{"pageNumber":"94","pageRowStart":"2325","pageSize":"25","recordCount":46638,"records":[{"id":70251059,"text":"70251059 - 2023 - Using high-frequency monitoring data to quantify city-wide suspended-sediment load and evaluate TMDL goals","interactions":[],"lastModifiedDate":"2024-01-19T13:23:35.008001","indexId":"70251059","displayToPublicDate":"2023-10-26T07:21:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Using high-frequency monitoring data to quantify city-wide suspended-sediment load and evaluate TMDL goals","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Excess sediment is a common reason water bodies in the USA become listed as impaired resulting in total maximum daily loads (TMDL) that require municipalities to invest millions of dollars annually on management practices aimed at reducing suspended-sediment loads (SSLs), yet monitoring data are rarely used to quantify SSLs and track TMDL progress. A monitoring network was created to quantify the SSL from the City of Roanoke, Virginia, USA (CoR), to the Roanoke River and Tinker Creek and help guide TMDL assessment and implementation. Suspended-sediment concentrations were estimated between 2020 and 2022 from high-frequency turbidity data using surrogate linear-regression models. Sixty-one percent of the total three-year SSL resulted from five large storm events. The average suspended-sediment yield from the CoR (58.1 metric tons/km<sup>2</sup>/year) was similar to other urban watersheds in the Eastern United States; however, the yield was nearly five times larger than the TMDL allocation (12.2 metric tons/km<sup>2</sup>/year). The TMDL allocated load was modeled based on a predominantly forested reference watershed and may not be a practical target for highly impervious watersheds within the CoR. The TMDL model used daily input data which likely does not capture the full range of SSLs during storm events, particularly from flashy urban streams. The average SSL following the five large storm events doubled that of the CoR’s annual allocated load from the TMDL. The results of this study highlight the importance of using high-frequency monitoring data to accurately estimate SSLs and evaluate TMDLs in urban areas.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10661-023-11905-3","usgsCitation":"Miller, S.A., Webber, J.S., Jastram, J.D., and Aguilar, M.F., 2023, Using high-frequency monitoring data to quantify city-wide suspended-sediment load and evaluate TMDL goals: Environmental Monitoring and Assessment, v. 195, 1372, 21 p., https://doi.org/10.1007/s10661-023-11905-3.","productDescription":"1372, 21 p.","ipdsId":"IP-150678","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":441759,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-023-11905-3","text":"Publisher Index Page"},{"id":424620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","city":"Roanoke","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.24874258454878,\n              37.427540986099004\n            ],\n            [\n              -80.24874258454878,\n              37.11280112946203\n            ],\n            [\n              -79.69667959626726,\n              37.11280112946203\n            ],\n            [\n              -79.69667959626726,\n              37.427540986099004\n            ],\n            [\n              -80.24874258454878,\n              37.427540986099004\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"195","noUsgsAuthors":false,"publicationDate":"2023-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Samuel Adam 0000-0003-4225-1601","orcid":"https://orcid.org/0000-0003-4225-1601","contributorId":333495,"corporation":false,"usgs":true,"family":"Miller","given":"Samuel","email":"","middleInitial":"Adam","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webber, James S. 0000-0001-6636-1368","orcid":"https://orcid.org/0000-0001-6636-1368","contributorId":222000,"corporation":false,"usgs":true,"family":"Webber","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jastram, John D. 0000-0002-9416-3358 jdjastra@usgs.gov","orcid":"https://orcid.org/0000-0002-9416-3358","contributorId":3531,"corporation":false,"usgs":true,"family":"Jastram","given":"John","email":"jdjastra@usgs.gov","middleInitial":"D.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aguilar, Marcus F 0000-0002-4431-9596","orcid":"https://orcid.org/0000-0002-4431-9596","contributorId":333497,"corporation":false,"usgs":false,"family":"Aguilar","given":"Marcus","email":"","middleInitial":"F","affiliations":[{"id":79901,"text":"City of Roanoke","active":true,"usgs":false}],"preferred":false,"id":892920,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70255637,"text":"70255637 - 2023 - Airport deicers: An unrecognized source of phosphorus loading in receiving waters","interactions":[],"lastModifiedDate":"2024-06-27T12:23:51.457735","indexId":"70255637","displayToPublicDate":"2023-10-26T07:20:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Airport deicers: An unrecognized source of phosphorus loading in receiving waters","docAbstract":"<div id=\"abstractBox\" class=\"article_abstract-content hlFld-Abstract\"><p class=\"articleBody_abstractText\">Airport ice control products contributed to total phosphorus (TP) loadings in a study of surface water runoff at a medium-sized airport from 2015 to 2021. Eleven airport ice control products had TP concentrations from 1–807 mg L<sup>–1</sup><span>&nbsp;</span>in liquid formulas, while solid pavement deicer had a TP concentration of 805 mg kg<sup>–1</sup>. Product application data, formula TP concentrations, and surface water sampling results were used to estimate TP concentration and loading contributions from these ice control products to receiving streams. Airport ice control products were found to contribute to TP in 84% of the water samples collected at downstream sites during deicing events, and TP concentrations at those sites exceeded aquatic life benchmarks in 70% of samples collected during deicing. A receiving stream 6 km downstream had TP attributed to airport ice control sources in 78% of the samples. TP loadings at an upstream site and the receiving stream site were greatest during the largest runoff events as is typical in urban runoff, but this pattern was not always followed at airport outfall sites due to the influence of TP in deicer products. Products analyzed in this study are used at airports across the United States and abroad, and findings suggest that airport deicers could represent a previously unrecognized source of phosphorus to adjacent waterways.</p></div>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.3c03417","usgsCitation":"Stefaniak, O.M., Corsi, S., Rutter, T., and Failey, G.G., 2023, Airport deicers: An unrecognized source of phosphorus loading in receiving waters: Environmental Science and Technology, v. 57, no. 44, p. 17051-17060, https://doi.org/10.1021/acs.est.3c03417.","productDescription":"10 p.","startPage":"17051","endPage":"17060","ipdsId":"IP-151889","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":441763,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.3c03417","text":"Publisher Index Page"},{"id":430564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Milwaukee","otherGeospatial":"Mitchell International Airport","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -87.96818787835865,\n              42.99613017336026\n            ],\n            [\n              -87.96818787835865,\n              42.88855126553827\n            ],\n            [\n              -87.84579156385327,\n              42.88855126553827\n            ],\n            [\n              -87.84579156385327,\n              42.99613017336026\n            ],\n            [\n              -87.96818787835865,\n              42.99613017336026\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"57","issue":"44","noUsgsAuthors":false,"publicationDate":"2023-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Stefaniak, Owen M. 0000-0001-5394-8338 ostefaniak@usgs.gov","orcid":"https://orcid.org/0000-0001-5394-8338","contributorId":271143,"corporation":false,"usgs":true,"family":"Stefaniak","given":"Owen","email":"ostefaniak@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":905009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":905010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rutter, Troy D. 0000-0001-5130-204X","orcid":"https://orcid.org/0000-0001-5130-204X","contributorId":306215,"corporation":false,"usgs":true,"family":"Rutter","given":"Troy D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":905011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Failey, Greg G.","contributorId":339739,"corporation":false,"usgs":false,"family":"Failey","given":"Greg","email":"","middleInitial":"G.","affiliations":[{"id":81398,"text":"Mitchell International Airport","active":true,"usgs":false}],"preferred":false,"id":905012,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70249723,"text":"sir20235114 - 2023 - Effects of noise from oil and gas development on ungulates and small mammals—A science synthesis to inform National Environmental Policy Act analyses","interactions":[],"lastModifiedDate":"2024-07-22T23:39:24.847096","indexId":"sir20235114","displayToPublicDate":"2023-10-25T13:15:00","publicationYear":"2023","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":"2023-5114","displayTitle":"Effects of Noise from Oil and Gas Development on Ungulates and Small Mammals—<i>A Science Synthesis to Inform National Environmental Policy Act Analyses</i>","title":"Effects of noise from oil and gas development on ungulates and small mammals—A science synthesis to inform National Environmental Policy Act analyses","docAbstract":"<p>The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of noise from oil and gas development on North American ungulates and small mammals, including rodents and leporids. We conducted a structured search of published scientific literature to find information about noise levels produced during oil and gas development, methods for analyzing sound propagation, the effects of noise on ungulates and small mammals, and measures to reduce noise emissions. We organized the sections of this synthesis to align with standard elements of NEPA analyses. We found that oil and gas development is a common source of human-caused noise on public lands and includes noise sources such as heavy construction and drilling machinery, long-term production machinery, truck traffic, and aircraft. Common techniques for predicting potential noise include field data collection using a sound level meter, inference from previously published data, and sound propagation modeling. A substantial body of research shows that human-caused noise can affect wildlife health and behavior, with variation in sensitivity to noise among species. Studies have shown consistent, detectable effects of noise on ungulates, but the amount of literature on ungulates is very small, and additional research could improve our understanding of differences in effects among species, seasons, and individual indicators of fitness. Several species of small mammals are dependent on audible signals for predator detection and communication, and noise has been shown to affect their vigilance and foraging behavior. However, other studies have documented no effects to rodents in noisy areas, and the effects of noise on small mammals may differ by species and study system. Techniques suggested in the literature for reducing noise emissions include sound barriers, seasonal and daily timing restrictions, traffic control measures, and siting infrastructure to take advantage of natural sound barriers. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference for literature about the effects of noise from oil and gas development on ungulates and small mammals.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235114","collaboration":"Prepared in cooperation with the Bureau of Land Management and the U.S. Fish and Wildlife Service","usgsCitation":"Rutherford, T.K., Maxwell, L.M., Kleist, N.J., Teige, E.C., Lehrter, R.J., Gilbert, M.A., Wood, D.J.A., Johnston, A.N., Mengelt, C., Tull, J.C., Haby, T.S., and Carter, S.K., 2023, Effects of noise from oil and gas development on ungulates and small mammals—A science synthesis to inform National Environmental Policy Act analyses (ver. 1.1, July 2024): U.S. Geological Survey Scientific Investigations Report 2023–5114, 44 p., https://doi.org/10.3133/https://doi.org/10.3133/sir20235114.","productDescription":"x, 44 p.","onlineOnly":"Y","ipdsId":"IP-154194","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":431306,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5114/images"},{"id":422101,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5114/sir20235114.pdf","text":"Report","size":"13.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5114"},{"id":422100,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5114/coverthb2.jpg"},{"id":431017,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2023/5114/version_Hist.txt","size":"8.00 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2023-511version history"},{"id":431307,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5114/sir20235114.xml"},{"id":431308,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235114/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5114"}],"edition":"Version 1.0: October 2023; Version 1.1: July 2024","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/fort/\" data-mce-href=\"https://www.usgs.gov/centers/fort/\">Fort Collins Science Center</a><br>U.S. Geological Survey<br>2150 Centre Ave., Bldg. C<br>Fort Collins, CO 80526-8118</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Purpose of This Report</li><li>How to Use This Report</li><li>Science Synthesis—Effects of Noise from Oil and Gas Development on Ungulates and Small Mammals</li><li>Methods for Developing This Science Synthesis</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Results of Studies of the Effects of Noise from Oil and Gas Development on Ungulates, Rodents, and Leporids</li><li>Appendix 2. Ungulate and Small Mammal Hearing Capabilities</li></ul>","publishedDate":"2023-10-25","revisedDate":"2024-07-22","noUsgsAuthors":false,"publicationDate":"2023-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Rutherford, Tait K. 0000-0003-4314-1519","orcid":"https://orcid.org/0000-0003-4314-1519","contributorId":331173,"corporation":false,"usgs":true,"family":"Rutherford","given":"Tait","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":886860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maxwell, Logan M. 0000-0002-8862-2327","orcid":"https://orcid.org/0000-0002-8862-2327","contributorId":331174,"corporation":false,"usgs":true,"family":"Maxwell","given":"Logan","email":"","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":886861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleist, Nathan J. 0000-0002-2468-4318","orcid":"https://orcid.org/0000-0002-2468-4318","contributorId":260598,"corporation":false,"usgs":true,"family":"Kleist","given":"Nathan","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":886862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Teige, Elisabeth C. 0000-0003-1553-792X","orcid":"https://orcid.org/0000-0003-1553-792X","contributorId":331175,"corporation":false,"usgs":true,"family":"Teige","given":"Elisabeth","email":"","middleInitial":"C.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":886863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lehrter, Richard J. 0000-0002-5760-9269","orcid":"https://orcid.org/0000-0002-5760-9269","contributorId":331176,"corporation":false,"usgs":false,"family":"Lehrter","given":"Richard","email":"","middleInitial":"J.","affiliations":[{"id":79144,"text":"BLM National Operations Center (Contractor)","active":true,"usgs":false}],"preferred":false,"id":886864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gilbert, Megan A.","contributorId":331177,"corporation":false,"usgs":false,"family":"Gilbert","given":"Megan","email":"","middleInitial":"A.","affiliations":[{"id":79145,"text":"BLM Headquarters","active":true,"usgs":false}],"preferred":false,"id":886865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, David J.A. 0000-0003-4315-5160","orcid":"https://orcid.org/0000-0003-4315-5160","contributorId":331178,"corporation":false,"usgs":false,"family":"Wood","given":"David","email":"","middleInitial":"J.A.","affiliations":[{"id":79146,"text":"BLM Montana-Dakotas","active":true,"usgs":false}],"preferred":false,"id":886866,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnston, Aaron N. 0000-0003-4659-0504","orcid":"https://orcid.org/0000-0003-4659-0504","contributorId":201768,"corporation":false,"usgs":true,"family":"Johnston","given":"Aaron","email":"","middleInitial":"N.