{"pageNumber":"189","pageRowStart":"4700","pageSize":"25","recordCount":68802,"records":[{"id":70225598,"text":"70225598 - 2021 - The ten steps to responsible Inland fisheries in practice: Reflections from diverse regional case studies around the globe","interactions":[],"lastModifiedDate":"2021-10-27T13:36:01.198174","indexId":"70225598","displayToPublicDate":"2021-07-15T07:28:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"The ten steps to responsible Inland fisheries in practice: Reflections from diverse regional case studies around the globe","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Inland fisheries make substantial contributions to food security and livelihoods locally, regionally, and globally but their conservation and management have been largely overlooked by policy makers. In an effort to remedy this limited recognition, a cross-sectoral community of scientists, practitioners, and policy makers from around the world convened a high-level meeting in 2015 at the Food and Agriculture Organization of the United Nations headquarters in Rome, Italy to develop recommendations for sustainable inland fisheries management. This meeting resulted in the production of the Rome Declaration, outlining ten key steps needed to achieve responsible inland fisheries. When the Ten Steps were conceived, they were framed in a global context because inland fisheries around the world face similar challenges, and it was hoped that these large-scale and ambitious steps would draw the attention of regional or international bodies for greater investment in their proper management. Most inland fisheries, however, are managed at a local (often community, watershed, or waterbody) scale with the “on-the-ground” practitioners, managers, assessment biologists, and stewardship officers responsible for achieving the promise of the Ten Steps. Here, we reflect on the relevance of the Ten Steps to practitioners using six regional case studies from around the globe (North America, South America, Europe, Asia, Australia, and Africa) to identify the extent to which existing efforts align with the Ten Steps and where there are opportunities to do more. Learning what is effective from local/regional actions should better inform a more global “action plan” and provide tangible guidance for implementation recognizing that global guidance needs to be informed by and acted upon by local practitioners. We conclude by considering the common challenges, synergies, and other emergent properties that arise from these case studies, and use these as a path forward to advancing responsible management of inland fisheries through the Rome Declaration. Of particular importance is the need to balance the high-level aspirational goals of the Ten Steps with the local cultural, socio-economic, and institutional realities that ultimately influence how humans interact with fisheries resources and aquatic ecosystems. This assessment provides valuable information on how to refine and implement the Ten Steps recognizing that success will require coordinated efforts among on-the-ground practitioners, scientists, stakeholders, rightsholders and international decision makers.</p></div></div></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s11160-021-09664-w","usgsCitation":"Cooke, S.J., Nyboer, E.A., Bennett, A., Lynch, A., Infante, D.M., Cowx, I.G., Beard, T., Bartley, D., Paukert, C., Reid, A.J., Funge-Smith, S., Gondwe, E., Kaunda, E., Koehn, J.D., Souter, N., Stokes, G.L., Castello, L., Leonard, N., Skov, C., Berg, S., and Taylor, W.W., 2021, The ten steps to responsible Inland fisheries in practice: Reflections from diverse regional case studies around the globe: Reviews in Fish Biology and Fisheries, v. 31, p. 843-877, https://doi.org/10.1007/s11160-021-09664-w.","productDescription":"35 p.","startPage":"843","endPage":"877","ipdsId":"IP-118803","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":467232,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/111966","text":"External Repository"},{"id":391009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","noUsgsAuthors":false,"publicationDate":"2021-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Cooke, Steven J.","contributorId":214435,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":825757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nyboer, Elizabeth A.","contributorId":250650,"corporation":false,"usgs":false,"family":"Nyboer","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":825758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Abigail","contributorId":268041,"corporation":false,"usgs":false,"family":"Bennett","given":"Abigail","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":825759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":246026,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail J.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":825760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Infante, Dana M.","contributorId":146114,"corporation":false,"usgs":false,"family":"Infante","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":16583,"text":"Department of Fisheries and Wildlife, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":825761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cowx, Ian G.","contributorId":37228,"corporation":false,"usgs":false,"family":"Cowx","given":"Ian","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":825762,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beard, T. Douglas Jr. 0000-0003-2632-2350","orcid":"https://orcid.org/0000-0003-2632-2350","contributorId":245522,"corporation":false,"usgs":true,"family":"Beard","given":"T. Douglas","suffix":"Jr.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":825763,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bartley, Devin","contributorId":166934,"corporation":false,"usgs":false,"family":"Bartley","given":"Devin","affiliations":[],"preferred":false,"id":825764,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Paukert, Craig 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":268045,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":825765,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reid, Andrea J.","contributorId":221029,"corporation":false,"usgs":false,"family":"Reid","given":"Andrea","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":825766,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Funge-Smith, Simon","contributorId":197466,"corporation":false,"usgs":false,"family":"Funge-Smith","given":"Simon","affiliations":[],"preferred":false,"id":825767,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gondwe, Edith","contributorId":268048,"corporation":false,"usgs":false,"family":"Gondwe","given":"Edith","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":825768,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kaunda, Emmanuel","contributorId":268049,"corporation":false,"usgs":false,"family":"Kaunda","given":"Emmanuel","email":"","affiliations":[{"id":55542,"text":"Lilongwe University","active":true,"usgs":false}],"preferred":false,"id":825769,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Koehn, John D.","contributorId":220481,"corporation":false,"usgs":false,"family":"Koehn","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":27292,"text":"Arthur Rylah Institute for Environmental Research","active":true,"usgs":false}],"preferred":false,"id":825770,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Souter, Nicholas J.","contributorId":268051,"corporation":false,"usgs":false,"family":"Souter","given":"Nicholas J.","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":825771,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Stokes, Gretchen L. 0000-0003-4202-6527","orcid":"https://orcid.org/0000-0003-4202-6527","contributorId":245640,"corporation":false,"usgs":false,"family":"Stokes","given":"Gretchen","email":"","middleInitial":"L.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":825772,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Castello, Leandro","contributorId":268053,"corporation":false,"usgs":false,"family":"Castello","given":"Leandro","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":825773,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Leonard, Nancy J.","contributorId":268054,"corporation":false,"usgs":false,"family":"Leonard","given":"Nancy J.","affiliations":[{"id":20304,"text":"Pacific States Marine Fisheries Commission","active":true,"usgs":false}],"preferred":false,"id":825774,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Skov, Christian","contributorId":268055,"corporation":false,"usgs":false,"family":"Skov","given":"Christian","email":"","affiliations":[{"id":50046,"text":"Technical University of Denmark","active":true,"usgs":false}],"preferred":false,"id":825775,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Berg, Soren","contributorId":268056,"corporation":false,"usgs":false,"family":"Berg","given":"Soren","email":"","affiliations":[{"id":50046,"text":"Technical University of Denmark","active":true,"usgs":false}],"preferred":false,"id":825776,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Taylor, William W.","contributorId":166927,"corporation":false,"usgs":false,"family":"Taylor","given":"William","email":"","middleInitial":"W.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":825778,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70221835,"text":"sir20215031 - 2021 - Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho","interactions":[],"lastModifiedDate":"2021-07-16T12:31:02.274219","indexId":"sir20215031","displayToPublicDate":"2021-07-15T07:17:18","publicationYear":"2021","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":"2021-5031","displayTitle":"Optimization of the Idaho National Laboratory Water-Quality Aquifer Monitoring Network, Southeastern Idaho","title":"Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho","docAbstract":"<p class=\"p1\">Long-term monitoring of water-quality data collected from wells at the Idaho National Laboratory (INL) has provided essential information for delineating the movement of radiochemical and chemical wastes in the eastern Snake River Plain aquifer, southeastern Idaho. Since 1949, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, has maintained as many as 200 wells in the INL water-quality monitoring network. A network design tool, distributed as an R package, was developed to evaluate and optimize groundwater monitoring in the existing network based on water-quality data collected at 153 sampling sites since January 1, 1989. The objective of the optimization design tool is to reduce well monitoring redundancy while retaining sufficient data to reliably characterize water-quality conditions in the aquifer. A spatial optimization was used to identify a set of wells whose removal leads to the smallest increase in the deviation between interpolated concentration maps using the existing and reduced monitoring networks while preserving significant long-term trends and seasonal components in the data. Additionally, a temporal optimization was used to identify reductions in sampling frequencies by minimizing the redundancy in sampling events.</p><p class=\"p1\">Spatial optimization uses an islands genetic algorithm to identify near-optimal network designs removing 10, 20, 30, 40, and 50 wells from the existing monitoring network. With this method, choosing a greater number of wells to remove results in greater cost savings and decreased accuracy of the average relative difference between interpolated maps of the reduced-dataset and the full-dataset. The genetic search algorithm identified reduced networks that best capture the spatial patterns of the average concentration plume while preserving long-term temporal trends at individual wells. Concentration data for 10 analyte types are integrated in a single optimization so that all datasets may be evaluated simultaneously. A constituent was selected for inclusion in the spatial optimization problem when the observations were sufficient to (1) establish a two-range variability model, (2) classify at least one concentration time series as a continuous record block, and (3) make a prediction using the quantile-kriging interpolation method. The selected constituents include sodium, chloride, sulfate, nitrate, carbon tetrachloride, 1,1-dichloroethylene, 1,1,1-trichloroethane, trichloroethylene, tritium, strontium-90, and plutonium-238.</p><p class=\"p2\">In temporal optimization, an iterative-thinning method was used to find an optimal sampling frequency for each analyte-well pair. Optimal frequencies indicate that for many of the wells, samples may be collected less frequently and still be able to characterize the concentration over time. The optimization results indicated that the sample-collection interval may be increased by an of average of 273 days owing to temporal redundancy.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215031","collaboration":"DOE/ID-22252<br />Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Fisher, J.C., Bartholomay, R.C., Rattray, G.W., and Maimer, N.V., 2021, Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho: U.S. Geological Survey Scientific Investigations Report 2021–5031 (DOE/ID-22252), 63 p., https://doi.org/10.3133/sir20215031.","productDescription":"Report: vii, 63 p.; Appendix 1-12; 2 Software Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071486","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":387046,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app02.html","text":"Appendix 2","size":"854 KB","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5031 Appendix 2"},{"id":387045,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app01.html","text":"Appendix 1","size":"6.3 MB","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5031 Appendix 1"},{"id":387058,"rank":16,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9X71CSU","text":"USGS software release —","description":"USGS software release","linkHelpText":"ObsNetQW—Assessment of a water-quality aquifer monitoring network"},{"id":387057,"rank":15,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9PP9UXZ","text":"USGS software release —","description":"USGS software release","linkHelpText":"inldata—Collection of datasets for the U.S. Geological Survey-Idaho National Laboratory aquifer monitoring networks"},{"id":387056,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app12.pdf","text":"Appendix 12","size":"116 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 12"},{"id":387054,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app10.pdf","text":"Appendix 10","size":"171 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 10"},{"id":387053,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app09.pdf","text":"Appendix 9","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 9"},{"id":387052,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app08.pdf","text":"Appendix 8","size":"138 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 8"},{"id":387051,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app07.pdf","text":"Appendix 7","size":"7.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 7"},{"id":387047,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app03.pdf","text":"Appendix 3","size":"354 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 3"},{"id":387043,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5031/coverthb.jpg"},{"id":387048,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app04.pdf","text":"Appendix 4","size":"14.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 4"},{"id":387049,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app05.pdf","text":"Appendix 5","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 5"},{"id":387050,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app06.pdf","text":"Appendix 6","size":"154 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 6"},{"id":387044,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031.pdf","text":"Report","size":"14.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031"},{"id":387055,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5031/sir20215031_app11.pdf","text":"Appendix 11","size":"21.