511\n            ],\n            [\n              -105.40008544921875,\n              39.791654835253425\n            ],\n            [\n              -106.171875,\n              39.791654835253425\n            ],\n            [\n              -106.171875,\n              39.27053717095511\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"95","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e54de4b060350a15d0b5","contributors":{"authors":[{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verplanck, Philip L. 0000-0002-3653-6419","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":202205,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip L.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":739209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kimball, Briant bkimball@usgs.gov","contributorId":206033,"corporation":false,"usgs":true,"family":"Kimball","given":"Briant","email":"bkimball@usgs.gov","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739210,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":184043,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739211,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70197933,"text":"70197933 - 2018 - Before-after, control-impact analysis of evidence for the impacts of water level on Walleye, Northern Pike and Yellow Perch in lakes of the Rainy-Namakan complex (MN, USA and ON, CA)","interactions":[],"lastModifiedDate":"2018-06-27T13:26:27","indexId":"70197933","displayToPublicDate":"2018-06-27T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Before-after, control-impact analysis of evidence for the impacts of water level on Walleye, Northern Pike and Yellow Perch in lakes of the Rainy-Namakan complex (MN, USA and ON, CA)","docAbstract":"Water level (WL) fluctuations in lakes influence many aspects of ecosystem processes.\nConcern about the potential impact of WL fluctuations on fisheries was one of the factors\nthat motivated the decision in 2000 to alter the management of WL in the Rainy-Namakan\nreservoir complex (on the border between the U.S. state of Minnesota and the Canadian\nprovince of Ontario). We used a Before-After, Control-Impact (BACI) framework to identify\npotential impacts of the change in WL management to Walleye, Northern Pike and Yellow\nPerch catch per unit effort (CPUE). The CPUE of these species from 1990±1999 and from\n2005±2014 were compared in four impact lakes (Lake Kabetogama, Namakan Lake, Rainy\nLake and Sand Point Lake) and two control lakes (Lake of the Woods and Lake Vermilion)\nusing a simple Bayesian model. Changes in fish CPUE in the impact lakes were often similar\nto changes that occurred in at least one control lake. The only change that was not similar to\nchanges in control lakes was an increase of Yellow Perch in Lake Kabetogama. The two\ncontrol lakes often differed substantially from each other, such that if only one had been\navailable our conclusions about the role of WL management on fisheries would be very different.\nIn general, identifying cause-and-effect relationships in observational field data is\nvery difficult, and the BACI analysis used here does not specify a causative mechanism,\nso co-occurring environmental and management changes may obscure the effect of WL\nmanagement.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0198612","usgsCitation":"Larson, J.H., Maki, R., Vondra, B.A., and Peterson, K.E., 2018, Before-after, control-impact analysis of evidence for the impacts of water level on Walleye, Northern Pike and Yellow Perch in lakes of the Rainy-Namakan complex (MN, USA and ON, CA): PLoS ONE, v. 13, no. 6, e0198612; 10 p., https://doi.org/10.1371/journal.pone.0198612.","productDescription":"e0198612; 10 p.","ipdsId":"IP-079647","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468627,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0198612","text":"Publisher Index Page"},{"id":355391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Minnesota, Ontario","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -96.1083984375,\n              47.88688085106901\n            ],\n            [\n              -91.40625,\n              47.88688085106901\n            ],\n            [\n              -91.40625,\n              49.809631563563094\n            ],\n            [\n              -96.1083984375,\n              49.809631563563094\n            ],\n            [\n              -96.1083984375,\n              47.88688085106901\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-07","publicationStatus":"PW","scienceBaseUri":"5b46e54ce4b060350a15d0b1","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":739223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maki, Ryan P.","contributorId":190131,"corporation":false,"usgs":false,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":739224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vondra, Benjamin A.","contributorId":206035,"corporation":false,"usgs":false,"family":"Vondra","given":"Benjamin","email":"","middleInitial":"A.