{"pageNumber":"44","pageRowStart":"1075","pageSize":"25","recordCount":11004,"records":[{"id":70227173,"text":"sir20215126 - 2022 - Hydrology and water quality in 15 watersheds in DeKalb County, Georgia, 2012–16","interactions":[],"lastModifiedDate":"2026-04-02T20:03:05.696911","indexId":"sir20215126","displayToPublicDate":"2022-01-05T16:40:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5126","displayTitle":"Hydrology and Water Quality in 15 Watersheds in DeKalb County, Georgia, 2012–16","title":"Hydrology and water quality in 15 watersheds in DeKalb County, Georgia, 2012–16","docAbstract":"<p>The U.S. Geological Survey, in cooperation with DeKalb County Department of Watershed Management, established a long-term water-quantity and water-quality monitoring program in 2012 to monitor and analyze the hydrologic and water-quality conditions of 15 watersheds in DeKalb County, Georgia—an urban and suburban area located in north-central Georgia that includes the easternmost part of the City of Atlanta. This report synthesizes the watershed characteristics and monitoring data collected for the first 5 years of the program, 2012 through 2016. The study area was predominantly medium-density residential (43.9 percent), commercial/industrial/institutional (21.4 percent), forest/park/agriculture (13.6 percent), and high-density residential (11.5 percent) land uses. Land-surface slope averaged 8.7 percent, imperviousness averaged 25.3 percent, and population density averaged 2,936 people per square mile. Watershed imperviousness ranged from 8.7 to 36.6 percent.</p><p>In the study area for 2014 to 2016 (when streamflow data were available for all watersheds), runoff represented 40.9 percent of precipitation. Hydrograph separations indicated that 43 percent of runoff occurred as base flow, whereas the remainder occurred as stormflow. Higher watershed imperviousness was significantly related to higher amounts of runoff (Pearson product-moment correlation coefficient [<i>r</i>] = 0.517), higher runoff ratios (<i>r</i> = 0.646), and lower amounts (<i>r</i> = −0.637) and proportions (<i>r</i> = −0.898) of base-flow runoff. Stormwater best management practices have been implemented in the study watersheds; however, these practices do not appear to fully mitigate the effects of urban development and land use on stream hydrology.</p><p>Total copper, lead, and zinc concentrations in base-flow and stormflow samples exceeded the national recommended aquatic life criteria for chronic and acute conditions, respectively, to varying degrees. <i>Escherichia coli</i> density predictive regression models indicated that the U.S. Environmental Protection Agency’s Beach Action Value was exceeded at individual watersheds between 44.6 and 100 percent of the time. Exceedance of the Beach Action Value indicates possible unsafe conditions for primary contact recreation and could be used for timely notification of the potential health risks. Annual loads and yields were estimated for 15 constituents. Loads were typically higher for years with higher runoff while variations among watershed yields appear associated with watershed and land use characteristics. The lowest yields for almost all constituents occurred in the Stone Mountain Creek watershed—likely the result of the retention of sediment and reduction of nutrients in Stone Mountain Lake and two smaller downstream reservoirs within the watershed. The Little Stone Mountain Creek watershed also had some of the lowest yields for most constituents, likely due to the lack of many pollutant sources associated with its predominantly medium-density residential land use (95.5 percent), but had the highest total nitrate plus nitrite yields. The Intrenchment Creek watershed consistently had some of the highest yields across all constituents except for total nitrate plus nitrite. The high yields may be related to its high percentage of impervious area (36.0 percent) and high amount of heavily developed land use (high-density residential, 29.9 percent and commercial/industrial/institutional, 26.0 percent). Mean watershed constituent yields in this study were significantly higher than those from a similar analysis of 13 suburban to urban watersheds in adjacent Gwinnett County for 6 of the 10 constituents compared.</p><p>This study provides a thorough assessment of watershed characteristics, hydrology, and water-quality conditions of the 15 study watersheds and can be used to identify possible factors that affect runoff and water quality. Watershed managers can use these data and analyses to inform management decisions regarding the designated uses of streams, minimization of flooding, protection of aquatic habitats, and optimization of the effectiveness of best management practices.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215126","collaboration":"Prepared in cooperation with DeKalb County Department of Watershed Management","usgsCitation":"Aulenbach, B.T., Kolb, K., Joiner, J.K., and Knaak, A.E., 2022, Hydrology and water quality in 15 watersheds in DeKalb County, Georgia, 2012–16: U.S. Geological Survey Scientific Investigations Report 2021–5126, 105 p., https://doi.org/10.3133/sir20215126.","productDescription":"Report: xii, 105 p.; Data Release; Database","numberOfPages":"105","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-117184","costCenters":[{"id":316,"text":"Georgia Water Science 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<a href=\"https://www.usgs.gov/centers/sa-water\" data-mce-href=\"https://www.usgs.gov/centers/sa-water\">South Atlantic Water Science Center</a><br>U.S. Geological Survey<br>1770 Corporate Drive, Suite 500<br>Norcross, GA 30093</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Design and Methods</li><li>Watershed Characteristics</li><li>Water Budget</li><li>Surface-Water Quality</li><li>Discussion</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Water-Quality Assurance and Control Summary</li><li>Appendix 2. Regression-Model Load Estimation Methodology Changes</li><li>Appendix 3. LOADEST Load Model Evaluation</li><li>Appendix 4. Assessment of Effects of Time-Step Load Methodology on Load Estimates</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2022-01-05","noUsgsAuthors":false,"publicationDate":"2022-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829912,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolb, Katharine 0000-0002-1663-1662 kkolb@usgs.gov","orcid":"https://orcid.org/0000-0002-1663-1662","contributorId":5537,"corporation":false,"usgs":true,"family":"Kolb","given":"Katharine","email":"kkolb@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":829913,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joiner, John K. 0000-0001-9702-4911 jkjoiner@usgs.gov","orcid":"https://orcid.org/0000-0001-9702-4911","contributorId":3056,"corporation":false,"usgs":true,"family":"Joiner","given":"John","email":"jkjoiner@usgs.gov","middleInitial":"K.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829914,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knaak, Andrew E. 0000-0003-1813-8959 aknaak@usgs.gov","orcid":"https://orcid.org/0000-0003-1813-8959","contributorId":3123,"corporation":false,"usgs":true,"family":"Knaak","given":"Andrew","email":"aknaak@usgs.gov","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829915,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227265,"text":"sir20215102 - 2022 - Main-stem seepage and base-flow recession time constants in the Niobrara National Scenic River Basin, Nebraska, 2016–18","interactions":[],"lastModifiedDate":"2026-04-02T19:42:13.334029","indexId":"sir20215102","displayToPublicDate":"2022-01-05T16:35:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5102","displayTitle":"Main-Stem Seepage and Base-Flow Recession Time Constants in the Niobrara National Scenic River Basin, Nebraska, 2016–18","title":"Main-stem seepage and base-flow recession time constants in the Niobrara National Scenic River Basin, Nebraska, 2016–18","docAbstract":"<p>The Niobrara River of northern Nebraska is a valuable water resource that sustains irrigated agriculture and recreation, as well as a diverse ecosystem. Large-quantity withdrawals from the source aquifer system have the potential to reduce the flow into the river and to adversely affect the free-flowing condition of the Niobrara National Scenic River (NSR). Therefore, to understand the magnitude and characteristics of those flows, the U.S. Geological Survey (USGS), in cooperation with the National Park Service, began a study to quantify seepage gains/losses along the eastern half of the Niobrara NSR and to create a map characterizing the base-flow recession time constant (tau) in the Niobrara NSR study area.</p><p>In 2016, a seepage study was completed to quantify seepage gains/losses along the eastern half of the Niobrara NSR. The seepage study results indicated that the main-stem streamflow on the Niobrara River increases 375 cubic feet per second (ft<sup>3</sup>/s) in the 39.9-mile study reach (river mile 119.3 to river mile 79.4). Although most of the streamflow increases are attributed to tributary inflows (297 ft<sup>3</sup>/s, 79 percent), 78 ft<sup>3</sup>/s are attributed to seepage gains within the reach. Seepage rates in the study reach ranged from 1.41 cubic feet per second per mile ([ft<sup>3</sup>/s]/mi) to 2.56 (ft<sup>3</sup>/s)/mi, with a mean seepage rate of 2 (ft<sup>3</sup>/s)/mi.</p><p>Tau values were calculated at 10 sites in the Niobrara NSR study area, and kriging geostatistical techniques were used to develop a contour map to estimate tau values at locations where streamflow was not measured. The minimum tau value was 12.1 days at Willow Creek at Atwood Road near Carns, Nebraska (USGS station 06463670), and the maximum value was 45.5 days at Tyler Falls at Fort Niobrara National Wildlife Refuge near Valentine, Nebr. (USGS station 06461150).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215102","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Strauch, K.R., and Soenksen, P.J., 2022, Main-stem seepage and base-flow recession time constants in the Niobrara National Scenic River Basin, Nebraska, 2016–18: U.S. Geological Survey Scientific Investigations Report 2021–5102, 17 p., https://doi.org/10.3133/sir20215102.","productDescription":"Report: vi, 17 p.; Data Release; Dataset","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125025","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":393921,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PDP1BI","text":"USGS data release","linkHelpText":"Datasets used to map the base-flow recession time constants in the Niobrara National Scenic River in Nebraska, 2016–18"},{"id":502117,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112068.htm","linkFileType":{"id":5,"text":"html"}},{"id":393922,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":393920,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5102/sir20215102.pdf","text":"Report","size":"2.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5102"},{"id":393919,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5102/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Niobrara National Scenic River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.974609375,\n              41.64007838467894\n            ],\n            [\n              -100.08544921874999,\n              41.64007838467894\n            ],\n            [\n              -100.08544921874999,\n              42.956422511073335\n            ],\n            [\n              -103.974609375,\n              42.956422511073335\n            ],\n            [\n              -103.974609375,\n              41.64007838467894\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/nebraska-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/nebraska-water-science-center\">Nebraska Water Science Center</a><br>U.S. Geological Survey<br>5231 South 19th Street<br>Lincoln, NE 68512</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Main-Stem Seepage</li><li>Base-Flow Recession Time Constants</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-01-05","noUsgsAuthors":false,"publicationDate":"2022-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Strauch, Kellan R. 0000-0002-7218-2099 kstrauch@usgs.gov","orcid":"https://orcid.org/0000-0002-7218-2099","contributorId":1006,"corporation":false,"usgs":true,"family":"Strauch","given":"Kellan","email":"kstrauch@usgs.gov","middleInitial":"R.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soenksen, Philip J. pjsoenks@usgs.gov","contributorId":3983,"corporation":false,"usgs":true,"family":"Soenksen","given":"Philip","email":"pjsoenks@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":830199,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227180,"text":"70227180 - 2022 - Landscape and stocking effects on population genetics of Tennessee Brook Trout","interactions":[],"lastModifiedDate":"2022-03-28T16:36:37.268059","indexId":"70227180","displayToPublicDate":"2022-01-04T10:26:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Landscape and stocking effects on population genetics of Tennessee Brook Trout","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Throughout their range, Brook Trout (<i>Salvelinus fontinalis</i>) occupy thousands of disjunct drainages with varying levels of disturbance, which presents substantial challenges for conservation. Within the southern Appalachian Mountains, fragmentation and genetic drift have been identified as key threats to the genetic diversity of the Brook Trout populations. In addition, extensive historic stocking of domestic lineages of Brook Trout to augment fisheries may have eroded endemic diversity and impacted locally adapted populations. We used 12 microsatellite loci to describe patterns of genetic diversity within 108 populations of wild Brook Trout from Tennessee and used linear models to explore the impacts of land use, drainage area, and hatchery stockings on metrics of genetic diversity, effective population size, and hatchery introgression. We found levels of within-population diversity varied widely, although many populations showed very limited diversity. The extent of hatchery introgression also varied across the landscape, with some populations showing high affinity to hatchery lineages and others appearing to retain their endemic character. However, we found relatively weak relationships between genetic metrics and landscape characteristics, suggesting that contemporary landscape variables are not strongly related to observed patterns of genetic diversity. We consider this result to reflect both the complex history of these populations and the challenges associated with accurately defining drainages for each population. Our study highlights the importance of genetic data to guide management decisions, as complex processes interact to shape the genetic structure of populations and make it difficult to infer the status of unsampled populations.