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5031 Appendix 11"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.4393310546875,\n              43.45291889355465\n            ],\n            [\n              -112.4725341796875,\n              43.432977075795606\n            ],\n            [\n              -112.43957519531251,\n              44.06390660801777\n            ],\n            [\n              -113.389892578125,\n              44.09547572946637\n            ],\n            [\n              -113.4393310546875,\n              43.45291889355465\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/id-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/id-water\">Idaho Water Science Center</a><br>U.S. Geological Survey<br>230 Collins Road<br>Boise, Idaho 83702-4520</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Sources and Descriptions of Data</li><li>Temporal Regression</li><li>Spatial Interpolation</li><li>Spatial Optimization</li><li>Temporal Optimization</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>Appendixes</li></ul>","publishedDate":"2021-07-15","noUsgsAuthors":false,"publicationDate":"2021-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Fisher, Jason C. 0000-0001-9032-8912 jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maimer, Neil V. 0000-0003-3047-3282 nmaimer@usgs.gov","orcid":"https://orcid.org/0000-0003-3047-3282","contributorId":5659,"corporation":false,"usgs":true,"family":"Maimer","given":"Neil","email":"nmaimer@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818877,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70221916,"text":"ofr20211051 - 2021 - Groundwater and surface-water data from the C-aquifer monitoring program, Northeastern Arizona, 2012–2019","interactions":[],"lastModifiedDate":"2021-07-15T10:09:37.240431","indexId":"ofr20211051","displayToPublicDate":"2021-07-14T14:13:29","publicationYear":"2021","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":"2021-1051","displayTitle":"Groundwater and Surface-Water Data from the C-Aquifer Monitoring Program, Northeastern Arizona, 2012–2019","title":"Groundwater and surface-water data from the C-aquifer monitoring program, Northeastern Arizona, 2012–2019","docAbstract":"<p>The Coconino aquifer (C aquifer) is a regionally extensive multiple-aquifer system supplying water for municipal, agricultural, and industrial use in northeastern Arizona, northwestern New Mexico, and southeastern Utah. This report focuses on the C aquifer in the arid to semi-arid area between St. Johns, Ariz., and Flagstaff, Ariz., along the Interstate-40 corridor where an increase in groundwater withdrawals coupled with ongoing drought conditions increase the potential for substantial water-level decline within the aquifer.</p><p>The U.S. Geological Survey (USGS) C-aquifer Monitoring Program began in 2005 to establish baseline groundwater and surface-water conditions and to quantify physical and water-chemistry responses to pumping stresses and climate. This report presents data previously reported in Brown and Macy (2012) that extend back as far as the 1950s, along with new data collected from the USGS C-aquifer Monitoring Program since that publication, from water years 2012 to 2019.</p><p>Water levels in 17 wells are measured quarterly as part of the C-aquifer Monitoring Program, and five of those are continuously monitored at 15-minute intervals. Water levels in an additional 18 wells in the study area are measured periodically by the USGS or other agencies. The largest historical change in water level in the study area was a decrease of 81.20 feet in Lake Mary 1 Well near Flagstaff between 1962 and 2018. Changes in water levels were greatest around major pumping centers and in the eastern extent of the study area.</p><p>Surface-water water-quality parameters (pH, water temperature, specific conductance, and dissolved oxygen) and streamflow discharge measurements were collected and analyzed along perennial, groundwater-fed reaches of Clear Creek, Chevelon Creek, and the Little Colorado River during nine baseflow investigations of varying extent between 2005 and 2019. Both Clear Creek and Chevelon Creek gain in flow from the beginning of their perennial reaches to their outflow into the Little Colorado River. The Little Colorado River has relatively steady streamflow in the reach between where the two tributaries enter the river. Chevelon Creek showed an increase in median specific conductance during all baseflow investigations of nearly 4,000 microsiemens per centimeter (μS/cm) from near the headwaters to the confluence with the Little Colorado River; Clear Creek also showed an increase in median specific conductance of almost 5,000 μS/cm from headwaters to confluence. Water temperature, dissolved oxygen, and pH do not show substantial trends along the reaches of Clear Creek, Chevelon Creek, or the Little Colorado River.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211051","collaboration":"Prepared in cooperation with the Navajo Nation and the City of Flagstaff","usgsCitation":"Jones, C.J.R., and Robinson, M.J., 2021, Groundwater and surface-water data from the C-aquifer monitoring program, Northeastern Arizona, 2012–2019: U.S. Geological Survey Open-File Report 2021–1051, 34 p., https://doi.org/10.3133/ofr20211051.","productDescription":"vi, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-115787","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":387185,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20121196","text":"Open-File Report 2012-1196","linkHelpText":"- Groundwater, Surface-Water, and Water-Chemistry Data from C-aquifer Monitoring Program, Northeastern Arizona, 2005-11"},{"id":387177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1051/covrthb.jpg"},{"id":387178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1051/ofr20211051.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.829833984375,\n              34.27083595165\n            ],\n            [\n              -109.149169921875,\n              34.27083595165\n            ],\n            [\n              -109.149169921875,\n              36.146746777814364\n            ],\n            [\n              -111.829833984375,\n              36.146746777814364\n            ],\n            [\n              -111.829833984375,\n              34.27083595165\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_az@usgs.gov\" data-mce-href=\"mailto:dc_az@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/az-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/az-water\">Arizona Water Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>520 N. Park Avenue<br>Tucson, AZ 85719</p>","tableOfContents":"<ul><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Description of Study Area&nbsp;&nbsp;</li><li>Hydrologic Data&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>References Cited&nbsp;</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-07-14","noUsgsAuthors":false,"publicationDate":"2021-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Casey J.R. 0000-0002-6991-8026","orcid":"https://orcid.org/0000-0002-6991-8026","contributorId":223364,"corporation":false,"usgs":true,"family":"Jones","given":"Casey","email":"","middleInitial":"J.R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Michael J. 0000-0003-3855-3914","orcid":"https://orcid.org/0000-0003-3855-3914","contributorId":240588,"corporation":false,"usgs":true,"family":"Robinson","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819294,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237744,"text":"70237744 - 2021 - Event scale relationships of DOC and TDN fluxes in throughfall and stemflow diverge from stream exports in a forested catchment","interactions":[],"lastModifiedDate":"2023-08-03T21:28:06.924605","indexId":"70237744","displayToPublicDate":"2021-07-14T08:53:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Event scale relationships of DOC and TDN fluxes in throughfall and stemflow diverge from stream exports in a forested catchment","docAbstract":"<p><span>Aquatic fluxes of carbon and nutrients link terrestrial and aquatic ecosystems. Within forests, storm events drive both the delivery of carbon and nitrogen to the forest floor and the export of these solutes from the land via streams. To increase understanding of the relationships between hydrologic event character and the relative fluxes of carbon and nitrogen in throughfall, stemflow and streams, we measured dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) concentrations in each flow path for 23 events in a forested watershed in Vermont, USA. DOC and TDN concentrations increased with streamflow, indicating their export was limited by water transport of catchment stores. DOC and TDN concentrations in throughfall and stemflow decreased exponentially with increasing precipitation, suggesting that precipitation removed a portion of available sources from tree surfaces during the events. DOC and TDN fluxes were estimated for 76 events across a 2-year period. For most events, throughfall and stemflow fluxes greatly exceeded stream fluxes, but the imbalance narrowed for larger storms (&gt;30&nbsp;mm). The largest 10 stream events exported 40% of all stream event DOC whereas those same 10 events contributed 14% of all throughfall export. Approximately 2–5 times more DOC and TDN was exported from trees during rain events than left the catchment via streams annually. The diverging influence of event size on tree versus stream fluxes has important implications for forested ecosystems as hydrological events increase in intensity and frequency due to climate change.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JG006281","usgsCitation":"Ryan, K.A., Adler, T., Chalmers, A.T., Perdrial, J., Shanley, J.B., and Stubbins, A., 2021, Event scale relationships of DOC and TDN fluxes in throughfall and stemflow diverge from stream exports in a forested catchment: Journal of Geophysical Research: Biogeosciences, v. 126, no. 7, e2021JG006281, 23 p., https://doi.org/10.1029/2021JG006281.","productDescription":"e2021JG006281, 23 p.","ipdsId":"IP-128922","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":436273,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OCS8P7","text":"USGS data release","linkHelpText":"Storm Event Dissolved Organic Carbon and Total Dissolved Nitrogen Concentrations and Yields for Precipitation, Throughfall, Stemflow, and Stream Water and Hourly Streamflow and Precipitation Record for the W-9 Catchment, Sleepers River Research Watershed, 2017 and 2018 (ver. 2.0, September 2022)"},{"id":408603,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Sleepers River Research Watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -72.32144973179821,\n              44.56971018097872\n            ],\n            [\n              -72.32144973179821,\n              44.37610677503369\n            ],\n            [\n              -72.000598189831,\n              44.37610677503369\n            ],\n            [\n              -72.000598189831,\n              44.56971018097872\n            ],\n            [\n              -72.32144973179821,\n              44.56971018097872\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"126","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Ryan, Kevin A.","contributorId":298331,"corporation":false,"usgs":false,"family":"Ryan","given":"Kevin","email":"","middleInitial":"A.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":855421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adler, Thomas","contributorId":244156,"corporation":false,"usgs":false,"family":"Adler","given":"Thomas","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":855422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalmers, Ann T. 0000-0002-5199-8080","orcid":"https://orcid.org/0000-0002-5199-8080","contributorId":217381,"corporation":false,"usgs":true,"family":"Chalmers","given":"Ann","email":"","middleInitial":"T.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":855423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perdrial, Julia","contributorId":190445,"corporation":false,"usgs":false,"family":"Perdrial","given":"Julia","affiliations":[],"preferred":false,"id":855424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":855425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stubbins, Aron","contributorId":191244,"corporation":false,"usgs":false,"family":"Stubbins","given":"Aron","email":"","affiliations":[],"preferred":false,"id":855426,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70222456,"text":"70222456 - 2021 - Long-term year-round observations of magmatic CO2 emissions on Mammoth Mountain, California, USA","interactions":[],"lastModifiedDate":"2021-07-30T13:39:50.498578","indexId":"70222456","displayToPublicDate":"2021-07-14T08:37:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Long-term year-round observations of magmatic CO2 emissions on Mammoth Mountain, California, USA","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp00050\">Diffuse emission of magmatic CO<sub>2</sub><span>&nbsp;is one of the main indicators of volcanic unrest at Mammoth Mountain, but the presence of deep seasonal&nbsp;snowpack&nbsp;at the site has hindered year-round CO</span><sub>2</sub><span>&nbsp;flux observations. A permanent&nbsp;eddy covariance&nbsp;station was established at the largest area of diffuse CO</span><sub>2</sub><span>&nbsp;</span>degassing on Mammoth Mountain (Horseshoe Lake tree kill) that measured CO<sub>2</sub><span>&nbsp;</span>fluxes (<i>F</i><sub><i>c</i></sub><span>) and&nbsp;meteorological parameters&nbsp;on a half-hourly basis. From July 22, 2014 to May 24, 2020,&nbsp;</span><i>F</i><sub><i>c</i></sub><span>&nbsp;</span>ranged from −35 to 10,546 g m<sup>−2</sup><span>&nbsp;</span>d<sup>−1</sup>.<span>&nbsp;</span><i>F</i><sub><i>c</i></sub><span>&nbsp;</span>decreased on average by 53% over the study period, tracking the long-term decline in CO<sub>2</sub><span>&nbsp;</span>emissions following the last major increase that occurred at the Horseshoe Lake tree kill area from 2009 to 2011. Statistical and spectral analyses were applied to the<span>&nbsp;</span><i>F</i><sub><i>c</i></sub><span>&nbsp;</span>and ancillary meteorological parameter time series to understand (1) relationships between these parameters, (2) their dominant periodicities, and (3) changes in<span>&nbsp;</span><i>F</i><sub><i>c</i></sub><span>&nbsp;</span>that may be unexplained by meteorological forcing. Variations in detrended<span>&nbsp;</span><i>F</i><sub><i>c</i></sub><span>&nbsp;</span>(<i>F</i><sub><i>cdt</i></sub>) were most strongly correlated with wind direction and atmospheric temperature, followed by atmospheric pressure on diurnal to annual time scales, but wind direction likely exerted the most direct control on<span>&nbsp;</span><i>F</i><sub><i>cdt</i></sub>. Comparison of the smoothed (180-d span)<span>&nbsp;</span><i>F</i><sub><i>cdt</i></sub><span>&nbsp;time series to the time series of average-daily&nbsp;snow water equivalent&nbsp;measured ~1 km away suggested that snowpack may have suppressed CO</span><sub>2</sub><span>&nbsp;</span>emissions. No evidence of a change in CO<sub>2</sub><span>&nbsp;</span>emissions related to the last major seismic swarm beneath Mammoth Mountain on February 2–18, 2014 was observed.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107347","usgsCitation":"Lewicki, J.L., 2021, Long-term year-round observations of magmatic CO2 emissions on Mammoth Mountain, California, USA: Journal of Volcanology and Geothermal Research, v. 418, 107347, 13 p., https://doi.org/10.1016/j.jvolgeores.2021.107347.","productDescription":"107347, 13 p.","ipdsId":"IP-128355","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":436276,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OJ3KFK","text":"USGS data release","linkHelpText":"Long-term CO2 emissions measurements, Horseshoe Lake tree kill area, Mammoth Mountain, CA"},{"id":387587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.25659179687499,\n              37.42252593456307\n            ],\n            [\n              -118.564453125,\n              37.42252593456307\n            ],\n            [\n              -118.564453125,\n              37.89219554724437\n            ],\n            [\n              -119.25659179687499,\n              37.89219554724437\n            ],\n            [\n              -119.25659179687499,\n              37.42252593456307\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"418","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":820097,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70222564,"text":"70222564 - 2021 - A reactive transport approach to modeling cave seepage water chemistry I: Carbon isotope transformations","interactions":[],"lastModifiedDate":"2021-09-14T16:45:51.996528","indexId":"70222564","displayToPublicDate":"2021-07-14T07:58:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"A reactive transport approach to modeling cave seepage water chemistry I: Carbon isotope transformations","docAbstract":"<p><span>The majority of Critical Zone research has emphasized silicate lithologies, which are typified by relatively slow rates of reactivity and incongruent weathering. However, the relatively simpler weathering of carbonate-dominated lithology can result in secondary mineral deposits, such as speleothems, which provide a long-term archive for Critical Zone processes. In particular, carbon isotopic variability in speleothems has the potential to provide records of changes in vegetation, soil respiration, carbon stabilization in deep soils, and/or chemical weathering in the host rock. Despite this opportunity to reconstruct many Critical Zone processes, multiple influences can also make interpretion of these speleothem carbon isotope records challenging. The integration of observational data and simulations specific to karst systems offers an interpretive framework for these unique time-averaged records accumulated through the evolution of carbonate landscapes. Here, we present a forward and process-based reactive transport simulation based on a multi-year monitoring study of Blue Spring Cave in central Tennessee, USA. The simulations describe the fluid-driven weathering of limestone including explicit tracking of dissolved calcium, stable carbon, and radiocarbon isotope ratios based on reaction rates calibrated through laboratory batch reaction data. We find that calcium concentrations and radiocarbon isotope ratios are strongly influenced by the combination of fluid flow rate and soil CO</span><sub>2</sub><span>&nbsp;content, and require rapid gas phase communication between the overlying soil boundary condition and interior karst to sustain both elevated limestone weathering rates and relatively modern radiocarbon signatures. Stable carbon isotopes are largely dictated by temperature-dependent equilibrium fractionation among contemporaneous species. These simulations are extended to a wide range of parameter space to demonstrate the environmental factors that these isotope proxies record.