{"pageNumber":"845","pageRowStart":"21100","pageSize":"25","recordCount":184617,"records":[{"id":70196994,"text":"ds1087 - 2018 - Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014","interactions":[],"lastModifiedDate":"2018-07-03T12:45:49","indexId":"ds1087","displayToPublicDate":"2018-07-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1087","title":"Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014","docAbstract":"

Groundwater-quality data were collected from 502 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program and are included in this report. Most of the wells (500) were sampled from January through December 2015, and 2 of them were sampled in 2013. The data were collected from five types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; and vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic speciation, chromium [VI], and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release. Some data from environmental samples collected in 2013 and quality-control samples collected in 2014 also are included in the associated data release; these data are associated with networks described in this report and have not been published previously.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1087","usgsCitation":"Arnold, T.L., Bexfield, L.M., Musgrove, M., Stackelberg, P.E., Lindsey, B.D., Kingsbury, J.A., Kulongoski, J.T., and Belitz, K., 2018, Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014: U.S. Geological Survey Data Series 1087, 68 p., https://doi.org/10.3133/ds1087.","productDescription":"Report: ix, 67 p.; Data Release","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091701","costCenters":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":355481,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1087/coverthb.jpg"},{"id":355482,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1087/ds1087.pdf","text":"Report","size":"16.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1087"},{"id":355483,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XK8DHK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Datasets from Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January through December 2015 and Previously Unpublished Data from 2013–2014"}],"country":"United States","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
405 N. Goodwin
Urbana, IL 61801

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-07-03","noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d07d","contributors":{"authors":[{"text":"Arnold, Terri 0000-0003-1406-6054 tlarnold@usgs.gov","orcid":"https://orcid.org/0000-0003-1406-6054","contributorId":1598,"corporation":false,"usgs":false,"family":"Arnold","given":"Terri","email":"tlarnold@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":false,"id":735215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":735216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":197013,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":739490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stackelberg, Paul E. 0000-0002-1818-355X pestack@usgs.gov","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":1069,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","email":"pestack@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":434,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce D.","email":"blindsey@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":739493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":156272,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739494,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":739495,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196904,"text":"ofr20181081 - 2018 - U.S. Geological Survey Community for Data Integration 2017 Workshop Proceedings","interactions":[],"lastModifiedDate":"2018-10-24T14:43:27","indexId":"ofr20181081","displayToPublicDate":"2018-07-02T15:50:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1081","title":"U.S. Geological Survey Community for Data Integration 2017 Workshop Proceedings","docAbstract":"

Executive Summary

The U.S. Geological Survey (USGS) Community for Data Integration (CDI) Workshop was held May 16–19, 2017 at the Denver Federal Center. There were 183 in-person attendees and 35 virtual attendees over four days. The theme of the workshop was “Enabling Integrated Science,” with the purpose of bringing together the community to discuss current topics, shared challenges, and steps forward to advance integrated science at the USGS.

The CDI welcomed several keynote speakers, including Bill Werkheiser, USGS Acting Director; Kevin T. Gallagher, USGS Associate Director of the Core Science Systems Mission Area; Bruce Caron, Earth Science Information Partners Community Architect; and Tim Quinn, Chief of the USGS Office of Enterprise Information. Their presentations focused on the importance of collaborative, cross-disciplinary, and open science and the role of the CDI in identifying and supporting new opportunities in these areas for the USGS and its partners.

In addition to the stated theme, the workshop agenda was driven by the needs of the CDI, with topics highlighting current resources and technologies that could help attendees in their daily work. Topical sessions were proposed by CDI members and included subjects such as data citation, information technology architecture, legacy data, real-time data, and many more. Plenary speakers from the community talked about USGS activities in data science, elevation and hydrography data integration, advanced scientific computing solutions, cloud computing, data-management training, and data-sharing agreements. Two panels addressed the role of the CDI in enabling integrated science and examples of CDI-supported projects in action.

Breakout discussions focused on the workshop theme of “Enabling Integrated Science” and covered five topics: Data and Data Integration, Modeling, Computing Capacity, Science Data Integration, and User Needs and Experience. Sessions on each topic identified actions that could bring the USGS and the broader Earth science community closer to the goal of making integrated science commonplace. The breakouts produced recommendations with the broad themes of improving communication and connections across the USGS, reducing duplication and increasing knowledge transfer, increasing training and testbed opportunities to learn and experiment, and creating community-supported standards to enable better integration and interoperability.

The DataBlast poster and live demonstration session showcased 36 projects from around the CDI and included recent CDI-funded projects as well as other USGS and partner initiatives that were related to data and software integration and discovery.

Importantly, the CDI workshop provided a forum for scientists, technologists, data and resource managers, program managers, and others to convene face to face to discuss common methods, interests, challenges, and solutions related to scientific data and technologies. As a result of this rare convergence, new connections were made across disciplines, backgrounds, and geographical locations, seeding future activities and collaborations. Sharing of ideas from all attendees was encouraged through the use of a mobile application to collect real-time questions and feedback from the audience

The primary outcomes of the workshop are the recommendations from the breakout sessions titled “Roadmap Discussions on Enabling Integrated Science” and from the topical sessions detailed in these proceedings. These sessions, as well as the plenary discussions, identified new areas of collaboration and learning that the CDI will facilitate, such as data science, software development, scientific modeling practices, and user needs and experience. The CDI will build on the results of the workshop to guide its future topics, events, and funding opportunities to support an integrated science capacity for the USGS.

 

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181081","usgsCitation":"Hsu, L., Hutchison, V.B., Langseth, M.L., and Wheeler, B., 2018, U.S. Geological Survey Community for Data Integration 2017 Workshop Proceedings: U.S. Geological Survey Open-File Report 2018–1081, 56 p., https://doi.org/10.3133/ofr20181081.","productDescription":"viii, 56 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-092748","costCenters":[{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":355343,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1081/coverthb.jpg"},{"id":355344,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1081/ofr20181081.pdf","text":"Report","size":"5.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1081"}],"contact":"

Core Science Analytics, Synthesis, and Library
U.S. Geological Survey
108 National Center
12201 Sunrise Valley Drive,
Reston, VA 20192

","tableOfContents":"","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2018-07-02","noUsgsAuthors":false,"publicationDate":"2018-07-02","publicationStatus":"PW","scienceBaseUri":"5b46e545e4b060350a15d07f","contributors":{"authors":[{"text":"Hsu, Leslie 0000-0002-5353-807X lhsu@usgs.gov","orcid":"https://orcid.org/0000-0002-5353-807X","contributorId":191745,"corporation":false,"usgs":true,"family":"Hsu","given":"Leslie","email":"lhsu@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":734967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hutchison, Vivian B. 0000-0001-5301-3698 vhutchison@usgs.gov","orcid":"https://orcid.org/0000-0001-5301-3698","contributorId":5100,"corporation":false,"usgs":true,"family":"Hutchison","given":"Vivian B.","email":"vhutchison@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":734968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langseth, Madison L. 0000-0002-4472-9106 mlangseth@usgs.gov","orcid":"https://orcid.org/0000-0002-4472-9106","contributorId":147810,"corporation":false,"usgs":true,"family":"Langseth","given":"Madison","email":"mlangseth@usgs.gov","middleInitial":"L.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":734969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wheeler, Benjamin 0000-0001-5875-1163 bwheeler@usgs.gov","orcid":"https://orcid.org/0000-0001-5875-1163","contributorId":5949,"corporation":false,"usgs":true,"family":"Wheeler","given":"Benjamin","email":"bwheeler@usgs.gov","affiliations":[],"preferred":true,"id":734970,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199039,"text":"70199039 - 2018 - Real-time nowcasting of microbiological water quality at recreational beaches: A wavelet and artificial neural network-based hybrid modeling approach","interactions":[],"lastModifiedDate":"2018-08-29T15:47:30","indexId":"70199039","displayToPublicDate":"2018-07-02T15:47:12","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Real-time nowcasting of microbiological water quality at recreational beaches: A wavelet and artificial neural network-based hybrid modeling approach","docAbstract":"

The number of beach closings caused by bacterial contamination has continued to rise in recent years, putting beachgoers at risk of exposure to contaminated water. Current approaches predict levels of indicator bacteria using regression models containing a number of explanatory variables. Data-based modeling approaches can supplement routine monitoring data and provide highly accurate short-term forecasts of beach water quality. In this paper, we apply the nonlinear autoregressive network with exogenous inputs (NARX) method with explanatory variables to predict Escherichia coli concentrations at four Lake Michigan beach sites. We also apply the nonlinear input–output network (NIO) and nonlinear autoregressive neural network (NAR) methods in addition to a hybrid wavelet-NAR (WA-NAR) model and demonstrate their application. All models were tested using 3 months of observed data. Results revealed that the NARX models provided the best performance and that the WA-NAR model, which requires no explanatory variables, outperformed the NIO and NAR models; therefore, the WA-NAR model is suitable for application to data scarce regions. The models proposed in this paper were evaluated using multiple performance metrics, including sensitivity and specificity measures, and produced results comparable or superior to those of previous mechanistic and statistical models developed for the same beach sites. The relatively high R2 values between data and the NARX models (R2 values of ∼0.8 for the beach sites and ∼0.9 for the river site) indicate that the new class of models shows promise for beach management.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.8b01022","usgsCitation":"Zhang, J., Qiu, H., Li, X., Niu, J., Nevers, M., Hu, X., and Phanikumar, M.S., 2018, Real-time nowcasting of microbiological water quality at recreational beaches: A wavelet and artificial neural network-based hybrid modeling approach: Environmental Science & Technology, v. 52, no. 15, p. 8446-8455, https://doi.org/10.1021/acs.est.8b01022.","productDescription":"10 p.","startPage":"8446","endPage":"8455","ipdsId":"IP-094837","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":356935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"15","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-29","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f98","contributors":{"authors":[{"text":"Zhang, Juan","contributorId":207432,"corporation":false,"usgs":false,"family":"Zhang","given":"Juan","email":"","affiliations":[{"id":37539,"text":"Jinan University","active":true,"usgs":false}],"preferred":false,"id":743839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qiu, Han","contributorId":207433,"corporation":false,"usgs":false,"family":"Qiu","given":"Han","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":743840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Xiaoyu","contributorId":207434,"corporation":false,"usgs":false,"family":"Li","given":"Xiaoyu","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":743841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niu, Jie","contributorId":207435,"corporation":false,"usgs":false,"family":"Niu","given":"Jie","email":"","affiliations":[{"id":37539,"text":"Jinan University","active":true,"usgs":false}],"preferred":false,"id":743842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":743838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hu, Xiaonong","contributorId":207436,"corporation":false,"usgs":false,"family":"Hu","given":"Xiaonong","email":"","affiliations":[{"id":37539,"text":"Jinan University","active":true,"usgs":false}],"preferred":false,"id":743843,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Phanikumar, Mantha S.","contributorId":147924,"corporation":false,"usgs":false,"family":"Phanikumar","given":"Mantha","email":"","middleInitial":"S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":743844,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201402,"text":"70201402 - 2018 - The foraminifera of Chincoteague Bay, Assateague Island, and the surrounding areas: A regional distribution study","interactions":[],"lastModifiedDate":"2025-05-13T18:36:32.220109","indexId":"70201402","displayToPublicDate":"2018-07-02T14:56:15","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2294,"text":"Journal of Foraminiferal Research","active":true,"publicationSubtype":{"id":10}},"title":"The foraminifera of Chincoteague Bay, Assateague Island, and the surrounding areas: A regional distribution study","docAbstract":"

