{"pageNumber":"104","pageRowStart":"2575","pageSize":"25","recordCount":185258,"records":[{"id":70269934,"text":"70269934 - 2025 - Responses of larval fish and zooplankton to whole-lake 2,4-D herbicide treatments used to control Eurasian watermilfoil in northern Wisconsin lakes","interactions":[],"lastModifiedDate":"2025-08-07T14:58:32.388642","indexId":"70269934","displayToPublicDate":"2025-03-25T07:47:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Responses of larval fish and zooplankton to whole-lake 2,4-D herbicide treatments used to control Eurasian watermilfoil in northern Wisconsin lakes","docAbstract":"<p><span>In North America, Eurasian watermilfoil&nbsp;</span><i>Myriophyllum spicatum</i><span>&nbsp;is one of the most widespread non-native aquatic plant species in freshwater ecosystems. Applications of 2,4-dichlorophenoxyacetic acid (2,4-D) herbicides are often utilized to control Eurasian watermilfoil. Herbicide applications may have unintended effects on non-target organisms like zooplankton and fish, but these effects are poorly understood. Our objectives were to determine if whole-lake 2,4-D herbicide treatments (epilimnetic target rate = 0.3&nbsp;ppm) used to control Eurasian watermilfoil affected (1) density, diversity, and size of zooplankton and (2) density, diversity, and growth of larval fishes in three northern Wisconsin lakes when compared to trends observed in three untreated reference lakes. Average peak concentrations of 2,4-D following applications ranged from 0.152 to 0.257&nbsp;ppm. We found no statistically significant evidence that the applications influenced the zooplankton and larval fish metrics we examined, but subtle responses to the herbicides may not have been detected given the inherent variation in our response metrics. Additional replication and research are needed to assess responses to higher concentrations and repeated applications over time and to document responses across a broader range of lake types and fish communities.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s10750-024-05698-w","usgsCitation":"Rydell, N., VanDeHey, J., Dembkowski, D., Gauthier, K., Van Egeren, S., Kubitz, J.A., Naumann, T.R., and Isermann, D.A., 2025, Responses of larval fish and zooplankton to whole-lake 2,4-D herbicide treatments used to control Eurasian watermilfoil in northern Wisconsin lakes: Hydrobiologia, v. 852, p. 2769-2786, https://doi.org/10.1007/s10750-024-05698-w.","productDescription":"18 p.","startPage":"2769","endPage":"2786","ipdsId":"IP-155041","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Oneida County, Vilas County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.04240173435862,\n              46.27854767707535\n            ],\n            [\n              -90.04240173435862,\n              45.62776439323994\n            ],\n            [\n              -89.31466895402599,\n              45.62776439323994\n            ],\n            [\n              -89.31466895402599,\n              46.27854767707535\n            ],\n            [\n              -90.04240173435862,\n              46.27854767707535\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"852","noUsgsAuthors":false,"publicationDate":"2025-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Rydell, Nicholas","contributorId":359357,"corporation":false,"usgs":false,"family":"Rydell","given":"Nicholas","affiliations":[{"id":675,"text":"Wisconsin Cooperative Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":945177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"VanDeHey, Justin","contributorId":191463,"corporation":false,"usgs":false,"family":"VanDeHey","given":"Justin","affiliations":[],"preferred":false,"id":945178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dembkowski, Daniel","contributorId":348816,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":945179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gauthier, Kevin","contributorId":359358,"corporation":false,"usgs":false,"family":"Gauthier","given":"Kevin","affiliations":[],"preferred":false,"id":945180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Egeren, Scott","contributorId":359359,"corporation":false,"usgs":false,"family":"Van Egeren","given":"Scott","affiliations":[],"preferred":false,"id":945181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kubitz, Jody A.","contributorId":175430,"corporation":false,"usgs":false,"family":"Kubitz","given":"Jody","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":945182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Naumann, Terry R.","contributorId":61652,"corporation":false,"usgs":true,"family":"Naumann","given":"Terry","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":945183,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":944988,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70265266,"text":"70265266 - 2025 - No magmatic driving force for Europan sea-floor volcanism","interactions":[],"lastModifiedDate":"2025-05-28T14:55:26.641908","indexId":"70265266","displayToPublicDate":"2025-03-24T15:17:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6448,"text":"Nature Astronomy","active":true,"publicationSubtype":{"id":10}},"title":"No magmatic driving force for Europan sea-floor volcanism","docAbstract":"The internal ocean of Jupiter’s moon Europa is thought to be a prime candidate for hosting extraterrestrial life. Europa’s silicate interior may contribute to habitability via the generation of reactants through hydrothermal activity, serpentinization, or other geological processes occurring on or just below Europa’s seafloor. However, silicate melting is thought to occur at >100 km depth in Europa’s mantle and it is unknown if this magma is able to penetrate and travel through the moon’s likely thick, brittle lithosphere to erupt at the seafloor. Here we combine previous modeling approaches to Europan interior melt generation and lithospheric dyke transport to show that Europan seafloor volcanism is strongly inhibited by its lithosphere. The low stress state of the Europan interior hinders the ability of dykes to penetrate through the lithosphere. Should dykes form, they penetrate <5% of the 200–250 km-thick lithosphere. Low mantle melt fractions (3–5%) drive sluggish pore-space magma flow, leading to dyke influxes 10,000 times lower than that necessary for seafloor eruption. These results strongly suggest that models of Europan habitability reliant on present-day volcanism at its seafloor are implausible.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41550-025-02508-8","usgsCitation":"Green, A., Elder, C., Bland, M., Tackley, P., and Byrne, P., 2025, No magmatic driving force for Europan sea-floor volcanism: Nature Astronomy, v. 9, p. 640-649, https://doi.org/10.1038/s41550-025-02508-8.","productDescription":"10 p.","startPage":"640","endPage":"649","ipdsId":"IP-163125","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":484178,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Europa","volume":"9","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Green, A.P.","contributorId":352969,"corporation":false,"usgs":false,"family":"Green","given":"A.P.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":932638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elder, Catherine","contributorId":331017,"corporation":false,"usgs":false,"family":"Elder","given":"Catherine","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":932627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bland, Michael Thomas 0000-0001-5543-1519","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":352963,"corporation":false,"usgs":true,"family":"Bland","given":"Michael Thomas","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":932628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tackley, Paul","contributorId":352966,"corporation":false,"usgs":false,"family":"Tackley","given":"Paul","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":932629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Byrne, Paul K.","contributorId":237950,"corporation":false,"usgs":false,"family":"Byrne","given":"Paul K.","affiliations":[{"id":47656,"text":"Planetary Research Group, Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":932630,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70264759,"text":"fs20253006 - 2025 - Fiber-optic distributed temperature sensing of hydrologic processes—Diverse deployments and new applications by the U.S. Geological Survey","interactions":[],"lastModifiedDate":"2025-03-25T13:57:23.669017","indexId":"fs20253006","displayToPublicDate":"2025-03-24T14:45:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3006","displayTitle":"Fiber-Optic Distributed Temperature Sensing of Hydrologic Processes—Diverse Deployments and New Applications by the U.S. Geological Survey","title":"Fiber-optic distributed temperature sensing of hydrologic processes—Diverse deployments and new applications by the U.S. Geological Survey","docAbstract":"<p>Fiber-optic distributed temperature sensing instruments harness the temperature-dependent properties of glass to measure temperature continuously along optical fibers by using precise pulses of laser light. In the mid-2000s, this technology was refined for environmental monitoring purposes such as snowpack-air exchange, groundwater/surface-water exchange, and lake-water stratification. Fiber-optic distributed temperature sensing has revealed unprecedented details about preferential flow processes; however, the method is labor intensive and requires specific training, resulting in limited use by the broader water community. With the ongoing national implementation of the U.S. Geological Survey Next Generation Water Observing System, there has been renewed interest in harnessing the unique spatiotemporal monitoring capabilities of fiber-optic distributed temperature sensing. This fact sheet briefly describes this technology, highlights uses by the U.S. Geological Survey, and discusses current applications and future opportunities.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253006","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"Briggs, M.A., Rey, D.M., Opatz, C.C., Terry, N.C., Newman, C.P., Gruhn, L.R., and Johnson, C.D., 2025, Fiber-optic distributed temperature sensing of hydrologic processes—Diverse deployments and new applications by the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2025–3006, 6 p., https://doi.org/10.3133/fs20253006.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-163064","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":483673,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3006/coverthb.jpg"},{"id":483674,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3006/fs20253006.pdf","text":"Report","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3006 PDF"},{"id":483675,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253006/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3006 HTML"},{"id":483676,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3006/fs20253006.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2025-3006 XML"},{"id":483677,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3006/images/"}],"contact":"<p>Program Manager, <a href=\"https://www.usgs.gov/mission-areas/water-resources/science/next-generation-water-observing-system-ngwos\" data-mce-href=\"https://www.usgs.gov/mission-areas/water-resources/science/next-generation-water-observing-system-ngwos\">Next Generation Water Observing System</a><br>Water Resources Mission Area<br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>What Is Fiber-Optic Distributed Temperature Sensing, and How Has It Been Used by the U.S. Geological Survey?</li><li>Examples of FO–DTS Applied to Diverse Hydrologic Monitoring</li><li>Application to U.S. Geological Survey Hydrologic Monitoring Technology Testbeds</li><li>Opportunities for Broader Implementation of FO–DTS Monitoring</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2025-03-24","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":931552,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":931553,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Opatz, Chad C. 0000-0002-5272-0195 copatz@usgs.gov","orcid":"https://orcid.org/0000-0002-5272-0195","contributorId":167704,"corporation":false,"usgs":true,"family":"Opatz","given":"Chad C.","email":"copatz@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Terry, Neil C. 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","middleInitial":"C.