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2021.06.041","usgsCitation":"Druhan, J., Lawrence, C., Covey, A., Giannetta, M., and Oster, J., 2021, A reactive transport approach to modeling cave seepage water chemistry I: Carbon isotope transformations: Geochimica et Cosmochimica Acta, v. 311, p. 374-400, https://doi.org/10.1016/j.gca.2021.06.041.","productDescription":"27 p.","startPage":"374","endPage":"400","ipdsId":"IP-125015","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":451520,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2021.06.041","text":"Publisher Index Page"},{"id":436277,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90OTSDY","text":"USGS data release","linkHelpText":"Data from a reactive transport modeling study of cave seepage water chemistry"},{"id":387713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"311","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Druhan, Jennifer","contributorId":245460,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":820565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Corey 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202373,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":820566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Covey, Aaron","contributorId":261749,"corporation":false,"usgs":false,"family":"Covey","given":"Aaron","email":"","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":820567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giannetta, Max","contributorId":261750,"corporation":false,"usgs":false,"family":"Giannetta","given":"Max","email":"","affiliations":[{"id":35161,"text":"University of Illinois, Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":820568,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oster, Jessica","contributorId":223020,"corporation":false,"usgs":false,"family":"Oster","given":"Jessica","email":"","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":820569,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70222526,"text":"70222526 - 2021 - Urbanization impacts on evapotranspiration across various spatio-temporal scales","interactions":[],"lastModifiedDate":"2021-08-03T12:57:40.484127","indexId":"70222526","displayToPublicDate":"2021-07-14T07:55:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Urbanization impacts on evapotranspiration across various spatio-temporal scales","docAbstract":"<div class=\"article-section__content en main\"><p>Urbanization has been shown to locally increase the nighttime temperatures creating urban heat islands, which partly arise due to evapotranspiration (ET) reduction. It is unclear how the direction and magnitude of the change in local ET due to urbanization varies globally across different climatic regimes. This knowledge gap is critical, both for the key role of ET in the energy and water balance accounting for the majority of local precipitation, and for reducing the urban heat island effect. We explore and assess the impacts of urbanization on monthly and mean annual ET across a range of landscapes from local to global spatial scales. Remotely sensed land cover and ET available at 1&nbsp;km resolution are used to quantify the differences in ET between urban and surrounding non-urban areas across the globe. The observed patterns show that the statistically significant difference between urban and non-urban ET can be estimated to first order as a function of local hydroclimate, with arid regions seeing increased ET, and humid regions showing decreased ET. Cities under cold climates also evaporate more than their non-urban surroundings during the winter, as the urban micro-climate has increased energy availability resulting from human activities. Increased ET in arid cities arises from municipal water withdrawals and increased irrigation during drought conditions. These results can help inform planners to improve the integration of environmental conditions into the design and management of urban landscapes.</p></div>","language":"English","publisher":"Wiley","doi":"10.1029/2021EF002045","usgsCitation":"Mazrooei, A., Reitz, M., Wang, D., and Sankarasubramanian, A., 2021, Urbanization impacts on evapotranspiration across various spatio-temporal scales: Earth's Future, v. 9, no. 8, e2021EF002045, 15 p., https://doi.org/10.1029/2021EF002045.","productDescription":"e2021EF002045, 15 p.","ipdsId":"IP-116430","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":489022,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ef002045","text":"Publisher Index Page"},{"id":436278,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93SYCF4","text":"USGS data release","linkHelpText":"Urbanization Impacts on Evapotranspiration Across Various Spatio-temporal Scales"},{"id":387653,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Mazrooei, Amirhossein","contributorId":241036,"corporation":false,"usgs":false,"family":"Mazrooei","given":"Amirhossein","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":820466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reitz, Meredith 0000-0001-9519-6103 mreitz@usgs.gov","orcid":"https://orcid.org/0000-0001-9519-6103","contributorId":196694,"corporation":false,"usgs":true,"family":"Reitz","given":"Meredith","email":"mreitz@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":820467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Dingbao","contributorId":166993,"corporation":false,"usgs":false,"family":"Wang","given":"Dingbao","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":820468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankarasubramanian, A. 0000-0002-7668-1311","orcid":"https://orcid.org/0000-0002-7668-1311","contributorId":241034,"corporation":false,"usgs":false,"family":"Sankarasubramanian","given":"A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":820469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70222566,"text":"70222566 - 2021 - A reactive transport approach to modeling cave seepage water chemistry II: Elemental signatures","interactions":[],"lastModifiedDate":"2021-09-14T16:44:59.280495","indexId":"70222566","displayToPublicDate":"2021-07-14T07:53:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"A reactive transport approach to modeling cave seepage water chemistry II: Elemental signatures","docAbstract":"<p><span>Karst&nbsp;systems are useful for examining spatial and temporal variability in Critical Zone processes because they provide a window into the subsurface where waters have interacted with vegetation, soils,&nbsp;regolith, and&nbsp;bedrock&nbsp;across a range of length and timescales. These hydrologic pathways frequently include the precipitation of&nbsp;speleothems, which provide long-term archives of climate and environmental change. Trace element ratios in speleothems (Mg/Ca, Sr/Ca, Ba/Ca) have the potential to provide information about past changes in rainfall and&nbsp;infiltration, but controls on them can be complex and their interpretation must be based on an understanding of the modern cave system. Here we integrate observations of surface conditions, bedrock, soil, and drip water chemistry of Blue Spring Cave in Tennessee, USA with the reactive transport model CrunchTope, which we have calibrated for karst systems to investigate the primary controls on trace element variations in cave&nbsp;seepage waters. We find that measured drip water Mg/Ca and Sr/Ca are captured within the model through variable amounts of&nbsp;limestone&nbsp;dissolution followed by precipitation of secondary&nbsp;calcite&nbsp;that happens within the cave rather than the host limestone. However, strong spatial controls on drip water Mg/Ca and Sr/Ca likely reflect seepage water interactions with variable amounts of diagenetic phases in the host rock. In contrast, Ba/Ca values are consistent across the cave and vary with effective rainfall, suggesting that this parameter may be the most consistent metric for limestone dissolution and prior calcite precipitation and can act as a proxy for rainfall and infiltration in this cave system. Our findings emphasize the importance of evaluating spatial heterogeneity in cave drip waters and outline a novel modeling approach for determining the dominant controls on drip water chemistry in support of the interpretations of&nbsp;</span>paleoclimate<span>&nbsp;records.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2021.06.040","usgsCitation":"Oster, J., Covey, A., Lawrence, C., Giannetta, M., and Druhan, J., 2021, A reactive transport approach to modeling cave seepage water chemistry II: Elemental signatures: Geochimica et Cosmochimica Acta, v. 311, p. 353-373, https://doi.org/10.1016/j.gca.2021.06.040.","productDescription":"21 p.","startPage":"353","endPage":"373","ipdsId":"IP-125017","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":451523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2021.06.040","text":"Publisher Index Page"},{"id":387712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"311","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oster, Jessica","contributorId":223020,"corporation":false,"usgs":false,"family":"Oster","given":"Jessica","email":"","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":820570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Covey, Aaron","contributorId":261749,"corporation":false,"usgs":false,"family":"Covey","given":"Aaron","email":"","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":820571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Corey 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202373,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":820572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giannetta, Max","contributorId":261750,"corporation":false,"usgs":false,"family":"Giannetta","given":"Max","email":"","affiliations":[{"id":35161,"text":"University of Illinois, Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":820573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Druhan, Jennifer","contributorId":245460,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":820574,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70222111,"text":"70222111 - 2021 - Influence of invasive submerged aquatic vegetation (E. densa) on currents and sediment transport in a freshwater tidal system","interactions":[],"lastModifiedDate":"2021-09-14T16:29:41.086323","indexId":"70222111","displayToPublicDate":"2021-07-14T06:57:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Influence of invasive submerged aquatic vegetation (<i>E. densa</i>) on currents and sediment transport in a freshwater tidal system","title":"Influence of invasive submerged aquatic vegetation (E. densa) on currents and sediment transport in a freshwater tidal system","docAbstract":"<p>We present a field study combining measurements of vegetation density, vegetative drag, and reduction of suspended-sediment concentration (SSC) within patches of the invasive submerged aquatic plant<span>&nbsp;</span><i>Egeria densa</i>. Our study was motivated by concern that sediment trapping by<span>&nbsp;</span><i>E. densa</i>, which has proliferated in the Sacramento–San Joaquin Delta, is impacting marsh accretion and reducing turbidity. In the freshwater tidal Delta,<span>&nbsp;</span><i>E. densa</i><span>&nbsp;</span>occupies shallow regions, frequently along channel margins. We investigated two sites: Lindsey Slough, a muddy low-energy backwater, and the lower Mokelumne River, with stronger currents and sandy bed sediments. At the two sites biomass density, frontal area, and areal density of the submerged aquatic vegetation (SAV) were similar. Current attenuation within<span>&nbsp;</span><i>E. densa</i><span>&nbsp;</span>exceeded 90% and the vegetative drag coefficient followed<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/8648ae5f-3564-44db-b169-853d0b427cee/wrcr25436-math-0001.png\" alt=\"urn:x-wiley:00431397:media:wrcr25436:wrcr25436-math-0001\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/8648ae5f-3564-44db-b169-853d0b427cee/wrcr25436-math-0001.png\">, where<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/aac64a41-503a-4972-abb5-4b9942cce2b7/wrcr25436-math-0002.png\" alt=\"urn:x-wiley:00431397:media:wrcr25436:wrcr25436-math-0002\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/aac64a41-503a-4972-abb5-4b9942cce2b7/wrcr25436-math-0002.png\"><span>&nbsp;</span>is stem Reynolds number. The SAV reduced SSC by an average of 18% in Lindsey Slough. At Mokelumne River the reduction ranged 0–40%, with greatest trapping when discharge and SSC were elevated. This depletion of SSC decreases the transport of sediment to marshes by the same percentage, as the rising tide must pass through fringing SAV before reaching marshes. Sediment trapping in<span>&nbsp;</span><i>E. densa</i><span>&nbsp;</span>in the Delta is limited by low flux through the canopy and low settling velocity of suspended sediment (mostly flocculated mud). Sediment trapping by SAV has the potential to reduce channel SSC, but the magnitude and sign of the effect can vary with local factors including vegetative coverage and the depositional or erosional nature of the setting.</p>","language":"English","publisher":"Wiley","doi":"10.1029/2020WR028789","usgsCitation":"Lacy, J.R., Foster-Martinez, M.R., Allen, R.M., and Drexler, J.Z., 2021, Influence of invasive submerged aquatic vegetation (E. densa) on currents and sediment transport in a freshwater tidal system: Water Resources Research, v. 57, e2020WR028789, 22 p., https://doi.org/10.1029/2020WR028789.","productDescription":"e2020WR028789, 22 p.","ipdsId":"IP-119960","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":387286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.83288574218749,\n              37.67512527892127\n            ],\n            [\n              -120.311279296875,\n              37.67512527892127\n            ],\n            [\n              -120.311279296875,\n              38.66192241975437\n            ],\n            [\n              -121.83288574218749,\n              38.66192241975437\n            ],\n            [\n              -121.83288574218749,\n              37.67512527892127\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"57","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":819563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster-Martinez, Madeline R.","contributorId":201705,"corporation":false,"usgs":false,"family":"Foster-Martinez","given":"Madeline","email":"","middleInitial":"R.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":819564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Rachel M. 0000-0002-0287-6466","orcid":"https://orcid.org/0000-0002-0287-6466","contributorId":261242,"corporation":false,"usgs":false,"family":"Allen","given":"Rachel","email":"","middleInitial":"M.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":819565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":819566,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70221897,"text":"ofr20211061 - 2021 - Spatial and temporal distribution of radio-tagged Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) suckers in Clear Lake Reservoir and associated spawning tributaries, Northern California, 2015–17","interactions":[],"lastModifiedDate":"2021-07-14T18:43:40.52114","indexId":"ofr20211061","displayToPublicDate":"2021-07-13T13:15:14","publicationYear":"2021","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":"2021-1061","displayTitle":"Spatial and Temporal Distribution of Radio-Tagged Lost River (<em>Deltistes luxatus</em>) and Shortnose (<em>Chasmistes brevirostris</em>) Suckers in Clear Lake Reservoir and Associated Spawning Tributaries, Northern California, 2015–17","title":"Spatial and temporal distribution of radio-tagged Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) suckers in Clear Lake Reservoir and associated spawning tributaries, Northern California, 2015–17","docAbstract":"<h1>Executive Summary</h1><p class=\"p1\">Data from a multi-year radio telemetry study were used to assess seasonal distribution patterns for two long-lived, federally endangered catostomids across substantially different water conditions in Clear Lake Reservoir, northern California. Lost River (<i>Deltistes luxatus</i>) and shortnose (<i>Chasmistes brevirostris</i>) suckers, two species endemic to the Klamath Basin, were implanted with radio transmitters in each of 3 years in an effort to expand our understanding of seasonal sucker movements within the reservoir and their migrations in spawning tributaries. Clear Lake Reservoir and its tributaries are part of a critical management unit within the Lost River Basin Recovery Unit for populations of Lost River and shortnose suckers. We documented residency and migratory behaviors and how behaviors were affected by lake surface elevations and water management practices.