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":886867,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mengelt, Claudia 0000-0001-7869-5170","orcid":"https://orcid.org/0000-0001-7869-5170","contributorId":304087,"corporation":false,"usgs":true,"family":"Mengelt","given":"Claudia","email":"","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":886868,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tull, John C. 0000-0002-0680-008X","orcid":"https://orcid.org/0000-0002-0680-008X","contributorId":201650,"corporation":false,"usgs":false,"family":"Tull","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":886869,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Haby, Travis S. 0000-0003-2204-9967","orcid":"https://orcid.org/0000-0003-2204-9967","contributorId":138831,"corporation":false,"usgs":false,"family":"Haby","given":"Travis","email":"","middleInitial":"S.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":886870,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":886871,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70249996,"text":"70249996 - 2023 - Construction and modification of debris-flow alluvial fans as captured in the geomorphic and sedimentary record: Examples from the western Sangre de Cristo Mountains, south-central Colorado","interactions":[],"lastModifiedDate":"2023-11-12T14:15:31.35482","indexId":"70249996","displayToPublicDate":"2023-10-25T08:03:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5198,"text":"Geological Society of America Special Papers ","active":true,"publicationSubtype":{"id":10}},"title":"Construction and modification of debris-flow alluvial fans as captured in the geomorphic and sedimentary record: Examples from the western Sangre de Cristo Mountains, south-central Colorado","docAbstract":"<p><span>Debris-flow alluvial fans are iconic features of dynamic landscapes and are hypothesized to record tectonic and climatic change. Here, we highlight their complex formation and evolution through an exemplary suite of Quaternary debris-flow alluvial fans emanating from the western range front of the Sangre de Cristo Mountains in south-central Colorado, USA. To evaluate the constructive and modifying processes that produce fan form and the associated sedimentary signatures, we applied a combined geomorphologic and sedimentologic approach using sedimentary facies analysis, soils mapping, high-resolution topographic data, and luminescence geochronology to document timing of fan construction and modification. We explored two subsets of fans in the study area: a southern set sourced from the extensively glaciated drainages of the Blanca Peak massif, and a northern set from the unglaciated drainages south of Great Sand Dunes National Park. Both sets of fans have: (1) active and successively abandoned surfaces that show evolving degradation of primary features through modification by secondary processes, (2) associated facies that display distinct characteristics representative of primary depositional and secondary modifying sedimentary processes, and (3) evidence of primary debris flow with subsequent modification by secondary processes. We found that surface geomorphology and facies assemblages in exposed alluvial-fan deposits represent sediment transport processes on both active and abandoned lobes. The link between fan surface morphologies and the sedimentary facies of their deposits provides a basis for an evolutionary process–based interpretation of debris-flow alluvial-fan geomorphology and provides a better understanding of complexities in buried paleosurfaces (intraformational progressive unconformities), surficial deformation, and landform development as recorded in debris-flow fan deposits in the sedimentary record.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/2023.2561(01)","usgsCitation":"Nicovich, S., Schmitt, J., Gray, H., Klinger, R.E., and Mahan, S.A., 2023, Construction and modification of debris-flow alluvial fans as captured in the geomorphic and sedimentary record: Examples from the western Sangre de Cristo Mountains, south-central Colorado: Geological Society of America Special Papers , v. 561, 48 p., https://doi.org/10.1130/2023.2561(01).","productDescription":"48 p.","ipdsId":"IP-144536","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":441768,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2023.2561(01)","text":"Publisher Index Page"},{"id":435138,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96162BF","text":"USGS data release","linkHelpText":"Data Release for Luminescence: Construction and modification of debris-flow alluvial fans as captured in the geomorphic and sedimentary record: examples from the western Sangre de Cristo Mountains, south-central Colorado"},{"id":422521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Sangre de Cristo Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -107.01583616224015,\n              38.75219123538736\n            ],\n            [\n              -107.01583616224015,\n              37.01816107244015\n            ],\n            [\n              -104.81857053724035,\n              37.01816107244015\n            ],\n            [\n              -104.81857053724035,\n              38.75219123538736\n            ],\n            [\n              -107.01583616224015,\n              38.75219123538736\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"561","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nicovich, Sylvia","contributorId":210054,"corporation":false,"usgs":false,"family":"Nicovich","given":"Sylvia","affiliations":[{"id":38060,"text":"Department of Earth Sciences, Montana State University, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":887922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmitt, James","contributorId":256655,"corporation":false,"usgs":false,"family":"Schmitt","given":"James","email":"","affiliations":[{"id":38060,"text":"Department of Earth Sciences, Montana State University, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":887923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Harrison J. 0000-0002-4555-7473","orcid":"https://orcid.org/0000-0002-4555-7473","contributorId":207019,"corporation":false,"usgs":true,"family":"Gray","given":"Harrison J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":887924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klinger, Ralph E.","contributorId":172929,"corporation":false,"usgs":false,"family":"Klinger","given":"Ralph","email":"","middleInitial":"E.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":887925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":887926,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70249660,"text":"70249660 - 2023 - Movement behavior, habitat selection, and functional responses to habitat availability among four species of wintering waterfowl in California","interactions":[],"lastModifiedDate":"2023-10-24T11:41:49.145479","indexId":"70249660","displayToPublicDate":"2023-10-23T06:37:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Movement behavior, habitat selection, and functional responses to habitat availability among four species of wintering waterfowl in California","docAbstract":"<p>Habitat selection analyses provide a window into the perceived value of habitats by animals and how those perceptions compare with other animals, change across time, or change in relation to availability (termed functional responses). Habitat selection analysis and functional responses can be used to develop strategies to avoid habitat limitations, guide habitat management, and set attainable conservation goals. GPS relocations of marked animals are the principal data used in habitat selection analysis. The accuracy and frequency with which tracking devices collect data are increasing and may result in non-stationary point processes that result from latent behaviors previously unidentifiable in sparse data.</p>","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.1232704","usgsCitation":"Overton, C.T., and Casazza, M.L., 2023, Movement behavior, habitat selection, and functional responses to habitat availability among four species of wintering waterfowl in California: Frontiers in Ecology and Evolution, v. 11, 1232704, 15 p., https://doi.org/10.3389/fevo.2023.1232704.","productDescription":"1232704, 15 p.","ipdsId":"IP-154265","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441800,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1232704","text":"Publisher Index Page"},{"id":435143,"rank":0,"type":{"id":30,"text":"Data 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,{"id":70250147,"text":"70250147 - 2023 - Annual and inter-annual variability in the diffuse attenuation coefficient and turbidity in an urbanized Washington lake from 2013 to 2022 assessed using Landsat-8/9","interactions":[],"lastModifiedDate":"2023-11-22T15:55:03.53343","indexId":"70250147","displayToPublicDate":"2023-10-21T09:47:05","publicationYear":"2023","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":"Annual and inter-annual variability in the diffuse attenuation coefficient and turbidity in an urbanized Washington lake from 2013 to 2022 assessed using Landsat-8/9","docAbstract":"<p><span>Water clarity, defined in this study using measurements of the downwelling diffuse light attenuation coefficient (K</span><sub>d</sub><span>) and turbidity, is an important indicator of lake trophic status and ecosystem health. We used in-situ measurements to evaluate existing semi-analytical models for K</span><sub>d</sub><span>&nbsp;and turbidity, developed a regional turbidity model based on spectral shape, and evaluated the spatial and temporal trends in Lake Washington from 2013 to 2022 using Landsat-8/9 Operational Land Imager (OLI). We found no significant trends from 2013 to 2022 in K</span><sub>d</sub><span>&nbsp;or turbidity when both the annual and full datasets were considered. In addition to the spring peak lasting from April through June, autumn K</span><sub>d</sub><span>&nbsp;peaks were present at all sites, a pattern consistent with seasonal chlorophyll&nbsp;</span><span class=\"html-italic\">a</span><span>&nbsp;and zooplankton concentrations. There existed no autumn peak in the monthly turbidity dataset, and the spring peak occurred two months before the K</span><sub>d</sub><span>&nbsp;peak, nearly mirroring seasonal variability in the Cedar River discharge rates over the same period. The K</span><sub>d</sub><span>&nbsp;and turbidity algorithms were thus each more sensitive to different sources of water clarity variability in Lake Washington.</span></p>","language":"English","publisher":"MPDI","doi":"10.3390/rs15205055","usgsCitation":"Schulien, J.A., Code, T.J., DeGasperi, C.L., Beauchamp, D., Tonus Ellis, A., and Litt, A.H., 2023, Annual and inter-annual variability in the diffuse attenuation coefficient and turbidity in an urbanized Washington lake from 2013 to 2022 assessed using Landsat-8/9: Remote Sensing, v. 15, no. 20, 5055, 19 p., https://doi.org/10.3390/rs15205055.","productDescription":"5055, 19 p.","ipdsId":"IP-158607","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":441806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs15205055","text":"Publisher Index Page"},{"id":422837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.29668187426911,\n              47.76219367672758\n            ],\n            [\n              -122.2936983290256,\n              47.49342533323215\n            ],\n            [\n              -122.1703784589545,\n              47.49342533323215\n            ],\n            [\n              -122.19822488122844,\n              47.75617656843582\n            ],\n            [\n              -122.29668187426911,\n              47.76219367672758\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","issue":"20","noUsgsAuthors":false,"publicationDate":"2023-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Schulien, Jennifer A.","contributorId":331715,"corporation":false,"usgs":false,"family":"Schulien","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":79272,"text":"Schulien Consulting","active":true,"usgs":false}],"preferred":false,"id":888561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Code, Tessa Julianne 0000-0003-1481-020X","orcid":"https://orcid.org/0000-0003-1481-020X","contributorId":331687,"corporation":false,"usgs":true,"family":"Code","given":"Tessa","email":"","middleInitial":"Julianne","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeGasperi, Curtis L.","contributorId":257393,"corporation":false,"usgs":false,"family":"DeGasperi","given":"Curtis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":888563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tonus Ellis, Arielle","contributorId":331716,"corporation":false,"usgs":false,"family":"Tonus Ellis","given":"Arielle","email":"","affiliations":[{"id":36795,"text":"University of Washington, School of Aquatic and Fishery Sciences","active":true,"usgs":false}],"preferred":false,"id":888565,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Litt, Arni H.","contributorId":331717,"corporation":false,"usgs":false,"family":"Litt","given":"Arni","email":"","middleInitial":"H.","affiliations":[{"id":36795,"text":"University of Washington, School of Aquatic and Fishery Sciences","active":true,"usgs":false}],"preferred":false,"id":888566,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250398,"text":"70250398 - 2023 - Conservation genomics of an endangered montane amphibian reveals low population structure, low genomic diversity and selection pressure from disease","interactions":[],"lastModifiedDate":"2023-12-07T12:43:30.698976","indexId":"70250398","displayToPublicDate":"2023-10-21T06:40:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Conservation genomics of an endangered montane amphibian reveals low population structure, low genomic diversity and selection pressure from disease","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Wildlife diseases are a major global threat to biodiversity. Boreal toads (<i>Anaxyrus [Bufo] boreas</i>) are a state-endangered species in the southern Rocky Mountains of Colorado and New Mexico, and a species of concern in Wyoming, largely due to lethal skin infections caused by the amphibian chytrid fungus<span>&nbsp;</span><i>Batrachochytrium dendrobatidis</i><span>&nbsp;</span>(<i>Bd</i>). We performed conservation and landscape genomic analyses using single nucleotide polymorphisms from double-digest, restriction site-associated DNA sequencing in combination with the development of the first boreal toad (and first North American toad) reference genome to investigate population structure, genomic diversity, landscape connectivity and adaptive divergence. Genomic diversity (<i>π</i><span>&nbsp;</span>= 0.00034–0.00040) and effective population sizes (<i>N</i><sub>e</sub><span>&nbsp;</span>= 8.9–38.4) were low, likely due to post-Pleistocene founder effects and<span>&nbsp;</span><i>Bd</i>-related population crashes over the last three decades. Population structure was also low, likely due to formerly high connectivity among a higher density of geographically proximate populations. Boreal toad gene flow was facilitated by low precipitation, cold minimum temperatures, less tree canopy, low heat load and less urbanization. We found &gt;8X more putatively adaptive loci related to<span>&nbsp;</span><i>Bd</i><span>&nbsp;</span>intensity than to all other environmental factors combined, and evidence for genes under selection related to immune response, heart development and regulation and skin function. These data suggest boreal toads in habitats with<span>&nbsp;</span><i>Bd</i><span>&nbsp;</span>have experienced stronger selection pressure from disease than from other, broad-scale environmental variations. These findings can be used by managers to conserve and recover the species through actions including reintroduction and supplementation of populations that have declined due to<span>&nbsp;</span><i>Bd</i>.