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":931555,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931556,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gruhn, Lance R. 0000-0002-7120-3003 lgruhn@usgs.gov","orcid":"https://orcid.org/0000-0002-7120-3003","contributorId":219710,"corporation":false,"usgs":true,"family":"Gruhn","given":"Lance","email":"lgruhn@usgs.gov","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931557,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Carole D. 0000-0001-6941-1578","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":245365,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":931558,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70265967,"text":"70265967 - 2025 - Assessing earthquake risks to lifeline infrastructure systems in the United States","interactions":[],"lastModifiedDate":"2025-04-22T16:01:31.164657","indexId":"70265967","displayToPublicDate":"2025-03-24T10:58:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21204,"text":"International Journal of Critical Infrastructure Protection","active":true,"publicationSubtype":{"id":10}},"title":"Assessing earthquake risks to lifeline infrastructure systems in the United States","docAbstract":"<p><span>The security and economic stability of the United States rely heavily on robust lifeline infrastructure systems and yet the risks to such systems are seldom quantified at the national scale. For example, while earthquake risks to buildings in the United States have been investigated at the national scale regularly, such risks to gas pipelines have rarely been investigated nationally. In this paper, we use examples from two critical infrastructure sectors to demonstrate (1) the nature of earthquake risks to lifeline infrastructure systems, (2) complexities involved in regional seismic risk assessments, and (3) how such risks change with time. We found that bridge risks can be underestimated by at least 64 % when viewed from repair costs instead of traffic demands and that regional risks can be underestimated by 19 % when spatial correlations of ground motion are ignored. Further, exceedance of traffic demand can be 50 times more likely to occur when viewed at the regional scale than when viewed at an individual bridge. Similarly, exceedance of repairs can be 180 times more likely to occur when viewed at the pipeline network level than at a segment-specific level. Finally, sensitivity analyses with the 2018 and 2023 USGS National Seismic Hazard Models indicate an increase in bridge risk of at least 24 % and an increase in exposed gas pipeline mileage of 43 %. The evolution of risks, complexities involved in assessments, and limited resources jointly underscore the need for more routine updates to nationwide seismic risk assessments of lifeline systems in the United States.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijcip.2025.100758","usgsCitation":"Kwong, N.S., and Jaiswal, K.S., 2025, Assessing earthquake risks to lifeline infrastructure systems in the United States: International Journal of Critical Infrastructure Protection, v. 49, 100758, https://doi.org/10.1016/j.ijcip.2025.100758.","productDescription":"100758","ipdsId":"IP-170667","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":484841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":934185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":934186,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70266111,"text":"70266111 - 2025 - The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models","interactions":[],"lastModifiedDate":"2025-04-25T15:31:50.116638","indexId":"70266111","displayToPublicDate":"2025-03-24T10:29:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21214,"text":"Peer Community Journal","active":true,"publicationSubtype":{"id":10}},"title":"The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models","docAbstract":"<p><span>Survival is a key life history parameter that can inform management decisions and basic life history research. Because true survival is often confounded with emigration from the study area, many studies are forced to estimate apparent survival (i.e., probability of surviving and remaining inside the study area), which can be much lower than true survival for highly mobile species.&nbsp; One method for estimating true survival is the Barker joint live-recapture/live-resight (JLRLR) model, which combines capture data from a study area (hereafter the ‘capture site’) with resighting data from a broader geographic area. This model assumes that live resights occur throughout the entire area where animals can disperse to and this assumption is often not met in practice. Here we use simulation to evaluate survival bias from a JLRLR model under study design scenarios that differ in the site selection for resights: global, random, fixed including the capture site, and fixed excluding the capture site. Simulation results indicate that fixed designs that included the capture site showed negative survival bias, whereas fixed designs that excluded the capture site exhibited positive survival bias. The magnitude of the bias was dependent on movement and survival, where scenarios with high survival and frequent movement had minimal bias. In an effort to help minimize bias, we developed a multistate version of the JLRLR and demonstrated reductions in survival bias compared to the single-state version for most designs. Our results suggest minimizing bias can be accomplished by: 1) using a random resight design when feasible if global sampling is not possible, 2) using the multistate JLRLR model when appropriate, 3) including the capture site in the resight sampling frame when possible, and 4) reporting survival as apparent survival if fixed sites are used for resight with the single state JLRLR model.</span></p>","language":"English","publisher":"PeerJ","doi":"10.24072/pcjournal.533","usgsCitation":"Dzul, M.C., Yackulic, C., and Kendall, W.L., 2025, The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models: Peer Community Journal, v. 5, e34, 24 p., https://doi.org/10.24072/pcjournal.533.","productDescription":"e34, 24 p.","ipdsId":"IP-158705","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":487775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.24072/pcjournal.533","text":"Publisher Index Page"},{"id":485061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":934620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70265081,"text":"70265081 - 2025 - Planting seeds for thriving data management","interactions":[],"lastModifiedDate":"2025-04-01T15:28:49.893757","indexId":"70265081","displayToPublicDate":"2025-03-24T10:27:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7602,"text":"Eos, American Geophysical Union","active":true,"publicationSubtype":{"id":10}},"title":"Planting seeds for thriving data management","docAbstract":"The volumes and varieties of data coming from all types of scientific instrumentation around the globe and beyond are rapidly growing. To reuse and capitalize on these data effectively, scientists must be able to share and access them efficiently, which requires the data to be well managed. \nMany scientists intuit that research data management (RDM) done well does not mean using dusty USB drives or aging laptops for storage. Yet the path to strong data management is not always clear. How is RDM done? Who does it? For science to advance, we need to bolster cyberinfrastructure and human capacity to ensure that the data being collected are reusable by both humans and machines.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025EO250109","usgsCitation":"Benson, A., Beaulieu, S., Bishop, B., Diggs, S., and Formel, S., 2025, Planting seeds for thriving data management: Eos, American Geophysical Union, HTML Document, https://doi.org/10.1029/2025EO250109.","productDescription":"HTML Document","ipdsId":"IP-172647","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":488673,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025eo250109","text":"Publisher Index Page"},{"id":484072,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Abigail 0000-0002-4391-107X","orcid":"https://orcid.org/0000-0002-4391-107X","contributorId":352933,"corporation":false,"usgs":false,"family":"Benson","given":"Abigail","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":932501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beaulieu, Stace 0000-0002-2609-5453","orcid":"https://orcid.org/0000-0002-2609-5453","contributorId":352935,"corporation":false,"usgs":false,"family":"Beaulieu","given":"Stace","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":932502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bishop, Bradley Wade 0000-0002-5022-2707","orcid":"https://orcid.org/0000-0002-5022-2707","contributorId":352937,"corporation":false,"usgs":false,"family":"Bishop","given":"Bradley Wade","affiliations":[{"id":63836,"text":"University of Tennessee, Knoxville","active":true,"usgs":false}],"preferred":false,"id":932503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diggs, Stephen C. 0000-0003-3814-6104","orcid":"https://orcid.org/0000-0003-3814-6104","contributorId":352939,"corporation":false,"usgs":false,"family":"Diggs","given":"Stephen C.","affiliations":[{"id":84309,"text":"University of California Office of the President","active":true,"usgs":false}],"preferred":false,"id":932504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Formel, Stephen Killfoile 0000-0001-7418-1244","orcid":"https://orcid.org/0000-0001-7418-1244","contributorId":338237,"corporation":false,"usgs":true,"family":"Formel","given":"Stephen Killfoile","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":932500,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70265072,"text":"70265072 - 2025 - Consideration of grid cell size to represent stream network geometry for the conterminous United States","interactions":[],"lastModifiedDate":"2025-05-12T15:41:31.487096","indexId":"70265072","displayToPublicDate":"2025-03-24T09:17:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Consideration of grid cell size to represent stream network geometry for the conterminous United States","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13484","usgsCitation":"Fleming, B.J., Belitz, K., and Killian, C.D., 2025, Consideration of grid cell size to represent stream network geometry for the conterminous United States: Groundwater, v. 63, no. 3, p. 301-305, https://doi.org/10.1111/gwat.13484.","productDescription":"5 p.","startPage":"301","endPage":"305","ipdsId":"IP-164331","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":490113,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13484","text":"Publisher Index Page"},{"id":484060,"rank":1,"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        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       [\n                -120.62286,\n                34.60855\n              ],\n              [\n                -120.74433,\n                35.15686\n              ],\n              [\n                -121.71457,\n                36.16153\n              ],\n              [\n                -122.54747,\n                37.55176\n              ],\n              [\n                -122.51201,\n                37.78339\n              ],\n              [\n                -122.95319,\n                38.11371\n              ],\n              [\n                -123.7272,\n                38.95166\n              ],\n              [\n                -123.86517,\n                39.76699\n              ],\n              [\n                -124.39807,\n                40.3132\n              ],\n              [\n                -124.17886,\n                41.14202\n              ],\n              [\n                -124.2137,\n                41.99964\n              ],\n              [\n                -124.53284,\n                42.76599\n              ],\n              [\n                -124.14214,\n                43.70838\n              ],\n              [\n                -124.02053,\n                44.6159\n              ],\n              [\n                -123.89893,\n                45.52341\n              ],\n              [\n                -124.07963,\n                46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\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":"63","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Killian, Courtney D. 0000-0002-2137-2722","orcid":"https://orcid.org/0000-0002-2137-2722","contributorId":213990,"corporation":false,"usgs":true,"family":"Killian","given":"Courtney","email":"","middleInitial":"D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932469,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70265015,"text":"70265015 - 