</p></div></div><div id=\"cobranding-and-download-availability-text\" class=\"note test-pdf-link\"><br></div>","language":"English","publisher":"Springer","doi":"10.1007/s10592-021-01404-8","usgsCitation":"Hargrove, J.S., Kazyak, D.C., Lubinski, B.A., Rogers, K., Bowers, O.K., Fesenmyer, K.A., Habera, J.W., and Henegar, J., 2022, Landscape and stocking effects on population genetics of Tennessee Brook Trout: Conservation Genetics, v. 23, p. 341-357, https://doi.org/10.1007/s10592-021-01404-8.","productDescription":"17 p.","startPage":"341","endPage":"357","ipdsId":"IP-124760","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":393865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.4903564453125,\n              35.26804693351555\n            ],\n            [\n              -84.2486572265625,\n              35.106428057364255\n            ],\n            [\n              -81.6888427734375,\n              36.27527883184338\n            ],\n            [\n              -81.650390625,\n              36.619936625629215\n            ],\n            [\n              -81.968994140625,\n              36.6640126988417\n            ],\n            [\n              -84.0399169921875,\n              35.764343479667176\n            ],\n            [\n              -84.4903564453125,\n              35.26804693351555\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2021-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Hargrove, John S.","contributorId":270750,"corporation":false,"usgs":false,"family":"Hargrove","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":56209,"text":"Tennessee Tech University","active":true,"usgs":false}],"preferred":false,"id":829957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":829958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":829959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogers, Karli M. 0000-0002-6188-7405","orcid":"https://orcid.org/0000-0002-6188-7405","contributorId":205635,"corporation":false,"usgs":true,"family":"Rogers","given":"Karli M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":829960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowers, Olivia K.","contributorId":270751,"corporation":false,"usgs":false,"family":"Bowers","given":"Olivia","email":"","middleInitial":"K.","affiliations":[{"id":56209,"text":"Tennessee Tech University","active":true,"usgs":false}],"preferred":false,"id":829961,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fesenmyer, Kurt A.","contributorId":214341,"corporation":false,"usgs":false,"family":"Fesenmyer","given":"Kurt","email":"","middleInitial":"A.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":830108,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Habera, Jim W.","contributorId":270752,"corporation":false,"usgs":false,"family":"Habera","given":"Jim","email":"","middleInitial":"W.","affiliations":[{"id":13408,"text":"Tennessee Wildlife Resources Agency","active":true,"usgs":false}],"preferred":false,"id":829962,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Henegar, Jason","contributorId":236865,"corporation":false,"usgs":false,"family":"Henegar","given":"Jason","email":"","affiliations":[{"id":13408,"text":"Tennessee Wildlife Resources Agency","active":true,"usgs":false}],"preferred":false,"id":829963,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70230706,"text":"70230706 - 2022 - Extensive species diversification and marked geographic phylogenetic structure in the Mesoamerican genus Stenopelmatus (Orthoptera: Stenopelmatidae: Stenopelmatinae) revealed by mitochondrial and nuclear 3RAD data","interactions":[],"lastModifiedDate":"2022-04-21T11:44:48.585013","indexId":"70230706","displayToPublicDate":"2022-01-04T06:42:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5630,"text":"Invertebrate Systematics","active":true,"publicationSubtype":{"id":10}},"title":"Extensive species diversification and marked geographic phylogenetic structure in the Mesoamerican genus Stenopelmatus (Orthoptera: Stenopelmatidae: Stenopelmatinae) revealed by mitochondrial and nuclear 3RAD data","docAbstract":"<div class=\"journal-abstract green-item\"><p>The Jerusalem cricket subfamily Stenopelmatinae is distributed from south-western Canada through the western half of the United States to as far south as Ecuador. Recently, the generic classification of this subfamily was updated to contain two genera, the western North American<span>&nbsp;</span><i>Ammopelmatus</i>, and the Mexican, and central and northern South American<span>&nbsp;</span><i>Stenopelmatus</i>. The taxonomy of the latter genus was also revised, with 5, 13 and 14 species being respectively validated, declared as nomen dubium and described as new. Despite this effort, the systematics of<span>&nbsp;</span><i>Stenopelmatus</i><span>&nbsp;</span>is still far from complete. Here, we generated sequences of the mitochondrial DNA barcoding locus and performed two distinct DNA sequence-based approaches to assess the species’ limits among several populations of<span>&nbsp;</span><i>Stenopelmatus</i>, with emphasis on populations from central and south-east Mexico. We reconstructed the phylogenetic relationships among representative species of the main clades within the genus using nuclear 3RAD data and carried out a molecular clock analysis to investigate its biogeographic history. The two DNA sequence-based approaches consistently recovered 34 putative species, several of which are apparently undescribed. Our estimates of phylogeny confirmed the recent generic update of Stenopelmatinae and revealed a marked phylogeographic structure within<span>&nbsp;</span><i>Stenopelmatus</i>. Based on our results, we propose the existence of four species-groups within the genus (the<span>&nbsp;</span><i>faulkneri</i>,<span>&nbsp;</span><i>talpa</i>, Central America and<span>&nbsp;</span><i>piceiventris</i><span>&nbsp;</span>species-groups). The geographic distribution of these species-groups and our molecular clock estimates are congruent with the geological processes that took place in mountain ranges along central and southern Mexico, particularly since the Neogene. Our study emphasises the necessity to continue performing more taxonomic and phylogenetic studies on<span>&nbsp;</span><i>Stenopelmatus</i><span>&nbsp;</span>to clarify its actual species richness and evolutionary history in Mesoamerica.</p></div>","language":"English","publisher":"CSIRO","doi":"10.1071/IS21022","usgsCitation":"Gutiérrez, J.S., Zaldivar-Riveron, A., Weissman, D., and Vandergast, A.G., 2022, Extensive species diversification and marked geographic phylogenetic structure in the Mesoamerican genus Stenopelmatus (Orthoptera: Stenopelmatidae: Stenopelmatinae) revealed by mitochondrial and nuclear 3RAD data: Invertebrate Systematics, v. 36, no. 1, 21 p., https://doi.org/10.1071/IS21022.","productDescription":"21 p.","ipdsId":"IP-130796","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":399387,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Gutiérrez, Jorge S.","contributorId":290528,"corporation":false,"usgs":false,"family":"Gutiérrez","given":"Jorge","middleInitial":"S.","affiliations":[{"id":62447,"text":"Universidad Nacional Autónoma de México, Ciudad de México, México","active":true,"usgs":false}],"preferred":false,"id":841192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zaldivar-Riveron, Alejandro","contributorId":290529,"corporation":false,"usgs":false,"family":"Zaldivar-Riveron","given":"Alejandro","email":"","affiliations":[{"id":62448,"text":"Estación Biológica de Doñana (EBD–CSIC), Sevilla, España","active":true,"usgs":false}],"preferred":false,"id":841193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weissman, David B","contributorId":195222,"corporation":false,"usgs":false,"family":"Weissman","given":"David B","affiliations":[],"preferred":false,"id":841194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":841195,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227426,"text":"70227426 - 2022 - Gas hydrates on Alaskan marine margins","interactions":[],"lastModifiedDate":"2022-01-14T16:38:17.536274","indexId":"70227426","displayToPublicDate":"2022-01-01T10:32:18","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Gas hydrates on Alaskan marine margins","docAbstract":"<p><span>Gas hydrate distributions on the marine margins of the U.S. state of Alaska are more poorly known than those on other U.S. margins, where bottom simulating reflections have been systematically mapped on marine seismic data to support modern, quantitative assessments of gas-in-place in gas hydrates. The extent of bottom simulating reflections in the U.S. Beaufort Sea has been known since the late 1970s, and researchers have investigated the possibility that remnant gas hydrate persists in association with decaying subsea permafrost on both the U.S. and Canadian Beaufort continental shelves. In the Bering Sea, possible gas hydrate-related features have been widely mapped, revealing zones of free gas and concentrated gas hydrate within the hydrate stability zone in features called velocity amplitude anomalies (VAMPs). However, there are few reports on bottom simulating reflections along the more than 2500 km of the Aleutian arc and along the transform plate margin in southeast Alaska. Here we examine selected seismic profiles from southeast Alaska, along the Aleutian margin, and on the Bering continental slope, emphasizing surveys acquired with large airgun arrays, and review the results obtained from Bering Sea’s Aleutian Basin and from the U.S. Beaufort Sea. In the new analyses, we detect hydrate-related bottom simulating reflections in southeastern Alaska and the eastern and central parts of the Aleutian arc, but not in the western Aleutian arc or beneath the continental slope from the island arc north into the Aleutian Basin. In the Bering Sea, recognition of hydrate-related bottom simulating reflections is complicated by the widespread existence of a bottom simulating reflector associated with a diagenetic transition (opal CT). Our detection of continental slope hydrate-related bottom simulating reflections in southeast Alaska and the eastern and central Aleutian arcs expands the area of potential gas hydrate distribution on Alaskan margins and underscores the need for more systematic analysis of existing seismic data to inform quantitative evaluation of gas-in-place.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World atlas of submarine gas hydrates in continental margins","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-81186-0_17","usgsCitation":"Ruppel, C.D., and Hart, P.E., 2022, Gas hydrates on Alaskan marine margins, chap. <i>of</i> World atlas of submarine gas hydrates in continental margins, p. 209-223, https://doi.org/10.1007/978-3-030-81186-0_17.","productDescription":"15 p.","startPage":"209","endPage":"223","ipdsId":"IP-122791","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":394384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Sea’s Aleutian basin, U.S. Beaufort Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -159.169921875,\n              69.59589006237648\n            ],\n            [\n              -140.18554687499997,\n              69.59589006237648\n            ],\n            [\n              -140.18554687499997,\n              73.42842364106816\n            ],\n            [\n              -159.169921875,\n              73.42842364106816\n            ],\n            [\n              -159.169921875,\n              69.59589006237648\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -177.01171875,\n              47.87214396888731\n            ],\n            [\n              -153.017578125,\n              47.87214396888731\n            ],\n            [\n              -153.017578125,\n              61.39671887310411\n            ],\n            [\n              -177.01171875,\n              61.39671887310411\n            ],\n            [\n              -177.01171875,\n              47.87214396888731\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationDate":"2022-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":195778,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830833,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70230305,"text":"70230305 - 2022 - Caretta caretta (Loggerhead Sea Turtle) nesting exchange","interactions":[],"lastModifiedDate":"2022-04-07T13:32:18.48214","indexId":"70230305","displayToPublicDate":"2022-01-01T08:27:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"displayTitle":"<i>Caretta caretta</i> (Loggerhead Sea Turtle) nesting exchange","title":"Caretta caretta (Loggerhead Sea Turtle) nesting exchange","docAbstract":"<p>The Northwest Atlantic population of Loggerhead Sea Turtles (<i>Caretta caretta</i>) is one of the largest <i>C. caretta</i> populations in the world and is listed as threatened. This population was divided into five genetically distinct subpopulations, including the Northern Gulf of Mexico (NGoM) subpopulation (Shamblin et al. 2017 Mar. Bio. 164:138). Across the NGoM, the majority of <i>C. caretta</i> nesting occurs in Franklin and Gulf Counties, Florida, USA (Florida Fish and Wildlife Conservation Commission, https://myfwc.com/research/wildlife/sea-turtles/nesting/nesting-atlas/). Few <i>C. caretta</i> nests are documented on Texas, USA, beaches and as such, less is known about the individuals that nest in Texas (see Shaver et al. 2020 Front. Mar. Sci. 7:1, Frandsen et al. 2020 Herp. Review 51:825) as compared to those that nest on beaches in the eastern part of the range (Lamont et al. 2014 Mar. Bio. 161:2659). Although <i>C. caretta</i> individuals have been tracked to Texas from nesting beaches throughout the Southeastern USA (Hart et al. 2014, PLoS One, 9), movements of <i>C. caretta</i> away from Texas beaches are rare. Here we detail the exchange of an adult female <i>C. caretta</i> that emerged and was tagged on the beach in Texas and then subsequently documented nesting in Northwest Florida.</p>","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Lamont, M., Walker, J.S., and Shaver, D.J., 2022, Caretta caretta (Loggerhead Sea Turtle) nesting exchange: Herpetological Review, v. 52, no. 3, p. 626-627.","productDescription":"2 p.","startPage":"626","endPage":"627","ipdsId":"IP-128942","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":398308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.086181640625,\n              26.15543796871355\n            ],\n            [\n              -97.31689453125,\n              27.21555620902969\n            ],\n            [\n              -96.207275390625,\n              28.372068829631633\n            ],\n            [\n              -94.6142578125,\n              29.334298230315675\n            ],\n            [\n              -93.85620117187499,\n              29.69759650228319\n            ],\n            [\n              -94.22973632812499,\n              29.897805610155874\n            ],\n            [\n              -95.020751953125,\n              29.850173125689896\n            ],\n            [\n              -95.44921875,\n              29.152161283318915\n            ],\n            [\n              -96.45996093749999,\n              28.76765910569123\n            ],\n            [\n              -97.03125,\n              28.38173504322308\n            ],\n            [\n              -97.72338867187499,\n              27.332735136859146\n            ],\n            [\n              -97.503662109375,\n              26.086388149394875\n            ],\n            [\n              -97.086181640625,\n              26.15543796871355\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"52","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":206817,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":839927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Jennifer S.","contributorId":289853,"corporation":false,"usgs":false,"family":"Walker","given":"Jennifer","email":"","middleInitial":"S.