{"pageNumber":"209","pageRowStart":"5200","pageSize":"25","recordCount":41062,"records":[{"id":70257014,"text":"70257014 - 2021 - SUAS and machine learning integration in waterfowl population surveys","interactions":[],"lastModifiedDate":"2024-09-05T15:50:32.691376","indexId":"70257014","displayToPublicDate":"2021-12-21T10:45:17","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"SUAS and machine learning integration in waterfowl population surveys","docAbstract":"<p><span>The rapid technological development of small Unmanned Aircraft Systems (sUAS) has led to an increase in capabilities of aerial image collection and analysis for monitoring a variety of wildlife species including waterfowl. Biologists mainly rely on conducting ocular surveys from fixed-wing aircraft or helicopters to estimate waterfowl abundance. sUAS provide an alternative that is safer, less expensive, and more flexible. Researchers have attempted to estimate waterfowl abundance from aerial imagery, but this method has proven to be too time consuming. Machine learning provides the opportunity to more efficiently estimate waterfowl abundance from aerial imagery. In this paper, we present a new integrated system of sUAS and machine learning for waterfowl population surveys. This system provides a user-friendly process for sUAS survey design, deployment, and data post-processing using deep learning methods to automatically detect and count waterfowl. To develop this system, we conducted many sUAS flights to capture a diversity of imagery and assembled six datasets of imagery taken from both fix-winged aircraft and sUAS flights. We used these datasets to develop and evaluate state-of-the-art deep learning models for waterfowl detection. Our system of using a combination of sUAS and machine learning has proved to be an efficient and accurate approach for collecting, analyzing, and estimating waterfowl abundance.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)","conferenceDate":"November 1-3, 2021","language":"English","doi":"10.1109/ICTAI52525.2021.00084","usgsCitation":"Tang, Z., Zhang, Y., Wang, Y.Q., Shang, Y., Viegut, R., Webb, E.B., Raedeke, A., and Sartwell, J., 2021, SUAS and machine learning integration in waterfowl population surveys, <i>in</i> 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), November 1-3, 2021, p. 517-521, https://doi.org/10.1109/ICTAI52525.2021.00084.","productDescription":"6 p.","startPage":"517","endPage":"521","ipdsId":"IP-131231","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tang, Z.","contributorId":341913,"corporation":false,"usgs":false,"family":"Tang","given":"Z.","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":909151,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Y.","contributorId":274978,"corporation":false,"usgs":false,"family":"Zhang","given":"Y.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":909152,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Y. Q.","contributorId":221210,"corporation":false,"usgs":false,"family":"Wang","given":"Y.","email":"","middleInitial":"Q.","affiliations":[],"preferred":false,"id":909153,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shang, Y.","contributorId":341914,"corporation":false,"usgs":false,"family":"Shang","given":"Y.","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":909154,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Viegut, R.","contributorId":341915,"corporation":false,"usgs":false,"family":"Viegut","given":"R.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":909155,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":909156,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Raedeke, Andy","contributorId":341916,"corporation":false,"usgs":false,"family":"Raedeke","given":"Andy","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":909157,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sartwell, J.","contributorId":341917,"corporation":false,"usgs":false,"family":"Sartwell","given":"J.","email":"","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":909158,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70226913,"text":"70226913 - 2021 - Invasive sea lamprey detection and characterization using interdigitated electrode (IDE) contact sensor","interactions":[],"lastModifiedDate":"2021-12-21T15:30:33.915647","indexId":"70226913","displayToPublicDate":"2021-12-21T09:22:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9956,"text":"IEEE Sensors Journal","active":true,"publicationSubtype":{"id":10}},"title":"Invasive sea lamprey detection and characterization using interdigitated electrode (IDE) contact sensor","docAbstract":"The ability to monitor invasive sea lamprey (Petromyzon marinus) populations in the Laurentian Great Lakes is critical to protecting the region’s $ 7 billion USD fishing industry and preserving its biodiversity. Monitoring these invaders requires considerable fieldwork and human power, making remote lamprey detection systems attractive for their continuous monitoring capabilities and potential for workload reduction. However, a lack of available methods for detecting sea lamprey hampers development of such systems. Here we present a sensor composed of two exposed planar interdigitated electrodes (IDE) along with a DC measurement system for the detection of lamprey attachment underwater. Measuring voltage instead of impedance, reduces cost and signal processing complexity, making the device more attractive for field deployment. The system is calibrated to a baseline output voltage and deviations from this baseline occur when objects touch the IDE. Validation was done through testing on live adult sea lampreys using video recordings to correlate lamprey attachments to the sensor response. Three response types were identified corresponding to different attachments: sustained, short and sliding-sustained. Sensor response to sustained and sliding-sustained attachments showed a characteristic exponential decay whereas the response due to short attachments was indistinguishable from measurement noise. Lamprey size was found to have a weak linear correlation with both response parameters, positive for the voltage drop and negative for the time constant of voltage drop. A representative circuit for the lamprey-sensor interaction is proposed and simulated using element values calculated from the response parameters. The response of the model shows agreement with experimental data.","language":"English","publisher":"Institute of Electrical and Electronics Engineers","doi":"10.1109/JSEN.2021.3122884","usgsCitation":"Gonzalez-Afanador, I., Shi, H., Holbrook, C., Tan, X., and Sepulveda, N., 2021, Invasive sea lamprey detection and characterization using interdigitated electrode (IDE) contact sensor: IEEE Sensors Journal, v. 21, no. 24, p. 27947-27956, https://doi.org/10.1109/JSEN.2021.3122884.","productDescription":"10 p.","startPage":"27947","endPage":"27956","ipdsId":"IP-132564","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":450001,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1109/jsen.2021.3122884","text":"Publisher Index Page"},{"id":393194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great 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cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":828765,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tan, Xiaobo 0000-0002-5542-6266","orcid":"https://orcid.org/0000-0002-5542-6266","contributorId":214765,"corporation":false,"usgs":false,"family":"Tan","given":"Xiaobo","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":828766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sepulveda, Nelson","contributorId":264255,"corporation":false,"usgs":false,"family":"Sepulveda","given":"Nelson","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":828767,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226950,"text":"70226950 - 2021 - From anecdotes to quantification: Advances in characterizing volcanic eruption impacts on the built environment","interactions":[],"lastModifiedDate":"2025-01-31T14:29:28.940814","indexId":"70226950","displayToPublicDate":"2021-12-21T07:12:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"From anecdotes to quantification: Advances in characterizing volcanic eruption impacts on the built environment","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p><span>Over the past 20&nbsp;years, our understanding of volcanic eruption impacts on the built environment has transformed from being primarily observational with small datasets to one grounded in field investigations, laboratory experiments, and quantitative modeling, with an emphasis on stakeholder collaboration and co-creation. Here, we summarize key advances and knowledge gaps of impacts across volcanic hazards and built environment types from the past 20 + years. Studies have concentrated on impacts from tephra fall (ash) and to buildings, with less examination of other hazards’ impacts to critical infrastructure. As we look to the next decade, we speculate on likely research directions, including the increasing role of new technologies, higher resolution modeling, transdisciplinary collaborations, and evidence-based mitigative solutions.</span></p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s00445-021-01506-8","usgsCitation":"Deligne, N.I., Jenkins, S.F., Meredith, E.S., Williams, G.T., Leonard, G.S., Stewart, C., Wilson, T.M., Biass, S., Blake, D.M., Blong, R.J., Bonadonna, C., Calderon, R., Hayes, J.L., Johnston, D.M., Kennedy, B.M., Magill, C.R., Spence, R., Wallace, K.L., Wardman, J., Weir, A.M., Wilson, G., and Zuccaro, G., 2021, From anecdotes to quantification: Advances in characterizing volcanic eruption impacts on the built environment: Bulletin of Volcanology, v. 84, no. 2, 7, 9 p., https://doi.org/10.1007/s00445-021-01506-8.","productDescription":"7, 9 p.","ipdsId":"IP-130731","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":393298,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427269,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70226950/70226950.pdf","text":"USGS open-access version of article","size":"1 MB"}],"volume":"84","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Deligne, Natalia I. 0000-0001-9221-8581","orcid":"https://orcid.org/0000-0001-9221-8581","contributorId":257389,"corporation":false,"usgs":true,"family":"Deligne","given":"Natalia","email":"","middleInitial":"I.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":828900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Susanna F. 0000-0002-7523-1423","orcid":"https://orcid.org/0000-0002-7523-1423","contributorId":270268,"corporation":false,"usgs":false,"family":"Jenkins","given":"Susanna","email":"","middleInitial":"F.","affiliations":[{"id":56128,"text":"Earth Observatory of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":828901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meredith, Elinor S. 0000-0002-3869-1180","orcid":"https://orcid.org/0000-0002-3869-1180","contributorId":270269,"corporation":false,"usgs":false,"family":"Meredith","given":"Elinor","email":"","middleInitial":"S.","affiliations":[{"id":56128,"text":"Earth Observatory of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":828902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, George T. 0000-0002-5924-2499","orcid":"https://orcid.org/0000-0002-5924-2499","contributorId":270270,"corporation":false,"usgs":false,"family":"Williams","given":"George","email":"","middleInitial":"T.","affiliations":[{"id":56128,"text":"Earth Observatory of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":828903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leonard, Graham S.","contributorId":127469,"corporation":false,"usgs":false,"family":"Leonard","given":"Graham","email":"","middleInitial":"S.","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":828904,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, Carol","contributorId":236960,"corporation":false,"usgs":false,"family":"Stewart","given":"Carol","email":"","affiliations":[{"id":47573,"text":"Massey University, NZ","active":true,"usgs":false}],"preferred":false,"id":828905,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Thomas M. 0000-0002-8816-0708","orcid":"https://orcid.org/0000-0002-8816-0708","contributorId":270271,"corporation":false,"usgs":false,"family":"Wilson","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":828906,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Biass, Sebastien","contributorId":243518,"corporation":false,"usgs":false,"family":"Biass","given":"Sebastien","email":"","affiliations":[{"id":35755,"text":"University of Hawai’i at Mānoa","active":true,"usgs":false}],"preferred":false,"id":828907,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Blake, Daniel M.","contributorId":270272,"corporation":false,"usgs":false,"family":"Blake","given":"Daniel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":828908,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Blong, Russell J. 0000-0002-9284-3747","orcid":"https://orcid.org/0000-0002-9284-3747","contributorId":270273,"corporation":false,"usgs":false,"family":"Blong","given":"Russell","email":"","middleInitial":"J.","affiliations":[{"id":56129,"text":"Risk Frontiers","active":true,"usgs":false}],"preferred":true,"id":828909,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bonadonna, Costanza","contributorId":199721,"corporation":false,"usgs":false,"family":"Bonadonna","given":"Costanza","email":"","affiliations":[],"preferred":false,"id":828910,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Calderon, Rodrigo","contributorId":270274,"corporation":false,"usgs":false,"family":"Calderon","given":"Rodrigo","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":true,"id":828911,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hayes, Josh L. 0000-0001-7099-1063","orcid":"https://orcid.org/0000-0001-7099-1063","contributorId":270275,"corporation":false,"usgs":false,"family":"Hayes","given":"Josh","email":"","middleInitial":"L.","affiliations":[{"id":56128,"text":"Earth Observatory of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":828912,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Johnston, David M. 0000-0001-5114-5355","orcid":"https://orcid.org/0000-0001-5114-5355","contributorId":239591,"corporation":false,"usgs":false,"family":"Johnston","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":828913,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kennedy, Ben M. 0000-0001-7235-6493","orcid":"https://orcid.org/0000-0001-7235-6493","contributorId":270276,"corporation":false,"usgs":false,"family":"Kennedy","given":"Ben","email":"","middleInitial":"M.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":828914,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Magill, Christina R. 0000-0001-8872-1678","orcid":"https://orcid.org/0000-0001-8872-1678","contributorId":270277,"corporation":false,"usgs":false,"family":"Magill","given":"Christina","email":"","middleInitial":"R.","affiliations":[{"id":36277,"text":"GNS 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0000-0002-0252-8429","orcid":"https://orcid.org/0000-0002-0252-8429","contributorId":270279,"corporation":false,"usgs":false,"family":"Wardman","given":"John","email":"","affiliations":[{"id":56132,"text":"AXA XL","active":true,"usgs":false}],"preferred":false,"id":828918,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Weir, Alanna M. 0000-0001-7449-016X","orcid":"https://orcid.org/0000-0001-7449-016X","contributorId":270280,"corporation":false,"usgs":false,"family":"Weir","given":"Alanna","email":"","middleInitial":"M.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":828919,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Wilson, Grant","contributorId":270281,"corporation":false,"usgs":false,"family":"Wilson","given":"Grant","email":"","affiliations":[{"id":56133,"text":"National Emergency Management Agency, New Zealand","active":true,"usgs":false}],"preferred":false,"id":828920,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Zuccaro, Giulio 0000-0001-8572-067X","orcid":"https://orcid.org/0000-0001-8572-067X","contributorId":270282,"corporation":false,"usgs":false,"family":"Zuccaro","given":"Giulio","email":"","affiliations":[{"id":35512,"text":"University of Naples Federico II","active":true,"usgs":false}],"preferred":false,"id":828921,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}}