2025 - Bayesian calibration of the 40K decay scheme with implications for 40K-based geochronology","interactions":[],"lastModifiedDate":"2025-04-28T15:14:09.946352","indexId":"70265015","displayToPublicDate":"2025-03-24T09:11:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Bayesian calibration of the <sup>40</sup>K decay scheme with implications for <sup>40</sup>K-based geochronology","title":"Bayesian calibration of the 40K decay scheme with implications for 40K-based geochronology","docAbstract":"<p><span>The K/Ar and&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar geochronometers are based on the naturally occurring radionuclide&nbsp;</span><sup>40</sup><span>K. Their precision and accuracy are limited by uncertainties on the&nbsp;</span><sup>40</sup><span>K decay constants and, in the case of the&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar geochronometer, the isotopic composition of neutron fluence monitors. To address these limitations, we introduce a Bayesian calibration of the&nbsp;</span><sup>40</sup><span>K decay scheme. We formulate robust priors for all model parameters including partial&nbsp;</span><sup>40</sup><span>K decay constants,&nbsp;</span><sup>238</sup><span>U and&nbsp;</span><sup>235</sup><span>U decay constants, and age offset parameters to account for phenomena that can perturb apparent U-Pb and&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar ages. We then harness a set of complementary&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar,&nbsp;</span><sup>238</sup><span>U/</span><sup>206</sup><span>Pb, and&nbsp;</span><sup>235</sup><span>U/</span><sup>207</sup><span>Pb data from well- characterized geological samples with ages from 1.919 ka to 2000 Ma to derive Bayesian estimates of the&nbsp;</span><sup>40</sup><span>K decay constants. Posterior values for the partial&nbsp;</span><sup>40</sup><span>K decay constants are&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><msup is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3B2;</mi></mrow><mo is=&quot;true&quot;>-</mo></msup></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>β</sub>-</span></span></span><span>= (4.9252&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.0054)&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−10</sup><span>&nbsp;yr</span><sup>−1</sup><span>,&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><msup is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3B2;</mi></mrow><mo is=&quot;true&quot;>+</mo></msup></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>β</sub>+</span></span></span><span>&nbsp;= (5.6658&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-5-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.1543)&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-6-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−15</sup><span>&nbsp;yr</span><sup>−1</sup><span>,&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-7-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><msup is=&quot;true&quot;><mrow is=&quot;true&quot;><mi mathvariant=&quot;italic&quot; is=&quot;true&quot;>EC</mi></mrow><mrow is=&quot;true&quot;><mo is=&quot;true&quot;>&amp;#x2217;</mo></mrow></msup></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>EC0</sub></span></span></span><span>&nbsp;= (5.7404&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-8-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.0053)&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-9-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−11</sup><span>&nbsp;yr</span><sup>−1</sup><span>, and&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-10-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi mathvariant=&quot;italic&quot; is=&quot;true&quot;>EC</mi></mrow><mn is=&quot;true&quot;>0</mn></msub></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>EC0</sub></span></span></span><span>= (4.9060&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-11-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.2942)</span><span class=\"math\"><span id=\"MathJax-Element-12-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−13</sup><span>&nbsp;yr</span><sup>−1</sup><span>&nbsp;(uncertainties reported at the 68 % (1&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-13-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi is=&quot;true&quot;>&amp;#x3C3;</mi></math>\"><span class=\"MJX_Assistive_MathML\">σ</span></span></span><span>) credible interval). These combine to a total&nbsp;</span><sup>40</sup><span>K decay constant&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-14-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><mrow is=&quot;true&quot;><mi mathvariant=&quot;italic&quot; is=&quot;true&quot;>tot</mi></mrow></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>tot</sub></span></span></span><span>= (5.5042&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-15-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.0054)</span><span class=\"math\"><span id=\"MathJax-Element-16-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−10</sup><span>&nbsp;yr</span><sup>−1</sup><span>. Model estimates of the&nbsp;</span><sup>238</sup><span>U and&nbsp;</span><sup>235</sup><span>U decay constants are statistically indistinguishable from those reported by&nbsp;</span><span class=\"anchor-text-container\"><span class=\"anchor-text\">Jaffey</span></span><span class=\"anchor-text-container\"><span class=\"anchor-text\"> et al. (1971)</span></span><span>. Posterior values of the&nbsp;</span><sup>40</sup><span>K decay constants and the&nbsp;</span><sup>40</sup><span>Ar*/</span><sup>40</sup><span>K isotopic composition of Fish Canyon sanidine (FCs) define a K/Ar FCs age of 28.183&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-17-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.017 Ma (1&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-18-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi is=&quot;true&quot;>&amp;#x3C3;</mi></math>\"><span class=\"MJX_Assistive_MathML\">σ</span></span></span><span>). Significantly, Bayesian calibrated&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar ages align with astronomically tuned ages throughout the Cenozoic and with&nbsp;</span><sup>238</sup><span>U/</span><sup>206</sup><span>Pb and&nbsp;</span><sup>235</sup><span>U/</span><sup>207</sup><span>Pb ages in the Mesozoic, Paleozoic, and Proterozoic, as well as having comparable precision to the&nbsp;</span><sup>238</sup><span>U/</span><sup>206</sup><span>Pb method. Thus, Bayesian calibration of the 40 K decay scheme and the K/Ar age of FCs reconciles the&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar, U-Pb, and astronomical chronometers.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2025.03.024","usgsCitation":"Carter, J., Hasler, C., Fuentes, A., Tholt, A., Morgan, L.E., and Renne, P.R., 2025, Bayesian calibration of the 40K decay scheme with implications for 40K-based geochronology: Geochimica et Cosmochimica Acta, v. 397, p. 149-163, https://doi.org/10.1016/j.gca.2025.03.024.","productDescription":"14 p.","startPage":"149","endPage":"163","ipdsId":"IP-172690","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":483986,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"397","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Jack N.","contributorId":317971,"corporation":false,"usgs":false,"family":"Carter","given":"Jack N.","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":932300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hasler, Caroline","contributorId":352885,"corporation":false,"usgs":false,"family":"Hasler","given":"Caroline","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":932301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuentes, Anthony","contributorId":352886,"corporation":false,"usgs":false,"family":"Fuentes","given":"Anthony","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":932302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tholt, Andrew","contributorId":352887,"corporation":false,"usgs":false,"family":"Tholt","given":"Andrew","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":932303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":932304,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Renne, Paul R. 0000-0003-1769-5235","orcid":"https://orcid.org/0000-0003-1769-5235","contributorId":229577,"corporation":false,"usgs":false,"family":"Renne","given":"Paul","email":"","middleInitial":"R.","affiliations":[{"id":37390,"text":"Department of Earth and Planetary Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":932305,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70264851,"text":"70264851 - 2025 - An enhanced national-scale urban tree canopy cover dataset for the United States","interactions":[],"lastModifiedDate":"2025-03-26T15:27:52.723666","indexId":"70264851","displayToPublicDate":"2025-03-24T08:13:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"An enhanced national-scale urban tree canopy cover dataset for the United States","docAbstract":"<p><span>Moderate-resolution (30-m) national map products have limited capacity to represent fine-scale, heterogeneous urban forms and processes, yet improvements from incorporating higher resolution predictor data remain rare. In this study, we applied random forest models to high-resolution land cover data for 71 U.S. urban areas, moderate-resolution National Land Cover Database (NLCD) Tree Canopy Cover (TCC), and additional explanatory climatic and structural data to develop an enhanced urban TCC dataset for U.S. urban areas. With a coefficient of determination (R</span><sup>2</sup><span>) of 0.747, our model estimated TCC within 3% for 62 urban areas and added 13.4% more city-level TCC on average, compared to the native NLCD TCC product. Cross validations indicated model stability suitable for building a national-scale TCC dataset (median R</span><sup>2</sup><span>&nbsp;of 0.752, 0.675, and 0.743 for 1,000-fold cross validation, urban area leave-one-out cross validation, and cross validation by Census block group median year built, respectively). Additionally, our model code can be used to improve moderate-resolution TCC in other parts of the world where high-resolution land cover data have limited spatiotemporal availability.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41597-025-04816-0","usgsCitation":"Corro, L.M., Bagstad, K.J., Heris, M., Ibsen, P.C., Schleeweis, K., Diffendorfer, J., Troy, A., Megown, K., and O'Neil-Dunne, J., 2025, An enhanced national-scale urban tree canopy cover dataset for the United States: Scientific Data, v. 12, 490, 14 p., https://doi.org/10.1038/s41597-025-04816-0.","productDescription":"490, 14 p.","ipdsId":"IP-166001","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":488662,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-025-04816-0","text":"Publisher Index Page"},{"id":483878,"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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Austin","contributorId":139102,"corporation":false,"usgs":false,"family":"Troy","given":"Austin","email":"","affiliations":[{"id":12652,"text":"University of Colorado-Denver","active":true,"usgs":false}],"preferred":false,"id":932053,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Megown, Kevin","contributorId":140260,"corporation":false,"usgs":false,"family":"Megown","given":"Kevin","email":"","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":932054,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O'Neil-Dunne, Jarlath P.M.","contributorId":352303,"corporation":false,"usgs":false,"family":"O'Neil-Dunne","given":"Jarlath P.M.","affiliations":[{"id":84167,"text":"Spatial Analysis Laboratory, Rubenstein School of Environment & Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":932055,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70265863,"text":"70265863 - 2025 - Properties of solid bitumen formed during hydrous, anhydrous, and brine pyrolysis of oil shale: Implications for solid bitumen reflectance in source-rock reservoirs","interactions":[],"lastModifiedDate":"2025-04-17T15:18:25.844259","indexId":"70265863","displayToPublicDate":"2025-03-24T08:13:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Properties of solid bitumen formed during hydrous, anhydrous, and brine pyrolysis of oil shale: Implications for solid bitumen reflectance in source-rock reservoirs","docAbstract":"<p><span>Solid bitumen reflectance (BR</span><sub>o</sub><span>&nbsp;in %) is widely used as a thermal maturity proxy in source-rock reservoirs, yet solid bitumen texture and physical attributes may be affected by