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":739225,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Kevin E.","contributorId":177489,"corporation":false,"usgs":false,"family":"Peterson","given":"Kevin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":739226,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199079,"text":"70199079 - 2018 - Fungal loop transfer of nitrogen depends on biocrust constituents and nitrogen form","interactions":[],"lastModifiedDate":"2018-08-31T10:27:03","indexId":"70199079","displayToPublicDate":"2018-06-22T10:26:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Fungal loop transfer of nitrogen depends on biocrust constituents and nitrogen form","docAbstract":"<p><span>Besides performing multiple ecosystem services individually and collectively, biocrust constituents may also create biological networks connecting spatially and temporally distinct processes. In the fungal loop hypothesis rainfall variability allows fungi to act as conduits and reservoirs, translocating resources between soils and host plants. To evaluate the extent to which biocrust species composition and nitrogen (N) form influence loops, we created a minor, localized rainfall event containing&nbsp;</span><sup>15</sup><span>NH</span><sub>4</sub><sup>+</sup><span>&nbsp;and&nbsp;</span><sup>15</sup><span>NO</span><sub>3</sub><sup>−</sup><span>. We then measured the resulting&nbsp;</span><i>δ</i><sup>15</sup><span>N in the surrounding dry cyanobacteria- and lichen-dominated crusts and grass,&nbsp;</span><i>Achnatherum hymenoides</i><span>, after 24 h. We also estimated the biomass of fungal constituents using quantitative PCR and characterized fungal communities by sequencing the 18S&nbsp;rRNA gene. We found evidence for the initiation of fungal loops in cyanobacteria-dominated crusts where&nbsp;</span><sup>15</sup><span>N, from&nbsp;</span><sup>15</sup><span>NH</span><sub>4</sub><sup>+</sup><span>, moved 40 mm h</span><sup>−1</sup><span>&nbsp;in biocrust soils with the&nbsp;</span><i>δ</i><sup>15</sup><span>N of crusts decreasing as the radial distance from the water addition increased (linear mixed effects model (LMEM)):&nbsp;</span><i>R</i><sup>2</sup><span> = 0.67,&nbsp;</span><i>F</i><sub>2,12</sub><span> = 11,&nbsp;</span><i>P</i><span> = 0.002). In cyanobacteria crusts,&nbsp;</span><i>δ</i><sup>15</sup><span>N, from&nbsp;</span><sup>15</sup><span>NH</span><sub>4</sub><sup>+</sup><span>, was diluted as Ascomycota biomass increased (LMEM:&nbsp;</span><i>R</i><sup>2</sup><span> = 0.63,&nbsp;</span><i>F</i><sub>2,8</sub><span> = 6.8,&nbsp;</span><i>P</i><span> = 0.02), Ascomycota accounted for 82 % (±2.8) of all fungal sequences, and one order, Pleosporales, comprised 66 % (±6.9) of Ascomycota. The seeming lack of loops in moss-dominated crusts may stem from the relatively large moss biomass effectively absorbing and holding N from our minor wet deposition event. The substantial movement of&nbsp;</span><sup>15</sup><span>NH</span><sub>4</sub><sup>+</sup><span>&nbsp;may indicate a fungal preference for the reduced N form during amino acid transformation and translocation. We found a marginally significant enrichment of&nbsp;</span><i>δ</i><sup>15</sup><span>N in&nbsp;</span><i>A. hymenoides</i><span>&nbsp;leaves but only in cyanobacteria biocrusts translocating&nbsp;</span><sup>15</sup><span>N, offering evidence of links between biocrust constituents and higher plants. Our results suggest that minor rainfall events may initiate fungal loops potentially allowing constituents, like dark septate Pleosporales, to rapidly translocate N from NH</span><sub>4</sub><sup>+</sup><span>&nbsp;over NO</span><sub>3</sub><sup>−</sup><span>&nbsp;through biocrust networks.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/bg-15-3831-2018","usgsCitation":"Aanderud, Z.T., Smart, T.B., Wu, N., Taylor, A.S., Zhang, Y., and Belnap, J., 2018, Fungal loop transfer of nitrogen depends on biocrust constituents and nitrogen form: Biogeosciences, v. 15, no. 12, p. 3831-3840, https://doi.org/10.5194/bg-15-3831-2018.","productDescription":"10 p.","startPage":"3831","endPage":"3840","ipdsId":"IP-091786","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468633,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-15-3831-2018","text":"Publisher Index Page"},{"id":356987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-22","publicationStatus":"PW","scienceBaseUri":"5b98a2a3e4b0702d0e842fa8","contributors":{"authors":[{"text":"Aanderud, Zachary T.","contributorId":176977,"corporation":false,"usgs":false,"family":"Aanderud","given":"Zachary","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":743959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smart, Trevor B.","contributorId":207495,"corporation":false,"usgs":false,"family":"Smart","given":"Trevor","email":"","middleInitial":"B.","affiliations":[{"id":37545,"text":"Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USA","active":true,"usgs":false}],"preferred":false,"id":743960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Nan","contributorId":207496,"corporation":false,"usgs":false,"family":"Wu","given":"Nan","email":"","affiliations":[{"id":37546,"text":"Xinjiang Institute of Ecology and Geography, Key Laboratory of Biogeography and Bioresource in Arid Land, Chinese Academy of Sciences,","active":true,"usgs":false}],"preferred":false,"id":743961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Alexander S.","contributorId":207497,"corporation":false,"usgs":false,"family":"Taylor","given":"Alexander","email":"","middleInitial":"S.","affiliations":[{"id":37545,"text":"Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USA","active":true,"usgs":false}],"preferred":false,"id":743963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Yuanming","contributorId":173232,"corporation":false,"usgs":false,"family":"Zhang","given":"Yuanming","email":"","affiliations":[{"id":27200,"text":"Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China","active":true,"usgs":false}],"preferred":false,"id":743962,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743958,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197821,"text":"70197821 - 2018 - Use of Bank Swallow (Riparia riparia) burrows as shelter by Common Tern (Sterna hirundo) chicks","interactions":[],"lastModifiedDate":"2018-06-21T09:19:49","indexId":"70197821","displayToPublicDate":"2018-06-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Use of Bank Swallow (<i>Riparia riparia</i>) burrows as shelter by Common Tern (<i>Sterna hirundo</i>) chicks","title":"Use of Bank Swallow (Riparia riparia) burrows