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/mec.17175","usgsCitation":"Trumbo, D., Hardy, B., Crockett, H., Muths, E., Forester, B.R., Cheek, R., Zimmerman, S.J., Corey-Rivas, S., Bailey, L., and Funk, C., 2023, Conservation genomics of an endangered montane amphibian reveals low population structure, low genomic diversity and selection pressure from disease: Molecular Ecology, v. 32, no. 24, p. 6777-6795, https://doi.org/10.1111/mec.17175.","productDescription":"19 p.","startPage":"6777","endPage":"6795","ipdsId":"IP-149446","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":441816,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/mec.17175","text":"Publisher Index Page"},{"id":423290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.49262128312715,\n              40.99730982801444\n            ],\n            [\n              -109.05219159562684,\n              40.99730982801444\n            ],\n            [\n              -109.05219159562684,\n              38.73779953677936\n            ],\n            [\n              -105.49262128312715,\n              38.73779953677936\n            ],\n            [\n              -105.49262128312715,\n              40.99730982801444\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"32","issue":"24","noUsgsAuthors":false,"publicationDate":"2023-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Trumbo, Daryl","contributorId":197454,"corporation":false,"usgs":false,"family":"Trumbo","given":"Daryl","affiliations":[],"preferred":false,"id":889761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hardy, Bennett","contributorId":303568,"corporation":false,"usgs":false,"family":"Hardy","given":"Bennett","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":889762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crockett, Harry","contributorId":198489,"corporation":false,"usgs":false,"family":"Crockett","given":"Harry","affiliations":[],"preferred":false,"id":889763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245923,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":889764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Forester, Brenna R.","contributorId":261215,"corporation":false,"usgs":false,"family":"Forester","given":"Brenna","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":889765,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheek, Rebecca","contributorId":332238,"corporation":false,"usgs":false,"family":"Cheek","given":"Rebecca","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":889766,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zimmerman, Shawna J 0000-0003-3394-6102 szimmerman@usgs.gov","orcid":"https://orcid.org/0000-0003-3394-6102","contributorId":238076,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Shawna","email":"szimmerman@usgs.gov","middleInitial":"J","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":889767,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Corey-Rivas, Sarah","contributorId":332239,"corporation":false,"usgs":false,"family":"Corey-Rivas","given":"Sarah","email":"","affiliations":[{"id":79426,"text":"New Mexico Highlands University","active":true,"usgs":false}],"preferred":false,"id":889768,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bailey, Larissa L.","contributorId":229353,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":889769,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Funk, Chris","contributorId":302160,"corporation":false,"usgs":false,"family":"Funk","given":"Chris","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":889770,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70253914,"text":"70253914 - 2023 - Opera Dynamic Surface Water extents for Harmonized Landsat Sentinel-2 (DSWX-HLS) validation activities","interactions":[],"lastModifiedDate":"2024-05-03T15:46:15.033278","indexId":"70253914","displayToPublicDate":"2023-10-20T10:39:40","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Opera Dynamic Surface Water extents for Harmonized Landsat Sentinel-2 (DSWX-HLS) validation activities","docAbstract":"<p><span>We present the validation methodology and results of Dynamic Surface Water eXtent from Harmonized Landsat Sentinel-2 (DSWx-HLS). The DSWx-HLS product is the first of the DSWx suite, comprised of products each which map water from Earth Observation optical and SAR satellites. We detail the generation of high-resolution (3 m) validation datasets from a globally-stratified sample of dry, moderate, and wet sites. We provide the precise accounting of the classification metrics used to verify the Observational Products for End-users from Remote Sensing Analysis (OPERA) project requirements. We also report broader classification metrics across the validation datasets considered. OPERA performs validation in the public domain to ensure that the validation activities are transparent and reproducible. The resulting validation datasets and provisional OPERA products are publicly available; the software used for validation is also open-source.</span></p>","conferenceTitle":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","conferenceDate":"July 16-21, 2023","conferenceLocation":"Pasadena, CA","language":"English","publisher":"IEEE","doi":"10.1109/IGARSS52108.2023.10283397","usgsCitation":"Arena, N., Bato, G., Bekaert, D., Bonnema, M., Chan, S., Chapman, B., Jones, J., Handwerger, A., Lewandowski, A., Marshak, C., Sangha, S., and Venkataramani, K., 2023, Opera Dynamic Surface Water extents for Harmonized Landsat Sentinel-2 (DSWX-HLS) validation activities, IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, July 16-21, 2023, p. 2723-2726, https://doi.org/10.1109/IGARSS52108.2023.10283397.","productDescription":"4 p.","startPage":"2723","endPage":"2726","ipdsId":"IP-153954","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":428363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arena, Nicholas","contributorId":336167,"corporation":false,"usgs":false,"family":"Arena","given":"Nicholas","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bato, Grace","contributorId":336168,"corporation":false,"usgs":false,"family":"Bato","given":"Grace","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bekaert, David","contributorId":336169,"corporation":false,"usgs":false,"family":"Bekaert","given":"David","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonnema, Matthew","contributorId":336170,"corporation":false,"usgs":false,"family":"Bonnema","given":"Matthew","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chan, Steven","contributorId":336171,"corporation":false,"usgs":false,"family":"Chan","given":"Steven","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900091,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chapman, Bruce","contributorId":336172,"corporation":false,"usgs":false,"family":"Chapman","given":"Bruce","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900092,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":900093,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Handwerger, Alexander L.","contributorId":336174,"corporation":false,"usgs":false,"family":"Handwerger","given":"Alexander L.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900094,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lewandowski, Alex","contributorId":336176,"corporation":false,"usgs":false,"family":"Lewandowski","given":"Alex","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900095,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Marshak, Charlie","contributorId":336178,"corporation":false,"usgs":false,"family":"Marshak","given":"Charlie","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900096,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sangha, Simran","contributorId":336183,"corporation":false,"usgs":false,"family":"Sangha","given":"Simran","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900097,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Venkataramani, Karthik","contributorId":336185,"corporation":false,"usgs":false,"family":"Venkataramani","given":"Karthik","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":900098,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70256488,"text":"70256488 - 2023 - Change-point models for identifying behavioral transitions in wild animals","interactions":[],"lastModifiedDate":"2024-08-07T15:40:00.947336","indexId":"70256488","displayToPublicDate":"2023-10-20T10:36:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Change-point models for identifying behavioral transitions in wild animals","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Animal behavior can be difficult, time-consuming, and costly to observe in the field directly. Innovative modeling methods, such as hidden Markov models (HMMs), allow researchers to infer unobserved animal behaviors from movement data, and implementations often assume that transitions between states occur multiple times. However, some behavioral shifts of interest, such as parturition, migration initiation, and juvenile dispersal, may only occur once during an observation period, and HMMs may not be the best approach to identify these changes. We present two change-point models for identifying single transitions in movement behavior: a location-based change-point model and a movement metric-based change-point model. We first conducted a simulation study to determine the ability of these models to detect a behavioral transition given different amounts of data and the degree of behavioral shifts. We then applied our models to two ungulate species in central Pennsylvania that were fitted with global positioning system collars and vaginal implant transmitters to test hypotheses related to parturition behavior. We fit these models in a Bayesian framework and directly compared the ability of each model to describe the parturition behavior across species. Our simulation study demonstrated that successful change point estimation using either model was possible given at least 12 h of post-change observations and 15 min fix interval. However, our models received mixed support among deer and elk in Pennsylvania due to behavioral variation between species and among individuals. Our results demonstrate that when the behavior follows the dynamics proposed by the two models, researchers can identify the timing of a behavioral change. Although we refer to detecting parturition events, our results can be applied to any behavior that results in a single change in time.</p></div></div>","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-023-00430-0","usgsCitation":"Gundermann, K., Diefenbach, D.R., Walter, W., Corondi, A., Banfield, J., Wallingford, B., Stainbrook, D., Rosenberry, C., and Buderman, F., 2023, Change-point models for identifying behavioral transitions in wild animals: Movement Ecology, v. 11, 65, 15 p., https://doi.org/10.1186/s40462-023-00430-0.","productDescription":"65, 15 p.","ipdsId":"IP-149981","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441819,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-023-00430-0","text":"Publisher Index Page"},{"id":432342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Gundermann, K.P.","contributorId":340853,"corporation":false,"usgs":false,"family":"Gundermann","given":"K.P.","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":907608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907610,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Corondi, A","contributorId":340854,"corporation":false,"usgs":false,"family":"Corondi","given":"A","email":"","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":907611,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Banfield, J.E.","contributorId":340856,"corporation":false,"usgs":false,"family":"Banfield","given":"J.E.","email":"","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":907612,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wallingford, B.D.","contributorId":340857,"corporation":false,"usgs":false,"family":"Wallingford","given":"B.D.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":907613,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stainbrook, D.P.","contributorId":340859,"corporation":false,"usgs":false,"family":"Stainbrook","given":"D.P.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":907614,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rosenberry, C.S.","contributorId":340861,"corporation":false,"usgs":false,"family":"Rosenberry","given":"C.S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":907615,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Buderman, F.E.","contributorId":340863,"corporation":false,"usgs":false,"family":"Buderman","given":"F.E.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":907616,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70247132,"text":"70247132 - 2023 - Monitoring long-term changes of urban surface temperature using time-series land cover and remote sensing data across 50 major cities in the United States","interactions":[],"lastModifiedDate":"2024-05-28T14:42:03.934403","indexId":"70247132","displayToPublicDate":"2023-10-20T09:35:45","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Monitoring long-term changes of urban surface temperature using time-series land cover and remote sensing data across 50 major cities in the United States","docAbstract":"<p><span>The increase of developed land changes the Earth’s ecosystems and, in doing so, impacts the natural environment and further affects the services it provides to humans. Urban growth and associated land cover transitions alter the thermal and physical properties of the land surface, resulting in surface temperature change in urban areas. In this study, we integrated both land cover and surface temperature information to characterize surface temperature spatiotemporal variations using the recently available time series of Landsat land surface temperature and annual land change products. We analyzed over thirty-year trends of land surface temperature (LST) in urban and surrounding non-urban lands. We found that the transitions of different land cover types to urban affected urban LST trends differently, and further impacted the temporal trend of urban heat island intensity.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"IGARSS 2023 - 2023 IEEE international geoscience and remote sensing symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","conferenceDate":"July 16-21, 2023","conferenceLocation":"Pasadena, CA","language":"English","publisher":"IEEE","doi":"10.1109/IGARSS52108.2023.10282543","usgsCitation":"Xian, G.Z., Shi, H., Mueller, C.W., Hussain, R.A., Sayler, K., and Howard, D., 2023, Monitoring long-term changes of urban surface temperature using time-series land cover and remote sensing data across 50 major cities in the United States, <i>in</i> IGARSS 2023 - 2023 IEEE international geoscience and remote sensing symposium, Pasadena, CA, July 16-21, 2023, p. 321-324, https://doi.org/10.1109/IGARSS52108.2023.10282543.","productDescription":"4 p.","startPage":"321","endPage":"324","ipdsId":"IP-153766","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":429327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"continental United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n               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Center","active":true,"usgs":true}],"preferred":true,"id":879005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Chase William 0000-0002-9948-1304","orcid":"https://orcid.org/0000-0002-9948-1304","contributorId":317297,"corporation":false,"usgs":true,"family":"Mueller","given":"Chase","email":"","middleInitial":"William","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":879006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hussain, Reza A 0000-0002-5445-3027","orcid":"https://orcid.org/0000-0002-5445-3027","contributorId":317298,"corporation":false,"usgs":true,"family":"Hussain","given":"Reza","email":"","middleInitial":"A","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":879007,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sayler, Kristi L. 0000-0003-2514-242X sayler@usgs.gov","orcid":"https://orcid.org/0000-0003-2514-242X","contributorId":2988,"corporation":false,"usgs":true,"family":"Sayler","given":"Kristi","email":"sayler@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":879008,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Howard, Daniel 0000-0002-7563-7538","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":56946,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":879009,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70246672,"text":"70246672 - 2023 - Mapping the Surface Urban Heat Island effect using the Landsat Surface Temperature Product","interactions":[],"lastModifiedDate":"2024-05-28T14:05:25.727146","indexId":"70246672","displayToPublicDate":"2023-10-20T09:04:28","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Mapping the Surface Urban Heat Island effect using the Landsat Surface Temperature Product","docAbstract":"<p><span>Urban development and associated land cover and land use change alter the thermal, hydrological, and physical properties of the land surface. Urban areas usually exhibit relatively warmer air and surface temperatures than surrounding non-urban lands, a phenomenon recognized as Surface Urban Heat Island (SUHI). As urban areas continue to develop and the climate continues to warm, it has become increasingly important to quantify and map the SUHI effect and learn how to mitigate it. To help meet the expanding need of analysis ready data for SUHI based studies, a methodology was developed to evaluate Land Surface Temperature (LST) using the Landsat Collection 1 Provisional Surface Temperature Science Product. The Landsat derived LST products were processed for 50 major cities throughout the Conterminous U.S. The SUHI product package includes per-pixel annual surface temperature, annual intensity, annual hotspot, and hotspot probability bands from 1985 to 2020.