</p><p class=\"p1\">Adult suckers were captured during autumn trammel net sampling in the west lobe of the reservoir and implanted with internal radio transmitters. A total of 163 suckers were radio-tagged (75 in 2014, 64 in 2015, and 24 in 2016); 27 more shortnose suckers were tagged than Lost River suckers to reflect the larger population of shortnose suckers in the reservoir. Sex ratios were approximately equal for each species. Aerial telemetry surveys were used to monitor radio-tagged fish from January 20 to December 2 each year and to document the upstream extent of spawning migrations in the tributaries. Surveys were scheduled more frequently during the spawning season (February–June) when suckers are known to move out of the reservoir and into spawning tributaries.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211061","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Banet, N.V., Hewitt, D.A., Dolan-Caret, A., and Harris, A.C., 2021, Spatial and temporal distribution of radio-tagged Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) suckers in Clear Lake Reservoir and associated spawning tributaries, Northern California, 2015–17: U.S. Geological Survey Open-File Report 2021–1061, 37 p., https://doi.org/10.3133/ofr20211061.","productDescription":"vi, 37 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-120279","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":387167,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2021/1061/ofr20211061_landing.html","text":"Animated movements and migrations","description":"OFR 2021-1061 Animated movements and migrations."},{"id":387166,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1061/ofr20211061.pdf","text":"Report","size":"12.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1061"},{"id":387165,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1061/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.25610351562499,\n              41.78616105896385\n            ],\n            [\n              -121.03637695312499,\n              41.78616105896385\n            ],\n            [\n              -121.03637695312499,\n              41.93548729665268\n            ],\n            [\n              -121.25610351562499,\n              41.93548729665268\n            ],\n            [\n              -121.25610351562499,\n              41.78616105896385\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wfrc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/wfrc\">Western Fisheries Research Center</a><br>U.S. Geological Survey<br>6505 NE 65th Street<br>Seattle, Washington 98115-5016</p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Description of Study Area</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2021-07-13","noUsgsAuthors":false,"publicationDate":"2021-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Banet, Nathan 0000-0002-8537-1702","orcid":"https://orcid.org/0000-0002-8537-1702","contributorId":217751,"corporation":false,"usgs":true,"family":"Banet","given":"Nathan","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dolan-Caret, Amari 0000-0001-9155-6116 amaridc@usgs.gov","orcid":"https://orcid.org/0000-0001-9155-6116","contributorId":149805,"corporation":false,"usgs":true,"family":"Dolan-Caret","given":"Amari","email":"amaridc@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Alta C. 0000-0002-2123-3028 aharris@usgs.gov","orcid":"https://orcid.org/0000-0002-2123-3028","contributorId":3490,"corporation":false,"usgs":true,"family":"Harris","given":"Alta C.","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819254,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70221881,"text":"fs20213039 - 2021 - Arizona and Landsat","interactions":[],"lastModifiedDate":"2023-01-24T11:49:54.477263","indexId":"fs20213039","displayToPublicDate":"2021-07-13T11:47:03","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-3039","displayTitle":"Arizona and Landsat","title":"Arizona and Landsat","docAbstract":"<p>Arizona is a land of massive grandeur, deep gorges, lofty mountains, immense plains, and elevated mesas—and, without question, its crown jewel is the Grand Canyon. The spectacular canyon, one of the seven natural wonders of the world, was created when the Colorado River carved a channel through northern Arizona, revealing nearly two billion years of the Earth's history.</p><p>Yet, for all its ancient beauty, Arizona and its landscapes are experiencing a transformation.</p><p>Arizonans face more extreme temperatures and drought because of climate change. Amid a drought in the western United States, Lake Mead, one of Arizona's main water resources, dropped to a record low level in June 2021. Climate change is making extreme weather events such as dust storms and heat waves more common, posing higher risks to human health, according to the Centers for Disease Control and Prevention.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213039","usgsCitation":"U.S. Geological Survey, 2021, Arizona and Landsat (ver. 1.1, January 2023): U.S. Geological Survey Fact Sheet 2021–3039, 2 p., https://doi.org/10.3133/fs20213039.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-130596","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":412226,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20213039/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":412182,"rank":5,"type":{"id":34,"text":"Image 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 \"}}]}","edition":"Version 1.0: July 13, 2021; Version 1.1: January 23, 2023","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a> <br>U.S. Geological Survey<br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Water Usage</li><li>Fire Modeling</li><li>Urban Sprawl</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-07-13","revisedDate":"2023-01-23","noUsgsAuthors":false,"publicationDate":"2021-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":819201,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70224340,"text":"70224340 - 2021 - Responses of soil extracellular enzyme activities and bacterial community composition to seasonal stages of drought in a semiarid grassland","interactions":[],"lastModifiedDate":"2021-09-23T12:02:51.662738","indexId":"70224340","displayToPublicDate":"2021-07-12T06:59:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Responses of soil extracellular enzyme activities and bacterial community composition to seasonal stages of drought in a semiarid grassland","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">Extreme drought can strongly impact belowground communities and biogeochemical processes, including soil microbial community composition and extracellular enzyme activities (EEAs), which are considered key agents in ecosystem carbon (C) and nutrient cycling. However, our understanding of how seasonal timing of drought during the growing season affects soil microbial communities and their activity remains notably poor. In this study, we investigated the responses of soil physicochemical properties, EEAs, and bacterial community composition to extreme-duration drought imposed in the early-, mid-, or late-stages of the growing season in a semiarid grassland ecosystem in Inner Mongolia, China. Compared with the ambient control, the activities of C-, nitrogen (N)-, and phosphorus (P)-acquisition enzymes were significantly decreased in the mid- and/or late-stages of drought. Bacterial community diversity also significantly decreased in the mid- and late-stage drought treatments. Soil water content was the most important factor explaining changes in soil EEAs and bacterial community composition. At the end of the growing season, the activities of C-, N-, and P-acquisition enzymes had mostly recovered, while the bacterial community diversity in the mid- and late-stage drought treatments was still lower than the ambient control. Overall, our study demonstrates that the effects of extreme drought on soil EEAs and bacterial community composition depend on the timing of drought. Our results highlight that understanding the effects of extreme-duration drought at different stages of the growing season may play a vital role in predicting the responses of belowground function to global changes in grassland ecosystems.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2021.115327","usgsCitation":"Gao, W., Reed, S., Munson, S.M., Rui, Y., Fan, W., Zheng, Z., Li, L., Che, R., Xue, K., Du, J., Cui, X., Wang, Y., and Hao, Y., 2021, Responses of soil extracellular enzyme activities and bacterial community composition to seasonal stages of drought in a semiarid grassland: Geoderma, v. 401, 115327, 11 p., https://doi.org/10.1016/j.geoderma.2021.115327.","productDescription":"115327, 11 p.","ipdsId":"IP-127998","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":451546,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2021.108528","usgsCitation":"Irvin, J., Zhou, S., McNicol, G., Lu, F., Liu, V., Fluet-Chouinard, E., Ouyang, Z., Knox, S., Lucas-Moffat, A., Trotta, C., Papale, D., Vitale, D., Mammarella, I., Alekseychik, P., Aurela, M., Avati, A., Baldocchi, D., Bansal, S., Bohrer, G., Campbell, D.I., Chen, J., Chu, H., Dalmagro, H.J., Delwiche, K.B., Desai, A.R., Euskirchen, E.S., Feron, S., Goeckede, M., Heimann, M., Helbig, M., Helfter, C., Hemes, K.S., Hirano, T., Iwata, H., Jurasinski, G., Kalhori, A., Kondrich, A., Lai, D., Lohila, A., Malholtra, A., Merbold, L., Mitra, B., Ng, A., Nilsson, M.B., Noormets, A., Peichl, M., Rey-Sanchez, A.C., Richardson, A.D., Runkle, B.R., Schafer, K.V., Sonnentag, O., Stuart-Haëntjens, E., Sturtevant, C., Ueyama, M., Valach, A.C., Vargas, R., Vourlitis, G.L., Ward, E., Wong, G.X., Zona, D., Alberto, M.C., Billesbach, D.P., Celis, G., Dolman, H., Friborg, T., Fuchs, K., Gogo, S., Gondwe, M.J., Goodrich, J.P., Gottschalk, P., Hortnagl, L., Jacotot, A., Koebsch, F., Kasak, K., Maier, R., Morin, T.H., Nemitz, E., Oechel, W.C., Oikawa, P.Y., Ono, K., Sachs, T., Sakabe, A., Schuur, E.A., Shortt, R., Sullivan, R.C., Szutu, D.J., Tuittila, E., Varlagin, A., Verfaillie, J.G., Wille, C., Windham-Myers, L., Poulter, B., and Jackson, R.B., 2021, Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands: Agricultural and Forest Meteorology, v. 308–309, 108528, 22 p., https://doi.org/10.1016/j.agrformet.2021.108528.","productDescription":"108528, 22 p.","ipdsId":"IP-126298","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":451557,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2021.108528","text":"Publisher Index Page"},{"id":410275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"308–309","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Irvin, Jeremy","contributorId":299776,"corporation":false,"usgs":false,"family":"Irvin","given":"Jeremy","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhou, Sharon","contributorId":299777,"corporation":false,"usgs":false,"family":"Zhou","given":"Sharon","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNicol, Gavin 0000-0002-6655-8045","orcid":"https://orcid.org/0000-0002-6655-8045","contributorId":260536,"corporation":false,"usgs":false,"family":"McNicol","given":"Gavin","email":"","affiliations":[],"preferred":false,"id":858604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Fred","contributorId":299807,"corporation":false,"usgs":false,"family":"Lu","given":"Fred","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liu, Vincent","contributorId":299778,"corporation":false,"usgs":false,"family":"Liu","given":"Vincent","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858606,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fluet-Chouinard, Etienne","contributorId":217392,"corporation":false,"usgs":false,"family":"Fluet-Chouinard","given":"Etienne","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":858607,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ouyang, Zutao","contributorId":260556,"corporation":false,"usgs":false,"family":"Ouyang","given":"Zutao","email":"","affiliations":[],"preferred":false,"id":858608,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knox, Sara Helen 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":272609,"corporation":false,"usgs":false,"family":"Knox","given":"Sara Helen","affiliations":[{"id":56388,"text":"U. 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,{"id":70221786,"text":"ofr20211064 - 2021 - Instruments, methods, rationale, and derived data used to quantify and compare the trapping efficiencies of four types of pressure-difference bedload samplers","interactions":[],"lastModifiedDate":"2021-07-09T18:52:23.587817","indexId":"ofr20211064","displayToPublicDate":"2021-07-09T11:55:00","publicationYear":"2021","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":"2021-1064","displayTitle":"Instruments, Methods, Rationale, and Derived Data Used to Quantify and Compare the Trapping Efficiencies of Four Types of Pressure-Difference Bedload Samplers","title":"Instruments, methods, rationale, and derived data used to quantify and compare the trapping efficiencies of four types of pressure-difference bedload samplers","docAbstract":"<p>Bedload and ancillary data were collected to calculate and compare the bedload trapping efficiencies of four types of pressure-difference bedload samplers as part of episodic, sediment-recirculating flume experiments at the St. Anthony Falls Laboratory, University of Minnesota, Minneapolis, in January–March 2006. The bedload-sampler experiments, which were conceived, organized, and led by the U.S. Geological Survey’s Office of Surface Water, were part of a broader suite of experiments performed in the rectangular, concrete-lined, sediment-recirculating Main Channel Facility (“main channel flume”). Collectively referred to as “StreamLab06,” the experiments were conducted under the auspices of the National Center for Earth-Surface Dynamics, University of Minnesota.</p><p>Four pressure-difference-type bedload samplers—a standard Helley-Smith, US BLH-84, Elwha, and Toutle River-2—were deployed by using hand-held rods in the main flume in a series of trials during steady flows as part of the first two of seven phases of the StreamLab06 experiments. The Phase I flows were released over a sand bed. Gravel composed the bed during the Phase II flows. Bedload samples were collected during flows ranging from 2.0 cubic meters per second (near the incipient motion of bed material) to 5.5 cubic meters per second. A total of 2,030 bedload samples were collected—1,000 as part of 19 sand-bed trials, and 1,030 as part of 27 gravel-bed trials.</p><p>Bedload was captured in five contiguous weigh drums inside a slot spanning the full width of the main flume channel 8.5 meters downstream from the cross-section in which the bedload samplers were deployed. The contents of each drum were automatically weighed and recorded as a time series about every 1.1 seconds. Each drum automatically, independently, and episodically dumped its contents into the bottom of the slot upon the accumulation of a pre-determined mass of entrapped sediment, after which the drum continued to capture and weigh bedload. An auger at the bottom of the slot evacuated the accumulating sediment to a side-channel pump that piped the captured sediments upstream and discharged them back to the flume.</p><p>Bedload-transport rates were calculated from measurements of the masses of material trapped by the bedload samplers and from the data produced by the automated bedload capture-and-weigh system of the main channel flume. These data were used to compute at-a-point and mean bedload-transport rates for subsequent use in developing bedload-trapping efficiency (calibration) coefficients for each bedload sampler and for comparing the relative trapping efficiencies of the manually deployed bedload samplers. The data were collected to enable the use of several computational methods for deriving bedload-trapping coefficients.</p><p>Continuous ancillary data including stage, water discharge, and water temperature were automatically collected and stored. Flow depths were manually measured and recorded concurrent with each at-a-point bedload-sampler deployment. Other information obtained during parts of the experiments included longitudinal water-surface slope, bedload particle-size distributions, and suspended-sediment concentrations and percent sand analyzed from samples collected by depth integration with a US DH-48 isokinetic suspended-sediment sampler.</p><p>This report describes the types and availability of the bedload and ancillary data derived through the StreamLab06 experiments. The data are available from the St. Anthony Falls Laboratory and the U.S. Geological Survey through a data release. Also included are selected descriptive and historical information as well as the background, experimental design, experimental caveats, and other factors relevant to the production of the bedload-transport and ancillary data produced through Phases I and II of the StreamLab06 experiments.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211064","usgsCitation":"Gray, J.R., Schwarz, G.E., Dean, D.J., Czuba, J.A., and Groten, J.T., 2021, Instruments, methods, rationale, and derived data used to quantify and compare the trapping efficiencies of four types of pressure-difference bedload samplers: U.S. Geological Survey Open-File Report 2021–1064, 61 p., https://doi.org/10.3133/ofr20211064.","productDescription":"Report: vii, 61 p.; Data Release","numberOfPages":"61","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098017","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":386969,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1064/ofr20211064.pdf","text":"Report","size":"70.