,{"id":70226907,"text":"sir20215132 - 2021 - Kootenai River white sturgeon (Acipenser transmontanus) fine-scale habitat selection and preference, Kootenai River near Bonners Ferry, Idaho, 2017","interactions":[],"lastModifiedDate":"2023-05-31T11:20:34.120912","indexId":"sir20215132","displayToPublicDate":"2021-12-20T12:52:33","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":"2021-5132","displayTitle":"Kootenai River White Sturgeon (<em>Acipenser transmontanus</em>) Fine-Scale Habitat Selection and Preference, Kootenai River near Bonners Ferry, Idaho, 2017","title":"Kootenai River white sturgeon (Acipenser transmontanus) fine-scale habitat selection and preference, Kootenai River near Bonners Ferry, Idaho, 2017","docAbstract":"<p class=\"p1\">To quantify fine-scale Kootenai River white sturgeon (<i>Acipenser transmontanus</i>) staging and spawning habitat selection and preference within a recently restored reach of the Kootenai River, the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, integrated acoustic telemetry data with two-dimensional hydraulic model simulations within a 1.5-kilometer reach of the Kootenai River near Bonners Ferry, northern Idaho. Twenty-seven individual Kootenai River white sturgeon were detected in the study reach during May 6–June 30, 2017. The largest concentration of fish positions occurred near the edge of the gravel bar adjacent to the right bank pool-forming structure and additional concentrations of fish positions occurred near two recently constructed rock substrate clusters. The difference in preferred and available depth distributions quantifies that Kootenai River white sturgeon generally preferred depths of 7–11.5 meters, deeper than the most frequently available depths. About 71 percent of the detections occurred within the lower one-third of the water column, placing Kootenai River white sturgeon at or near the channel bed. The difference in available and preferred water velocities indicated that Kootenai River white sturgeon generally preferred a wide range of velocities from 0.0 to 1.0 meters per second, and generally preferred velocities that were less than the most frequently occurring available velocities. Kootenai River white sturgeon generally preferred the downstream part of the study area where water velocities were less than those in the upstream part. This study concludes that Kootenai River white sturgeon generally avoided shallow areas with increased velocities and generally favored deep areas with lower velocities near recently constructed restoration structures.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215132","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Fosness, R.L., Dudunake, T.J., McDonald, R.R., Hardy, R.S., Young, S., Ireland, S., and Hoffman, G.C., 2021, Kootenai River white sturgeon (<em>Acipenser transmontanus</em>) fine-scale habitat selection and preference, Kootenai River near Bonners Ferry, Idaho, 2017: U.S. Geological Survey Scientific Investigations Report 2021–5132, 21 p., https://doi.org/10.3133/sir20215132.","productDescription":"Report: vii, 21 p; Data Release","onlineOnly":"Y","ipdsId":"IP-105165","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":396731,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5132/sir20215132.XML","description":"SIR 2021-5132"},{"id":393132,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97TMY3D","text":"USGS data release","description":"USGS Data Release","linkHelpText":"White sturgeon fine-scale habitat model archive, Kootenai River near Bonners Ferry, Idaho, 2017"},{"id":393131,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5132/sir20215132.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5132"},{"id":393130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5132/coverthb.jpg"},{"id":396944,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5132/images"},{"id":402990,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215132/full","description":"SIR 2021-5132"}],"country":"United States","state":"Idaho","city":"Bonners Ferry","otherGeospatial":"Kootenai River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.6802978515625,\n              48.58205840283824\n            ],\n            [\n              -116.05957031249999,\n              48.58205840283824\n            ],\n            [\n              -116.05957031249999,\n              48.99824008113872\n            ],\n            [\n              -116.6802978515625,\n              48.99824008113872\n            ],\n            [\n              -116.6802978515625,\n              48.58205840283824\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>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Kootenai River White Sturgeon Fine-Scale Habitat Selection and Preference</li><li>Considerations for Future Habitat Studies</li><li>Discussion</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2021-12-20","noUsgsAuthors":false,"publicationDate":"2021-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudunake, Taylor J. 0000-0001-7650-2419 tdudunake@usgs.gov","orcid":"https://orcid.org/0000-0001-7650-2419","contributorId":213485,"corporation":false,"usgs":true,"family":"Dudunake","given":"Taylor","email":"tdudunake@usgs.gov","middleInitial":"J.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":828744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":828745,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardy, Ryan S.","contributorId":167032,"corporation":false,"usgs":false,"family":"Hardy","given":"Ryan","email":"","middleInitial":"S.","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":828746,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, Shawn","contributorId":213546,"corporation":false,"usgs":false,"family":"Young","given":"Shawn","affiliations":[{"id":29827,"text":"Kootenai Tribe of Idaho, Bonners Ferry, ID, USA","active":true,"usgs":false}],"preferred":false,"id":828747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ireland, Susan","contributorId":270219,"corporation":false,"usgs":false,"family":"Ireland","given":"Susan","affiliations":[{"id":29827,"text":"Kootenai Tribe of Idaho, Bonners Ferry, ID, USA","active":true,"usgs":false}],"preferred":false,"id":828748,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hoffman, Gregory C.","contributorId":270220,"corporation":false,"usgs":false,"family":"Hoffman","given":"Gregory","email":"","middleInitial":"C.","affiliations":[{"id":12620,"text":"U.S. Army Corp. of Engineers","active":true,"usgs":false}],"preferred":false,"id":828749,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70226881,"text":"ofr20211114 - 2021 - Synthesis of habitat availability and carrying capacity research to support water management decisions and enhance conditions for Pacific salmon in the Willamette River, Oregon","interactions":[],"lastModifiedDate":"2021-12-21T14:36:54.966393","indexId":"ofr20211114","displayToPublicDate":"2021-12-20T09:58:57","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":"2021-1114","displayTitle":"Synthesis of Habitat Availability and Carrying Capacity Research to Support Water Management Decisions and Enhance Conditions for Pacific Salmon in the Willamette River, Oregon","title":"Synthesis of habitat availability and carrying capacity research to support water management decisions and enhance conditions for Pacific salmon in the Willamette River, Oregon","docAbstract":"<p class=\"p1\">Flow management is complex in the Willamette River Basin where the U.S. Army Corps of Engineers owns and operates a system of 13 dams and reservoirs (hereinafter Willamette Project), which are spread throughout three large tributaries including the Middle Fork Willamette, McKenzie, and Santiam Rivers. The primary purpose of the Willamette Project is flood-risk management, which provides critical protection to the Willamette Valley, but flow managers must also consider factors such as power generation, water-quality improvement, irrigation, recreation, and protection for aquatic species such as U.S. Endangered Species Act-listed Chinook salmon (<i>Oncorhynchus tshawytscha</i>) and steelhead (<i>O. mykiss</i>). Flow-management decision-making in the basin can benefit from models that allow for flow-scenario comparisons and a wide range of modeling methods are available. For this study, we examined existing datasets and modeling efforts in the basin and provided an overview of available options. Most previous studies used Physical Habitat Simulation System, habitat data were collected from a series of transects within modeled reaches, and habitat suitability indices were obtained from the literature, or using expert opinion. These studies provide information for specific reaches of the Willamette River Basin, which limits their ability to provide broad-scale predictive capability. Recent efforts to develop a two-dimensional hydraulic model in the mainstem Willamette River, and in specific reaches of primary tributaries downstream from Project dams, have bolstered modeling capabilities in the basin. This work has developed spatially continuous water depth and velocity data in more than 250 kilometers (km) of river downstream from Project dams and has predictive capability throughout the year at flows up to normal peak levels. Additionally, other methods are described for estimating habitat availability, which include habitat suitability criteria, logistic regression, occupancy and abundance modeling, and energetic based approaches. There are strengths and weaknesses to each approach and selection of the preferred approach in the Willamette River Basin will depend on the desired metrics of interest and the risk tolerance of managers and stakeholders in the basin.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211114","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Kock, T.J., Perry, R.W., Hansen, G.S., White, J., Stratton Garvin, L., and Wallick, J.R., 2021, Synthesis of habitat availability and carrying capacity research to support water management decisions and enhance conditions for Pacific salmon in the Willamette River, Oregon: U.S. Geological Survey Open-File Report 2021–1114, 24 p., https://doi.org/10.3133/ofr20211114.","productDescription":"vii, 24 p.","onlineOnly":"Y","ipdsId":"IP-127909","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":393073,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1114/ofr20211114.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1114"},{"id":393072,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1114/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.33251953125,\n              43.41302868475145\n            ],\n            [\n              -121.59667968749999,\n              43.41302868475145\n            ],\n            [\n              -121.59667968749999,\n              45.79050946752472\n            ],\n            [\n              -123.33251953125,\n              45.79050946752472\n            ],\n            [\n              -123.33251953125,\n              43.41302868475145\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>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Objective 1—Review Existing Willamette River Datasets and Identify Key Data Gaps</li><li>Objective 2—Summarize Methods to Estimate Habitat Availability</li><li>Objective 3—Identify Optimal Methods for Estimating Carrying Capacity and its Influence on Density-Dependent Processes in the Willamette River and its Major Tributaries</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2021-12-20","noUsgsAuthors":false,"publicationDate":"2021-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":828608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":828609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Gabriel S. 0000-0001-6272-3632 ghansen@usgs.gov","orcid":"https://orcid.org/0000-0001-6272-3632","contributorId":3422,"corporation":false,"usgs":true,"family":"Hansen","given":"Gabriel","email":"ghansen@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":828610,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, James 0000-0002-7255-3785 jameswhite@usgs.gov","orcid":"https://orcid.org/0000-0002-7255-3785","contributorId":193492,"corporation":false,"usgs":true,"family":"White","given":"James","email":"jameswhite@usgs.gov","affiliations":[],"preferred":true,"id":828611,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stratton Garvin, Laurel E. 0000-0001-8567-8619 lstratton@usgs.gov","orcid":"https://orcid.org/0000-0001-8567-8619","contributorId":270182,"corporation":false,"usgs":true,"family":"Stratton Garvin","given":"Laurel","email":"lstratton@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828612,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wallick, J. Rose 0000-0002-9392-272X rosewall@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-272X","contributorId":3583,"corporation":false,"usgs":true,"family":"Wallick","given":"J. Rose","email":"rosewall@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828613,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226963,"text":"70226963 - 2021 - Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area","interactions":[],"lastModifiedDate":"2021-12-22T12:45:24.962293","indexId":"70226963","displayToPublicDate":"2021-12-20T06:41:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Advances in estimating actual evapotranspiration (ETa) with remote sensing (RS) have contributed to improving hydrological, agricultural, and climatological studies. In this study, we evaluated the applicability of Vegetation-Index (VI) -based ETa (ET-VI) for mapping and monitoring drought in arid agricultural systems in a region where a lack of ground data hampers ETa work. To map ETa (2000–2019), ET-VIs were translated and localized using Landsat-derived 3- and 2-band Enhanced Vegetation Indices (EVI and EVI2) over croplands in the Zayandehrud River Basin (ZRB) in Iran. Since EVI and EVI2 were optimized for the MODerate Imaging Spectroradiometer (MODIS), using these VIs with Landsat sensors required a cross-sensor transformation to allow for their use in the ET-VI algorithm. The before- and after- impact of applying these empirical translation methods on the ETa estimations was examined. We also compared the effect of cropping patterns’ interannual change on the annual ETa rate using the maximum Normalized Difference Vegetation Index (NDVI) time series. The performance of the different ET-VIs products was then evaluated. Our results show that ETa estimates agreed well with each other and are all suitable to monitor ETa in the ZRB. Compared to ETc values, ETa estimations from MODIS-based continuity corrected Landsat-EVI (EVI2) (EVI<sub>MccL</sub><span>&nbsp;</span>and EVI2<sub>MccL</sub>) performed slightly better across croplands than those of Landsat-EVI (EVI2) without transformation. The analysis of harvested areas and ET-VIs anomalies revealed a decline in the extent of cultivated areas and a loss of corresponding water resources downstream. The findings show the importance of continuity correction across sensors when using empirical algorithms designed and optimized for specific sensors. Our comprehensive ETa estimation of agricultural water use at 30 m spatial resolution provides an inexpensive monitoring tool for cropping areas and their water consumption.<span>&nbsp;</span></div>","language":"English","publisher":"MDPI","doi":"10.3390/rs13245167","usgsCitation":"Abbasi, N., Nouri, H., Didan, K., Barreto Munez, A., Chavoshi Borujeni, S., Salemi, H., Opp, C., Siebert, S., and Nagler, P.L., 2021, Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area: Remote Sensing, v. 13, no. 24, 5167, 27 p., https://doi.org/10.3390/rs13245167.","productDescription":"5167, 27 p.","ipdsId":"IP-133278","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":450008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13245167","text":"Publisher Index Page"},{"id":393291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"24","noUsgsAuthors":false,"publicationDate":"2021-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Abbasi, Neda","contributorId":270293,"corporation":false,"usgs":false,"family":"Abbasi","given":"Neda","email":"","affiliations":[{"id":56138,"text":"Dept of Crop Sciences, University of Göttingen, Von-Siebold-Straße 8, 37075, Göttingen, Germany; Dept of Geography, Philipps-Universität Marburg, Deutschhausstraße 10, 35032, Marburg, Germany","active":true,"usgs":false}],"preferred":false,"id":828951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nouri, Hamideh","contributorId":178847,"corporation":false,"usgs":false,"family":"Nouri","given":"Hamideh","affiliations":[],"preferred":false,"id":828952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":828953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barreto Munez, Armando","contributorId":270294,"corporation":false,"usgs":false,"family":"Barreto Munez","given":"Armando","email":"","affiliations":[{"id":56140,"text":"Biosystems Engineering. The University of Arizona, 1177 E. 4th St., Tucson, AZ 85719, USA","active":true,"usgs":false}],"preferred":false,"id":828954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chavoshi Borujeni, Sattar","contributorId":241612,"corporation":false,"usgs":false,"family":"Chavoshi Borujeni","given":"Sattar","email":"","affiliations":[{"id":48363,"text":"Soil Conservation and Watershed Management Research Department, Isfahan Agricultural and Natural Resources Research and Education Centre, AREEO, Isfahan, Iran","active":true,"usgs":false}],"preferred":false,"id":828955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salemi, Hamidreza","contributorId":270295,"corporation":false,"usgs":false,"family":"Salemi","given":"Hamidreza","email":"","affiliations":[{"id":56141,"text":"Agricultural Engineering Research Institute, Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan 19395-1113, Iran","active":true,"usgs":false}],"preferred":false,"id":828956,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Opp, Christian","contributorId":270296,"corporation":false,"usgs":false,"family":"Opp","given":"Christian","email":"","affiliations":[{"id":56142,"text":"Dept of Geography, Philipps-Universität Marburg, Deutschhausstraße 10, 35032, Marburg, Germany","active":true,"usgs":false}],"preferred":false,"id":828957,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siebert, Stefan","contributorId":270297,"corporation":false,"usgs":false,"family":"Siebert","given":"Stefan","email":"","affiliations":[{"id":56143,"text":"Dept of Crop Sciences, University of Göttingen, Von-Siebold-Straße 8, 37075, Göttingen, Germany","active":true,"usgs":false}],"preferred":false,"id":828958,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":828959,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70226852,"text":"sir20215138 - 2021 - Streamflow response to potential changes in climate in the Upper Rio Grande Basin","interactions":[],"lastModifiedDate":"2022-01-04T23:47:17.277742","indexId":"sir20215138","displayToPublicDate":"2021-12-16T16:27:02","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":"2021-5138","displayTitle":"Streamflow Response to Potential Changes in Climate in the Upper Rio Grande Basin","title":"Streamflow response to potential changes in climate in the Upper Rio Grande Basin","docAbstract":"<p>The Rio Grande is a vital water source for the southwestern States of Colorado, New Mexico, and Texas and for northern Mexico. The river serves as the primary source of water for irrigation in the region, has many environmental and recreational uses, and is used by more than 13 million people including those in the Cities of Albuquerque and Las Cruces, New Mexico; El Paso, Texas; and Ciudad Juárez, Chihuahua, Mexico. However, concern is growing over the increasing gap between water supply and demand in the Upper Rio Grande Basin. As populations increase and agricultural crop patterns change, demands for water are increasing, at the same time the region is undergoing a decrease in supply due to drought and climate change.