varying environmental constraints during its formation, e.g., water saturation, mineral catalysis, or salinity. Herein we investigated the development of solid bitumen properties during artificial maturation using three diverse (lacustrine to marine) oil shale samples containing abundant amorphous H-rich sedimentary organic matter (bituminite). The oil shales were treated via pyrolysis (320&nbsp;°C, 72&nbsp;h) using hydrous, anhydrous, and brine conditions, causing the development of a newly formed solid bitumen in the experiment residues from the thermal conversion of bituminite. The properties of the newly formed solid bitumen then were evaluated via geochemical screening tests, optical and electron microscopy, and infrared spectroscopy. Experimental residues also were treated via solvent extraction, allowing characterization of the effects of extraction on solid bitumen. Results showed that bituminite with higher resin and asphaltene components evolved to a solid bitumen with higher reflectance (as a percentage of the original value) when exposed to the same heat treatment, relative to bituminite with higher saturate and aromatic components. Aromatization of solid bitumen also was generally more pronounced in the presence of deionized water relative to anhydrous conditions, supporting prior observations. These results suggest the compositions of primary sedimentary organic matter, and the local concentration of water, affect the development of solid bitumen during thermal advance, potentially explaining the origin of multiple solid bitumen populations with varying reflectance in source-rock reservoir samples or in a single microscope field. Experiments using brine were inconclusive regarding enhanced/decreased aromatization, which could be attributed to the salinities of the brines used in the tests. Extraction of residues caused a consistent increase in BR</span><sub>o</sub><span>&nbsp;values, suggesting that migrating or expelled oils could cause an increase in BR</span><sub>o</sub><span>&nbsp;via natural solvation and absent an increase in temperature. This work provides insights into the development and evolution of BR</span><sub>o</sub><span>&nbsp;in source-rock reservoirs as a function of the composition of the original bituminite and changing environmental conditions, with potentially broad application for petroleum prospecting and resource estimation.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2025.106365","usgsCitation":"Hackley, P.C., Birdwell, J.E., and McAleer, R.J., 2025, Properties of solid bitumen formed during hydrous, anhydrous, and brine pyrolysis of oil shale: Implications for solid bitumen reflectance in source-rock reservoirs: Applied Geochemistry, v. 185, 106365, 19 p., https://doi.org/10.1016/j.apgeochem.2025.106365.","productDescription":"106365, 19 p.","ipdsId":"IP-170606","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":488282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70265612,"text":"70265612 - 2025 - Ranking river basins for stream temperature research and monitoring in the contiguous United States","interactions":[],"lastModifiedDate":"2025-04-14T16:30:55.176106","indexId":"70265612","displayToPublicDate":"2025-03-23T09:24:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Ranking river basins for stream temperature research and monitoring in the contiguous United States","docAbstract":"There is a need to prioritize research and data collection in river basins by integrating information from environmental, ecological, and socioeconomic datasets to maintain acceptable water quality for human uses and ecosystem health. Multiple anthropogenic and natural stressors are responsible for driving changes in stream temperatures that can alter ecosystems and degrade water quality. These stressors are variable spatially and temporally, which can be challenging for prioritizing monitoring and research. In this study, an evaluation of variables related to stream temperature was performed for 163 candidate basins of the contiguous United States to highlight potential focal areas. Thirty variables were combined in six components: anthropogenic forcing, natural forcing, climate change, ecological sensitivity, socioeconomic sensitivity, and data availability. The components were incorporated into three themes: vulnerability of streams to thermal change, vulnerability of ecosystems, and vulnerability of communities. By evaluating each theme separately, patterns of vulnerability and potential resiliency were identified as well as consistency in ranks within the themes. For example, results of the national scale ranking indicated the Southern California Coastal basin (within California-Nevada region) was the highest-ranking priority in vulnerability of streams to thermal change and vulnerability of ecosystems. The analysis also identified vulnerable basins with gaps in monitoring. For example, the Missouri-Oahe basin (within the Northern High Plains region) was the highest-ranking priority for vulnerable communities with limitations in data availability. The ranking approach provides insight into basins that are resilient and are ideal candidates for monitoring and research.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2025.133163","usgsCitation":"Naranjo, R.C., Johnson, Z., Lucas, L., Baker, N.T., and Green, C., 2025, Ranking river basins for stream temperature research and monitoring in the contiguous United States: Journal of Hydrology, v. 658, 133163, 15 p., https://doi.org/10.1016/j.jhydrol.2025.133163.","productDescription":"133163, 15 p.","ipdsId":"IP-157155","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":488228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2025.133163","text":"Publisher Index Page"},{"id":484513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": 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,{"id":70265789,"text":"70265789 - 2025 - Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp Ctenopharyngodon idella in the Sandusky River","interactions":[],"lastModifiedDate":"2025-04-16T14:26:35.866043","indexId":"70265789","displayToPublicDate":"2025-03-23T09:18:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp <i>Ctenopharyngodon idella</i> in the Sandusky River","title":"Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp Ctenopharyngodon idella in the Sandusky River","docAbstract":"<p><span>Natural resources management is often concerned with conserving rare-native or controlling rare-invasive fishes. Informing and assessing conservation and control efforts frequently requires information from captures. When little is understood about spatial and temporal fish distributions, captures can be infrequent and costly. If successful management depends on effective management response, optimizing for efficiency may be the difference between success and failure. We compared per vessel hour capture efficiencies for invasive grass carp (</span><i>Ctenopharyngodon idella</i><span>) between two methods: electrofishing-only (electrofishing) and in combination with a trammel net (combination). Capture and effort information including 174 captures from 1853 capture attempts from 1706 total hours of effort in the Sandusky River, OH, USA from 2020–2023 was used to fit a generalized linear model. Captures were allowed to vary by river kilometer, month, and year to account for unequal capture rates and effort. Captures were offset by total vessel hours or the count of independent efforts to compare methods that prioritize detection at a single location (e.g., combination) to methods that prioritize exploiting more locations (e.g., electrofishing). Including trammel nets was intended to increase single site detection, but we found that electrofishing-only was at least 2.4x more efficient (catch per vessel hour) than when combined with a trammel net with no significant difference in catch per removal effort. Complex methods intended to increase single site detection may reduce the number of efforts completed. Therefore, overall capture efficiency and total capture numbers for rare fish may be increased through methods that prioritize per-hour efficiency.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2025.107344","usgsCitation":"Hunter, R., Qian, S.S., Fischer, J., Brown, R., Nathan, L., Dettmers, J., Roberts, J., Hilling, C.D., Acre, M.R., Mapes, R., Young, R., and Mayer, C.M., 2025, Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp Ctenopharyngodon idella in the Sandusky River: Fisheries Research, v. 285, 107344, 10 p., https://doi.org/10.1016/j.fishres.2025.107344.","productDescription":"107344, 10 p.","ipdsId":"IP-170360","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science 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L.","contributorId":241112,"corporation":false,"usgs":false,"family":"Fischer","given":"Jason L.","affiliations":[],"preferred":false,"id":933534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Ryan","contributorId":204846,"corporation":false,"usgs":false,"family":"Brown","given":"Ryan","affiliations":[{"id":36993,"text":"RAND","active":true,"usgs":false}],"preferred":false,"id":933535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nathan, Lucas","contributorId":236997,"corporation":false,"usgs":false,"family":"Nathan","given":"Lucas","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":933536,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dettmers, John M.","contributorId":341569,"corporation":false,"usgs":false,"family":"Dettmers","given":"John M.","affiliations":[{"id":7019,"text":"Great Lakes Fishery 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,{"id":70264814,"text":"70264814 - 2025 - New paleomagnetic constraints on the eruption timing, stratigraphy, and post-emplacement deformation of the Picture Gorge Basalt within the Columbia River Basalt Group","interactions":[],"lastModifiedDate":"2025-05-12T17:23:12.440493","indexId":"70264814","displayToPublicDate":"2025-03-23T08:08:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"New paleomagnetic constraints on the eruption timing, stratigraphy, and post-emplacement deformation of the Picture Gorge Basalt within the Columbia River Basalt Group","docAbstract":"The Picture Gorge Basalt (PGB) is part of the Miocene Columbia River Basalt Group (CRBG).\nThe PGB, which outcrops in eastern Oregon, is considered coincident in time with the voluminous Grande Ronde Basalt. New radiometric ages have expanded the age‐range of the PGB, suggesting it began erupting prior to the Steens Basalt to its south and continued until after cessation of the Grande Ronde Basalt eruptions, an interval of 1.5 Ma. However, the existing paleomagnetism of the PGB implies this eruption timeline is an overestimate. To reconcile the radiometric and paleomagnetic timescales for the PGB, we conducted a paleomagnetic study on sections of the PGB to construct a detailed, high‐quality magnetostratigraphy. Our data indicate the stratigraphically lowest lava flows in the PGB are of reversed polarity, revealing a new paleomagnetic transition with the PGB and a reversed (R)–normal (N)–reversed (R) sequence. This suggests one of two timeline possibilities for PGB volcanism: (a) eruptions began and during through CRBG polarity chrons R0–N0–R1, penecontemporaneous with Steens Basalt, or (b) eruptions began and persisted during CRBG polarity chrons R1–N1–R2. Our work supports a longer interval of PGB volcanism than was suggested by previous paleomagnetic data but is at odds with the suggestion that PGB eruptions lasted through the entire main CRBG. We favor a scenario wherein PGB eruptions begin with R0 and continue into the R1 paleomagnetic interval. The paleomagnetic results also record a ∼18° vertical‐axis rotation of east‐central Oregon after ∼16 Ma with respect to stable North America.