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":839928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaver, Donna J.","contributorId":191186,"corporation":false,"usgs":false,"family":"Shaver","given":"Donna","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":839929,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70246520,"text":"70246520 - 2022 - Reconstructing the paleoceanographic and redox conditions responsible for variations in uranium content in North American Devonian black shales","interactions":[],"lastModifiedDate":"2023-07-07T12:17:22.507283","indexId":"70246520","displayToPublicDate":"2021-12-27T07:13:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructing the paleoceanographic and redox conditions responsible for variations in uranium content in North American Devonian black shales","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0040\">The uranium (U) content, and more recently, the ratio between<span>&nbsp;</span><sup>238</sup>U and<span>&nbsp;</span><sup>235</sup><span>U in&nbsp;black shales&nbsp;are commonly applied as a proxy to determine&nbsp;redox conditions&nbsp;and infer organic-richness. Uranium contents typically display a linear relationship with&nbsp;total organic carbon&nbsp;(TOC) in shales. This relationship is due to the processes and mechanisms responsible for the incorporation of U into the sediment during the deposition and&nbsp;remineralization&nbsp;of organic matter. This U/TOC relationship can vary, however, and some shales display uncharacteristically low U content despite having high TOC content, while others show large enrichments of U relative to TOC. Here we examine the U to TOC ratios and U-isotope compositions of three Upper Devonian-Lower Mississippian shales: the Woodford Shale, the Cleveland Shale, and the Bakken Shale, with two study sites in Oklahoma, one site in eastern Kentucky, and three sites in eastern Montana and western North Dakota, respectively. The U/TOC ratios of each shale are distinct from one another exhibiting average ratios ranging from 3 in the Cleveland Shale, to over 10 in the Bakken Shale. The distinct geochemical composition of the three shales suggests that, although lithologically similar, each study site represents a markedly different and dynamic&nbsp;depositional environment. The low average U/TOC (~3) along with the relatively high δ</span><sup>238</sup><span>U values (~0.03‰) of the Cleveland Shale core suggests deposition along the basin margin under normal marine conditions with periods of reduced bottom water&nbsp;oxygenation, likely due to fluctuations in the location of the&nbsp;pycnocline. The Woodford Shale on the other hand, shows higher U/TOC ratios (~4, George core, ~9, Poe core) and δ</span><sup>238</sup>U (~0.02‰ average, George core, ~0.06‰ average, Poe core), which suggests an unrestricted setting with intermittent euxinic conditions. In contrast, high U/TOC ratios (2–15), and very high δ<sup>238</sup><span>U values (up to 0.55‰) in the Bakken Shale cores indicate intense metal draw-down into sediments under sulfidic waters. The results show that when the U/TOC ratios and U-isotopic compositions of each studied shale are compared to modern anoxic basins and upwelling areas, it allows for an enhanced understanding of the paleoenvironmental conditions such as basin restriction and redox state of waters within the Late&nbsp;Devonian&nbsp;epicontinental seas&nbsp;of North America.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2021.110763","usgsCitation":"Abshire, M.L., Riedinger, N., Clymer, J.M., Scott, C., Severmann, S., Romaniello, S.J., and Puckette, J.O., 2022, Reconstructing the paleoceanographic and redox conditions responsible for variations in uranium content in North American Devonian black shales: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 587, 110763, 11 p., https://doi.org/10.1016/j.palaeo.2021.110763.","productDescription":"110763, 11 p.","ipdsId":"IP-126011","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":449352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.palaeo.2021.110763","text":"Publisher Index Page"},{"id":418743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"587","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Abshire, Michelle L.","contributorId":316208,"corporation":false,"usgs":false,"family":"Abshire","given":"Michelle","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":877030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riedinger, Natascha","contributorId":316209,"corporation":false,"usgs":false,"family":"Riedinger","given":"Natascha","email":"","affiliations":[],"preferred":false,"id":877031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clymer, John M.","contributorId":316210,"corporation":false,"usgs":false,"family":"Clymer","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":877032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":877033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Severmann, Silke","contributorId":316211,"corporation":false,"usgs":false,"family":"Severmann","given":"Silke","email":"","affiliations":[],"preferred":false,"id":877034,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romaniello, Stephen J.","contributorId":316212,"corporation":false,"usgs":false,"family":"Romaniello","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":877035,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Puckette, James O.","contributorId":316213,"corporation":false,"usgs":false,"family":"Puckette","given":"James","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":877036,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70228290,"text":"70228290 - 2022 - The statistical power to detect regional temporal trends in riverine contaminants in the Chesapeake Bay Watershed, USA","interactions":[],"lastModifiedDate":"2022-02-08T15:19:11.175812","indexId":"70228290","displayToPublicDate":"2021-12-21T09:03:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"The statistical power to detect regional temporal trends in riverine contaminants in the Chesapeake Bay Watershed, USA","docAbstract":"Chemical contamination of riverine ecosystems is largely a result of urbanization, industrialization, and agricultural activities occurring on adjacent terrestrial landscapes. Land management activities (e.g., Best Management Practices) are an important tool used to reduce point and non-point sources of pollution. However, the ability to confidently make inferences about the efficacy of land management activities on reducing in-stream chemical concentrations is poorly understood. We estimated regional temporal trends and components of variation for commonly used herbicides (atrazine and metolachlor), total estrogenicity, and riverine sediment concentrations of total PCBs for rivers in the Chesapeake Bay Watershed, USA. We then used the estimated variance components to perform a power analysis and evaluated the statistical power to detect regional temporal trends under different monitoring scenarios. Scenarios included varying the magnitude of the annual contaminant decline, the number of sites sampled each year, the number of years sampled, and sampling frequency. Monitoring for short time periods (e.g., 5 years) was inadequate for detecting regional temporal trends, regardless of the number of sites sampled or the magnitude of the annual declines. Even when monitoring over a 20-year period, sampling a relatively large number of sites each year was required (e.g., > 50 sites) to achieve adequate statistical power for smaller trend magnitudes (declines of 5 – 7%/year). Annual sampling frequency had little impact on power for any monitoring scenario. All sampling scenarios were underpowered for sediment total PCBs. Power was greatest for total estrogenicity, suggesting that this aggregate measure of estrogenic activity may be a useful indicator. This study provides information that can be used to help (1) guide the development of monitoring programs aimed at detecting regional declines in riverine chemical contaminant concentrations in response to land management actions, and (2) set expectations for the ability to detect changes over time.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.152435","usgsCitation":"Wagner, T., McLaughlin, P., Smalling, K., Breitmeyer, S.E., Gordon, S.E., and Noe, G.E., 2022, The statistical power to detect regional temporal trends in riverine contaminants in the Chesapeake Bay Watershed, USA: Science of the Total Environment, v. 812, 152435, 10 p., https://doi.org/10.1016/j.scitotenv.2021.152435.","productDescription":"152435, 10 p.","ipdsId":"IP-133554","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":449382,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.152435","text":"Publisher Index Page"},{"id":395615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.1904296875,\n              38.41916639395372\n            ],\n            [\n              -75.223388671875,\n              38.64261790634527\n            ],\n            [\n              -75.35522460937499,\n              38.79690830348427\n           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-76.893310546875,\n              36.932330061503144\n            ],\n            [\n              -76.871337890625,\n              36.83566824724438\n            ],\n            [\n              -76.849365234375,\n              36.677230602346214\n            ],\n            [\n              -76.7724609375,\n              36.527294814546245\n            ],\n            [\n              -76.629638671875,\n              36.55377524336089\n            ],\n            [\n              -76.46484375,\n              36.589068371399115\n            ],\n            [\n              -76.35498046875,\n              36.48314061639213\n            ],\n            [\n              -76.256103515625,\n              36.57142382346277\n            ],\n            [\n              -76.190185546875,\n              36.66841891894786\n            ],\n            [\n              -76.0693359375,\n              36.65079252503471\n            ],\n            [\n              -75.9375,\n              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]\n}","volume":"812","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaughlin, Paul","contributorId":275082,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Paul","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":833618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Breitmeyer, Sara E. 0000-0003-0609-1559 sbreitmeyer@usgs.gov","orcid":"https://orcid.org/0000-0003-0609-1559","contributorId":172622,"corporation":false,"usgs":true,"family":"Breitmeyer","given":"Sara","email":"sbreitmeyer@usgs.gov","middleInitial":"E.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":833620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":833621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":833622,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226977,"text":"70226977 - 2022 - Genetic variation in sea otters (Enhydra lutris) from the North Pacific with relevance to the threatened Southwest Alaska Distinct Population Segment","interactions":[],"lastModifiedDate":"2022-07-07T16:30:36.665143","indexId":"70226977","displayToPublicDate":"2021-12-20T07:25:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2671,"text":"Marine Mammal Science","active":true,"publicationSubtype":{"id":10}},"title":"Genetic variation in sea otters (Enhydra lutris) from the North Pacific with relevance to the threatened Southwest Alaska Distinct Population Segment","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>For the sea otter (<i>Enhydra lutris</i>), genetic population structure is an area of research that has not received significant attention, especially in Southwest Alaska where that distinct population segment has been listed as threatened since 2005 pursuant to the U.S. Endangered Species Act. In this study, 501 samples from 14 locations from Prince William Sound, Alaska to the Commander Islands in Russia were analyzed for variation at 13 microsatellite loci. Our results indicate a high degree of genetic divergence among the 14 locations (<i>F</i><sub>ST</sub>&nbsp;=&nbsp;0.120) with gene flow conforming to the isolation by distance (IBD) model (<i>r</i><sup><i>2</i></sup>&nbsp;=&nbsp;0.491,<span>&nbsp;</span><i>p</i> &lt; .05). The 14 sampling locations formed six geographic associations in clustering and ordination analyses that likely correspond to remnant population lineages: (1) Southcentral Alaska, (2) Kodiak and North Alaska Peninsula, (3) South Alaska Peninsula and Bristol Bay, (4) Eastern Aleutian, (5) Western Aleutian, and (6) the Commander Islands. Except for South Alaska Peninsula and Bristol Bay, these clusters closely agree with previously defined stock and management unit boundaries. Our results reveal significant genetic population structure and are generally congruent with current management strategies for the threatened Southwest Alaska distinct population segment.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/mms.12899","usgsCitation":"Flannery, B.G., Russ, O.L., St. Martin, M., Beatty, W.S., Worman, K., Garlich-Miller, J., Gill, V., Lemons, P.R., Monson, D., Kloecker, K.A., Esler, D., and Wenburg, J., 2022, Genetic variation in sea otters (Enhydra lutris) from the North Pacific with relevance to the threatened Southwest Alaska Distinct Population Segment: Marine Mammal Science, v. 38, no. 3, p. 858-880, https://doi.org/10.1111/mms.12899.","productDescription":"23 p.","startPage":"858","endPage":"880","ipdsId":"IP-118770","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":488539,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/mms.12899","text":"Publisher Index Page"},{"id":393350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -153.23730468749997,\n              59.17592824927136\n            ],\n            [\n              -153.06152343749997,\n              59.19843857520702\n            ],\n            [\n              -154.02832031249997,\n              59.57885104663186\n            ],\n            [\n              -156.26953124999997,\n              59.4227275008145\n            ],\n            [\n              -157.54394531249997,\n              58.90464570301998\n            ],\n            [\n              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Michelle","contributorId":189169,"corporation":false,"usgs":false,"family":"St. Martin","given":"Michelle","affiliations":[],"preferred":false,"id":829041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":146301,"corporation":false,"usgs":false,"family":"Beatty","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":829042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Worman, Kristen","contributorId":270331,"corporation":false,"usgs":false,"family":"Worman","given":"Kristen","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":829043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garlich-Miller, Joel","contributorId":270332,"corporation":false,"usgs":false,"family":"Garlich-Miller","given":"Joel","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":829044,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gill, Verena A.","contributorId":140658,"corporation":false,"usgs":false,"family":"Gill","given":"Verena A.