as shelter by Common Tern (Sterna hirundo) chicks","docAbstract":"The availability of shelter to avoid predation and ameliorate physiologically stressful conditions is often important to the survival of avian hatchlings. However, as changes in habitat availability force birds to nest in nontraditional locations, young must quickly adapt to using novel sources of shelter. Two Common Tern (Sterna hirundo) colonies (one vegetated and one barren) were observed during the 2017 breeding season on a remote island habitat restoration project during data collection for a larger associated study. While chicks within the vegetated colony sought shade under vegetation, those in the barren colony were frequently found under anthropogenically constructed chick shelters. The first reported instance of Common Tern chicks using Bank Swallow (Riparia riparia) burrows for shelter was also observed in the barren colony. This behavior, when paired with other similar reports, suggests that this species is able to recognize beneficial shelters, both natural and anthropogenic, and use them at a young age, an important ability if they are to successfully reproduce in atypical habitats","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.041.0210","usgsCitation":"McGowan, P.C., Reintsma, K., Sullivan, J.D., DeVoss, K.P., Wall, J.L., Zimnik, M.D., Callahan, C.R., Schultz, B., and Prosser, D.J., 2018, Use of Bank Swallow (Riparia riparia) burrows as shelter by Common Tern (Sterna hirundo) chicks: Waterbirds, v. 41, no. 2, p. 179-182, https://doi.org/10.1675/063.041.0210.","productDescription":"4 p.","startPage":"179","endPage":"182","ipdsId":"IP-089905","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":355240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Poplar Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.41883850097656,\n              38.73212548425921\n            ],\n            [\n              -76.34193420410156,\n              38.73212548425921\n            ],\n            [\n              -76.34193420410156,\n              38.79690830348427\n            ],\n            [\n              -76.41883850097656,\n              38.79690830348427\n            ],\n            [\n              -76.41883850097656,\n              38.73212548425921\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"41","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e554e4b060350a15d0df","contributors":{"authors":[{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":738656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reintsma, Kaitlyn","contributorId":205843,"corporation":false,"usgs":true,"family":"Reintsma","given":"Kaitlyn","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738655,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Jeffery D.","contributorId":202910,"corporation":false,"usgs":false,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":738657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeVoss, Katie P.","contributorId":205844,"corporation":false,"usgs":false,"family":"DeVoss","given":"Katie","email":"","middleInitial":"P.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":738658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wall, Jennifer L.","contributorId":205845,"corporation":false,"usgs":false,"family":"Wall","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":738659,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimnik, Mia D.","contributorId":205846,"corporation":false,"usgs":false,"family":"Zimnik","given":"Mia","email":"","middleInitial":"D.","affiliations":[{"id":37175,"text":"Hood College","active":true,"usgs":false}],"preferred":false,"id":738660,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":738661,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schultz, Bill","contributorId":205847,"corporation":false,"usgs":false,"family":"Schultz","given":"Bill","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":738662,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738654,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70197806,"text":"70197806 - 2018 - Origin of methane and sources of high concentrations in Los Angeles groundwater","interactions":[],"lastModifiedDate":"2018-06-20T16:24:11","indexId":"70197806","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Origin of methane and sources of high concentrations in Los Angeles groundwater","docAbstract":"In 2014, samples from 37 monitoring wells at 17 locations, within or near oil fields, and one site >5 km from oil fields, in the Los Angeles Basin, California, were analyzed for dissolved hydrocarbon gas isotopes and abundances. The wells sample a variety of depths of an aquifer system composed of unconsolidated and semiconsolidated sediments under various conditions of confinement. Concentrations of methane in groundwater samples ranged from 0.002 to 150 mg/L—some of the highest concentrations reported in a densely populated urban area. The δ13C and δ2H of the methane ranged from −80.8 to −45.5 per mil (‰) and −249.8 to −134.9‰, respectively, and, along with oxidation‐reduction processes, helped to identify the origin of methane as microbial methanogenesis and CO2 reduction as its main formation pathway. The distribution of methane concentrations and isotopes is consistent with the high concentrations of methane in Los Angeles Basin groundwater originating from relatively shallow microbial production in anoxic or suboxic conditions. Source of the methane is the aquifer sediments rather than the upward migration or leakage of thermogenic methane associated with oil fields in the basin.