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1064"},{"id":386970,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1064/coverthb.jpg"},{"id":386971,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VBB2YF","text":"USGS data release","linkHelpText":"Data describing the trapping efficiency of four types of pressure-difference bedload samplers, St. Anthony Falls Laboratory, Minneapolis, Minnesota, 2006"}],"contact":"<p>Chief, Analysis and Prediction Branch<br><a href=\"https://www.usgs.gov/mission-areas/water-resources\" data-mce-href=\"https://www.usgs.gov/mission-areas/water-resources\">Water Resources Mission Area</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Mail Stop 415<br>Reston, VA 20192</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Historical Pressure-Difference Bedload-Sampler Trapping Efficiency Comparisons and Calibrations</li><li>Rationale for the StreamLab06 Bedload-Sampler Calibration Experiments</li><li>The StreamLab06 Bedload-Sampler Trapping-Efficiency Tests</li><li>Bedload and Ancillary Data</li><li>References Cited</li><li>Appendix 1</li><li>Appendix 2</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2021-07-09","noUsgsAuthors":false,"publicationDate":"2021-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Gray, John R. 0000-0002-8817-3701 jrgray@usgs.gov","orcid":"https://orcid.org/0000-0002-8817-3701","contributorId":1158,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jrgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":818702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":213621,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory","email":"gschwarz@usgs.gov","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":818703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dean, David J. 0000-0003-0203-088X djdean@usgs.gov","orcid":"https://orcid.org/0000-0003-0203-088X","contributorId":131047,"corporation":false,"usgs":true,"family":"Dean","given":"David","email":"djdean@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":818704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Czuba, Jonathan A. 0000-0002-9485-2604","orcid":"https://orcid.org/0000-0002-9485-2604","contributorId":150072,"corporation":false,"usgs":true,"family":"Czuba","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818705,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Groten, Joel T. 0000-0002-0441-8442 jgroten@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-8442","contributorId":173464,"corporation":false,"usgs":true,"family":"Groten","given":"Joel","email":"jgroten@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818706,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70221822,"text":"sir20215027 - 2021 - Occurrence and distribution of mercury in streams and reservoirs in the Triangle Area of North Carolina, July 2007–June 2009","interactions":[],"lastModifiedDate":"2021-07-09T18:48:34.290205","indexId":"sir20215027","displayToPublicDate":"2021-07-09T08:49:28","publicationYear":"2021","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":"2021-5027","displayTitle":"Occurrence and Distribution of Mercury in Streams  and Reservoirs in the Triangle Area of North Carolina, July 2007–June 2009","title":"Occurrence and distribution of mercury in streams and reservoirs in the Triangle Area of North Carolina, July 2007–June 2009","docAbstract":"<p>During the time period 2001–2006, the U.S. Geological Survey reported mercury-concentration measurements that exceeded the North Carolina water-quality criterion (NCWQC) of 0.012 microgram per liter for total recoverable mercury in streams and reservoirs across the Triangle Area of North Carolina. Mercury data were sparse, however, generally consisting of only one or two water samples per year. Additional monitoring and data analysis were needed to better determine the occurrence and distribution of mercury in the Triangle Area for all seasons and waterbody types as well as associations between mercury concentrations and water-quality and land-use parameters. Water at fifteen reservoir and 14 stream sites across the Triangle Area was sampled at various times between August 2007 and June 2009, with water samples collected from both the surfaces and bottoms of the water columns in reservoirs and from the surfaces of streams. A bed sediment sample was also collected at all reservoir sites and at all but one stream site. A total of 301 water samples was collected at reservoir sites. Filtered and total recoverable mercury were detected in at least one water sample collected from each reservoir site. A total of 77 water samples was collected from stream sites with filtered mercury detected in samples from one-half of these sites, and total recoverable mercury detected in at least one water sample from all but two sites. Total recoverable and filtered mercury concentrations exceeded the NCWQC for mercury more frequently in reservoir than in stream samples. Differences in sampling frequencies among seasons and between streams and reservoirs, however, may have negatively biased overall estimates of mercury concentrations in streams relative to reservoirs. Filtered mercury concentrations in surface-water samples from reservoirs and total recoverable mercury concentrations in bottom samples from reservoirs were highest in the fall, whereas no seasonal trends in filtered or total recoverable mercury were detected from stream samples. Total mercury concentrations were calculated for the bulk sample on the basis of the percentage of the grains in the bulk sample whose diameters that were smaller than 0.0625 millimeters. Total mercury concentrations in bed sediment were generally higher for samples from reservoir sites compared to streams sites, although the highest total mercury concentration in bed sediment was from a stream site. Concentrations of total recoverable mercury in water samples from stream sites all fell within the general range for streams and lakes without on-site significant anthropogenic sources (for example, mercury mines or industrial pollution), whereas samples collected from eight reservoir sites had total mercury concentrations in a range characteristic of sites affected by mercury mines or industrial pollution. Results suggested that litterfall may be a source of mercury in streams, whereas atmospheric deposition is likely a dominant source for reservoirs; however, high concentrations of filtered and total recoverable mercury concentrations in the fall season in some reservoir-water samples may warrant further analysis of potential hydrologic factors. Mercury concentrations in all water and bed sediment samples were below levels expected to cause adverse effects to humans and aquatic biota, indicating that mercury levels at the study sites in the Triangle Area were unlikely to cause an immediate health risk to humans or aquatic organisms. The high variability among several sample replicates for total recoverable mercury, however, indicated that inferences from total recoverable mercury concentrations can be tenuous.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215027","collaboration":"Prepared in cooperation with the Triangle Area Water Supply Monitoring Project Steering Committee","usgsCitation":"McKee, A.M., Fitzgerald, S., and Giorgino, M., 2021, Occurrence and distribution of mercury in streams and reservoirs in the Triangle Area of North Carolina, July 2007–June 2009: U.S. Geological Survey Scientific Investigations Report 2021–5027, 42 p., https://doi.org/10.3133/sir20215027.","productDescription":"Report: x, 42 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-114002","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":387025,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S4EMC7","text":"USGS Data Release","linkHelpText":"Water and bed sediment data associated with the occurrence and distribution of mercury in streams and reservoirs in the Triangle Area of North Carolina, July 2007 -June 2009"},{"id":387023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5027/coverthb.jpg"},{"id":387024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5027/sir20215027.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5027"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.64263916015625,\n              35.31512519050729\n            ],\n            [\n              -78.12103271484375,\n              35.31512519050729\n            ],\n            [\n              -78.12103271484375,\n              36.49859745028132\n            ],\n            [\n              -79.64263916015625,\n              36.49859745028132\n            ],\n            [\n              -79.64263916015625,\n              35.31512519050729\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/sa-water\" data-mce-href=\"https://www.usgs.gov/centers/sa-water\">South Atlantic Water Science Center</a><br>U.S. Geological Survey<br>1770 Corporate Drive, Suite 500<br>Norcross, GA 30093</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>References Cited</li><li>Appendix 1. Randomly Generated Numbers Below the Method Detection Level for Use in Statistical Analysis</li><li>Appendix 2. Accuracy of Bed Sediment Total Mercury and Total Organic-Carbon Analyses Determined for Reference Materials</li><li>Appendix 3. Precision of Constituent Analyses in Replicate Water Samples</li></ul>","publishedDate":"2021-07-09","noUsgsAuthors":false,"publicationDate":"2021-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"McKee, Anna M. 0000-0003-2790-5320 amckee@usgs.gov","orcid":"https://orcid.org/0000-0003-2790-5320","contributorId":166725,"corporation":false,"usgs":true,"family":"McKee","given":"Anna","email":"amckee@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzgerald, Sharon 0000-0002-6288-867X safitzge@usgs.gov","orcid":"https://orcid.org/0000-0002-6288-867X","contributorId":139701,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Sharon","email":"safitzge@usgs.gov","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giorgino, Mary J. 0000-0001-7152-1856 giorgino@usgs.gov","orcid":"https://orcid.org/0000-0001-7152-1856","contributorId":205646,"corporation":false,"usgs":true,"family":"Giorgino","given":"Mary","email":"giorgino@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818855,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70222569,"text":"70222569 - 2021 - Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll-a in north temperate lakes","interactions":[],"lastModifiedDate":"2021-09-14T16:43:21.140757","indexId":"70222569","displayToPublicDate":"2021-07-09T07:14:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll-<i>a</i> in north temperate lakes","title":"Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll-a in north temperate lakes","docAbstract":"<p><span>Winter conditions, such as ice cover and snow accumulation, are changing rapidly at northern latitudes and can have important implications for lake processes. For example, snowmelt in the watershed—a defining feature of lake hydrology because it delivers a large portion of annual nutrient inputs—is becoming earlier. Consequently, earlier and a shorter duration of snowmelt are expected to affect annual phytoplankton biomass. To test this hypothesis, we developed an index of runoff timing based on the date when 50% of cumulative runoff between January 1 and May 31&nbsp;had occurred. The runoff index was computed using stream discharge for inflows, outflows, or for flows from nearby streams for 41&nbsp;lakes in Europe and North America. The runoff index was then compared with summer chlorophyll-</span><i>a</i><span>&nbsp;(Chl-</span><i>a</i><span>) concentration (a proxy for phytoplankton biomass) across 5–53&nbsp;years for each lake. Earlier runoff generally corresponded to lower summer Chl-</span><i>a</i><span>. Furthermore, years with earlier runoff also had lower winter/spring runoff magnitude, more protracted runoff, and earlier ice-out. We examined several lake characteristics that may regulate the strength of the relationship between runoff timing and summer Chl-</span><i>a</i><span>&nbsp;concentrations; however, our tested covariates had little effect on the relationship. Date of ice-out was not clearly related to summer Chl-</span><i>a</i><span>&nbsp;concentrations. Our results indicate that ongoing changes in winter conditions may have important consequences for summer phytoplankton biomass and production.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15797","usgsCitation":"Hrycik, A.R., Isles, P.D., Adrian, R., Albright, M., Bacon, L.C., Berger, S.A., Bhattacharya, R., Grossart, H., Hejzlar, J., Hetherington, A.L., Knoll, L.B., Laas, A., McDonald, C.P., Merrell, K., Nejstgaard, J.C., Nelson, K., Noges, P., Paterson, A.M., Pilla, R.M., Robertson, D., Rudstam, L.G., Rusak, J.A., Sadro, S., Silow, E.A., Stockwell, J.D., Yao, H., Yokota, K., and Pierson, D.C., 2021, Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll-a in north temperate lakes: Global Change Biology, v. 27, no. 19, p. 4615-4629, https://doi.org/10.1111/gcb.15797.","productDescription":"15 p.","startPage":"4615","endPage":"4629","ipdsId":"IP-121909","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":451574,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/111965","text":"External Repository"},{"id":387703,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"19","noUsgsAuthors":false,"publicationDate":"2021-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Hrycik, Allison R. 0000-0002-0870-3398","orcid":"https://orcid.org/0000-0002-0870-3398","contributorId":217379,"corporation":false,"usgs":false,"family":"Hrycik","given":"Allison","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":820575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Isles, Peter D. F. 0000-0003-4446-6788","orcid":"https://orcid.org/0000-0003-4446-6788","contributorId":261751,"corporation":false,"usgs":false,"family":"Isles","given":"Peter","email":"","middleInitial":"D. F.","affiliations":[{"id":52989,"text":"SUNY Buffalo State College","active":true,"usgs":false}],"preferred":false,"id":820576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adrian, Rita 0000-0002-6318-7189","orcid":"https://orcid.org/0000-0002-6318-7189","contributorId":166831,"corporation":false,"usgs":false,"family":"Adrian","given":"Rita","email":"","affiliations":[{"id":24542,"text":"Department of Ecosystem Research, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 301, D- 12587 Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":820577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Albright, Matthew","contributorId":261752,"corporation":false,"usgs":false,"family":"Albright","given":"Matthew","email":"","affiliations":[{"id":52990,"text":"SUNY Oneonta Biological Field Station","active":true,"usgs":false}],"preferred":false,"id":820578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bacon, Linda C. 0000-0001-8744-4656","orcid":"https://orcid.org/0000-0001-8744-4656","contributorId":204064,"corporation":false,"usgs":false,"family":"Bacon","given":"Linda","email":"","middleInitial":"C.","affiliations":[{"id":36816,"text":"Department of Environmental Protection, State of Maine","active":true,"usgs":false}],"preferred":false,"id":820579,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Berger, Stella A. 0000-0002-8835-545X","orcid":"https://orcid.org/0000-0002-8835-545X","contributorId":244069,"corporation":false,"usgs":false,"family":"Berger","given":"Stella","email":"","middleInitial":"A.","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":820580,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bhattacharya, Ruchi 0000-0001-5657-9603","orcid":"https://orcid.org/0000-0001-5657-9603","contributorId":223162,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"Ruchi","email":"","affiliations":[],"preferred":false,"id":820581,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grossart, Hans-Peter 0000-0002-9141-0325","orcid":"https://orcid.org/0000-0002-9141-0325","contributorId":194460,"corporation":false,"usgs":false,"family":"Grossart","given":"Hans-Peter","email":"","affiliations":[],"preferred":false,"id":820582,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hejzlar, Josef 0000-0002-7186-4776","orcid":"https://orcid.org/0000-0002-7186-4776","contributorId":243013,"corporation":false,"usgs":false,"family":"Hejzlar","given":"Josef","email":"","affiliations":[{"id":38766,"text":"Institute of Hydrobiology, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":820583,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hetherington, Amy L. 0000-0003-3002-2924","orcid":"https://orcid.org/0000-0003-3002-2924","contributorId":166842,"corporation":false,"usgs":false,"family":"Hetherington","given":"Amy","email":"","middleInitial":"L.","affiliations":[{"id":24552,"text":"Department of Natural Resources, Cornell University, Ithaca, New York, 14853, USA.","active":true,"usgs":false}],"preferred":false,"id":820584,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Knoll, Lesley B. 0000-0003-0347-5979","orcid":"https://orcid.org/0000-0003-0347-5979","contributorId":194463,"corporation":false,"usgs":false,"family":"Knoll","given":"Lesley","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":820585,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Laas, Alo 0000-0002-4801-0377","orcid":"https://orcid.org/0000-0002-4801-0377","contributorId":261753,"corporation":false,"usgs":false,"family":"Laas","given":"Alo","email":"","affiliations":[{"id":18000,"text":"Estonian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":820586,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McDonald, Cory P. 0000-0002-1208-8471","orcid":"https://orcid.org/0000-0002-1208-8471","contributorId":261754,"corporation":false,"usgs":false,"family":"McDonald","given":"Cory","email":"","middleInitial":"P.