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":829045,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lemons, Patrick R.","contributorId":192738,"corporation":false,"usgs":false,"family":"Lemons","given":"Patrick","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":829046,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Monson, Daniel 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":196670,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":829047,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kloecker, Kimberly A. 0000-0002-2461-968X kkloecker@usgs.gov","orcid":"https://orcid.org/0000-0002-2461-968X","contributorId":3442,"corporation":false,"usgs":true,"family":"Kloecker","given":"Kimberly","email":"kkloecker@usgs.gov","middleInitial":"A.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":829048,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":829049,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wenburg, John","contributorId":199672,"corporation":false,"usgs":false,"family":"Wenburg","given":"John","affiliations":[],"preferred":false,"id":829050,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70227053,"text":"70227053 - 2022 - Effects of stream intermittency on minnow (Leuciscidae) and darter (Percidae) trophic dynamics in an agricultural watershed","interactions":[],"lastModifiedDate":"2022-06-16T15:11:44.759721","indexId":"70227053","displayToPublicDate":"2021-12-19T08:41:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9968,"text":"Ecology of Freshwater Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Effects of stream intermittency on minnow (Leuciscidae) and darter (Percidae) trophic dynamics in an agricultural watershed","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Stream intermittency is predicted to increase where water withdrawals and climate warming are increasing. In regions coupled with high fish diversity, understanding how intermittency influences fish trophic ecology is critical for informing ecosystem function. This study compared fish diets across seasons in perennial and intermittent streams to estimate the immediate and cumulative effects of stream drying on fish foraging patterns. We used gut content analysis to compare the diets of small-bodied, secondary consumer fishes, including two minnow and three darter species found in the lower Flint River Basin of southwestern Georgia, during both the summer (before stream dry-down) and fall (post flow resumption) seasons. Fish communities in perennial streams had greater diet richness compared to fishes in intermittent streams for both seasons. Darter diets were characterised by rheophilic aquatic insects in perennial streams and by benthic crustaceans (copepods, cladocerans and isopods) and predatory aquatic insects in intermittent streams. Minnow diets were typified by freshwater sponges, eggs and organic detritus in intermittent streams and by terrestrial insects and diatoms in perennial streams. Fishes in intermittent streams consumed significantly more benthic crustaceans in the fall (37% increase in proportional volume) compared to preflow cessation conditions in the summer, suggesting these organisms play an important, yet relatively unrecognised role in supporting fish communities in southeastern streams. Our findings enhance our understanding of how stream intermittency influences the trophic dynamics of secondary consumer fishes in an agricultural watershed increasingly affected by water scarcity.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/eff.12649","usgsCitation":"Fallon, C.E., Capps, K., Freeman, M., Smith, C.R., and Golladay, S.W., 2022, Effects of stream intermittency on minnow (Leuciscidae) and darter (Percidae) trophic dynamics in an agricultural watershed: Ecology of Freshwater Fishes, v. 31, no. 3, p. 544-558, https://doi.org/10.1111/eff.12649.","productDescription":"15 p.","startPage":"544","endPage":"558","ipdsId":"IP-132426","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":393496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.957275390625,\n              31.11879439598953\n            ],\n            [\n              -83.91357421875,\n              31.11879439598953\n            ],\n            [\n              -83.91357421875,\n              32.05464469054932\n            ],\n            [\n              -84.957275390625,\n              32.05464469054932\n            ],\n            [\n              -84.957275390625,\n              31.11879439598953\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Fallon, Christine E.","contributorId":270489,"corporation":false,"usgs":false,"family":"Fallon","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":829398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capps, Krista A.","contributorId":270490,"corporation":false,"usgs":false,"family":"Capps","given":"Krista A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":829399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":829400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Chelsea R.","contributorId":270491,"corporation":false,"usgs":false,"family":"Smith","given":"Chelsea","email":"","middleInitial":"R.","affiliations":[{"id":56171,"text":"The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":829401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Golladay, Stephen W.","contributorId":223819,"corporation":false,"usgs":false,"family":"Golladay","given":"Stephen","email":"","middleInitial":"W.","affiliations":[{"id":37541,"text":"Joseph W. Jones Ecological Research Center","active":true,"usgs":false}],"preferred":false,"id":829402,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226875,"text":"70226875 - 2022 - Using fish community and population indicators to assess the biological condition of streams and rivers of the Chesapeake Bay watershed, USA","interactions":[],"lastModifiedDate":"2021-12-20T12:06:31.635434","indexId":"70226875","displayToPublicDate":"2021-12-16T08:59:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Using fish community and population indicators to assess the biological condition of streams and rivers of the Chesapeake Bay watershed, USA","docAbstract":"<p><span>The development of indicators to assess relative freshwater condition is critical for management and conservation. Predictive modeling can enhance the utility of indicators by providing estimates of condition for unsurveyed locations.</span><span>&nbsp;</span><span>Such approaches grant understanding of where “good” and “poor” conditions occur and provide insight into landscape contexts supporting such conditions. However, as assessments are conducted at large extents crossing jurisdictional boundaries, combined datasets are likely not suited for traditional assessment approaches which rely on jurisdictionally-specific reference sites. Here, we used a large dataset compiled from multiple providers to assess the condition of fish habitat for non-tidal streams and rivers in the Chesapeake Bay watershed</span><span>&nbsp;</span><span>(CBW), USA. We concurrently used community and species-level analyses to provide a more holistic view of habitat conditions by using random forest</span><span>&nbsp;</span><span>models</span><span>&nbsp;</span><span>to predict</span><span>&nbsp;</span><span>selected</span><span>&nbsp;</span><span>metrics</span><span>&nbsp;</span><span>and species occurrence with landscape data for</span><span>&nbsp;</span><span>inland CBW stream reaches.</span><span>&nbsp;</span><span>Community analyses included metrics describing composition, tolerances, habitat preferences, and functional traits of fish communities whereas species-level analyses consisted of distribution models for key sensitive and gamefish species. For community analyses, a final index was calculated as the average of</span><span>&nbsp;</span><span>selected</span><span>&nbsp;</span><span>metric deciles</span><span>&nbsp;</span><span>with higher scores inferring</span><span>&nbsp;</span><span>less biologically altered (i.e., better) conditions, providing an alternative to using reference sites.</span><span>&nbsp;</span><span>For species analyses, species occurrence was predicted</span><span>&nbsp;</span><span>for</span><span>&nbsp;</span><span>stream reaches, with presence indicating suitable habitat. Uncertainty was calculated for both approaches using model prediction intervals.</span><span>&nbsp;</span><span>Results indicated different numbers of suitable metrics for each region,</span><span>&nbsp;</span><span>with most in the Northern Appalachian (15) and least in the Southern Appalachian Piedmont (3). Four species</span><span>&nbsp;</span><span>(three sensitive)</span><span>&nbsp;</span><span>were suitable for modeling.</span><span>&nbsp;</span><span>At the CBW scale, predictions</span><span>&nbsp;</span><span>did not vary</span><span>&nbsp;</span><span>greatly</span><span>&nbsp;</span><span>among deciles</span><span>&nbsp;</span><span>for the community or species analyses for 2001, 2006, 2011, and 2016. Most stream reaches did not vary in mean decile rank or in species occurrence between 2001 and 2016; however, the largest community changes occurred in large rivers in the Coastal Plains</span><span>&nbsp;</span><span>ecoregion and the largest species occurrence changes occurred in Torrent Suckers in medium-sized rivers. When compared, results from community analyses agreed for one</span><span>&nbsp;</span><span>sensitive</span><span>&nbsp;</span><span>species (Brook Trout) but not</span><span>&nbsp;</span><span>the other three, potentially due to regionally inappropriate tolerance assignment. Comparisons also demonstrated substantial variation among approaches suggesting a lack of redundancy. While each approach traditionally has its targeted audience and respective strengths and weaknesses, concurrent use of these approaches permits direct comparisons and may assuage shortcomings of each approach when considered separately.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.108488","usgsCitation":"Maloney, K.O., Krause, K.P., Cashman, M.J., Daniel, W., Gressler, B.P., Wieferich, D.J., and Young, J.A., 2022, Using fish community and population indicators to assess the biological condition of streams and rivers of the Chesapeake Bay watershed, USA: Ecological Indicators, v. 134, 108488, 17 p., https://doi.org/10.1016/j.ecolind.2021.108488.","productDescription":"108488, 17 p.","ipdsId":"IP-133787","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research 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The U.S. Federal Government owns or holds in trust about 259 million hectares of land, in addition to the Trust species obligations. We completed the first comprehensive review of potential toxin-producing algal blooms in surface waters on Federal lands and Trust species exposed to algal toxins. Events were sorted into three tiers based on potentially toxic algae abundance or toxin concentration and related effects on animal morbidity and mortality. At least 11.1% of Federal lands are known to have been affected by algal events, but exposure is likely underreported. The occurrence of potential toxin producers and their toxins (Tier 1) have been documented 337 times, health advisory threshold exceedances (Tier 2) were reported 943 times, and 86 events involved animal sickness or death linked to cyanobacteria or marine toxins (Tier 3). Trust species exposed to cyano- or algal toxins included marine mammals, migratory birds, threatened and endangered species, and species of concern. We report numerous data gaps ranging from potential effects on human health from consuming intoxicated animals to the infrequency of measuring and reporting certain toxins. Improvements to field and laboratory methods, more consistent evaluation of toxin exposure, decreased latency on data analysis, delivery and interpretation will be necessary to improve response and management strategies for protecting human and animal health where issues persist.</p></div></div>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/10643389.2021.2010511","usgsCitation":"Laughrey, Z.R., Christensen, V., Dusek, R.J., Senegal, S., Lankton, J.S., Ziegler, T., Jones, L.C., Jones, D.K., Williams, B., Gordon, S.E., Clyde, G.A., Emery, E.B., and Loftin, K.A., 2022, A review of algal toxin exposures on reserved federal lands and among trust species in the United States: Critical Reviews in Environmental Science and Technology, v. 52, no. 23, p. 4284-4307, https://doi.org/10.1080/10643389.2021.2010511.","productDescription":"24 p.","startPage":"4284","endPage":"4307","ipdsId":"IP-114198","costCenters":[{"id":242,"text":"Eastern Geographic Science 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,{"id":70226749,"text":"70226749 - 2022 - Seismotectonic analysis of the 2019–2020 Puerto Rico sequence: The value of absolute earthquake relocations in improved interpretations of active tectonics","interactions":[],"lastModifiedDate":"2022-03-15T16:32:42.300614","indexId":"70226749","displayToPublicDate":"2021-12-08T06:37:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Seismotectonic analysis of the 2019–2020 Puerto Rico sequence: The value of absolute earthquake relocations in improved interpretations of active tectonics","docAbstract":"<p><span>We present a new catalog of calibrated earthquake relocations from the 2019–2020 Puerto Rico earthquake sequence related to the 7 January 2020&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=\"><i>M</i><sub>w</sub></span></span><span> 6.4 earthquake that occurred offshore of southwest Puerto Rico at a depth of 15.9&nbsp;km. Utilizing these relocated earthquakes and associated moment tensor solutions, we can delineate several distinct fault systems that were activated during the sequence and show that the <span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=\"><i>M</i><sub>w</sub></span></span></span><span> 6.4 mainshock may have resulted from positive changes in Coulomb stress from earlier events. Seismicity and mechanisms define (1)&nbsp;a west–southwest (∼260°) zone of seismicity comprised of largely sinistral strike‐slip and oblique‐slip earthquakes that mostly occurs later in the sequence and to the west of the mainshock, (2)&nbsp;an area of extensional faulting that includes the mainshock and occurs largely within the mainshock’s rupture area, and (3)&nbsp;an north–northeast (∼30°)‐striking zone of seismicity, consisting primarily of dextral strike‐slip events that occurs before and following the mainshock and generally above (shallower than) the normal‐faulting events. These linear features intersect within the <span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=\"><i>M</i><sub>w</sub></span></span></span><span>&nbsp;6.4 mainshock’s fault plane in southwest Puerto Rico. In addition, we show that earthquake relocations for&nbsp;</span><strong>M</strong><span>&nbsp;4+ normal‐faulting events, when traced along their fault planes, daylight along east–west‐trending bathymetric features offshore of southwest Puerto Rico. Correlation of these normal‐faulting events with bathymetric features suggests an active fault system that may be a contributor to previously uncharacterized seismic hazards in southwest Puerto Rico.