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JB030728","usgsCitation":"Pivarunas, A.F., Avery, M.S., Hagstrum, J.T., Bennett, S.E., and Calvert, A.T., 2025, New paleomagnetic constraints on the eruption timing, stratigraphy, and post-emplacement deformation of the Picture Gorge Basalt within the Columbia River Basalt Group: Journal of Geophysical Research: Solid Earth, v. 130, no. 3, e2024JB030728, 22 p., https://doi.org/10.1029/2024JB030728.","productDescription":"e2024JB030728, 22 p.","ipdsId":"IP-164403","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":483811,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Picture Gorge Basalt","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.78165767306925,\n              45.33100443084706\n            ],\n            [\n              -120.78165767306925,\n              44.91041597686524\n            ],\n            [\n              -120.04351223849272,\n              44.91041597686524\n            ],\n            [\n              -120.04351223849272,\n              45.33100443084706\n            ],\n            [\n              -120.78165767306925,\n              45.33100443084706\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"130","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Pivarunas, Anthony Francis 0000-0002-0003-2059","orcid":"https://orcid.org/0000-0002-0003-2059","contributorId":301014,"corporation":false,"usgs":true,"family":"Pivarunas","given":"Anthony","email":"","middleInitial":"Francis","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":931816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Avery, Margaret Susan 0000-0002-8504-7072","orcid":"https://orcid.org/0000-0002-8504-7072","contributorId":329991,"corporation":false,"usgs":true,"family":"Avery","given":"Margaret","email":"","middleInitial":"Susan","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":931817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagstrum, Jonathan T. 0000-0002-0689-280X jhag@usgs.gov","orcid":"https://orcid.org/0000-0002-0689-280X","contributorId":3474,"corporation":false,"usgs":true,"family":"Hagstrum","given":"Jonathan","email":"jhag@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":931818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Scott E.K. 0000-0002-9772-4122 sekbennett@usgs.gov","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":5340,"corporation":false,"usgs":true,"family":"Bennett","given":"Scott","email":"sekbennett@usgs.gov","middleInitial":"E.K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":931819,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":931820,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70269982,"text":"70269982 - 2025 - Predicting invasiveness of freshwater fishes imported into North America: Regional differences in models and outcomes","interactions":[],"lastModifiedDate":"2025-08-07T15:54:16.040989","indexId":"70269982","displayToPublicDate":"2025-03-22T10:47:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Predicting invasiveness of freshwater fishes imported into North America: Regional differences in models and outcomes","docAbstract":"<p><span>Biological invasions driven by international trade heighten the urgency for development of invasion risk models, as the traits and parameters that consistently predict successful invasion remain unresolved. For four regions of North America that include parts of the United States and Canada (Sacramento-San Joaquin River Basins, Lower Colorado River Basin, Great Lakes Region, Mid-Atlantic Region), we construct and compare classification tree models to reveal robust predictors for the establishment and ecological impact stages of freshwater fish invasion. We subsequently apply the models to identify invasive fish species in trade and conduct pathway analyses to determine which trades (aquarium, biological supply, live bait, live food, water garden) and source continents pose the greatest risk to each region. Model results differed by invasion stage and region. Across regions, establishment models shared climate-related predictors including climate match and temperature tolerance. Three of the four impact models contained prior establishment success. The greatest number of species (548) were predicted to establish in the Sacramento-San Joaquin while the fewest (5) were predicted to establish in the Mid-Atlantic. Forty species were predicted to establish in multiple regions, five of which were also predicted to have high impact. The aquarium trade and Asia supplied the most species predicted to establish. Taken together, the results highlight region-specific models, indicating no universal model predicts invasion. Climate-related and prior establishment variables were most useful to risk assessments. The regional models, and identified high-risk pathways and potential invaders, could be applied to prevent future fish invasions in North America.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-025-03560-1","usgsCitation":"Howeth, J., Amjad, S., Gantz, C., Mandrak, N., Angermeier, P., Marchetti, M., Olden, J., and Lodge, D., 2025, Predicting invasiveness of freshwater fishes imported into North America: Regional differences in models and outcomes: Biological Invasions, v. 27, 107, 26 p., https://doi.org/10.1007/s10530-025-03560-1.","productDescription":"107, 26 p.","ipdsId":"IP-171323","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493802,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-025-03560-1","text":"Publisher Index 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Alabama","active":true,"usgs":false}],"preferred":false,"id":945123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gantz, Crysta A.","contributorId":359288,"corporation":false,"usgs":false,"family":"Gantz","given":"Crysta A.","affiliations":[{"id":39516,"text":"University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":945124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mandrak, Nicholas E.","contributorId":359290,"corporation":false,"usgs":false,"family":"Mandrak","given":"Nicholas E.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":945125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Angermeier, Paul L. 0000-0003-2864-170X","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":204519,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul L.","affiliations":[{"id":199,"text":"Coop Res Unit 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,{"id":70266168,"text":"70266168 - 2025 - Predicting bat roosts in bridges using Bayesian Additive Regression Trees","interactions":[],"lastModifiedDate":"2025-04-30T14:55:09.773729","indexId":"70266168","displayToPublicDate":"2025-03-22T08:11:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Predicting bat roosts in bridges using Bayesian Additive Regression Trees","docAbstract":"Human-built structures can provide important habitat for wildlife, but predicting which structures are most likely to be used remains challenging. To evaluate the predictive capabilities of data-driven ensemble modeling approaches, we conducted surveys for bats and signs of bat use, such as urine and guano staining, at bridges across the southwestern United States. We developed a bat roost discovery tool using Bayesian Additive Regression Trees (BART) and evaluated the predictive ability of this model against other commonly used approaches. We found that the lack of nearby water resources was associated with a lower predicted probability of bat presence or signs of bat use at bridges. While the presence of nearby water resources was associated with higher average predicted probability of bat presence or signs of bat use, high uncertainty surrounding these estimates indicates that other factors also play a role in determining which bridge roosts bats are more likely to use. As such, our model could be particularly useful for predicting which bridges can be excluded from survey efforts due to low probability of bat presence or signs of bat use. We extrapolated our model to unsurveyed bridges across the study region and provide an interactive dashboard application interface for the exploration of these results. Overall, this study demonstrates the application of BART as a predictive tool for prioritizing future bridge surveys for bats roosting in transportation structures.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e03551","usgsCitation":"Oram, J., Wray, A.K., Davis, H.T., de Wit, L., Frick, W.F., Hoegh, A.B., Irvine, K.M., Pollock, P., Schuhmann, A.N., Tousley, F.C., and Reichert, B., 2025, Predicting bat roosts in bridges using Bayesian Additive Regression Trees: Global Ecology and Conservation, v. 60, e03551, 12 p., https://doi.org/10.1016/j.gecco.2025.e03551.","productDescription":"e03551, 12 p.","ipdsId":"IP-176127","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490934,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14HVQHW","text":"USGS data release","linkHelpText":"North American Bat Monitoring Program (NABat) OneHealth (ver. 2.0, June 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However, the full value of repeat spectroscopy, the information embedded within different temporal scales, and the reliability of existing algorithms across diverse ecosystem types and vegetation phenophases have remained elusive due to the absence of suitable sub-seasonal spectroscopy data. In response, the Surface Biology and Geology (SBG) High-Frequency Time Series (SHIFT) campaign was initiated during late February 2022 in Santa Barbara County, California. SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. This ambitious endeavor included weekly Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquisitions for 13 weeks (spanning February 24 to May 29, 2022), accompanied by coordinated terrestrial vegetation and coastal aquatic data collection. 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,{"id":70265231,"text":"70265231 - 2025 - Linking environmental variability to long-term demographic change of an endangered species using integrated population models","interactions":[],"lastModifiedDate":"2025-05-12T15:43:41.572164","indexId":"70265231","displayToPublicDate":"2025-03-21T09:21:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Linking environmental variability to long-term demographic change of an endangered species using integrated population models","docAbstract":"<ol class=\"\"><li>Understanding how species populations change with environmental conditions is important for implementing effective habitat management and conservation strategies. Challenges to evaluating population-level responses to environmental conditions arise when data are sparse or not spatiotemporally aligned, especially for at-risk species with small, declining numbers.</li><li>We synthesized 30 years (1992–2021) of three partially aligned data sets to build a Bayesian integrated population model (IPM) and evaluate demographic and environmental drivers of growth rates for six separately managed ‘subpopulations’ (A–F) of the federally endangered Cape Sable seaside sparrow endemic to the Florida Everglades.</li><li>We found that juvenile survival peaked at inundation periods (hydroperiods) around 100–220 days and dropped sharply outside those values, while adult survival increased with longer periods of water depth &lt;20 cm, but not with longer periods of water depth &gt;20 cm. Fecundity increased when water depths were more stable, more area was dry, intervals between fires were longer and less area was burned.</li><li>Changes in population growth rates tended to occur in years that juvenile and adult survival were associated with hydroperiod, especially in the two largest subpopulations B and E. Population growth rates were also associated with hydrologic conditions during the breeding season and fire dynamics through changes in fecundity, most notably in the smaller subpopulations A, C/F and D.</li><li><i>Synthesis and applications</i>. Our IPM represents the first long-term population analysis of the Cape Sable seaside sparrow connecting demographic processes to environmental factors. Our results suggest that sustaining periods of shallow water year-round may enhance Cape Sable seaside sparrow survival and population growth. Also, limiting water depth variability and maintaining dry conditions during the breeding season and inhibiting fires in consecutive years may increase fecundity and population growth. Identifying the mechanistic links between environmental and population dynamics could inform how species are expected to respond to management decisions and anticipated ecosystem changes.