Foraminiferal census data from Chincoteague Bay, Newport Bay, the salt marshes of Assateague Island, adjacent mainland salt marshes, and the inner-shelf, were assessed to determine the current assemblages in Chincoteague Bay, and how the different environments surrounding the bay, and the gradients within the bay, influence the microfossil distribution. Determining the current background distribution and its drivers allows for future comparisons to determine paleoenvironmental conditions, impacts from natural and anthropogenic pollution, and the influence of climate change. Foraminiferal census data were compared to sedimentological characteristics and environmental parameters, exhibiting strong correlations with salinity, sediment organic content, and grain-size. Foraminiferal distributions exhibited a gradient from an assemblage dominated by Elphidium cf. E. excavatum near Chincoteague inlet to an assemblage dominated by Ammonia parkinsoniana and Ammobaculites cf. Ab. exiguus in the more restricted central and northern portions of the bay. The sites closest to the mouth of Trappe Creek in Newport Bay, along the western side of Chincoteague Bay and in the central bay, had a greater relative abundance of dead agglutinated taxa compared with the majority of sites in Chincoteague Bay. Despite the overwhelming dominance of calcareous taxa throughout the bay, dissolution may affect the preservation potential of Cribroelphidium poeyanum and Haynesina germanica in the northern and central portions of Chincoteague Bay, as indicated by seasonal pH data. Similarly, the sandy back-barrier lagoonal sites exhibited relatively low densities, potentially a result of dissolution or mechanical destruction.

","language":"English","publisher":"Cushman Foundation for Foraminiferal Research","doi":"10.2113/gsjfr.48.3.223","usgsCitation":"Ellis, A.M., Shaw, J., Osterman, L.E., and Smith, C.G., 2018, The foraminifera of Chincoteague Bay, Assateague Island, and the surrounding areas: A regional distribution study: Journal of Foraminiferal Research, v. 48, no. 3, p. 223-240, https://doi.org/10.2113/gsjfr.48.3.223.","productDescription":"18 p.","startPage":"223","endPage":"240","ipdsId":"IP-089998","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":360253,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Assateague Island, Chincoteague Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.52825927734375,\n 37.84883250647402\n ],\n [\n -75.07919311523438,\n 37.84883250647402\n ],\n [\n -75.07919311523438,\n 38.31795595794451\n ],\n [\n -75.52825927734375,\n 38.31795595794451\n ],\n [\n -75.52825927734375,\n 37.84883250647402\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c137dd5e4b006c4f851489a","contributors":{"authors":[{"text":"Ellis, Alisha M. 0000-0002-1785-020X aellis@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-020X","contributorId":192957,"corporation":false,"usgs":true,"family":"Ellis","given":"Alisha","email":"aellis@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaw, Jaimie E.","contributorId":211432,"corporation":false,"usgs":false,"family":"Shaw","given":"Jaimie E.","affiliations":[{"id":25340,"text":"Cherokee Nation Technologies","active":true,"usgs":false}],"preferred":false,"id":754048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osterman, Lisa E. osterman@usgs.gov","contributorId":3058,"corporation":false,"usgs":true,"family":"Osterman","given":"Lisa","email":"osterman@usgs.gov","middleInitial":"E.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754192,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198662,"text":"70198662 - 2018 - On the robustness of N‐mixture models","interactions":[],"lastModifiedDate":"2018-08-14T14:01:30","indexId":"70198662","displayToPublicDate":"2018-07-02T14:01:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"On the robustness of N‐mixture models","docAbstract":"

N‐mixture models provide an appealing alternative to mark–recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the N‐mixture models: inference is very sensitive to the model's assumptions. We consider the effects of three violations of assumptions that might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness‐of‐fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2362","usgsCitation":"Link, W.A., Schofield, M.R., Barker, R.J., and Sauer, J.R., 2018, On the robustness of N‐mixture models: Ecology, v. 99, no. 7, p. 1547-1551, https://doi.org/10.1002/ecy.2362.","productDescription":"5 p.","startPage":"1547","endPage":"1551","ipdsId":"IP-092400","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":356444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-06","publicationStatus":"PW","scienceBaseUri":"5b98a2a2e4b0702d0e842f9a","contributors":{"authors":[{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":742385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schofield, Matthew R.","contributorId":207010,"corporation":false,"usgs":false,"family":"Schofield","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":37428,"text":"Dept of Math/Stat, University of Otago, New Zealand","active":true,"usgs":false}],"preferred":false,"id":742386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barker, Richard J.","contributorId":207011,"corporation":false,"usgs":false,"family":"Barker","given":"Richard","email":"","middleInitial":"J.","affiliations":[{"id":37428,"text":"Dept of Math/Stat, University of Otago, New Zealand","active":true,"usgs":false}],"preferred":false,"id":742387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":742388,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199447,"text":"70199447 - 2018 - Inferring presence of the western toad (Anaxyrus boreas) species complex using environmental DNA","interactions":[],"lastModifiedDate":"2018-09-18T13:28:26","indexId":"70199447","displayToPublicDate":"2018-07-02T13:28:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Inferring presence of the western toad (Anaxyrus boreas) species complex using environmental DNA","title":"Inferring presence of the western toad (Anaxyrus boreas) species complex using environmental DNA","docAbstract":"

Western toads (species complex comprised of Anaxyrus boreas, A. canorus, A. exsul, and A. nelsoni) are widely distributed in the western United States but are declining, particularly in the southeastern extent of their range. The subspecies A. b. boreas is listed as a Species of Greatest Conservation Need in New Mexico, Colorado, Utah, and Wyoming. Reliable and sensitive methods for delineating distributions of western toads are critical for monitoring the status of the species and prioritizing conservation efforts. We developed two qPCR assays for detecting western toad DNA in environmental DNA samples. Both markers efficiently and reliably detect low concentrations of western toad DNA across their range in the conterminous U. S. without detecting non-target, sympatric species. To determine the optimal annual sampling period, we then tested these markers using repeated sampling in ponds where western toads were known to be present. Quantities of collected eDNA varied widely across samples, but sample-level detections across sites exceeded 80% for June sampling. In the later summer, detection dropped off sharply with only a single detection in the ten samples collected throughout August.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2018.e00438","usgsCitation":"Franklin, T.W., Dysthe, J.C., Golden, M., McKelvey, K.S., Hossack, B.R., Carim, K.J., Tait, C., Young, M.K., and Schwartz, M.K., 2018, Inferring presence of the western toad (Anaxyrus boreas) species complex using environmental DNA: Global Ecology and Conservation, v. 15, p. 1-9, https://doi.org/10.1016/j.gecco.2018.e00438.","productDescription":"e00438; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-096364","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2018.e00438","text":"Publisher Index Page"},{"id":357435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02fd7e4b0fc368eb5398d","contributors":{"authors":[{"text":"Franklin, Thomas W.","contributorId":207966,"corporation":false,"usgs":false,"family":"Franklin","given":"Thomas","email":"","middleInitial":"W.","affiliations":[{"id":37672,"text":"1United States Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, 800 East Beckwith Ave., Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":745359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dysthe, Joseph C.","contributorId":207967,"corporation":false,"usgs":false,"family":"Dysthe","given":"Joseph","email":"","middleInitial":"C.","affiliations":[{"id":37672,"text":"1United States Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, 800 East Beckwith Ave., Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":745360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golden, Michael","contributorId":207968,"corporation":false,"usgs":false,"family":"Golden","given":"Michael","email":"","affiliations":[{"id":37673,"text":"United States Department of Agriculture, Forest Service, Dixie National Forest, 1789 N Wedgewood Ln, Cedar City UT","active":true,"usgs":false}],"preferred":false,"id":745361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKelvey, Kevin S.","contributorId":207969,"corporation":false,"usgs":false,"family":"McKelvey","given":"Kevin","email":"","middleInitial":"S.","affiliations":[{"id":37674,"text":"United States Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, 800 East Beckwith Ave., Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":745362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":745358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carim, Kellie J.","contributorId":207971,"corporation":false,"usgs":false,"family":"Carim","given":"Kellie","email":"","middleInitial":"J.","affiliations":[{"id":37672,"text":"1United States Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, 800 East Beckwith Ave., Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":745365,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tait, Cynthia","contributorId":207970,"corporation":false,"usgs":false,"family":"Tait","given":"Cynthia","email":"","affiliations":[{"id":37675,"text":"4United States Department of Agriculture, Forest Service, Intermountain Region, 324 25th Street, Ogden, UT","active":true,"usgs":false}],"preferred":false,"id":745364,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Young, Michael K.","contributorId":177836,"corporation":false,"usgs":false,"family":"Young","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":745363,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schwartz, Michael K.","contributorId":199035,"corporation":false,"usgs":false,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":745366,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198336,"text":"70198336 - 2018 - Duck nest depredation, predator behavior, and female response using video","interactions":[],"lastModifiedDate":"2018-07-31T08:58:55","indexId":"70198336","displayToPublicDate":"2018-07-02T08:58:49","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Duck nest depredation, predator behavior, and female response using video","docAbstract":"

Depredation plays an important role in determining duck nest success and predator and female duck behavior during nest depredation can influence nest fate. We examined depredation of mallard (Anas platyrhynchos) and gadwall (A. strepera) nests in Suisun Marsh, California, USA, in 2015–2016 with continuous infrared video monitoring to identify nest predators and characterize predator and female duck behavior during depredation events. We recorded predators at 44% of 147 nests monitored. Raccoons (Procyon lotor) were the most frequent predator observed at nests (40% of nests visited and 53% of depredated eggs) followed by striped skunks (Mephitis mephitis; 27% and 27%), coyotes (Canis latrans; 4% and 9%), common ravens (Corvus corax; 4% and 9%), gopher snakes (Pituophis catenifer catenifer; 19% and 0%), and western yellow‐bellied racers (Coluber constrictor mormon; 1% and 0%). The number of eggs depredated per depredation bout varied among predators (raccoons: 7.3 eggs; skunks: 2.5; coyotes: 7.4; ravens: 7.7; and snakes: 0.0). Mammal depredation occurred between 1600 and 0400, whereas snakes and ravens were observed at nests during the day (snakes: 1000–2100; ravens: 1700). Females flushed from nests immediately before predator arrival (\"urn:x-wiley:14381656:media:jwmg21444:jwmg21444-math-0001\" = 29.0 ± 16.6 [SD] sec), and this timing did not vary among predators. However, the length of nest depredation bouts varied among predators. Nest visits by gopher snakes were longer (18.6 ± 19.4 min) than depredation bouts by other predators (12.3 ± 10.7 min), but snakes did not successfully consume any eggs. Females took more time to return to nests when nests were depredated by raccoons (239 ± 137 min), whereas females returned more quickly when nests were visited by skunks (81 ± 163 min) or gopher snakes (15 ± 128 min). Partial clutch depredation occurred at 15% of depredated nests, but only 23% of partially depredated nests successfully hatched ≥1 egg. Our results indicate that predator type and behavior can influence female behavior and nest fate, and that management actions that reduce the effectiveness of raccoons and skunks encountering waterfowl nests may benefit these nesting populations.