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"IGARSS 2023 - 2023 IEEE international geoscience and remote sensing symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","conferenceDate":"July 16-21, 2023","conferenceLocation":"Pasadena, CA","language":"English","publisher":"IEEE","doi":"10.1109/IGARSS52108.2023.10282386","usgsCitation":"Mueller, C., Hussain, R., Xian, G.Z., Shi, H., and Arab, S., 2023, Mapping the Surface Urban Heat Island effect using the Landsat Surface Temperature Product, <i>in</i> IGARSS 2023 - 2023 IEEE international geoscience and remote sensing symposium, Pasadena, CA, July 16-21, 2023, p. 441-444, https://doi.org/10.1109/IGARSS52108.2023.10282386.","productDescription":"4 p.","startPage":"441","endPage":"444","ipdsId":"IP-153990","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":429325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                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xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":877863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shi, Hua 0000-0001-7013-1565","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":302265,"corporation":false,"usgs":false,"family":"Shi","given":"Hua","affiliations":[],"preferred":false,"id":877864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arab, Saeed 0000-0003-1602-8801","orcid":"https://orcid.org/0000-0003-1602-8801","contributorId":299964,"corporation":false,"usgs":false,"family":"Arab","given":"Saeed","email":"","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":877865,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70251165,"text":"70251165 - 2023 - Comparing NISAR (using Sentinel-1), USDA/NASS CDL, and ground truth crop/non-crop areas in an urban agricultural region","interactions":[],"lastModifiedDate":"2024-01-25T13:03:36.65225","indexId":"70251165","displayToPublicDate":"2023-10-20T06:59:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"Comparing NISAR (using Sentinel-1), USDA/NASS CDL, and ground truth crop/non-crop areas in an urban agricultural region","docAbstract":"<div class=\"html-p\">A general limitation in assessing the accuracy of land cover mapping is the availability of ground truth data. At sites where ground truth is not available, potentially inaccurate proxy datasets are used for sub-field-scale resolution investigations at large spatial scales, i.e., in the Contiguous United States. The USDA/NASS Cropland Data Layer (CDL) is a popular agricultural land cover dataset due to its high accuracy (&gt;80%), resolution (30 m), and inclusions of many land cover and crop types. However, because the CDL is derived from satellite imagery and has resulting uncertainties, comparisons to available in situ data are necessary for verifying classification performance. This study compares the cropland mapping accuracies (crop/non-crop) of an optical approach (CDL) and the radar-based crop area (CA) approach used for the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) L- and S-band mission but using Sentinel-1 C-band data. CDL and CA performance are compared to ground truth data that includes 54 agricultural production and research fields located at USDA’s Beltsville Agricultural Research Center (BARC) in Maryland, USA. We also evaluate non-crop mapping accuracy using twenty-six built-up and thirteen forest sites at BARC. The results show that the CDL and CA have a good pixel-wise agreement with one another (87%). However, the CA is notably more accurate compared to ground truth data than the CDL. The 2017–2021 mean accuracies for the CDL and CA, respectively, are 77% and 96% for crop, 100% and 94% for built-up, and 100% and 100% for forest, yielding an overall accuracy of 86% for the CDL and 96% for CA. This difference mainly stems from the CDL under-detecting crop cover at BARC, especially in 2017 and 2018. We also note that annual accuracy levels varied less for the CA (91–98%) than for the CDL (79–93%). This study demonstrates that a computationally inexpensive radar-based cropland mapping approach can also give accurate results over complex landscapes with accuracies similar to or better than optical approaches.</div>","language":"English","publisher":"MDPI","doi":"10.3390/s23208595","usgsCitation":"Kraatz, S., Lamb, B.T., Hively, W.D., Jennewein, J., Gao, F., Cosh, M.H., and Siqueira, P., 2023, Comparing NISAR (using Sentinel-1), USDA/NASS CDL, and ground truth crop/non-crop areas in an urban agricultural region: Sensors, v. 23, no. 20, 8595, 26 p., https://doi.org/10.3390/s23208595.","productDescription":"8595, 26 p.","ipdsId":"IP-154886","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":441826,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s23208595","text":"Publisher Index Page"},{"id":424947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -76.95,\n              39.161296434160306\n            ],\n            [\n              -76.95,\n              38.93946741714126\n            ],\n            [\n              -76.8,\n              38.93946741714126\n            ],\n            [\n              -76.8,\n              39.161296434160306\n            ],\n            [\n              -76.95,\n              39.161296434160306\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"23","issue":"20","noUsgsAuthors":false,"publicationDate":"2023-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraatz, Simon","contributorId":333602,"corporation":false,"usgs":false,"family":"Kraatz","given":"Simon","email":"","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":893319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamb, Brian T. 0000-0001-7957-5488","orcid":"https://orcid.org/0000-0001-7957-5488","contributorId":291893,"corporation":false,"usgs":true,"family":"Lamb","given":"Brian","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":893321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jennewein, Jyoti","contributorId":243442,"corporation":false,"usgs":false,"family":"Jennewein","given":"Jyoti","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":893322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gao, Feng 0000-0002-1865-2846","orcid":"https://orcid.org/0000-0002-1865-2846","contributorId":70671,"corporation":false,"usgs":false,"family":"Gao","given":"Feng","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":893323,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cosh, Michael H.","contributorId":146998,"corporation":false,"usgs":false,"family":"Cosh","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":893324,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Siqueira, Paul","contributorId":333605,"corporation":false,"usgs":false,"family":"Siqueira","given":"Paul","email":"","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":893325,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70254447,"text":"70254447 - 2023 - Restructuring and serving web-accessible streamflow data from the NOAA National Water Model historic simulations","interactions":[],"lastModifiedDate":"2024-05-24T11:53:28.457658","indexId":"70254447","displayToPublicDate":"2023-10-20T06:50:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17783,"text":"Nature, Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Restructuring and serving web-accessible streamflow data from the NOAA National Water Model historic simulations","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>In 2016, the National Oceanic and Atmospheric Administration deployed the first iteration of an operational National Water Model (NWM) to forecast the water cycle in the continental United States. With many versions, an hourly, multi-decadal historic simulation is made available to the public. In all released to date,&nbsp;the&nbsp;files containing simulated&nbsp;streamflow contain a snapshot of model conditions across the entire domain for a single timestep which makes accessing&nbsp; time series a technical and resource-intensive challenge. In the most recent release, extracting a complete streamflow time series for a single location requires managing 367,920 files (~16.2 TB). In this work we describe a&nbsp;reproducible process for restructuring a sequential set of NWM steamflow files for efficient time series access and provide restructured datasets for versions 1.2 (1993–2018), 2.0 (1993–2020), and 2.1 (1979–2022). These datasets have been made accessible via an OPeNDAP enabled THREDDS data server&nbsp;for public use&nbsp;and a brief analysis highlights&nbsp;the latest version of the model should not be assumed best for all locations. Lastly we describe an R package that expedites data retrieval with examples for multiple use-cases.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41597-023-02316-7","usgsCitation":"Johnson, J.M., Blodgett, D.L., Clarke, K., and Pollak, J., 2023, Restructuring and serving web-accessible streamflow data from the NOAA National Water Model historic simulations: Nature, Scientific Data, v. 10, 725, 10 p., https://doi.org/10.1038/s41597-023-02316-7.","productDescription":"725, 10 p.","ipdsId":"IP-119244","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":441831,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-023-02316-7","text":"Publisher Index Page"},{"id":429242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": 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            [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2023-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, J. Michael","contributorId":336915,"corporation":false,"usgs":false,"family":"Johnson","given":"J.","email":"","middleInitial":"Michael","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":901387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":901388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clarke, Keith C.","contributorId":336916,"corporation":false,"usgs":false,"family":"Clarke","given":"Keith C.","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":901389,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pollak, Jon","contributorId":336918,"corporation":false,"usgs":false,"family":"Pollak","given":"Jon","email":"","affiliations":[{"id":80911,"text":"CUAHSI","active":true,"usgs":false}],"preferred":false,"id":901390,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70259657,"text":"70259657 - 2023 - Ecological associations of non-native ungulates on the Hawaiian Island of Lāna‘i","interactions":[],"lastModifiedDate":"2024-10-19T13:24:47.508554","indexId":"70259657","displayToPublicDate":"2023-10-19T08:23:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Ecological associations of non-native ungulates on the Hawaiian Island of Lāna‘i","docAbstract":"<div id=\"abstract\" class=\"element\"><p>Sustained-yield hunting of introduced ungulates in the Hawaiian Islands often conflicts with the conservation of native species, but there is little reliable data to guide effective management. European mouflon sheep (<i>Ovis musimon</i>; mouflon) and axis deer (<i>Axis axis</i>; deer) were introduced on the island of Lāna‘i<i><span>&nbsp;</span></i>to provide additional hunting opportunities.<i><span>&nbsp;</span></i>Managers will require better information regarding the ecological associations of introduced ungulate species, relative to the habitats occupied, to resolve longstanding conflicts between native species conservation and sustained-yield hunting on islands. To address this information need, we modeled sheep and deer ecological associations, habitat-use, and suitability using data obtained from an intensive aerial survey completed in 2013 and temporally matching environmental data. In habitat suitability models evaluated by Receiver Operating Characteristic (ROC) metrics, predictor importance in a generalized linear model (GLM) of deer decreased in the following order: afternoon cloud cover, topographic slope, mean annual precipitation (MAP), elevation, normalized difference vegetation index (NDVI), and bare soil index. In a random GLM model of mouflon, predictor importance decreased in the following order: afternoon cloud cover, deer habitat suitability, NDVI, bare soil index, topographic slope, elevation, and MAP. Mouflon were restricted to lower elevation arid slopes, whereas deer were more broadly distributed throughout upland environments of the island. The presence of deer was also an important predictor for mouflon distribution, although mouflon was not an important predictor of deer, suggesting asymmetrical competition. Removal of the more abundant deer population may lead to an increase in abundance and distribution of mouflon without containment. This work represents the first habitat suitability analysis for all nonnative ungulates on any entire Hawaiian island. Our results are applicable to other islands where conflicts may arise with introduced ungulates, sustained-yield hunting, and native species conservation.</p></div><div id=\"recommended_citation\" class=\"element\"><br></div>","language":"English","publisher":"Berryman Insititute","doi":"10.26077/be03-b519","usgsCitation":"Hess, S.C., Brinck, K., Leopold, C.R., Muise, J., and Sprague, J., 2023, Ecological associations of non-native ungulates on the Hawaiian Island of Lāna‘i: Human-Wildlife Interactions, v. 17, no. 2, 14 p., https://doi.org/10.26077/be03-b519.","productDescription":"14 p.","ipdsId":"IP-134608","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":463043,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Lāna‘i","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -157.25852174158157,\n              21.072831141997597\n            ],\n            [\n              -157.25852174158157,\n              20.56423494187817\n            ],\n            [\n              -156.5879617183619,\n              20.56423494187817\n            ],\n            [\n              -156.5879617183619,\n              21.072831141997597\n            ],\n            [\n              -157.25852174158157,\n              21.072831141997597\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hess, Steven C.","contributorId":176679,"corporation":false,"usgs":false,"family":"Hess","given":"Steven","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":916161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":916162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leopold, Christina R","contributorId":345275,"corporation":false,"usgs":false,"family":"Leopold","given":"Christina","email":"","middleInitial":"R","affiliations":[{"id":82536,"text":"0000-0003-0499-3196","active":true,"usgs":false}],"preferred":false,"id":916163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muise, Jacob","contributorId":240997,"corporation":false,"usgs":false,"family":"Muise","given":"Jacob","email":"","affiliations":[{"id":48185,"text":"KIA Hawaii","active":true,"usgs":false}],"preferred":false,"id":916164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sprague, Jonathan","contributorId":240998,"corporation":false,"usgs":false,"family":"Sprague","given":"Jonathan","email":"","affiliations":[{"id":48186,"text":"Pulama Lana‘i","active":true,"usgs":false}],"preferred":false,"id":916165,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241162,"text":"70241162 - 2023 - Landslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA","interactions":[],"lastModifiedDate":"2023-11-08T11:48:36.011532","indexId":"70241162","displayToPublicDate":"2023-10-18T11:44:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Landslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA","docAbstract":"<p><span>Probabilistic