{"pageNumber":"39","pageRowStart":"950","pageSize":"25","recordCount":11004,"records":[{"id":70254298,"text":"70254298 - 2022 - Satellite remote sensing of crop water use across the Missouri River Basin for 1986–2018 period","interactions":[],"lastModifiedDate":"2024-05-17T11:43:50.362857","indexId":"70254298","displayToPublicDate":"2022-06-24T06:42:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Satellite remote sensing of crop water use across the Missouri River Basin for 1986–2018 period","docAbstract":"<div id=\"preview-section-abstract\"><div id=\"abstracts\" class=\"Abstracts u-font-serif text-s\"><div id=\"ab0010\" class=\"abstract author\"><div id=\"abs0010\"><p id=\"sp0060\"><span>Understanding historical crop water use (CWU) dynamics is important to improve land and water management. In this study, well-validated (coefficient of determination = 0.91, percent bias = 4%, and percent&nbsp;root mean square error&nbsp;= 11.8%) Landsat-based actual&nbsp;evapotranspiration&nbsp;(ETa) time-series estimations were used to (1) assess summer season CWU (CWU-Su) dynamics, (2) investigate CWU-Su trends over the study period (1986–2018; 33 years) at the regional- and pixel-scales, and (3) attribute CWU-Su driving factors across Missouri River Basin. Spatial variability of the ETa estimations along with the observed bimodal probability density distribution of ETa highlighted a strong relation between&nbsp;land cover&nbsp;and water uses across the basin. The bimodal distribution of ETa also indicated the presence of two major landcovers in the basin. The drier foothill regions in northwestern Missouri River Basin, dominated by grassland/shrubland, showed lower ETa (&lt; 500&nbsp;mm/year), whereas cropland dominated regions in lower semi-humid basin and forested subbasins exhibited higher ETa (&gt; 600&nbsp;mm/year). The CWU-Su anomalies revealed the vulnerability of the basin to year-to-year weather conditions. The CWU-Su trend analysis revealed a significant positive trend (p&nbsp;&lt;&nbsp;0.1) at the regional-scale affecting 30% of basin’s cropland pixels. The cropland pixels under positive CWU-Su trend were found to be clustered in the eastern and central Missouri River Basin as a result of the combined effect of increased crop production area, increased crop yields, crop practice shifts to higher&nbsp;biomass crops, and increased irrigated land. The effect of improved irrigation and water management practices on reducing CWU-Su was observed in western Missouri River Basin, which had a stable major crop throughout the study period. Overall, the study highlights the usefulness of&nbsp;Landsat&nbsp;imagery and remote sensing-based&nbsp;</span>ETa modeling<span>&nbsp;</span>approaches in generating historical time-series ETa maps over a wide range of elevation, vegetation, and climate.</p></div></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2022.107792","usgsCitation":"Bawa, A., Senay, G.B., and Kumar, S., 2022, Satellite remote sensing of crop water use across the Missouri River Basin for 1986–2018 period: Agricultural Water Management, v. 271, 107792, https://doi.org/10.1016/j.agwat.2022.107792.","productDescription":"107792","ipdsId":"IP-136886","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467179,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agwat.2022.107792","text":"Publisher Index Page"},{"id":428791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Missouri River Basin","volume":"271","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bawa, Arun 0000-0003-1226-0320","orcid":"https://orcid.org/0000-0003-1226-0320","contributorId":336731,"corporation":false,"usgs":false,"family":"Bawa","given":"Arun","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":900926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":900927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, Sandeep 0000-0002-2717-5455","orcid":"https://orcid.org/0000-0002-2717-5455","contributorId":336732,"corporation":false,"usgs":false,"family":"Kumar","given":"Sandeep","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":900928,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70232271,"text":"sir20225049 - 2022 - Revisions to the Virginia Coastal Plain hydrogeologic framework southwest of the James River","interactions":[],"lastModifiedDate":"2026-04-09T17:54:31.905597","indexId":"sir20225049","displayToPublicDate":"2022-06-23T08:00:00","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":"2022-5049","displayTitle":"Revisions to the Virginia Coastal Plain Hydrogeologic Framework Southwest of the James River","title":"Revisions to the Virginia Coastal Plain hydrogeologic framework southwest of the James River","docAbstract":"<p>New drilling information reveals that altitudes of some hydrogeologic units of the Virginia Coastal Plain aquifer system differ by as much as 50 feet (ft) from those previously known, namely the Aquia and Potomac aquifers, the Potomac confining zone, and the Nanjemoy-Marlboro and Saint Marys confining units. In addition, the lateral margins of some hydrogeologic units are located as much as several miles from previously estimated locations. The largest revisions to unit margins were for the Aquia aquifer and the Nanjemoy-Marlboro and Saint Marys confining units. Interpretation of new geophysical logs, sediment core, and cuttings as well as revised interpretations to existing data indicate channels and embayments are also preserved on eroded top surfaces of the shallowest hydrogeologic units including the Yorktown confining zone, Yorktown-Eastover aquifer, Saint Marys confining unit, Potomac confining zone, and Potomac aquifer.</p><p>Enhanced details on the configuration of part of the aquifer system southwest of the James River are provided by sediment cores and cuttings as well as geophysical logs from 36 recently drilled boreholes. These, along with reinterpretation of data from 93 preexisting boreholes, form the basis for revised top-surface altitudes and margins of hydrogeologic units beneath parts of Prince George, Surry, Sussex, Isle of Wight, and Southampton Counties and the cities of Franklin and Suffolk.</p><p>Groundwater withdrawals in the Virginia Coastal Plain cause widespread water-level declines, create the potential for saltwater intrusion, and contribute to regionwide land subsidence. A description of the aquifer system, termed a hydrogeologic framework, was developed by the U.S. Geological Survey in 2006 and provides information needed to base withdrawal-permitting decisions by the Virginia Department of Environmental Quality. This revision of part of the hydrogeologic framework southwest of the James River is based on interpretations of both new and previously analyzed borehole data. The revision is strictly confined to the study area extent and hydrogeologic units not found within the study area were not revised and are not discussed in this report. The newly determined hydrogeologic-unit altitudes and margins have implications for groundwater-withdrawal permitting. New interpretations have found that the Yorktown Eastover aquifer is absent in the southwestern part of the City of Suffolk, owing to what is most likely an isolated area of sediment-texture facies change. Most notably, the top-surface altitudes of the Aquia and Potomac aquifers have been lowered by as much as 50 ft from previous interpretations. This means that wells previously believed to be screened in the top of the Potomac aquifer could, based on these new interpretations, be screened in the bottom of the Aquia aquifer. These changes to aquifers in which wells are screened means that there is potentially more room in the groundwater withdrawal permitting for the Potomac aquifer, the largest and most productive aquifer in Virginia, and overpumping occurring in the Aquia aquifer.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225049","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"Caldwell, S.H., and McFarland, E.R., 2022, Revisions to the Virginia Coastal Plain hydrogeologic framework southwest of the James River: U.S. Geological Survey Scientific Investigations Report 2022–5049, 24 p., https://doi.org/10.3133/sir20225049.","productDescription":"Report: vii, 24 p.; Data Release","numberOfPages":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-134149","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":402411,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5049/images/"},{"id":402409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5049/sir20225049.pdf","text":"Report","size":"3.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5049"},{"id":402412,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5049/sir20225049.XML"},{"id":402408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5049/coverthb.jpg"},{"id":402452,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225049/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5049"},{"id":402410,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91XJ640","text":"USGS data release","linkHelpText":"Shapefiles of hydrogeologic unit extents and top-surface altitude contours used in the revised hydrogeologic framework for the Virginia Coastal Plain Southwest of the James River"},{"id":502404,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113194.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.4151611328125,\n              36.56039393337068\n            ],\n            [\n              -76.63787841796875,\n              36.56039393337068\n            ],\n            [\n              -76.63787841796875,\n              37.199706196161735\n            ],\n            [\n              -77.4151611328125,\n              37.199706196161735\n            ],\n            [\n              -77.4151611328125,\n              36.56039393337068\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/virginia-and-west-virginia-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/virginia-and-west-virginia-water-science-center\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, VA 23228</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>Revision of Coastal Plain Hydrogeologic Framework</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2022-06-23","noUsgsAuthors":false,"publicationDate":"2022-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Samuel H. 0000-0002-4444-7002","orcid":"https://orcid.org/0000-0002-4444-7002","contributorId":292520,"corporation":false,"usgs":true,"family":"Caldwell","given":"Samuel","email":"","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":844949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McFarland, E. Randolph 0000-0002-4135-6842","orcid":"https://orcid.org/0000-0002-4135-6842","contributorId":292521,"corporation":false,"usgs":false,"family":"McFarland","given":"E. Randolph","affiliations":[{"id":32931,"text":"USGS - Retired","active":true,"usgs":false}],"preferred":false,"id":844950,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70232276,"text":"sir20225050 - 2022 - Mapping the altitude of the top of the Dockum Group and paleochannel analysis using surface geophysical methods on and near Cannon Air Force Base in Curry County, New Mexico, 2020","interactions":[],"lastModifiedDate":"2026-04-09T17:57:01.788707","indexId":"sir20225050","displayToPublicDate":"2022-06-22T14:13:29","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":"2022-5050","displayTitle":"Mapping the Altitude of the Top of the Dockum Group and Paleochannel Analysis Using Surface Geophysical Methods On and Near Cannon Air Force Base in Curry County, New Mexico, 2020","title":"Mapping the altitude of the top of the Dockum Group and paleochannel analysis using surface geophysical methods on and near Cannon Air Force Base in Curry County, New Mexico, 2020","docAbstract":"<p>The hydrogeology on and near Cannon Air Force Base (AFB) in eastern New Mexico was assessed to gain a better understanding of preferential groundwater flow paths through paleochannels. In and near the study area, paleochannels incised the top surface of the Dockum Group (Chinle Formation) and were subsequently filled in with electrically resistive coarse-grained sediments of the overlying Ogallala Formation, resulting in a preferential groundwater flow path in the form of a paleochannel network. A better understanding of the spatial characteristics of this preferential groundwater flow path is needed to support ongoing efforts to remediate groundwater contamination at Cannon AFB. Therefore, the U.S. Geological Survey, in cooperation with the U.S. Air Force Civil Engineer Center, used surface geophysical resistivity methods and data compiled from previous studies to better understand the spatial distribution and characteristics of the paleochannel network incised into the top of the Dockum Group.</p><p>Previous studies have shown these paleochannels incised into the top of the Dockum Group with increasing resolution, but limited borehole data on and near Cannon AFB continued to make accurately mapping the top of Dockum Group challenging. For this study, surface geophysical resistivity measurements in the form of time-domain electromagnetic soundings made by the U.S. Geological Survey were used in conjunction with data previously published by Architecture, Engineering, Construction, Operations, and Management and borehole data compiled from the New Mexico Water Rights Reporting System database to prepare an updated map of the top of the Dockum Group that includes the location and characteristics of paleochannels incised into the top of the Dockum Group (Chinle Formation). A total of 149 borehole picks (determinations of the tops and bases of geologic units and their hydrogeologic-unit equivalents) were obtained from previous studies, along with 72 additional borehole picks from the New Mexico Water Rights Reporting System database and 43 picks from newly collected time-domain electromagnetic soundings. The data were gridded and contoured using Oasis Montaj v. 9.8.1.</p><p>The updated map of the top of Dockum Group has many areas of uncertainty greater than 20 feet, because there are not enough data for the gridding process to reliably determine a value. However, this interpretation of the altitude of the top of the Dockum Group represents a substantial improvement in data resolution compared to previous studies.</p><p>Two methodologies were used to evaluate paleochannels incised in the top of the Dockum Group across the study area: (1) trend-removal grid analysis and (2) analysis with Esri’s ArcMap Hydrology toolset. These two paleochannel analysis techniques show groundwater flow direction as well as areas having the deepest saturated thickness. Hydrologically, these techniques show where aquifer storage is highest (in the deepest parts of the paleochannel network), as well as the spatial distribution of preferential groundwater flow paths (the paleochannels). The analyses indicate a large paleochannel trending to the southeast, with smaller channels feeding in from the west. Areas where groundwater management could be more beneficial are indicated by locations where these flow lines intersect the deeper parts of the paleochannel.