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210238","usgsCitation":"Cromwell, C., Furlong, K., Bergman, E., Benz, H.M., Yeck, W.L., and Herman, M., 2022, Seismotectonic analysis of the 2019–2020 Puerto Rico sequence: The value of absolute earthquake relocations in improved interpretations of active tectonics: Seismological Research Letters, v. 93, no. 2A, p. 544-554, https://doi.org/10.1785/0220210238.","productDescription":"11 p.","startPage":"544","endPage":"554","ipdsId":"IP-134220","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":449446,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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,{"id":70226719,"text":"70226719 - 2022 - Review of ESA SYMP 7: A dynamic perspective on ecosystem restoration–establishing temporal connectivity at the intersection between paleoecology and restoration ecology","interactions":[],"lastModifiedDate":"2022-01-25T17:28:32.758596","indexId":"70226719","displayToPublicDate":"2021-11-27T06:56:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9941,"text":"Bulletin Ecological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Review of ESA SYMP 7: A dynamic perspective on ecosystem restoration–establishing temporal connectivity at the intersection between paleoecology and restoration ecology","docAbstract":"Landscape connectivity is vital not only spatially, but also temporally; as ecosystems change, it is important to be aware of past, present, and future variables that may impact ecosystem function and biodiversity. As climate and environments continue to change, choosing appropriate restoration targets is becoming more challenging. By considering the paleoecological and paleoenvironmental record for a given region, restoration practitioners are not only able to bear witness to that region’s dynamic history, but also potentially identify multiple, alternative natural ecosystem states. Indeed, one of the deliverables of conservation paleobiology, a field that applies paleontological data and methods to present-day conservation, is to inform restoration targets. Consideration of future change is equally important, and paleoecological and paleoclimatological data are essential for informing models that can help us understand how climate change is affecting species and ecosystems at different temporal scales. The symposium “A dynamic perspective on ecosystem restoration: Establishing temporal\nconnectivity at the intersection between paleoecology and restoration ecology” gathered representatives from macroecology, paleoecology, and restoration ecology to share their perspectives on temporal connectivity and how consideration of an ecosystem’s past, present, and future can positively impact restoration and conservation. Some speakers approached the topic theoretically, while others considered it from a more practical and applied standpoint. The goals of the symposium were to build a stronger relationship among the subdisciplines, stimulate new ideas, and identify data and/or products that would be useful to share across subdisciplines.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/bes2.1954","usgsCitation":"Reid, R., McGuire, J., Svenning, J., Wingard, G.L., and Moreno-Mateos, D., 2022, Review of ESA SYMP 7: A dynamic perspective on ecosystem restoration–establishing temporal connectivity at the intersection between paleoecology and restoration ecology: Bulletin Ecological Society of America, v. 103, no. 1, e01954, 6 p., https://doi.org/10.1002/bes2.1954.","productDescription":"e01954, 6 p.","ipdsId":"IP-134688","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":467212,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/bes2.1954","text":"External Repository"},{"id":392566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Reid, Rachel","contributorId":269802,"corporation":false,"usgs":false,"family":"Reid","given":"Rachel","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":827949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Jenny","contributorId":269803,"corporation":false,"usgs":false,"family":"McGuire","given":"Jenny","email":"","affiliations":[{"id":56035,"text":"GA Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":827950,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Svenning, Jens-Christiane","contributorId":269804,"corporation":false,"usgs":false,"family":"Svenning","given":"Jens-Christiane","email":"","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":827951,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":827952,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moreno-Mateos, David","contributorId":269806,"corporation":false,"usgs":false,"family":"Moreno-Mateos","given":"David","email":"","affiliations":[{"id":16810,"text":"Harvard Univ.","active":true,"usgs":false}],"preferred":false,"id":827953,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227326,"text":"70227326 - 2022 - Factors Affecting Groundwater Quality Used for Domestic Supply in Marcellus Shale Region of North-Central and North-East Pennsylvania, USA","interactions":[],"lastModifiedDate":"2022-01-10T12:59:36.251299","indexId":"70227326","displayToPublicDate":"2021-11-24T06:56:57","publicationYear":"2022","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":"Factors Affecting Groundwater Quality Used for Domestic Supply in Marcellus Shale Region of North-Central and North-East Pennsylvania, USA","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>Factors affecting groundwater quality used for domestic supply within the Marcellus Shale footprint in north-central and north-east Pennsylvania are identified using a combination of spatial, statistical, and geochemical modeling. Untreated groundwater, sampled during 2011–2017 from 472 domestic wells within the study area, exhibited wide ranges in pH (4.5–9.3), total dissolved solids (TDS, 22–1960&nbsp;mg/L), sodium (0.3–760&nbsp;mg/L), chloride (0.3–1020&nbsp;mg/L), bromide (&lt;0.01–8.6&nbsp;mg/L), and methane (&lt;0.001–77&nbsp;mg/L). The wells had depths ranging from 10 to 394&nbsp;m; 69.5 percent were completed in&nbsp;sandstone&nbsp;bedrock, 19.3 percent in shale, 4.2 percent in&nbsp;siltstone, 4 percent in carbonate, and 3 percent in unconsolidated alluvial or glacial deposits. Groundwater quality in the Delaware River watershed, in the eastern part of the study area where Marcellus gas has not been developed, was similar to that in the Susquehanna, Allegheny, and Genesee River watersheds in the western part of the study area where&nbsp;natural gas production&nbsp;from Marcellus Shale has been ongoing since 2008. Most groundwaters were calcium/bicarbonate type with near-neutral pH; approximately 10 percent were sodium/bicarbonate and 1 percent were sodium/chloride types. Sodium-enriched waters, which were mostly from shale and siltstone aquifers, had the greatest frequency of elevated pH (&gt;8.5) and elevated concentrations of TDS (&gt;250&nbsp;mg/L), bromide (&gt;0.15&nbsp;mg/L), methane (&gt;7.0&nbsp;mg/L), and lithium (&gt;60&nbsp;μg/L). Geochemical models indicate these characteristics could result from progressive mineral dissolution combined with cation exchange, plus mixing with locally important&nbsp;salinity&nbsp;sources, including as much as 0.7 percent Appalachian Basin brine and/or road-deicing salt. Multivariate correlation models suggest the observed variability in methane concentrations may be attributed to several environmental factors, such as geochemical evolution along&nbsp;groundwater flow&nbsp;paths,&nbsp;redox conditions, and/or mixing with saline groundwater or brine. Most samples having elevated methane were from shale aquifers, which were mainly in the Susquehanna River basin and had the greatest density of gas wells compared to other&nbsp;</span>lithologies<span>. Samples having elevated methane were also observed in the Delaware River watershed and other areas outside gas development.&nbsp;Isotopic compositions&nbsp;of methane for a subset of 39 samples (selected because of elevated methane) and relatively high ratios of methane to ethane in those samples indicated methane could be derived from microbial gas mixed with thermogenic gas that may have undergone degradation and/or fractionation during migration. The methods used in this study could be broadly applicable to understanding major factors affecting groundwater quality, particularly for explaining variations in&nbsp;ionic composition&nbsp;with pH and identifying sources of salinity and associated constituents (e.g. sodium, chloride, bromide, lithium, methane) that may have geogenic or anthropogenic origins.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2021.105149","usgsCitation":"Cravotta, C., Senior, L.A., and Conlon, M.D., 2022, Factors Affecting Groundwater Quality Used for Domestic Supply in Marcellus Shale Region of North-Central and North-East Pennsylvania, USA: Applied Geochemistry, v. 137, 105149, 19 p., https://doi.org/10.1016/j.apgeochem.2021.105149.","productDescription":"105149, 19 p.","ipdsId":"IP-129093","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":449515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2021.105149","text":"Publisher Index Page"},{"id":394090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Marcellus Shale region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.640625,\n              42.06560675405716\n            ],\n            [\n              -76.728515625,\n              40.91351257612758\n            ],\n            [\n              -75.0146484375,\n              40.94671366508002\n            ],\n            [\n              -74.8828125,\n              41.21172151054787\n            ],\n            [\n              -74.8388671875,\n              41.44272637767212\n            ],\n            [\n              -75.1904296875,\n              42.032974332441405\n            ],\n            [\n              -76.640625,\n              42.06560675405716\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"137","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senior, Lisa A. 0000-0003-2629-1996 lasenior@usgs.gov","orcid":"https://orcid.org/0000-0003-2629-1996","contributorId":2150,"corporation":false,"usgs":true,"family":"Senior","given":"Lisa","email":"lasenior@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conlon, Matthew D. 0000-0001-8266-9610 mconlon@usgs.gov","orcid":"https://orcid.org/0000-0001-8266-9610","contributorId":201291,"corporation":false,"usgs":true,"family":"Conlon","given":"Matthew","email":"mconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830477,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70226953,"text":"70226953 - 2022 - Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States","interactions":[],"lastModifiedDate":"2022-03-15T16:40:05.579972","indexId":"70226953","displayToPublicDate":"2021-11-19T07:08:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Historical mine and mineral deposit datasets are routinely used to inform quantitative mineral assessment models, but they also can contain a wealth of supplementary qualitative information that is generally underutilized. We present a workflow that uses correspondence analysis, an exploratory tool commonly applied to multivariate abundance data, to better utilize qualitative data in these historical datasets. The workflow involves extraction of qualitative information on ore mineralogy from a mineral deposit database, attaches those data to a target geological feature, and analyzes the underlying data structure with correspondence analysis and hierarchical clustering. The output of correspondence analysis is inversely weighted to the relative frequency of ore minerals, and therefore rare mineral species (i.e., those with unusually low frequencies) can disproportionately contribute to the total variance of the dataset. We present a novel technique for aggregating frequencies of rare mineral species that minimizes this effect. We apply this workflow to evaluate how ore mineral assemblages in former and active mines vary in spatial relation to silicic calderas in the southwestern United States. The most common ore mineral associations observed spatially and genetically associated to calderas include those related to polymetallic, base metal-rich systems and epithermal Au–Ag systems. Three other groups of mineralized calderas were identified, including: (1) Hg–Sb mineralized calderas in the northern Great Basin and western Nevada volcanic field; (2) calderas associated with elevated abundances of Mn oxides/hydroxides, fluorite, and Be-minerals, mostly in eastern Utah and New Mexico; and (3) calderas with numerous U ± F deposits, which are located in central Colorado, the eastern Great Basin and in northern Nevada. The latter three groups are associated with economically significant critical mineral resources, including the Li resources of the McDermitt complex and Be associated with the Spor Mountain on the margin of the Thomas caldera complex. We conclude that correspondence analysis is a promising technique that can enhance data exploration of the qualitative information held within mineral deposit datasets. Consequently, it could have numerous applications for mineral potential mapping, resource assessment projects, and characterization of mineral systems.</p></div></div><div id=\"cobranding-and-download-availability-text\" class=\"note test-pdf-link\"><br></div>","language":"English","publisher":"Springer","doi":"10.1007/s11053-021-09963-w","usgsCitation":"Rosera, J.M., and Coleman, D.S., 2022, Correspondence analysis for mineral commodity research: An example workflow for mineralized calderas, southwest United States: Natural Resources Research, v. 31, p. 9-36, https://doi.org/10.1007/s11053-021-09963-w.","productDescription":"28 p.","startPage":"9","endPage":"36","ipdsId":"IP-130118","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":393297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.541015625,\n              31.12819929911196\n            ],\n            [\n              -102.48046875,\n              31.12819929911196\n            ],\n            [\n              -102.48046875,\n              42.16340342422401\n            ],\n            [\n              -124.541015625,\n              42.16340342422401\n            ],\n            [\n              -124.541015625,\n              31.12819929911196\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","noUsgsAuthors":false,"publicationDate":"2021-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosera, Joshua Mark 0000-0003-3807-5000","orcid":"https://orcid.org/0000-0003-3807-5000","contributorId":270284,"corporation":false,"usgs":true,"family":"Rosera","given":"Joshua","email":"","middleInitial":"Mark","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":828923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coleman, Drew S","contributorId":192880,"corporation":false,"usgs":false,"family":"Coleman","given":"Drew","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":828924,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70226494,"text":"70226494 - 2022 - Downhill from Austin and Ely to Las Vegas: U-Pb detrital zircon suites from the Eocene–Oligocene Titus Canyon Formation and associated strata, Death Valley, California","interactions":[],"lastModifiedDate":"2021-11-22T12:31:58.451448","indexId":"70226494","displayToPublicDate":"2021-11-19T06:29:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Downhill from Austin and Ely to Las Vegas: U-Pb detrital zircon suites from the Eocene–Oligocene Titus Canyon Formation and associated strata, Death Valley, California","docAbstract":"<div class=\"widget widget-BookChapterMainView widget-instance-BookChapterMainView\"><div class=\"content-inner-wrap\"><div class=\"book-chapter-body\"><div id=\"ContentTab\" class=\"content active\"><div class=\"widget widget-BookSectionsText widget-instance-BookChaptertext\"><div class=\"module-widget\"><div class=\"widget-items\" data-widgetname=\"BookSectionsText\"><div