models to inform landslide early warning systems often rely on rainfall totals observed during past events with landslides. However, these models are generally developed for broad regions using large catalogs, with dozens, hundreds, or even thousands of landslide occurrences. This study evaluates strategies for training landslide forecasting models with a scanty record of landslide-triggering events, which is a typical limitation in remote, sparsely populated regions. We evaluate 136 statistical models trained on a precipitation dataset with five landslide-triggering precipitation events recorded near Sitka, Alaska, USA, as well as&nbsp;</span><span class=\"inline-formula\"><i>&gt;</i></span><span> 6000 d of non-triggering rainfall (2002–2020). We also conduct extensive statistical evaluation for three primary purposes: (1)&nbsp;to select the best-fitting models, (2)&nbsp;to evaluate performance of the preferred models, and (3)&nbsp;to select and evaluate warning thresholds. We use Akaike, Bayesian, and leave-one-out information criteria to compare the 136 models, which are trained on different cumulative precipitation variables at time intervals ranging from 1 h to 2&nbsp;weeks, using both frequentist and Bayesian methods to estimate the daily probability and intensity of potential landslide occurrence (logistic regression and Poisson regression). We evaluate the best-fit models using leave-one-out validation as well as by testing a subset of the data. Despite this sparse landslide inventory, we find that probabilistic models can effectively distinguish days with landslides from days without slide activity. Our statistical analyses show that 3 h precipitation totals are the best predictor of elevated landslide hazard, and adding antecedent precipitation (days to weeks) did not improve model performance. This relatively short timescale of precipitation combined with the limited role of antecedent conditions likely reflects the rapid draining of porous colluvial soils on the very steep hillslopes around Sitka. Although frequentist and Bayesian inferences produce similar estimates of landslide hazard, they do have different implications for use and interpretation: frequentist models are familiar and easy to implement, but Bayesian models capture the rare-events problem more explicitly and allow for better understanding of parameter uncertainty given the available data. We use the resulting estimates of daily landslide probability to establish two decision boundaries that define three levels of warning. With these decision boundaries, the frequentist logistic regression model incorporates National Weather Service quantitative precipitation forecasts into a real-time landslide early warning “dashboard” system (</span><span class=\"uri\"><a rel=\"noopener\" href=\"https://sitkalandslide.org/\" target=\"_blank\" data-mce-href=\"https://sitkalandslide.org/\">https://sitkalandslide.org/</a></span><span>, last access: 9&nbsp;October&nbsp;2023). This dashboard provides accessible and data-driven situational awareness for community members and emergency managers.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-23-3261-2023","usgsCitation":"Patton, A., Luna, L., Roering, J.J., Jacobs, A., Korup, O., and Mirus, B., 2023, Landslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA: Natural Hazards and Earth System Sciences, v. 23, no. 10, p. 3261-3284, https://doi.org/10.5194/nhess-23-3261-2023.","productDescription":"24 p.","startPage":"3261","endPage":"3284","ipdsId":"IP-148647","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":441845,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-23-3261-2023","text":"Publisher Index Page"},{"id":422429,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Sitka","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -135.5083890264902,\n              57.18995904083906\n            ],\n            [\n              -135.5083890264902,\n              56.972958920434166\n            ],\n            [\n              -135.177168114468,\n              56.972958920434166\n            ],\n            [\n              -135.177168114468,\n              57.18995904083906\n            ],\n            [\n              -135.5083890264902,\n              57.18995904083906\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"23","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Patton, Annette","contributorId":303028,"corporation":false,"usgs":false,"family":"Patton","given":"Annette","email":"","affiliations":[{"id":65615,"text":"Sitka Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":866314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luna, Lisa","contributorId":303029,"corporation":false,"usgs":false,"family":"Luna","given":"Lisa","email":"","affiliations":[{"id":52955,"text":"University of Potsdam","active":true,"usgs":false}],"preferred":false,"id":866315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roering, Josh J.","contributorId":303030,"corporation":false,"usgs":false,"family":"Roering","given":"Josh","email":"","middleInitial":"J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":866316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacobs, Aaron","contributorId":204855,"corporation":false,"usgs":false,"family":"Jacobs","given":"Aaron","email":"","affiliations":[{"id":36995,"text":"NWS","active":true,"usgs":false}],"preferred":false,"id":866317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Korup, Oliver","contributorId":218071,"corporation":false,"usgs":false,"family":"Korup","given":"Oliver","email":"","affiliations":[{"id":39735,"text":"Institute of Earth and Environmental Science, University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":866318,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":267912,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":866319,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70256600,"text":"70256600 - 2023 - Assessing potential spawning locations of Silver Chub in Lake Erie","interactions":[],"lastModifiedDate":"2024-08-23T16:05:33.325572","indexId":"70256600","displayToPublicDate":"2023-10-18T10:57:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessing potential spawning locations of Silver Chub in Lake Erie","docAbstract":"<h3 id=\"nafm10870-sec-0054-title\" class=\"article-section__sub-title section1\">Objective</h3><p>Silver Chub<span>&nbsp;</span><i>Macrhybopsis storeriana</i>, a predominately riverine species throughout its native range, exists within Lake Erie as the only known lake population. Its population declined in the 1950s and never fully recovered. Canada has listed Silver Chub in the Great Lakes–St. Lawrence River as endangered and has initiated a recovery plan that recognized the identification of spawning areas as a critical component to inform Silver Chub's recovery potential.</p><h3 id=\"nafm10870-sec-0053-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We investigated potential spawning locations of Silver Chub using capture records, otolith microchemistry, and daily age analysis. Lapillus otolith Sr:Ca ratios from 27 age-0 Silver Chub were used to identify potential spawning areas. Daily ages estimated from lapilli were used to calculate hatch dates, which then were compared with capture data of adults and river flows to further inform potential spawning areas.</p><h3 id=\"nafm10870-sec-0051-title\" class=\"article-section__sub-title section1\">Result</h3><p>The Detroit River (and its nearshore area) was all but ruled out as a potential spawning location. The Maumee, Portage, and Sandusky rivers or their nearshore areas were all possible spawning locations. Projected hatch dates spanned the end of May through the end of June and occurred across a wide range of flows, although some peaks in hatch dates corresponded to flow peaks, indicating recruitment is potentially enhanced by high flows.</p><h3 id=\"nafm10870-sec-0050-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>Silver Chub spawning period and hypothesized spawning rivers or lacustuaries overlap those of invasive Grass Carp<span>&nbsp;</span><i>Ctenopharyngodon idella</i>, creating a need to jointly consider Grass Carp control efforts with conservation of Silver Chub when assessing management alternatives. Further research on spawning guild and the use of rivers themselves or nearshore areas influenced by rivers as spawning areas are required to maximize potential for conservation and recovery of Silver Chub.</p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10870","usgsCitation":"McKenna, J.R., Bowen, A., Farver, J.R., Long, J.M., Miner, J.G., Stott, N.D., and Kocovsky, P.M., 2023, Assessing potential spawning locations of Silver Chub in Lake Erie: North American Journal of Fisheries Management, v. 43, no. 5, p. 1166-1179, https://doi.org/10.1002/nafm.10870.","productDescription":"14 p.","startPage":"1166","endPage":"1179","ipdsId":"IP-139223","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":441847,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10870","text":"Publisher Index Page"},{"id":433107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -78.90437674926393,\n              42.88573072124271\n            ],\n            [\n              -79.52141499356523,\n              42.87769210959476\n            ],\n            [\n              -80.22678399206747,\n              42.79281581499302\n            ],\n            [\n              -80.51880625151767,\n              42.57814946253396\n            ],\n            [\n              -81.02026663661093,\n              42.67543230196293\n            ],\n            [\n              -81.30128454543694,\n              42.67543535756306\n            ],\n            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R.","contributorId":341316,"corporation":false,"usgs":false,"family":"McKenna","given":"Jorden","email":"","middleInitial":"R.","affiliations":[{"id":81722,"text":"Lake Erie Biological Station","active":true,"usgs":false}],"preferred":false,"id":908227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowen, Anjanette","contributorId":341317,"corporation":false,"usgs":false,"family":"Bowen","given":"Anjanette","affiliations":[{"id":81723,"text":"US Fish and Wildlife Service Alpena Fish and Wildlife Conservation Office","active":true,"usgs":false}],"preferred":false,"id":908228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farver, John R.","contributorId":341318,"corporation":false,"usgs":false,"family":"Farver","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":908229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miner, Jeffrey G.","contributorId":341319,"corporation":false,"usgs":false,"family":"Miner","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":908231,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stott, Nathan D.","contributorId":341320,"corporation":false,"usgs":false,"family":"Stott","given":"Nathan","email":"","middleInitial":"D.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":908232,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kocovsky, Patrick M. 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":3429,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","middleInitial":"M.","affiliations":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":908233,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70249600,"text":"70249600 - 2023 - Inter-comparison of measurements of inorganic chemical components in precipitation from NADP and CAPMoN at collocated sites in the USA and Canada during 1986–2019","interactions":[],"lastModifiedDate":"2023-10-20T13:19:06.53518","indexId":"70249600","displayToPublicDate":"2023-10-18T09:23:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Inter-comparison of measurements of inorganic chemical components in precipitation from NADP and CAPMoN at collocated sites in the USA and Canada during 1986–2019","docAbstract":"<p><span>Wet deposition monitoring is a critical part of the long-term monitoring of acid deposition, which aims to assess the ecological impact of anthropogenic emissions of SO</span><sub>2</sub><span>&nbsp;and NO</span><sub>x</sub><span>. In North America, long-term wet deposition has been monitored through two national networks: the Canadian Air and Precipitation Monitoring Network (CAPMoN) and the US National Atmospheric Deposition Program (NADP), for Canada and the USA, respectively. In order to assess the comparability of measurements from the two networks, collocated measurements have been made at two sites, one in each country, since 1986 (Sirois et al., in&nbsp;</span><i>Environmental Monitoring and Assessment, 62</i><span>, 273–303, 2000; Wetherbee et al., in&nbsp;</span><i>Environmental Monitoring and Assessment</i><span>, 1995–2004, 2010). In this study, we compared the measurements from NADP and CAPMoN instrumentation at the collocated sites at the Pennsylvania State University (Penn State), USA, from 1989 to 2016, and Frelighsburg, Quebec, Canada, from 2002 to 2019. We also included in the study the collocated daily-vs-weekly measurements by the CAPMoN network during 1999–2001 and 2016–2017 in order to evaluate the differences in wet concentration of ions due to sampling frequency alone. The study serves as an extension to two previous CAPMoN-NADP inter-comparisons by Sirois et al. (</span><i>Environmental Monitoring and Assessment, 62</i><span>, 273–303, 2000) and Wetherbee et al., in (</span><i>Environmental Monitoring and Assessment</i><span>, 1995–2004, 2010). At the Penn State University site, for 1986–2019, CAPMoN was higher than NADP for all ions, in terms of weekly concentration, precipitation-weighted annual mean concentration, and annual wet deposition. The precipitation-weighted annual mean concentrations were higher for SO</span><sub>4</sub><sup>2−</sup><span>&nbsp;(2%), NO</span><sub>3</sub><sup>−</sup><span>&nbsp;(12%), NH</span><sub>4</sub><sup>+</sup><span>&nbsp;(16%), H</span><sup>+</sup><span>&nbsp;(6%), and base cations and Cl</span><sup>−</sup><span>&nbsp;(11–15%). For annual wet deposition, CAPMoN was higher for SO</span><sub>4</sub><sup>−2</sup><span>, NO</span><sub>3</sub><sup>−</sup><span>, NH</span><sub>4</sub><sup>+</sup><span>&nbsp;and H</span><sup>+</sup><span>&nbsp;(5–17%), and base cations and Cl</span><sup>−</sup><span>&nbsp;(12–17%) during 1986–2019. At the Frelighsburg site, NADP changed the sample collector in October 2011. For 2002–2011, the relative differences at the Frelighsburg site were positive and similar in magnitude to those at the Penn State site. For 2012–2019, the precipitation-weighted annual mean concentrations were 5–27% lower than NADP, except for H</span><sup>+</sup><span>, which was 23% higher. The change in sample collector by NADP had the largest effect on between-network biases. The comparisons of daily-vs-weekly measurements conducted by the CAPMoN network during 1999–2001 and 2016–2017 show that the weekly measurements were higher than the daily measurements by 1–3% for SO</span><sub>4</sub><sup>2−</sup><span>, NO</span><sub>3</sub><sup>−</sup><span>, and NH</span><sub>4</sub><sup>+</sup><span>; 3–9% for Ca</span><sup>2+</sup><span>, Mg</span><sup>2+</sup><span>, Na</span><sup>+</sup><span>, and Cl</span><sup>−</sup><span>; 10–24% for K</span><sup>+</sup><span>; and lower for H</span><sup>+</sup><span>&nbsp;by 8–30% in terms of precipitation-weighted mean concentration. Thus, differences in sampling frequencies did not contribute to the systematically higher CAPMoN measurements. Understanding the biases in the data for these networks is important for interpretation of continental scale deposition models and transboundary comparison of wet deposition trends.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s10661-023-11771-z","usgsCitation":"Feng, J., Cole, A., Wetherbee, G.A., and Banwait, K., 2023, Inter-comparison of measurements of inorganic chemical components in precipitation from NADP and CAPMoN at collocated sites in the USA and Canada during 1986–2019: Environmental Monitoring and Assessment, v. 195, 1333, 34 p., https://doi.org/10.1007/s10661-023-11771-z.","productDescription":"1333, 34 p.","ipdsId":"IP-153496","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":441851,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-023-11771-z","text":"Publisher Index Page"},{"id":422000,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"195","noUsgsAuthors":false,"publicationDate":"2023-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Feng, Jian","contributorId":330980,"corporation":false,"usgs":false,"family":"Feng","given":"Jian","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":886400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Amanda","contributorId":330981,"corporation":false,"usgs":false,"family":"Cole","given":"Amanda","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":886401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wetherbee, Gregory A. 0000-0002-6720-2294","orcid":"https://orcid.org/0000-0002-6720-2294","contributorId":215100,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory","email":"","middleInitial":"A.