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225050","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center","usgsCitation":"Payne, J.D., Teeple, A.P., McDowell, J., Wallace, D., and Hancock, W.A., 2022, Mapping the altitude of the top of the Dockum Group and paleochannel analysis using surface geophysical methods on and near Cannon Air Force Base in Curry County, New Mexico, 2020: U.S. Geological Survey Scientific Investigations Report 2022–5050, 21 p., https://doi.org/10.3133/sir20225050.","productDescription":"Report: iv, 21 p.; 2 Data Releases; Dataset","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-125577","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":402443,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P6KWR5","text":"USGS data release","linkHelpText":"Surface geophysical data used for mapping the top of the Dockum Group on Cannon Air Force Base in Curry County, New Mexico, 2020"},{"id":402444,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/543e6b86e4b0fd76af69cf4c","text":"USGS data release","linkHelpText":"1 meter digital elevation models (DEMs)—USGS National Map 3DEP downloadable data collection"},{"id":402440,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5050/sir20225050.XML"},{"id":402439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5050/sir20225050.pdf","text":"Report","size":"1.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5050"},{"id":402438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5050/coverthb.jpg"},{"id":402462,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225050/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402442,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://nmwrrs.ose.state.nm.us/nmwrrs/wellSurfaceDiversion.html","text":"New Mexico Office of the State Engineer online database","linkHelpText":"—New Mexico Water Rights Reporting System"},{"id":402441,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5050/images"},{"id":502405,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113200.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Mexico","county":"Curry County","otherGeospatial":"Cannon Air Force Base","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.375,\n              34.333\n            ],\n            [\n              -103.25,\n              34.333\n            ],\n            [\n              -103.25,\n              34.458333\n            ],\n            [\n              -103.375,\n              34.458333\n            ],\n            [\n              -103.375,\n              34.333\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/ot-water\" data-mce-href=\"https://www.usgs.gov/centers/ot-water\">Oklahoma-Texas Water Science Center</a> <br>U.S. Geological Survey <br>1505 Ferguson Lane <br>Austin, TX 78754-4501</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Data Collection, Compilation, and Processing Methods</li><li>Hydrogeologic Unit Interpretation</li><li>Paleochannel Analysis</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2022-06-22","noUsgsAuthors":false,"publicationDate":"2022-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Payne, Jason D. 0000-0003-4294-7924","orcid":"https://orcid.org/0000-0003-4294-7924","contributorId":257453,"corporation":false,"usgs":true,"family":"Payne","given":"Jason","email":"","middleInitial":"D.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teeple, Andrew P. 0000-0003-1781-8354","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":217876,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew P.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDowell, Jeremy 0000-0002-8132-9806","orcid":"https://orcid.org/0000-0002-8132-9806","contributorId":221296,"corporation":false,"usgs":true,"family":"McDowell","given":"Jeremy","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallace, David 0000-0002-9134-8197","orcid":"https://orcid.org/0000-0002-9134-8197","contributorId":220786,"corporation":false,"usgs":true,"family":"Wallace","given":"David","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844965,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hancock, Walker A.","contributorId":292524,"corporation":false,"usgs":false,"family":"Hancock","given":"Walker","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":844966,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70238603,"text":"70238603 - 2022 - Population genetics reveals bidirectional fish movement across the Continental Divide via an interbasin water transfer","interactions":[],"lastModifiedDate":"2022-12-01T14:20:07.824544","indexId":"70238603","displayToPublicDate":"2022-06-22T08:14:13","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":"Population genetics reveals bidirectional fish movement across the Continental Divide via an interbasin water transfer","docAbstract":"<p><span>Interbasin water transfers are becoming an increasingly common tool to satisfy municipal and agricultural water demand, but their impacts on movement and gene flow of aquatic organisms are poorly understood. The Grand Ditch is an interbasin water transfer that diverts water from tributaries of the upper Colorado River on the west side of the Continental Divide to the upper Cache la Poudre River on the east side of the Continental Divide. We used single nucleotide polymorphisms to characterize population genetic structure in cutthroat trout (</span><i>Oncorhynchus clarkii</i><span>) and determine if fish utilize the Grand Ditch as a movement corridor. Samples were collected from two sites on the west side and three sites on the east side of the Continental Divide. We identified two or three genetic clusters, and relative migration rates and spatial distributions of admixed individuals indicated that the Grand Ditch facilitated bidirectional fish movement across the Continental Divide, a major biogeographic barrier. Previous studies have demonstrated ecological impacts of interbasin water transfers, but our study is one of the first to use genetics to understand how interbasin water transfers affect connectivity between previously isolated watersheds. We also discuss implications on native trout management and balancing water demand and biodiversity conservation.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10592-022-01455-5","usgsCitation":"Harris, A., Oyler-McCance, S.J., Fike, J., Fairchild, M., Kennedy, C.M., Crockett, H.J., Winkelman, D.L., and Kanno, Y., 2022, Population genetics reveals bidirectional fish movement across the Continental Divide via an interbasin water transfer: Conservation Genetics, v. 23, p. 839-851, https://doi.org/10.1007/s10592-022-01455-5.","productDescription":"13 p.","startPage":"839","endPage":"851","ipdsId":"IP-136388","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":502545,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":409921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Arapaho and Roosevelt National Forests, Rocky Mountain National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.48445207177413,\n              40.56757183578418\n            ],\n            [\n              -106.39934138151587,\n              40.56757183578418\n            ],\n            [\n              -106.39934138151587,\n              39.6680633227534\n            ],\n            [\n              -105.48445207177413,\n              39.6680633227534\n            ],\n            [\n              -105.48445207177413,\n              40.56757183578418\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2022-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Audrey","contributorId":299560,"corporation":false,"usgs":false,"family":"Harris","given":"Audrey","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":858065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fairchild, Matthew P","contributorId":299561,"corporation":false,"usgs":false,"family":"Fairchild","given":"Matthew P","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":858068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Christopher M","contributorId":299562,"corporation":false,"usgs":false,"family":"Kennedy","given":"Christopher","email":"","middleInitial":"M","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":858069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crockett, Harry J","contributorId":299564,"corporation":false,"usgs":false,"family":"Crockett","given":"Harry","email":"","middleInitial":"J","affiliations":[{"id":36246,"text":"CPW","active":true,"usgs":false}],"preferred":false,"id":858070,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":858071,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kanno, Yoichiro","contributorId":210653,"corporation":false,"usgs":false,"family":"Kanno","given":"Yoichiro","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":858072,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70232367,"text":"70232367 - 2022 - Characterizing mauka-to-makai connections for aquatic ecosystem conservation on Maui, Hawaiʻi","interactions":[],"lastModifiedDate":"2022-06-29T12:28:54.824391","indexId":"70232367","displayToPublicDate":"2022-06-22T07:26:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing mauka-to-makai connections for aquatic ecosystem conservation on Maui, Hawaiʻi","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0045\"><span>Mauka-to-makai (mountain to sea in the Hawaiian language) hydrologic connectivity – commonly referred to as ridge-to-reef – directly affects biogeochemical processes and socioecological functions across terrestrial, freshwater, and marine systems. The supply of freshwater to estuarine and&nbsp;nearshore environments&nbsp;in a ridge-to-reef system supports the food, water, and habitats utilized by&nbsp;</span>marine fauna<span>. In addition, the ecosystem services derived from this land-to-sea connectivity support social and cultural practices (hereafter referred to as socio-cultural) including fishing,&nbsp;aquaculture,&nbsp;wetland&nbsp;agriculture, religious ceremonies, and recreational activities. To effectively guide island resource management, a better understanding of the linkages from ridge-to-reef across natural and social usages is critical, particularly in the context of climate change, with anticipated increasing temperature and shifting precipitation patterns. The objective of this study was to identify spatial linkages that promote multiple and diverse uses, following the ridge-to-reef concept, at an island-wide scale to identify regions of high conservation importance for aquatic resources. We selected the Island of Maui as a study representative of many Pacific islands. Diverse datasets, including&nbsp;agricultural lands&nbsp;within&nbsp;watersheds, wetland locations, presence of stream species, indicators of&nbsp;freshwater input&nbsp;from streams, coral cover, nearshore fish biomass, socio-cultural data such as fishpond locations, wetland&nbsp;taro&nbsp;cultivation, beach recreation use, and lastly the dynamically downscaled&nbsp;Coupled Model Intercomparison Project&nbsp;Phase (CMIP5) future climate projections scenarios (Representative Concentration Pathway (RCP) 4.5 &amp; 8.5) were used to examine the spatial linkages through hydrological connectivity from land to the sea. Zonation spatial planning software was used to prioritize areas of high management and conservation value and to help inform aquatic resources management. The resulting prioritized areas included many minimally disturbed watersheds in east Maui and western nearshore and coastal zones that are adjacent to diverse coral reefs. These results are driven by the importance of fish biomass and coral reef distribution as well as traditional wetland taro cultivation and coastal access points for recreation. These results underline the importance of examining ridge-to-reef systems for aquatic resource management and including important social and cultural values in resource management upon planning adaptation strategies for climate change. Improving our understanding of diverse natural and socio-cultural influences on habitat conditions and their values in these areas provides an opportunity to strategically plan future management and conservation actions.</span></p></div></div><div id=\"ab0010\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2022.101704","usgsCitation":"Wilmot, E., Wong, J.P., Tsang, Y., Lynch, A., Infante, D.M., Oleson, K.L., Strauch, A., and Clilverd, H., 2022, Characterizing mauka-to-makai connections for aquatic ecosystem conservation on Maui, Hawaiʻi: Ecological Informatics, v. 70, 101704, 12 p., https://doi.org/10.1016/j.ecoinf.2022.101704.","productDescription":"101704, 12 p.","ipdsId":"IP-134842","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447363,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoinf.2022.101704","text":"Publisher Index Page"},{"id":402671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -156.8023681640625,\n              20.53507732696281\n            ],\n            [\n              -155.8905029296875,\n              20.53507732696281\n            ],\n            [\n              -155.8905029296875,\n              21.09475053314019\n            ],\n            [\n              -156.8023681640625,\n              21.09475053314019\n            ],\n            [\n              -156.8023681640625,\n              20.53507732696281\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"70","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wilmot, Ella","contributorId":292646,"corporation":false,"usgs":false,"family":"Wilmot","given":"Ella","email":"","affiliations":[{"id":62956,"text":"University of Hawaii-Manoa","active":true,"usgs":false}],"preferred":false,"id":845364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wong, Jesse P.","contributorId":264850,"corporation":false,"usgs":false,"family":"Wong","given":"Jesse","email":"","middleInitial":"P.","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":845365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tsang, Yinphan","contributorId":292647,"corporation":false,"usgs":false,"family":"Tsang","given":"Yinphan","affiliations":[],"preferred":false,"id":845372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":207361,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":845366,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Infante, Dana M.","contributorId":146114,"corporation":false,"usgs":false,"family":"Infante","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":16583,"text":"Department of Fisheries and Wildlife, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":845367,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oleson, Kirsten L. L. 0000-0002-7992-5051","orcid":"https://orcid.org/0000-0002-7992-5051","contributorId":211871,"corporation":false,"usgs":false,"family":"Oleson","given":"Kirsten","email":"","middleInitial":"L. L.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":845368,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Strauch, Ayron","contributorId":221124,"corporation":false,"usgs":false,"family":"Strauch","given":"Ayron","email":"","affiliations":[{"id":40327,"text":"State of Hawai‘i, Department of Land and Natural Resources, Commission on Water Resource Management","active":true,"usgs":false}],"preferred":false,"id":845369,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clilverd, Hannah","contributorId":216755,"corporation":false,"usgs":false,"family":"Clilverd","given":"Hannah","email":"","affiliations":[{"id":17202,"text":"University of Hawaii, Manoa","active":true,"usgs":false}],"preferred":false,"id":845370,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70232898,"text":"70232898 - 2022 - Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination","interactions":[],"lastModifiedDate":"2022-09-14T15:38:47.959998","indexId":"70232898","displayToPublicDate":"2022-06-21T11:44:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12585,"text":"eLife","active":true,"publicationSubtype":{"id":10}},"title":"Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination","docAbstract":"<p><span>In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July–December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July–December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July–December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model.