</p><p>Quantifying the impact of projected climate change on Rio Grande streamflow is difficult because of numerous anthropogenic influences on the hydrologic system. The conveyance and use of surface water in the Upper Rio Grande Basin are achieved through an engineered system of reservoirs, diversions, and irrigation canals designed to deliver water to agricultural, municipal, and industrial users, who greatly reduce the cumulative volume of water in the river. For example, streamflow at Fort Quitman, Tex., the southernmost point of the Upper Rio Grande Basin, has undergone a 95-percent reduction in flow relative to the river’s native state, and some stretches of the river can intermittently go dry. Because streamflow in the basin is highly altered, disentangling the impacts of climate change and changes in streamflow due to anthropogenic influences such as dams, diversions, and other forms of water use is difficult. Therefore, a model of naturalized flow was developed to determine to what degree changes in streamflow can be attributed to potential changes in future temperature and precipitation without quantifying future changes in anthropogenic influences. This study, conducted by the U.S. Geological Survey in cooperation with the South Central Climate Adaptation Science Center and the U.S. Army Corps of Engineers, included the development and calibration of a watershed model of the Upper Rio Grande Basin using the Precipitation-Runoff Modeling System to simulate naturalized streamflow conditions for historical and future time periods.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215138","collaboration":"Prepared in cooperation with the South Central Climate Adaptation Science Center","usgsCitation":"Moeser, C.D., Chavarria, S.B., and Wootten, A.M., 2021, Streamflow response to potential changes in climate in the Upper Rio Grande Basin: U.S. Geological Survey Scientific Investigations Report 2021–5138, 41 p., https://doi.org/10.3133/sir20215138.","productDescription":"Report: x, 41 p.; Data Release","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125477","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":49928,"text":"South Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":393890,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://webapps.usgs.gov/urgb-prms/","text":"Streamflow Response to Potential Changes in Climate—Upper Rio Grande Basin"},{"id":392955,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5138/sir20215138.pdf","text":"Report","size":"25.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5138"},{"id":392954,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5138/coverthb.jpg"},{"id":392958,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5138/images"},{"id":392956,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ML93QB","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Hydrologic simulations using projected climate data as input to the Precipitation-Runoff Modeling System (PRMS) in the Upper Rio Grande Basin (ver. 2.0, September 2021)"}],"country":"Mexico, United States","state":"Colorado, New Mexico, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.7314453125,\n              30.410781790845864\n            ],\n            [\n              -102.21679687500001,\n              30.410781790845864\n            ],\n            [\n              -102.21679687500001,\n              38.30718056188316\n            ],\n            [\n              -109.7314453125,\n              38.30718056188316\n            ],\n            [\n              -109.7314453125,\n              30.410781790845864\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/nm-water\" href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a> <br>U.S. Geological Survey <br>6700 Edith Blvd. NE <br>Albuquerque, NM 87113</p><p><a data-mce-href=\"../contact\" 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>Conclusion</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-12-16","noUsgsAuthors":false,"publicationDate":"2021-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Moeser, C. David 0000-0003-0154-9110","orcid":"https://orcid.org/0000-0003-0154-9110","contributorId":214563,"corporation":false,"usgs":true,"family":"Moeser","given":"C.","email":"","middleInitial":"David","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chavarria, Shaleene B. 0000-0001-8792-1010","orcid":"https://orcid.org/0000-0001-8792-1010","contributorId":223376,"corporation":false,"usgs":true,"family":"Chavarria","given":"Shaleene","email":"","middleInitial":"B.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wootten, Adrienne M. 0000-0001-6004-5823","orcid":"https://orcid.org/0000-0001-6004-5823","contributorId":270141,"corporation":false,"usgs":false,"family":"Wootten","given":"Adrienne","email":"","middleInitial":"M.","affiliations":[{"id":49928,"text":"South Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":828491,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70226709,"text":"sir20215124 - 2021 - Groundwater chemistry, hydrogeologic properties, bioremediation potential, and three-dimensional numerical simulation of the sand and gravel aquifer at Naval Air Station Whiting Field, near Milton, Florida, 2015–20","interactions":[],"lastModifiedDate":"2022-04-14T16:00:18.279252","indexId":"sir20215124","displayToPublicDate":"2021-12-16T14:25:00","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":"2021-5124","displayTitle":"Groundwater Chemistry, Hydrogeologic Properties, Bioremediation Potential, and Three-Dimensional Numerical Simulation of the Sand and Gravel Aquifer at Naval Air Station Whiting Field, near Milton, Florida, 2015–20","title":"Groundwater chemistry, hydrogeologic properties, bioremediation potential, and three-dimensional numerical simulation of the sand and gravel aquifer at Naval Air Station Whiting Field, near Milton, Florida, 2015–20","docAbstract":"<p>The U.S. Geological Survey completed a study between 2015 and 2020 of groundwater contamination in the sand and gravel aquifer at a Superfund site in northwestern Florida. Groundwater-quality samples were collected from representative monitoring wells located along a groundwater-flow pathway and analyzed in the field and laboratory. In general, ambient groundwater in the sand and gravel aquifer is acidic, dilute, and oxic. Groundwater age-dating results indicate recharge to the contaminated parts of the aquifer occurred between the 1970s and 1980s. Natural gamma, electromagnetic induction, and borehole nuclear magnetic resonance logs indicated that aquifer hydraulic conductivities generally increased with depth as the aquifer formation material became coarser, characteristic of a prograding marginal-marine delta depositional environment. Aquifer formation material incubated with radiocarbon (carbon-14) <i>cis</i>-1,2-Dichloroethylene demonstrated biodegradation directly to carbon dioxide in contaminated and uncontaminated parts of the aquifer. A three-dimensional, numerical groundwater-flow MODFLOW model of the sand and gravel aquifer in the study area was constructed. The calibrated model reasonably reproduced measured groundwater heads and streamflows. Moreover, the model can be used to run simulations of outcomes of potential remedial strategies, such as monitored natural attenuation, as part of future feasibility studies in the area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215124","collaboration":"Prepared in cooperation with the U.S. Navy Naval Facilities Engineering Systems Command Southeast","usgsCitation":"Landmeyer, J.E., Swain, E.D., Johnson, C.D., Lisle, J.T., McBride, W.S., Chung, D.H., and Singletary, M.A., 2021, Groundwater chemistry, hydrogeologic properties, bioremediation potential, and three-dimensional numerical simulation of the sand and gravel aquifer at Naval Air Station Whiting Field, near Milton, Florida, 2015–20: U.S. Geological Survey Scientific Investigations Report 2021–5124, 52 p., https://doi.org/10.3133/sir20215124.","productDescription":"Report: xi, 52 p.; Data Release: Dataset","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-119956","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":393011,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215124/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":393010,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M0OD8F","text":"USGS data release","linkHelpText":"MODFLOW simulator used to assess groundwater flow for the Whiting Field Naval Air Station, Milton, FL"},{"id":392549,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":392548,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5124/images/"},{"id":392547,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5124/sir20215124.XML"},{"id":392546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5124/sir20215124.pdf","text":"Report","size":"4.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5124"},{"id":392545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5124/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Naval Air Station Whiting Field","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.10304260253906,\n              30.621368403494955\n            ],\n            [\n              -86.89773559570312,\n              30.621368403494955\n            ],\n            [\n              -86.89773559570312,\n              30.784317689718897\n            ],\n            [\n              -87.10304260253906,\n              30.784317689718897\n            ],\n            [\n              -87.10304260253906,\n              30.621368403494955\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<br>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>Description of the Study Area</li><li>Methods</li><li>Results and Discussion of Sand and Gravel Aquifer Analysis</li><li>Assumptions and Limitations of Methods Used</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2021-12-16","noUsgsAuthors":false,"publicationDate":"2021-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Landmeyer, James 0000-0002-5640-3816 jlandmey@usgs.gov","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":3257,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"jlandmey@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Carole D. 0000-0001-6941-1578 cjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":1891,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole","email":"cjohnson@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":827884,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lisle, John T. 0000-0002-5447-2092 jlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-5447-2092","contributorId":2944,"corporation":false,"usgs":true,"family":"Lisle","given":"John","email":"jlisle@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":827885,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McBride, W. Scott 0000-0003-1828-2838","orcid":"https://orcid.org/0000-0003-1828-2838","contributorId":201573,"corporation":false,"usgs":true,"family":"McBride","given":"W.","email":"","middleInitial":"Scott","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":827886,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chung, David H.","contributorId":269778,"corporation":false,"usgs":false,"family":"Chung","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":36522,"text":"U.S. Navy","active":true,"usgs":false}],"preferred":true,"id":827887,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Singletary , Michael A. ","contributorId":184217,"corporation":false,"usgs":false,"family":"Singletary ","given":"Michael A. ","affiliations":[],"preferred":false,"id":827888,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70228839,"text":"70228839 - 2021 - Oral sylvatic plague vaccine does not adequately protect prairie dogs (Cynomys spp.) for endangered black-footed ferret (Mustela nigripes) conservation","interactions":[],"lastModifiedDate":"2022-02-23T12:38:42.085936","indexId":"70228839","displayToPublicDate":"2021-12-16T06:32:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3675,"text":"Vector-Borne and Zoonotic Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Oral sylvatic plague vaccine does not adequately protect prairie dogs (Cynomys spp.) for endangered black-footed ferret (Mustela nigripes) conservation","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>The plague bacterium<span>&nbsp;</span><i>Yersinia pestis</i><span>&nbsp;</span>is lethal to endangered black-footed ferrets (<i>Mustela nigripes</i>, BFF) and the prairie dogs (<i>Cynomys</i><span>&nbsp;</span>spp., PD) on which they depend for habitat and prey. We assessed the effectiveness of an oral sylvatic plague vaccine delivered in baits to black-tailed PD (<i>Cynomys ludovicianus</i>, BTPD) from 2013 to 2017 on the Charles M. Russell National Wildlife Refuge (CMR) in northcentral Montana. We permanently marked BTPD on four paired vaccine (<i>N</i> = 1,349 individuals) and placebo plots (<i>N</i> = 926; 7,027 total captures). We analyzed capture–recapture data under a Cormack–Jolly–Seber model to estimate annual apparent survival. Overall, survival averaged 0.05 lower on vaccine plots than on paired placebo plots. Immediately before noticeable die-offs and detecting plague on pairs CMR1 and CMR2, 89% of BTPD sampled on vaccine plots had consumed at least one bait and the immune systems (pleural) of 40% were likely boosted by consuming baits over multiple years. Survival to the following year was 0.16 and 0.05 on the vaccine plots and 0.19 and 0.06 on the placebo plots for pairs CMR1 and CMR2, respectively. These rates were markedly lower than 0.63, the overall average estimate on those same plots during the previous 3 years. PD populations subjected to such large die-offs would not be expected to sustain a BFF population. An overriding limitation to achieving sufficient protection rests with vaccine delivery constraints. Late summer/fall bait distribution results in the highest bait uptake rates. However, the PD birth pulse each spring can double the size of populations in most years, greatly reducing the proportion of vaccinates in populations and diminishing potential herd immunity benefits. In addition to nonvaccinated juveniles and PD that do not consume bait, incomplete vaccine protection and time required for immunity to develop leaves a large majority of PD populations vulnerable to plague for 6–7 months or more each year.</p></div></div>","language":"English","publisher":"Mary Ann Liebert, Inc. Publishers","doi":"10.1089/vbz.2021.0049","usgsCitation":"Matchett, M.R., Stanley, T., McCollister, M.F., Eads, D.A., Boulerice, J., and Biggins, D.E., 2021, Oral sylvatic plague vaccine does not adequately protect prairie dogs (Cynomys spp.) for endangered black-footed ferret (Mustela nigripes) conservation: Vector-Borne and Zoonotic Diseases, v. 21, no. 12, p. 921-940, https://doi.org/10.1089/vbz.2021.0049.","productDescription":"20 p.","startPage":"921","endPage":"940","ipdsId":"IP-126549","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":450015,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8742283","text":"Publisher Index Page"},{"id":436086,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98EGZYI","text":"USGS data release","linkHelpText":"Black-tailed prairie dog movement and bait uptake data from 2013-2017 in Montana"},{"id":436085,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JAZVE6","text":"USGS data release","linkHelpText":"Black-tailed prairie dog capture data from plots treated and not treated with oral plague vaccine from 2013-2017 in Montana"},{"id":396330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Charles M. Russell National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.34167480468749,\n              47.15984001304432\n            ],\n            [\n              -105.765380859375,\n              47.15984001304432\n            ],\n            [\n              -105.765380859375,\n              48.188063481211415\n            ],\n            [\n              -108.34167480468749,\n              48.188063481211415\n            ],\n            [\n              -108.34167480468749,\n              47.15984001304432\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"21","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Matchett, Marc R.","contributorId":193409,"corporation":false,"usgs":false,"family":"Matchett","given":"Marc","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":835678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanley, Thomas 0000-0002-8393-0005","orcid":"https://orcid.org/0000-0002-8393-0005","contributorId":210435,"corporation":false,"usgs":true,"family":"Stanley","given":"Thomas","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCollister, Matthew F.","contributorId":264909,"corporation":false,"usgs":false,"family":"McCollister","given":"Matthew","email":"","middleInitial":"F.