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":886402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banwait, Kulbir","contributorId":330982,"corporation":false,"usgs":false,"family":"Banwait","given":"Kulbir","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":886403,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70252214,"text":"70252214 - 2023 - Variability in terrestrial characteristics and erosion rates on the Alaskan Beaufort Sea coast","interactions":[],"lastModifiedDate":"2024-03-20T11:53:06.811606","indexId":"70252214","displayToPublicDate":"2023-10-18T06:50:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Variability in terrestrial characteristics and erosion rates on the Alaskan Beaufort Sea coast","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Arctic coastal environments are eroding and rapidly changing. A lack of pan-Arctic observations limits our ability to understand controls on coastal erosion rates across the entire Arctic region. Here, we capitalize on an abundance of geospatial and remotely sensed data, in addition to model output, from the North Slope of Alaska to identify relationships between historical erosion rates and landscape characteristics to guide future modeling and observational efforts across the Arctic. Using existing datasets from the Alaska Beaufort Sea coast and a hierarchical clustering algorithm, we developed a set of 16 coastal typologies that captures the defining characteristics of environments susceptible to coastal erosion. Relationships between landscape characteristics and historical erosion rates show that no single variable alone is a good predictor of erosion rates. Variability in erosion rate decreases with increasing coastal elevation, but erosion rate magnitudes are highest for intermediate elevations. Areas along the Alaskan Beaufort Sea coast (ABSC) protected by barrier islands showed a three times lower erosion rate on average, suggesting that barrier islands are critical to maintaining mainland shore position. Finally, typologies with the highest erosion rates are not broadly representative of the ABSC and are generally associated with low elevation, north- to northeast-facing shorelines, a peaty pebbly silty lithology, and glaciomarine deposits with high ice content. All else being equal, warmer permafrost is also associated with higher erosion rates, suggesting that warming permafrost temperatures may contribute to higher future erosion rates on permafrost coasts. The suite of typologies can be used to guide future modeling and observational efforts by quantifying the distribution of coastlines with specific landscape characteristics and erosion rates.</p></div>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ad04b8","usgsCitation":"Piliouras, A., Jones, B.M., Clevenger, T., Gibbs, A.E., and Rowland, J.C., 2023, Variability in terrestrial characteristics and erosion rates on the Alaskan Beaufort Sea coast: Environmental Research Letters, v. 18, 114050, 10 p., https://doi.org/10.1088/1748-9326/ad04b8.","productDescription":"114050, 10 p.","ipdsId":"IP-141537","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441857,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ad04b8","text":"Publisher Index Page"},{"id":426794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -160.82972953158225,\n              72.33792024202972\n            ],\n            [\n              -160.82972953158225,\n              68.87395946820305\n            ],\n            [\n              -140.35121390658202,\n              68.87395946820305\n            ],\n            [\n              -140.35121390658202,\n              72.33792024202972\n            ],\n            [\n              -160.82972953158225,\n              72.33792024202972\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"18","noUsgsAuthors":false,"publicationDate":"2023-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Piliouras, Anastasia","contributorId":334927,"corporation":false,"usgs":false,"family":"Piliouras","given":"Anastasia","email":"","affiliations":[{"id":80287,"text":"Department of Geosciences, Pennsylvania State University, University Park, PA","active":true,"usgs":false}],"preferred":false,"id":896945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M.","contributorId":305542,"corporation":false,"usgs":false,"family":"Jones","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":896946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clevenger, Tabatha","contributorId":334928,"corporation":false,"usgs":false,"family":"Clevenger","given":"Tabatha","email":"","affiliations":[{"id":80288,"text":"Department of Earth Science and Geography, Vassar College, Poughkeepsie, NY","active":true,"usgs":false}],"preferred":false,"id":896947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":896948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowland, Joel C.","contributorId":169046,"corporation":false,"usgs":false,"family":"Rowland","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":896949,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70269403,"text":"70269403 - 2023 - High potential but low achievement: Frequent disturbance constrains the light use efficiency of river ecosystems","interactions":[],"lastModifiedDate":"2025-07-22T14:48:02.96331","indexId":"70269403","displayToPublicDate":"2023-10-18T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"High potential but low achievement: Frequent disturbance constrains the light use efficiency of river ecosystems","docAbstract":"<p><span>We rarely consider light limitation in ecosystem productivity, yet light limitation is a major constraint on river autotrophy. Because the light that reaches benthic autotrophs must first pass through terrestrial vegetation and an overlying water column that can be loaded with sediments or colored organic material, there is strong selection for river autotrophs to have high light use efficiencies (LUEs), that is, the efficiency at which light energy is converted to biomass. In contrast to prior studies that have estimated river LUE on single days, we calculated continuous LUE over more than 6 full years for 64 free-flowing rivers across the United States. This dataset represents the largest compilation of continuous estimates of daily rates of gross primary productivity (GPP) and daily light inputs from which we calculated daily estimates of LUE. Early estimates of LUE in rivers found that clearwater springs with stable flows could achieve LUEs of 4%, much higher than LUEs reported for terrestrial plants. We found that 53% of the rivers in our dataset have LUEs that exceed 4% on at least one day of their time series. Because of the high variability in daily LUE, measurements taken on any given day may misrepresent a river ecosystem's annual LUE. Though most rivers share a high potential, the mean annual LUE of all rivers in our dataset is much lower, only 0.5%. We found that rivers with more variable flow regimes had lower annual LUEs, which indicates that LUE is constrained by hydrologic disturbances that remove, bury, or shade autotrophic biomass. Comparisons of LUE across ecosystems allow us to reframe our view of rivers, by recognizing the high efficiency with which they convert light to biomass compared with lentic, marine, and terrestrial ecosystems.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4659","usgsCitation":"Thellman, A., Savoy, P., and Bernhardt, E., 2023, High potential but low achievement: Frequent disturbance constrains the light use efficiency of river ecosystems: Ecosphere, v. 14, no. 10, e4659, 9 p., https://doi.org/10.1002/ecs2.4659.","productDescription":"e4659, 9 p.","ipdsId":"IP-151660","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":492879,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4659","text":"Publisher Index Page"},{"id":492731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                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]\n}","volume":"14","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Thellman, Audrey 0000-0003-3716-6664","orcid":"https://orcid.org/0000-0003-3716-6664","contributorId":265349,"corporation":false,"usgs":false,"family":"Thellman","given":"Audrey","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":943676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savoy, Philip 0000-0002-6075-837X","orcid":"https://orcid.org/0000-0002-6075-837X","contributorId":300288,"corporation":false,"usgs":true,"family":"Savoy","given":"Philip","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":943677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bernhardt, Emily S.","contributorId":92143,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily S.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false}],"preferred":false,"id":943678,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70249501,"text":"sir20235089 - 2023 - Arsenic, chromium, uranium, and vanadium in rock, alluvium, and groundwater, Mojave River and Morongo Areas, western Mojave Desert, southern California","interactions":[],"lastModifiedDate":"2026-03-12T21:10:49.839691","indexId":"sir20235089","displayToPublicDate":"2023-10-16T13:41:24","publicationYear":"2023","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":"2023-5089","displayTitle":"Arsenic, Chromium, Uranium, and Vanadium in Rock, Alluvium, and Groundwater, Mojave River and Morongo Areas, Western Mojave Desert, Southern California","title":"Arsenic, chromium, uranium, and vanadium in rock, alluvium, and groundwater, Mojave River and Morongo Areas, western Mojave Desert, southern California","docAbstract":"<p>Trace elements within groundwater that originate from aquifer materials and pose potential public-health hazards if consumed are known as geogenic contaminants. The geogenic contaminants arsenic, chromium, and vanadium can form negatively charged ions with oxygen known as oxyanions. Uranium complexes with bicarbonate and carbonate to form negatively charged ions having aqueous chemistry similar to oxyanions. The concentrations of arsenic, chromium, uranium, and vanadium in groundwater result from the combined effects of (1) geologic abundance within aquifer materials; (2) the fraction of these elements that have weathered from and sorbed to the surfaces of mineral grains and are potentially available to groundwater; and (3) the aqueous chemistry of dissolved oxyanions in groundwater during different redox conditions and pH, both of which are affected by hydrogeology, including the length of time groundwater has been in contact with aquifer materials. Concentrations of arsenic, chromium, uranium, and vanadium were measured in samples of (1) rock, surficial alluvium, and drill cuttings using portable (handheld) X-ray fluorescence (pXRF); (2) operationally defined fractions extractable from these materials; and (3) water from wells sampled between 2000 and 2018 within the 3,500 square mile Mojave River area and Morongo area of the western Mojave Desert, southern California.</p><p>Regionally, rock and surficial alluvium in the Mojave River and Morongo areas are high in arsenic, low in chromium and uranium, and near the average bulk continental crust concentration for vanadium. Locally, high chromium concentrations are present in mafic rock within the San Gabriel Mountains; high uranium concentrations are present in felsic rock within the San Bernardino Mountains; and high arsenic, uranium, and vanadium concentrations are present in extrusive (volcanic) felsic rock within uplands surrounding groundwater basins along the Mojave River downstream from Barstow, California. Elemental assemblages identified using principal component analyses (PCA) of pXRF data were used to characterize felsic, mafic, and felsic volcanic source terranes in rock, surficial alluvium, and in geologic material penetrated by selected monitoring wells drilled between 1994 and 2018. Highly felsic alluvium associated with recent deposition from the Mojave River was identified along the 90-mile length of the floodplain aquifer along the river. The thickness of these highly felsic alluvial deposits ranged from 200 feet (ft) near Victorville and near Barstow to a thin veneer about 30 ft thick downstream from Victorville and downstream portions of the floodplain aquifer within the Mojave Valley.</p><p>Groundwater in the Mojave River and Morongo areas was generally oxic and alkaline (pH≥7.5). Maximum concentrations of arsenic, hexavalent chromium [Cr(VI)], uranium, and vanadium in water from as many as 498 wells sampled between 2000 and 2018 were 360, 140, 1,470, and 690 micrograms per liter (μg/L), respectively. Water from 22 percent of sampled wells exceeded the U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) for arsenic of 10 μg/L, with arsenic concentrations commonly exceeding the MCL in water from wells east of Barstow, deep wells in the Victorville fan, and in suboxic or reduced groundwater within the floodplain aquifer. Water from about 1 percent of sampled wells had Cr(VI) concentrations greater than the California MCL for total chromium of 50 μg/L, whereas 13 percent of sampled wells had Cr(VI) concentrations greater than the former California MCL of 10 μg/L. Hexavalent chromium concentrations were highest in water from wells in the Sheep Creek alluvial fan, eroded from mafic rock in the San Gabriel Mountains, although Cr(VI) concentrations greater than the former California MCL also were present elsewhere in the study area where mafic materials or older groundwater were present. Water from about 9 percent of sampled wells exceeded the EPA MCL for uranium of 30 μg/L, with concentrations exceeding the MCL commonly associated with irrigation return from agricultural land overlying the floodplain aquifer. Water from about 7 percent of sampled wells had vanadium concentrations greater than the California notification level of 50 μg/L; most of these wells were in the Victorville fan within the Mojave River area. In general, arsenic concentrations were higher in suboxic or reduced water; chromium concentrations were higher in oxic, alkaline (pH≥7.5) water; uranium concentrations were higher in circumneutral to slightly alkaline water (pH≤7.4); and vanadium concentrations were higher in highly alkaline (pH≥8.0) water, independent of redox status.</p><p>Concentrations within geologic source terranes are not the sole factor controlling the concentrations of geogenic elements in groundwater. Differences in mineral weathering, pH-dependent sorption to surface-exchange sites on mineral grains, and aqueous geochemistry (especially redox status and pH) affect geogenic element concentrations in groundwater. Consequently, the relative abundances of arsenic, Cr(VI), uranium, and vanadium in groundwater differ from their relative abundances in the average bulk continental crust and their regional abundances in rock and surficial alluvium within groundwater basins of the western Mojave Desert. Processes that control the concentrations of arsenic, chromium, uranium, and vanadium in groundwater operate at the mineral-grain and aquifer scale.</p><p>At the mineral-grain scale, sequential chemical extraction data show arsenic and uranium are more available to groundwater (under specific geochemical conditions) than chromium or vanadium, which largely are unavailable within unweathered mineral grains. Additionally, chromium and vanadium form few aqueous complexes and bind tightly with iron minerals within surface coatings on mineral grains making them less available to groundwater, whereas complexation with other dissolved ions enhances the solubility of uranium and, to a lesser extent, arsenic. Complexation also increases the valence (less negative charge) and increases the size of dissolved oxyanions and uranium complexes with bicarbonate and carbonate making them less readily sorbed to aquifer materials.