</span></p>","language":"English","publisher":"eLife Sciences Publications, Ltd","doi":"10.7554/eLife.73584","usgsCitation":"Truelove, S., Smith, C.P., Qin, M., Mullany, L., Borchering, R.K., Lessler, J., Shea, K., Howerton, E., Contamin, L., Levander, J., Kerr, J., Hochheiser, H., Kinsey, M., Tallaksen, K., Wilson, S., Shin, L., Rainwater-Lovett, K., Lemaitre, J., Dent, J., Kaminsky, J., Lee, E.C., Perez-Saez, J., Hill, A., Karlen, D., Chinazzi, M., Davis, J., Mu, K., Xiong, X., Pastore y Piontti, A., Vespignani, A., Srivastava, A., Porebski, P., Venkatramanan, S., Adiga, A., Lewis, B., Klahn, B., Outten, J., Orr, M., Harrison, G., Hurt, B., Chen, J., Vullikanti, A., Marathe, M., Hoops, S., Bhattacharya, P., Machi, D., Chen, S., Paul, R., Janies, D., Thill, J., Galanti, M., Yamana, T., Pei, S., Shaman, J.L., Healy, J., Slayton, R.B., Biggerstaff, M., Johansson, M.A., Runge, M.C., and Viboud, C., 2022, Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination: eLife, v. 11, e73584, 17 p., https://doi.org/10.7554/eLife.73584.","productDescription":"e73584, 17 p.","ipdsId":"IP-131448","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7554/elife.73584","text":"Publisher Index Page"},{"id":406680,"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\": 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Prevention","active":true,"usgs":false}],"preferred":false,"id":851760,"contributorType":{"id":1,"text":"Authors"},"rank":56},{"text":"Biggerstaff, Matthew","contributorId":258040,"corporation":false,"usgs":false,"family":"Biggerstaff","given":"Matthew","email":"","affiliations":[{"id":27265,"text":"Centers for Disease Control and Prevention","active":true,"usgs":false}],"preferred":false,"id":851761,"contributorType":{"id":1,"text":"Authors"},"rank":57},{"text":"Johansson, Michael A","contributorId":258041,"corporation":false,"usgs":false,"family":"Johansson","given":"Michael","email":"","middleInitial":"A","affiliations":[{"id":27265,"text":"Centers for Disease Control and Prevention","active":true,"usgs":false}],"preferred":false,"id":851762,"contributorType":{"id":1,"text":"Authors"},"rank":58},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":846452,"contributorType":{"id":1,"text":"Authors"},"rank":59},{"text":"Viboud, Cecile 0000-0003-3243-4711","orcid":"https://orcid.org/0000-0003-3243-4711","contributorId":258034,"corporation":false,"usgs":false,"family":"Viboud","given":"Cecile","email":"","affiliations":[{"id":52216,"text":"National Institutes of Health Fogarty International Center","active":true,"usgs":false}],"preferred":false,"id":846454,"contributorType":{"id":1,"text":"Authors"},"rank":60}]}}
,{"id":70239285,"text":"70239285 - 2022 - Geoenvironmental model for roll-type uranium deposits in the Texas Gulf Coast","interactions":[],"lastModifiedDate":"2023-01-06T12:49:39.192331","indexId":"70239285","displayToPublicDate":"2022-06-20T06:46:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5207,"text":"Minerals","active":true,"publicationSubtype":{"id":10}},"title":"Geoenvironmental model for roll-type uranium deposits in the Texas Gulf Coast","docAbstract":"<div class=\"html-p\">Geoenvironmental models were formulated by the U.S. Geological Survey in the 1990s to describe potential environmental effects of extracting different types of ore deposits in different geologic and climatic regions. This paper presents a geoenvironmental model for roll-front (roll-type) uranium deposits in the Texas Coastal Plain. The model reviews descriptive and quantitative information derived from environmental studies and existing databases to depict existing conditions and potential environmental concerns associated with mining this deposit type. This geoenvironmental model describes how features of the deposits including host rock; ore and gangue mineralogy; geologic, hydrologic, and climatic settings; and mining methods (legacy open-pit and in situ recovery [ISR]) influence potential environmental effects from mining. Element concentrations in soil and water are compared to regulatory thresholds to depict ambient surface water and groundwater conditions. Although most open-pit operations in this region have been reclaimed, concerns remain about groundwater quality at three of the four former mills that supported former open-pit mines and are undergoing closure activities. The primary environmental concerns with ISR mining are (1) radon gas at active ISR operations, (2) radiation or contaminant leakage during production and transport of ISR resin or yellowcake, (3) uranium excursions into groundwater surrounding active ISR operations, and (4) contamination of groundwater after ISR mining. Although existing regulations attempt to address these concerns, some problems remain. Researchers suggest that reactive transport modeling and a better understanding of geology, stratigraphy, and geochemistry of ISR production areas could minimize excursions into surrounding aquifers and improve results of groundwater restoration.</div>","language":"English","publisher":"MDPI","doi":"10.3390/min12060780","usgsCitation":"Walton-Day, K., Blake, J., Seal,, R., Gallegos, T., Jean Dupree, and Becher, K.D., 2022, Geoenvironmental model for roll-type uranium deposits in the Texas Gulf Coast: Minerals, v. 12, no. 6, 780, 34 p., https://doi.org/10.3390/min12060780.","productDescription":"780, 34 p.","ipdsId":"IP-136921","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":447387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/min12060780","text":"Publisher Index Page"},{"id":411480,"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        \"coordinates\": [\n          [\n            [\n              -99.33528666210017,\n              26.89578699824432\n            ],\n            [\n              -99.11565337352738,\n              26.267254950900764\n            ],\n            [\n              -97.92963361523617,\n              25.872681365510957\n            ],\n            [\n              -96.9632471455172,\n              26.030670273163835\n            ],\n            [\n              -96.91932048780222,\n              26.699741720191838\n            ],\n            [\n              -95.11832752150816,\n              28.3358549338098\n            ],\n            [\n              -93.66874781692972,\n              29.90908880278704\n            ],\n            [\n              -93.58089450150081,\n              30.62990043651834\n            ],\n            [\n              -95.60152075636765,\n              30.59209521003619\n            ],\n            [\n              -98.06141358837951,\n              29.22136658295345\n            ],\n            [\n              -99.33528666210017,\n              26.89578699824432\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":184043,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blake, Johanna 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":217272,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seal,, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":861004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gallegos, Tanya J. 0000-0003-3350-6473","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":206859,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":861005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jean Dupree","contributorId":300633,"corporation":false,"usgs":false,"family":"Jean Dupree","affiliations":[{"id":32931,"text":"USGS - Retired","active":true,"usgs":false}],"preferred":false,"id":861006,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Becher, Kent D 0000-0002-3947-0793","orcid":"https://orcid.org/0000-0002-3947-0793","contributorId":290642,"corporation":false,"usgs":false,"family":"Becher","given":"Kent","email":"","middleInitial":"D","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":861007,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70232341,"text":"70232341 - 2022 - Assessing wave attenuation with rising sea levels for sustainable oyster reef-based living shorelines","interactions":[],"lastModifiedDate":"2022-06-28T12:44:32.089718","indexId":"70232341","displayToPublicDate":"2022-06-17T07:39:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10939,"text":"Frontiers in Built Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing wave attenuation with rising sea levels for sustainable oyster reef-based living shorelines","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb15\">In densely populated coastal areas with sea-level rise (SLR), protecting the shorelines against erosion due to the wave impact is crucial. Along with many engineered structures like seawalls and breakwaters, there are also green structures like constructed oyster reefs (CORs) that can not only attenuate the incident waves but also grow and maintain pace with SLR. However, there is a lack of data and understanding of the long-term wave attenuation capacity of the living shoreline structures under SLR. In this study, we used the phase-resolving Boussinesq model, FUNWAVE-TVD, to examine the hydrodynamics including wave height and wave-induced currents around the CORs in the Gandys Beach living shoreline project area in the upper Delaware Bay, United States. Waves were measured at six locations (offshore to onshore, with and without CORs) in the Gandys Beach living shoreline project area for two winter months, during which four nor’easters occurred. We selected three cases that represent prevailing wind, wave, and tide conditions to examine the fine spatial and temporal changes in wave height and current velocity by the construction of the reefs. Wave heights and wave energy spectra generated from FUNWAVE-TVD were then validated with field observations. It is found that FUNWAVE-TVD is capable of simulating waves and associated hydrodynamic processes that interact with CORs. The model results show that wave attenuation rates vary with the incident wave properties and water depth, and wave-induced circulation patterns are affected by the CORs. The wave attenuation capacity of CORs over the next 100 years was simulated with the incorporation of the oyster reef optimal growth zone. Our study found that sustainable wave attenuation capacity can only be achieved when suitable habitat for COR is provided, thus it can vertically grow with SLR. Suitable habitat includes optimal intertidal inundation duration, current velocity for larval transport and settlement, on-reef oyster survival and growth, and other environmental conditions including salinity, temperature, and nutrient availability. Furthermore, the model results suggest that it would take CORs approximately 9 years after construction to reach and maintain the maximum wave attenuation capacity in sustainable living shorelines.</p></div>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fbuil.2022.884849","usgsCitation":"Salatin, R., Wang, H., Chen, Q., and Zhu, L., 2022, Assessing wave attenuation with rising sea levels for sustainable oyster reef-based living shorelines: Frontiers in Built Environment, v. 8, 884849, 16 p., https://doi.org/10.3389/fbuil.2022.884849.","productDescription":"884849, 16 p.","ipdsId":"IP-138476","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447401,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fbuil.2022.884849","text":"Publisher Index Page"},{"id":402591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.849609375,\n              38.496593518947584\n            ],\n            [\n              -74.5751953125,\n              38.496593518947584\n            ],\n            [\n              -74.5751953125,\n              40.019201307686785\n            ],\n            [\n              -75.849609375,\n              40.019201307686785\n            ],\n            [\n              -75.849609375,\n              38.496593518947584\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Salatin, Reza 0000-0001-5372-3948","orcid":"https://orcid.org/0000-0001-5372-3948","contributorId":292618,"corporation":false,"usgs":false,"family":"Salatin","given":"Reza","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":845285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":221902,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":845286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":845287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":845288,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70232243,"text":"sir20225055 - 2022 - Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019","interactions":[],"lastModifiedDate":"2026-04-23T16:36:07.756303","indexId":"sir20225055","displayToPublicDate":"2022-06-17T07:23:22","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":"2022-5055","displayTitle":"Assessment of Streamflow Trends in the Eastern Dakotas, Water Years 1960–2019","title":"Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019","docAbstract":"<p>Hydrologic extremes, whether periods of drought or flooding, are occurring more frequently with greater severity and can have substantial economic impacts. Along with flooding, the timing and volume of streamflow also is changing across the United States. The focus of this report is to characterize a unique trend in mean annual streamflow occurring in eastern North and South Dakota, hereafter referred to as the eastern Dakotas, that is not being observed anywhere else in the conterminous United States.</p><p>Streamflow records for 1,853 U.S. Geological Survey streamgages obtained from the U.S. Geological Survey National Water Information System database with a continuous record of mean annual streamflow during water years 1960–2019 were included in this study. Using a Kendall tau statistical test (<i>p</i>-value less than or equal to 0.10), 573 streamgages had a statistically significant upward trend in mean annual streamflow and are primarily located in the Midwest and northeastern United States. Of the streamgages, 182 had a statistically significant downward trend and are located primarily in the western and southeastern States. Several sites had increases in streamflow between 100 and 500 percent. Most of the streamgages with the highest increases in mean annual streamflow are along the same rivers in the eastern Dakotas, regardless of basin size.</p><p>A comparison of mean annual streamflow of the last decade (2010–19) to the first decade (1960–69) of the study period shows that the largest increases in annual streamflow volumes in the United States also are in the eastern Dakotas. Among all 1,853 streamgages in the United States, the Sheyenne River near Warwick, North Dakota (U.S. Geological Survey station 05056000), has the greatest percent change, with an increase of 486 percent. Several factors may be contributing to increasing trends in streamflow in the eastern Dakotas and may include, in part, precipitation changes owing to climatic variation within the region, geologic makeup of the subsurface, and land-use changes. A better understanding of these research areas will help producers, resource managers, and infrastructure engineers to make more informed environmental and economic decisions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225055","usgsCitation":"Norton, P.A., Delzer, G.C., Valder, J.F., Tatge, W.S., and Ryberg, K.R., 2022, Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019: U.S. Geological Survey Scientific Investigations Report 2022–5055, 11 p., https://doi.org/10.3133/sir20225055.","productDescription":"Report: iv, 11 p.; Dataset","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-134818","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":402287,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":402283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5055/coverthb.jpg"},{"id":402285,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.XML"},{"id":402284,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5055"},{"id":402286,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5055/images"},{"id":402316,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225055/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":503369,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113196.