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.70038","collaboration":"U.S. Fish and Wildlife Service, National Park Service","usgsCitation":"Martinez, M.T., D’Acunto, L., and Romanach, S., 2025, Linking environmental variability to long-term demographic change of an endangered species using integrated population models: Journal of Applied Ecology, v. 62, no. 5, p. 1137-1151, https://doi.org/10.1111/1365-2664.70038.","productDescription":"15 p.","startPage":"1137","endPage":"1151","ipdsId":"IP-163974","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488471,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.70038","text":"Publisher Index Page"},{"id":484130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.27756478832899,\n              25.9167\n            ],\n            [\n              -81.27756478832899,\n              25.0833\n            ],\n            [\n              -80.40679117600436,\n              25.0833\n            ],\n            [\n              -80.40679117600436,\n              25.9167\n            ],\n            [\n              -81.27756478832899,\n              25.9167\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"62","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Martinez, Marisa Takada 0000-0002-1915-6019","orcid":"https://orcid.org/0000-0002-1915-6019","contributorId":304805,"corporation":false,"usgs":true,"family":"Martinez","given":"Marisa","email":"","middleInitial":"Takada","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":223479,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932553,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70265260,"text":"70265260 - 2025 - Drought in the Delta: Socio-ecological impacts, responses, and tools","interactions":[],"lastModifiedDate":"2025-04-03T23:10:53.927858","indexId":"70265260","displayToPublicDate":"2025-03-20T15:43:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Drought in the Delta: Socio-ecological impacts, responses, and tools","docAbstract":"Droughts are frequent events in the western United States, and can disrupt water supply and degrade water quality, challenging water management in the Sacramento–San Joaquin Delta (Delta). This chapter for the State of Bay–Delta Science report describes what drought means for the Delta, how drought is managed in the Delta, and how drought management has changed over time. Projections of future climate indicate the possibility of increased frequency and severity of droughts which would have increasing effects on California’s water system, society, and ecological functions within and beyond the Delta. California has experienced several major droughts in the 20th and 21st centuries, each of which has caused significant social and ecological impacts and motivated improvements in water management. Droughts decrease native fish populations, increase harmful algal blooms, and promote the spread of many invasive plant and animal species. For people living within the Delta and those that rely on Delta water exports, droughts increase drinking water costs and decrease agricultural production, negatively affecting agricultural economies and labor markets. Tools developed in response to droughts include actions that increase supply, such as building water infrastructure, actions to reduce demand, such as water conservation campaigns, and mitigation actions, such as monetary relief for drought-impacted communities. Improving drought resilience requires development of additional drought responses, increased forecasting accuracy, and increased awareness of impacts on vulnerable communities and ecosystems. Even with development of additional management actions, strategies, and regulations, there will likely be difficulties meeting the current levels of demand for water. Drought conditions already cause conflict between human and environmental uses, and with more extreme droughts possible in the future and projected increases in demand, it will be challenging to provide for all users’ needs even with major changes to water management in the Delta.","language":"English","publisher":"San Francisco Estuary and Watershed Science","doi":"10.15447/sfews.2025v23iss1art3","usgsCitation":"Hartman, R., Knowles, N., Fencl, A., and Ekstrom, J., 2025, Drought in the Delta: Socio-ecological impacts, responses, and tools: San Francisco Estuary and Watershed Science, v. 23, no. 1, 3, 62 p., https://doi.org/10.15447/sfews.2025v23iss1art3.","productDescription":"3, 62 p.","ipdsId":"IP-165574","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":488603,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2025v23iss1art3","text":"Publisher Index Page"},{"id":484181,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.34896936938145,\n              38.77286456314664\n            ],\n            [\n              -123.34896936938145,\n              36.830761244624284\n            ],\n            [\n              -120.62613364311007,\n              36.830761244624284\n            ],\n            [\n              -120.62613364311007,\n              38.77286456314664\n            ],\n            [\n              -123.34896936938145,\n              38.77286456314664\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"23","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Hartman, Rosemary","contributorId":352954,"corporation":false,"usgs":false,"family":"Hartman","given":"Rosemary","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":932621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knowles, Noah 0000-0001-5652-1049","orcid":"https://orcid.org/0000-0001-5652-1049","contributorId":206338,"corporation":false,"usgs":true,"family":"Knowles","given":"Noah","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":932622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fencl, Amanda","contributorId":352956,"corporation":false,"usgs":false,"family":"Fencl","given":"Amanda","affiliations":[{"id":27801,"text":"Union of Concerned Scientists","active":true,"usgs":false}],"preferred":false,"id":932623,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ekstrom, Julia","contributorId":352958,"corporation":false,"usgs":false,"family":"Ekstrom","given":"Julia","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":932624,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70264694,"text":"ofr20251004 - 2025 - Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States","interactions":[],"lastModifiedDate":"2025-03-26T19:46:15.392167","indexId":"ofr20251004","displayToPublicDate":"2025-03-20T13:10:17","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1004","displayTitle":"Science Needs for Determining the Effects of Climate Change on Harmful Algal Blooms in the Southeastern United States","title":"Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States","docAbstract":"<p>The Southeastern United States has many lakes, streams, and reservoirs that serve as important drinking water sources with recreational, agricultural, and ecological uses. However, harmful algal blooms (HABs) are becoming more common in these waters, causing health issues for humans and animals. HABs have been listed as a contaminant of emerging concern, and the magnitude, frequency, and duration of HABs appear to be increasing at the global scale. While it is well known that nutrients stimulate algae growth, it is not clear how climate change and other parameters stimulate the development of toxin production by HABs. The scientific literature describes parameters, such as storm occurrence, temperature, dissolved metals, erosion of soils, increasing length of growing season, discharge, and hydroperiod, that may affect algae growth and toxin production. Climate and hydrologic models address many of the physical and environmental parameters that influence HABs, but no climate models directly address HABs. This report compiles information from the existing literature pertaining to HABs and the modeling and forecasting of HABS. This compilation is done through the incorporation of climate change models. HAB research that involves climate change will require multiple disciplines that bring together ecologists, hydrologists, climatologists, engineers, economists, and new technology. Resource managers could use geographic data about the occurrence and distribution of HABs to develop models that identify waterbodies more vulnerable to HAB events. Development of such models will require teams capable of integrating biological, chemical, and physical factors. Model development will require additional research that can resolve anthropogenic and climate-related environmental factors to identify trends in freshwater HABs. The complexity and interconnectedness of the parameters that influence HAB occurrences will make model development challenging and require rigorous regional calibration.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251004","issn":"2331-1258","collaboration":"Prepared in cooperation with the Southeast Climate Adaptation Science Center and  Tennessee State University","usgsCitation":"Byl, T.D., Moore, D.M., Cunningham, C., and Young, D., 2025, Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States: U.S. Geological Survey Open-File Report 2025–1004, 29 p., https://doi.org/10.3133/ofr20251004.","productDescription":"vii, 29 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-156959","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":483554,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251004/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1004 HTML"},{"id":483549,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1004/coverthb.jpg"},{"id":483553,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1004/ofr20251004.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1004 XML"},{"id":483551,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1004/ofr20251004.pdf","size":"7.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1004"},{"id":483550,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1004/images"}],"contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\" href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>640 Grassmere Park, Suite 100<br>Nashville, TN 37211<br></p><p><a id=\"LPlnkOWAb30f03cb-e6c0-c412-988f-235c353ce0b0\" class=\"OWAAutoLink\" href=\"https://pubs.usgs.gov/contact\" data-auth=\"NotApplicable\" data-olk-copy-source=\"MailCompose\" data-mce-href=\"../contact\">Contact Us- USGS Publications Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Background on HABs and Cyanobacteria</li><li>Drivers of HAB Events</li><li>Development of Models</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2025-03-20","noUsgsAuthors":false,"publicationDate":"2025-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Byl, Tom D. 0000-0001-6907-9149","orcid":"https://orcid.org/0000-0001-6907-9149","contributorId":352440,"corporation":false,"usgs":true,"family":"Byl","given":"Tom D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Devin M. 0009-0003-6919-8625","orcid":"https://orcid.org/0009-0003-6919-8625","contributorId":352441,"corporation":false,"usgs":false,"family":"Moore","given":"Devin M.","affiliations":[{"id":13370,"text":"Tennessee State University","active":true,"usgs":false}],"preferred":true,"id":931297,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cunningham, Champagne 0000-0001-6318-5434","orcid":"https://orcid.org/0000-0001-6318-5434","contributorId":352442,"corporation":false,"usgs":true,"family":"Cunningham","given":"Champagne","affiliations":[],"preferred":true,"id":931301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, De’Etra","contributorId":352443,"corporation":false,"usgs":false,"family":"Young","given":"De’Etra","affiliations":[{"id":13370,"text":"Tennessee State University","active":true,"usgs":false}],"preferred":true,"id":931300,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70267200,"text":"70267200 - 2025 - Exploration of a piscicide delivery method for invasive Black Carp","interactions":[],"lastModifiedDate":"2025-05-16T15:50:36.730751","indexId":"70267200","displayToPublicDate":"2025-03-20T10:49:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Exploration of a piscicide delivery method for invasive Black Carp","docAbstract":"<p><span>A piscicide delivery method was designed to selectively target Black Carp&nbsp;</span><i>Mylopharyngodon piceus,</i><span>&nbsp;an invasive fish species in North America, which possesses pharyngeal teeth adapted for crushing mollusk prey. Many North American mollusks exist in small, fragmented populations susceptible to local extirpation. A Black Carp-selective toxic bait deployed properly could be used to protect those populations. Results represent initial efforts to construct an effective single-dose species-selective toxic bait. We prepared a bait by attaching a glass vial containing toxicant (antimycin A) to the exterior of a&nbsp;</span><i>Corbicula fluminea</i><span>&nbsp;clam valve. We designed the vial to break from the force of the fish’s pharyngeal teeth when attempting to crush and consume the clam. We tested suitable vial sizes for encapsulating piscicide and two attachment materials, an aquarium epoxy and ultraviolet light-cured attachment material. The aquarium epoxy was rigid and reinforced vials. The ultraviolet light-cured attachment material was softer, resulting in more vials broken at 3- and 24-h post feeding. In a second trial, toxic baits consisting of antimycin A piscicide were administered in pure ethanol and acetone carriers to Black Carp in assembled baits with vials attached to live clam valves at three concentrations (40.0 mg/mL in ethanol, 170.8 mg/mL and 341.5 mg/mL in acetone). We selected aquarium epoxy for assembled baits based on the bond between the epoxy and glass vial, which allowed a greater surface area to be exposed and broken. While Black Carp successfully broke vials containing piscicide, no treatment caused carp mortality. The delivery method was unsuccessful as a single dose antimycin A piscicide bait for Black Carp. Additional considerations for this approach are provided.