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":820587,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Merrell, Kellie","contributorId":261755,"corporation":false,"usgs":false,"family":"Merrell","given":"Kellie","email":"","affiliations":[{"id":52992,"text":"Vermont Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":820588,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Nejstgaard, Jens C. 0000-0003-1236-0647","orcid":"https://orcid.org/0000-0003-1236-0647","contributorId":261756,"corporation":false,"usgs":false,"family":"Nejstgaard","given":"Jens","email":"","middleInitial":"C.","affiliations":[{"id":52993,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB)","active":true,"usgs":false}],"preferred":false,"id":820589,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Nelson, Kirsten 0000-0002-5795-1056","orcid":"https://orcid.org/0000-0002-5795-1056","contributorId":261757,"corporation":false,"usgs":false,"family":"Nelson","given":"Kirsten","email":"","affiliations":[{"id":52994,"text":"New Hampshire Department of Environmental Services","active":true,"usgs":false}],"preferred":false,"id":820590,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Noges, Peeter 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0000-0001-9156-9486","orcid":"https://orcid.org/0000-0001-9156-9486","contributorId":261758,"corporation":false,"usgs":false,"family":"Pilla","given":"Rachel","email":"","middleInitial":"M.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":820593,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820594,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Rudstam, Lars G. 0000-0002-3732-6368","orcid":"https://orcid.org/0000-0002-3732-6368","contributorId":213508,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":820595,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Rusak, James A. 0000-0002-4939-6478","orcid":"https://orcid.org/0000-0002-4939-6478","contributorId":150301,"corporation":false,"usgs":false,"family":"Rusak","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":17970,"text":"Dorset Environmental Science Centre, Ontario Ministry of the Environment and Climate Change, Dorset, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":820596,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Sadro, Steven 0000-0002-6416-3840","orcid":"https://orcid.org/0000-0002-6416-3840","contributorId":139662,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","email":"","affiliations":[{"id":12871,"text":"Marine Science Institute, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":820597,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Silow, Eugene A. 0000-0002-7039-3220","orcid":"https://orcid.org/0000-0002-7039-3220","contributorId":150308,"corporation":false,"usgs":false,"family":"Silow","given":"Eugene","email":"","middleInitial":"A.","affiliations":[{"id":17982,"text":"Scientific Research Institute of Biology, Irkutsk State University, Irkutsk, Russia","active":true,"usgs":false}],"preferred":false,"id":820598,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Stockwell, Jason D. 0000-0003-3393-6799","orcid":"https://orcid.org/0000-0003-3393-6799","contributorId":61004,"corporation":false,"usgs":false,"family":"Stockwell","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":820599,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Yao, Huaxia 0000-0001-5875-7215","orcid":"https://orcid.org/0000-0001-5875-7215","contributorId":261759,"corporation":false,"usgs":false,"family":"Yao","given":"Huaxia","email":"","affiliations":[{"id":52996,"text":"Dorset Environmental Science Centre","active":true,"usgs":false}],"preferred":false,"id":820600,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Yokota, Kiyoko 0000-0002-4578-6540","orcid":"https://orcid.org/0000-0002-4578-6540","contributorId":261760,"corporation":false,"usgs":false,"family":"Yokota","given":"Kiyoko","email":"","affiliations":[{"id":52997,"text":"State University of New York College at Oneonta","active":true,"usgs":false}],"preferred":false,"id":820601,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Pierson, Donald C. 0000-0001-6230-0146","orcid":"https://orcid.org/0000-0001-6230-0146","contributorId":204090,"corporation":false,"usgs":false,"family":"Pierson","given":"Donald","email":"","middleInitial":"C.","affiliations":[{"id":36836,"text":"Department of Ecology and Genetics, Uppsala University","active":true,"usgs":false}],"preferred":false,"id":820602,"contributorType":{"id":1,"text":"Authors"},"rank":28}]}}
,{"id":70221816,"text":"sir20215056 - 2021 - Hydraulic modeling at selected dam-removal and culvert-retrofit sites in the northeastern United States","interactions":[],"lastModifiedDate":"2021-07-09T11:58:58.971817","indexId":"sir20215056","displayToPublicDate":"2021-07-08T16:19:59","publicationYear":"2021","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":"2021-5056","displayTitle":"Hydraulic Modeling at Selected Dam-Removal and Culvert-Retrofit Sites in the Northeastern United States","title":"Hydraulic modeling at selected dam-removal and culvert-retrofit sites in the northeastern United States","docAbstract":"<p>Aquatic connectivity projects, such as removing dams and modifying culverts, have substantial benefits. The restoration of natural flow conditions improves water quality, sediment transport, aquatic and riparian habitat, and fish passage. These projects can also decrease hazards faced by communities by lowering water-surface elevations of flood waters and by removing the risk of dam breaches associated with aging or inadequate infrastructure.<br><br>This report documents and provides results of one- and two-dimensional hydraulic models developed for selected rivers and streams in the northeastern United States where a dam was removed or a culvert was retrofitted. The models were developed for conditions before and after the dam removal or culvert modification. The discharges applied in the models included monthly discharges and flood discharges for the annual exceedance probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent.<br><br>This study, by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, demonstrates the benefits resulting from dam removal and retrofitting undersized culverts in terms of decreased water-surface elevations during flooding and improved fish passage. The U.S. Army Corps of Engineers Hydrologic Engineering Center’s River Analysis System was used to model the sites in one- and two-dimensional hydraulics, and decreases in the 1-percent annual exceedance probability discharge water-surface elevation were found at all sites studied. The decreases in water-surface elevation at sites in which the impoundment was removed ranged from 1.3 to 10.4 feet. One site, Bradford Dam in Westerly, Rhode Island, had only a 0.2-foot decrease, but at that site the dam was replaced by a series of weirs to retain the upstream impoundment and allow fish passage.<br><br>Minimal differences were found between the water-surface elevations computed by the one- and two-dimensional models. The two-dimensional models, however, provide the additional benefit of detailed velocity and depth data throughout the channel at a resolution not possible with a one-dimensional model. These velocity and depth data allowed for assessment of the suitability for fish passage at the sites. Fish passage was improved at all the sites by removing the dams and retrofitting the culvert. Prolonged swim velocity criteria for selected fish species were maintained throughout three of the nine study sites, and burst swim velocity criteria were met at all study sites.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215056","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Olson, S.A., and Simeone, C.E., 2021, Hydraulic modeling at selected dam-removal and culvert-retrofit sites in the northeastern United States: U.S. Geological Survey Scientific Investigations Report 2021–5056, 37 p., https://doi.org/10.3133/sir20215056.","productDescription":"Report: vi, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","ipdsId":"IP-120501","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":387017,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LWIWVO","text":"USGS data release","linkHelpText":"Data and hydraulic models at selected dam removal and culvert retrofit sites in the northeastern United States"},{"id":387015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5056/coverthb.jpg"},{"id":387016,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5056/sir20215056.pdf","text":"Report","size":"6.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5056"}],"country":"United States","state":"Connecticut, Massachusetts, New Jersey, Rhode Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.2181396484375,\n              39.88866516883713\n            ],\n            [\n              -73.95721435546875,\n              39.88866516883713\n            ],\n   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     ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.17718505859375,\n              41.19932314127607\n            ],\n            [\n              -72.89703369140625,\n              41.19932314127607\n            ],\n            [\n              -72.89703369140625,\n              41.38917324986403\n            ],\n            [\n              -73.17718505859375,\n              41.38917324986403\n            ],\n            [\n              -73.17718505859375,\n              41.19932314127607\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.08953857421875,\n              41.2509675141624\n            ],\n            [\n        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-71.15295410156249,\n              41.82045509614034\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ nweng@usgs.gov\" data-mce-href=\"mailto:dc_ nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Development of Hydraulic Models</li><li>Model Execution</li><li>Model Results</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-07-08","noUsgsAuthors":false,"publicationDate":"2021-07-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simeone, Caelan E. 0000-0003-3263-6452 csimeone@usgs.gov","orcid":"https://orcid.org/0000-0003-3263-6452","contributorId":221126,"corporation":false,"usgs":true,"family":"Simeone","given":"Caelan","email":"csimeone@usgs.gov","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818842,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70221785,"text":"ofr20211071 - 2021 - Preliminary assessment of the wave generating potential from landslides at Barry Arm, Prince William Sound, Alaska","interactions":[],"lastModifiedDate":"2021-07-09T11:40:56.783498","indexId":"ofr20211071","displayToPublicDate":"2021-07-08T11:50:00","publicationYear":"2021","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":"2021-1071","displayTitle":"Preliminary Assessment of the Wave Generating Potential from Landslides at Barry Arm, Prince William Sound, Alaska","title":"Preliminary assessment of the wave generating potential from landslides at Barry Arm, Prince William Sound, Alaska","docAbstract":"<p>We simulated the concurrent rapid motion of landslides on an unstable slope at Barry Arm, Alaska. Movement of landslides into the adjacent fjord displaced fjord water and generated a tsunami, which propagated out of Barry Arm. Rather than assuming an initial sea surface height, velocity, and location for the tsunami, we generated the tsunami directly using a model capable of simulating the dynamics of both water and landslide material. The fjord below most of the landslide source area was occupied by the Barry Glacier until about 2012; therefore, our direct simulation of tsunami generation by landslide motion required new topographic and bathymetric data, which was collected in 2020. The topographic data also constrained landslide geometries and volumes. We considered four scenarios based on two landslide volumes and two landslide mobilities—a more mobile, contractive landslide and a less mobile, noncontractive landslide. The larger of the two volumes is 689 × 10<sup>6</sup> cubic meters (m<sup>3</sup>)—larger than the volume estimate in a previous study—and reflects the largest plausible volume given current observational data. The considered scenario that generated the largest wave heights resulted in forecast wave heights of over 200 meters (m) in the northern part of Barry Arm, adjacent to the landslide source area and runup on the opposite fjord wall in excess of 500 m. Simulated wave heights in excess of 5 m in southern Barry Arm and in Harriman Fjord occurred within 10–15 minutes (min) of landslide motion. The simulated tsunami reached Whittier, Alaska, approximately 20 min after initial rapid landslide motion, with peak heights of just over 2 m in Passage Fjord, 500 m offshore Whittier, occurring 26 min after initial rapid motion. Time of peak wave heights was consistent with previous modeling. Although results are preliminary and can be refined with additional observations and analyses, they provide a refined assessment of the upper bound of the hazard presented by the Barry Arm landslides. The results herein support the National Oceanic and Atmospheric Administration’s National Tsunami Warning Center mission to detect, forecast, and warn for tsunamis in Alaska.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211071","usgsCitation":"Barnhart, K.R., Jones, R.P., George, D.L., Coe, J.A., and Staley, D.M., 2021, Preliminary assessment of the wave generating potential from landslides at Barry Arm, Prince William Sound, Alaska: U.S. Geological Survey Open-File Report 2021–1071, 28 p., https://doi.org/10.3133/ofr20211071.","productDescription":"Report: v, 28 p.; Data Release","ipdsId":"IP-130004","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":386958,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XVJDNP","text":"USGS data release","linkHelpText":"Select model results from simulations of hypothetical rapid failures of landslides into Barry Arm Fjord, Prince William Sound, Alaska"},{"id":386957,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1071/ofr20211071.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1071"},{"id":386956,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1071/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Barry Arm, Prince William Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -148.90869140625,\n              60.77659627851085\n            ],\n            [\n              -147.95562744140625,\n              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Cited</li></ul>","publishedDate":"2021-07-08","noUsgsAuthors":false,"publicationDate":"2021-07-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":818697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Ryan P. 0000-0001-6363-7592","orcid":"https://orcid.org/0000-0001-6363-7592","contributorId":260774,"corporation":false,"usgs":true,"family":"Jones","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":818698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":818699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":818700,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":818701,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70222548,"text":"70222548 - 2021 - Investigation of scale-dependent groundwater/surface-water exchange in rivers by gradient self-potential logging: Numerical modeling and field experiments","interactions":[],"lastModifiedDate":"2021-08-04T12:10:45.87688","indexId":"70222548","displayToPublicDate":"2021-07-08T07:06:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9128,"text":"Journal of Environmental and Engineering Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Investigation of scale-dependent groundwater/surface-water exchange in rivers by gradient self-potential logging: Numerical modeling and field experiments","docAbstract":"<p><span>Exchanges of groundwater and surface-water are fundamental to a wide range of water-supply and water-quality management issues but challenging to map beyond the reach scale. Waterborne gradient self-potential (SP) measurements are directly sensitive to water flow through riverbed sediments and can be used to infer exchange locations, direction (gain versus loss), scale, and relative changes, but to date applications to river corridor hydrology are limited. Numerical modeling and field experiments were therefore performed herein, each emphasizing waterborne gradient SP logging for identifying and locating focused vertical groundwater discharge (surface-water gain) and recharge (surface-water loss) in a river. Two and three-dimensional numerical models were constructed to simulate the polarities, appearances, and peak amplitudes of streaming-potential and electric-field anomalies on a riverbed and in the surface-water that were attributable to steady-state vertical fluxes of groundwater through high-permeability conduits in the riverbed. Effects of varied hydraulic length-scale of exchange and surface-water depth were tested through numerical modeling. Modeling results aided in data acquisition and interpretation for three repeated field experiments performed along a 1.5–2.0 km reach of the Quashnet River in Cape Cod, Massachusetts, where focused, meter-scale groundwater discharges occur at discrete locations within otherwise ubiquitous and more diffuse groundwater upwelling conditions. Strong gradient SP anomalies were repeatedly measured in the Quashnet River at previously confirmed locations of focused groundwater discharge, showing the efficacy of waterborne gradient SP logging in identifying and characterizing groundwater/surface water exchange dynamics at multiple river network scales.