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"North Dakota, South Dakota","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.7666015625,\n              42.90816007196054\n            ],\n            [\n              -96.50390625,\n              42.90816007196054\n            ],\n            [\n              -96.50390625,\n              48.980216985374994\n            ],\n            [\n              -100.7666015625,\n              48.980216985374994\n            ],\n            [\n              -100.7666015625,\n              42.90816007196054\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/dakota-water\" data-mce-href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a> <br>U.S. Geological Survey <br>821 East Interstate Avenue, Bismarck, ND 58503 <br>1608 Mountain View Road, Rapid City, SD 57702</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods of Analysis Used in Assessing Streamflow Trends</li><li>Spatial Analysis of Streamflow Trends</li><li>Potential Factors Contributing to Increasing Streamflow Trends</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-06-17","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Norton, Parker A. 0000-0002-4638-2601 pnorton@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-2601","contributorId":2257,"corporation":false,"usgs":true,"family":"Norton","given":"Parker","email":"pnorton@usgs.gov","middleInitial":"A.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Delzer, Gregory C. 0000-0002-7077-4963 gcdelzer@usgs.gov","orcid":"https://orcid.org/0000-0002-7077-4963","contributorId":986,"corporation":false,"usgs":true,"family":"Delzer","given":"Gregory","email":"gcdelzer@usgs.gov","middleInitial":"C.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valder, Joshua F. 0000-0003-3733-8868","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":220912,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tatge, Wyatt S. 0000-0003-4414-2492","orcid":"https://orcid.org/0000-0003-4414-2492","contributorId":239544,"corporation":false,"usgs":true,"family":"Tatge","given":"Wyatt","email":"","middleInitial":"S.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844777,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70232209,"text":"fs20223042 - 2022 - Arkansas and Landsat","interactions":[],"lastModifiedDate":"2022-09-27T12:06:03.914652","indexId":"fs20223042","displayToPublicDate":"2022-06-14T09:25:10","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3042","displayTitle":"Arkansas and Landsat","title":"Arkansas and Landsat","docAbstract":"<p>Scenic Arkansas certainly lives up to its nickname, “The Natural State.” The Ozark Plateau and Ouachita Mountains boast stunning views, vast resources, and recreation. Hardwood and pine forests cover one-half of the State. The major rivers—Arkansas, Ouachita, Red, and White—offer recreation and navigation as they drain toward the Mississippi River, which forms the State’s eastern border. Smaller streams and rivers, reservoirs, and rice fields serve as homes for wildlife as well, including birds migrating along the Mississippi Flyway.</p><p>Agriculture has always been a key industry in Arkansas, which is the top rice producer in the United States. Poultry, soybeans, cotton, cattle, and timber are among other agricultural products that contribute to the State’s economy. The aquaculture industry has diversified from just goldfish to more than 20 species of fish and crustaceans.</p><p>Geological features include waterfalls, limestone caves, and the country’s only active diamond mine, Crater of Diamonds State Park, where visitors can keep any rock or mineral they find in the volcanic crater. Hot Springs National Park—within the city of Hot Springs—features thermal springs of water heated deep belowground that follow a fault line of the Ouachita Mountains up to the surface.</p><p>Here are a few ways Landsat has benefited Arkansas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223042","usgsCitation":"U.S. Geological Survey, 2022, Arkansas and Landsat: U.S. Geological Survey Fact Sheet 2022–3042, 2 p., https://doi.org/10.3133/fs20223042.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-139117","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":402141,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223042/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402139,"rank":3,"type":{"id":31,"text":"Publication 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 \"}}]}","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/programs/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/programs/national-land-imaging-program\">National Land Imaging Program</a> <br>U.S. Geological Survey <br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Monitoring Farm Reservoirs</li><li>Tracking Crops</li><li>Understanding Urban Growth</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-06-14","noUsgsAuthors":false,"publicationDate":"2022-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128240,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":844649,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70232196,"text":"70232196 - 2022 - Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data","interactions":[],"lastModifiedDate":"2022-06-13T15:44:24.981546","indexId":"70232196","displayToPublicDate":"2022-06-13T10:31:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0090\"><span>Algal blooms around the world are increasing in frequency and severity, often with the possibility of adverse effects on human and ecosystem health. The health and economic impacts associated with&nbsp;harmful algal blooms, or HABs, provide compelling rationale for developing new methods for monitoring these events via&nbsp;remote sensing. Although concentrations of chlorophyll-</span><i>a</i><span>&nbsp;and key pigments like phycocyanin are routinely estimated from satellite images and used to infer algal or cyanobacterial cell counts, current methods are unable to provide information on the taxonomic composition of a bloom. This study introduced a new approach capable of differentiating among genera based on their reflectance characteristics:&nbsp;Spectral Mixture Analysis&nbsp;for Surveillance of HABs, or SMASH. The foundation of SMASH is a multiple endmember spectral mixture analysis (MESMA) algorithm that takes a library of cyanobacteria endmembers and a hyperspectral image as input and estimates the fractional abundance of each genus, plus water, on a per-pixel basis. Importantly, we assume that the water column consists of only pure water and cyanobacteria, implying that our linear&nbsp;spectral unmixing&nbsp;models do not account for other optically active constituents such as&nbsp;suspended sediment&nbsp;and colored dissolved organic matter (CDOM). We used reflectance spectra for 12 genera measured under a microscope to populate an algal spectral library and applied the SMASH workflow to satellite images from four waterbodies across the United States. Normalized spectral separability scores indicated that the 12 genera were distinct from one another and the MESMA algorithm reproduced known input fractions for simulated mixtures that included all pairwise combinations of genera and water. We used Upper Klamath Lake as an example to illustrate data products generated via SMASH: maps of the normalized difference chlorophyll index and cyanobacterial index, a MESMA-based classification of algal genera, fraction images for each endmember, and a&nbsp;root mean square error&nbsp;(RMSE) image that summarizes uncertainty. For Upper Klamath Lake, these outputs highlighted a complex algal bloom featuring several genera, primarily&nbsp;</span><i>Aphanizomenon</i><span>, and intricate spatial patterns associated with&nbsp;gyres. The maximum RMSE constraint imposed on the MESMA algorithm provided a means of avoiding false positive detection of genera not present in a waterbody but must not be set so low as to leave much of an image unclassified in cases where genera included in the library are present. Comparison of endmember fractions with relative biovolumes calculated from field samples indicated that taxonomic information from SMASH was consistent with field observations. For example, the algorithm successfully identified&nbsp;</span><span><i>Microcystis</i></span><span>&nbsp;</span>in Owasco Lake but avoided misclassifying<span>&nbsp;</span><i>Asterionella</i>, a genus not yet included in our library, in Detroit Lake. This proof-of-concept investigation demonstrates the potential of SMASH to enhance our understanding of algal blooms, particularly with respect to their spatial and temporal dynamics.</p></div></div><div id=\"ab4005\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2022.113089","usgsCitation":"Legleiter, C.J., King, T.V., Carpenter, K.D., Hall, N., Mumford, A.C., Slonecker, E.T., Graham, J.L., Stengel, V.G., Simon, N., and Rosen, B.H., 2022, Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data: Remote Sensing of Environment, v. 279, 113089, 19 p., https://doi.org/10.1016/j.rse.2022.113089.","productDescription":"113089, 19 p.","ipdsId":"IP-135126","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - 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,{"id":70232415,"text":"70232415 - 2022 - Analysis of surface water trends for the conterminous United States using MODIS satellite data, 2003–2019","interactions":[],"lastModifiedDate":"2022-07-01T12:26:23.085105","indexId":"70232415","displayToPublicDate":"2022-06-13T07:24:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of surface water trends for the conterminous United States using MODIS satellite data, 2003–2019","docAbstract":"<div class=\"article-section__content en main\"><p>Satellite imagery is commonly used to map surface water extents over time, but many approaches yield discontinuous records resulting from cloud obstruction or image archive gaps. We applied the Dynamic Surface Water Extent (DSWE) model to downscaled (250-m) daily Moderate Resolution Imaging Spectroradiometer (MODIS) data in Google Earth Engine to generate monthly surface water maps for the conterminous United States (US) from 2003 through 2019. The aggregation of daily observations to monthly maps of maximum water extent produced records with diminished cloud and cloud shadow effects across most of the country. We used the continuous monthly record to analyze spatiotemporal surface water trends stratified within Environmental Protection Agency Ecoregions. Although not all ecoregion trends were significant (<i>p</i>&nbsp;&lt;&nbsp;0.05), results indicate that much of the western and eastern US underwent a decline in surface water over the 17-year period, while many ecoregions in the Great Plains had positive trends. Trends were also generated from monthly streamgage discharge records and compared to surface water trends from the same ecoregion. These approaches agreed on the directionality of trend detected for 54 of 85 ecoregions, particularly across the Great Plains and portions of the western US, whereas trends were not congruent in select western deserts, the Great Lakes region, and the southeastern US. By describing the geographic distribution of surface water over time and comparing these records to instrumented discharge data across the conterminous US, our findings demonstrate the efficacy of using satellite imagery to monitor surface water dynamics and supplement traditional instrumented monitoring.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021WR031399","usgsCitation":"Petrakis, R., Soulard, C.E., Waller, E.K., and Walker, J., 2022, Analysis of surface water trends for the conterminous United States using MODIS satellite data, 2003–2019: Water Resources Research, v. 58, no. 6, e2021WR031399, 24 p., https://doi.org/10.1029/2021WR031399.","productDescription":"e2021WR031399, 24 p.","ipdsId":"IP-129527","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":447457,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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          -124.14214,\n                43.70838\n              ],\n              [\n                -124.02053,\n                44.6159\n              ],\n              [\n                -123.89893,\n                45.52341\n              ],\n              [\n                -124.07963,\n                46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"58","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":845474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":845475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waller, Eric K. 0000-0002-9169-9210","orcid":"https://orcid.org/0000-0002-9169-9210","contributorId":203496,"corporation":false,"usgs":true,"family":"Waller","given":"Eric","email":"","middleInitial":"K.","affiliations":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":845476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walker, Jessica J. 0000-0002-3225-0317","orcid":"https://orcid.org/0000-0002-3225-0317","contributorId":207373,"corporation":false,"usgs":true,"family":"Walker","given":"Jessica J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":845477,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70246519,"text":"70246519 - 2022 - A novel method for conducting a geoenvironmental assessment of undiscovered ISR-amenable uranium Resources: Proof-of-concept in the Texas Coastal Plain","interactions":[],"lastModifiedDate":"2023-07-07T11:52:02.950211","indexId":"70246519","displayToPublicDate":"2022-06-12T06:46:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5207,"text":"Minerals","active":true,"publicationSubtype":{"id":10}},"title":"A novel method for conducting a geoenvironmental assessment of undiscovered ISR-amenable uranium Resources: Proof-of-concept in the Texas Coastal Plain","docAbstract":"<div class=\"html-p\">A geoenvironmental assessment methodology was developed to estimate waste quantities and disturbances that could be associated with the extraction of undiscovered uranium resources and identify areas on the landscape where uranium and other constituents of potential concern (COPCs) that may co-occur with uranium deposits in this region are likely to persist, if introduced into the environment. Prior to this work, a method was lacking to quantitively assess the environmental aspects associated with potential development of undiscovered uranium resources at a scale of a uranium resource assessment. The mining method of in situ recovery (ISR) was historically used to extract uranium from deposits in the Goliad Sand of the Texas Coastal Plain. For this reason, the study’s methodology projected the following types of wastes and disturbances commonly associated with ISR based on historical ISR mining records: the mine area, affected aquifer volume, mine pore volume, water pumped and disposed during uranium extraction and restoration, and radon emissions. Within the tract permissive for the occurrence of undiscovered uranium resources, maps and statistics of factors were derived that indicate the potential contaminant pathways. The percentage of days meeting the criteria for air stagnation indicate the potential for radon accumulation; the geochemical mobility of COPCs in groundwater in combination with effective recharge indicates the potential for infiltration of surface-derived COPCs; the geochemical mobility of COPCs in groundwater combined with hydraulic conductivity indicates the propensity for transmitting fluids away from contaminated or mined aquifers; and finally, geochemical mobility of COPCs in surface water combined with the factor for climatic erosivity (R factor) indicates the potential for COPCs to persist in surface waters due to runoff. This work resulted in a new methodology that can be applied to any undiscovered mineral resource to better understand possible wastes and disturbances associated with extraction and identify areas on the landscape where COPCs are likely to persist.