</span></p>","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-24-009","usgsCitation":"Kroboth, P., Stahlschmidt, B.H., and Chapman, D., 2025, Exploration of a piscicide delivery method for invasive Black Carp: Journal of Fish and Wildlife Management, https://doi.org/10.3996/JFWM-24-009.","ipdsId":"IP-146508","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":490130,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-24-009","text":"Publisher Index Page"},{"id":486079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kroboth, Patrick 0000-0002-9447-4818","orcid":"https://orcid.org/0000-0002-9447-4818","contributorId":216578,"corporation":false,"usgs":true,"family":"Kroboth","given":"Patrick","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stahlschmidt, Benjamin H. 0000-0001-6197-662X","orcid":"https://orcid.org/0000-0001-6197-662X","contributorId":211250,"corporation":false,"usgs":true,"family":"Stahlschmidt","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":937251,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70264194,"text":"dr1202 - 2025 - Four-band image mosaic of the Colorado River Corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2021 airborne image acquisition","interactions":[],"lastModifiedDate":"2025-03-21T13:39:32.835373","indexId":"dr1202","displayToPublicDate":"2025-03-20T09:20:09","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1202","displayTitle":"Four-Band Image Mosaic of the Colorado River Corridor Downstream of Glen Canyon Dam in Arizona, Derived from the May 2021 Airborne Image Acquisition","title":"Four-band image mosaic of the Colorado River Corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2021 airborne image acquisition","docAbstract":"<p>In May 2021, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center acquired airborne multispectral high-resolution data for the Colorado River in the Grand Canyon, Arizona. The image data, which consist of four spectral bands (red, band 1; green, band 2; blue, band 3; and near infrared, band 4) with a ground resolution of 20 centimeters, are available as 16-bit unsigned-integer GeoTIFF files in Sankey and others (2024) (available online at <a data-mce-href=\"https://doi.org/10.5066/P9BBGN6G\" href=\"https://doi.org/10.5066/P9BBGN6G\">https://doi.org/10.5066/P9BBGN6G</a>). The image files are projected in the State Plane Coordinate System, using the central Arizona zone (202) with the North American Datum of 1983 National Adjustment of 2011. The assessed spatial accuracy for these data is based on 47 ground-control points that were independent from the ground-control points used by the contractor for aerotriangulation and is reported at the 95-percent confidence level as 0.514 meter (m) and a root mean square error of 0.297 m. The intended uses of this dataset are primarily in support of scientific research and monitoring applications. Examples of these applications include high-resolution spatial and temporal change detection of the river channel, geomorphic landforms, riparian vegetation, and backwater and nearshore habitat, as well as other ecosystem-wide mapping. These imagery data also serve as reference material for field science mission planning, as base data for field data collection including community science activities, and as a highly detailed guide for technical boat operation during science activities such as reconnaissance for nighttime missions and navigating rapids during low flows.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1202","collaboration":"Prepared in cooperation with Northern Arizona University","usgsCitation":"Sankey, J.B., Bransky, N.D., Pigue, L.M., Kohl, K.A., and Gushue, T.M., 2025, Four-band image mosaic of the Colorado River corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2021 airborne image acquisition: U.S. Geological Survey Data Report 1202, https://doi.org/10.3133/dr1202.","productDescription":"Report: HTML Document; Data Release","onlineOnly":"Y","ipdsId":"IP-162668","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":483089,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1202/dr1202.XML"},{"id":483585,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":483091,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1202/full"},{"id":483090,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1202/images"},{"id":483526,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1027","description":"Durning, L.E., Sankey, J.B., Davis, P.A., and Sankey, T.T., 2016, Four-band image mosaic of the Colorado River corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2013 airborne image acquisition: U.S. Geological Survey Data Series 1027, https://doi.org/10.3133/ds1027.","linkHelpText":"- Four-band image mosaic of the Colorado River corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2013 airborne image acquisition"},{"id":483066,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/780/","description":"Davis, P.A., 2013, Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection: U.S. Geological Survey Data Series 780, https://pubs.usgs.gov/ds/780/.","linkHelpText":"- Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection"},{"id":483527,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"http://pubs.usgs.gov/of/2012/1139/","description":"Davis, P.A., 2012, Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009—Image-mosaic production and comparison with 2002 and 2005 image mosaics: U.S. Geological Survey Open-File Report 2012–1139, 82 p. (Available at http://pubs.usgs.gov/of/2012/1139/.)","linkHelpText":"- Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009—Image-mosaic production and comparison with 2002 and 2005 image mosaics"},{"id":483065,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/P93Y4FMJ","description":"Sankey, J.B., Bransky, N.B., Kohl, K.A., Gushue, T.M., Bedford, A.F., and Durning, L.E., 2025, Digital elevation model (DEM) and digital surface model (DSM) data for the Colorado River corridor in Grand Canyon National Park and Glen Canyon National Recreation Area (2002, 2009, 2013 and 2021), including accuracy assessment data: U.S. Geological Survey data release, https://doi.org/10.5066/P93Y4FMJ.","linkHelpText":"- Digital elevation model (DEM) and digital surface model (DSM) data for the Colorado River corridor in Grand Canyon National Park and Glen Canyon National Recreation Area (2002, 2009, 2013 and 2021), including accuracy assessment data"},{"id":483064,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BBGN6G","text":"USGS Data Release","description":"Sankey, J.B., Bransky, N., Pigue, L., Kohl, K., and Gushue, T.M., 2024, Four Band Image Mosaic of the Colorado River Corridor in Arizona—2021, including Accuracy Assessment Data: U.S. Geological Survey data release, https://doi.org/10.5066/P9BBGN6G.","linkHelpText":"Four band image mosaic of the Colorado River Corridor in Arizona—2021, including accuracy assessment data"},{"id":483525,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/F7TX3CHS","description":"Durning, L.E., Sankey, J.B., Davis, P.A., and Sankey, T.T., 2016, Four band Image mosaic of the Colorado River Corridor in Arizona--2013, including accuracy assessment data: U.S. Geological Survey data release, https://doi.org/10.5066/F7TX3CHS","linkHelpText":"- Four band Image mosaic of the Colorado River Corridor in Arizona--2013, including accuracy assessment data"}],"country":"United States","state":"Arizona, Nevada, Utah","otherGeospatial":"Colorado River, Glen Canyon Dam, Grand Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.25503634497424,\n              37.07331588090071\n            ],\n            [\n              -115.01927028989792,\n              37.07331588090071\n            ],\n            [\n              -115.01927028989792,\n              35.44030487638608\n            ],\n            [\n              -111.25503634497424,\n              35.44030487638608\n            ],\n            [\n              -111.25503634497424,\n              37.07331588090071\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/sbsc\" data-mce-href=\"https://www.usgs.gov/centers/sbsc\">Southwest Biological Science Center</a><br><a href=\"https://www.usgs.gov/\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>2255 N. Gemini Drive<br>Flagstaff, AZ 86001</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Data Collection</li><li>Image Processing</li><li>Accuracy and Error</li><li>Data Organization</li><li>Companion Data</li><li>References Cited</li><li>Appendix 1</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2025-03-20","noUsgsAuthors":false,"publicationDate":"2025-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":930112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bransky, Nathaniel D. 0000-0003-3113-7491","orcid":"https://orcid.org/0000-0003-3113-7491","contributorId":305709,"corporation":false,"usgs":true,"family":"Bransky","given":"Nathaniel","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":930113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pigue, Lori M. 0000-0002-6675-6877","orcid":"https://orcid.org/0000-0002-6675-6877","contributorId":330994,"corporation":false,"usgs":true,"family":"Pigue","given":"Lori","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":930114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kohl, Keith 0000-0001-6812-0373 kkohl@usgs.gov","orcid":"https://orcid.org/0000-0001-6812-0373","contributorId":1323,"corporation":false,"usgs":true,"family":"Kohl","given":"Keith","email":"kkohl@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":930115,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gushue, Thomas M. 0000-0002-7172-2460","orcid":"https://orcid.org/0000-0002-7172-2460","contributorId":213515,"corporation":false,"usgs":true,"family":"Gushue","given":"Thomas M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":930116,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70264734,"text":"70264734 - 2025 - Reconstruction of Holocene and Last Interglacial vegetation dynamics and wildfire activity in Southern Siberia","interactions":[],"lastModifiedDate":"2025-03-21T15:27:48.558095","indexId":"70264734","displayToPublicDate":"2025-03-20T08:09:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Reconstruction of Holocene and Last Interglacial vegetation dynamics and wildfire activity in Southern Siberia","docAbstract":"<p><span>Wildfires are a rapidly increasing threat to boreal forests. While our understanding of the drivers behind wildfires and their environmental impact is growing, it is mostly limited to the observational period. Here we focus on the boreal forests of southern Siberia and exploit a U–Th-dated stalagmite from Botovskaya Cave, located in the upper Lena region of southern Siberia, to document wildfire activity and vegetation dynamics during parts of two warm periods: the Last Interglacial (LIG; specifically part of the Last Interglacial maximum between 124.1 and 118.8 ka) and the Holocene (10–0 ka). Our record is based on levoglucosan (Lev), a biomarker sensitive to biomass burning, and on lignin oxidation products (LOPs) that discriminate between open and closed forest and hard- or softwood vegetation. In addition, we used carbonate carbon stable isotope ratios (</span><span class=\"inline-formula\"><i>δ</i><sup>13</sup>C</span><span>), which reflect a dominant control of the host rock, to evaluate soil respiration and local infiltration changes. Our LOP data suggest that, during the Last Interglacial, the region around Botovskaya Cave was characterised by open forest, which by ca. 121.5 ka underwent a transition from fire-resistant hardwood to fire-prone softwood. The Lev record indicates that fire activity was high and increased towards the end of Last Interglacial just before 119 ka. In contrast, the Holocene was characterised by a closed-forest environment with mixed hard- and softwood vegetation. Holocene fire activity varied but at a much lower level than during the Last Interglacial. We attribute the changes in wildfire activity during the intervals of interest to the interplay between vegetation and climate. The open forests of the Last Interglacial were more likely to ignite than their closed Holocene equivalents, and their flammability was aided by warmer and drier summers and a stronger seasonal temperature contrast due to the increase in seasonal insolation difference compared to the Holocene. Our comparison of the last two interglacial intervals suggests that, with increasing global temperatures, the boreal forest of southern Siberia may become progressively more vulnerable to higher wildfire activity.