</span></p>","language":"English","publisher":"EEGS","doi":"10.32389/JEEG20-066","usgsCitation":"Ikard, S., Briggs, M., and Lane, J.W., 2021, Investigation of scale-dependent groundwater/surface-water exchange in rivers by gradient self-potential logging: Numerical modeling and field experiments: Journal of Environmental and Engineering Geophysics, v. 26, no. 2, 181 p., https://doi.org/10.32389/JEEG20-066.","productDescription":"181 p.","ipdsId":"IP-126186","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":387675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Massachusetts","otherGeospatial":"Quashnet River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.51935195922852,\n              41.57115075028995\n            ],\n            [\n              -70.5057907104492,\n              41.57115075028995\n            ],\n            [\n              -70.5057907104492,\n              41.59400643013302\n            ],\n            [\n              -70.51935195922852,\n              41.59400643013302\n            ],\n            [\n              -70.51935195922852,\n              41.57115075028995\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"26","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":201775,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":820534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lane, John W. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":219742,"corporation":false,"usgs":true,"family":"Lane","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":820535,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70222423,"text":"70222423 - 2021 - Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument","interactions":[],"lastModifiedDate":"2021-07-28T12:01:05.400154","indexId":"70222423","displayToPublicDate":"2021-07-08T06:56:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9115,"text":"Environmental Software & Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument","docAbstract":"<p><span>Worldwide, billions of people rely on fresh groundwater reserves for their domestic, agricultural and industrial water use. Extreme droughts and excessive groundwater pumping put pressure on water authorities in maintaining sustainable water usage. High-resolution integrated models are valuable assets in supporting them. The Netherlands Hydrological Instrument (NHI) provides the Dutch water authorities with open source modeling software and data. However, NHI integrated&nbsp;</span>groundwater models<span>&nbsp;often require long run times and large memory usage, therefore strongly limiting their application. As a solution, we present a distributed memory&nbsp;parallelization, focusing on the National Hydrological Model. Depending on the level of integration, we show that significant speedups can be obtained up to two orders of magnitude. As far as we know, this is the first reported integrated groundwater parallelization of an operational hydrological model used for national-scale&nbsp;integrated water management&nbsp;and policy making. The parallel model code and data are freely available.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105092","usgsCitation":"Verkaik, J., Hughes, J.D., Walsum, V., Oude Essink, G., Lin, H., and Bierkens, M., 2021, Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument: Environmental Software & Modelling, v. 143, 105092, 15 p., https://doi.org/10.1016/j.envsoft.2021.105092.","productDescription":"105092, 15 p.","ipdsId":"IP-129864","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":451594,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105092","text":"Publisher Index Page"},{"id":387499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Verkaik, Jarno 0000-0001-7420-8304","orcid":"https://orcid.org/0000-0001-7420-8304","contributorId":261418,"corporation":false,"usgs":false,"family":"Verkaik","given":"Jarno","email":"","affiliations":[{"id":52847,"text":"Deltares and Utrecht University","active":true,"usgs":false}],"preferred":false,"id":819993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":819994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsum, van","contributorId":261419,"corporation":false,"usgs":false,"family":"Walsum","given":"van","email":"","affiliations":[{"id":52848,"text":"Wageningen Environmental Research","active":true,"usgs":false}],"preferred":false,"id":819995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oude Essink, G.H.P. 0000-0003-0931-6944","orcid":"https://orcid.org/0000-0003-0931-6944","contributorId":261420,"corporation":false,"usgs":false,"family":"Oude Essink","given":"G.H.P.","email":"","affiliations":[{"id":52847,"text":"Deltares and Utrecht University","active":true,"usgs":false}],"preferred":false,"id":819996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, H.X.","contributorId":261421,"corporation":false,"usgs":false,"family":"Lin","given":"H.X.","email":"","affiliations":[{"id":52849,"text":"Delft Institute of Applied Mathematics and Leiden University","active":true,"usgs":false}],"preferred":false,"id":819997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bierkens, M.F.P. 0000-0002-7411-6562","orcid":"https://orcid.org/0000-0002-7411-6562","contributorId":261422,"corporation":false,"usgs":false,"family":"Bierkens","given":"M.F.P.","affiliations":[{"id":52850,"text":"Utrecht University and Deltares","active":true,"usgs":false}],"preferred":false,"id":819998,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70240119,"text":"70240119 - 2021 - Factors influencing distributional shifts and abundance at the range core of a climate-sensitive mammal","interactions":[],"lastModifiedDate":"2023-01-27T12:56:42.509076","indexId":"70240119","displayToPublicDate":"2021-07-08T06:54:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing distributional shifts and abundance at the range core of a climate-sensitive mammal","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Species are frequently responding to contemporary climate change by shifting to higher elevations and poleward to track suitable climate space. However, depending on local conditions and species’ sensitivity, the nature of these shifts can be highly variable and difficult to predict. Here, we examine how the American pika (<i>Ochotona princeps</i>), a philopatric, montane lagomorph, responds to climatic gradients at three spatial scales. Using mixed-effects modeling in an information-theoretic approach, we evaluated a priori model suites regarding predictors of site occupancy, relative abundance, and elevational-range retraction across 760 talus patches, nested within 64 watersheds across the Northern Rocky Mountains of North America, during 2017–2020. The top environmental predictors differed across these response metrics. Warmer temperatures in summer and winter were associated with lower occupancy, lower relative abundances, and greater elevational retraction across watersheds. Occupancy was also strongly influenced by habitat patch size, but only when combined with climate metrics such as actual evapotranspiration. Using a second analytical approach, acute heat stress and summer precipitation best explained retraction residuals (i.e., the relative extent of retraction given the original elevational range of occupancy). Despite the study domain occurring near the species’ geographic-range center, where populations might have higher abundances and be at lower risk of climate-related stress, 33.9% of patches showed evidence of recent extirpations. Pika-extirpated sites averaged 1.44℃ warmer in summer than did occupied sites. Additionally, the minimum elevation of pika occupancy has retracted upslope in 69% of watersheds (mean: 281&nbsp;m). Our results emphasize the nuance associated with evaluating species’ range dynamics in response to climate gradients, variability, and temperature exceedances, especially in regions where species occupy gradients of conditions that may constitute multiple range edges. Furthermore, this study highlights the importance of evaluating diverse drivers across response metrics to improve the predictive accuracy of widely used, correlative models.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15793","usgsCitation":"Billman, P., Beever, E.A., McWethy, D.B., Thurman, L., and Wilson, K.C., 2021, Factors influencing distributional shifts and abundance at the range core of a climate-sensitive mammal: Global Change Biology, v. 27, no. 19, p. 4498-4515, https://doi.org/10.1111/gcb.15793.","productDescription":"18 p.","startPage":"4498","endPage":"4515","ipdsId":"IP-123267","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":451597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.15793","text":"Publisher Index Page"},{"id":412400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.96912848281637,\n              47.81775925984073\n            ],\n            [\n              -115.96912848281637,\n              43.011789546894505\n            ],\n            [\n              -111.0932694765071,\n              43.011789546894505\n            ],\n            [\n              -111.0932694765071,\n              47.81775925984073\n            ],\n            [\n              -115.96912848281637,\n              47.81775925984073\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"27","issue":"19","noUsgsAuthors":false,"publicationDate":"2021-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Billman, Peter D","contributorId":301821,"corporation":false,"usgs":false,"family":"Billman","given":"Peter D","affiliations":[{"id":65350,"text":"Dept. of Earth Sciences, Montana State University","active":true,"usgs":false}],"preferred":false,"id":862646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":2934,"corporation":false,"usgs":true,"family":"Beever","given":"Erik","email":"ebeever@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McWethy, Dave B.","contributorId":301822,"corporation":false,"usgs":false,"family":"McWethy","given":"Dave","email":"","middleInitial":"B.","affiliations":[{"id":65350,"text":"Dept. of Earth Sciences, Montana State University","active":true,"usgs":false}],"preferred":false,"id":862648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurman, Lindsey 0000-0003-3142-4909","orcid":"https://orcid.org/0000-0003-3142-4909","contributorId":269425,"corporation":false,"usgs":true,"family":"Thurman","given":"Lindsey","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Kenny C","contributorId":301823,"corporation":false,"usgs":false,"family":"Wilson","given":"Kenny","email":"","middleInitial":"C","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":862650,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70224969,"text":"70224969 - 2021 - Blue waters, green bottoms: Benthic filamentous algal blooms are an emerging threat to clear lakes worldwide","interactions":[],"lastModifiedDate":"2021-10-11T16:58:05.08129","indexId":"70224969","displayToPublicDate":"2021-07-07T08:25:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Blue waters, green bottoms: Benthic filamentous algal blooms are an emerging threat to clear lakes worldwide","docAbstract":"<p class=\"chapter-para\"><span>Nearshore (littoral) habitats of clear lakes with high water quality are increasingly experiencing unexplained proliferations of filamentous algae that grow on submerged surfaces. These filamentous algal blooms (FABs) are sometimes associated with nutrient pollution in groundwater, but complex changes in climate, nutrient transport, lake hydrodynamics, and food web structure may also facilitate this emerging threat to clear lakes. A coordinated effort among members of the public, managers, and scientists is needed to document the occurrence of FABs, to standardize methods for measuring their severity, to adapt existing data collection networks to include nearshore habitats, and to mitigate and reverse this profound structural change in lake ecosystems. Current models of lake eutrophication do not explain this littoral greening. However, a cohesive response to it is essential for protecting some of the world's most valued lakes and the flora, fauna, and ecosystem services they sustain.</span></p>","language":"English","publisher":"American Institute of Biological Sciences","doi":"10.1093/biosci/biab049","usgsCitation":"Vadeboncoeur, Y., Moore, M.V., Stewart, S.D., Chandra, S., Atkins, K., Baron, J., Bouma-Gregson, K., Brothers, S., Francoeur, S., Genzoli, L., Higgins, S.N., Hilt, S., Katona, L., Kelly, D., Oleksy, I., Ozersky, T., Powel, M., Roberts, D., Timoshkin, O., Tromboni, F., Vander Zanden, M.J., Volkova, E., Waters, S., Wood, S.A., and Yamamuro, M., 2021, Blue waters, green bottoms: Benthic filamentous algal blooms are an emerging threat to clear lakes worldwide: BioScience, v. 71, no. 10, p. 1011-1027, https://doi.org/10.1093/biosci/biab049.","productDescription":"17 p.","startPage":"1011","endPage":"1027","ipdsId":"IP-125146","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biab049","text":"Publisher Index Page"},{"id":390396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"71","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Vadeboncoeur, Yvonne","contributorId":267285,"corporation":false,"usgs":false,"family":"Vadeboncoeur","given":"Yvonne","email":"","affiliations":[{"id":13348,"text":"Wright State University","active":true,"usgs":false}],"preferred":false,"id":824919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Marianne V.","contributorId":267286,"corporation":false,"usgs":false,"family":"Moore","given":"Marianne","email":"","middleInitial":"V.","affiliations":[{"id":55461,"text":"Wellesley College","active":true,"usgs":false}],"preferred":false,"id":824920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Simon D.","contributorId":267287,"corporation":false,"usgs":false,"family":"Stewart","given":"Simon","email":"","middleInitial":"D.","affiliations":[{"id":55462,"text":"Cawthron Institue, New Zealand","active":true,"usgs":false}],"preferred":false,"id":824921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chandra, Sudeep","contributorId":267288,"corporation":false,"usgs":false,"family":"Chandra","given":"Sudeep","affiliations":[{"id":32871,"text":"University of Nevada at Reno","active":true,"usgs":false}],"preferred":false,"id":824922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkins, Karen","contributorId":267289,"corporation":false,"usgs":false,"family":"Atkins","given":"Karen","email":"","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":824923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baron, Jill S. 0000-0002-5902-6251","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":215101,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":824924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bouma-Gregson, Keith","contributorId":267290,"corporation":false,"usgs":false,"family":"Bouma-Gregson","given":"Keith","affiliations":[{"id":12702,"text":"California State Water Resources Control Board","active":true,"usgs":false}],"preferred":false,"id":824925,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brothers, Soren","contributorId":267291,"corporation":false,"usgs":false,"family":"Brothers","given":"Soren","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":824926,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Francoeur, Stephen","contributorId":267292,"corporation":false,"usgs":false,"family":"Francoeur","given":"Stephen","email":"","affiliations":[{"id":55463,"text":"Eastern Michigan University","active":true,"usgs":false}],"preferred":false,"id":824927,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Genzoli, Laurel","contributorId":267293,"corporation":false,"usgs":false,"family":"Genzoli","given":"Laurel","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":824928,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Higgins, Scott N.","contributorId":267294,"corporation":false,"usgs":false,"family":"Higgins","given":"Scott","email":"","middleInitial":"N.","affiliations":[{"id":55464,"text":"IISD Experimental Lakes Area, Canada","active":true,"usgs":false}],"preferred":false,"id":824929,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hilt, Sabine","contributorId":267295,"corporation":false,"usgs":false,"family":"Hilt","given":"Sabine","email":"","affiliations":[{"id":55465,"text":"Leibniz Institute