</div>","language":"English","publisher":"MDPI","doi":"10.3390/min12060747","usgsCitation":"Gallegos, T., Stengel, V.G., Walton-Day, K., Blake, J., Teeple, A., Humberson, D.G., Cahan, S., Yager, D., and Becher, K.D., 2022, A novel method for conducting a geoenvironmental assessment of undiscovered ISR-amenable uranium Resources: Proof-of-concept in the Texas Coastal Plain: Minerals, v. 12, no. 6, 747, 21 p., https://doi.org/10.3390/min12060747.","productDescription":"747, 21 p.","ipdsId":"IP-136342","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":447469,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/min12060747","text":"Publisher Index Page"},{"id":418741,"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        \"coordinates\": [\n          [\n            [\n              -96.9175352631714,\n              25.819063287006443\n            ],\n            [\n              -96.82968233171721,\n              27.662685556706492\n            ],\n            [\n              -95.42403542845311,\n              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Center","active":true,"usgs":true}],"preferred":true,"id":877021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stengel, Victoria G. 0000-0003-0481-3159 vstengel@usgs.gov","orcid":"https://orcid.org/0000-0003-0481-3159","contributorId":5932,"corporation":false,"usgs":true,"family":"Stengel","given":"Victoria","email":"vstengel@usgs.gov","middleInitial":"G.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":877022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":184043,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":877023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blake, Johanna 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":217272,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":877024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teeple, Andrew 0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":193061,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":877025,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Humberson, Delbert G 0000-0001-6789-9135","orcid":"https://orcid.org/0000-0001-6789-9135","contributorId":240891,"corporation":false,"usgs":false,"family":"Humberson","given":"Delbert","email":"","middleInitial":"G","affiliations":[],"preferred":false,"id":877026,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cahan, Steven M. 0000-0002-4776-3668","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":205929,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":877027,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yager, Douglas 0000-0001-5074-4022","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":202073,"corporation":false,"usgs":true,"family":"Yager","given":"Douglas","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":877028,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Becher, Kent D 0000-0002-3947-0793","orcid":"https://orcid.org/0000-0002-3947-0793","contributorId":290642,"corporation":false,"usgs":false,"family":"Becher","given":"Kent","email":"","middleInitial":"D","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":877029,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70246521,"text":"70246521 - 2022 - U-Pb and fission-track data from zircon and apatite resolve latest- and post-Alleghanian thermal histories along the Fall Line of the Atlantic margin of the southeastern United States","interactions":[],"lastModifiedDate":"2023-07-07T12:21:17.568399","indexId":"70246521","displayToPublicDate":"2022-06-10T07:18:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"U-Pb and fission-track data from zircon and apatite resolve latest- and post-Alleghanian thermal histories along the Fall Line of the Atlantic margin of the southeastern United States","docAbstract":"<div id=\"134124394\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>Although the Atlantic continental margin of the eastern United States is an archetypal passive margin, episodes of rejuvenation following continental breakup are increasingly well documented. To better constrain this history of rejuvenation along the southern portion of this continental margin, we present zircon U-Pb (ZUPb) age, zircon fission-track (ZFT) age, apatite U-Pb (AUPb) age, and apatite fission-track (AFT) age and length data from six bedrock samples. The samples were collected along the boundary between the exposed Appalachian hinterland (Piedmont province) and the updip limit of passive margin strata (Coastal Plain province). The samples were collected from central Virginia southward to the South Carolina–Georgia border. ZUPb age distributions are generally consistent with geologic mapping in each of the sample areas. The AUPb data are highly discordant owing to high common-Pb abundances, but for two plutons at the northern and southern ends of the sample area, they define a discordia regression line that indicates substantial Permo-Triassic exhumation-driven cooling. ZFT age distributions are highly dispersed but define central values ranging from Permian to Jurassic. AFT data mostly appear to define a singular underlying cooling age, generally approximately Jurassic or Early Cretaceous. Apatite fission tracks are moderately long (mean lengths in the range of ~13.5 µm), however track lengths for one sample in central North Carolina are shorter (~12.5 µm). To interpret the post-breakup thermal history, we present inverse models of time-temperature history for the five plutonic samples. The models show a history of (1) rapid cooling (&gt;10 °C/m.y.) from deep-crustal to near-surface temperatures by the Triassic, (2) hundreds of degrees of Triassic reheating, (3) Jurassic–Early Cretaceous cooling (at rates of 1–10 °C/m.y.), and (4) slow Late Cretaceous–Cenozoic cooling (~1 °C/m.y.). An additional suite of forward models is presented to further evaluate the magnitude of maximum Triassic reheating at one sample site that is particularly well constrained by thermal maturity data. The model results and geologic reasoning suggest that the inverse models may overestimate Triassic paleotemperatures but that other aspects of the inverse modeling are robust. Overall, this thermal history can be reconciled with several aspects of the lithostratigraphy of distal parts of the continental margin, including the lack of Jurassic–earliest Cretaceous strata beneath the southern Atlantic coastal plain and Cretaceous–Cenozoic grain-size trends.</p></div>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02447.1","usgsCitation":"Craddock, W.H., O'Sullivan, P., and McAleer, R.J., 2022, U-Pb and fission-track data from zircon and apatite resolve latest- and post-Alleghanian thermal histories along the Fall Line of the Atlantic margin of the southeastern United States: Geosphere, v. 18, no. 4, p. 1330-1353, https://doi.org/10.1130/GES02447.1.","productDescription":"24 p.","startPage":"1330","endPage":"1353","ipdsId":"IP-127916","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":447476,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02447.1","text":"Publisher Index Page"},{"id":418744,"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        \"coordinates\": [\n          [\n            [\n              -76.06589631767767,\n              40.62761013989578\n            ],\n            [\n              -76.81264623503682,\n              40.32689154960596\n            ],\n            [\n              -79.40430771293059,\n              40.02563596082908\n            ],\n            [\n              -81.51277806782672,\n              38.76941324786962\n            ],\n            [\n              -83.62124842272343,\n              36.33152035458974\n            ],\n            [\n              -84.63155713444466,\n              33.778910284254295\n            ],\n            [\n              -83.84088075135841,\n              32.7874625650833\n            ],\n            [\n              -82.1277485880051,\n              31.4481799351054\n            ],\n            [\n              -80.32676349319762,\n              31.672755039272587\n            ],\n            [\n              -77.51546968666938,\n              33.22949605942023\n            ],\n            [\n              -75.14344053741085,\n              35.02409793894682\n            ],\n            [\n              -73.12282311396812,\n              37.10613979176382\n            ],\n            [\n              -73.47423483978443,\n              39.24678773255735\n            ],\n            [\n              -76.06589631767767,\n              40.62761013989578\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"18","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":877037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Sullivan, Paul","contributorId":257903,"corporation":false,"usgs":false,"family":"O'Sullivan","given":"Paul","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":877038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":877039,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70232190,"text":"70232190 - 2022 - Dissolved organic matter within oil and gas associated wastewaters from U.S. unconventional petroleum plays: Comparisons and consequences for disposal and reuse","interactions":[],"lastModifiedDate":"2022-06-10T12:00:56.942391","indexId":"70232190","displayToPublicDate":"2022-06-08T06:53:55","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":"Dissolved organic matter within oil and gas associated wastewaters from U.S. unconventional petroleum plays: Comparisons and consequences for disposal and reuse","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0030\"><span>Wastewater generated during petroleum extraction (produced water) may contain high concentrations of dissolved organics due to their intimate association with organic-rich source rocks, expelled petroleum, and organic additives to fluids used for hydraulic fracturing of unconventional (e.g., shale) reservoirs. Dissolved organic matter (DOM) within produced water represents a challenge for treatment prior to beneficial reuse. High&nbsp;salinities&nbsp;characteristic of produced water, often 10× greater than seawater, coupled to the complex DOM ensemble create analytical obstacles with typical methods. Excitation-emission matrix&nbsp;</span>spectroscopy<span>&nbsp;(EEMS) can rapidly characterize the fluorescent component of DOM with little impact from matrix effects. We applied EEMS to evaluate DOM composition in 18 produced water samples from six North American unconventional petroleum plays. Represented reservoirs include the Eagle Ford Shale (Gulf Coast Basin), Wolfcamp/Cline Shales (Permian Basin), Marcellus Shale and Utica/Point Pleasant (Appalachian Basin), Niobrara Chalk (Denver-Julesburg Basin), and the Bakken Formation (Williston Basin). Results indicate that the relative chromophoric DOM composition in unconventional produced water may distinguish different&nbsp;lithologies,&nbsp;thermal maturity&nbsp;of resource types (e.g., heavy oil vs. dry gas), and fracturing fluid compositions, but is generally insensitive to salinity and DOM concentration. These results are discussed with perspective toward DOM influence on geochemical processes and the potential for targeted organic compound treatment for the reuse of produced water.</span></p></div></div><div id=\"ab0010\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.156331","usgsCitation":"McDevitt, B., Jubb, A., Varonka, M., Blondes, M., Engle, M.A., Gallegos, T., and Shelton, J., 2022, Dissolved organic matter within oil and gas associated wastewaters from U.S. unconventional petroleum plays: Comparisons and consequences for disposal and reuse: Science of the Total Environment, v. 838, no. 3, 156331, 10 p., https://doi.org/10.1016/j.scitotenv.2022.156331.","productDescription":"156331, 10 p.","ipdsId":"IP-133441","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science 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79968","active":true,"usgs":false}],"preferred":false,"id":844519,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gallegos, Tanya J. 0000-0003-3350-6473","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":206859,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":844520,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shelton, Jenna L. 0000-0002-1377-0675 jlshelton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-0675","contributorId":5025,"corporation":false,"usgs":true,"family":"Shelton","given":"Jenna L.","email":"jlshelton@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":844521,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70232234,"text":"70232234 - 2022 - Decadal-scale phenology and seasonal climate drivers of migratory baleen whales in a rapidly warming marine ecosystem","interactions":[],"lastModifiedDate":"2022-08-02T14:40:28.06704","indexId":"70232234","displayToPublicDate":"2022-06-07T09:04:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Decadal-scale phenology and seasonal climate drivers of migratory baleen whales in a rapidly warming marine ecosystem","docAbstract":"<p><span>Species' response to rapid climate change can be measured through shifts in timing of recurring biological events, known as phenology. The Gulf of Maine is one of the most rapidly warming regions of the ocean, and thus an ideal system to study phenological and biological responses to climate change. A better understanding of climate-induced changes in phenology is needed to effectively and adaptively manage human-wildlife conflicts. Using data from a 20+ year marine mammal observation program, we tested the hypothesis that the phenology of large whale habitat use in Cape Cod Bay has changed and is related to regional-scale shifts in the thermal onset of spring. We used a multi-season occupancy model to measure phenological shifts and evaluate trends in the date of peak habitat use for North Atlantic right (</span><i>Eubalaena glacialis</i><span>), humpback (</span><i>Megaptera novaeangliae</i><span>), and fin (</span><i>Balaenoptera physalus</i><span>) whales. The date of peak habitat use shifted by +18.1 days (0.90 days/year) for right whales and +19.1 days (0.96 days/year) for humpback whales. We then evaluated interannual variability in peak habitat use relative to thermal spring transition dates (STD), and hypothesized that right whales, as planktivorous specialist feeders, would exhibit a stronger response to thermal phenology than fin and humpback whales, which are more generalist piscivorous feeders. There was a significant negative effect of western region STD on right whale habitat use, and a significant positive effect of eastern region STD on fin whale habitat use indicating differential responses to spatial seasonal conditions. Protections for threatened and endangered whales have been designed to align with expected phenology of habitat use. Our results show that whales are becoming mismatched with static seasonal management measures through shifts in their timing of habitat use, and they suggest that effective management strategies may need to alter protections as species adapt to climate change.