class=\"category-section content-section js-content-section\" data-statsid=\"131783531\"><p>In a reconnaissance investigation aimed at interrogating the changing topography and paleogeography of the western United States prior to Basin and Range faulting, a preliminary study made use of U-Pb ages of detrital zircon suites from 16 samples from the Eocene–Oligocene Titus Canyon Formation, its overlying units, and correlatives near Death Valley. The Titus Canyon Formation unconformably overlies Neoproterozoic to Devonian strata in the Funeral and Grapevine Mountains of California and Nevada. Samples were collected from (1) the type area in Titus Canyon, (2) the headwaters of Monarch Canyon, and (3) unnamed Cenozoic strata exposed in a klippe of the Boundary Canyon fault in the central Funeral Mountains. Red beds and conglomerates at the base of the Titus Canyon Formation at locations 1 and 2, which contain previously reported 38–37 Ma fossils, yielded mostly Sierran batholith–age detrital zircons (defined by Triassic, Jurassic, and Cretaceous peaks). Overlying channelized fluvial sandstones, conglomerates, and minor lacustrine shale, marl, and limestone record an abrupt change in source region around 38–36 Ma or slightly later, from more local, Sierran arc–derived sediment to extraregional sources to the north. Clasts of red radiolarian-bearing chert, dark radiolarian chert, and quartzite indicate sources in the region of the Golconda and Roberts Mountains allochthons of northern Nevada. Sandstones intercalated with conglomerate contain increasing proportions of Cenozoic zircon sourced from south-migrating, caldera-forming eruptions at the latitude of Austin and Ely in Nevada with maximum depositional ages (MDAs) ranging from 36 to 24 Ma at the top of the Titus Canyon Formation. Carbonate clasts and ash-rich horizons become more prevalent in the overlying conglomeratic Panuga Formation (which contains a previously dated 15.7 Ma ash-flow tuff). The base of the higher, ash-dominated Wahguyhe Formation yielded a MDA of 14.4 Ma. The central Funeral Mountains section exposes a different sequence of units that, based on new data, are correlative to the Titus Canyon, Panuga, and Wahguyhe Formations at locations 1 and 2. An ash-flow tuff above its (unexposed) base provided a MDA of 34 Ma, and the youngest sample yielded a MDA of 12.7 Ma. The striking differences between age-correlative sections, together with map-based evidence for channelization, indicate that the Titus Canyon Formation and overlying units likely represent fluvial channel, floodplain, and lacustrine deposits as sediments mostly bypassed the region, moving south toward the Paleogene shoreline in the Mojave Desert. The profound changes in source regions and sedimentary facies documented in the Titus Canyon Formation took place during ignimbrite flareup magmatism and a proposed eastward shift of the continental divide from the axis of the Cretaceous arc to a new divide in central Nevada in response to thermal uplift and addition of magma to the crust. This uplift initiated south-flowing fluvial systems that supplied sediments to the Titus Canyon Formation and higher units.</p></div></div></div></div></div></div></div></div>","language":"English","publisher":"Geological Society of America","doi":"10.1130/2021.2555(14)","usgsCitation":"Miller, E.L., Raftrey, M., and Lundstern, J., 2022, Downhill from Austin and Ely to Las Vegas: U-Pb detrital zircon suites from the Eocene–Oligocene Titus Canyon Formation and associated strata, Death Valley, California: GSA Special Papers, v. 555, no. 14, 20 p., https://doi.org/10.1130/2021.2555(14).","productDescription":"20 p.","ipdsId":"IP-120514","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":449529,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1130/spe.s.16850284","text":"External Repository"},{"id":391968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.4091796875,\n              31.052933985705163\n            ],\n            [\n              -108.544921875,\n              31.052933985705163\n            ],\n            [\n              -108.544921875,\n              42.4234565179383\n            ],\n            [\n              -124.4091796875,\n              42.4234565179383\n            ],\n            [\n              -124.4091796875,\n              31.052933985705163\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"555","issue":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Elizabeth L. 0000-0002-6190-4826","orcid":"https://orcid.org/0000-0002-6190-4826","contributorId":269348,"corporation":false,"usgs":false,"family":"Miller","given":"Elizabeth","email":"","middleInitial":"L.","affiliations":[{"id":55934,"text":"Stanford University Department of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":827104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Raftrey, Mark","contributorId":269420,"corporation":false,"usgs":false,"family":"Raftrey","given":"Mark","email":"","affiliations":[{"id":55934,"text":"Stanford University Department of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":827105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lundstern, Jens-Erik 0000-0003-0000-8013","orcid":"https://orcid.org/0000-0003-0000-8013","contributorId":264189,"corporation":false,"usgs":true,"family":"Lundstern","given":"Jens-Erik","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":827106,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70265770,"text":"70265770 - 2022 - New insights on faulting and intrusion processes during the June 2007, East Rift Zone eruption of Kilauea volcano, Hawai'i","interactions":[],"lastModifiedDate":"2025-04-16T13:17:34.472644","indexId":"70265770","displayToPublicDate":"2021-11-12T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"New insights on faulting and intrusion processes during the June 2007, East Rift Zone eruption of Kilauea volcano, Hawai'i","docAbstract":"<p><span>The East Rift Zone (ERZ) of Kīlauea Volcano, Hawai'i, represents one of the most volcanically active regions in the world. The 2007 Father's Day (FD) dike intrusion, eruption, and accompanying slow-slip event (SSE) has been previously modeled using geodetic data to constrain the geometry of the intrusion and the timing and magnitude of the SSE. Here, we perform inversions of three interferometric synthetic aperture radar (InSAR) datasets and a new intensity offset tracking dataset to assess the effect of integrating intensity cross-correlation offsets into inversion problems and explore additional potential models for the intrusion geometry of the FD event based on this additional data. The overall lowest misfit single Okada model for all datasets opens 2.3&nbsp;m, strikes 73 degrees while dipping sub-vertically at 83 degrees, and extends approximately 2.9&nbsp;km to the ENE and 2.4&nbsp;km downdip. The differences are minor between complex en-echelon distributed Okada and decollement model of (Montgomery-Brown et al., 2010) or 3D-MBEM breaching models including multiple surface breaches and free-slipping decollement movement. Finally, we examine the static Coulomb stress changes for the proposed decollement fault created by our preferred model and a representative model of deep rift opening and find that deep rift zones dilation, not shallow ERZ intrusions, are likely modulating slip on the decollement.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107425","usgsCitation":"Leeburn, J., Wauthier, C., Montgomery-Brown, E.K., and Gonzalez-Santana, J., 2022, New insights on faulting and intrusion processes during the June 2007, East Rift Zone eruption of Kilauea volcano, Hawai'i: Journal of Volcanology and Geothermal Research, v. 421, 107425, 14 p., https://doi.org/10.1016/j.jvolgeores.2021.107425.","productDescription":"107425, 14 p.","ipdsId":"IP-125424","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488262,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107425","text":"Publisher Index Page"},{"id":484584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.2908512348302,\n              19.41341967491155\n            ],\n            [\n              -155.2908512348302,\n              19.401793724963014\n            ],\n            [\n              -155.27525765813795,\n              19.401793724963014\n            ],\n            [\n              -155.27525765813795,\n              19.41341967491155\n            ],\n            [\n              -155.2908512348302,\n              19.41341967491155\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"421","noUsgsAuthors":false,"publicationDate":"2021-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Leeburn, J.","contributorId":353406,"corporation":false,"usgs":false,"family":"Leeburn","given":"J.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":933489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wauthier, C.","contributorId":353409,"corporation":false,"usgs":false,"family":"Wauthier","given":"C.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":933490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Montgomery-Brown, Emily K. 0000-0001-6787-2055","orcid":"https://orcid.org/0000-0001-6787-2055","contributorId":214074,"corporation":false,"usgs":true,"family":"Montgomery-Brown","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":933491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzalez-Santana, J.","contributorId":353412,"corporation":false,"usgs":false,"family":"Gonzalez-Santana","given":"J.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":933492,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70226446,"text":"70226446 - 2022 - Magmatism, migrating topography, and the transition from Sevier shortening to Basin and Range extension, western United States","interactions":[],"lastModifiedDate":"2021-11-19T12:56:53.852331","indexId":"70226446","displayToPublicDate":"2021-11-02T07:06:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Magmatism, migrating topography, and the transition from Sevier shortening to Basin and Range extension, western United States","docAbstract":"<div class=\"widget widget-BookChapterMainView widget-instance-BookChapterMainView\"><div class=\"content-inner-wrap\"><div class=\"book-chapter-body\"><div id=\"ContentTab\" class=\"content active\"><div class=\"widget widget-BookSectionsText widget-instance-BookChaptertext\"><div class=\"module-widget\"><div class=\"widget-items\" data-widgetname=\"BookSectionsText\"><div class=\"category-section content-section js-content-section\" data-statsid=\"131715784\"><p>The paleogeographic evolution of the western U.S. Great Basin from the Late Cretaceous to the Cenozoic is critical to understanding how the North American Cordillera at this latitude transitioned from Mesozoic shortening to Cenozoic extension. According to a widely applied model, Cenozoic extension was driven by collapse of elevated crust supported by crustal thicknesses that were potentially double the present ~30–35 km. This model is difficult to reconcile with more recent estimates of moderate regional extension (≤50%) and the discovery that most high-angle, Basin and Range faults slipped rapidly ca. 17 Ma, tens of millions of years after crustal thickening occurred. Here, we integrated new and existing geochronology and geologic mapping in the Elko area of northeast Nevada, one of the few places in the Great Basin with substantial exposures of Paleogene strata. We improved the age control for strata that have been targeted for studies of regional paleoelevation and paleoclimate across this critical time span. In addition, a regional compilation of the ages of material within a network of middle Cenozoic paleodrainages that developed across the Great Basin shows that the age of basal paleovalley fill decreases southward roughly synchronous with voluminous ignimbrite flareup volcanism that swept south across the region ca. 45–20 Ma. Integrating these data sets with the regional record of faulting, sedimentation, erosion, and magmatism, we suggest that volcanism was accompanied by an elevation increase that disrupted drainage systems and shifted the continental divide east into central Nevada from its Late Cretaceous location along the Sierra Nevada arc. The north-south Eocene–Oligocene drainage divide defined by mapping of paleovalleys may thus have evolved as a dynamic feature that propagated southward with magmatism. Despite some local faulting, the northern Great Basin became a vast, elevated volcanic tableland that persisted until dissection by Basin and Range faulting that began ca. 21–17 Ma. Based on this more detailed geologic framework, it is unlikely that Basin and Range extension was driven by Cretaceous crustal overthickening; rather, preexisting crustal structure was just one of several factors that that led to Basin and Range faulting after ca. 17 Ma—in addition to thermal weakening of the crust associated with Cenozoic magmatism, thermally supported elevation, and changing boundary conditions. Because these causal factors evolved long after crustal thickening ended, during final removal and fragmentation of the shallowly subducting Farallon slab, they are compatible with normal-thickness (~45–50 km) crust beneath the Great Basin prior to extension and do not require development of a strongly elevated, Altiplano-like region during Mesozoic shortening.</p></div></div></div></div></div></div></div></div>","language":"English","publisher":"Geological Society of America","doi":"10.1130/2021.2555(13)","usgsCitation":"Lundstern, J., and Miller, E.L., 2022, Magmatism, migrating topography, and the transition from Sevier shortening to Basin and Range extension, western United States: GSA Special Papers, v. 555, no. 13, 23 p., https://doi.org/10.1130/2021.2555(13).","productDescription":"23 p.","ipdsId":"IP-120370","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":449564,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/essoar.10502328.1","text":"External Repository"},{"id":391861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"555","issue":"13","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lundstern, Jens-Erik 0000-0003-0000-8013","orcid":"https://orcid.org/0000-0003-0000-8013","contributorId":264189,"corporation":false,"usgs":true,"family":"Lundstern","given":"Jens-Erik","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":826935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Elizabeth L. 0000-0002-6190-4826","orcid":"https://orcid.org/0000-0002-6190-4826","contributorId":269348,"corporation":false,"usgs":false,"family":"Miller","given":"Elizabeth","email":"","middleInitial":"L.","affiliations":[{"id":55934,"text":"Stanford University Department of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":826936,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70230088,"text":"70230088 - 2022 - Evaluation of intensity prediction equations (IPEs) for small-magnitude earthquakes","interactions":[],"lastModifiedDate":"2022-03-28T11:37:05.776109","indexId":"70230088","displayToPublicDate":"2021-11-02T06:33:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of intensity prediction equations (IPEs) for small-magnitude earthquakes","docAbstract":"<div id=\"132397136\" class=\"article-section-wrapper js-article-section js-content-section  \"><p>This study assesses existing intensity prediction equations (IPEs) for small unspecified magnitude (<i>M</i><span>&nbsp;</span>≤3.5) earthquakes at short hypocentral distances (<span class=\"inline-formula no-formula-id\">⁠<span class=\"MathJax_Preview\"><span id=\"MJXp-Span-1\" class=\"MJXp-math\"><span id=\"MJXp-Span-2\" class=\"MJXp-msub\"><span id=\"MJXp-Span-3\" class=\"MJXp-mi MJXp-italic\">D</span><span id=\"MJXp-Span-4\" class=\"MJXp-mi MJXp-italic MJXp-script\">h</span></span></span></span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax MathJax_Processing\"></span>⁠</span>) and explores such earthquakes’ contribution to the felt shaking hazard. In particular, we consider IPEs by<span>&nbsp;</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf6\">Atkinson and Wald (2007)</a><span>&nbsp;</span>and<span>&nbsp;</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf7\">Atkinson<span>&nbsp;</span><i>et&nbsp;al.