of Freshwater Ecology and Inland Fisheries, Germany","active":true,"usgs":false}],"preferred":false,"id":824930,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Katona, Leon R.","contributorId":267333,"corporation":false,"usgs":false,"family":"Katona","given":"Leon R.","affiliations":[],"preferred":false,"id":824997,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Kelly, David","contributorId":267334,"corporation":false,"usgs":false,"family":"Kelly","given":"David","affiliations":[],"preferred":false,"id":824998,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Oleksy, Isabella","contributorId":267296,"corporation":false,"usgs":false,"family":"Oleksy","given":"Isabella","affiliations":[{"id":33412,"text":"Cary Institute for Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":824931,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Ozersky, Ted","contributorId":267297,"corporation":false,"usgs":false,"family":"Ozersky","given":"Ted","affiliations":[{"id":55466,"text":"University of Minnesota, Duluth","active":true,"usgs":false}],"preferred":false,"id":824932,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Powel, Mary","contributorId":267298,"corporation":false,"usgs":false,"family":"Powel","given":"Mary","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":824933,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Roberts, Derek","contributorId":267299,"corporation":false,"usgs":false,"family":"Roberts","given":"Derek","email":"","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":824934,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Timoshkin, Oleg","contributorId":267300,"corporation":false,"usgs":false,"family":"Timoshkin","given":"Oleg","email":"","affiliations":[{"id":55467,"text":"Siberian Branch of the Russian Academy of Sciences’ Limnological Institute","active":true,"usgs":false}],"preferred":false,"id":824935,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Tromboni, Flavia","contributorId":267335,"corporation":false,"usgs":false,"family":"Tromboni","given":"Flavia","email":"","affiliations":[],"preferred":false,"id":824999,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Vander Zanden, M. Jake","contributorId":265448,"corporation":false,"usgs":false,"family":"Vander Zanden","given":"M.","email":"","middleInitial":"Jake","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":825000,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Volkova, Ekaterina","contributorId":267301,"corporation":false,"usgs":false,"family":"Volkova","given":"Ekaterina","email":"","affiliations":[{"id":55467,"text":"Siberian Branch of the Russian Academy of Sciences’ Limnological Institute","active":true,"usgs":false}],"preferred":false,"id":824936,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Waters, Sean","contributorId":267336,"corporation":false,"usgs":false,"family":"Waters","given":"Sean","email":"","affiliations":[],"preferred":false,"id":825001,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Wood, Susanna A.","contributorId":267337,"corporation":false,"usgs":false,"family":"Wood","given":"Susanna","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":825002,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Yamamuro, Masumi","contributorId":267338,"corporation":false,"usgs":false,"family":"Yamamuro","given":"Masumi","email":"","affiliations":[],"preferred":false,"id":824938,"contributorType":{"id":1,"text":"Authors"},"rank":25}]}}
,{"id":70222412,"text":"70222412 - 2021 - Temperature variation and host immunity regulate viral persistence in a salmonid host","interactions":[],"lastModifiedDate":"2021-07-27T11:59:37.309609","indexId":"70222412","displayToPublicDate":"2021-07-07T06:33:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9113,"text":"Pathogens","active":true,"publicationSubtype":{"id":10}},"title":"Temperature variation and host immunity regulate viral persistence in a salmonid host","docAbstract":"<p><span>Environmental variation has important effects on host–pathogen interactions, affecting large-scale ecological processes such as the severity and frequency of epidemics. However, less is known about how the environment interacts with host immunity to modulate virus fitness within hosts. Here, we studied the interaction between host immune responses and water temperature on the long-term persistence of a model vertebrate virus, infectious hematopoietic necrosis virus (IHNV) in steelhead trout (</span><span class=\"html-italic\">Oncorhynchus mykiss</span><span>). We first used cell culture methods to factor out strong host immune responses, allowing us to test the effect of temperature on viral replication. We found that 15&nbsp;</span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;><semantics><msup><mrow /><mo>&amp;#x2218;</mo></msup></semantics></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"semantics\"><span id=\"MathJax-Span-4\" class=\"msup\"><span id=\"MathJax-Span-5\" class=\"mrow\"></span><span id=\"MathJax-Span-6\" class=\"mo\">∘</span></span></span></span></span></span></span><span>C water temperature accelerated IHNV replication compared to the colder 10 and 8&nbsp;</span><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;><semantics><msup><mrow /><mo>&amp;#x2218;</mo></msup></semantics></math>\"><span id=\"MathJax-Span-7\" class=\"math\"><span><span id=\"MathJax-Span-8\" class=\"mrow\"><span id=\"MathJax-Span-9\" class=\"semantics\"><span id=\"MathJax-Span-10\" class=\"msup\"><span id=\"MathJax-Span-11\" class=\"mrow\"></span><span id=\"MathJax-Span-12\" class=\"mo\">∘</span></span></span></span></span></span></span><span>C temperatures. We then conducted in vivo experiments to quantify the effect of 6, 10, and 15&nbsp;</span><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;><semantics><msup><mrow /><mo>&amp;#x2218;</mo></msup></semantics></math>\"><span id=\"MathJax-Span-13\" class=\"math\"><span><span id=\"MathJax-Span-14\" class=\"mrow\"><span id=\"MathJax-Span-15\" class=\"semantics\"><span id=\"MathJax-Span-16\" class=\"msup\"><span id=\"MathJax-Span-17\" class=\"mrow\"></span><span id=\"MathJax-Span-18\" class=\"mo\">∘</span></span></span></span></span></span></span><span>C water temperatures on IHNV persistence over 8 months. Fish held at 15 and 10&nbsp;</span><span id=\"MathJax-Element-4-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;><semantics><msup><mrow /><mo>&amp;#x2218;</mo></msup></semantics></math>\"><span id=\"MathJax-Span-19\" class=\"math\"><span><span id=\"MathJax-Span-20\" class=\"mrow\"><span id=\"MathJax-Span-21\" class=\"semantics\"><span id=\"MathJax-Span-22\" class=\"msup\"><span id=\"MathJax-Span-23\" class=\"mrow\"></span><span id=\"MathJax-Span-24\" class=\"mo\">∘</span></span></span></span></span></span></span><span>C were found to have higher prevalence of neutralizing antibodies compared to fish held at 6&nbsp;</span><span id=\"MathJax-Element-5-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;><semantics><msup><mrow /><mo>&amp;#x2218;</mo></msup></semantics></math>\"><span id=\"MathJax-Span-25\" class=\"math\"><span><span id=\"MathJax-Span-26\" class=\"mrow\"><span id=\"MathJax-Span-27\" class=\"semantics\"><span id=\"MathJax-Span-28\" class=\"msup\"><span id=\"MathJax-Span-29\" class=\"mrow\"></span><span id=\"MathJax-Span-30\" class=\"mo\">∘</span></span></span></span></span></span></span><span>C. We found that IHNV persisted for a shorter time at warmer temperatures and resulted in an overall lower fish mortality compared to colder temperatures. These results support the hypothesis that temperature and host immune responses interact to modulate virus persistence within hosts. When immune responses were minimized (i.e., in vitro) virus replication was higher at warmer temperatures. However, with a full potential for host immune responses (i.e., in vivo experiments) longer virus persistence and higher long-term virulence was favored in colder temperatures. We also found that the viral RNA that persisted at later time points (179 and 270 days post-exposure) was mostly localized in the kidney and spleen tissues. These tissues are composed of hematopoietic cells that are favored targets of the virus. By partitioning the effect of temperature on host and pathogen responses, our results help to better understand environmental drivers of host–pathogen interactions within hosts, providing insights into potential host–pathogen responses to climate change.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/pathogens10070855","usgsCitation":"Paez, D.J., Powers, R., Jia, P., Ballesteros, N., Kurath, G., Naish, K.A., and Purcell, M.K., 2021, Temperature variation and host immunity regulate viral persistence in a salmonid host: Pathogens, v. 10, no. 7, 855, 18 p., https://doi.org/10.3390/pathogens10070855.","productDescription":"855, 18 p.","ipdsId":"IP-129038","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":451619,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/pathogens10070855","text":"Publisher Index Page"},{"id":436284,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T4PH4Z","text":"USGS data release","linkHelpText":"Survival, viral load and neutralizing antibodies in steelhead trout and cell cultures exposed to infectious hematopoietic necrosis virus (IHNV) at 3 temperatures"},{"id":387453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Paez, David J.","contributorId":261396,"corporation":false,"usgs":false,"family":"Paez","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":52838,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle WA 98195, USA","active":true,"usgs":false}],"preferred":false,"id":819959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Rachel L. 0000-0001-6901-4361","orcid":"https://orcid.org/0000-0001-6901-4361","contributorId":190182,"corporation":false,"usgs":true,"family":"Powers","given":"Rachel L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jia, Peng","contributorId":191750,"corporation":false,"usgs":false,"family":"Jia","given":"Peng","email":"","affiliations":[],"preferred":false,"id":819961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ballesteros, Natalia","contributorId":261397,"corporation":false,"usgs":false,"family":"Ballesteros","given":"Natalia","email":"","affiliations":[{"id":52839,"text":"Department of Microbiology, University of Alabama at Birmingham, Birmingham AL 35294, USA","active":true,"usgs":false}],"preferred":false,"id":819962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kurath, Gael 0000-0003-3294-560X","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":220175,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Naish, Kerry A. 0000-0002-3275-8778","orcid":"https://orcid.org/0000-0002-3275-8778","contributorId":201136,"corporation":false,"usgs":false,"family":"Naish","given":"Kerry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":819964,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819965,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70221687,"text":"fs20213037 - 2021 - USGS Chesapeake Science Strategy 2021-2025","interactions":[],"lastModifiedDate":"2021-07-06T21:22:08.301712","indexId":"fs20213037","displayToPublicDate":"2021-07-06T17:25:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-3037","displayTitle":"USGS Chesapeake Science Strategy 2021-2025","title":"USGS Chesapeake Science Strategy 2021-2025","docAbstract":"<p>The Chesapeake Bay ecosystem is a national treasure that provides almost $100 billion annually of goods and services. The Chesapeake Bay Program (CBP), is one of the largest federal-state restoration partnerships in the United States and is underpinned by rigorous science. The U.S. Geological Survey (USGS) has a pivotal role as a science provider for assessing ecosystem condition and response in the Chesapeake watershed. Despite significant CBP accomplishments, the pressures of climate change and competing demands on land use and change require an acceleration of progress towards the 10 goals in the Chesapeake Bay Watershed Agreement. USGS Chesapeake studies are increasing efforts to provide integrated science and are engaging stakeholders to inform the multi-faceted restoration and conservation decisions to improve habitat for fish and waterfowl, and socio-economic benefits to the 18 million people living in the watershed.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213037","usgsCitation":"Hyer, K., and Phillips, S., 2021, USGS Chesapeake Science Strategy 2021-2025: U.S. Geological Survey Fact Sheet 2021–3037, 6 p., https://doi.org/10.3133/fs20213037.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-130753","costCenters":[{"id":50439,"text":"North Atlantic-Appalachian Regional Director's Office","active":true,"usgs":true}],"links":[{"id":386813,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3037/fs20213037.pdf","text":"Report","size":"8.93 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Activities</a><br>U.S. Geological Survey<br>5522 Research Park Drive<br>Baltimore, MD 21228</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Theme 1: Provide science for environmental management of stream health, fish habitat, and water quality</li><li>Theme 2: Assess the risks to coastal habitats and migratory waterbirds</li><li>Theme 3: Enhance landscape data and forecasting to inform watershed management</li><li>Theme 4: Integrate science and inform stakeholders</li><li>Selected references</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-06-30","noUsgsAuthors":false,"publicationDate":"2021-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Hyer, Kenneth 0000-0002-7156-7472 kenhyer@usgs.gov","orcid":"https://orcid.org/0000-0002-7156-7472","contributorId":173409,"corporation":false,"usgs":true,"family":"Hyer","given":"Kenneth","email":"kenhyer@usgs.gov","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":818425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Scott W. 0000-0002-1637-9428 swphilli@usgs.gov","orcid":"https://orcid.org/0000-0002-1637-9428","contributorId":191221,"corporation":false,"usgs":true,"family":"Phillips","given":"Scott","email":"swphilli@usgs.gov","middleInitial":"W.","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":818426,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70225622,"text":"70225622 - 2021 - Sea otter foraging behavior","interactions":[],"lastModifiedDate":"2021-10-28T14:28:42.879694","indexId":"70225622","displayToPublicDate":"2021-07-04T09:24:30","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Sea otter foraging behavior","docAbstract":"<p><span>Sea otters are marine specialists but diet generalists, which feed primarily on benthic mega-invertebrates (i.e., body dimension &gt;1&nbsp;cm). They locate and capture epibenthic and infaunal&nbsp;prey with their forepaws by relying on vision and tactile sensitivity during short-duration dives (generally &lt;2&nbsp;min) in shallow waters (routine dives &lt;30&nbsp;m and maximum dive depth ~100&nbsp;m) of the littoral zone. Sea otters have an elevated resting metabolic rate and small or no energy reserves in the form of blubber, so they feed every 3–4&nbsp;h. Foraging dives often occur in bouts (i.e., two or more consecutive dives), which may last several hours with 1–2&nbsp;min between dives, depending on the type of prey. Sea otters consume small or soft prey entirely or use their teeth or stone tools to access the flesh of mega-invertebrates with a shell, test, or exoskeleton. The daily percentage of time that sea otters devote to foraging depends on age, sex, presence of a pup, time of year, and prey abundance, which varies geographically, seasonally, and episodically. In areas occupied by sea otters for many years, epifaunal prey generally decline first followed by infaunal species, and this may result in greater foraging effort and diet specialization associated with density-dependent competition for food. Although prey availability strongly influences sea otter carrying capacity, both intrinsic and extrinsic factors influence population equilibrium density, resulting in spatiotemporal variations in foraging behavior.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ethology and behavioral ecology of sea otters and polar bears","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-66796-2_4","usgsCitation":"Davis, R.W., and Bodkin, J.L., 2021, Sea otter foraging behavior, chap. <i>of</i> Ethology and behavioral ecology of sea otters and polar bears, p. 57-81, https://doi.org/10.1007/978-3-030-66796-2_4.","productDescription":"25 p.","startPage":"57","endPage":"81","ipdsId":"IP-122462","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":451640,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-030-66796-2_4","text":"Publisher Index Page"},{"id":391086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-07-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Randall W.","contributorId":131160,"corporation":false,"usgs":false,"family":"Davis","given":"Randall","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":825975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bodkin, James L. 0000-0003-1641-4438 jbodkin@usgs.gov","orcid":"https://orcid.org/0000-0003-1641-4438","contributorId":748,"corporation":false,"usgs":true,"family":"Bodkin","given":"James","email":"jbodkin@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":825976,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
]}