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16225","usgsCitation":"Pendleton, D., Tingley, M., Ganley, L., Friedland, K., Mayo, C., Brown, M., McKenna, B., Jordaan, A., and Staudinger, M., 2022, Decadal-scale phenology and seasonal climate drivers of migratory baleen whales in a rapidly warming marine ecosystem: Global Change Biology, v. 28, no. 16, p. 4989-5005, https://doi.org/10.1111/gcb.16225.","productDescription":"17 p.","startPage":"4989","endPage":"5005","ipdsId":"IP-135322","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447501,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.16225","text":"External Repository"},{"id":402267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.6640625,\n              41.72213058512578\n            ],\n            [\n              -70.02685546875,\n              41.72213058512578\n            ],\n            [\n              -70.02685546875,\n              42.261049162113856\n            ],\n            [\n              -70.6640625,\n              42.261049162113856\n            ],\n            [\n              -70.6640625,\n              41.72213058512578\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","issue":"16","noUsgsAuthors":false,"publicationDate":"2022-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Pendleton, Dan","contributorId":292480,"corporation":false,"usgs":false,"family":"Pendleton","given":"Dan","email":"","affiliations":[{"id":48127,"text":"Anderson Cabot Center for Marine Life","active":true,"usgs":false}],"preferred":false,"id":844744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tingley, Morgan","contributorId":292481,"corporation":false,"usgs":false,"family":"Tingley","given":"Morgan","affiliations":[],"preferred":false,"id":844745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganley, Laura","contributorId":292482,"corporation":false,"usgs":false,"family":"Ganley","given":"Laura","email":"","affiliations":[],"preferred":false,"id":844746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friedland, Kevin","contributorId":292483,"corporation":false,"usgs":false,"family":"Friedland","given":"Kevin","affiliations":[],"preferred":false,"id":844747,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mayo, Charlie","contributorId":292484,"corporation":false,"usgs":false,"family":"Mayo","given":"Charlie","email":"","affiliations":[],"preferred":false,"id":844748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Moria","contributorId":292485,"corporation":false,"usgs":false,"family":"Brown","given":"Moria","email":"","affiliations":[],"preferred":false,"id":844749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKenna, Brigid","contributorId":292486,"corporation":false,"usgs":false,"family":"McKenna","given":"Brigid","email":"","affiliations":[],"preferred":false,"id":844750,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jordaan, Adrian","contributorId":292487,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[],"preferred":false,"id":844751,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Staudinger, Michelle 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":205971,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":844752,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70236870,"text":"70236870 - 2022 - Can’t see the flowers for the trees: Factors driving floral abundance within early-successional forests in the central Appalachian Mountains","interactions":[],"lastModifiedDate":"2022-09-21T13:55:01.164776","indexId":"70236870","displayToPublicDate":"2022-06-07T08:49:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1170,"text":"Canadian Journal of Forest Research","active":true,"publicationSubtype":{"id":10}},"title":"Can’t see the flowers for the trees: Factors driving floral abundance within early-successional forests in the central Appalachian Mountains","docAbstract":"<p><span>Silviculture can be a powerful tool for restoring and enhancing habitat for forest-dependent wildlife. In eastern North America, regenerating timber harvests support abundant wildflowers that provide essential forage for native pollinators. Factors driving floral resource availability within regenerating forests remain almost entirely unstudied. Recent efforts to increase the area of regenerating forests (&lt;10&nbsp;years old) through overstory removal harvest in the central Appalachian Mountains provide an opportunity to investigate the development of forest wildflower communities following canopy removal. We conducted 1208 surveys of blooming plants across 143 harvests, recording 1 525</span><span data-style=\"monospace\"> </span><span>245 flowers representing 220 taxa spanning 47 families. The number of flowers within recently harvested stands was negatively associated with fern and sapling cover but positively associated with grass and bramble (</span><i>Rubus</i><span>&nbsp;spp.) cover. Early in the growing season, more flowers bloomed in older regenerating stands (e.g., &gt;5&nbsp;years old), but this pattern reversed by the end of the growing season. Ultimately, our study demonstrates that the abundance of flowers available to pollinators within regenerating hardwood stands varies with factors associated with advancing succession. Recognizing the potential trade-off between woody regeneration (i.e., saplings) and pollinator forage availability may benefit forest managers who intend to provide floral resources to flower-dependent wildlife like pollinators via silviculture.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfr-2022-0014","usgsCitation":"Mathis, C.L., McNeil, D.J., Lee, M.R., Grozinger, C.M., Otto, C., and Larkin, J.L., 2022, Can’t see the flowers for the trees: Factors driving floral abundance within early-successional forests in the central Appalachian Mountains: Canadian Journal of Forest Research, v. 52, no. 7, p. 1002-1013, https://doi.org/10.1139/cjfr-2022-0014.","productDescription":"12 p.","startPage":"1002","endPage":"1013","ipdsId":"IP-137022","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":407133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"central Appalachian Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.62890625,\n              39.740986355883564\n            ],\n            [\n              -76.8218994140625,\n              39.740986355883564\n            ],\n            [\n              -74.77294921875,\n              41.1290213474951\n            ],\n            [\n              -76.17919921875,\n              41.83682786072714\n            ],\n            [\n              -79.62890625,\n              39.740986355883564\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"52","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mathis, Codey L.","contributorId":264822,"corporation":false,"usgs":false,"family":"Mathis","given":"Codey","email":"","middleInitial":"L.","affiliations":[{"id":54565,"text":"Indiana Un of Penns","active":true,"usgs":false}],"preferred":false,"id":852427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNeil, Daren J. Jr.","contributorId":264823,"corporation":false,"usgs":false,"family":"McNeil","given":"Daren","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":54566,"text":"Penn State Un","active":true,"usgs":false}],"preferred":false,"id":852428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Monica R.","contributorId":264824,"corporation":false,"usgs":false,"family":"Lee","given":"Monica","email":"","middleInitial":"R.","affiliations":[{"id":54565,"text":"Indiana Un of Penns","active":true,"usgs":false}],"preferred":false,"id":852429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grozinger, Christina M.","contributorId":214374,"corporation":false,"usgs":false,"family":"Grozinger","given":"Christina","email":"","middleInitial":"M.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":852430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":852431,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Larkin, Jeffery L.","contributorId":264972,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeffery","email":"","middleInitial":"L.","affiliations":[{"id":16979,"text":"University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":852624,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70232138,"text":"70232138 - 2022 - Regional walrus abundance estimate in the United States Chukchi Sea in autumn","interactions":[],"lastModifiedDate":"2022-08-02T14:29:29.483926","indexId":"70232138","displayToPublicDate":"2022-06-06T06:57:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Regional walrus abundance estimate in the United States Chukchi Sea in autumn","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Human activities (e.g., shipping, tourism, oil, gas development) have increased in the Chukchi Sea because of declining sea ice. The declining sea ice itself and these activities may affect Pacific walrus (<i>Odobenus rosmarus divergens</i>) abundance; however, previous walrus abundance estimates have been notably imprecise. When sea ice is absent from the eastern Chukchi Sea, walruses in waters of the United States usually rest together onshore at a single Alaska coastal haulout, where they can be surveyed more easily than when they rest on dispersed offshore ice floes. We estimated the number of walruses on land (herd size) at this haulout from 13 unoccupied aircraft system (UAS) surveys flown within a 10-day period in each of 2018 and 2019. We estimated population size of walruses using the haulout over the course of the surveys by combining herd size data with data from satellite-linked transmitters that indicated whether tagged walruses were in or out of water during each survey. Our estimates of the population size of walruses using the haulout during each year's survey period were similar to each other and more precise than historical walrus abundance estimates: posterior means (95% credibility intervals) were 166,000 (133,000–201,000) for 2018 and 189,000 (135,000–251,000) for 2019. Auxiliary observations support using these estimates to represent the size of the population using the eastern Chukchi Sea in autumn during the surveyed years. Our study site was the only substantial Chukchi Sea coastal haulout in the United States during the survey periods and study-specific tracking data (consistent with known distribution and movement patterns) indicated tagged walruses remained in eastern Chukchi waters during the survey periods. In addition, the imagery, telemetry, and analytical methods developed for this study advance the prospect for precise range-wide walrus population size estimates.</p></div></div>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22256","usgsCitation":"Fischbach, A.S., Taylor, R.L., and Jay, C.V., 2022, Regional walrus abundance estimate in the United States Chukchi Sea in autumn: Journal of Wildlife Management, v. 86, no. 6, e22256, 18 p., https://doi.org/10.1002/jwmg.22256.","productDescription":"e22256, 18 p.","ipdsId":"IP-128374","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":447525,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22256","text":"Publisher Index Page"},{"id":435820,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X1C0WX","text":"USGS data release","linkHelpText":"Walrus Haulout Aerial Survey Data Near Point Lay Alaska, Autumn 2018 and 2019"},{"id":435819,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DB7ZWP","text":"USGS data release","linkHelpText":"Behavior of Pacific Walruses (Odobenus rosmarus divergens) Hauled Out on Sea Ice During UAS Overflights, Eastern Chukchi Sea, 2015 "},{"id":435818,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FQ9TP6","text":"USGS data release","linkHelpText":"Tracking Data for Pacific Walrus (Odobenus rosmarus divergens)"},{"id":401915,"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              -163.3447265625,\n              67.15289820820026\n            ],\n            [\n              -152.490234375,\n              70.65633017009853\n            ],\n            [\n              -153.896484375,\n              71.6498329432346\n            ],\n            [\n              -158.994140625,\n              71.76019138754775\n            ],\n            [\n              -165.58593749999997,\n              70.58341752317065\n            ],\n            [\n              -167.431640625,\n              69.28725695167886\n            ],\n            [\n              -167.431640625,\n              67.60922060496382\n            ],\n            [\n              -164.7509765625,\n              66.93006025862448\n            ],\n            [\n              -163.3447265625,\n              67.15289820820026\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"86","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":844322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":844323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":844324,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70232183,"text":"70232183 - 2022 - Damage assessment for the 2018 lower East Rift Zone lava flows of Kīlauea volcano, Hawaiʻi","interactions":[],"lastModifiedDate":"2022-06-10T11:53:01.951056","indexId":"70232183","displayToPublicDate":"2022-06-06T06:50:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Damage assessment for the 2018 lower East Rift Zone lava flows of Kīlauea volcano, Hawaiʻi","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Cataloguing damage and its correlation with hazard intensity is one of the key components needed to robustly assess future risk and plan for mitigation as it provides important empirical data. Damage assessments following volcanic eruptions have been conducted for buildings and other structures following hazards such as tephra fall, pyroclastic density currents, and lahars. However, there are relatively limited quantitative descriptions of the damage caused by lava flows, despite the number of communities that have been devastated by lava flows in recent decades (e.g., Cumbre Vieja, La Palma, 2021; Nyiragongo, Democratic Republic of Congo, 2002 and 2021; Fogo, Cape Verde, 2014–2015). The 2018 lower East Rift Zone (LERZ) lava flows of Kīlauea volcano, Hawaiʻi, inundated 32.4 km<sup>2</sup><span>&nbsp;</span>of land in the Puna District, including residential properties, infrastructure, and farmland. During and after the eruption, US Geological Survey scientists and collaborators took over 8000 aerial and ground photographs and videos of the eruption processes, deposits, and impacts. This reconnaissance created one of the largest available impact datasets documenting an effusive eruption and provided a unique opportunity to conduct a comprehensive damage assessment. Drawing on this georeferenced dataset, satellite imagery, and 2019 ground-based damage surveys, we assessed the pre-event typology and post-event condition of structures within and adjacent to the area inundated by lava flows during the 2018 LERZ eruption. We created a database of damage: each structure was assigned a newly developed damage state and data quality category value. We assessed 3165 structures within the Puna District and classified 1839 structures (58%) as destroyed, 90 structures (3%) as damaged, and 1236 (39%) as unaffected. We observed a range of damage states, affected by the structural typology and hazard characteristics. Our study reveals that structures may be damaged or destroyed beyond the lava flow margin, due to thermal effects from the lava flow, fire spread, or from exposure to a range of hazards associated with fissure eruptions, such as steam, volcanic gases, or tephra fall. This study provides a major contribution to the currently limited evidence base required to forecast future lava flow impacts and assess risk.