","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21444","usgsCitation":"Croston, R., Ackerman, J., Herzog, M.P., Kohl, J.D., Hartman, C.A., Peterson, S.H., Overton, C.T., Feldheim, C.L., and Casazza, M.L., 2018, Duck nest depredation, predator behavior, and female response using video: Journal of Wildlife Management, v. 82, no. 5, p. 1014-1025, https://doi.org/10.1002/jwmg.21444.","productDescription":"12 p.","startPage":"1014","endPage":"1025","ipdsId":"IP-088484","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":356018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-08","publicationStatus":"PW","scienceBaseUri":"5b6fc418e4b0f5d57878e9e5","contributors":{"authors":[{"text":"Croston, Rebecca 0000-0003-4696-0878","orcid":"https://orcid.org/0000-0003-4696-0878","contributorId":206560,"corporation":false,"usgs":true,"family":"Croston","given":"Rebecca","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":741092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kohl, Jeffrey D. 0000-0003-0921-7460","orcid":"https://orcid.org/0000-0003-0921-7460","contributorId":206562,"corporation":false,"usgs":true,"family":"Kohl","given":"Jeffrey","email":"","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131109,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":741097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741098,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741099,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Feldheim, Cliff L.","contributorId":206561,"corporation":false,"usgs":false,"family":"Feldheim","given":"Cliff","email":"","middleInitial":"L.","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":741095,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741100,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70259745,"text":"70259745 - 2018 - Alaska Volcano Observatory alert and forecasting timeliness: 1989–2017","interactions":[],"lastModifiedDate":"2024-10-23T11:37:30.603843","indexId":"70259745","displayToPublicDate":"2018-07-02T06:34:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17169,"text":"Frontiers in Earth Science - Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Alaska Volcano Observatory alert and forecasting timeliness: 1989–2017","docAbstract":"

The Alaska Volcano Observatory (AVO) monitors volcanoes in Alaska and issues notifications and warnings of volcanic unrest and eruption. We evaluate the timeliness and accuracy of eruption forecasts for 53 eruptions at 20 volcanoes, beginning with Mount Redoubt's 1989–1990 eruption. Successful forecasts are defined as those where AVO issued a formal warning before eruption onset. These warning notifications are now part of AVO's Aviation Color Code and Volcanic Alert Level. This analysis considers only the start of an eruption, although many eruptions have multiple phases of activity. For the 21 eruptions at volcanoes with functioning local seismic networks, AVO has high forecasting success at volcanoes with: >15 years repose intervals and magmatic eruptions (4 out of 4, 100%); or larger eruptions (Volcanic Explosivity Index (VEI) 3 or greater; 6 out of 10, 60%). Therefore, AVO successfully forecast all four monitored, longer-repose period, VEI 3+ eruptions: Redoubt 1989–1990 and 2009, Spurr 1992, and Augustine 2005–2006. For volcanoes with functioning seismic monitoring networks, success rates are lower for: volcanoes with shorter repose periods (3 out of 16, 19%); more mafic compositions (3 out of 18, 17%); or smaller eruption size (VEI 2 or less, 1 out of 11, 9%). These eruptions (Okmok, Pavlof, Veniaminof, and Shishaldin) often lack detectable precursory signals. For 32 eruptions at volcanoes without functioning local seismic networks, the forecasting success rate is much lower (2, 6%; Kasatochi 2008 and Shishaldin 2014). For remote volcanoes where the main hazard is to aviation, rapid detection is a goal in the absence of in situ monitoring. Eruption detection has improved in recent years, shown by a decrease in the time between eruption onset and notification. Even limited seismic monitoring can detect precursory activity at volcanoes with certain characteristics (intermediate composition, longer repose times, larger eruptions), but difficulty persists in detecting subtle precursory activity at frequently active volcanoes with more mafic compositions. This suggests that volcano-specific characteristics should be considered when designing monitoring programs and evaluating forecasting success. More proximally-located sensors and data types are likely needed to forecast eruptive activity at frequently-active, more mafic volcanoes that generally produce smaller eruptions.

","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2018.00086","usgsCitation":"Cameron, C., Prejean, S., Coombs, M.L., Wallace, K.L., Power, J., and Roman, D., 2018, Alaska Volcano Observatory alert and forecasting timeliness: 1989–2017: Frontiers in Earth Science - Volcanology, v. 6, 86, 16 p., https://doi.org/10.3389/feart.2018.00086.","productDescription":"86, 16 p.","ipdsId":"IP-095805","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468608,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2018.00086","text":"Publisher Index Page"},{"id":463113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.0050499667423,\n 50.8246967104881\n ],\n [\n -160.54801871674235,\n 53.62315970952906\n ],\n [\n -146.83708121674246,\n 59.69382332205734\n ],\n [\n -148.50700309174243,\n 62.16910742042111\n ],\n [\n -153.25309684174235,\n 61.714365562658\n ],\n [\n -159.22965934174232,\n 58.79497961948812\n ],\n [\n -162.0421593417424,\n 57.21189226650853\n ],\n [\n -172.0616905917424,\n 54.50005217383722\n ],\n [\n -179.53239371674232,\n 53.30923541769238\n ],\n [\n -183.48747184174235,\n 52.674403054105795\n ],\n [\n -183.48747184174235,\n 51.70458578993842\n ],\n [\n -182.2570030917423,\n 51.04624916082764\n ],\n [\n -179.0050499667423,\n 50.8246967104881\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Cameron, Cheryl","contributorId":345428,"corporation":false,"usgs":false,"family":"Cameron","given":"Cheryl","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":916578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prejean, Stephanie 0000-0003-0510-1989 sprejean@usgs.gov","orcid":"https://orcid.org/0000-0003-0510-1989","contributorId":172404,"corporation":false,"usgs":true,"family":"Prejean","given":"Stephanie","email":"sprejean@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916581,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Power, John 0000-0002-7233-4398","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":215240,"corporation":false,"usgs":true,"family":"Power","given":"John","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916582,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roman, Diana C.","contributorId":345429,"corporation":false,"usgs":false,"family":"Roman","given":"Diana C.","affiliations":[{"id":30217,"text":"Carnegie Institution for Science","active":true,"usgs":false}],"preferred":false,"id":916583,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197978,"text":"70197978 - 2018 - Female hatchling American kestrels have a larger hippocampus than males: A link with sexual size dimorphism?","interactions":[],"lastModifiedDate":"2018-07-02T11:27:13","indexId":"70197978","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5717,"text":"Behavioural Brain Research","active":true,"publicationSubtype":{"id":10}},"title":"Female hatchling American kestrels have a larger hippocampus than males: A link with sexual size dimorphism?","docAbstract":"

The brain and underlying cognition may vary adaptively according to an organism’s ecology. As with all raptor species, adult American kestrels (Falco sparverius) are sexually dimorphic with females being larger than males. Related to this sexual dimorphism, kestrels display sex differences in hunting and migration, with females ranging more widely than males, suggesting possible sex differences in spatial cognition. However, hippocampus volume, the brain region responsible for spatial cognition, has not been investigated in raptors. Here, we measured hippocampus and telencephalon volumes in American kestrel hatchlings. Female hatchlings had a significantly larger hippocampus relative to the telencephalon and brain weight than males (∼12% larger), although telencephalon volume relative to brain weight and body size was similar between the sexes. The magnitude of this hippocampal sex difference is similar to that reported between male and female polygynous Microtus voles and migratory and non-migratory subspecies of Zonotrichia sparrows. Future research should determine if this sex difference in relative hippocampus volume of hatchling kestrels persists into adulthood and if similar patterns exist in other raptor species, thus potentially linking sex differences in the brain to sex differences of space use of adults in the wild.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.bbr.2018.04.037","usgsCitation":"Guigueno, M., Karouna-Renier, N., Henry, P.F., Head, J.A., Peters, L.E., Palace, V.P., Letcher, R.J., and Fernie, K.J., 2018, Female hatchling American kestrels have a larger hippocampus than males: A link with sexual size dimorphism?: Behavioural Brain Research, v. 349, p. 98-101, https://doi.org/10.1016/j.bbr.2018.04.037.","productDescription":"4 p.","startPage":"98","endPage":"101","ipdsId":"IP-092884","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468610,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.bbr.2018.04.037","text":"Publisher Index Page"},{"id":355450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"349","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e546e4b060350a15d087","contributors":{"authors":[{"text":"Guigueno, Melanie F.","contributorId":206107,"corporation":false,"usgs":false,"family":"Guigueno","given":"Melanie F.","affiliations":[{"id":37248,"text":"Environment & Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":739437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henry, Paula F. P. 0000-0002-7601-5546 phenry@usgs.gov","orcid":"https://orcid.org/0000-0002-7601-5546","contributorId":4485,"corporation":false,"usgs":true,"family":"Henry","given":"Paula","email":"phenry@usgs.gov","middleInitial":"F. P.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Head, Jessica A.","contributorId":206108,"corporation":false,"usgs":false,"family":"Head","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":739441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peters, Lisa E.","contributorId":176211,"corporation":false,"usgs":false,"family":"Peters","given":"Lisa","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":739442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Palace, Vince P.","contributorId":176210,"corporation":false,"usgs":false,"family":"Palace","given":"Vince","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":739443,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Letcher, Robert J.","contributorId":176209,"corporation":false,"usgs":false,"family":"Letcher","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":739439,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fernie, Kimberly J.","contributorId":176208,"corporation":false,"usgs":false,"family":"Fernie","given":"Kimberly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":739438,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70197967,"text":"ofr20181105 - 2018 - Status of selenium in south San Francisco Bay—A basis for modeling potential guidelines to meet National tissue criteria for fish and a proposed wildlife criterion for birds","interactions":[],"lastModifiedDate":"2018-07-02T16:36:31","indexId":"ofr20181105","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1105","title":"Status of selenium in south San Francisco Bay—A basis for modeling potential guidelines to meet National tissue criteria for fish and a proposed wildlife criterion for birds","docAbstract":"
The U.S. Environmental Protection Agency (EPA) proposed Aquatic Life and AquaticDependent Wildlife Criteria for Selenium (Se) in California’s San Francisco Bay and Delta (Bay-Delta) in June 2016. Here we apply the same modeling methodology—Ecosystem-Scale Selenium Modeling— to an assessment of conditions and documentation of food webs of south San Francisco Bay (South Bay) as an exploratory framework in support of site-specific Se criteria development. Long-term datasets contribute to the basis for modeling, especially the 21-year collection of the clam Macoma petalum from a mudflat at the lower end of South Bay (Lower South Bay). As such, this is a working document that may serve as a basis to establish an understanding of the specifics of Se biodynamics within the estuary and reduce uncertainties about how to protect it. This approach brings together the main factors involved in toxicity: likelihood of high exposure, inherent species sensitivity, and the behavioral ecology (for example, demographics and life history) of an organism in terms of susceptibility to a reproductive toxicant. Species sensitivity is represented here by use of the EPA’s current national tissue Se criterion for fish or that proposed to protect the eggs of aquatic birds for the Bay-Delta (U.S. Environmental Protection Agency, 2016a, 2016b, 2016c). This report also strives to bring together findings and field data across a body of literature for South Bay to provide an integrative assessment.