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":835680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":835681,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boulerice, Jesse","contributorId":279879,"corporation":false,"usgs":false,"family":"Boulerice","given":"Jesse","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":835682,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835683,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70266382,"text":"70266382 - 2021 - Predicting thermal responses of an Arctic lake to whole-lake warming manipulation","interactions":[],"lastModifiedDate":"2025-05-06T15:02:44.848921","indexId":"70266382","displayToPublicDate":"2021-12-16T00:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Predicting thermal responses of an Arctic lake to whole-lake warming manipulation","docAbstract":"We investigated how lake thermal processes responded to whole lake warming manipulation in an arctic lake through observations and numerical modeling. The warming manipulation was conducted by artificially heating the epilimnion as a proxy for climate warming. We performed numerical modeling with an improved lake scheme based on the Community Land Model (CLM). We simulated a control run (CTL) without warming and a warming manipulation simulation (WARM). Results indicated WARM accurately captured observed temperatures where water stratification was extended in time, and water stability was strengthened. Two additional sensitivity tests with different warming onset dates and of the same warming duration showed that earlier warming onsets are predicted to make the water column more stable and less easily mixed relative to a later onset of warming. The results provide a more complete understanding of lake thermal processes in arctic freshwater lake systems and how they will respond to predicted future warming.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021gl092680","collaboration":"Anne Giblin, Byron Crump","usgsCitation":"Zhang, Q., Jin, J., Budy, P., Null, S., Wang, X., and Pennock, C., 2021, Predicting thermal responses of an Arctic lake to whole-lake warming manipulation: Geophysical Research Letters, v. 48, no. 23, e2021GL092680, 10 p., https://doi.org/10.1029/2021gl092680.","productDescription":"e2021GL092680, 10 p.","ipdsId":"IP-127181","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Toolik Field Station","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -151.2972961040461,\n              69.55756830975835\n            ],\n            [\n              -151.2972961040461,\n              67.43265585446878\n            ],\n            [\n              -144.82092178397554,\n              67.43265585446878\n            ],\n            [\n              -144.82092178397554,\n              69.55756830975835\n            ],\n            [\n              -151.2972961040461,\n              69.55756830975835\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"23","noUsgsAuthors":false,"publicationDate":"2021-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Qunhui","contributorId":354518,"corporation":false,"usgs":false,"family":"Zhang","given":"Qunhui","affiliations":[{"id":66237,"text":"College of Resources and Environmental Science, Hunan Normal University, Changsha 410081, China","active":true,"usgs":false}],"preferred":false,"id":935789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jin, Jiming","contributorId":354519,"corporation":false,"usgs":false,"family":"Jin","given":"Jiming","affiliations":[{"id":66237,"text":"College of Resources and Environmental Science, Hunan Normal University, Changsha 410081, China","active":true,"usgs":false}],"preferred":false,"id":935790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Null, Sarah E.","contributorId":354520,"corporation":false,"usgs":false,"family":"Null","given":"Sarah E.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":935791,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Xiaochun","contributorId":354521,"corporation":false,"usgs":false,"family":"Wang","given":"Xiaochun","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":935792,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pennock, Casey A.","contributorId":354523,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":935793,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226871,"text":"70226871 - 2021 - Effects of low pH on the coral reef cryptic invertebrate communities near CO2 vents in Papua New Guinea","interactions":[],"lastModifiedDate":"2021-12-17T14:43:26.31306","indexId":"70226871","displayToPublicDate":"2021-12-15T08:27:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of low pH on the coral reef cryptic invertebrate communities near CO<sub>2</sub> vents in Papua New Guinea","title":"Effects of low pH on the coral reef cryptic invertebrate communities near CO2 vents in Papua New Guinea","docAbstract":"<p><span>Small cryptic invertebrates (the cryptofauna) are extremely abundant, ecologically important, and species rich on coral reefs. Ongoing ocean acidification is likely to have both direct effects on the biology of these organisms, as well as indirect effects through cascading impacts on their habitats and trophic relationships. Naturally acidified habitats have been important model systems for studying these complex interactions because entire communities that are adapted to these environmental conditions can be analyzed. However, few studies have examined the cryptofauna because they are difficult to census quantitatively in topographically complex habitats and are challenging to identify. We addressed these challenges by using Autonomous Reef Monitoring Structures (ARMS) for sampling reef-dwelling invertebrates &gt;2 mm in size and by using DNA barcoding for taxonomic identifications. The study took place in Papua New Guinea at two reef localities, each with three sites at varying distances from carbon dioxide seeps, thereby sampling across a natural gradient in acidification. We observed sharp overall declines in both the abundance (34–56%) and diversity (42–45%) of organisms in ARMS under the lowest pH conditions sampled (7.64–7.75). However, the overall abundance of gastropods increased slightly in lower pH conditions, and crustacean and gastropod families exhibited varying patterns. There was also variability in response between the two localities, despite their close proximity, as one control pH site displayed unusually low diversity and abundances for all invertebrate groups. The data illustrate the complexity of responses of the reef fauna to pH conditions, and the role of additional factors that influence the diversity and abundance of cryptic reef invertebrates.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0258725","usgsCitation":"Plaisance, L., Matterson, K., Fabricius, K., Drovetski, S.V., Meyer, C.F., and Knowlton, N., 2021, Effects of low pH on the coral reef cryptic invertebrate communities near CO2 vents in Papua New Guinea: PLoS ONE, v. 16, no. 12, e0258725, 19 p., https://doi.org/10.1371/journal.pone.0258725.","productDescription":"e0258725, 19 p.","ipdsId":"IP-125629","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":450019,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0258725","text":"Publisher Index Page"},{"id":393046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Papua New Guinea","state":"Milne Bay Province","otherGeospatial":"Dobu, Upa Upasina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              150.8474349975586,\n              -9.771994523201766\n            ],\n            [\n              150.8917236328125,\n              -9.771994523201766\n            ],\n            [\n              150.8917236328125,\n              -9.733590552033547\n            ],\n            [\n              150.8474349975586,\n              -9.733590552033547\n            ],\n            [\n              150.8474349975586,\n              -9.771994523201766\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              150.77533721923828,\n              -9.812593019509318\n            ],\n            [\n              150.79696655273438,\n              -9.812593019509318\n            ],\n            [\n              150.79696655273438,\n              -9.791279427997022\n            ],\n            [\n              150.77533721923828,\n              -9.791279427997022\n            ],\n            [\n              150.77533721923828,\n              -9.812593019509318\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Plaisance, Laetitia","contributorId":270161,"corporation":false,"usgs":false,"family":"Plaisance","given":"Laetitia","email":"","affiliations":[{"id":56101,"text":"Laboratoire Evolution et Diversité Biologique, CNRS/UPS, Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":828550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matterson, Kenan O.","contributorId":203367,"corporation":false,"usgs":false,"family":"Matterson","given":"Kenan O.","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":828551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fabricius, Katharina","contributorId":270162,"corporation":false,"usgs":false,"family":"Fabricius","given":"Katharina","email":"","affiliations":[{"id":56102,"text":"Australian Institute of Marine Science, Townsville, Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":828552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drovetski, Sergei V. 0000-0002-1832-5597","orcid":"https://orcid.org/0000-0002-1832-5597","contributorId":229520,"corporation":false,"usgs":true,"family":"Drovetski","given":"Sergei","middleInitial":"V.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":828553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyer, Christoph F. J.","contributorId":245693,"corporation":false,"usgs":false,"family":"Meyer","given":"Christoph","email":"","middleInitial":"F. J.","affiliations":[{"id":49282,"text":"Centre for Ecology, Evolution & Environmental Changes, University of Lisbon, Portugal; National Institute for Amazonian Research & Smithsonian Tropical Research Institute, Manaus, Brazil; University of Salford, UK","active":true,"usgs":false}],"preferred":false,"id":828554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knowlton, Nancy","contributorId":174345,"corporation":false,"usgs":false,"family":"Knowlton","given":"Nancy","email":"","affiliations":[{"id":27432,"text":"Department of Invertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, USA","active":true,"usgs":false}],"preferred":false,"id":828555,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70230949,"text":"70230949 - 2021 - How well do we know Europa’s topography? An evaluation of the variability in digital terrain models of Europa.","interactions":[],"lastModifiedDate":"2022-04-29T12:14:14.148908","indexId":"70230949","displayToPublicDate":"2021-12-15T07:12:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"How well do we know Europa’s topography? An evaluation of the variability in digital terrain models of Europa.","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Jupiter’s moon Europa harbors one of the most likely environments for extant extraterrestrial life. Determining whether Europa is truly habitable requires understanding the structure and thickness of its ice shell, including the existence of perched water or brines. Stereo-derived topography from images acquired by NASA Galileo’s Solid State Imager (SSI) of Europa are often used as a constraint on ice shell structure and heat flow, but the uncertainty in such topography has, to date, not been rigorously assessed. To evaluate the current uncertainty in Europa’s topography we generated and compared digital terrain models (DTMs) of Europa from SSI images using both the open-source Ames Stereo Pipeline (ASP) software and the commercial SOCET SET<sup>®</sup><span>&nbsp;</span>software. After first describing the criteria for assessing stereo quality in detail, we qualitatively and quantitatively describe both the horizontal resolution and vertical precision of the DTMs. We find that the horizontal resolution of the SOCET SET<sup>®</sup><span>&nbsp;</span>DTMs is typically 8–11× the root mean square (RMS) pixel scale of the images, whereas the resolution of the ASP DTMs is 9–13× the maximum pixel scale of the images. We calculate the RMS difference between the ASP and SOCET SET<sup>®</sup><span>&nbsp;</span>DTMs as a proxy for the expected vertical precision (EP), which is a function of the matching accuracy and stereo geometry. We consistently find that the matching accuracy is ~0.5 pixels, which is larger than well-established “rules of thumb” that state that the matching accuracy is 0.2–0.3 pixels. The true EP is therefore ~1.7× larger than might otherwise be assumed. In most cases, DTM errors are approximately normally distributed, and errors that are several times the derived EP occur as expected. However, in two DTMs, larger errors (differences) occur and correlate with real topography. These differences primarily result from manual editing of the SOCET SET<sup>®</sup><span>&nbsp;</span>DTMs. The product of the DTM error and the resolution is typically 4–8 pixel<sup>2</sup><span>&nbsp;</span>if calculated using the RMS image scale for SOCET SET<sup>®</sup><span>&nbsp;</span>DTMs and the maximum images scale for the ASP DTMs, which is consistent with recent work using martian data sets and suggests that the relationship applies more broadly. We evaluate how ASP parameters affect DTM quality and find that using a smaller subpixel refinement kernel results in DTMs with smaller (better) resolution but, in some cases, larger gaps, which are sometimes reduced by increasing the size of the correlation kernel. We conclude that users of ASP should always systematically evaluate the choice of parameters for a given dataset.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/rs13245097","usgsCitation":"Bland, M.T., Kirk, R.L., Galuszka, D.M., Mayer, D., Beyer, R.A., and Fergason, R.L., 2021, How well do we know Europa’s topography? An evaluation of the variability in digital terrain models of Europa.: Remote Sensing, v. 13, no. 24, 5097, 49 p., https://doi.org/10.3390/rs13245097.","productDescription":"5097, 49 p.","ipdsId":"IP-134770","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":450025,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13245097","text":"Publisher Index Page"},{"id":399885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"24","noUsgsAuthors":false,"publicationDate":"2021-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":841694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":841695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galuszka, Donna M. 0000-0003-1870-1182 dgaluszka@usgs.gov","orcid":"https://orcid.org/0000-0003-1870-1182","contributorId":3186,"corporation":false,"usgs":true,"family":"Galuszka","given":"Donna","email":"dgaluszka@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":841696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, David 0000-0001-8351-1807","orcid":"https://orcid.org/0000-0001-8351-1807","contributorId":215429,"corporation":false,"usgs":true,"family":"Mayer","given":"David","email":"","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":841697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beyer, R. 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,{"id":70226829,"text":"ofr20211094 - 2021 - Geochronologic, isotopic, and geochemical data from pre-Cretaceous plutonic rocks in the Lane Mountain area, San Bernardino County, California","interactions":[],"lastModifiedDate":"2023-03-29T17:44:09.016282","indexId":"ofr20211094","displayToPublicDate":"2021-12-14T12:02:52","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":"2021-1094","displayTitle":"Geochronologic, Isotopic, and Geochemical Data from Pre- Cretaceous Plutonic Rocks in the Lane Mountain Area, San Bernardino County, California","title":"Geochronologic, isotopic, and geochemical data from pre-Cretaceous plutonic rocks in the Lane Mountain area, San Bernardino County, California","docAbstract":"<p>Pre-Cretaceous, predominantly dioritic plutonic rocks in the Lane Mountain area, California, intrude metasedimentary and metavolcanic rocks considered part of the El Paso terrane. New geochronologic (uranium-lead zircon), geochemical, and isotopic data provide a reliable basis for dividing these pre-Cretaceous plutonic rocks into two mappable suites of Permian–Triassic and Late Jurassic ages. The 26 Permian–Triassic samples included in this report have a mean age of ~248 mega-annum (Ma), range in composition from monzodiorite to quartz monzonite and granodiorite, and have a mean initial <sup>87</sup>Sr/<sup>86</sup>Sr ratio (Sri) of ~0.7045. The 22 Late Jurassic samples have a mean age of ~149 Ma, range in composition from gabbro to granite, and have a mean Sr<sub>i</sub> of ~0.7055. Accurate mapping of these two plutonic suites and their detailed field relations with the associated metamorphic rocks is essential for resolving the geologic history and regional tectonic significance of the Lane Mountain area.