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01568-2","usgsCitation":"Meredith, E.S., Jenkins, S.F., Hayes, J.L., Deligne, N.I., Lallemant, D., Patrick, M.R., and Neal, C.A., 2022, Damage assessment for the 2018 lower East Rift Zone lava flows of Kīlauea volcano, Hawaiʻi: Bulletin of Volcanology, v. 84, 65, 23 p., https://doi.org/10.1007/s00445-022-01568-2.","productDescription":"65, 23 p.","ipdsId":"IP-130595","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":447528,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-022-01568-2","text":"Publisher Index Page"},{"id":402057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.3521728515625,\n              19.32280716454424\n            ],\n            [\n              -155.126953125,\n              19.32280716454424\n            ],\n            [\n              -155.126953125,\n              19.480834276134903\n            ],\n            [\n              -155.3521728515625,\n              19.480834276134903\n            ],\n            [\n              -155.3521728515625,\n              19.32280716454424\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"84","noUsgsAuthors":false,"publicationDate":"2022-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Meredith, Elinor S. 0000-0002-3869-1180","orcid":"https://orcid.org/0000-0002-3869-1180","contributorId":270269,"corporation":false,"usgs":false,"family":"Meredith","given":"Elinor","email":"","middleInitial":"S.","affiliations":[{"id":56128,"text":"Earth Observatory of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":844485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Susanna F. 0000-0002-7523-1423","orcid":"https://orcid.org/0000-0002-7523-1423","contributorId":270268,"corporation":false,"usgs":false,"family":"Jenkins","given":"Susanna","email":"","middleInitial":"F.","affiliations":[{"id":56128,"text":"Earth Observatory of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":844486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Josh L. 0000-0001-7099-1063","orcid":"https://orcid.org/0000-0001-7099-1063","contributorId":270275,"corporation":false,"usgs":false,"family":"Hayes","given":"Josh","email":"","middleInitial":"L.","affiliations":[{"id":56128,"text":"Earth Observatory of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":844487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deligne, Natalia I. 0000-0001-9221-8581","orcid":"https://orcid.org/0000-0001-9221-8581","contributorId":257389,"corporation":false,"usgs":true,"family":"Deligne","given":"Natalia","email":"","middleInitial":"I.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":844488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lallemant, David 0000-0001-5759-9972","orcid":"https://orcid.org/0000-0001-5759-9972","contributorId":290680,"corporation":false,"usgs":false,"family":"Lallemant","given":"David","email":"","affiliations":[{"id":16631,"text":"Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":844489,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":844490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neal, Christina A. 0000-0002-7697-7825 tneal@usgs.gov","orcid":"https://orcid.org/0000-0002-7697-7825","contributorId":131135,"corporation":false,"usgs":true,"family":"Neal","given":"Christina","email":"tneal@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":844491,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70232131,"text":"70232131 - 2022 - Maintenance and dissemination of avian-origin influenza A virus within the northern Atlantic Flyway of North America","interactions":[],"lastModifiedDate":"2023-01-06T13:11:09.711099","indexId":"70232131","displayToPublicDate":"2022-06-06T06:40:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2981,"text":"PLoS Pathogens","active":true,"publicationSubtype":{"id":10}},"title":"Maintenance and dissemination of avian-origin influenza A virus within the northern Atlantic Flyway of North America","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>Wild waterbirds, the natural reservoirs for avian influenza viruses, undergo migratory movements each year, connecting breeding and wintering grounds within broad corridors known as flyways. In a continental or global view, the study of virus movements within and across flyways is important to understanding virus diversity, evolution, and movement. From 2015 to 2017, we sampled waterfowl from breeding (Maine) and wintering (Maryland) areas within the Atlantic Flyway (AF) along the east coast of North America to investigate the spatio-temporal trends in persistence and spread of influenza A viruses (IAV). We isolated 109 IAVs from 1,821 cloacal / oropharyngeal samples targeting mallards<span>&nbsp;</span><i>(Anas platyrhynchos)</i><span>&nbsp;</span>and American black ducks<span>&nbsp;</span><i>(Anas rubripes)</i>, two species having ecological and conservation importance in the flyway that are also host reservoirs of IAV. Isolates with &gt;99% nucleotide similarity at all gene segments were found between eight pairs of birds in the northern site across years, indicating some degree of stability among genome constellations and the possibility of environmental persistence. No movement of whole genome constellations were identified between the two parts of the flyway, however, virus gene flow between the northern and southern study locations was evident. Examination of banding records indicate direct migratory waterfowl movements between the two locations within an annual season, providing a mechanism for the inferred viral gene flow. Bayesian phylogenetic analyses provided evidence for virus dissemination from other North American wild birds to AF dabbling ducks (Anatinae), shorebirds (Charidriformes), and poultry (Galliformes). Evidence was found for virus dissemination from shorebirds to gulls (Laridae), and dabbling ducks to shorebirds and poultry. The findings from this study contribute to the understanding of IAV ecology in waterfowl within the AF.</p></div></div>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.ppat.1010605","usgsCitation":"Prosser, D., Chen, J., Ahlstrom, C., Reeves, A.B., Poulson, R., Sullivan, J.D., McAuley, D., Callahan, C.R., McGowan, P.C., Bahl, J., Stallknecht, D., and Ramey, A.M., 2022, Maintenance and dissemination of avian-origin influenza A virus within the northern Atlantic Flyway of North America: PLoS Pathogens, v. 18, no. 6, e1010605, 25 p., https://doi.org/10.1371/journal.ppat.1010605.","productDescription":"e1010605, 25 p.","ipdsId":"IP-134661","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447535,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.ppat.1010605","text":"Publisher Index Page"},{"id":435822,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UF27FI","text":"USGS data release","linkHelpText":"Data concerning maintenance and dissemination of avian-origin influenza A virus within the Northern Atlantic Flyway of North America"},{"id":401911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.87109375,\n              36.491973470593685\n            ],\n            [\n              -75.322265625,\n              36.491973470593685\n            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Georgia","active":true,"usgs":false}],"preferred":false,"id":844293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahlstrom, Christina 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":214540,"corporation":false,"usgs":true,"family":"Ahlstrom","given":"Christina","email":"","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":844294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology 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,{"id":70231907,"text":"70231907 - 2022 - Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","interactions":[],"lastModifiedDate":"2023-01-18T15:51:07.526101","indexId":"70231907","displayToPublicDate":"2022-06-03T08:32:14","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":"Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","docAbstract":"<p>The North American Wetlands Conservation Act (16 U.S.C. 4401-4412) provided funding and administration for wetland management and conservation projects. The North American Wetland Conservation Fund, enabled in 1989 with the Act, provides financial resources. Resource allocation decisions are based, in part, on regional experts, particularly migratory bird Joint Ventures (JVs) (i.e., partnerships for cooperative planning and coordinated management of the continent’s waterfowl populations and habitats). The JVs evaluate funding proposals submitted with their respective regions each year and make funding recommendations to decision makers. Proposal evaluation procedures differ among JVs, however, it could be helpful to consider a transparent, repeatable, and data-driven framework for prioritization within regions. We used structured decision making and linear additive value models for ranking proposals within JV regions. We used two JVs as case studies and constructed two different value models using JV-specific objectives and weights. The framework was developed through a collaborative process with JV staff and stakeholders. Models were written in Microsoft Excel. To test these models, we used six NAWCA proposals submitted to the Upper Mississippi / Great Lakes Joint Venture in 2016 and seven proposals submitted to the Gulf Coast Joint Venture in 2017. We compared proposal ranks assigned by the value model to ranks assigned by each JV’s management board. Ranks assigned by the value model differed from ranks assigned by the board for the Upper Mississippi / Great Lakes Joint Venture, but not for the Gulf Coast Joint Venture. However, ranks from the value model could change markedly with different objective weights and value functions. The weighted linear value model was beneficial for ranking NAWCA proposals because it allows JVs to treat the ranking as a multiple objective problem and tailor the ranking to their specific regional concerns. We believe a structured decision making approach could be adapted by JV staff to facilitate a systematic and transparent process for proposal ranking by their management boards.</p>","language":"English","publisher":"U. S. Fish and Wildlife Service","doi":"10.3996/JFWM-21-089","usgsCitation":"Krainyk, A., Lyons, J.E., Soulliere, G.J., Coluccy, J.M., Wilson, B.C., Brasher, M.G., Al-Saffar, M.A., and Humburg, D.D., 2022, Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 375-395, https://doi.org/10.3996/JFWM-21-089.","productDescription":"21 p.","startPage":"375","endPage":"395","ipdsId":"IP-122603","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447556,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-089","text":"Publisher Index Page"},{"id":401678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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States\"}}]}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Krainyk, Anastasia 0000-0002-3100-9011","orcid":"https://orcid.org/0000-0002-3100-9011","contributorId":214391,"corporation":false,"usgs":true,"family":"Krainyk","given":"Anastasia","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soulliere, Gregory J.","contributorId":172329,"corporation":false,"usgs":false,"family":"Soulliere","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":844087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coluccy, John M.","contributorId":111382,"corporation":false,"usgs":true,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":844088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Barry C.","contributorId":12968,"corporation":false,"usgs":true,"family":"Wilson","given":"Barry","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":844089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brasher, Michael G.","contributorId":214393,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":844090,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Al-Saffar, Mohammed A","contributorId":292215,"corporation":false,"usgs":false,"family":"Al-Saffar","given":"Mohammed","email":"","middleInitial":"A","affiliations":[{"id":62842,"text":"USWFS","active":true,"usgs":false}],"preferred":false,"id":844091,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":844092,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70231846,"text":"sir20215113 - 2022 - Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","interactions":[],"lastModifiedDate":"2026-04-02T19:46:57.445783","indexId":"sir20215113","displayToPublicDate":"2022-06-03T08:07:20","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":"2021-5113","displayTitle":"Long-Term Groundwater Availability in the Waihe‘e, ‘Īao, and Waikapū Aquifer Systems, Maui, Hawai‘i","title":"Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","docAbstract":"<p>Groundwater levels have declined since the 1940s in the Wailuku area of central Maui, Hawai‘i, on the eastern flank of West Maui volcano, mainly in response to increased groundwater withdrawals. Available data since the 1980s also indicate a thinning of the freshwater lens and an increase in chloride concentrations of pumped water from production wells. These trends, combined with projected increases in demand for groundwater in central Maui, have led to concerns over groundwater availability and have highlighted a need to improve general understanding of the hydrologic effects of proposed groundwater withdrawals in the Waihe‘e, ‘Īao, and Waikapū areas of central Maui.</p><p>A numerical groundwater model was constructed to simulate the flow and salinity of groundwater in central Maui. The model simulates the effects of changes in groundwater withdrawals and recharge on water levels, freshwater-lens thicknesses, and chloride concentrations of pumped water from production wells. The model incorporates updated water-budget estimates of groundwater recharge from infiltration and direct recharge, seepage in stream channels, and inflow from inland areas. Mean annual groundwater recharge from infiltration and direct recharge was estimated using a daily water-budget model and the most current data, including the distributions of monthly rainfall and potential evapotranspiration, for the study area for nine historical periods from 1926 through 2012: 1926–69, 1970–79, 1980–84, 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, and 2010–12. The water-budget model also estimated groundwater recharge based on one hypothetical scenario that used 1980–2010 rainfall and 2017 land cover. For the nine historical periods, estimated recharge from infiltration and direct recharge within the area of the groundwater model ranged from 30.4 million gallons per day (Mgal/d) during 2010–12 to 98.7 Mgal/d during 1926–69. Variability in recharge during these periods mainly reflects changes in rainfall and irrigation over time. Between 2010 and 2014, streamflow restoration in previously diverted streams resulted in an estimated increase in recharge from seepage in stream channels of about 12.5 Mgal/d. Average groundwater inflow of about 39.6 Mgal/d from inland, dike-intruded areas to the main area of interest was estimated from an existing island-wide numerical groundwater-flow model, which is at a larger scale and incorporates a greater number of simplifying assumptions.