We find an assemblage of site-specific conditions that could affect modeling:
associated urban processes such as discharges from municipal wastewater treatment plants and drainage from mercury (Hg) mining and limestone extraction are sources of Se that characterize the Lower South Bay as the location of interest for Se exposure; • hydrodynamics are lagoon-like (that is, less flushing), which sustains elevated nutrients and phytoplankton blooms; • managed freshwater sources are a major hydrodynamic component; • birds, in addition to fish, are prominent predators in South Bay; • wetland restoration has recently intervened to play a significant role in ecosystem function that may include uptake of both Hg and Se; • the dietary food web of surficial-sediment to M. petalum is important because of the dominance of this clam species and its elevated Se bioaccumulation potential compared to other local food webs; and 2 • maximal Se concentrations may be limited by transitory or annually renewed food webs (for example, migratory shorebirds and decimation of clams from marshes). We also find that the constructed mechanistic model: • spatially connects to the Palo Alto mudflat site because of data availability; • accurately predicts average observed Se concentrations in M. petalum and in predator species of fish and birds; and • is able to bracket a range of potential protective water-column Se concentrations specific to predator species based on the EPA’s national Se criterion for whole-body fish tissue and a proposed site-specific criterion for bird eggs in the Bay-Delta.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181105","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Luoma, S.N., and Presser, T.S., 2018, Status of selenium in south San Francisco Bay—A basis for modeling potential guidelines to meet National tissue criteria for fish and a proposed wildlife criterion for birds: U.S. Geological Survey Open-File Report 2018–1105, 75 p., https://doi.org/10.3133/ofr20181105.","productDescription":"v, 75 p.","numberOfPages":"84","onlineOnly":"Y","ipdsId":"IP-099162","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":355438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1105/coverthb.jpg"},{"id":355452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1105/ofr20181105.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1105"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.13706970214844,\n 37.40725549559874\n ],\n [\n -121.91322326660156,\n 37.40725549559874\n ],\n [\n -121.91322326660156,\n 37.52225246712464\n ],\n [\n -122.13706970214844,\n 37.52225246712464\n ],\n [\n -122.13706970214844,\n 37.40725549559874\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

National Research Program
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-07-02","noUsgsAuthors":false,"publicationDate":"2018-07-02","publicationStatus":"PW","scienceBaseUri":"5b46e547e4b060350a15d08f","contributors":{"authors":[{"text":"Luoma, Samuel N. 0000-0001-5443-5091","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":205506,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":739414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Presser, Theresa S. 0000-0001-5643-0147 tpresser@usgs.gov","orcid":"https://orcid.org/0000-0001-5643-0147","contributorId":2467,"corporation":false,"usgs":true,"family":"Presser","given":"Theresa","email":"tpresser@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":739413,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197974,"text":"70197974 - 2018 - Using geologic structures to constrain constitutive laws not accessible in the laboratory","interactions":[],"lastModifiedDate":"2019-08-15T11:29:27","indexId":"70197974","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2468,"text":"Journal of Structural Geology","active":true,"publicationSubtype":{"id":10}},"title":"Using geologic structures to constrain constitutive laws not accessible in the laboratory","docAbstract":"

In this essay, we explore a central problem of structural geology today, and in the foreseeable future, which is the determination of constitutive laws governing rock deformation to produce geologic structures. Although laboratory experiments provide much needed data and insights about constitutive laws, these experiments cannot cover the range of conditions and compositions relevant to the formation of geologic structures. We advocate that structural geologists address this limitation by interpreting natural experiments, documented with field and microstructural data, using continuum mechanical models that enable the deduction of constitutive laws. To put this procedure into a historical context, we review the founding of structural geology by James Hutton in the late 18th century, and the seminal contributions to continuum mechanics from Newton to Cauchy that provide the tools to model geologic structures. The procedure is illustrated with two examples drawn from recent and on-going field investigations of crustal and mantle lithologies. We conclude by pointing to future research opportunities that will engage structural geologists in the pursuit of constitutive laws during the 21st century.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jsg.2018.06.006","usgsCitation":"Nevitt, J., Warren, J.M., Kumamoto, K.M., and Pollard, D.D., 2018, Using geologic structures to constrain constitutive laws not accessible in the laboratory: Journal of Structural Geology, v. 125, p. 55-63, https://doi.org/10.1016/j.jsg.2018.06.006.","productDescription":"9 p.","startPage":"55","endPage":"63","ipdsId":"IP-094175","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":355443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e547e4b060350a15d08d","contributors":{"authors":[{"text":"Nevitt, Johanna 0000-0003-3819-1773 jnevitt@usgs.gov","orcid":"https://orcid.org/0000-0003-3819-1773","contributorId":198144,"corporation":false,"usgs":true,"family":"Nevitt","given":"Johanna","email":"jnevitt@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":739409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warren, Jessica M. 0000-0002-4046-4200","orcid":"https://orcid.org/0000-0002-4046-4200","contributorId":206098,"corporation":false,"usgs":false,"family":"Warren","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":739410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumamoto, Kathryn M.","contributorId":206099,"corporation":false,"usgs":false,"family":"Kumamoto","given":"Kathryn","email":"","middleInitial":"M.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":739411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pollard, David D.","contributorId":206100,"corporation":false,"usgs":false,"family":"Pollard","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":739412,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198027,"text":"70198027 - 2018 - Wildlife management is science based: Myth or reality?","interactions":[],"lastModifiedDate":"2018-07-16T10:54:44","indexId":"70198027","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3587,"text":"The Wildlife Professional","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife management is science based: Myth or reality?","docAbstract":"

In the January/February issue of The Wildlife Professional, a group of wildlife leaders discussed what they considered \"myths\" in wildlife management and invited other wildlife professionals to contribute their favorites. Here, five wildlife professionals take up that theme with their discussions of the scientific basis of wildlife management.

","language":"English","publisher":"The Wildlife Society","usgsCitation":"Decker, D.J., Organ, J.F., Forstchen, A., Schiavone, M.V., and Fuller, A.K., 2018, Wildlife management is science based: Myth or reality?: The Wildlife Professional, no. July/August 2018, p. 30-32.","productDescription":"3 p.","startPage":"30","endPage":"32","ipdsId":"IP-097254","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":355629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"July/August 2018","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e546e4b060350a15d085","contributors":{"authors":[{"text":"Decker, Daniel J.","contributorId":166906,"corporation":false,"usgs":false,"family":"Decker","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":739968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Organ, John F. 0000-0002-0959-0639 jorgan@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-0639","contributorId":152568,"corporation":false,"usgs":true,"family":"Organ","given":"John","email":"jorgan@usgs.gov","middleInitial":"F.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":739969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forstchen, Ann","contributorId":166904,"corporation":false,"usgs":false,"family":"Forstchen","given":"Ann","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":739970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schiavone, Michael V.","contributorId":30064,"corporation":false,"usgs":false,"family":"Schiavone","given":"Michael","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":739971,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":740026,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197236,"text":"sir20185070 - 2018 - Characterization of peak streamflows and flood inundation of selected areas in southeastern Texas and southwestern Louisiana from the August and September 2017 flood resulting from Hurricane Harvey","interactions":[],"lastModifiedDate":"2018-07-13T09:35:54","indexId":"sir20185070","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5070","title":"Characterization of peak streamflows and flood inundation of selected areas in southeastern Texas and southwestern Louisiana from the August and September 2017 flood resulting from Hurricane Harvey","docAbstract":"

Hurricane Harvey made landfall near Rockport, Texas, on August 25, 2017, as a Category 4 hurricane with wind gusts exceeding 150 miles per hour. As Harvey moved inland, the forward motion of the storm slowed down and produced tremendous rainfall amounts over southeastern Texas, with 8-day rainfall amounts exceeding 60 inches in some locations, which is about 15 inches more than average annual amounts of rainfall for eastern Texas and the Texas coast. Historic flooding occurred in Texas as a result of the widespread, heavy rainfall; wind and flood damages were estimated to be $125 billion, and the storm resulted in at least 68 direct fatalities.