</p><p>The sub-0.706 Sr<sub>i</sub> values of both plutonic suites at Lane Mountain are consistent with previous suggestions that the El Paso terrane is allochthonous and did not develop on Precambrian continental lithosphere. Both suites are considered parts of northwest-trending magmatic arcs interpreted to have formed above east-dipping subduction zones along the evolving North American continental margin, and both arcs are interpreted to cross a major east-west-trending boundary between the El Paso terrane and rocks considered part of ancestral North America in the San Bernardino Mountains area to the south. The El Paso terrane thus appears to have been attached to the San Bernardino Mountains area at least since Permian–Triassic time, although the boundary probably has been modified by Cenozoic faulting.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211094","usgsCitation":"Stone, P., Brown, H.J., Cecil, M.R., Fleck, R.J., Vazquez, J.A., and Fitzpatrick, J.A., 2021, Geochronologic, isotopic, and geochemical data from pre-Cretaceous plutonic rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2021–1094, 74 p., https://doi.org/10.3133/ofr20211094.","productDescription":"viii, 74 p.","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-121822","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":436088,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KRD45S","text":"USGS data release","linkHelpText":"Tabular geochronologic, geochemical, and isotopic data from igneous rocks in the Lane Mountain area, San Bernardino County, California"},{"id":414904,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221115","text":"Open-File Report 2022-1115","description":"Stone, P., Cecil, M.R., Brown, H.J., and Vazquez, J.A., 2023, Geochronologic and geochemical data from metasedimentary and associated rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2022–1115, 34 p., https://doi.org/10.3133/ofr20221115.","linkHelpText":"- Geochronologic and Geochemical Data from Metasedimentary and Associated Rocks in the Lane Mountain Area, San Bernardino County, California"},{"id":392864,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191070","text":"Open-File Report 2019-1070","linkHelpText":"- Geochronologic, Isotopic, and Geochemical Data from Igneous Rocks in the Lane Mountain Area, San Bernardino County, California"},{"id":392863,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1094/ofr20211094.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":392862,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1094/covrthb.jpg"}],"country":"United States","state":"California","county":"San Berdardino 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Bernardino\",\"state\":\"CA\"}}]}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg/connect\">Contact Information</a>,<br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Menlo Park, California</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>Building 19, 350 N. Akron Rd.<br>P.O. Box 158<br>Moffett Field, CA 94035</p>","tableOfContents":"<ul><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Methods&nbsp;&nbsp;</li><li>Analytical Results&nbsp;&nbsp;</li><li>Map Relations in the Lane Mountain Area&nbsp;&nbsp;</li><li>Regional Relations&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>Acknowledgements&nbsp;&nbsp;</li><li>References Cited&nbsp;</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-12-14","noUsgsAuthors":false,"publicationDate":"2021-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Stone, Paul 0000-0002-1439-0156 pastone@usgs.gov","orcid":"https://orcid.org/0000-0002-1439-0156","contributorId":273,"corporation":false,"usgs":true,"family":"Stone","given":"Paul","email":"pastone@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":828413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Howard J.","contributorId":89582,"corporation":false,"usgs":true,"family":"Brown","given":"Howard J.","affiliations":[],"preferred":false,"id":828414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cecil, M. Robinson 0000-0003-1948-1919","orcid":"https://orcid.org/0000-0003-1948-1919","contributorId":216566,"corporation":false,"usgs":false,"family":"Cecil","given":"M.","email":"","middleInitial":"Robinson","affiliations":[{"id":39477,"text":"California State University Northridge","active":true,"usgs":false}],"preferred":true,"id":828415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleck, Robert J. 0000-0002-3149-8249 fleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3149-8249","contributorId":1048,"corporation":false,"usgs":true,"family":"Fleck","given":"Robert","email":"fleck@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":828416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":828417,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fitzpatrick, John A. 0000-0001-6738-7180 jfitzpat@usgs.gov","orcid":"https://orcid.org/0000-0001-6738-7180","contributorId":3719,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"John","email":"jfitzpat@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":828418,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226828,"text":"pp1867C - 2021 - Crater growth and lava-lake dynamics revealed through multitemporal terrestrial lidar scanning at Kīlauea Volcano, Hawaiʻi","interactions":[{"subject":{"id":70226828,"text":"pp1867C - 2021 - Crater growth and lava-lake dynamics revealed through multitemporal terrestrial lidar scanning at Kīlauea Volcano, Hawaiʻi","indexId":"pp1867C","publicationYear":"2021","noYear":false,"chapter":"C","displayTitle":"Crater Growth and Lava-Lake Dynamics Revealed Through Multitemporal Terrestrial Lidar Scanning at Kīlauea Volcano, Hawaiʻi","title":"Crater growth and lava-lake dynamics revealed through multitemporal terrestrial lidar scanning at Kīlauea Volcano, Hawaiʻi"},"predicate":"IS_PART_OF","object":{"id":70217129,"text":"pp1867 - 2021 - The 2008–2018 summit lava lake at Kīlauea Volcano, Hawai‘i","indexId":"pp1867","publicationYear":"2021","noYear":false,"title":"The 2008–2018 summit lava lake at Kīlauea Volcano, Hawai‘i"},"id":1}],"isPartOf":{"id":70217129,"text":"pp1867 - 2021 - The 2008–2018 summit lava lake at Kīlauea Volcano, Hawai‘i","indexId":"pp1867","publicationYear":"2021","noYear":false,"title":"The 2008–2018 summit lava lake at Kīlauea Volcano, Hawai‘i"},"lastModifiedDate":"2024-06-26T15:52:46.463119","indexId":"pp1867C","displayToPublicDate":"2021-12-14T10:04:56","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1867","chapter":"C","displayTitle":"Crater Growth and Lava-Lake Dynamics Revealed Through Multitemporal Terrestrial Lidar Scanning at Kīlauea Volcano, Hawaiʻi","title":"Crater growth and lava-lake dynamics revealed through multitemporal terrestrial lidar scanning at Kīlauea Volcano, Hawaiʻi","docAbstract":"<p>Lava lake surfaces display the tops of active magma columns and respond to eruption variables such as magmatic pressure, convection, degassing, and cooling, as well as interactions with the craters that contain them. However, they are challenging to study owing to the numerous hazards that accompany these eruptions, and they are typically difficult to observe because the emitted gas plumes obscure the lava lake surfaces. The 2008–2018 Overlook crater and lava lake at Kīlauea Volcano, Hawaiʻi, provided a remarkable opportunity to study several high-resolution data streams of eruption variables that impacted the lava lake. To investigate how the crater and associated lava lake responded to changes in these eruption variables, we acquired terrestrial light detection and ranging (lidar) surveys of the Overlook crater and lava lake surface from February 2012 through December 2013, supplemented with several earlier terrestrial and airborne lidar datasets, to quantitatively track changes in the shape of the lava lake surface and the crater walls. Lidar captures high-resolution data even when the lake is completely obscured by thick gas plumes. We used a novel “unrolling technique” to map volumetric changes in crater shape, because standard elevation differencing fails to capture all topographic changes on the nearly vertical, and sometimes overhanging, crater walls. We measured crater perimeter growth rates of approximately 52 meters per year from 2009 to 2013, with the greatest growth occurring along a line linking areas of persistent upwelling and downwelling. We suggest that the development of an oblong crater with a perimeter that grows linearly is best explained by a model where degradation is favored at the sites of persistent upwelling and downwelling and where growth is controlled by a lithology that varies little with respect to rock strength. We also found that most of the Overlook crater growth occurred during a relatively small number of significant rockfall events (~16) over this period. Additional lidar datasets revealed that the lava lake surface has a measurable slope from the areas of persistent upwelling to downwelling, although rockfalls from the crater walls temporarily changed the direction of crustal plate movement along with the magnitude and direction of the lava lake surface slope. Our study demonstrates that lidar is an effective tool for tracking the topography of an active volcanic crater when heavy outgassing renders other tools, such as structure from motion, ineffective.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1867C","usgsCitation":"LeWinter, A.L., Anderson, S.W., Finnegan, D.C., Patrick, M.R., and Orr, T.R., 2021, Crater growth and lava-lake dynamics revealed through multitemporal terrestrial lidar scanning at Kīlauea Volcano, Hawaiʻi, chap. C <em>of</em> Patrick, M., Orr, T., Swanson, D., and Houghton, B., eds., The 2008–2018 summit lava lake at Kīlauea Volcano, Hawaiʻi: U.S. Geological Survey Professional Paper 1867, 26 p., https://doi.org/10.3133/pp1867C.","productDescription":"viii, 26 p.","numberOfPages":"26","onlineOnly":"N","ipdsId":"IP-121567","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":392860,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1867/c/covrthb.jpg"},{"id":392861,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1867/c/pp1867c.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.3192138671875,\n              19.37593175537523\n            ],\n            [\n              -155.21896362304685,\n              19.37593175537523\n            ],\n            [\n              -155.21896362304685,\n              19.460118162137714\n            ],\n            [\n              -155.3192138671875,\n              19.460118162137714\n            ],\n            [\n              -155.3192138671875,\n              19.37593175537523\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:askHVO@usgs.gov\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"mailto:askHVO@usgs.gov\">Contact HVO</a><br><a href=\"https://www.usgs.gov/observatories/hawaiian-volcano-observatory\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/observatories/hawaiian-volcano-observatory\">Hawaiian Volcano Observatory</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>1266 Kamehameha Avenue<br>Suite A-8<br>Hilo, HI 96720</p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Background&nbsp;&nbsp;</li><li>Methodology&nbsp;&nbsp;</li><li>Results&nbsp;&nbsp;</li><li>Discussion&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>References&nbsp;</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-12-14","noUsgsAuthors":false,"publicationDate":"2021-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"LeWinter, Adam L.","contributorId":241892,"corporation":false,"usgs":false,"family":"LeWinter","given":"Adam","email":"","middleInitial":"L.","affiliations":[{"id":48447,"text":"U.S. Army Corps of Engineers Cold Regions Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":828408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Steve W.","contributorId":192765,"corporation":false,"usgs":false,"family":"Anderson","given":"Steve","email":"","middleInitial":"W.","affiliations":[],"preferred":true,"id":828409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finnegan, David C.","contributorId":192073,"corporation":false,"usgs":false,"family":"Finnegan","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":true,"id":828410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":828411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orr, Tim R. 0000-0003-1157-7588","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":214065,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":828412,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70228322,"text":"70228322 - 2021 - Digital Twin Earth - Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators","interactions":[],"lastModifiedDate":"2022-02-08T16:03:08.143881","indexId":"70228322","displayToPublicDate":"2021-12-13T10:00:10","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Digital Twin Earth - Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators","docAbstract":"Developing fast and accurate surrogates for physics-based coastal and ocean mod- els is an urgent need due to the coastal flood risk under accelerating sea level rise, and the computational expense of deterministic numerical models. For this purpose, we develop the first digital twin of Earth coastlines with new physics-informed machine learning techniques extending the state-of-art Neural Operator. As a proof-of-concept study, we built Fourier Neural Operator (FNO) surrogates on the simulations of an industry-standard coastal and ocean model – Nucleus for Euro- pean Modelling of the Ocean (NEMO). The resulting FNO surrogate accurately predicts the sea surface height in most regions while achieving upwards of 45x acceleration of NEMO. We delivered an open-source CoastalTwin platform in an end-to-end and modular way, to enable easy extensions to other simulations and ML-based surrogate methods. Our results and deliverable provide a promising approach to massively accelerate coastal dynamics simulators, which can enable scientists to efficiently execute many simulations for decision-making, uncertainty quantification, and other research activities.","conferenceTitle":"Fourth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2021)","conferenceDate":"December 13, 2021","language":"English","usgsCitation":"Jiang, P., Meinert, N., Jordao, H., Weisser, C., Holgate, S., Lavin, A., Lutjens, B., Newman, D., Wainright, H., Walker, C., and Barnard, P.L., 2021, Digital Twin Earth - Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators, Fourth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2021), December 13, 2021, 7 p.","productDescription":"7 p.","ipdsId":"IP-133822","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":395624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395603,"type":{"id":15,"text":"Index Page"},"url":"https://ml4physicalsciences.github.io/2021/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jiang, P.","contributorId":275155,"corporation":false,"usgs":false,"family":"Jiang","given":"P.","email":"","affiliations":[{"id":56728,"text":"Pacific NW National Lab","active":true,"usgs":false}],"preferred":false,"id":833732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meinert, N.","contributorId":275156,"corporation":false,"usgs":false,"family":"Meinert","given":"N.","email":"","affiliations":[{"id":48419,"text":"German Aerospace Center (DLR)","active":true,"usgs":false}],"preferred":false,"id":833733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jordao, H.","contributorId":275157,"corporation":false,"usgs":false,"family":"Jordao","given":"H.","email":"","affiliations":[{"id":56731,"text":"CERENA, Universidade de Lisboa, Portugal","active":true,"usgs":false}],"preferred":false,"id":833734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weisser, C.","contributorId":275158,"corporation":false,"usgs":false,"family":"Weisser","given":"C.","email":"","affiliations":[{"id":47799,"text":"MIT","active":true,"usgs":false}],"preferred":false,"id":833735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holgate, S.","contributorId":275159,"corporation":false,"usgs":false,"family":"Holgate","given":"S.","email":"","affiliations":[{"id":56732,"text":"IBM","active":true,"usgs":false}],"preferred":false,"id":833736,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lavin, A.","contributorId":275160,"corporation":false,"usgs":false,"family":"Lavin","given":"A.","email":"","affiliations":[{"id":56733,"text":"Institute for Simulation Intelligence","active":true,"usgs":false}],"preferred":false,"id":833737,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lutjens, B.","contributorId":275161,"corporation":false,"usgs":false,"family":"Lutjens","given":"B.","email":"","affiliations":[{"id":56734,"text":"MIT, IBM","active":true,"usgs":false}],"preferred":false,"id":833738,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Newman, D.","contributorId":275162,"corporation":false,"usgs":false,"family":"Newman","given":"D.","affiliations":[{"id":47799,"text":"MIT","active":true,"usgs":false}],"preferred":false,"id":833739,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wainright, H.","contributorId":275163,"corporation":false,"usgs":false,"family":"Wainright","given":"H.","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":833740,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walker, C.","contributorId":181836,"corporation":false,"usgs":false,"family":"Walker","given":"C.","affiliations":[],"preferred":false,"id":833741,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":833742,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70252839,"text":"70252839 - 2021 - Advances in the use of lampricides to control sea lampreys in the Laurentian Great Lakes, 2000–2019","interactions":[],"lastModifiedDate":"2024-04-09T12:19:14.241315","indexId":"70252839","displayToPublicDate":"2021-12-13T07:16:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Advances in the use of lampricides to control sea lampreys in the Laurentian Great Lakes, 2000–2019","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif text-s\"><div id=\"ab005\" class=\"abstract author\" lang=\"en\"><div id=\"as005\"><p id=\"sp0005\">The periodic application of chemical lampricides that selectively kill larval sea lampreys (<i>Petromyzon marinus</i><span>) in their nursery habitats remains a primary component of the Great Lakes Fishery Commission’s (GLFC) Sea Lamprey Control Program in the Laurentian Great Lakes. Lampricides include 3-trifluoromethyl-4-nitrophenol (TFM) and niclosamide, the 2-aminoethanol salt of 2′, 5-dichloro-4′-nitrosalicylanilide, which may be used as an additive to TFM during stream treatments, or alone in a granular, bottom-release formulation to target sea lamprey larvae in deepwater environments where dilution would render TFM ineffective. During the early 1990s, the GLFC identified lampricide reduction targets in response to societal concerns with pesticide use, rising lampricide costs, and promising research into alternative controls. By 1999, the GLFC’s control agents, Fisheries and Oceans Canada (DFO) and the&nbsp;U.S.