</i><span>&nbsp;</span>(2014)</a>, and evaluate their performance based on “Did You Feel It” (DYFI) reports and recorded peak ground velocities (PGVs) in the central United States. Both IPEs were developed based on DYFI reports in the central and eastern United States with moment magnitudes above<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span class=\"MathJax_Preview\"><span id=\"MJXp-Span-5\" class=\"MJXp-math\"><span id=\"MJXp-Span-6\" class=\"MJXp-msub\"><span id=\"MJXp-Span-7\" class=\"MJXp-mi MJXp-italic\">M</span><span id=\"MJXp-Span-8\" class=\"MJXp-mi MJXp-script\">w</span></span></span></span><span id=\"MathJax-Element-2-Frame\" class=\"MathJax MathJax_Processing\"></span></span>&nbsp;3.0. DYFI reports are often used as the ground truth when evaluating and developing IPEs, but they could be less reliable when there are limited responses for small‐magnitude earthquakes. We first compare the DYFI reports with intensities interpolated from recorded PGVs. Results suggest a minimal discrepancy between the two when the intensity is large enough to be felt (i.e.,<span>&nbsp;</span><i>M</i><span>&nbsp;</span>&gt;2 and<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span class=\"MathJax_Preview\"><span id=\"MJXp-Span-9\" class=\"MJXp-math\"><span id=\"MJXp-Span-10\" class=\"MJXp-msub\"><span id=\"MJXp-Span-11\" class=\"MJXp-mi MJXp-italic\">D</span><span id=\"MJXp-Span-12\" class=\"MJXp-mi MJXp-italic MJXp-script\">h</span></span><span id=\"MJXp-Span-13\" class=\"MJXp-mo\">&lt;</span><span id=\"MJXp-Span-14\" class=\"MJXp-mn\">15</span><span id=\"MJXp-Span-15\" class=\"MJXp-mtext\">  </span><span id=\"MJXp-Span-16\" class=\"MJXp-mi\">km</span></span></span><span id=\"MathJax-Element-3-Frame\" class=\"MathJax MathJax_Processing\"></span>⁠</span>). We then compare intensities from 31,617 DYFI reports of 3049 earthquakes with the two IPEs. Results suggest that both the IPEs match well with observed intensities for 2.0&lt;<span>&nbsp;</span><i>M</i><span>&nbsp;</span>&lt;3.0 and<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span class=\"MathJax_Preview\"><span id=\"MJXp-Span-17\" class=\"MJXp-math\"><span id=\"MJXp-Span-18\" class=\"MJXp-msub\"><span id=\"MJXp-Span-19\" class=\"MJXp-mi MJXp-italic\">D</span><span id=\"MJXp-Span-20\" class=\"MJXp-mi MJXp-italic MJXp-script\">h</span></span><span id=\"MJXp-Span-21\" class=\"MJXp-mo\">&lt;</span><span id=\"MJXp-Span-22\" class=\"MJXp-mn\">10</span><span id=\"MJXp-Span-23\" class=\"MJXp-mtext\">  </span><span id=\"MJXp-Span-24\" class=\"MJXp-mi\">km</span></span></span><span id=\"MathJax-Element-4-Frame\" class=\"MathJax MathJax_Processing\"></span>⁠</span>, but the IPE by<span>&nbsp;</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf7\">Atkinson<span>&nbsp;</span><i>et&nbsp;al.</i><span>&nbsp;</span>(2014)</a><span>&nbsp;</span>matches better for larger distances. We also observe that intensities from DYFI reports attenuate faster compared with the two IPEs, especially for distances greater than 10&nbsp;km. We then group DYFI reports by inferred<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span class=\"MathJax_Preview\"><span id=\"MJXp-Span-25\" class=\"MJXp-math\"><span id=\"MJXp-Span-26\" class=\"MJXp-msub\"><span id=\"MJXp-Span-27\" class=\"MJXp-mi MJXp-italic\">V</span><span id=\"MJXp-Span-28\" class=\"MJXp-mrow MJXp-script\"><span id=\"MJXp-Span-29\" class=\"MJXp-mi MJXp-italic\">S</span><span id=\"MJXp-Span-30\" class=\"MJXp-mn\">30</span></span></span></span></span><span id=\"MathJax-Element-5-Frame\" class=\"MathJax MathJax_Processing\"></span></span><span>&nbsp;</span>as a proxy for site amplification effects. We observe that intensities at sites with<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span class=\"MathJax_Preview\"><span id=\"MJXp-Span-31\" class=\"MJXp-math\"><span id=\"MJXp-Span-32\" class=\"MJXp-msub\"><span id=\"MJXp-Span-33\" class=\"MJXp-mi MJXp-italic\">V</span><span id=\"MJXp-Span-34\" class=\"MJXp-mrow MJXp-script\"><span id=\"MJXp-Span-35\" class=\"MJXp-mi MJXp-italic\">S</span><span id=\"MJXp-Span-36\" class=\"MJXp-mn\">30</span></span></span></span></span><span id=\"MathJax-Element-6-Frame\" class=\"MathJax MathJax_Processing\"></span></span><span>&nbsp;</span>around 300&nbsp;m/s are consistently higher than at sites with<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span class=\"MathJax_Preview\"><span id=\"MJXp-Span-37\" class=\"MJXp-math\"><span id=\"MJXp-Span-38\" class=\"MJXp-msub\"><span id=\"MJXp-Span-39\" class=\"MJXp-mi MJXp-italic\">V</span><span id=\"MJXp-Span-40\" class=\"MJXp-mrow MJXp-script\"><span id=\"MJXp-Span-41\" class=\"MJXp-mi MJXp-italic\">S</span><span id=\"MJXp-Span-42\" class=\"MJXp-mn\">30</span></span></span></span></span><span id=\"MathJax-Element-7-Frame\" class=\"MathJax MathJax_Processing\"></span></span><span>&nbsp;</span>around 700&nbsp;m/s and are also closer to the two IPEs. Finally, we conduct hazard disaggregation for earthquakes at close distances (<span class=\"inline-formula no-formula-id\">⁠<span class=\"MathJax_Preview\"><span id=\"MJXp-Span-43\" class=\"MJXp-math\"><span id=\"MJXp-Span-44\" class=\"MJXp-msub\"><span id=\"MJXp-Span-45\" class=\"MJXp-mi MJXp-italic\">D</span><span id=\"MJXp-Span-46\" class=\"MJXp-mi MJXp-italic MJXp-script\">h</span></span><span id=\"MJXp-Span-47\" class=\"MJXp-mo\">=</span><span id=\"MJXp-Span-48\" class=\"MJXp-mn\">7.5</span><span id=\"MJXp-Span-49\" class=\"MJXp-mtext\">  </span><span id=\"MJXp-Span-50\" class=\"MJXp-mi\">km</span></span></span><span id=\"MathJax-Element-8-Frame\" class=\"MathJax MathJax_Processing\"></span>⁠</span>) using the observed records. Results suggest that earthquakes with magnitudes below M&nbsp;3.0 contribute more than 40% to the occurrence of felt shaking.</p></div>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210150","usgsCitation":"Teng, G., Baker, J.W., and Wald, D.J., 2022, Evaluation of intensity prediction equations (IPEs) for small-magnitude earthquakes: Bulletin of the Seismological Society of America, v. 112, no. 1, p. 316-330, https://doi.org/10.1785/0120210150.","productDescription":"15 p.","startPage":"316","endPage":"330","ipdsId":"IP-133450","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":397680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Teng, Ganyu","contributorId":248392,"corporation":false,"usgs":false,"family":"Teng","given":"Ganyu","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":838971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Jack W.","contributorId":115861,"corporation":false,"usgs":false,"family":"Baker","given":"Jack","email":"","middleInitial":"W.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":838972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":838973,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70225665,"text":"70225665 - 2022 - Selective host attachment by Ixodes scapularis (Acari: Ixodidae): Tick-lizard associations in the southeastern United States","interactions":[],"lastModifiedDate":"2022-01-25T17:07:07.479062","indexId":"70225665","displayToPublicDate":"2021-10-29T09:06:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2385,"text":"Journal of Medical Entomology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Selective host attachment by <i>Ixodes scapularis</i> (Acari: Ixodidae): Tick-lizard associations in the southeastern United States","title":"Selective host attachment by Ixodes scapularis (Acari: Ixodidae): Tick-lizard associations in the southeastern United States","docAbstract":"<p><span>Questing behavior and host associations of immature blacklegged ticks,&nbsp;</span><i>Ixodes scapularis</i><span>&nbsp;Say, from the southeastern United States are known to differ from those in the north. To elucidate these relationships we describe host associations of larval and nymphal&nbsp;</span><i>I. scapularis</i><span>&nbsp;from 8 lizard species sampled from 5 sites in the southeastern U.S. Larvae and nymphs attached in greater numbers to larger lizards than to smaller lizards, with differential levels of attachment to different lizard species. Blacklegged ticks are generally attached to skinks of the genus&nbsp;</span><i>Plestiodon</i><span>&nbsp;in greater numbers per unit lizard weight than to anoles (</span><i>Anolis</i><span>) or fence lizards (</span><i>Sceloporus</i><span>). The broad-headed skink,&nbsp;</span><i>Plestiodon laticeps</i><span>&nbsp;(Schneider), was a particularly important host for immature&nbsp;</span><i>I. scapularis</i><span>&nbsp;in our study and in several previous studies of tick–host associations in the southeast. Blacklegged ticks show selective attachment to&nbsp;</span><i>Plestiodon</i><span>&nbsp;lizard hosts in the southeast, but whether this results from behavioral host preferences or from ecological factors such as timing or microhabitat distributions of tick questing and host activity remains to be determined.</span></p>","language":"English","publisher":"Entomological Society of America","doi":"10.1093/jme/tjab181","usgsCitation":"Ginsberg, H., Hickling, G.J., Pang, G., Tsao, J.I., Fitzgerald, M., Ross, B., Rulison, E.L., and Burke, R.L., 2022, Selective host attachment by Ixodes scapularis (Acari: Ixodidae): Tick-lizard associations in the southeastern United States: Journal of Medical Entomology, v. 59, no. 1, p. 267-272, https://doi.org/10.1093/jme/tjab181.","productDescription":"6 p.","startPage":"267","endPage":"272","ipdsId":"IP-129930","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":490082,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/133","text":"External Repository"},{"id":391270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, North Carolina, South Carolina, Tennessee","otherGeospatial":"Arnold Air Force Base, Mattamuskeet National Wildlife Refuge, Oakmulgee Talladega National Forest, Savannah River Site, Tall Timbers Research Station","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.837158203125,\n              33.109373145334544\n            ],\n            [\n              -81.46568298339844,\n              33.109373145334544\n            ],\n            [\n              -81.46568298339844,\n              33.38099943104024\n            ],\n            [\n              -81.837158203125,\n              33.38099943104024\n            ],\n            [\n              -81.837158203125,\n              33.109373145334544\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.33438110351562,\n              35.431582013221266\n            ],\n            [\n              -76.0308837890625,\n              35.431582013221266\n            ],\n            [\n              -76.0308837890625,\n              35.58808520476323\n            ],\n            [\n              -76.33438110351562,\n              35.58808520476323\n            ],\n            [\n              -76.33438110351562,\n              35.431582013221266\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.20285034179688,\n              35.305039297693426\n            ],\n            [\n              -86.0009765625,\n              35.305039297693426\n            ],\n            [\n              -86.0009765625,\n              35.459551379037606\n            ],\n            [\n              -86.20285034179688,\n              35.459551379037606\n            ],\n            [\n              -86.20285034179688,\n              35.305039297693426\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.550048828125,\n              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30.679701616967396\n            ],\n            [\n              -84.23320770263672,\n              30.63850281977284\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"59","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Ginsberg, Howard 0000-0002-4933-2466","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":15473,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hickling, Graham J.","contributorId":140903,"corporation":false,"usgs":false,"family":"Hickling","given":"Graham","email":"","middleInitial":"J.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":826107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pang, Genevieve","contributorId":221488,"corporation":false,"usgs":false,"family":"Pang","given":"Genevieve","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":826110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tsao, Jean I.","contributorId":140905,"corporation":false,"usgs":false,"family":"Tsao","given":"Jean","email":"","middleInitial":"I.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":826108,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzgerald, Meghan","contributorId":268188,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Meghan","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":826109,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ross, Breann","contributorId":248548,"corporation":false,"usgs":false,"family":"Ross","given":"Breann","email":"","affiliations":[{"id":6921,"text":"Hofstra University","active":true,"usgs":false}],"preferred":false,"id":826111,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rulison, Eric L.","contributorId":87478,"corporation":false,"usgs":false,"family":"Rulison","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":826112,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Burke, Russell L.","contributorId":127374,"corporation":false,"usgs":false,"family":"Burke","given":"Russell","email":"","middleInitial":"L.","affiliations":[{"id":6921,"text":"Hofstra University","active":true,"usgs":false}],"preferred":false,"id":826113,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70226527,"text":"70226527 - 2022 - The role of preexisting upper plate strike-slip faults during long-lived (ca. 30 Myr) oblique flat slab subduction, southern Alaska","interactions":[],"lastModifiedDate":"2021-11-23T14:16:17.67564","indexId":"70226527","displayToPublicDate":"2021-10-27T08:13:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The role of preexisting upper plate strike-slip faults during long-lived (ca. 30 Myr) oblique flat slab subduction, southern Alaska","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0020\" class=\"abstract author\"><div id=\"as0020\"><p id=\"sp0100\">Upper plates of subduction zones commonly respond to flat slab subduction by structural reactivation, magmatic arc disruption, and foreland basin inversion. However, the role of active strike-slip faults in focusing convergent deformation and magmatism in response to oblique flat slab subduction remains less clear. Here, we present new detrital apatite fission-track (dAFT) ages from 12 modern catchments in the eastern Alaska Range, Alaska, USA, to reveal how the dextral Denali fault system has facilitated bedrock exhumation and topographic growth during ca. 30 Ma-to-present oblique flat slab subduction of the Yakutat oceanic plateau. Additionally, a 940 ka (<sup>40</sup>Ar/<sup>39</sup>Ar whole rock) basalt flow is spatially associated with Cenozoic structures, locally reset AFT ages and provides the first evidence for Quaternary volcanism along the southern flank of the eastern Alaska Range. We integrate our new data with other thermochronologic, geochronologic, and regional geologic datasets to show that (1) most high topography regions in southern Alaska have undergone rapid bedrock cooling and exhumation since ca. 30 Ma; (2) elevated terrain and young cooling are spatially associated with long-lived active strike-slip fault systems; (3) topographic growth associated with strike-slip fault deformation led to local inversion of basin systems and drainage reorganization; (4) the onset of oblique oceanic plateau subduction is coeval with a southward shift in arc magmatism from one region of active strike-slip faulting to another above the northeastern edge of the flat slab; and (5) Quaternary volcanism marks the revival of magmatism in the eastern Alaska Range above the geophysically imaged northeastern edge of the flat slab. Our analysis of the post-30 Ma geologic evolution of southern Alaska demonstrates that strike-slip fault systems that were active at the time of slab flattening evolved into transpression zones that focused bedrock cooling, rock exhumation, and topographic growth.