In the immediate aftermath of the Harvey-related flood event, the U.S. Geological Survey (USGS) and the Federal Emergency Management Agency initiated a cooperative study to evaluate the magnitude of the flood, determine the probability of occurrence, and map the extent of the flood in Texas. Seventy-four USGS streamflow-gaging stations in Texas with at least 15 years of record and no large data gaps in the period of record had a 2017 annual peak streamflow related to Harvey ranking in the top five of all annual peaks for each given station. New peaks of record streamflow were recorded at 40 of the 74 USGS streamflow-gaging stations. The number of years of peak streamflow record for the 74 analyzed streamflow-gaging stations ranged from 18 to 105, with a mean number of 55 years. The annual exceedance probability estimates for the analyzed streamflow-gaging stations ranged from less than 0.2 to 14.0 percent. USGS field crews surveyed 2,123 high-water marks to obtain water-surface elevations, in feet above the North American Vertical Datum of 1988. In some locations, several water-surface elevations were averaged to obtain 1 water-surface elevation, resulting in 1,258 water-surface elevations. Some of these high-water marks were used, along with peak-stage data from USGS streamflow-gaging stations, to create 19 inundation maps to document the areal extent of the maximum depth of the flooding. Digital datasets of the inundation area, modeling boundary, water-depth rasters, and final map products are available from the USGS data release associated with this report (https://doi.org/10.5066/F7VH5N3N).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185070","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Watson, K.M., Harwell, G.R., Wallace, D.S., Welborn, T.L., Stengel, V.G., and McDowell, J.S., 2018, Characterization of peak streamflows and flood inundation of selected areas in southeastern Texas and southwestern Louisiana from the August and September 2017 flood resulting from Hurricane Harvey: U.S. Geological Survey Scientific Investigations Report 2018–5070, 44 p., https://doi.org/10.3133/sir20185070.","productDescription":"Report: viii, 44 p.; Data Release","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095268","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":355276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5070/sir20185070.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5070"},{"id":355275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5070/coverthb.jpg"},{"id":355277,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VH5N3N","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data used to characterize peak streamflows and flood inundation resulting from Hurricane Harvey of selected areas in southeastern Texas and southwestern Louisiana, August–September 2017"}],"country":"United States","state":"Arkansas, Louisiana, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.00830078125,\n 27.332735136859146\n ],\n [\n -92.7685546875,\n 27.332735136859146\n ],\n [\n -92.7685546875,\n 33.358061612778876\n ],\n [\n -101.00830078125,\n 33.358061612778876\n ],\n [\n -101.00830078125,\n 27.332735136859146\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2018-07-02","noUsgsAuthors":false,"publicationDate":"2018-07-02","publicationStatus":"PW","scienceBaseUri":"5b46e547e4b060350a15d097","contributors":{"authors":[{"text":"Watson, Kara M. 0000-0002-2685-0260 kmwatson@usgs.gov","orcid":"https://orcid.org/0000-0002-2685-0260","contributorId":2134,"corporation":false,"usgs":true,"family":"Watson","given":"Kara","email":"kmwatson@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harwell, Glenn R. 0000-0003-4265-2296","orcid":"https://orcid.org/0000-0003-4265-2296","contributorId":205197,"corporation":false,"usgs":true,"family":"Harwell","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallace, David S. 0000-0002-9134-8197","orcid":"https://orcid.org/0000-0002-9134-8197","contributorId":205198,"corporation":false,"usgs":true,"family":"Wallace","given":"David S.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736326,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welborn, Toby L. 0000-0003-4839-2405 tlwelbor@usgs.gov","orcid":"https://orcid.org/0000-0003-4839-2405","contributorId":2295,"corporation":false,"usgs":true,"family":"Welborn","given":"Toby","email":"tlwelbor@usgs.gov","middleInitial":"L.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stengel, Victoria G. 0000-0003-0481-3159 vstengel@usgs.gov","orcid":"https://orcid.org/0000-0003-0481-3159","contributorId":5932,"corporation":false,"usgs":true,"family":"Stengel","given":"Victoria","email":"vstengel@usgs.gov","middleInitial":"G.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736328,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDowell, Jeremy S. 0000-0002-8132-9806","orcid":"https://orcid.org/0000-0002-8132-9806","contributorId":205199,"corporation":false,"usgs":true,"family":"McDowell","given":"Jeremy S.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":736329,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198075,"text":"70198075 - 2018 - Tropical wetlands in the Anthropocene: The critical role of wet-dry cycles","interactions":[],"lastModifiedDate":"2018-07-16T10:51:28","indexId":"70198075","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3427,"text":"Solutions Journal","active":true,"publicationSubtype":{"id":10}},"title":"Tropical wetlands in the Anthropocene: The critical role of wet-dry cycles","docAbstract":"In the face of climate change and increasing human water demands for agriculture, industry, and cities, the fate of wetland ecosystems in tropical wet-dry climates is threatened. To maximize biodiversity and ecological resilience, the value of the ecosystem services provided by tropical wetlands can be incorporated into regional land use and water management decisions. Environmental planners and resource managers can work to protect both the “dry” and “wet” phases of the wet-dry hydrologic cycles. These cycles have shaped and maintained these ecosystems in the past and they can be used to maximize biodiversity and resilience in the future.","language":"English","publisher":"Solutions Journal","usgsCitation":"Osland, M.J., and Middleton, B.A., 2018, Tropical wetlands in the Anthropocene: The critical role of wet-dry cycles: Solutions Journal, v. 9, no. 3, 14 p.","productDescription":"14 p.","ipdsId":"IP-096321","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":355661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355632,"type":{"id":15,"text":"Index Page"},"url":"https://www.thesolutionsjournal.com/article/tropical-wetlands-anthropocene-critical-role-wet-dry-cycles/"}],"volume":"9","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc419e4b0f5d57878e9e9","contributors":{"authors":[{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","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":739913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":739914,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198072,"text":"70198072 - 2018 - Managing conflicts in the River of Grass","interactions":[],"lastModifiedDate":"2019-12-21T09:09:49","indexId":"70198072","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3427,"text":"Solutions Journal","active":true,"publicationSubtype":{"id":10}},"title":"Managing conflicts in the River of Grass","docAbstract":"

Chances are, you would not pack up and move to a new home without first researching the neighborhood, reviewing your finances, and maybe investigating schools nearby. Similarly, you would not buy the first car you find on a magazine cover without first reviewing the technical specifications, exploring your options, and perhaps taking a test drive. Even when making simple purchases online, you probably shop around, check out customer reviews, and scan seller feedback ratings.

Rarely do we act on impulse alone when faced with decisions. Rather, we typically start with a vision of what we want before gathering the necessary information, weighing our options, prioritizing our values, and evaluating possible tradeoffs. In making choices that range from lighthearted to life-changing, we use this commonsense strategy every day of our lives.

Environmental decision-making is no different. For decades, natural resource managers faced with complicated problems have made decisions by breaking them into smaller components that are easier to approach. And like our day-to day decisions, the process is ideally guided by a shared vision of the future. However, it can become complicated when multiple, seemingly disparate views on what the future should hold emerge. As Lewis Carroll once wrote, “If you don’t know where you are going, any road will get you there.”

Divining a vision of the future for the Florida Everglades and making supporting decisions is a complex undertaking. But unlike Alice thrust through the looking glass, we have tools and techniques to help us make sense of it all. The application of tools to help decision-making can move us closer to the successful restoration of this imperiled landscape.

","language":"English","publisher":"Solutions","usgsCitation":"Romanach, S.S., Beerens, J.M., Perez, L., Haider, S., and Pearlstine, L.G., 2018, Managing conflicts in the River of Grass: Solutions Journal, v. 9, no. 3, 8 p.","productDescription":"8 p.","ipdsId":"IP-087571","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":355655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355627,"type":{"id":15,"text":"Index Page"},"url":"https://www.thesolutionsjournal.com/article/managing-conflicts-river-grass/"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.78771972656249,\n 25.06072125231416\n ],\n [\n -80.3485107421875,\n 25.06072125231416\n ],\n [\n -80.3485107421875,\n 26.185018250078308\n ],\n [\n -81.78771972656249,\n 26.185018250078308\n ],\n [\n -81.78771972656249,\n 25.06072125231416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc41ae4b0f5d57878e9eb","contributors":{"authors":[{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@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":739901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beerens, James M. 0000-0001-8143-916X jbeerens@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":143722,"corporation":false,"usgs":true,"family":"Beerens","given":"James","email":"jbeerens@usgs.gov","middleInitial":"M.","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":739902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perez, Larry","contributorId":206254,"corporation":false,"usgs":false,"family":"Perez","given":"Larry","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":739905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haider, Saira M. 0000-0001-9306-3454","orcid":"https://orcid.org/0000-0001-9306-3454","contributorId":206253,"corporation":false,"usgs":true,"family":"Haider","given":"Saira","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":739903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearlstine, Leonard G.","contributorId":34751,"corporation":false,"usgs":false,"family":"Pearlstine","given":"Leonard","email":"","middleInitial":"G.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":739904,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197977,"text":"70197977 - 2018 - Projected 21st century coastal flooding in the Southern California Bight. Part 2: Tools for assessing climate change-driven coastal hazards and socio-economic impacts","interactions":[],"lastModifiedDate":"2018-07-02T11:22:21","indexId":"70197977","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Projected 21st century coastal flooding in the Southern California Bight. Part 2: Tools for assessing climate change-driven coastal hazards and socio-economic impacts","docAbstract":"

This paper is the second of two that describes the Coastal Storm Modeling System (CoSMoS) approach for quantifying physical hazards and socio-economic hazard exposure in coastal zones affected by sea-level rise and changing coastal storms. The modelling approach, presented in Part 1, downscales atmospheric global-scale projections to local scale coastal flood impacts by deterministically computing the combined hazards of sea-level rise, waves, storm surges, astronomic tides, fluvial discharges, and changes in shoreline positions. The method is demonstrated through an application to Southern California, United States, where the shoreline is a mix of bluffs, beaches, highly managed coastal communities, and infrastructure of high economic value. Results show that inclusion of 100-year projected coastal storms will increase flooding by 9–350% (an additional average 53.0 ± 16.0 km2) in addition to a 25–500 cm sea-level rise. The greater flooding extents translate to a 55–110% increase in residential impact and a 40–90% increase in building replacement costs. To communicate hazards and ranges in socio-economic exposures to these hazards, a set of tools were collaboratively designed and tested with stakeholders and policy makers; these tools consist of two web-based mapping and analytic applications as well as virtual reality visualizations. To reach a larger audience and enhance usability of the data, outreach and engagement included workshop-style trainings for targeted end-users and innovative applications of the virtual reality visualizations.