&nbsp;Fish and Wildlife Service (USFWS), had reduced TFM use by 36%. However, without effective alternative methods to compensate for increasing larval and juvenile production, sea lamprey abundance and lake trout (</span><i>Salvelinus namaycush</i><span>) marking rates rose throughout the Great Lakes. Beginning in the early 2000s, the GLFC and its control agents responded to burgeoning sea lamprey populations by implementing measures to advance the use of lampricides, which included: 1) assessing and controlling sea lamprey larvae that survived treatment; 2) enhancing treatment efficacy; 3) developing new technology to effectively treat larval populations that inhabit deepwater environments; 4) increasing operational capacity to treat more tributaries and lentic areas at shorter intervals; and, 5) conducting large-scale and targeted treatment strategies. When comparing lampricide use between the decades of 1990–1999 and 2010–2019, significant increases occurred in the mean number of treatments and amounts of TFM and niclosamide applied annually. Concurrent with these actions, researchers undertook studies to identify factors that erode lampricide treatment efficiency, elucidate physiological mode of action, and investigate lethal and sub-lethal impacts of lampricide exposure on aquatic organisms. By integrating new operational tactics and strategies with advances in&nbsp;science and technology, the GLFC, DFO, and USFWS, with support from the U.S. Geological Survey and the U.S. Army Corps of Engineers, have achieved unprecedented suppression of sea lampreys and reduction in lake trout marking in the Great Lakes. However, emerging challenges potentially threaten the future use of lampricides.</span></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.jglr.2021.08.009","usgsCitation":"Sullivan, W., Burkett, D.P., Boogaard, M.A., Criger, L.A., Freiberger, C., Hubert, T., Leistner, K., Morrison, B.J., Nowicki, S.M., Robertson, S., Rowlinson, A., Scotland, B., and Sullivan, T.B., 2021, Advances in the use of lampricides to control sea lampreys in the Laurentian Great Lakes, 2000–2019: Journal of Great Lakes Research, v. 47, no. 1, p. S216-S237, https://doi.org/10.1016/j.jglr.2021.08.009.","productDescription":"22 p.","startPage":"S216","endPage":"S237","ipdsId":"IP-121937","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":450028,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2021.08.009","text":"Publisher Index Page"},{"id":427618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sullivan, W Paul","contributorId":335466,"corporation":false,"usgs":false,"family":"Sullivan","given":"W Paul","affiliations":[{"id":65453,"text":"Fisheries and Oceans Canada (Retired)","active":true,"usgs":false}],"preferred":false,"id":898405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burkett, Dale P.","contributorId":257530,"corporation":false,"usgs":false,"family":"Burkett","given":"Dale","email":"","middleInitial":"P.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":898406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boogaard, Michael A. 0000-0002-5192-8437 mboogaard@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-8437","contributorId":865,"corporation":false,"usgs":true,"family":"Boogaard","given":"Michael","email":"mboogaard@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":898407,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Criger, Lori A.","contributorId":191036,"corporation":false,"usgs":false,"family":"Criger","given":"Lori","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":898408,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freiberger, Christopher","contributorId":335469,"corporation":false,"usgs":false,"family":"Freiberger","given":"Christopher","email":"","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":898409,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hubert, Terrance 0000-0001-9712-1738","orcid":"https://orcid.org/0000-0001-9712-1738","contributorId":215420,"corporation":false,"usgs":false,"family":"Hubert","given":"Terrance","affiliations":[{"id":39242,"text":"UMESC (retired)","active":true,"usgs":false}],"preferred":false,"id":898410,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leistner, Keith","contributorId":335471,"corporation":false,"usgs":false,"family":"Leistner","given":"Keith","email":"","affiliations":[{"id":80413,"text":"Leistner Aquatic Services","active":true,"usgs":false}],"preferred":false,"id":898411,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morrison, Bruce J.","contributorId":150824,"corporation":false,"usgs":false,"family":"Morrison","given":"Bruce","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":898412,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nowicki, Shawn M","contributorId":335472,"corporation":false,"usgs":false,"family":"Nowicki","given":"Shawn","email":"","middleInitial":"M","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":898413,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Robertson, Shawn","contributorId":335473,"corporation":false,"usgs":false,"family":"Robertson","given":"Shawn","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":898414,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rowlinson, Alan","contributorId":335474,"corporation":false,"usgs":false,"family":"Rowlinson","given":"Alan","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":898415,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Scotland, Barry","contributorId":335475,"corporation":false,"usgs":false,"family":"Scotland","given":"Barry","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":898416,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sullivan, Timothy B","contributorId":335476,"corporation":false,"usgs":false,"family":"Sullivan","given":"Timothy","email":"","middleInitial":"B","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":898417,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70228081,"text":"70228081 - 2021 - Lake sturgeon (Acipenser fulvescens) annual adult survival estimated from acoustic telemetry","interactions":[],"lastModifiedDate":"2022-02-03T13:24:36.087071","indexId":"70228081","displayToPublicDate":"2021-12-13T07:15:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Lake sturgeon (Acipenser fulvescens) annual adult survival estimated from acoustic telemetry","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab005\" class=\"abstract author\" lang=\"en\"><div id=\"as005\"><p id=\"sp0005\"><span>Survival of adult fishes is critical to the conservation and management of wild populations, particularly for long-lived, slow to reproduce species. Most sturgeon species are of conservation concern, but their long lifespans and large ranges have made estimation of adult survival rates challenging. In this study, acoustic&nbsp;telemetry&nbsp;was used to track 205 lake sturgeon (</span><i>Acipenser fulvescens</i>) tagged in the St. Clair and Detroit rivers of the Laurentian Great Lakes over seven years (2012–2019). The objective of this study was to determine if annual survival was related to sex, size, tagging location (river), or year post-tagging using Cormack-Jolly-Seber (CJS) models. Annual survival was high among all seven years (range of point estimates: 95–99%) and did not differ based on sex, tagging year, size at time of tagging, or tagging location. Lake sturgeon detection probability on acoustic receivers was high each year (range of point estimates: 82–99%) and increased as the number of receivers in the system increased. High survival rates of lake sturgeon were consistent with levels thought required for lake sturgeon to be self-sustaining in the St. Clair – Detroit river system. Our application of acoustic telemetry detections as input to CJS models demonstrated the usefulness of this approach and should be considered for population assessment studies throughout the Great Lakes and beyond.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.08.007","usgsCitation":"Colborne, S.F., Hayden, T., Holbrook, C., Krueger, C.C., and Hondorp, D.W., 2021, Lake sturgeon (Acipenser fulvescens) annual adult survival estimated from acoustic telemetry: Journal of Great Lakes Research, v. 47, no. 6, p. 1814-1823, https://doi.org/10.1016/j.jglr.2021.08.007.","productDescription":"10 p.","startPage":"1814","endPage":"1823","ipdsId":"IP-130702","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":395337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan","otherGeospatial":"St. Clair River, Lake St. Clair, Detroit River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.616943359375,\n              41.94314874732696\n            ],\n            [\n              -81.968994140625,\n              41.94314874732696\n            ],\n            [\n              -81.968994140625,\n              43.15710884095329\n            ],\n            [\n              -83.616943359375,\n              43.15710884095329\n            ],\n            [\n              -83.616943359375,\n              41.94314874732696\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"47","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Colborne, Scott F. 0000-0002-0143-8456","orcid":"https://orcid.org/0000-0002-0143-8456","contributorId":274488,"corporation":false,"usgs":false,"family":"Colborne","given":"Scott","email":"","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayden, Todd A. 0000-0002-0451-0425","orcid":"https://orcid.org/0000-0002-0451-0425","contributorId":274490,"corporation":false,"usgs":false,"family":"Hayden","given":"Todd A.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":833060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krueger, Charles C. 0000-0002-6735-5012","orcid":"https://orcid.org/0000-0002-6735-5012","contributorId":274493,"corporation":false,"usgs":false,"family":"Krueger","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hondorp, Darryl W. 0000-0002-5182-1963 dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":833042,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70250492,"text":"70250492 - 2021 - Guiding the Arctic Rivers Project Climate Model Development: Results from the Climate Information Survey","interactions":[],"lastModifiedDate":"2023-12-13T12:55:02.913582","indexId":"70250492","displayToPublicDate":"2021-12-13T06:52:44","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Guiding the Arctic Rivers Project Climate Model Development: Results from the Climate Information Survey","docAbstract":"<p>No abstract available.&nbsp;</p>","language":"English","publisher":"University of Colorado, Boulder","collaboration":"University of Colorado, Boulder; Institute for Tribal Environmental Professionals; National Center for Atmospheric Research","usgsCitation":"Herman-Mercer, N.M., 2021, Guiding the Arctic Rivers Project Climate Model Development: Results from the Climate Information Survey, 27 p.","productDescription":"27 p.","ipdsId":"IP-134119","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":423511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423505,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.colorado.edu/research/arctic-rivers/sites/default/files/attached-files/arp_modelsurveyresults_report_final.pdf"}],"country":"Canada, United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -134.5522950063096,\n              59.87028426766375\n            ],\n            [\n              -133.24373664299094,\n              61.28424546566808\n            ],\n            [\n              -134.02887166098213,\n              63.05529254448754\n            ],\n            [\n              -136.77684422395126,\n              65.05797812818923\n            ],\n            [\n              -140.17909596857976,\n              66.66285098504187\n            ],\n            [\n              -140.57166347757536,\n              69.21575646485616\n            ],\n            [\n              -142.5345010225534,\n              70.03568521513193\n            ],\n            [\n              -154.573237965085,\n              71.4172689598237\n            ],\n            [\n              -160.59260643635076,\n              70.8674732710819\n            ],\n            [\n              -166.35026323495282,\n              68.7464270445748\n            ],\n            [\n              -166.08855156228913,\n              67.72775212396189\n            ],\n            [\n              -164.91084903530233,\n              67.1758201951771\n            ],\n            [\n              -166.8736865802803,\n              66.34986352746296\n            ],\n            [\n              -167.65882159827146,\n              65.44146322228974\n            ],\n            [\n              -165.56512821696163,\n              63.7581904273662\n            ],\n            [\n              -165.95769572595722,\n              62.15218786087863\n            ],\n            [\n              -166.6119749076166,\n              61.221310865102566\n            ],\n            [\n              -164.91084903530233,\n              59.87028426766375\n            ],\n            [\n              -161.6394531270057,\n              58.18719425432104\n            ],\n            [\n              -158.6297688913728,\n              57.63105594029915\n            ],\n            [\n              -155.88179632840357,\n              57.91020117337476\n            ],\n            [\n              -151.43269789312018,\n              58.39353282771856\n            ],\n            [\n              -146.7218877851731,\n              59.87028426766375\n            ],\n            [\n              -143.84305938587198,\n              60.00139362894262\n            ],\n            [\n              -140.83337515023914,\n              59.73865592328997\n            ],\n            [\n              -138.4779700962655,\n              59.60650723894122\n            ],\n            [\n              -137.16941173294686,\n              59.27385018786782\n            ],\n            [\n              -134.5522950063096,\n              59.87028426766375\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Herman-Mercer, Nicole M. 0000-0001-5933-4978 nhmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-5933-4978","contributorId":3927,"corporation":false,"usgs":true,"family":"Herman-Mercer","given":"Nicole","email":"nhmercer@usgs.gov","middleInitial":"M.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":890140,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70226844,"text":"70226844 - 2021 - Life-history attributes of Arctic-breeding birds drive uneven responses to environmental variability across different phases of the reproductive cycle","interactions":[],"lastModifiedDate":"2022-01-06T17:45:08.622262","indexId":"70226844","displayToPublicDate":"2021-12-13T06:45:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Life-history attributes of Arctic-breeding birds drive uneven responses to environmental variability across different phases of the reproductive cycle","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Animals exhibit varied life-history traits that reflect adaptive responses to their environments. For Arctic-breeding birds, traits related to diet, egg nutrient allocation, clutch size, and chick growth are predicted to be under increasing selection pressure due to rapid climate change and increasing environmental variability across high-latitude regions. We compared four migratory birds (black brant [<i>Branta bernicla nigricans</i>], lesser snow geese [<i>Chen caerulescens caerulescens</i>], semipalmated sandpipers [<i>Calidris pusilla</i>], and Lapland longspurs [<i>Calcarius lapponicus</i>]) with varied life histories at an Arctic site in Alaska, USA, to understand how life-history traits help moderate environmental variability across different phases of the reproductive cycle. We monitored aspects of reproductive performance related to the timing of breeding, reproductive investment, and chick growth from 2011 to 2018. In response to early snowmelt and warm temperatures, semipalmated sandpipers advanced their site arrival and bred in higher numbers, while brant and snow geese increased clutch sizes; all four species advanced their nest initiation dates. During chick rearing, longspur nestlings were relatively resilient to environmental variation, whereas warmer temperatures increased the growth rates of sandpiper chicks but reduced growth rates of snow goose goslings. These responses generally aligned with traits along the capital-income spectrum of nutrient acquisition and altricial–precocial modes of chick growth. Under a warming climate, the ability to mobilize endogenous reserves likely provides geese with relative flexibility to adjust the timing of breeding and the size of clutches. Higher temperatures, however, may negatively affect the quality of herbaceous foods and slow gosling growth. Species may possess traits that are beneficial during one phase of the reproductive cycle and others that may be detrimental at another phase, uneven responses that may be amplified with future climate warming. These results underscore the need to consider multiple phases of the reproductive cycle when assessing the effects of environmental variability on Arctic-breeding birds.