</p><p>At the aquifer scale, hydrogeology (including isolation of water in aquifers from surface sources of recharge, older groundwater age, and long contact times between groundwater and aquifer materials) combined with geochemical processes (such as silicate weathering) to produce alkaline groundwater. Desorption from sorption sites on the surfaces of mineral grains with increasing pH increases arsenic, chromium, and vanadium concentrations in water from wells and increases Cr(VI) concentrations as long as water remains oxic.</p><p>Aqueous geochemistry and concentrations of geogenic contaminants also are affected by anthropogenic activities including (1) discharge of treated municipal wastewater, which may change the redox status of groundwater; (2) return from irrigated agriculture, which may alter the chemistry of groundwater and increase the solubility of trace elements such as uranium; and (3) groundwater pumping and subsequent water-level declines, which may change the source of water yielded by wells. The quality of water imported from northern California and infiltrated from ponds for groundwater recharge may be altered by naturally present trace elements, especially uranium in areas of agricultural land use or chromium within mafic alluvium.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235089","collaboration":"Prepared in cooperation with the Mojave Water Agency","programNote":"U.S. Geological Survey Cooperative Water Program","usgsCitation":"Izbicki, J.A., Groover, K.D., and Seymour, W.A., 2023, Arsenic, chromium, uranium, and vanadium in rock, alluvium, and groundwater, western Mojave Desert, southern California: U.S. Geological Survey Scientific Investigations Report 2023–5089, 96 p., https://doi.org/10.3133/sir20235089.","productDescription":"Report: xiii, 96 p., 3 Data Releases; 2 Tables","numberOfPages":"96","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101005","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501053,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115509.htm","linkFileType":{"id":5,"text":"html"}},{"id":421873,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir20235089_table2.1.csv","text":"Table 2.1","size":"3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Well Identification and National Water Information System Record Numbers for Wells Sampled in the Mojave River and Morongo Groundwater Basins as Part of This Study July 2016 to October 2016 and for Wells Sampled as Part of the Groundwater Ambient Monitoring Assessment Program Priority Basin Project Mojave Basin Domestic-Supply Aquifer Study January to May 2018 western Mojave Desert southern California"},{"id":421877,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C7U6DW","text":"USGS Data Release","description":"Groover, K.D., Goldrath, D.A., Bennett, G.L., Johnson, T.D., and Watson, E.E., 2019, Groundwater-quality data in the Mojave Basin Shallow Aquifer Study Unit, 2018—Results from the California GAMA Priority Basin Project: U.S. Geological Survey data release, https://doi.org/10.5066/P9C7U6DW.","linkHelpText":"Groundwater-quality data in the Mojave Basin Shallow Aquifer Study Unit, 2018—Results from the California GAMA Priority Basin Project"},{"id":421878,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://ca.water.usgs.gov/mojave/mojave-water-quality.html","text":"USGS Data Release","description":"Metzger, L.F., Landon, M.K., House, S.F., and Olsen, L.D., 2015, Mapping selected trace elements and major ions, 2000–2012, Mojave River and Morongo Groundwater Basins, Southwestern Mojave Desert, San Bernardino County, California: U.S. Geological Survey data release, https://ca.water.usgs.gov/mojave/mojave-water-quality.html.","linkHelpText":"Mapping selected trace elements and major ions, 2000–2012, Mojave River and Morongo Groundwater Basins, Southwestern Mojave Desert, San Bernardino County, California"},{"id":421923,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235089/full"},{"id":421973,"rank":10,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir_20235089.pdf","text":"Report","size":"30 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":421869,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5089/covrthb.jpg"},{"id":421871,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir20235089.xml"},{"id":421872,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir20235089_table1.1.csv","text":"Table 1.1","size":"3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"-  Boreholes having portable (handheld) X-ray fluoresence (pXRF) data from drill cuttings, Mojave River and Morongo groundwater basins, western Mojave Desert, southern California"},{"id":421874,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5089/images"},{"id":421876,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CU0EH3","text":"USGS Data Release","description":"Groover, K.D., and Izbicki, J.A., 2018, Field portable X-ray fluorescence and associated quality control data for the western Mojave Desert, San Bernardino County, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9CU0EH3.","linkHelpText":"Field portable X-ray fluorescence and associated quality control data for the western Mojave Desert, San Bernardino County, California"}],"country":"United States","state":"California","otherGeospatial":"Western Mojave Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.4,\n              35.2\n            ],\n            [\n              -117.4,\n              34.00\n            ],\n            [\n              -116.0,\n              34\n            ],\n            [\n              -116,\n              35.2\n            ],\n            [\n              -117.4,\n              35.2\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Geologic And Geochemical Data&nbsp;</li><li>Synthesis of Geologic and Geochemical Data&nbsp;</li><li>Conclusions&nbsp;</li><li>References Cited&nbsp;</li><li>Appendix 1.&nbsp;</li><li>Appendix 2.</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-10-16","noUsgsAuthors":false,"publicationDate":"2023-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":152474,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","email":"jaizbick@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":885965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Groover, Krishangi D. 0000-0002-5805-8913 kgroover@usgs.gov","orcid":"https://orcid.org/0000-0002-5805-8913","contributorId":5626,"corporation":false,"usgs":true,"family":"Groover","given":"Krishangi","email":"kgroover@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":885966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seymour, Whitney A. 0000-0002-5999-6573 wseymour@usgs.gov","orcid":"https://orcid.org/0000-0002-5999-6573","contributorId":4131,"corporation":false,"usgs":true,"family":"Seymour","given":"Whitney","email":"wseymour@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":885967,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70256086,"text":"70256086 - 2023 - BatTool: Projecting bat populations facing multiple stressors using a demographic model","interactions":[],"lastModifiedDate":"2024-07-19T11:57:51.992521","indexId":"70256086","displayToPublicDate":"2023-10-16T06:55:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"BatTool: Projecting bat populations facing multiple stressors using a demographic model","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Bats provide ecologically and agriculturally important ecosystem services but are currently experiencing population declines caused by multiple environmental stressors, including mortality from white-nose syndrome and wind energy development. Analyses of the current and future health and viability of these species may support conservation management decision making. Demographic modeling provides a quantitative tool for decision makers and conservation managers to make more informed decisions, but widespread adoption of these tools can be limited because of the complexity of the mathematical, statistical, and computational components involved in implementing these models. In this work, we provide an exposition of the BatTool R package, detailing the primary components of the matrix projection model, a publicly accessible graphical user interface (<a href=\"https://rconnect.usgs.gov/battool\" data-mce-href=\"https://rconnect.usgs.gov/battool\">https://rconnect.usgs.gov/battool</a>) facilitating user-defined scenario analyses, and its intended uses and limitations (Wiens et al., US Geol Surv Data Release 2022; Wiens et al., US Geol Surv Softw Release 2022). We present a case study involving wind energy permitting, weighing the effects of potential mortality caused by a hypothetical wind energy facility on the projected abundance of four imperiled bat species in the Midwestern United States.</p></div></div>","language":"English","publisher":"British Ecological Society","doi":"10.1186/s12862-023-02159-1","usgsCitation":"Wiens, A.M., Schorg, A., Szymanski, J., and Thogmartin, W.E., 2023, BatTool: Projecting bat populations facing multiple stressors using a demographic model: Methods in Ecology and Evolution, v. 23, 61, 16 p., https://doi.org/10.1186/s12862-023-02159-1.","productDescription":"61, 16 p.","ipdsId":"IP-132438","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":441872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12862-023-02159-1","text":"Publisher Index Page"},{"id":431237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","noUsgsAuthors":false,"publicationDate":"2023-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Wiens, Ashton M. 0000-0002-7030-0602","orcid":"https://orcid.org/0000-0002-7030-0602","contributorId":271176,"corporation":false,"usgs":true,"family":"Wiens","given":"Ashton","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":906644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schorg, Amber","contributorId":333055,"corporation":false,"usgs":false,"family":"Schorg","given":"Amber","email":"","affiliations":[{"id":68344,"text":"U.S. Fish and Wildlife Service (USFWS)","active":true,"usgs":false}],"preferred":false,"id":906645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Szymanski, Jennifer","contributorId":15123,"corporation":false,"usgs":false,"family":"Szymanski","given":"Jennifer","affiliations":[{"id":6969,"text":"U.S. Fish and Wildlife Service, Division of Endangered Species","active":true,"usgs":false}],"preferred":false,"id":906646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":906647,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250400,"text":"70250400 - 2023 - Science to support conservation action in a large river system: The Willamette River, Oregon, USA","interactions":[],"lastModifiedDate":"2023-12-07T12:58:26.054885","indexId":"70250400","displayToPublicDate":"2023-10-14T06:52:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17103,"text":"Water Biology and Security","active":true,"publicationSubtype":{"id":10}},"title":"Science to support conservation action in a large river system: The Willamette River, Oregon, USA","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif text-s\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>Management and conservation efforts that support the recovery and protection of large rivers are daunting, reflecting the complexity of the challenge and extent of effort (in terms of policy, economic investment, and spatial extent) needed to afford measurable change. These large systems have generally experienced intensive development and regulation, compromising their capacity to respond to disturbances such as climate change or wildfire. Functionally, large river and&nbsp;basin management&nbsp;require insights gained from social, ecological, geophysical, and hydrological sciences. This multi-disciplinary perspective can unveil the integrated relationship between a river network's biotic community and seasonally variable environmental conditions that are often influenced by human activities. Large rivers and their basins are constantly changing due to anthropogenic influences and as climate modifies patterns of temperature and precipitation. Because of these factors, the state of knowledge must advance to address changing conditions. The Willamette River, in western Oregon,&nbsp;USA, is a prime example of a basin that has experienced significant degradation and investment in rehabilitation in recent decades. Innovative science has facilitated development of fine-scale, spatially extensive datasets and models that can generate targeted conservation and rehabilitation actions that are prioritized across the entire river network. This prioritization allows investment decisions to be driven by site-specific conditions while simultaneously considering potentials for ecological improvement. Here, we review hydrologic, geomorphic, ecologic, and social conditions in the Willamette River basin through time—including pre-settlement, river development, and contemporary periods—and offer a future vision for consideration. Currently, detailed information about fish populations and habitat, hydrologic conditions,&nbsp;</span>geomorphology, water quality, and land use can be leveraged to make informed decisions about protection, rehabilitation, and development. The time is ripe for strategic management and goal development for the entire Willamette River, and these efforts can be informed by comprehensive science realized through established institutions (e.g., public agencies, non-profit watershed groups, Tribes, and universities) focused on conservation and management. The approaches to science and social-network creation that were pioneered in the Willamette River basin offer insights into the development of comprehensive conservation-based planning that could be implemented in other large river systems globally.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.watbs.2023.100203","usgsCitation":"Flitcroft, R.L., Whitman, L., White, J., Wallick, J., Stratton Garvin, L.E., Smith, C., Plotnikoff, R., Mulvey, M., Kock, T.J., Jones, K., Gruendike, P., Gombert, C., Giannico, G., Dutterer, A., Brown, D.G., Barrett, H., and Hughes, R.M., 2023, Science to support conservation action in a large river system: The Willamette River, Oregon, USA: Water Biology and Security, v. 2, no. 4, 100203, 16 p., https://doi.org/10.1016/j.watbs.2023.100203.","productDescription":"100203, 16 p.","ipdsId":"IP-148710","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":441883,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watbs.2023.100203","text":"Publisher Index Page"},{"id":423291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.70885566657823,\n              46.467292298881915\n            ],\n            [\n              -124.70885566657823,\n              43.55562581742163\n            ],\n            [\n              -121.35802558845327,\n              43.55562581742163\n            ],\n            [\n              -121.35802558845327,\n              46.467292298881915\n            ],\n            [\n              -124.70885566657823,\n              46.467292298881915\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"2","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Flitcroft, Rebecca L. 0000-0003-3341-996X","orcid":"https://orcid.org/0000-0003-3341-996X","contributorId":172180,"corporation":false,"usgs":false,"family":"Flitcroft","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":889772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitman, Luke","contributorId":290613,"corporation":false,"usgs":false,"family":"Whitman","given":"Luke","email":"","affiliations":[{"id":36223,"text":"Oregon Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":889773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":889774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":889775,"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":889776,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Cassandra 0000-0003-1088-1772 cassandrasmith@usgs.gov","orcid":"https://orcid.org/0000-0003-1088-1772","contributorId":193491,"corporation":false,"usgs":true,"family":"Smith","given":"Cassandra","email":"cassandrasmith@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889777,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Plotnikoff, Robert","contributorId":332240,"corporation":false,"usgs":false,"family":"Plotnikoff","given":"Robert","email":"","affiliations":[{"id":79427,"text":"Snohomish County Department of Conservation