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JG004026","usgsCitation":"Kulongoski, J.T., McMahon, P.B., Land, M., Wright, M., Johnson, T., and Landon, M.K., 2018, Origin of methane and sources of high concentrations in Los Angeles groundwater: Journal of Geophysical Research: Biogeosciences, v. 123, no. 3, p. 818-831, https://doi.org/10.1002/2017JG004026.","productDescription":"14 p.","startPage":"818","endPage":"831","ipdsId":"IP-078703","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","otherGeospatial":"Los Angeles Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.46533203125,\n              33.458942753687644\n            ],\n            [\n              -117.630615234375,\n              33.458942753687644\n            ],\n            [\n              -117.630615234375,\n              34.97600151317588\n            ],\n            [\n              -119.46533203125,\n              34.97600151317588\n            ],\n            [\n              -119.46533203125,\n              33.458942753687644\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"123","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-11","publicationStatus":"PW","scienceBaseUri":"5b46e555e4b060350a15d0eb","contributors":{"authors":[{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Land, Michael 0000-0001-5141-0307 mtland@usgs.gov","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":171938,"corporation":false,"usgs":true,"family":"Land","given":"Michael","email":"mtland@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Michael 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":151031,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Theodore","contributorId":205833,"corporation":false,"usgs":false,"family":"Johnson","given":"Theodore","affiliations":[{"id":37173,"text":"Water Replenishment District of Southern California","active":true,"usgs":false}],"preferred":false,"id":738600,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738601,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197782,"text":"70197782 - 2018 - A simple, cost-effective emitter for controlled release of fish pheromones: development, testing, and application to management of the invasive sea lamprey","interactions":[],"lastModifiedDate":"2018-06-21T09:55:11","indexId":"70197782","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A simple, cost-effective emitter for controlled release of fish pheromones: development, testing, and application to management of the invasive sea lamprey","docAbstract":"Semiochemicals that elicit species-specific attraction or repulsion have proven useful in the management of terrestrial pests and hold considerable promise for control of nuisance aquatic species, particularly invasive fishes. Because aquatic ecosystems are typically large and open, use of a semiochemical to control a spatially dispersed invader will require the development of a cost-effective emitter that is easy to produce, environmentally benign, inexpensive, and controls the release of the semiochemical without altering its structure. We examined the release properties of five polymers, and chose polyethylene glycol (PEG) as the best alternative. In a series of laboratory and field experiments, we examined the response of the invasive sea lamprey to PEG, and to a partial sex pheromone emitted from PEG that has proven effective as a trap bait to capture migrating sea lamprey prior to spawning. Our findings confirm that the sea lamprey does not behaviorally respond to PEG, and that the attractant response to the pheromone component was conserved when emitted from PEG. Further, we deployed the pheromone-PEG emitters as trap bait during typical control operations in three Great Lakes tributaries, observing similar improvements in trap performance when compared to a previous study using mechanically pumped liquid pheromone. Finally, the polymer emitters tended to dissolve unevenly in high flow conditions. We demonstrate that housing the emitter stabilizes the dissolution rate at high water velocity. We conclude the performance characteristics of PEG emitters to achieve controlled-release of a semiochemical are sufficient to recommend its use in conservation and management activities related to native and invasive aquatic organisms.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0197569","usgsCitation":"Wagner, C., Hanson, J.E., Meckley, T.D., Johnson, N., and Bals, J.D., 2018, A simple, cost-effective emitter for controlled release of fish pheromones: development, testing, and application to management of the invasive sea lamprey: PLoS ONE, v. 13, no. 6, p. 1-17, https://doi.org/10.1371/journal.pone.0197569.","productDescription":"e0197569; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-096735","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":468641,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0197569","text":"Publisher Index Page"},{"id":355197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5b46e556e4b060350a15d0f3","contributors":{"authors":[{"text":"Wagner, C. Michael","contributorId":173006,"corporation":false,"usgs":false,"family":"Wagner","given":"C. Michael","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":738478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanson, James E.","contributorId":198866,"corporation":false,"usgs":false,"family":"Hanson","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":738479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meckley, Trevor D.","contributorId":205787,"corporation":false,"usgs":false,"family":"Meckley","given":"Trevor","email":"","middleInitial":"D.