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2021.117242","usgsCitation":"Waldien, T., Lease, R.O., Roeske, S., Benowitz, J., and O'Sullivan, P., 2022, The role of preexisting upper plate strike-slip faults during long-lived (ca. 30 Myr) oblique flat slab subduction, southern Alaska: Earth and Planetary Science Letters, v. 557, 117242, 12 p., https://doi.org/10.1016/j.epsl.2021.117242.","productDescription":"117242, 12 p.","ipdsId":"IP-133224","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":449588,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2021.117242","text":"Publisher Index Page"},{"id":392043,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154.072265625,\n              57.18390185831188\n            ],\n            [\n              -135.703125,\n              57.18390185831188\n            ],\n            [\n              -135.703125,\n              63.93737246791484\n            ],\n            [\n              -154.072265625,\n              63.93737246791484\n            ],\n            [\n              -154.072265625,\n              57.18390185831188\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"557","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Waldien, Trevor","contributorId":269432,"corporation":false,"usgs":false,"family":"Waldien","given":"Trevor","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":827200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":827201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roeske, Sarah","contributorId":269434,"corporation":false,"usgs":false,"family":"Roeske","given":"Sarah","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":827202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benowitz, Jeff","contributorId":269436,"corporation":false,"usgs":false,"family":"Benowitz","given":"Jeff","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":827203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O'Sullivan, Paul","contributorId":269438,"corporation":false,"usgs":false,"family":"O'Sullivan","given":"Paul","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":827204,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70256761,"text":"70256761 - 2022 - Retention and dimensional changes of evergreen brush piles within a flood control reservoir","interactions":[],"lastModifiedDate":"2024-09-04T16:45:33.982342","indexId":"70256761","displayToPublicDate":"2021-10-15T11:40:21","publicationYear":"2022","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":"Retention and dimensional changes of evergreen brush piles within a flood control reservoir","docAbstract":"<p><span>Brush piles (i.e., trees and large woody debris) are often installed in reservoirs to supplement fish habitat. The retention and dimensional change of brush piles after installation is important information that can be used to maximize the effectiveness of this management action. We evaluated the retention and dimensional change of 70 eastern red cedar&nbsp;</span><i>Juniperus virginiana</i><span>&nbsp;and bald cypress&nbsp;</span><i>Taxodium distichum</i><span>&nbsp;brush piles in an embayment of a drawdown reservoir up to four annual cycles of submergence and exposure. We used satellite imagery to supplement our onsite measurements of retention. We also examined spatial patterns of brush pile retention and dimensional change. Brush piles were lost at 10% per year, and their volume was lost at 14% per year. We compared our rates of brush pile retention and dimensional change with those from a holdout data set of 50 brush piles. Estimates between data sets did not differ statistically. Spatial patterns of retention and dimensional change coincided with morphological features in our study area, suggesting that retention and dimensional change is influenced by variable physical forces (e.g., wave action and flow) at installation locations. Our estimates of brush pile retention and dimensional change can be used to generally sustain desirable brush densities. For example, to maintain a fixed total volume of brush in our study embayment, roughly 23% of the total brush volume installed would need to be replaced annually. Similar research in reservoirs managed for other purposes is needed, as length and cycle of inundation could lead to variable rates of retention and dimensional change. Additionally, advancements into computer-assisted detection and volume estimation could reduce the time and effort needed to monitor brush piles.</span></p>","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/JFWM-21-033","usgsCitation":"Aldridge, C., Norris, D., Hatcher, H., Coppola, G., Colvin, M., and Miranda, L.E., 2022, Retention and dimensional changes of evergreen brush piles within a flood control reservoir: Journal of Fish and Wildlife Management, v. 13, no. 1, p. 223-235, https://doi.org/10.3996/JFWM-21-033.","productDescription":"13 p.","startPage":"223","endPage":"235","ipdsId":"IP-119765","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":449622,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-033","text":"Publisher Index Page"},{"id":433459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Long Branch Creek embayment of Enid Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -89.84895707764991,\n              34.12639444197403\n            ],\n            [\n              -89.84895707764991,\n              34.10300231952699\n            ],\n            [\n              -89.8179302628156,\n              34.10300231952699\n            ],\n            [\n              -89.8179302628156,\n              34.12639444197403\n            ],\n            [\n              -89.84895707764991,\n              34.12639444197403\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Aldridge, C.A.","contributorId":275883,"corporation":false,"usgs":false,"family":"Aldridge","given":"C.A.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norris, D.M.","contributorId":341780,"corporation":false,"usgs":false,"family":"Norris","given":"D.M.","email":"","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":908888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatcher, H.R.","contributorId":278602,"corporation":false,"usgs":false,"family":"Hatcher","given":"H.R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coppola, G.","contributorId":265335,"corporation":false,"usgs":false,"family":"Coppola","given":"G.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, M.E.","contributorId":341781,"corporation":false,"usgs":false,"family":"Colvin","given":"M.E.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908892,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70239360,"text":"70239360 - 2022 - Landscape- and local- level variables affect monarchs in Midwest grasslands","interactions":[],"lastModifiedDate":"2023-01-11T14:43:38.850966","indexId":"70239360","displayToPublicDate":"2021-10-15T08:29:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Landscape- and local- level variables affect monarchs in Midwest grasslands","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Context</h3><p>It is estimated that over one billion milkweed stems need to be restored to sustain the eastern North American migratory population of monarch butterflies; where and in what context the stems should be placed on the landscape is key to addressing habitat deficits.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Objectives</h3><p>We assessed how the amount of appropriate habitat surrounding a particular patch of monarch habitat affects monarch presence and reproduction. To ensure that habitat restoration efforts are targeted towards areas that maximize monarch population growth, it is important to understand the effects of landscape heterogeneity on monarch occurrence in habitat patches (i.e. grasslands with milkweeds) across the landscape.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>Over two summers (2018–2019), we surveyed monarch adults, larvae, and eggs at sixty grassland sites in Wisconsin that varied in patch size and landscape context (proportion grassland, forest edge density, and road density). We also estimated milkweed density and floral richness to characterize local patch quality.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Adult monarch abundance was highest at patches with the lowest proportion of surrounding grassland and lowest road density, and was heavily influenced by patch quality variables. Egg and larva density in a patch increased with milkweed density and floral richness within a patch. Patch size was unrelated to monarch abundance.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>These results suggest that optimal sites for monarch habitat restoration are within landscapes which contain little habitat and that high milkweed density and floral richness and abundance should be conservation goals.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-021-01341-4","usgsCitation":"Bruce, A.S., Thogmartin, W.E., Trosen, C., Oberhauser, K., and Gratton, C., 2022, Landscape- and local- level variables affect monarchs in Midwest grasslands: Landscape Ecology, v. 37, p. 93-108, https://doi.org/10.1007/s10980-021-01341-4.","productDescription":"16 p.","startPage":"93","endPage":"108","ipdsId":"IP-126868","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":449629,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.21203/rs.3.rs-346846/v1","text":"External Repository"},{"id":436048,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91T59BO","text":"USGS data release","linkHelpText":"R code: Landscape- and local-level variables associated with monarch breeding occurrence and abundance at patches in Wisconsin grasslands"},{"id":411717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Chris","contributorId":191428,"corporation":false,"usgs":false,"family":"Trosen","given":"Chris","email":"","affiliations":[],"preferred":false,"id":861261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oberhauser, Karen","contributorId":191431,"corporation":false,"usgs":false,"family":"Oberhauser","given":"Karen","affiliations":[],"preferred":false,"id":861262,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gratton, Claudio","contributorId":296881,"corporation":false,"usgs":false,"family":"Gratton","given":"Claudio","email":"","affiliations":[],"preferred":false,"id":861263,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70223313,"text":"70223313 - 2022 - Development of a multiplex fluorescence in situ hybridization assay to identify coinfections in young-of-the-year smallmouth bass","interactions":[],"lastModifiedDate":"2022-03-28T15:36:43.061897","indexId":"70223313","displayToPublicDate":"2021-10-08T09:01:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2177,"text":"Journal of Aquatic Animal Health","active":true,"publicationSubtype":{"id":10}},"title":"Development of a multiplex fluorescence in situ hybridization assay to identify coinfections in young-of-the-year smallmouth bass","docAbstract":"<p><span>Histopathological assessments of young-of-the-year (age-0) Smallmouth Bass&nbsp;</span><i>Micropterus dolomieu</i><span>&nbsp;in the Susquehanna River drainage identified a high prevalence of the myxozoan&nbsp;</span><i>Myxobolus inornatus</i><span>. This myxozoan infects the connective tissue of the muscle below the skin but is sometimes observed in the esophagus and buccal cavity. In some instances, shallow infections cause breaks in the skin, which could increase the chance of opportunistic bacterial infections. Several microbial pathogens, including&nbsp;</span><i>Flavobacterium columnare</i><span>,&nbsp;</span><i>Aeromonas</i><span>&nbsp;spp., and Largemouth Bass virus, have also been cultured from clinically diseased young of year. A multiplex fluorescence in&nbsp;situ hybridization (FISH) assay was developed to determine potential colocalization of&nbsp;</span><i>M. inornatus</i><span>,&nbsp;</span><i>Flavobacterium</i><span>&nbsp;spp., and&nbsp;</span><i>Aeromonas</i><span>&nbsp;spp. infections. With FISH, 75% of age-0 Smallmouth Bass exhibited&nbsp;</span><i>M. inornatus</i><span>&nbsp;infections, 10% had&nbsp;</span><i>Aeromonas</i><span>&nbsp;spp. infections, and 5% had&nbsp;</span><i>Flavobacterium</i><span>&nbsp;spp. infections, while 3% had coinfections with both bacterial species and&nbsp;</span><i>M. inornatus</i><span>. The results of the multiplex FISH assay revealed a low occurrence of coinfections of&nbsp;</span><i>Flavobacterium</i><span>&nbsp;spp. and/or&nbsp;</span><i>Aeromonas</i><span>&nbsp;spp. with&nbsp;</span><i>M. inornatus</i><span>&nbsp;in randomly sampled individuals.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/aah.10144","usgsCitation":"Walsh, H.L., Blazer, V., and Mazik, P.M., 2022, Development of a multiplex fluorescence in situ hybridization assay to identify coinfections in young-of-the-year smallmouth bass: Journal of Aquatic Animal Health, v. 34, no. 1, p. 12-19, https://doi.org/10.1002/aah.10144.","productDescription":"8 p.","startPage":"12","endPage":"19","ipdsId":"IP-128341","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":449664,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/aah.10144","text":"External Repository"},{"id":391011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Susquehanna River drainage","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.0411376953125,\n              39.78321267821705\n            ],\n            [\n              -75.6243896484375,\n              39.78321267821705\n            ],\n            [\n              -75.6243896484375,\n              41.89409955811395\n            ],\n            [\n              -79.0411376953125,\n              41.89409955811395\n            ],\n            [\n              -79.0411376953125,\n              39.78321267821705\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":821693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":821694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821695,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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