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8448","usgsCitation":"Ruthrauff, D.R., Patil, V.P., Hupp, J.W., and Ward, D.H., 2021, Life-history attributes of Arctic-breeding birds drive uneven responses to environmental variability across different phases of the reproductive cycle: Ecology and Evolution, v. 11, no. 24, p. 18514-18530, https://doi.org/10.1002/ece3.8448.","productDescription":"17 p.","startPage":"18514","endPage":"18530","ipdsId":"IP-129731","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":450031,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.8448","text":"Publisher Index Page"},{"id":436095,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZH3JNQ","text":"USGS data release","linkHelpText":"Juvenile Shorebird Morphological Data Collected in Alaska and Canada"},{"id":436094,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UE2Q73","text":"USGS data release","linkHelpText":"Environmental Data from the Colville River Delta, Alaska"},{"id":436093,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AMSIEJ","text":"USGS data release","linkHelpText":"Arthropod Abundance Data from the Colville River Delta, Alaska"},{"id":436092,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CDID03","text":"USGS data release","linkHelpText":"Avian Demographic Data from the Colville River Delta, Alaska"},{"id":436091,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BJBRTO","text":"USGS data release","linkHelpText":"Information from Bird Nests Monitored on the Colville River Delta, Alaska, 2011-2018"},{"id":392942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Colville River Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -150.85739135742188,\n              70.37047384596998\n            ],\n            [\n              -150.64727783203125,\n              70.37047384596998\n            ],\n            [\n              -150.64727783203125,\n              70.46\n            ],\n            [\n              -150.85739135742188,\n              70.46\n            ],\n            [\n              -150.85739135742188,\n              70.37047384596998\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"24","noUsgsAuthors":false,"publicationDate":"2021-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruthrauff, Daniel R. 0000-0003-1355-9156 druthrauff@usgs.gov","orcid":"https://orcid.org/0000-0003-1355-9156","contributorId":4181,"corporation":false,"usgs":true,"family":"Ruthrauff","given":"Daniel","email":"druthrauff@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":828458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patil, Vijay P. 0000-0002-9357-194X vpatil@usgs.gov","orcid":"https://orcid.org/0000-0002-9357-194X","contributorId":203676,"corporation":false,"usgs":true,"family":"Patil","given":"Vijay","email":"vpatil@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":828459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":828460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":828461,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70229704,"text":"70229704 - 2021 - Using social values in the prioritization of research: Quantitative examples and generalizations","interactions":[],"lastModifiedDate":"2022-03-16T15:50:46.326266","indexId":"70229704","displayToPublicDate":"2021-12-09T10:39:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Using social values in the prioritization of research: Quantitative examples and generalizations","docAbstract":"<ol class=\"\"><li>Identifying critical uncertainties about ecological systems can help prioritize research efforts intended to inform management decisions. However, exclusively focusing on the ecological system neglects the objectives of natural resource managers and the associated social values tied to risks and rewards of actions.</li><li>I demonstrate how to prioritize research efforts for a harvested population by applying expected value of perfect information (EVPI) to harvest decisions made with a density-independent matrix population model. Research priorities identified by EVPI diverge from priorities identified by matrix elasticity analyses that ignore social utility.</li><li>Using a density-dependent harvest model, the value of information about the intrinsic productivity of a population is shown to be sensitive to the socially determined penalty for implementing a harvest rate that deviates from the goal because of imperfection in estimation.</li><li><i>Synthesis and applications</i>. The effect of including social values into harvest decision-making depends on the assumed population model, uncertainty in population vital rates, and the particular form of the utility function used to represent risk/reward of harvest. EVPI analyses that include perceived utility of different outcomes can be used by managers seeking to optimize monitoring and research spending. Collaboration between applied ecologists and social scientists that quantitatively measure peoples' values is needed in many structured decision-making processes.</li><li><br></li></ol>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8394","usgsCitation":"Falcy, M.R., 2021, Using social values in the prioritization of research: Quantitative examples and generalizations: Ecology and Evolution, v. 11, no. 24, p. 18000-18010, https://doi.org/10.1002/ece3.8394.","productDescription":"11 p.","startPage":"18000","endPage":"18010","ipdsId":"IP-133813","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":450050,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.8394","text":"Publisher Index Page"},{"id":397163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"24","noUsgsAuthors":false,"publicationDate":"2021-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Falcy, Matthew Richard 0000-0002-3332-2239","orcid":"https://orcid.org/0000-0002-3332-2239","contributorId":288500,"corporation":false,"usgs":true,"family":"Falcy","given":"Matthew","email":"","middleInitial":"Richard","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":838025,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70226873,"text":"70226873 - 2021 - Ten simple rules for creating a scientific web application","interactions":[],"lastModifiedDate":"2021-12-17T14:58:45.469602","indexId":"70226873","displayToPublicDate":"2021-12-09T08:53:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5727,"text":"PLOS Computational Biology","active":true,"publicationSubtype":{"id":10}},"title":"Ten simple rules for creating a scientific web application","docAbstract":"<p><span>The use of scientific web applications (SWApps) across biological and environmental sciences has grown exponentially over the past decade or so. Although quantitative evidence for such increased use in practice is scant, collectively, we have observed that these tools become more commonplace in teaching, outreach, and in science coproduction (e.g., as decision support tools). Despite the increased popularity of SWApps, researchers often receive little or no training in creating such tools. Although rolling out SWApps can be a relatively simple and quick process using modern, popular platforms like R shiny apps or Tableau dashboards, making them useful, usable, and sustainable is not. These 10 simple rules for creating a SWApp provide a foundation upon which researchers with little to no experience in web application design and development can consider, plan, and carry out SWApp projects.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pcbi.1009574","usgsCitation":"Burnett, J.L., Dale, R., Hou, C.Y., Palomo-Munoz, G., Stack-Whitney, K., Aulenbach, S., Bristol, R.S., Valle, D., and Wellman, T., 2021, Ten simple rules for creating a scientific web application: PLOS Computational Biology, v. 17, no. 12, e1009574, 12, https://doi.org/10.1371/journal.pcbi.1009574.","productDescription":"e1009574, 12","ipdsId":"IP-124888","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":450052,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pcbi.1009574","text":"Publisher Index Page"},{"id":393048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Burnett, Jessica Leigh 0000-0002-0896-5099","orcid":"https://orcid.org/0000-0002-0896-5099","contributorId":248195,"corporation":false,"usgs":true,"family":"Burnett","given":"Jessica","email":"","middleInitial":"Leigh","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":828562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dale, Renee 0000-0002-1674-1247","orcid":"https://orcid.org/0000-0002-1674-1247","contributorId":270163,"corporation":false,"usgs":false,"family":"Dale","given":"Renee","email":"","affiliations":[{"id":56103,"text":"Donald Danforth Plant Science Center","active":true,"usgs":false}],"preferred":false,"id":828563,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hou, Chung Yi 0000-0002-8087-1775","orcid":"https://orcid.org/0000-0002-8087-1775","contributorId":270164,"corporation":false,"usgs":false,"family":"Hou","given":"Chung","email":"","middleInitial":"Yi","affiliations":[{"id":37768,"text":"USGS Contractor","active":true,"usgs":false}],"preferred":false,"id":828564,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palomo-Munoz, Gabriela","contributorId":248196,"corporation":false,"usgs":false,"family":"Palomo-Munoz","given":"Gabriela","email":"","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":828605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stack-Whitney, Kaitlin 0000-0002-0815-5037","orcid":"https://orcid.org/0000-0002-0815-5037","contributorId":270165,"corporation":false,"usgs":false,"family":"Stack-Whitney","given":"Kaitlin","email":"","affiliations":[{"id":32390,"text":"Rochester Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":828567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aulenbach, Steven 0000-0002-0172-6538","orcid":"https://orcid.org/0000-0002-0172-6538","contributorId":261331,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Steven","email":"","affiliations":[{"id":207,"text":"Core Research Center","active":true,"usgs":true}],"preferred":true,"id":828565,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bristol, R. Sky 0000-0003-1682-4031 sbristol@usgs.gov","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":3585,"corporation":false,"usgs":true,"family":"Bristol","given":"R.","email":"sbristol@usgs.gov","middleInitial":"Sky","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":828566,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Valle, Denis 0000-0002-9830-8876","orcid":"https://orcid.org/0000-0002-9830-8876","contributorId":270166,"corporation":false,"usgs":false,"family":"Valle","given":"Denis","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":828569,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wellman, Tristan 0000-0003-3049-6214 twellman@usgs.gov","orcid":"https://orcid.org/0000-0003-3049-6214","contributorId":2166,"corporation":false,"usgs":true,"family":"Wellman","given":"Tristan","email":"twellman@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828568,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70226811,"text":"70226811 - 2021 - Evaluating establishment success of non-native fishes introduced to inland aquatic habitats of tropical Pacific islands","interactions":[],"lastModifiedDate":"2023-06-09T13:57:50.600653","indexId":"70226811","displayToPublicDate":"2021-12-09T07:13:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9949,"text":"Journal of Vertebrate Biology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating establishment success of non-native fishes introduced to inland aquatic habitats of tropical Pacific islands","docAbstract":"<div class=\"div0\"><div class=\"row ArticleContentRow\"><p id=\"ID0EF\" class=\"first\">An information-theoretic approach was used to evaluate non-native freshwater fish species introduced to insular habitats of Hawaii and Guam comparing successful establishments<span>&nbsp;</span><i>vs.</i><span>&nbsp;</span>failures. Since the late 1800s, as many as 81 non-native freshwater fish species have been recorded as introduced to Hawaii and Guam (combined) and 50 (62%) of these are documented as having one or more established populations. We examined eleven independent variables to investigate establishment success by creating 21<span>&nbsp;</span><i>a priori</i><span>&nbsp;</span>logistic regression models ranked using Akaike's Information Criterion adjusted for small sample size. An additional eight post-hoc models were included that comprised the best<span>&nbsp;</span><i>a priori</i><span>&nbsp;</span>model and various combinations of individual variables. The best overall model of establishment probability included effects of taxonomic affinity (family membership), prior establishment success on other tropical islands, and hypoxia tolerance. Establishment success in Hawaii and Guam was highest for those species established on many other islands, and according to our best model air-breathing fishes were more likely to become established. Six fish families, each with from three to 18 species introduced to Pacific islands, were highly successful at establishment: Cichlidae (16 established of 18 species introduced), Poeciliidae (seven of eight), Cyprinidae (four of seven), Centrarchidae (four of four), Clariidae (three of three), and Loricariidae (three of four). Those that successfully established include both small and moderately large-bodied taxa, while representing a diverse array of other morphological and life-history traits. Pathways and motives associated with fish introductions in the Pacific have been linked to desires to develop aquaculture, enhance wild stocks of food, sport, and bait fishes, for use as biological control agents, or are linked to the ornamental fish trade. We found that many established species were introduced via multiple pathways (up to eight) and our analyses suggest that the combination of prior establishment success on other tropical islands and presence of non-native fishes in multiple pathways was indicative of high propagule pressure. Our study results and conclusions on Pacific tropical island introductions are in general agreement with previous studies on non-native freshwater fishes in other regions of the world and similar to observations in continental ecosystems and temperate zones.