","language":"English","publisher":"MDPI","doi":"10.3390/jmse6030076","usgsCitation":"Erikson, L.H., Barnard, P., O'Neill, A., Wood, N.J., Jones, J.M., Finzi Hart, J., Vitousek, S., Limber, P.W., Hayden, M., Fitzgibbon, M., Lovering, J., and Foxgrover, A.C., 2018, Projected 21st century coastal flooding in the Southern California Bight. Part 2: Tools for assessing climate change-driven coastal hazards and socio-economic impacts: Journal of Marine Science and Engineering, v. 6, no. 3, p. 1-19, https://doi.org/10.3390/jmse6030076.","productDescription":"Article 76; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-098756","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468609,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse6030076","text":"Publisher Index Page"},{"id":355449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.860595703125,\n 32.52828936482526\n ],\n [\n -117.037353515625,\n 32.52828936482526\n ],\n [\n -117.037353515625,\n 34.542762387234845\n ],\n [\n -120.860595703125,\n 34.542762387234845\n ],\n [\n -120.860595703125,\n 32.52828936482526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-02","publicationStatus":"PW","scienceBaseUri":"5b46e546e4b060350a15d089","contributors":{"authors":[{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Neill, Andrea C. 0000-0003-1656-4372 aoneill@usgs.gov","orcid":"https://orcid.org/0000-0003-1656-4372","contributorId":5351,"corporation":false,"usgs":true,"family":"O'Neill","given":"Andrea C.","email":"aoneill@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":739427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":739428,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finzi Hart, Juliette 0000-0003-3179-2699","orcid":"https://orcid.org/0000-0003-3179-2699","contributorId":206104,"corporation":false,"usgs":true,"family":"Finzi Hart","given":"Juliette","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739429,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vitousek, Sean","contributorId":190192,"corporation":false,"usgs":false,"family":"Vitousek","given":"Sean","affiliations":[],"preferred":false,"id":739430,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Limber, Patrick W. 0000-0002-8207-3750 plimber@usgs.gov","orcid":"https://orcid.org/0000-0002-8207-3750","contributorId":196794,"corporation":false,"usgs":true,"family":"Limber","given":"Patrick","email":"plimber@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739431,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hayden, Maya","contributorId":206106,"corporation":false,"usgs":false,"family":"Hayden","given":"Maya","affiliations":[{"id":37247,"text":"Point Blue Conservation","active":true,"usgs":false}],"preferred":false,"id":739432,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fitzgibbon, Michael","contributorId":206105,"corporation":false,"usgs":false,"family":"Fitzgibbon","given":"Michael","email":"","affiliations":[{"id":37247,"text":"Point Blue Conservation","active":true,"usgs":false}],"preferred":false,"id":739444,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lovering, Jessica 0000-0002-0705-9633","orcid":"https://orcid.org/0000-0002-0705-9633","contributorId":204726,"corporation":false,"usgs":true,"family":"Lovering","given":"Jessica","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739445,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Foxgrover, Amy C. 0000-0003-0638-5776 afoxgrover@usgs.gov","orcid":"https://orcid.org/0000-0003-0638-5776","contributorId":3261,"corporation":false,"usgs":true,"family":"Foxgrover","given":"Amy","email":"afoxgrover@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739446,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70198083,"text":"70198083 - 2018 - Turning on the faucet to a healthy coast","interactions":[],"lastModifiedDate":"2018-07-13T10:02:04","indexId":"70198083","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3427,"text":"Solutions Journal","active":true,"publicationSubtype":{"id":10}},"title":"Turning on the faucet to a healthy coast","docAbstract":"Coastal re-engineering and freshwater extraction have reduced water flow into the estuaries of the world. Because of these activities, stressed coastal vegetation is especially vulnerable to die-off during droughts, contributing to a loss of human services related to storm protection, fisheries and water quality. The subsequent collapse of vegetation is often as related to the loss of flow as to the rise in salinity. The solution to the problem in regions with rapidly expanding human populations may be to apply strategically timed freshwater releases to estuaries. To be successful, the water requirements of both humans and natural environments need careful assessment. Flow management projects have been successful in reviving vegetation in a number of settings including The Everglades, Murray River, Mississippi River and Nueces River. These projects can be contentious, for example, if the projects have caused negative impacts to the oyster industry. Beyond the human services provided, flowing water has an intrinsic personal value for which many people are willing to pay.","language":"English","publisher":"Solutions Journal","usgsCitation":"Middleton, B., and Montagna, P.A., 2018, Turning on the faucet to a healthy coast: Solutions Journal, v. 9, no. 3, 14 p.","productDescription":"14 p.","ipdsId":"IP-091390","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":355662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355646,"type":{"id":15,"text":"Index Page"},"url":"https://www.thesolutionsjournal.com/article/turning-faucet-healthy-coast/"}],"country":"United States","volume":"9","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc419e4b0f5d57878e9e7","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206267,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":739935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Montagna, Paul A.","contributorId":177033,"corporation":false,"usgs":false,"family":"Montagna","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":739936,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197943,"text":"70197943 - 2018 - Methylmercury dynamics in Upper Sacramento Valley rice fields with low background soil mercury levels","interactions":[],"lastModifiedDate":"2018-07-03T10:53:43","indexId":"70197943","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Methylmercury dynamics in Upper Sacramento Valley rice fields with low background soil mercury levels","docAbstract":"

Few studies have considered how methylmercury (MeHg, a toxic form of Hg produced in anaerobic soils) production in rice (Oryza sativa L.) fields can affect water quality, and little is known about MeHg dynamics in rice fields. Surface water MeHg and total Hg (THg) imports, exports, and storage were studied in two commercial rice fields in the Sacramento Valley, California, where soil THg was low (25 and 57 ng g−1). The median concentration of MeHg in drainage water exiting the fields was 0.17 ng g−1 (range: <0.007–2.1 ng g−1). Compared with irrigation water, drainage water had similar MeHg concentrations, and lower THg concentrations during the growing season. Significantly elevated drainage water MeHg and THg concentrations were observed in the fallow season compared with the growing season. An analysis of surface water loads indicates that fields were net importers of both MeHg (76–110 ng m−2) and THg (1947–7224 ng m−2) during the growing season, and net exporters of MeHg (35–200 ng m−2) and THg (248–6496 ng m−2) during the fallow season. At harvest, 190 to 700 ng MeHg m−2 and 1400 to 1700 ng THg m−2 were removed from fields in rice grain. Rice straw, which contained 120 to 180 ng MeHg m−2 and 7000–10,500 ng m−2 THg was incorporated into the soil. These results indicate that efforts to reduce MeHg and THg exports in rice drainage water should focus on the fallow season. Substantial amounts of MeHg and THg were stored in plants, and these pools should be considered in future studies.

","language":"English","publisher":"ASA, CSSA, and SSSA","doi":"10.2134/jeq2017.10.0390","usgsCitation":"Tanner, K.C., Windham-Myers, L., Marvin-DiPasquale, M.C., Fleck, J., Tate, K.W., and Linquist, B.A., 2018, Methylmercury dynamics in Upper Sacramento Valley rice fields with low background soil mercury levels: Journal of Environmental Quality, v. 47, no. 4, p. 830-838, https://doi.org/10.2134/jeq2017.10.0390.","productDescription":"9 p.","startPage":"830","endPage":"838","ipdsId":"IP-086490","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":355448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e547e4b060350a15d093","contributors":{"authors":[{"text":"Tanner, K. Christy","contributorId":179307,"corporation":false,"usgs":false,"family":"Tanner","given":"K.","email":"","middleInitial":"Christy","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":739261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":739262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":739260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tate, Kenneth W.","contributorId":179308,"corporation":false,"usgs":false,"family":"Tate","given":"Kenneth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":739264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Linquist, Bruce A.","contributorId":179310,"corporation":false,"usgs":false,"family":"Linquist","given":"Bruce","email":"","middleInitial":"A.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":739265,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198048,"text":"70198048 - 2018 - Geochemical characterization and modeling of regional groundwater contributing to the Verde River, Arizona between Mormon Pocket and the USGS Clarkdale gage","interactions":[],"lastModifiedDate":"2018-07-16T10:52:46","indexId":"70198048","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical characterization and modeling of regional groundwater contributing to the Verde River, Arizona between Mormon Pocket and the USGS Clarkdale gage","docAbstract":"We use synoptic surveys of stream discharge, stable isotopes, and dissolved noble gases to identify the source of groundwater discharge to the Verde River in central Arizona. The Verde River more than doubles in discharge in Mormon Pocket over a 1.4 km distance that includes three discrete locations of visible spring input to the river and other diffuse groundwater inputs. A detailed study of the Verde River between Mormon Pocket and the USGS Clarkdale Gage was conducted to better constrain the location of groundwater inputs, the geochemical signature and constrain the source of groundwater input. Discharge, water quality parameters (temperature, pH, specific conductance, and dissolved oxygen), stable isotopes (δ18O and δ2H), noble gases (He, Ne, Ar, Kr and Xe), and radon (222Rn) from river water were collected. Groundwater samples from springs and wells in the area were collected and analyzed for tracers measured in the stream along with some additional analytes (major ions, strontium isotopes (87Sr/86Sr), carbon-14, δ13C, and tritium). Groundwater isotopic signature is consistent with a regional groundwater source. Groundwater springs discharging to the river have a depleted stable isotopic signature indicating recharge source up to 1000 m higher than the discharge location in the Verde River and are significantly fresher than stream water. Spring water has a radiocarbon age of several thousand years and some areas have tritium less than the laboratory reporting level or low concentrations of tritium (1.5 TU). The strontium isotopes indicate groundwater interaction with tertiary volcanic rock and Paleozoic sedimentary rocks. Along the study reach with distance downstream, Verde stream water chemistry shows increased 222Rn, freshening, increased 4He, and isotopic depletion with distance downstream. We estimated total groundwater discharge by inverting a stream transport model against 222Rn and discharge measured in the stream. The salinity, 4He, and stable isotope composition of discharging groundwater was then estimated by fitting modeled values to observed in-stream values. Estimated groundwater inflow to the stream was well within the ranges observed in springs, indicating that the main source of streamflow is deep, regional groundwater. These results show that synoptic surveys of environmental tracers in streams can be used to estimate the isotopic composition and constrain the source of groundwater discharging to streams. Our data provide direct field evidence that deep, regional groundwater discharge can be a significant source of streamflow generation in arid, topographically complex watersheds.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2018.06.078","usgsCitation":"Beisner, K.R., Gardner, W.P., and Hunt, A.G., 2018, Geochemical characterization and modeling of regional groundwater contributing to the Verde River, Arizona between Mormon Pocket and the USGS Clarkdale gage: Journal of Hydrology, v. 564, p. 99-114, https://doi.org/10.1016/j.jhydrol.2018.06.078.","productDescription":"15 p.","startPage":"99","endPage":"114","ipdsId":"IP-093900","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":355615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","volume":"564","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e545e4b060350a15d083","contributors":{"authors":[{"text":"Beisner, Kimberly R. 0000-0002-2077-6899 kbeisner@usgs.gov","orcid":"https://orcid.org/0000-0002-2077-6899","contributorId":2733,"corporation":false,"usgs":true,"family":"Beisner","given":"Kimberly","email":"kbeisner@usgs.gov","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, W. Payton 0000-0003-0664-001X","orcid":"https://orcid.org/0000-0003-0664-001X","contributorId":206198,"corporation":false,"usgs":false,"family":"Gardner","given":"W.","email":"","middleInitial":"Payton","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":739769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":739768,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197946,"text":"sir20185089 - 2018 - Water-quality conditions with an emphasis on cyanobacteria and associated toxins and taste-and-odor compounds in the Kansas River, Kansas, July 2012 through September 2016","interactions":[],"lastModifiedDate":"2018-09-25T06:22:34","indexId":"sir20185089","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5089","title":"Water-quality conditions with an emphasis on cyanobacteria and associated toxins and taste-and-odor compounds in the Kansas River, Kansas, July 2012 through September 2016","docAbstract":"

Cyanobacteria cause a multitude of water-quality concerns, including the potential to produce toxins and taste-and-odor compounds that may cause substantial economic and public health concerns, and are of particular interest in lakes, reservoirs, and rivers that are used for drinking-water supply. Extensive cyanobacterial blooms typically do not develop in the Kansas River; however, reservoirs in the lower Kansas River Basin occasionally develop blooms that may affect downstream water quality. During July 2012 through September 2016, continuous and (or) discrete water-quality data were collected at several sites (Wamego, De Soto, and three main reservoir-fed tributaries) on the Kansas River to characterize the sources, frequency and magnitude of occurrence, and causes of cyanobacteria, cyanobacterial toxins, and taste-and-odor compounds and to develop a real-time notification system of changing water-quality conditions that may affect drinking-water treatment.