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":738480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":738477,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bals, Jason D.","contributorId":205788,"corporation":false,"usgs":false,"family":"Bals","given":"Jason","email":"","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":738481,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70204848,"text":"70204848 - 2018 - A framework for identifying and characterising coral reef “oases” against a backdrop of degradation","interactions":[],"lastModifiedDate":"2020-09-01T14:08:16.952561","indexId":"70204848","displayToPublicDate":"2018-06-18T08:10:12","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A framework for identifying and characterising coral reef “oases” against a backdrop of degradation","docAbstract":"<ol class=\"\"><li>Human activities have led to widespread ecological decline; however, the severity of degradation is spatially heterogeneous due to some locations resisting, escaping, or rebounding from disturbances.</li><li>We developed a framework for identifying oases within coral reef regions using long‐term monitoring data. We calculated standardised estimates of coral cover (<i>z</i>‐scores) to distinguish sites that deviated positively from regional means. We also used the coefficient of variation (CV) of coral cover to quantify how oases varied temporally, and to distinguish among types of oases. We estimated “coral calcification capacity” (CCC), a measure of the coral community's ability to produce calcium carbonate structures and tested for an association between this metric and<span>&nbsp;</span><i>z</i>‐scores of coral cover.</li><li>We illustrated our<span>&nbsp;</span><i>z</i>‐score approach within a modelling framework by extracting<span>&nbsp;</span><i>z</i>‐scores and CVs from simulated data based on four generalized trajectories of coral cover. We then applied the approach to time‐series data from long‐term reef monitoring programmes in four focal regions in the Pacific (the main Hawaiian Islands and Mo'orea, French Polynesia) and western Atlantic (the Florida Keys and St. John, US Virgin Islands). Among the 123 sites analysed, 38 had positive<span>&nbsp;</span><i>z</i>‐scores for median coral cover and were categorised as oases.</li><li><i>Synthesis and applications</i>. Our framework provides ecosystem managers with a valuable tool for conservation by identifying “oases” within degraded areas. By evaluating trajectories of change in state (e.g., coral cover) among oases, our approach may help in identifying the mechanisms responsible for spatial variability in ecosystem condition. Increased mechanistic understanding can guide whether management of a particular location should emphasise protection, mitigation or restoration. Analysis of the empirical data suggest that the majority of our coral reef oases originated by either escaping or resisting disturbances, although some sites showed a high capacity for recovery, while others were candidates for restoration. Finally, our measure of reef condition (i.e., median<span>&nbsp;</span><i>z</i>‐scores of coral cover) correlated positively with coral calcification capacity suggesting that our approach identified oases that are also exceptional for one critical component of ecological function.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13179","usgsCitation":"Guest, J.R., Edmunds, P.J., Gates, R.D., Kuffner, I.B., Andersson, A.J., Barnes, B.B., Chollett, I., Courtney, T.A., Elahi, R., Gross, K., Lenz, E.A., Mitarai, S., Mumby, P.J., Nelson, H.R., Parker, B.A., Putnam, H.M., Rogers, C.S., and Toth, L., 2018, A framework for identifying and characterising coral reef “oases” against a backdrop of degradation: Journal of Applied Ecology, v. 55, no. 6, p. 2865-2875, https://doi.org/10.1111/1365-2664.13179.","productDescription":"11 p.","startPage":"2865","endPage":"2875","ipdsId":"IP-088135","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13179","text":"Publisher Index Page"},{"id":366671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"French Polynesia, United States, US Virgin Islands","state":"Florida, Hawaii","otherGeospatial":"Florida Keys","volume":"55","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Guest, James R.","contributorId":204566,"corporation":false,"usgs":false,"family":"Guest","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":768732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edmunds, Peter J.","contributorId":204567,"corporation":false,"usgs":false,"family":"Edmunds","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":36956,"text":"California State University","active":true,"usgs":false}],"preferred":false,"id":768733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gates, Ruth D.","contributorId":167853,"corporation":false,"usgs":false,"family":"Gates","given":"Ruth","email":"","middleInitial":"D.","affiliations":[{"id":24839,"text":"Hawai'i Institute of Marine Biology, Hawaii","active":true,"usgs":false}],"preferred":false,"id":768734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 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Kevin","contributorId":71483,"corporation":false,"usgs":true,"family":"Gross","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":768741,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lenz, Elizabeth A.","contributorId":218227,"corporation":false,"usgs":false,"family":"Lenz","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":768742,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mitarai, Satoshi","contributorId":218228,"corporation":false,"usgs":false,"family":"Mitarai","given":"Satoshi","email":"","affiliations":[],"preferred":false,"id":768743,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mumby, Peter J.","contributorId":175366,"corporation":false,"usgs":false,"family":"Mumby","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":768744,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Nelson, Hannah 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caroline_rogers@usgs.gov","orcid":"https://orcid.org/0000-0001-9056-6961","contributorId":3126,"corporation":false,"usgs":true,"family":"Rogers","given":"Caroline","email":"caroline_rogers@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":768748,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768749,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70221454,"text":"70221454 - 2018 - Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model","interactions":[],"lastModifiedDate":"2021-06-16T14:14:34.261411","indexId":"70221454","displayToPublicDate":"2018-06-16T08:52:24","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7168,"text":"Journal of the American Water Resources Association (JAWRA)","active":true,"publicationSubtype":{"id":10}},"title":"Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model","docAbstract":"We test the use of a mixed-effects model for estimating lag to peak for small basins in Maine (drainage areas from 0.8 to 78 km2). Lag to peak is defined as the time between the center of volume of the excess rainfall during a storm event and the resulting peak streamflow. A mixed-effects model allows for multiple observations at sites without violating model assumptions inherent in traditional ordinary least squares models, which assume each observation is independent. The mixed model includes basin drainage area and maximum 15-min rainfall depth for individual storms as explanatory features. Based on a remove-one-site cross-validation analysis, the prediction errors of this model ranged from 42% to +73%. The mixed model substantially outperformed three published models for lag to peak and one published model for centroid lag for estimating lag to peak for small basins in Maine. Lag to peak estimates are a key input to rainfallrunoff models used to design hydraulic infrastructure. The improved accuracy and consistency with model assumptions indicates that mixed models may provide increased data utilization that could enhance models and estimates of lag to peak in other regions.","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12653","usgsCitation":"Lombard, P.J., and Holtschlag, D., 2018, Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model: Journal of the American Water Resources Association (JAWRA), v. 54, no. 4, p. 949-961, https://doi.org/10.1111/1752-1688.12653.","productDescription":"13 p.","startPage":"949","endPage":"961","ipdsId":"IP-089128","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":437859,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PK0F3D","text":"USGS data release","linkHelpText":"Precipitation and streamflow data for computing lag to peak at selected stations in Maine"},{"id":386535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Maine","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -69.08203125,\n              47.517200697839414\n            ],\n            [\n              -70.0048828125,\n              46.558860303117164\n            ],\n            [\n              -70.9716796875,\n              45.27488643704891\n            ],\n            [\n              -70.751953125,\n              43.100982876188546\n            ],\n            [\n              -66.8408203125,\n              44.84029065139799\n            ],\n            [\n              -67.3681640625,\n              45.82879925192134\n            ],\n            [\n              -67.9833984375,\n              47.368594345213374\n            ],\n            [\n              -69.08203125,\n              47.517200697839414\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"54","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":205225,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holtschlag, David 0000-0001-5185-4928","orcid":"https://orcid.org/0000-0001-5185-4928","contributorId":215360,"corporation":false,"usgs":true,"family":"Holtschlag","given":"David","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817755,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70221449,"text":"70221449 - 2018 - Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015","interactions":[],"lastModifiedDate":"2021-06-17T10:29:24.325243","indexId":"70221449","displayToPublicDate":"2018-06-16T07:48:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">The Weighted Regressions on Time, Discharge, and Season (WRTDS) model was used to derive estimates of suspended-sediment concentration (SSC) and suspended-sediment load (SSL), their dependence on discharge, and their trends with confidence intervals, for one site each on the lowermost Mississippi and Atchafalaya Rivers. The WRTDS model reduces uncertainty in SSCs related to variable streamflow conditions. Flow-normalized SSCs in each river were similar, and decreased from about 260 mg/L to 130 mg/L from 1980 through 2015; combined annual SSL in the two rivers decreased from about 200 Megatons per year (MT/y) to about 100 MT/y. Declines in SSC and SSL were more gradual from 2005 through 2015 and show signs of stabilizing. Our estimates of SSL in 2015 differ markedly from several recently published estimates of current and projected future Mississippi River SSLs, which were generally around 200 MT/y. However, these values came mostly from a different site upstream on the Mississippi River. The relationship between SSC and streamflow differed in an important way between the two rivers. SSC increased as streamflow increased for the entire range of observed streamflow in the Atchafalaya River. In the Mississippi River, SSC followed the same pattern during low and moderate streamflow but decreased at the highest streamflow that tended to occur between January and July. Since much of the water flowing in the Atchafalaya originates from the Mississippi River, the difference suggests a within-basin source of suspended sediment for the Atchafalaya River that is absent in the lower Mississippi River. These findings have important implications for the restoration of deltaic wetlands in coastal Louisiana. Accurate estimates of the SSL available in each river are crucial for understanding how effective diversions of river water into adjacent estuaries will be in sustaining these wetlands. Our study demonstrates that there might be far less sediment available than previously reported. Further, the difference in the relationship between SSC and streamflow in the two rivers is highly relevant to the ongoing discussion of coastal restoration strategies because the delta building that is occurring at the mouth of the Atchafalaya River is frequently used as a model of what could be expected with controlled diversions in the lower Mississippi River delta. The differences in the SSC behavior with changes in streamflow between the two rivers needs to be considered when results from the Atchafalaya River system are projected to those of the Mississippi River.