</p></div></div>","language":"English","publisher":"BioOne","doi":"10.25225/jvb.21064","usgsCitation":"Walsh, S., Nico, L., and Miller, M.W., 2021, Evaluating establishment success of non-native fishes introduced to inland aquatic habitats of tropical Pacific islands: Journal of Vertebrate Biology, v. 70, no. 4, 21064, 23 p.; Data Release, https://doi.org/10.25225/jvb.21064.","productDescription":"21064, 23 p.; Data Release","ipdsId":"IP-117081","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":450056,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.25225/jvb.21064","text":"Publisher Index Page"},{"id":392851,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417874,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NGPB6F"}],"country":"United States","state":"Hawaii","otherGeospatial":"Guam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -160.6201171875,\n              18.562947442888312\n            ],\n            [\n              -153.984375,\n              18.562947442888312\n            ],\n            [\n              -153.984375,\n              22.553147478403194\n            ],\n            [\n              -160.6201171875,\n              22.553147478403194\n            ],\n            [\n              -160.6201171875,\n              18.562947442888312\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              144.437255859375,\n              13.197164523281993\n            ],\n            [\n              145.12939453125,\n              13.197164523281993\n            ],\n            [\n              145.12939453125,\n              13.838079936422462\n            ],\n            [\n              144.437255859375,\n              13.838079936422462\n            ],\n            [\n              144.437255859375,\n              13.197164523281993\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"70","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Stephen 0000-0002-1009-8537","orcid":"https://orcid.org/0000-0002-1009-8537","contributorId":213404,"corporation":false,"usgs":true,"family":"Walsh","given":"Stephen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":828359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nico, Leo 0000-0002-4488-7737","orcid":"https://orcid.org/0000-0002-4488-7737","contributorId":219326,"corporation":false,"usgs":true,"family":"Nico","given":"Leo","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":828360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Mark W. 0000-0003-4211-1393","orcid":"https://orcid.org/0000-0003-4211-1393","contributorId":270066,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":56068,"text":"Integrated Statistics, Woods Hole, MA","active":true,"usgs":false}],"preferred":false,"id":828361,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70227478,"text":"70227478 - 2021 - Spatial network clustering reveals elk population structure and local variation in prevalence of chronic wasting disease","interactions":[],"lastModifiedDate":"2022-01-19T12:58:47.519847","indexId":"70227478","displayToPublicDate":"2021-12-09T06:55:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatial network clustering reveals elk population structure and local variation in prevalence of chronic wasting disease","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Spatial organization plays prominent roles in disease transmission, genetics, and demography of wildlife populations and is therefore an important consideration not only for wildlife management, but also for inference about populations and processes. We used hierarchical agglomerative clustering of a spatial graph network to partition Wind Cave National Park (WICA) into five regions used by 163 female elk (<i>Cervus elaphus</i>) marked with global positioning system collars during 2005–08 and 2011–13. We grouped elk based on differential use of the five regions, developed a priori models for inter-group variation in the occurrence of chronic wasting disease (CWD), and used Akaike's information criterion to compare models and stratify regions. Previous descriptions of elk population structure, which have been based on social contact or overlap of individual ranges, have distinguished spatially disjunct population subsets. Constructing hierarchical partitions of the landscape enabled us to also discern and describe overlapping and nested subsets. During 2016–18, apparent park-wide prevalence of CWD was 0.18 (90% CI = [0.146, 0.182]); however, prevalence within three spatial strata used primarily by different elk ranged from 0.03 ([0.008, 0.074]) to 0.29 ([0.211, 0.375]). In context with published estimates of recruitment, predation, and anthropogenic mortality, such differences in prevalence equate to increasing local abundance of elk in southwestern WICA, stable to declining abundance in the west/northwest, and rapidly declining abundance in the east. Despite the modest size of WICA (11,357 ha), park-wide averages conflate effects of elk distribution and disease, obscuring spatial patterns with profound implications for study and management of elk and CWD. Graph networks have been used widely in ecology to describe such phenomena as social relationships, connectivity of habitat patches, animal movements, and the spread of disease. Extension to partitioning of geographic range is straightforward but entails different considerations. We discuss allocation of sampling effort, construction of an initial partition, specification of a model for graph cohesion, selection of a clustering algorithm, and identification of useful partitions.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3781","usgsCitation":"Sargeant, G., Wild, M.A., Schroeder, G.M., Powers, J.G., and Galloway, N., 2021, Spatial network clustering reveals elk population structure and local variation in prevalence of chronic wasting disease: Ecosphere, v. 12, no. 12, e03781, 16 p., https://doi.org/10.1002/ecs2.3781.","productDescription":"e03781, 16 p.","ipdsId":"IP-111896","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":488645,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3781","text":"Publisher Index Page"},{"id":436100,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VPV6FO","text":"USGS data release","linkHelpText":"Supporting data: Spatial network clustering reveals elk population structure and local variation in prevalence of chronic wasting disease at Wind Cave National Park, 2005--18"},{"id":394503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Wind Cave National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.56399536132812,\n              43.481822852999905\n            ],\n            [\n              -103.34152221679688,\n              43.481822852999905\n            ],\n            [\n              -103.34152221679688,\n              43.64005063334696\n            ],\n            [\n              -103.56399536132812,\n              43.64005063334696\n            ],\n            [\n              -103.56399536132812,\n              43.481822852999905\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Sargeant, Glen A. 0000-0003-3845-8503","orcid":"https://orcid.org/0000-0003-3845-8503","contributorId":219538,"corporation":false,"usgs":true,"family":"Sargeant","given":"Glen A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":831122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wild, Margaret A.","contributorId":225083,"corporation":false,"usgs":false,"family":"Wild","given":"Margaret","email":"","middleInitial":"A.","affiliations":[],"preferred":true,"id":831123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schroeder, Gregory M.","contributorId":271190,"corporation":false,"usgs":false,"family":"Schroeder","given":"Gregory","email":"","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":831124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powers, Jenny G.","contributorId":10710,"corporation":false,"usgs":true,"family":"Powers","given":"Jenny","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":831125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galloway, Nathan L.","contributorId":271191,"corporation":false,"usgs":false,"family":"Galloway","given":"Nathan L.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":831126,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226782,"text":"70226782 - 2021 - Subsurface swimming and stationary diving are metabolically cheap in adult Pacific walruses (Odobenus rosmarus divergens)","interactions":[],"lastModifiedDate":"2021-12-13T12:49:29.699464","indexId":"70226782","displayToPublicDate":"2021-12-09T06:48:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2275,"text":"Journal of Experimental Biology","active":true,"publicationSubtype":{"id":10}},"title":"Subsurface swimming and stationary diving are metabolically cheap in adult Pacific walruses (Odobenus rosmarus divergens)","docAbstract":"<div class=\"article-section-wrapper js-article-section js-content-section  \"><p>Walruses rely on sea-ice to efficiently forage and rest between diving bouts while maintaining proximity to prime foraging habitat. Recent declines in summer sea ice have resulted in walruses hauling out on land where they have to travel farther to access productive benthic habitat while potentially increasing energetic costs. Despite the need to better understand the impact of sea ice loss on energy expenditure, knowledge about metabolic demands of specific behaviours in walruses is scarce. In the present study, 3 adult female Pacific walruses (<i>Odobenus rosmarus divergens</i>) housed in professional care participated in flow-through respirometry trials to measure metabolic rates while floating inactive at the water surface during a minimum of 5 min, during a 180&nbsp;s stationary dive, and while swimming ∼90 m horizontally underwater. Metabolic rates during stationary dives (3.82±0.56 l O<sub>2</sub> min<sup>−1</sup>) were lower than those measured at the water surface (4.64±1.04 l<i> </i>O<sub>2</sub> min<sup>−1</sup>), which did not differ from rates measured during subsurface swimming (4.91±0.77 l O<sub>2</sub> min<sup>−1</sup>). Thus, neither stationary diving nor subsurface swimming resulted in metabolic rates above those exhibited by walruses at the water surface. These results suggest that walruses minimize their energetic investment during underwater behaviours as reported for other marine mammals. Although environmental factors experienced by free-ranging walruses (e.g. winds or currents) likely affect metabolic rates, our results provide important information for understanding how behavioural changes affect energetic costs and can be used to improve bioenergetics models aimed at predicting the metabolic consequences of climate change on walruses.</p></div>","language":"English","publisher":"The Company of Biologists","doi":"10.1242/jeb.242993","usgsCitation":"Borque-Espinosa, A., Rode, K.D., Ferrero-Fernandex, D., Forte, A., Capaccioni-Azzati, R., and Fahlman, A., 2021, Subsurface swimming and stationary diving are metabolically cheap in adult Pacific walruses (Odobenus rosmarus divergens): Journal of Experimental Biology, v. 224, no. 23, jeb242993, https://doi.org/10.1242/jeb.242993.","productDescription":"jeb242993","ipdsId":"IP-129635","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":450061,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1242/jeb.242993","text":"Publisher Index Page"},{"id":436101,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UQVFSW","text":"USGS data release","linkHelpText":"Metabolic Rates Measured in Three Captive Adult Female Walruses (Odobenus rosmarus divergens) While Resting and Diving"},{"id":392781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"224","issue":"23","noUsgsAuthors":false,"publicationDate":"2021-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Borque-Espinosa, Alicia","contributorId":269982,"corporation":false,"usgs":false,"family":"Borque-Espinosa","given":"Alicia","email":"","affiliations":[{"id":56054,"text":"Universitat de Valencia","active":true,"usgs":false}],"preferred":false,"id":828233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":828234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrero-Fernandex, Diana","contributorId":269983,"corporation":false,"usgs":false,"family":"Ferrero-Fernandex","given":"Diana","email":"","affiliations":[{"id":56055,"text":"Avanqua Oceanografic","active":true,"usgs":false}],"preferred":false,"id":828235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forte, Anabel","contributorId":269984,"corporation":false,"usgs":false,"family":"Forte","given":"Anabel","email":"","affiliations":[{"id":56054,"text":"Universitat de Valencia","active":true,"usgs":false}],"preferred":false,"id":828236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Capaccioni-Azzati, Romana","contributorId":269985,"corporation":false,"usgs":false,"family":"Capaccioni-Azzati","given":"Romana","email":"","affiliations":[{"id":56054,"text":"Universitat de Valencia","active":true,"usgs":false}],"preferred":false,"id":828237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fahlman, Andreas","contributorId":269986,"corporation":false,"usgs":false,"family":"Fahlman","given":"Andreas","email":"","affiliations":[{"id":56058,"text":"Fundacion Oceanografic de la Comunitat Valenciana","active":true,"usgs":false}],"preferred":false,"id":828238,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226693,"text":"ofr20211109 - 2021 - Occurrence and distribution of PFAS in sampled source water of public drinking-water supplies in the surficial aquifer in Delaware, 2018; PFAS and groundwater age-dating results","interactions":[],"lastModifiedDate":"2022-04-14T16:00:56.281413","indexId":"ofr20211109","displayToPublicDate":"2021-12-08T14:10:00","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":"2021-1109","displayTitle":"Occurrence and Distribution of PFAS in Sampled Source Water of Public Drinking-Water Supplies in the Surficial Aquifer in Delaware, 2018; PFAS and Groundwater Age-Dating Results","title":"Occurrence and distribution of PFAS in sampled source water of public drinking-water supplies in the surficial aquifer in Delaware, 2018; PFAS and groundwater age-dating results","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Delaware Department of Natural Resources and Environmental Control and the Delaware Geological Survey, conducted a groundwater-quality investigation to (1) describe the occurrence and distribution of PFAS, and (2) document any changes in groundwater quality in the Columbia aquifer public water-supply wells in the Delaware Coastal Plain between 2000 and 2008 and between 2008 and 2018. Thirty public water-supply wells located throughout the Columbia aquifer of the Delaware Coastal Plain were sampled from August through November 2018. Groundwater collected from the wells was analyzed for the occurrence and distribution of 18 per- and polyfluorinated alkyl substances (PFAS) as well as groundwater age. Descriptive statistical analyses were performed to assess PFAS analytical results within the well network and the combined perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) concentrations were compared to the U.S. Environmental Protection Agency’s (EPA) health advisory level (HAL) for informational purposes only and not for evidence of compliance or noncompliance with Federal regulations. The EPA’s HAL is a health-based reference level for public drinking water as supplied to customers and is not applied to source (raw) water. Groundwater-age data were compared for sites sampled in 2000, 2008, and 2018 to document any changes.</p><p>All samples were analyzed for 18 PFAS using EPA Method 537 (modified). Forty-four percent of the analyzed PFAS were detected in the study well network. Sixteen of the sampled wells have one or more PFAS detections, and as many as eight different PFAS were found in a single sample. Wells with a higher number of PFAS detected (five or more) were in New Castle and Sussex Counties. The PFAS most frequently detected were PFOA, with 47 percent detection; perfluorohexanoic acid (PFHxA), with 33 percent detection; and PFOS and perfluorohexane sulfonate (PFHxS), with 27 percent detection each. PFAS concentrations were below 1,000 parts per trillion (ppt). Two wells exceeded the EPA’s lifetime-drinking water health advisory level of 70 ppt for combined concentrations of PFOA and PFOS.</p><p>The average age of groundwater entering the screens of the supply wells sampled in 2018 ranged from 8.2 to 45.8 years, with a median groundwater age of 25.7 years. Groundwater age was positively correlated with well depth and negatively correlated with dissolved oxygen. Groundwater age and PFAS concentrations were negatively correlated in the Columbia aquifer. Data from the 23 resampled wells indicate a significant positive difference in the average modeled groundwater-sample-age results. The average groundwater age from samples collected in 2018 was generally 5 years older than the average groundwater age from samples collected in 2008. The same pattern was found during cycle two (2008) of this study, where the 2008 groundwater age was on average 7 years older than the samples collected in 2000. The distribution of groundwater sample ages among the 17 trend wells and during the three study cycles (2000, 2008, and 2018) indicates that sample-age medians were statistically different from zero; well-water sample-age data show a slight increase in groundwater sample age.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211109","collaboration":"Prepared in cooperation with the Delaware Geological Survey and Delaware Department of Natural Resources and Environmental Control","usgsCitation":"Reyes, B., 2021, Occurrence and distribution of PFAS in sampled source water of public drinking-water supplies in the surficial aquifer in Delaware, 2018; PFAS and groundwater age-dating results: U.S. Geological Survey Open-File Report 2021–1109, 27 p., https://doi.org/10.3133/ofr20211109.","productDescription":"Report: vii, 27 p.; Data Release; 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in support of the occurrence and distribution of per- and polyfluoroalkyl substances in sampled source water of public drinking-water supplies in the surficial aquifer in Delaware, 2018:"},{"id":392488,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1109/ofr20211109.pdf","text":"Report","size":"2.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1109"},{"id":392487,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1109/coverthb.jpg"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"mailto:dc_md@usgs.gov\" data-mce-href=\"mailto:dc_md@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/md-de-dc-water\" data-mce-href=\"https://www.usgs.gov/centers/md-de-dc-water\">Maryland-Delaware-D.C. Water Science Center</a><br>U.S. Geological Survey<br>5522 Research Park Drive<br>Catonsville, MD 21228</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Description of Study Area</li><li>PFAS General Description</li><li>Study Methods</li><li>PFAS Results</li><li>Groundwater Age Results</li><li>Summary</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Groundwater-quality data for sampled public water-supply wells in the Columbia aquifer in Delaware, sampled in 2018—Field parameters</li><li>Appendix 2. Groundwater-quality data for sampled public water-supply wells in the Columbia aquifer in Delaware, sampled in 2018—Age dating, dissolved-gas data</li><li>Appendix 3. Groundwater-quality data for sampled public water-supply wells in the Columbia aquifer in Delaware, sampled in 2018—Age dating with sulfur hexafluoride data</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-12-08","noUsgsAuthors":false,"publicationDate":"2021-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Reyes, Betzaida 0000-0002-1398-0824 breyes@usgs.gov","orcid":"https://orcid.org/0000-0002-1398-0824","contributorId":2250,"corporation":false,"usgs":true,"family":"Reyes","given":"Betzaida","email":"breyes@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827716,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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