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/cp-21-661-2025","usgsCitation":"Margerum, J., Homann, J., Umbo, S., Nehrke, G., Hoffmann, T., Vaks, A., Kononov, A., Osintsev, A., Giesche, A., Mason, A., Lechleitner, F., Henderson, G., Kwiecien, O., and Breitenbach, S., 2025, Reconstruction of Holocene and Last Interglacial vegetation dynamics and wildfire activity in Southern Siberia: Climate of the Past, v. 21, no. 3, p. 661-677, https://doi.org/10.5194/cp-21-661-2025.","productDescription":"17 p.","startPage":"661","endPage":"677","ipdsId":"IP-165953","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":488363,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-21-661-2025","text":"Publisher Index Page"},{"id":483662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia","otherGeospatial":"Botovskaya Cave, Siberia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              104.97249739324332,\n              55.0006548103033\n            ],\n            [\n              104.97249739324332,\n              54.87985401356909\n            ],\n            [\n              105.12004339826586,\n              54.87985401356909\n            ],\n            [\n              105.12004339826586,\n              55.0006548103033\n            ],\n            [\n              104.97249739324332,\n              55.0006548103033\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"21","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Margerum, Jade","contributorId":352494,"corporation":false,"usgs":false,"family":"Margerum","given":"Jade","affiliations":[{"id":84240,"text":"Department of Earth and Environmental Sciences, Northumbria University, Newcastle-Upon-Tyne, NE1 8ST, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":931488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homann, Julia","contributorId":352495,"corporation":false,"usgs":false,"family":"Homann","given":"Julia","affiliations":[{"id":84241,"text":"Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":931489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Umbo, Stuart","contributorId":352496,"corporation":false,"usgs":false,"family":"Umbo","given":"Stuart","affiliations":[{"id":84240,"text":"Department of Earth and Environmental Sciences, Northumbria University, Newcastle-Upon-Tyne, NE1 8ST, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":931490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nehrke, Gernot","contributorId":352497,"corporation":false,"usgs":false,"family":"Nehrke","given":"Gernot","affiliations":[{"id":84242,"text":"Alfred Wegener Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Section Marine BioGeoSciences, 27570 Bremerhaven, Germany","active":true,"usgs":false}],"preferred":false,"id":931491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoffmann, Thorsten","contributorId":352498,"corporation":false,"usgs":false,"family":"Hoffmann","given":"Thorsten","affiliations":[{"id":84241,"text":"Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":931492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vaks, Anton","contributorId":352499,"corporation":false,"usgs":false,"family":"Vaks","given":"Anton","affiliations":[{"id":84243,"text":"Geological Survey of Israel, 32 Yeshayahu Leibowitz Street, 9692100 Jerusalem, Israel","active":true,"usgs":false}],"preferred":false,"id":931493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kononov, Aleksandr","contributorId":352500,"corporation":false,"usgs":false,"family":"Kononov","given":"Aleksandr","affiliations":[{"id":84244,"text":"Irkutsk Nation al Research Technical University, Irkutsk, 664074, Russia; Institute of the Earth's Crust, Russian Academy of Sciences, Siberian Branch, Irkutsk, 664033, Russia","active":true,"usgs":false}],"preferred":false,"id":931494,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Osintsev, Alexander","contributorId":352501,"corporation":false,"usgs":false,"family":"Osintsev","given":"Alexander","affiliations":[{"id":84245,"text":"Speleoclub Arabika, St. Mamina-Sibiryaka 6a, 664058 Irkutsk, Russia","active":true,"usgs":false}],"preferred":false,"id":931495,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Giesche, Alena Maria 0000-0003-3673-7269","orcid":"https://orcid.org/0000-0003-3673-7269","contributorId":344659,"corporation":false,"usgs":true,"family":"Giesche","given":"Alena Maria","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":931496,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mason, Andrew","contributorId":352502,"corporation":false,"usgs":false,"family":"Mason","given":"Andrew","affiliations":[{"id":84247,"text":"Department of Earth Sciences, University of Oxford, South Parks Road, OX1 3AN Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":931497,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lechleitner, Franziska A.","contributorId":352503,"corporation":false,"usgs":false,"family":"Lechleitner","given":"Franziska A.","affiliations":[{"id":84248,"text":"Department of Chemistry, Biochemistry and Pharmaceutical Sciences & Oeschger Centre for Climate Change Research, Universität Bern, Freiestrasse 3, 3012 Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":931498,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Henderson, Gideon M.","contributorId":352504,"corporation":false,"usgs":false,"family":"Henderson","given":"Gideon M.","affiliations":[{"id":84247,"text":"Department of Earth Sciences, University of Oxford, South Parks Road, OX1 3AN Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":931499,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kwiecien, Ola","contributorId":352505,"corporation":false,"usgs":false,"family":"Kwiecien","given":"Ola","affiliations":[{"id":84240,"text":"Department of Earth and Environmental Sciences, Northumbria University, Newcastle-Upon-Tyne, NE1 8ST, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":931500,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Breitenbach, Sebastian F.M.","contributorId":352506,"corporation":false,"usgs":false,"family":"Breitenbach","given":"Sebastian F.M.","affiliations":[{"id":84240,"text":"Department of Earth and Environmental Sciences, Northumbria University, Newcastle-Upon-Tyne, NE1 8ST, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":931501,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70264658,"text":"sir20255013 - 2025 - Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022","interactions":[],"lastModifiedDate":"2025-07-23T17:11:15.939504","indexId":"sir20255013","displayToPublicDate":"2025-03-19T11:57:37","publicationYear":"2025","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":"2025-5013","displayTitle":"Hydrogeologic Investigation, Framework, and Conceptual Flow Model of the Antlers Aquifer, Southeastern Oklahoma, 1980–2022","title":"Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022","docAbstract":"<p>The 1973 Oklahoma Groundwater Law (Oklahoma Statute §82–1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin. Every 20 years, the Oklahoma Water Resources Board is required to update the hydrologic investigation on which the maximum annual yield determinations were based. The maximum annual yield allocated per acre of land is used to set the equal-proportionate share pumping rate. The maximum annual yield of 5,913,600 acre-feet per year and equal-proportionate-share of 2.1 acre-feet per acre per year currently (2025) in place for the Antlers aquifer were issued by the Oklahoma Water Resources Board on February 14, 1995. Because more than 20 years have elapsed since the 1995 final order for the Antlers aquifer was issued, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, completed an in-depth hydrologic study that included a hydrogeologic framework and conceptual groundwater-flow model for the 1980–2022 study period.</p><p>The results of an analysis of land use, long-term climate patterns, streamflow and base-flow patterns, historical groundwater use, as well as groundwater-level fluctuations across the Antlers aquifer are described. In addition, groundwater quality was analyzed for total dissolved solids concentrations and major ions for the Antlers aquifer. An updated hydrogeologic framework was developed that included refining the aquifer boundary in Oklahoma, the creation of new potentiometric surface and saturated thickness of fresh groundwater maps, one multiple-well aquifer test, slug tests, and an analysis of lithologic logs across the aquifer. A conceptual groundwater flow model and water budget were developed by incorporating estimates of recharge from precipitation, saturated-zone evapotranspiration, streambed seepage, lateral groundwater flows, vertical leakage, and withdrawals from groundwater wells.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255013","issn":"2328-0328","collaboration":"Prepared in cooperation with the Oklahoma Water Resources Board","usgsCitation":"Fetkovich, E.J., Morris, A.S., Dale, I.A., Codner, C., Kirby, E.A., Baciocco, C.A., Rogers, I.M.J., Wagner, D.L., Tomlinson, Z.D., and Fiorentino, E.G., 2025, Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022: U.S. Geological Survey Scientific Investigations Report 2025–5013, 55 p., https://doi.org/10.3133/sir20255013.","productDescription":"Report: x, 55 p.; Data Release; Dataset","numberOfPages":"70","onlineOnly":"Y","ipdsId":"IP-149893","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":492792,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118496.htm","linkFileType":{"id":5,"text":"html"}},{"id":483543,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255013/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5013 HTML"},{"id":483492,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://waterdata.usgs.gov/nwis","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":483491,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14C6QFS","text":"USGS Data Release","linkHelpText":"- Soil-water-balance model and data used in the hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1967–2022"},{"id":483483,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5013/coverthb.jpg"},{"id":483484,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5013/images"},{"id":483485,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5013/sir20255013.pdf","size":"41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5013"},{"id":483542,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5013/sir20255013.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5013 XML"}],"country":"United States","state":"Oklahoma, Texas","otherGeospatial":"Antlers aquifer study","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -97.55,\n              34.5\n            ],\n            [\n              -97.55,\n              33.25\n            ],\n            [\n              -94.5,\n              33.25\n            ],\n            [\n              -94.5,\n              34.5\n            ],\n            [\n              -97.55,\n              34.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/ot-water\" href=\"https://www.usgs.gov/centers/ot-water\">Oklahoma-Texas Water Science Center</a><br>U.S. Geological Survey<br>1505 Ferguson Lane<br>Austin, TX 78754–4501</p><p><a id=\"LPlnkOWAb30f03cb-e6c0-c412-988f-235c353ce0b0\" class=\"OWAAutoLink\" href=\"https://pubs.usgs.gov/contact\" data-auth=\"NotApplicable\" data-mce-href=\"../contact\">Contact Us- USGS Publications Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;</li><li>Abstract</li><li>Introduction</li><li>Hydrogeology of the Antlers Aquifer and Surrounding Units</li><li>Hydrogeologic Framework of the Antlers Aquifer</li><li>Conceptual Groundwater Flow Model and Water Budget</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2025-03-19","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Fetkovich, Evin J. 0000-0002-8899-8543","orcid":"https://orcid.org/0000-0002-8899-8543","contributorId":328666,"corporation":false,"usgs":true,"family":"Fetkovich","given":"Evin","email":"","middleInitial":"J.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Amy S. 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