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2018.05.068","usgsCitation":"Mize, S., Murphy, J.C., Diehl, T.H., and Demcheck, D.K., 2018, Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015: Journal of Hydrology, v. 564, p. 1-11, https://doi.org/10.1016/j.jhydrol.2018.05.068.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-079997","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":386526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Mississippi River, Lower Atchafalaya River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.60400390625,\n              30.996445897426373\n            ],\n            [\n              -91.5106201171875,\n              31.043521630684204\n            ],\n            [\n              -91.527099609375,\n              31.194007509998823\n            ],\n            [\n              -91.746826171875,\n              31.17050982470345\n            ],\n            [\n              -91.82922363281249,\n              31.123496964067325\n            ],\n            [\n              -91.86767578124999,\n              30.97289931126414\n            ],\n            [\n              -91.8511962890625,\n              30.543338954230222\n            ],\n            [\n              -91.71936035156249,\n              30.140376821599734\n            ],\n            [\n              -91.6094970703125,\n              29.702368038541767\n            ],\n            [\n              -91.4996337890625,\n              29.44916482692468\n            ],\n            [\n              -91.131591796875,\n              29.35345166863502\n            ],\n            [\n              -91.03271484375,\n              29.578234494739206\n            ],\n            [\n              -91.021728515625,\n              29.954934549656144\n            ],\n            [\n              -90.6976318359375,\n              29.835878945929952\n            ],\n            [\n              -90.054931640625,\n              29.702368038541767\n            ],\n            [\n              -89.7967529296875,\n              29.67850809103362\n            ],\n            [\n              -89.84619140625,\n              29.950175057288813\n            ],\n            [\n              -90.3350830078125,\n              30.059585699708215\n            ],\n            [\n              -90.8734130859375,\n              30.183121842195515\n            ],\n            [\n              -91.23596191406249,\n              30.694611546632277\n            ],\n            [\n              -91.60400390625,\n              30.996445897426373\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"564","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mize, Scott 0000-0001-6751-5568","orcid":"https://orcid.org/0000-0001-6751-5568","contributorId":218508,"corporation":false,"usgs":true,"family":"Mize","given":"Scott","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":167405,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":817746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Demcheck, Dennis K. 0000-0003-2981-078X","orcid":"https://orcid.org/0000-0003-2981-078X","contributorId":210305,"corporation":false,"usgs":true,"family":"Demcheck","given":"Dennis","email":"","middleInitial":"K.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817748,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70197646,"text":"70197646 - 2018 - Rapid crop cover mapping for the conterminous United States","interactions":[],"lastModifiedDate":"2018-06-14T15:57:50","indexId":"70197646","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Rapid crop cover mapping for the conterminous United States","docAbstract":"<p><span>Timely crop cover maps with sufficient resolution are important components to various environmental planning and research applications. Through the modification and use of a previously developed crop classification model (CCM), which was originally developed to generate historical annual crop cover maps, we hypothesized that such crop cover maps could be generated rapidly during the growing season. Through a process of incrementally removing weekly and monthly independent variables from the CCM and implementing a ‘two model mapping’ approach, we found it viable to generate conterminous United States-wide rapid crop cover maps at a resolution of 250 m for the current year by the month of September. In this approach, we divided the CCM model into one ‘crop type model’ to handle the classification of nine specific crops and a second, binary model to classify the presence or absence of ‘other’ crops. Under the two model mapping approach, the training errors were 0.8% and 1.5% for the crop type and binary model, respectively, while test errors were 5.5% and 6.4%, respectively. With spatial mapping accuracies for annual maps reaching upwards of 70%, this approach demonstrated a strong potential for generating rapid crop cover maps by the 1</span><sup>st</sup><span><span>&nbsp;</span>of September.