and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":889778,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mulvey, Michael","contributorId":332241,"corporation":false,"usgs":false,"family":"Mulvey","given":"Michael","email":"","affiliations":[{"id":79428,"text":"Oregon Department of Environmental Quality Lab","active":true,"usgs":false}],"preferred":false,"id":889779,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kock, Tobias J. 0000-0001-8976-0230","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":214550,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":889780,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jones, Krista 0000-0002-0301-4497","orcid":"https://orcid.org/0000-0002-0301-4497","contributorId":205206,"corporation":false,"usgs":true,"family":"Jones","given":"Krista","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889781,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gruendike, Peter","contributorId":332242,"corporation":false,"usgs":false,"family":"Gruendike","given":"Peter","email":"","affiliations":[{"id":56400,"text":"River Design Group","active":true,"usgs":false}],"preferred":false,"id":889782,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gombert, Carolyn","contributorId":332243,"corporation":false,"usgs":false,"family":"Gombert","given":"Carolyn","email":"","affiliations":[{"id":79429,"text":"Bureau of Reclamation, Sedimentation and River Hydraulics Group","active":true,"usgs":false}],"preferred":false,"id":889783,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Giannico, Guillermo","contributorId":146928,"corporation":false,"usgs":false,"family":"Giannico","given":"Guillermo","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":889784,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dutterer, Andrew","contributorId":332244,"corporation":false,"usgs":false,"family":"Dutterer","given":"Andrew","email":"","affiliations":[{"id":79430,"text":"Oregon Watershed Enhancement Board","active":true,"usgs":false}],"preferred":false,"id":889785,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Brown, Daniel G.","contributorId":139611,"corporation":false,"usgs":false,"family":"Brown","given":"Daniel","email":"","middleInitial":"G.","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":889786,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Barrett, Hannah","contributorId":332245,"corporation":false,"usgs":false,"family":"Barrett","given":"Hannah","email":"","affiliations":[{"id":79431,"text":"Oregon State University, Department of Fisheries, Wildlife, and Conservation Sciences","active":true,"usgs":false}],"preferred":false,"id":889787,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Hughes, Robert M.","contributorId":332246,"corporation":false,"usgs":false,"family":"Hughes","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":79432,"text":"Amnisopes Institute","active":true,"usgs":false}],"preferred":false,"id":889788,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70250123,"text":"70250123 - 2023 - Growth performance of Rainbow Trout in reservoir tributaries and implications for steelhead growth potential above Skagit River dams","interactions":[],"lastModifiedDate":"2023-11-22T16:06:40.787482","indexId":"70250123","displayToPublicDate":"2023-10-13T09:55:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Growth performance of Rainbow Trout in reservoir tributaries and implications for steelhead growth potential above Skagit River dams","docAbstract":"<h3 id=\"nafm10944-sec-1001-title\" class=\"article-section__sub-title section1\">Objective</h3><p>In the Pacific Northwest (USA), Pacific salmon<span>&nbsp;</span><i>Oncorhynchus</i><span>&nbsp;</span>spp. populations have been declining significantly for decades, prompting stakeholders to respond with a variety of conservation and restoration measures. One such measure being considered in the Skagit River basin (Washington, USA) is the introduction of steelhead<span>&nbsp;</span><i>Oncorhynchus mykiss</i><span>&nbsp;</span>(anadromous Rainbow Trout) above the impassable Gorge, Diablo, and Ross dams to bolster their populations. Because freshwater growth is key to survival at subsequent life stages, we evaluated current trends in size and growth of Rainbow Trout among key tributaries to Gorge, Diablo, and Ross reservoirs using empirical data collection and bioenergetics modeling.</p><h3 id=\"nafm10944-sec-1002-title\" class=\"article-section__sub-title section1\">Methods</h3><p>For nine candidate streams, a bioenergetics model was used to assess how temperature and prey consumption affected growth performance of Rainbow Trout between annuli 1 and 2, and 2 and 3. Thermal scenarios were created to evaluate how fish growth responded to temperature variability while total annual consumption was constrained within empirical growth estimates. We then compared these results to back-calculated size thresholds established by size-at-age observed in wild steelhead adults that returned to the Skagit River below the dams.</p><h3 id=\"nafm10944-sec-1003-title\" class=\"article-section__sub-title section1\">Result</h3><p>Of the streams proposed for introductions, there was one instance (McMillan Creek) in the nominal simulations where growth met or exceeded the size at annulus 2 or 3 of a returning adult steelhead (24.9 g at annulus 2 and 50.3 g at annulus 3). Modeled growth under different thermal scenarios showed that colder temperatures (0.1–10.7°C, Canyon Creek) produced higher growth than under the nominal or warm scenarios (2.0–15.3°C, Canyon Creek), as well as one additional tributary where size at annulus 2 or 3 (±2 SE) was comparable to the threshold established by adult steelhead below the dams (Big Beaver Creek, annulus 3).</p><h3 id=\"nafm10944-sec-1004-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>These results suggest Rainbow Trout growth is most limited by prey availability in the examined upper Skagit tributaries.</p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10944","usgsCitation":"Jensen, B.L., Johnson, R.C., Duda, J.J., Ostberg, C.O., Code, T.J., Mclean, J.H., Stenberg, K.D., Larsen, K., Hoy, M.S., and Beauchamp, D., 2023, Growth performance of Rainbow Trout in reservoir tributaries and implications for steelhead growth potential above Skagit River dams: North American Journal of Fisheries Management, v. 43, no. 5, p. 1427-1446, https://doi.org/10.1002/nafm.10944.","productDescription":"20 p.","startPage":"1427","endPage":"1446","ipdsId":"IP-147915","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":422838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Skagit River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.76,\n              49\n            ],\n            [\n              -121.335,\n              49\n            ],\n            [\n              -121.335,\n              48.5\n            ],\n            [\n              -120.76,\n              48.5\n            ],\n            [\n              -120.76,\n              49\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"43","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-10-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Jensen, Benjamin Lorenz 0000-0003-1199-973X","orcid":"https://orcid.org/0000-0003-1199-973X","contributorId":306036,"corporation":false,"usgs":true,"family":"Jensen","given":"Benjamin","email":"","middleInitial":"Lorenz","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Rachelle Carina 0000-0003-1480-4088","orcid":"https://orcid.org/0000-0003-1480-4088","contributorId":241962,"corporation":false,"usgs":true,"family":"Johnson","given":"Rachelle","email":"","middleInitial":"Carina","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ostberg, Carl O. 0000-0003-1479-8458","orcid":"https://orcid.org/0000-0003-1479-8458","contributorId":220731,"corporation":false,"usgs":true,"family":"Ostberg","given":"Carl","middleInitial":"O.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Code, Tessa Julianne 0000-0003-1481-020X","orcid":"https://orcid.org/0000-0003-1481-020X","contributorId":331687,"corporation":false,"usgs":true,"family":"Code","given":"Tessa","email":"","middleInitial":"Julianne","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mclean, Jonathan H 0000-0001-5940-3689","orcid":"https://orcid.org/0000-0001-5940-3689","contributorId":331688,"corporation":false,"usgs":true,"family":"Mclean","given":"Jonathan","email":"","middleInitial":"H","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stenberg, Karl D. 0000-0001-9802-2707 kstenberg@usgs.gov","orcid":"https://orcid.org/0000-0001-9802-2707","contributorId":3747,"corporation":false,"usgs":true,"family":"Stenberg","given":"Karl","email":"kstenberg@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Larsen, Kimberly 0000-0001-7978-2452","orcid":"https://orcid.org/0000-0001-7978-2452","contributorId":202172,"corporation":false,"usgs":true,"family":"Larsen","given":"Kimberly","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888480,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hoy, Marshal S. 0000-0003-2828-9697","orcid":"https://orcid.org/0000-0003-2828-9697","contributorId":220730,"corporation":false,"usgs":true,"family":"Hoy","given":"Marshal","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888481,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888482,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70249591,"text":"70249591 - 2023 - Dispersal of juvenile Barrow’s goldeneyes (Bucephala islandica) mirrors that of breeding adults","interactions":[],"lastModifiedDate":"2023-10-19T13:25:00.109235","indexId":"70249591","displayToPublicDate":"2023-10-12T07:00:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Dispersal of juvenile Barrow’s goldeneyes (<i>Bucephala islandica</i>) mirrors that of breeding adults","title":"Dispersal of juvenile Barrow’s goldeneyes (Bucephala islandica) mirrors that of breeding adults","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Barrow’s goldeneyes across western North America have been shown to have a high degree of subpopulation independence using several data types. However, evidence for structured populations based on mitochondrial DNA, band recoveries, and tracking of adults is discordant with evidence from autosomal DNA. We used satellite tracking data from both juveniles and adults marked on natal and breeding grounds, respectively, in British Columbia, Canada to evaluate the hypothesis that male-biased juvenile dispersal maintains genetic panmixia of Pacific Barrow’s goldeneyes otherwise structured by migratory movements and high winter and breeding site fidelity of adults. We found that juvenile males traveled to overwintering sites located within the range of the overwintering sites of juvenile females, adult males, and adult females. Juvenile males migrated at the same time, travelled the same distance when moving between natal and overwintering sites, and had the same winter dispersion as juvenile females. Although juveniles did not travel with attendant females, all juveniles overwintered within the wintering range of adults. We tracked some juveniles into the following spring/summer and even second winter. Prospecting juveniles of both sexes travelled from their wintering grounds to potential breeding sites in the proximity of Riske Creek and within the bounds of the breeding locations used by adults. Juveniles tracked for more than a year also showed relatively high winter site fidelity. Because Barrow’s goldeneyes pair on wintering grounds, our tracking data are not consistent with the hypothesis that male-biased juvenile dispersal explains the genetic structure in the mitochondrial DNA and panmixia in the autosomal DNA of Barrow’s goldeneye. We suggest that uncommon or episodic dispersal of males might be enough to homogenize autosomal DNA but is unlikely to influence demographic population structure relevant to contemporary population management.</p></div></div>","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-023-00423-z","usgsCitation":"Forstner, T., Boyd, S., Esler, D., and Green, D., 2023, Dispersal of juvenile Barrow’s goldeneyes (Bucephala islandica) mirrors that of breeding adults: Movement Ecology, v. 11, 62, 11 p., https://doi.org/10.1186/s40462-023-00423-z.","productDescription":"62, 11 p.","ipdsId":"IP-152532","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":441891,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1186/s40462-023-00423-z","text":"Publisher Index Page"},{"id":421954,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -130.9100680281842,\n              53.167292643909775\n            ],\n            [\n              -130.9100680281842,\n              47.0335576933322\n            ],\n            [\n              -118.34170865318431,\n              47.0335576933322\n            ],\n            [\n              -118.34170865318431,\n              53.167292643909775\n            ],\n            [\n              -130.9100680281842,\n              53.167292643909775\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Forstner, Tess","contributorId":330968,"corporation":false,"usgs":false,"family":"Forstner","given":"Tess","email":"","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":886352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyd, Sean","contributorId":76672,"corporation":false,"usgs":false,"family":"Boyd","given":"Sean","affiliations":[{"id":6962,"text":"Science and Technology Branch, Environment Canada","active":true,"usgs":false}],"preferred":false,"id":886353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":true,"id":886354,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Green, David","contributorId":167789,"corporation":false,"usgs":false,"family":"Green","given":"David","affiliations":[],"preferred":false,"id":886355,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70251562,"text":"70251562 - 2023 - Evaluation of portable Raman spectroscopic analysis for source-rock thermal maturity assessments on bulk crushed rock","interactions":[],"lastModifiedDate":"2024-02-16T12:43:20.124591","indexId":"70251562","displayToPublicDate":"2023-10-12T06:40:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of portable Raman spectroscopic analysis for source-rock thermal maturity assessments on bulk crushed rock","docAbstract":"<p>This study presents a simplified method and empirical relationships for determining organic matter thermal maturity using a portable Raman system equipped with a 785 nm laser, for analysis of crushed, whole-rock samples. Suites of rocks represented by shale and coal samples with various mineralogical composition, thermal maturity, and total organic carbon (TOC) were used to test the method and build correlations between Raman band separation (RBS) values and traditional thermal maturity indicators, organic matter reflectance (Ro), and programmed temperature pyrolysis (Tmax) values. A set of disparate shale samples, where both vitrinite and solid bitumen reflectance values were reported, have Ro values that range from 0.40 to 4.62%. Above 3.35% Ro, the corresponding RBS values plateau at ∼290 cm−1, thus correlations were evaluated with a linear regression (R2 = 0.96) between 0.40 and 3.35% Ro. Shale samples with Ro &lt; 2% and Tmax &lt; 551 were also used to correlate Tmax and RBS, yielding a linear correlation with an R2 of 0.94. For the coal data set, Ro values range from 1.21 to 4.08% and correlated RBS values plateau at ∼250 cm−1 above Ro = 3.0%, suggesting its correlative application below this maturity level. Several sample preparation methods were tested on cuttings material and standard deviation values for RBS were minimized by washing, drying, and hand crushing the material to pass through a 40-mesh sieve, although less preparation can still yield reliable results. The high degrees of correlation between whole-rock RBS data and two thermal maturity indicators demonstrate the utility of this approach for generating source rock thermal maturity data from minimally processed, whole-rock samples which could easily be applied in field or laboratory settings.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2023.104374","usgsCitation":"Stokes, M., Jubb, A., Hackley, P.C., Birdwell, J.E., Barnhart, E.P., Scott, C., Shelton, J., Sanders, M.M., and Hatcherian, J.J., 2023, Evaluation of portable Raman spectroscopic analysis for source-rock thermal maturity assessments on bulk crushed rock: International Journal of Coal Geology, v. 279, 104374, https://doi.org/10.1016/j.coal.2023.104374.","productDescription":"104374","ipdsId":"IP-157149","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science 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