Algal biomass, as estimated by chlorophyll, was consistently higher at the downstream De Soto site than the upstream Wamego site. Higher algal biomass at the De Soto site likely was caused by algal growth during downstream transport without major losses due to grazing by aquatic organisms or other processes. Algal biomass at the Wamego and De Soto sites was negatively correlated with streamflow and total and bioavailable nutrient concentrations. The negative association between algal biomass and nutrients in the Kansas River likely reflects the relatively strong positive association between nutrient concentrations and streamflows.

Cyanobacteria were relatively common in the Kansas River but rarely dominated the algal community. Like overall algal biomass, cyanobacterial abundances typically were higher at the De Soto site than the Wamego site. Cyanobacterial abundances generally peaked in late summer or early fall (July through October), with smaller peaks occasionally observed in spring (April through May). Cyanobacteria in the Kansas River rarely exceeded 20,000 cells per milliliter, the abundance at which cyanobacteria may become a concern for drinking-water treatment. Relations between cyanobacterial abundance and streamflow, turbidity, and nutrients in the Kansas River were similar to those between chlorophyll and total phytoplankton abundance, indicating the same processes that influence overall algal biomass and dynamics also are influencing cyanobacteria.

The cyanotoxin microcystin was detected in about 27 percent of the samples collected from Kansas River tributary and main-stem sites. Cylindrospermopsin was detected in one sample from the De Soto site. Microcystin occurrence and concentration were similar between the Wamego and De Soto sites. Concentrations exceeded the U.S. Environmental Protection Agency health advisory guidance values for finished drinking water of 0.3 (for bottle-fed infants and pre-school children) and 1.6 micrograms per liter (μg/L; for school-age children and adults) in 6 percent or less of samples collected. These guidance values are for finished drinking water and are not directly applicable to observed environmental concentrations but do provide a benchmark for comparison. Microcystin was detected most often and had the highest concentrations during summer. Though seasonal patterns in microcystin occurrence were generally consistent, seasonal maxima varied by an order of magnitude across years.

The taste-and-odor compounds geosmin and 2-methylisoborneol (MIB) were detected in about 78 and 43 percent of samples, respectively, collected across all sites (main stem and tributaries). Geosmin and MIB occurrence and concentration varied considerably between the Wamego and De Soto sites. Geosmin was detected in about 67 percent of Wamego samples and 81 percent of De Soto samples. The human detection threshold of 5 nanograms per liter (ng/L) was exceeded for geosmin in about 11 and 17 percent of the samples collected at the Wamego and De Soto sites, respectively. Geosmin was detected during all months of the year at both sites, and there were no clear seasonal patterns. MIB was detected less frequently in the Kansas River than geosmin and was observed in about 42 percent of Wamego samples and 33 percent of De Soto samples. Concentrations exceeded 5 ng/L in about 7 and 5 percent of samples from the Wamego and De Soto sites, respectively. As observed for geosmin, there were no clear seasonal patterns in MIB occurrence or concentration.

There seems to be a connection between microcystin detections in the Kansas River and occurrence of microcystin in upstream reservoirs (and tributary streams). Microcystin concentrations greater than 0.3 μg/L may be likely during the summer when streamflow is less than 3,000 cubic feet per second (ft3/s) and contributions from Milford Lake exceed about 30 percent of total flow in the Kansas River. Observed microcystin concentrations typically were higher at the De Soto site than the Wamego or tributary sites during 2012 through 2016, indicating cyanobacteria may continue to grow and produce microcystin once introduced to the Kansas River.

The spatial and temporal patterns in geosmin and MIB occurrence and concentration were more complex than microcystin. There were no clear connections between geosmin and MIB occurrence in the Kansas River and potential upstream reservoir (or tributary stream) sources. Likewise, there was not a clear relation between algal biomass, cyanobacteria, or actinomycetes bacteria and taste-and-odor events in the Kansas River. Geosmin and MIB were not strongly correlated with any measured environmental variable at either Kansas River site.

Continuous water-quality data may be used independently or in combination with regression models to provide information on changing water-quality conditions that may affect drinking-water treatment processes or recreational activities on the Kansas River. For example, logistic regression model outputs and continuous water-quality data may both be indicative of the potential for microcystin events. Logistic regression models that are estimating a high probability of microcystin occurrence at concentrations above 0.1 μg/L can be used as one indicator. Streamflows less than 3,000 ft3/s during upstream reservoir releases during periods with low turbidity and increased chlorophyll fluorescence, specific conductance, and pH values may also be indicative of microcystin events. Advanced or near-real-time notification may inform proactive, rather than reactive, management strategies when water-quality conditions are changing rapidly or are likely to cause cyanobacteria-related events.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185089","collaboration":"Prepared in cooperation with the Kansas Water Office, the City of Lawrence, the City of Olathe, the City of Topeka, and Johnson County WaterOne","usgsCitation":"Graham, J.L., Foster, G.M., Williams, T.J., Mahoney, M.D., May, M.R., and Loftin, K.A., 2018, Water-quality conditions with an emphasis on cyanobacteria and associated toxins and taste-and-odor compounds in the Kansas River, Kansas, July 2012 through September 2016: U.S. Geological Survey Scientific Investigations Report 2018–5089, 55 p., https://doi.org/10.3133/sir20185089.","productDescription":"Report: vi, 54 p.; 6 Appendixes; 2 Data Releases","numberOfPages":"66","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-091849","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":355473,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EVITTP","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Phytoplankton data for the Kansas River and tributaries, July 2012 through February 2017"},{"id":355474,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P973V4A9","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Discrete water-quality data for the Kansas River and tributaries, July 2012 - September 2016"},{"id":355471,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix5.pdf","text":"Appendix 5","size":"239kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 5"},{"id":355465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5089/coverthb2.jpg"},{"id":355472,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix6.pdf","text":"Appendix 6","size":"701 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 6"},{"id":355466,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089.pdf","text":"Report","size":"3.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089"},{"id":355467,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix1.pdf","text":"Appendix 1","size":"365 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 1"},{"id":355468,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix2.pdf","text":"Appendix 2","size":"370 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 2"},{"id":355469,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix3.pdf","text":"Appendix 3","size":"377 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 3"},{"id":355470,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5089/sir20185089_appendix4.pdf","text":"Appendix 4","size":"372 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5089 Appendix 4"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97,\n 38.5\n ],\n [\n -94.6307373046875,\n 38.5\n ],\n [\n -94.6307373046875,\n 40\n ],\n [\n -97,\n 40\n ],\n [\n -97,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049 

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-07-02","noUsgsAuthors":false,"publicationDate":"2018-07-02","publicationStatus":"PW","scienceBaseUri":"5b46e547e4b060350a15d091","contributors":{"authors":[{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":739270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, Guy M. 0000-0002-9581-057X gfoster@usgs.gov","orcid":"https://orcid.org/0000-0002-9581-057X","contributorId":149145,"corporation":false,"usgs":true,"family":"Foster","given":"Guy","email":"gfoster@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Thomas J. 0000-0003-3124-3243 tjwilliams@usgs.gov","orcid":"https://orcid.org/0000-0003-3124-3243","contributorId":185244,"corporation":false,"usgs":true,"family":"Williams","given":"Thomas","email":"tjwilliams@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":739272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mahoney, Matthew D. 0000-0002-9008-7132","orcid":"https://orcid.org/0000-0002-9008-7132","contributorId":206054,"corporation":false,"usgs":true,"family":"Mahoney","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":739273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"May, Madison R. 0000-0001-9628-4041 mmay@usgs.gov","orcid":"https://orcid.org/0000-0001-9628-4041","contributorId":167612,"corporation":false,"usgs":true,"family":"May","given":"Madison","email":"mmay@usgs.gov","middleInitial":"R.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":739274,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":739275,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197441,"text":"sir20185075 - 2018 - Nutrient loads in the Lost River and Klamath River Basins, south-central Oregon and northern California, March 2012–March 2015","interactions":[],"lastModifiedDate":"2018-07-03T09:38:08","indexId":"sir20185075","displayToPublicDate":"2018-07-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5075","title":"Nutrient loads in the Lost River and Klamath River Basins, south-central Oregon and northern California, March 2012–March 2015","docAbstract":"

The U.S. Geological Survey and Bureau of Reclamation collected water-quality data from March 2012 to March 2015 at locations in the Lost River and Klamath River Basins, Oregon, in an effort to characterize water quality and compute a nutrient budget for the Bureau of Reclamation Klamath Reclamation Project. The study described in this report resulted in the following significant findings:

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185075","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Schenk, L.N., Stewart, M.A., and Eldridge, S.L.C., 2018, Nutrient loads in the Lost River and Klamath River Basins, south-central Oregon and northern California, March 2012–March 2015: U.S. Geological Survey Scientific Investigations Report 2018-5075, 55 p., https://doi.org/10.3133/sir20185075.","productDescription":"Report: viii, 55 p.; 7 Tables; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091255","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":355460,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5075/sir20185075_table05b_splits_USGS.xlsx","text":"Table 5B","size":"70 KB xlsx","description":"SIR 2018-5075 Table 5B"},{"id":355461,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5075/sir20185075_table05c_replicates_USGS.xlsx","text":"Table 5C","size":"55 KB xlsx","description":"SIR 2018-5075 Table 5C"},{"id":355464,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5075/sir20185075_appendix01.pdf","text":"Appendix 1","size":"586 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5075 Appendix 1"},{"id":355463,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5075/sir20185075_table08_alldata.csv","text":"Table 8","size":"171 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2018-5075 Table 8"},{"id":355462,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5075/sir20185075_table05d_spikes_USGS.xlsx","text":"Table 5D","size":"166 KB xlsx","description":"SIR 2018-5075 Table 5D"},{"id":355455,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5075/coverthb.jpg"},{"id":355456,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5075/sir20185075.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5075"},{"id":355457,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5075/sir20185075_table04a_blanks_BOR.xlsx","text":"Table 4A","size":"42 KB xlsx","description":"SIR 2018-5075 Table 4A"},{"id":355458,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5075/sir20185075_table04b_replicates_BOR.xlsx","text":"Table 4B","size":"64 KB xlsx","description":"SIR 2018-5075 Table 4B"},{"id":355459,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5075/sir20185075_table05a_blanks_USGS.xlsx","text":"Table 5A","size":"78 KB xlsx","description":"SIR 2018-5075 Table 5A"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River Basin, Lost River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 41.75\n ],\n [\n -121,\n 41.75\n ],\n [\n -121,\n 42.25\n ],\n [\n -122,\n 42.25\n ],\n [\n -122,\n 41.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-07-02","noUsgsAuthors":false,"publicationDate":"2018-07-02","publicationStatus":"PW","scienceBaseUri":"5b46e547e4b060350a15d095","contributors":{"authors":[{"text":"Schenk, Liam N. 0000-0002-2491-0813 lschenk@usgs.gov","orcid":"https://orcid.org/0000-0002-2491-0813","contributorId":4273,"corporation":false,"usgs":true,"family":"Schenk","given":"Liam","email":"lschenk@usgs.gov","middleInitial":"N.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, Marc A. 0000-0003-1140-6316 mastewar@usgs.gov","orcid":"https://orcid.org/0000-0003-1140-6316","contributorId":2277,"corporation":false,"usgs":true,"family":"Stewart","given":"Marc","email":"mastewar@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell Eldridge, Sara L. 0000-0001-8838-8940 seldridge@usgs.gov","orcid":"https://orcid.org/0000-0001-8838-8940","contributorId":64502,"corporation":false,"usgs":true,"family":"Caldwell Eldridge","given":"Sara","email":"seldridge@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":737167,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"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":"

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 (Popenaias popeii, Texas Hornshell) plus two other mussel species (Potamilus metnecktayi, Salina Mucket; and Truncilla cognata, 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.

","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":566,"text":"Southeast 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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 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Michigan Basin","docAbstract":"

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.

","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":70198560,"text":"70198560 - 2018 - Shifts in the relationship between mRNA and protein abundance of gill ion-transporters during smolt development and seawater acclimation in Atlantic salmon (Salmo salar)","interactions":[],"lastModifiedDate":"2018-08-07T16:25:35","indexId":"70198560","displayToPublicDate":"2018-07-01T16:25:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1289,"text":"Comparative Biochemistry and Physiology, Part A: Molecular & Integrative Physiology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Shifts in the relationship between mRNA and protein abundance of gill ion-transporters during smolt development and seawater acclimation in Atlantic salmon (Salmo salar)","title":"Shifts in the relationship between mRNA and protein abundance of gill ion-transporters during smolt development and seawater acclimation in Atlantic salmon (Salmo salar)","docAbstract":"

Smolting Atlantic salmon exhibit a seasonal increase in seawater tolerance that is associated with changes in the abundance of major gill ion-transporter transcripts and proteins. In the present study, we investigate how the transcript and protein abundance of specific ion-transporter isoforms relate to each other during smolt development and seawater acclimation, and how each correlates to seawater tolerance. We show that during smolt development both mRNA and protein abundance of gill Na+/K+-ATPase α1a subunit (NKAα1a) decreased but the decrease in the mRNA was five-times greater than that of the protein. Gill NKAα1b mRNA levels increased only slightly (1.5-fold) throughout development whereas protein abundance increased 30-fold at its peak. Gill Na+/K+/2Cl− co-transporter 1 (NKCC1) increased at the mRNA and protein level (5- and 12-fold) in smolts. The abundance of a gill ion-transporter's mRNA and protein changed in the same direction through development and after seawater transfer, but the changes were not always strongly correlated: NKAα1a (r = 0.768), NKAα1b (r = 0.40), and NKCC1 (r = 0.898). The maintenance of plasma chloride concentration correlated most strongly with the abundance of NKAα1a mRNA, and the ratio of NKAα1b to NKAα1a mRNA and protein. Growth performance after seawater transfer correlated most strongly with the abundance of NKAα1b protein and the ratio of NKAα1b to NKAα1a protein. Our results indicate that the abundance of ion-transporter mRNA and protein do not always correlate well and a decrease in the abundance of gill NKAα1a mRNA and increase in NKAα1b protein are strong predictors of seawater tolerance and growth performance after seawater transfer.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.cbpa.2018.03.020","usgsCitation":"Christensen, A., Regish, A.M., and McCormick, S.D., 2018, Shifts in the relationship between mRNA and protein abundance of gill ion-transporters during smolt development and seawater acclimation in Atlantic salmon (Salmo salar): Comparative Biochemistry and Physiology, Part A: Molecular & Integrative Physiology, v. 221, p. 63-73, https://doi.org/10.1016/j.cbpa.2018.03.020.","productDescription":"11 p.","startPage":"63","endPage":"73","ipdsId":"IP-070424","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468612,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cbpa.2018.03.020","text":"Publisher Index Page"},{"id":356315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"221","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc41ae4b0f5d57878e9ed","contributors":{"authors":[{"text":"Christensen, Arne K.","contributorId":206846,"corporation":false,"usgs":false,"family":"Christensen","given":"Arne K.","affiliations":[{"id":37414,"text":"Anna Maria College","active":true,"usgs":false}],"preferred":false,"id":741927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regish, Amy M. 0000-0003-4747-4265 aregish@usgs.gov","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":5415,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"aregish@usgs.gov","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":741928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":741926,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200910,"text":"70200910 - 2018 - Environmental controls, emergent scaling, and predictions of greenhouse gas (GHG) fluxes in coastal salt marshes","interactions":[],"lastModifiedDate":"2018-11-14T15:03:45","indexId":"70200910","displayToPublicDate":"2018-07-01T15:03:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Environmental controls, emergent scaling, and predictions of greenhouse gas (GHG) fluxes in coastal salt marshes","docAbstract":"

Coastal salt marshes play an important role in mitigating global warming by removing atmospheric carbon at a high rate. We investigated the environmental controls and emergent scaling of major greenhouse gas (GHG) fluxes such as carbon dioxide (CO2) and methane (CH4) in coastal salt marshes by conducting data analytics and empirical modeling. The underlying hypothesis is that the salt marsh GHG fluxes follow emergent scaling relationships with their environmental drivers, leading to parsimonious predictive models. CO2 and CH4 fluxes, photosynthetically active radiation (PAR), air and soil temperatures, well water level, soil moisture, and porewater pH and salinity were measured during May–October 2013 from four marshes in Waquoit Bay and adjacent estuaries, MA, USA. The salt marshes exhibited high CO2 uptake and low CH4 emission, which did not significantly vary with the nitrogen loading gradient (5–126 kg · ha−1 · year−1) among the salt marshes. Soil temperature was the strongest driver of both fluxes, representing 2 and 4–5 times higher influence than PAR and salinity, respectively. Well water level, soil moisture, and pH did not have a predictive control on the GHG fluxes, although both fluxes were significantly higher during high tides than low tides. The results were leveraged to develop emergent power law‐based parsimonious scaling models to accurately predict the salt marsh GHG fluxes from PAR, soil temperature, and salinity (Nash‐Sutcliffe Efficiency = 0.80–0.91). The scaling models are available as a user‐friendly Excel spreadsheet named Coastal Wetland GHG Model to explore scenarios of GHG fluxes in tidal marshes under a changing climate and environment.

","language":"English","publisher":"AGU","doi":"10.1029/2018JG004556","usgsCitation":"Abdul-Aziz, O.I., Ishitaq, K.S., Tang, J., Moseman-Valtierra, S., Kroeger, K.D., Gonneea Eagle, M., Mora, J., and Morkeski, K., 2018, Environmental controls, emergent scaling, and predictions of greenhouse gas (GHG) fluxes in coastal salt marshes: Journal of Geophysical Research G: Biogeosciences, v. 123, no. 7, p. 2234-2256, https://doi.org/10.1029/2018JG004556.","productDescription":"23 p.","startPage":"2234","endPage":"2256","ipdsId":"IP-093072","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jg004556","text":"Publisher Index Page"},{"id":359427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.5,\n 41.54301946112854\n ],\n [\n -70.5833,\n 41.54301946112854\n ],\n [\n -70.5833,\n 41.5833\n ],\n [\n -70.5,\n 41.5833\n ],\n [\n -70.5,\n 41.54301946112854\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"7","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-28","publicationStatus":"PW","scienceBaseUri":"5bed4274e4b0b3fc5cf91c90","contributors":{"authors":[{"text":"Abdul-Aziz, Omar I.","contributorId":192386,"corporation":false,"usgs":false,"family":"Abdul-Aziz","given":"Omar","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":751228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ishitaq, Khandker S.","contributorId":210612,"corporation":false,"usgs":false,"family":"Ishitaq","given":"Khandker","email":"","middleInitial":"S.","affiliations":[{"id":38119,"text":"Ecological and Water Resources Engineering Laboratory (EWREL), Department of Civil and Environmental Engineering, West Virginia University, 395 Evansdale Drive, PO Box 6103, Morgantown, WV 26506,","active":true,"usgs":false}],"preferred":false,"id":751229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tang, Jianwu","contributorId":174890,"corporation":false,"usgs":false,"family":"Tang","given":"Jianwu","email":"","affiliations":[{"id":27818,"text":"The Ecosystems Center, Marine Biological Laboratory. Woods Hole, MA 02543.","active":true,"usgs":false}],"preferred":false,"id":751230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moseman-Valtierra, Serena","contributorId":140087,"corporation":false,"usgs":false,"family":"Moseman-Valtierra","given":"Serena","email":"","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":751231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":751232,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gonneea Eagle, Meagan 0000-0001-5072-2755 mgonneea@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":174590,"corporation":false,"usgs":true,"family":"Gonneea Eagle","given":"Meagan","email":"mgonneea@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":751233,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mora, Jordan","contributorId":208060,"corporation":false,"usgs":false,"family":"Mora","given":"Jordan","email":"","affiliations":[{"id":37699,"text":"Waquoit Bay National Estuarine Research Reserve, Waquoit, Mass","active":true,"usgs":false}],"preferred":false,"id":751234,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morkeski, Kate","contributorId":210613,"corporation":false,"usgs":false,"family":"Morkeski","given":"Kate","email":"","affiliations":[{"id":38120,"text":"Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, 266 Woods Hole Road, Woods Hole, MA 02543, USA","active":true,"usgs":false}],"preferred":false,"id":751235,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}