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-26284-w","usgsCitation":"Dahal, D., Wylie, B.K., and Howard, D., 2018, Rapid crop cover mapping for the conterminous United States: Scientific Reports, v. 8, Article number: 8631; 12 p., https://doi.org/10.1038/s41598-018-26284-w.","productDescription":"Article number: 8631; 12 p.","ipdsId":"IP-089563","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-26284-w","text":"Publisher Index 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wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":738034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howard, Daniel 0000-0002-7563-7538","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":56946,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":738035,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70216310,"text":"70216310 - 2018 - Divergent effects of land-use, propagule pressure, and climate on woody riparian invasion","interactions":[],"lastModifiedDate":"2020-11-11T15:01:54.712614","indexId":"70216310","displayToPublicDate":"2018-06-13T08:56:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Divergent effects of land-use, propagule pressure, and climate on woody riparian invasion","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Landscape-scale analyses of biological invasion are needed to understand the relative importance of environmental drivers that vary at larger scales, such as climate, propagule pressure, resource availability, and human disturbance. One poorly understood landscape-scale question is, how does human land-use influence riparian plant invasion? To evaluate the relative importance of land-use, climate, propagule pressure, and water availability in riparian invasion, we examined tamarisk (<i>Tamarix ramosissima, T. chinensis</i>, hybrids), Russian olive (<i>Elaeagnus angustifolia</i>), and Siberian elm (<i>Ulmus pumila</i>) occurrence, abundance, and dominance in 238 riparian sites in developed, cultivated, and undeveloped areas of four western USA river basins (281,946&nbsp;km<sup>2</sup>). Temperature and propagule pressure from individuals planted nearby largely drove invasive species occurrence, whereas factors likely to affect resource availability (e.g., land-use, precipitation, streamflow intermittency) were more important to abundance and dominance, supporting the argument that species distribution models based on occurrence alone may fail to identify conditions where invasive species have the greatest impact. The role of land-use varied among taxa: urban and suburban land-use increased Siberian elm occurrence, abundance, and dominance, and urban land-use increased Russian olive occurrence, whereas suburban land-use reduced tamarisk dominance. Surprisingly, Siberian elm, which has received scant prior scientific and management attention, occurred as or more frequently than tamarisk and Russian olive (except in undeveloped areas of the Colorado River headwaters) and had higher density and dominance than tamarisk and Russian olive in developed areas. More research is needed to understand the impacts of this largely unrecognized invader on riparian ecosystem services, particularly in urban and suburban areas.</p></div></div><div id=\"cobranding-and-download-availability-text\" class=\"note test-pdf-link\"><br></div>","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1773-5","usgsCitation":"Perry, L.G., Reynolds, L.V., and Shafroth, P., 2018, Divergent effects of land-use, propagule pressure, and climate on woody riparian invasion: Biological Invasions, v. 20, p. 3271-3295, https://doi.org/10.1007/s10530-018-1773-5.","productDescription":"25 p.","startPage":"3271","endPage":"3295","ipdsId":"IP-097094","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":437863,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TX3DPF","text":"USGS data release","linkHelpText":"Woody riparian invasive plant presence, stem density, and rank dominance and environmental conditions in 2012 at 238 bridge crossings in the Colorado Headwaters, upper/middle Rio Grande, upper Arkansas, and South Platte River Basins, USA"},{"id":380410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.7216796875,\n              40.88029480552824\n            ],\n            [\n              -104.5458984375,\n              40.81380923056958\n            ],\n            [\n              -109.1162109375,\n              40.74725696280421\n            ],\n            [\n              -109.2919921875,\n              38.58252615935333\n            ],\n            [\n              -109.072265625,\n              36.66841891894786\n            ],\n            [\n              -107.9296875,\n              32.99023555965106\n            ],\n            [\n              -104.853515625,\n              33.76088200086917\n            ],\n            [\n              -103.35937499999999,\n              35.92464453144099\n            ],\n            [\n              -101.90917968749999,\n              38.51378825951165\n            ],\n            [\n              -102.26074218749999,\n              39.50404070558415\n            ],\n            [\n              -104.7216796875,\n              40.88029480552824\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Laura G","contributorId":177873,"corporation":false,"usgs":false,"family":"Perry","given":"Laura","email":"","middleInitial":"G","affiliations":[],"preferred":false,"id":804626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reynolds, Lindsay V.","contributorId":141182,"corporation":false,"usgs":false,"family":"Reynolds","given":"Lindsay","email":"","middleInitial":"V.","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":804627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":804628,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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