</p><p>The numerical groundwater model developed for this study was calibrated to 1926–2012 transient water levels, vertical salinity profiles, and chloride concentrations of water pumped by production wells in the study area. The model was then used to evaluate one future recharge and six selected withdrawal scenarios, developed in consultation with the Maui Department of Water Supply, in terms of long-term changes in water level and 50-percent ocean-water salinity surface. The groundwater model was also used to simulate the future salinity of water withdrawn by existing and proposed production wells. The simulations were run to steady-state conditions, providing an estimate of the long-term effects of changes in withdrawal and recharge on the groundwater resource. Results of the simulated future withdrawal scenarios indicate that, relative to 2017–18 rates, the scenarios’ long-term effect of increased withdrawals ultimately leads to lower water levels and a higher 50-percent ocean-water salinity surface indicating a thinning of the freshwater lens. Results also indicate that the increased withdrawals produce some groundwater with chloride concentration below 250 milligrams per liter and some groundwater with higher chloride concentration. The amount of drawdown near production wells and the quality of water withdrawn from production wells is dependent on the rate and spatial distribution of the withdrawals.</p><p>The model was also used to evaluate how groundwater availability may be affected for a drier recharge scenario based on a published study of future climate. Model results of the future recharge scenario indicate that the rate of groundwater recharge is a controlling factor for (1) water levels, (2) the 50-percent ocean-water salinity surface, and (3) the quality of water withdrawn from production wells in the Wailuku area. Coupled with reduced groundwater recharge (with all other factors remaining equal), the modeled future withdrawals in the scenario would tend to cause lower water levels, a higher 50-percent ocean-water salinity surface, and increased salinity of water withdrawn from production wells.</p><p>The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the long-term hydrologic effects of additional groundwater withdrawals in central Maui. The model has several limitations, including its non-uniqueness and inability to account for local-scale heterogeneities. Short-term effects of changes in recharge and withdrawals—and optimization of pumping rates to meet increased demand for water with acceptable salinity—are possible conditions for future simulation analyses.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215113","collaboration":"Prepared in cooperation with the County of Maui Department of Water Supply","usgsCitation":"Rotzoll, K., Oki, D.S., Johnson, A.G., and Souza, W.R., 2022, Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2021–5113, 80 p., https://doi.org/10.3133/sir20215113.","productDescription":"Report: ix, 80 p., Data Release","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-119307","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":502120,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113156.htm","linkFileType":{"id":5,"text":"html"}},{"id":401475,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P959B45F","text":"SUTRA model used to evaluate long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","description":"Rotzoll, K., 2022, SUTRA model used to evaluate long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i: U.S. Geological Survey data release, https://doi.org/10.5066/P959B45F."},{"id":401474,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5113/sir20215113.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":401473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5113/covrthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.95916748046875,\n              20.720153096892663\n            ],\n            [\n              -156.0003662109375,\n              20.792066100825636\n            ],\n            [\n              -156.26953125,\n              20.958874775031518\n            ],\n            [\n              -156.47003173828125,\n              20.912700155617568\n            ],\n            [\n              -156.60736083984375,\n              21.056307701901847\n            ],\n            [\n              -156.7254638671875,\n              20.93578924489374\n            ],\n            [\n              -156.65679931640625,\n              20.802336592979056\n            ],\n            [\n              -156.533203125,\n              20.756113874762082\n            ],\n            [\n              -156.4947509765625,\n              20.781794909576234\n            ],\n            [\n              -156.4617919921875,\n              20.750977144077833\n            ],\n            [\n              -156.4398193359375,\n              20.601936194281016\n            ],\n            [\n              -156.3629150390625,\n              20.56593890346526\n            ],\n            [\n              -156.2860107421875,\n              20.571081893508193\n            ],\n            [\n              -156.02783203124997,\n              20.6379249854131\n            ],\n            [\n              -155.9564208984375,\n              20.7098770198879\n            ],\n            [\n              -155.95916748046875,\n              20.720153096892663\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_hi@usgs.gov\" data-mce-href=\"mailto:dc_hi@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/piwsc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/piwsc\">Pacific Islands Water Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov\">U.S. Geological Survey</a><br>Inouye Regional Center<br>1845 Wasp Blvd., B176<br>Honolulu, HI 96818</p>","tableOfContents":"<ul><li>Acknowledgements&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Purpose and Scope&nbsp;&nbsp;</li><li>Setting&nbsp;&nbsp;</li><li>Hydrogeologic Framework and Rock Properties&nbsp;&nbsp;</li><li>Groundwater-Flow System&nbsp;&nbsp;</li><li>Simulation of Groundwater Flow&nbsp;&nbsp;</li><li>Limitations&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>References Cited&nbsp;&nbsp;</li><li>Appendix 1. Estimation of Recharge with a Water Budget&nbsp;</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2022-06-03","noUsgsAuthors":false,"publicationDate":"2022-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Rotzoll, Kolja 0000-0002-5910-888X kolja@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":3325,"corporation":false,"usgs":true,"family":"Rotzoll","given":"Kolja","email":"kolja@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":843965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oki, Delwyn S. 0000-0002-6913-8804 dsoki@usgs.gov","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":1901,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn","email":"dsoki@usgs.gov","middleInitial":"S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Adam G. 0000-0003-2448-5746 ajohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-2448-5746","contributorId":4752,"corporation":false,"usgs":true,"family":"Johnson","given":"Adam","email":"ajohnson@usgs.gov","middleInitial":"G.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Souza, William R.","contributorId":90295,"corporation":false,"usgs":true,"family":"Souza","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":843968,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70236670,"text":"70236670 - 2022 - Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022","interactions":[],"lastModifiedDate":"2022-09-15T16:53:08.222861","indexId":"70236670","displayToPublicDate":"2022-06-01T11:41:56","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":12588,"text":"Lateral Lines","active":true,"publicationSubtype":{"id":30}},"title":"Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022","docAbstract":"<p>The Winchester TU Chapter partnered with US Geological Survey scientists to forecast habitat conditions for brook trout in Virginia. The results can be viewed here: https://chesapeake.usgs.gov/fishforecast/ </p><p>TU members deployed stream temperature gages within several streams across the region: Dry River, Passage Creek, Spout Run, Beaver Creek, Mossy Creek. The USGS then used the temperature data to evaluate current and future conditions for brook trout.&nbsp;</p>","language":"English","publisher":"Trout Unlimited, Winchester Chapter #638","usgsCitation":"Hitt, N.P., 2022, Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022: Lateral Lines, no. June 2022, p. 8-9.","productDescription":"2 p.","startPage":"8","endPage":"9","ipdsId":"IP-141316","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":406771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":406769,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://winchestertu.org/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","otherGeospatial":"Spout Run","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.12721252441406,\n              39.03\n            ],\n            [\n              -78,\n              39.03\n            ],\n            [\n              -78,\n              39.144972625112224\n            ],\n            [\n              -78.12721252441406,\n              39.144972625112224\n            ],\n            [\n              -78.12721252441406,\n              39.03\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","issue":"June 2022","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":238185,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"","middleInitial":"P.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":851822,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70237855,"text":"70237855 - 2022 - The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA","interactions":[],"lastModifiedDate":"2022-10-27T15:51:09.02612","indexId":"70237855","displayToPublicDate":"2022-06-01T10:44:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2979,"text":"PLoS Biology","active":true,"publicationSubtype":{"id":10}},"title":"The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA","docAbstract":"<p><span>Snake fungal disease (SFD; ophidiomycosis), caused by the pathogen&nbsp;</span><i>Ophidiomyces ophiodiicola</i><span>&nbsp;(</span><i>Oo</i><span>), has been documented in wild snakes in North America and Eurasia, and is considered an emerging disease in the eastern United States of America. However, a lack of historical disease data has made it challenging to determine whether&nbsp;</span><i>Oo</i><span>&nbsp;is a recent arrival to the USA or whether SFD emergence is due to other factors. Here, we examined the genomes of 82&nbsp;</span><i>Oo</i><span>&nbsp;strains to determine the pathogen’s history in the eastern USA.&nbsp;</span><i>Oo</i><span>&nbsp;strains from the USA formed a clade (Clade II) distinct from European strains (Clade I), and molecular dating indicated that these clades diverged too recently (approximately 2,000 years ago) for transcontinental dispersal of&nbsp;</span><i>Oo</i><span>&nbsp;to have occurred via natural snake movements across Beringia. A lack of nonrecombinant intermediates between clonal lineages in Clade II indicates that&nbsp;</span><i>Oo</i><span>&nbsp;has actually been introduced multiple times to North America from an unsampled source population, and molecular dating indicates that several of these introductions occurred within the last few hundred years. Molecular dating also indicated that the most common Clade II clonal lineages have expanded recently in the USA, with time of most recent common ancestor mean estimates ranging from 1985 to 2007 CE. The presence of Clade II in captive snakes worldwide demonstrates a potential mechanism of introduction and highlights that additional incursions are likely unless action is taken to reduce the risk of pathogen translocation and spillover into wild snake populations.</span></p>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pbio.3001676","usgsCitation":"Ladner, J.T., Palmer, J.M., Ettinger, C.L., Stajich, J.E., Farrell, T.M., Glorioso, B.M., Lawson, B., Price, S.J., Stengle, A.G., Grear, D.A., and Lorch, J.M., 2022, The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA: PLoS Biology, v. 20, no. 6, e3001676, 24 p., https://doi.org/10.1371/journal.pbio.3001676.","productDescription":"e3001676, 24 p.","ipdsId":"IP-137982","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research 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,{"id":70237644,"text":"70237644 - 2022 - Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","interactions":[],"lastModifiedDate":"2022-10-18T13:57:05.161824","indexId":"70237644","displayToPublicDate":"2022-06-01T08:44:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (<i>Dreissena</i> spp.) environmental DNA","title":"Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","docAbstract":"<p><span>Environmental (e)DNA tools are sensitive and cost-effective for early detection of invasive species. However, the uncertainty associated with the interpretation of positive eDNA detections makes it challenging to determine appropriate natural resource management responses. Multiple sources of error can give rise to positive detections of eDNA in a sample when individuals of that species are not present at the site or a widespread infestation is not imminent. Acting on an erroneous eDNA inference could result in needless costs or reductions in desirable resources. Alternatively, failure to rapidly act on eDNA results that truly indicate invader presence could compound negative impacts and lead to high, long-term costs to manage infestations. We used a structured decision making (SDM) process, which incorporates tradeoffs and uncertainties, to evaluate appropriate response actions following hypothetical eDNA detections of invasive dreissenid mussel (</span><i>Dreissena</i><span>&nbsp;spp.) eDNA in Jordanelle Reservoir, Utah (USA). We worked with decision-makers and stakeholders to identify objectives and discrete management action alternatives to assess consequences and tradeoffs. Alternatives ranged from no action to intensive and expensive control efforts. The best performing alternative was delayed containment described by immediate attempts to confirm the eDNA detections using non-molecular sampling techniques followed by mandatory watercraft exit inspections to prevent dreissenid mussel spread to regional water bodies. Non-molecular sampling increased public support for management by demonstrating a commitment to monitor the invasion state before action, whereas containment decreased likelihood of regional spread to other waters. Delayed containment had the lowest downside risk, and the highest upside gains relative to other alternative actions. Sensitivity analyses showed our results to be robust to parameter and outcome uncertainty.</span></p>","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2022.13.2.06","usgsCitation":"Sepulveda, A., Smith, D.R., O'Donnell, K., Owens, N., White, B., Richter, C.A., Merkes, C.M., Wolf, S., Rau, M., Neilson, M., Daniel, W., Dumoulin, C.E., and Hunter, M., 2022, Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA: Management of Biological Invasions, v. 13, no. 2, p. 344-368, https://doi.org/10.3391/mbi.2022.13.2.06.","productDescription":"25 p.","startPage":"344","endPage":"368","ipdsId":"IP-133646","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences 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