{"pageNumber":"151","pageRowStart":"3750","pageSize":"25","recordCount":68788,"records":[{"id":70231301,"text":"sir20225042 - 2022 - Age and water-quality characteristics of groundwater discharge to the South Loup River, Nebraska, 2019","interactions":[],"lastModifiedDate":"2022-05-09T14:59:38.525295","indexId":"sir20225042","displayToPublicDate":"2022-05-09T09:35:46","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":"2022-5042","displayTitle":"Age and Water-Quality Characteristics of Groundwater Discharge to the South Loup River, Nebraska, 2019","title":"Age and water-quality characteristics of groundwater discharge to the South Loup River, Nebraska, 2019","docAbstract":"<p>Streams in the Loup River Basin are sensitive to groundwater withdrawals because of the close hydrologic connection between groundwater and surface water. The U.S. Geological Survey, in cooperation with the Upper Loup and Lower Loup Natural Resources Districts, and the Nebraska Environmental Trust, studied the age and water-quality characteristics of groundwater near the South Loup River to assess the possible effects of a multiyear drought on streamflow.</p><p>Groundwater sampled in wells screened in Quaternary-age deposits displayed a wide range of mean ages (27 to 2,100 years), fraction modern, and susceptibility index values. Groundwater with higher concentrations of chloride and higher specific conductance was indicative of younger groundwater with a narrower age distribution and is more sensitive to climatic disturbances such as short-term drought conditions, based on the calculated susceptibility index. Groundwater samples from wells and springs in Pliocene-age deposits were categorized into two groups with different geochemical and age characteristics. One sample group of springs and wells, called the Western Pliocene, had higher concentrations of chloride and nitrate with young mean ages (18 to 77 years) and narrow age distributions. Groundwater in the Western Pliocene sample group is susceptible to short-term drought. In contrast, the other sample group from Pliocene-age deposits to the east (called Pliocene) had lower concentrations of nitrate, chloride, and mean groundwater ages ranging from 1,900 to 2,900 years old and is less likely to be affected by short-term drought conditions. Groundwater sampled from three wells screened in the Ogallala Formation was shown to have the oldest mean ages ranging from 8,700 to 23,000 years and the lowest calculated susceptibility index values observed in this study. Strong upward hydraulic gradients measured in wells indicated that groundwater from the Ogallala Formation is likely contributing to streamflow of the South Loup River.</p><p>Continuously measured gage height and specific conductance data indicated groundwater discharge from Quaternary-age deposits was highly responsive to precipitation events. In contrast, groundwater discharge from Pliocene-age deposits (Pliocene sample group) was far less responsive, indicating groundwater discharge from Pliocene-age deposits is likely more resilient to short-term drought conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225042","collaboration":"Prepared in cooperation with the Upper Loup and Lower Loup Natural Resources Districts and the Nebraska Environmental Trust","usgsCitation":"Hobza, C.M., and Solder, J.E., 2022, Age and water-quality characteristics of groundwater discharge to the South Loup River, Nebraska, 2019: U.S. Geological Survey Scientific Investigations Report 2022–5042, 57 p., https://doi.org/10.3133/sir20225042.","productDescription":"Report: ix, 57 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-129114","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":400243,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5042/images"},{"id":400242,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.XML"},{"id":400241,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.pdf","text":"Report","size":"15.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5042"},{"id":400244,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L6B4XE","text":"USGS data release","linkHelpText":"Lumped parameter models of groundwater age, South Loup River, Nebraska"},{"id":400240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5042/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"South Loup River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.8599853515625,\n              41.075210270566636\n            ],\n            [\n              -98.5089111328125,\n              41.075210270566636\n            ],\n            [\n              -98.5089111328125,\n              42.07376224008719\n            ],\n            [\n              -100.8599853515625,\n              42.07376224008719\n            ],\n            [\n              -100.8599853515625,\n              41.075210270566636\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/ne-water\" data-mce-href=\"https://www.usgs.gov/centers/ne-water\">Nebraska Water Science Center</a><br>U.S. Geological Survey<br>5231 South 19th Street<br>Lincoln, NE 68512</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Methods</li><li>Water Quality, Groundwater Age, and Streamflow in the South Loup River Basin</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-05-09","noUsgsAuthors":false,"publicationDate":"2022-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Solder, John E. 0000-0002-0660-3326 jsolder@usgs.gov","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":171916,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"jsolder@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842273,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70230874,"text":"ofr20221023 - 2022 - Compilation and evaluation of data used to identify groundwater sources under the direct influence of surface water in Pennsylvania","interactions":[],"lastModifiedDate":"2026-03-30T13:33:08.570297","indexId":"ofr20221023","displayToPublicDate":"2022-05-09T09:30:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1023","displayTitle":"Compilation and Evaluation of Data Used to Identify Groundwater Sources Under the Direct Influence of Surface Water in Pennsylvania","title":"Compilation and evaluation of data used to identify groundwater sources under the direct influence of surface water in Pennsylvania","docAbstract":"<p>A study was conducted to compile and evaluate data used to identify groundwater sources that are under the direct influence of surface water (GUDI) in Pennsylvania. In the early 1990s, the Pennsylvania Department of Environmental Protection (PADEP) implemented the Surface Water Identification Protocol (SWIP) for the identification of GUDI sources. Since the establishment of the SWIP, PADEP has classified more than 500 individual sources across Pennsylvania as GUDI, but Pennsylvania’s complex geology and physiography provide a challenge for a uniform method of GUDI determination. Components used in this study to compile and evaluate data associated with GUDI determination include: (1) a preliminary review of file information for 43 public water-supply wells, (2) quality control and addition of data to PADEP’s database for public water-supply systems to prepare data for analysis, and (3) exploratory evaluation of existing GUDI sources in the database with respect to hydrogeologic and source-construction characteristics that are currently utilized in the assessment methodology.</p><p>Case files for 43 wells from PADEP’s Northcentral and Southcentral regions were reviewed to: (1) provide a better understanding of how the SWIP was applied in practice, (2) verify and compile missing data, and (3) find additional attributes not previously available that might explain a well’s categorization as GUDI. Review of file information showed that the SWIP outlined in PADEP technical guidance was usually followed, but for some sources, the GUDI determination was more complex and could not be easily summarized.</p><p>Data compiled for study analyses provided by PADEP include source data derived from public water-supply system case files, a source-information database for public water-supply systems, and Microscopic Particulate Analysis (MPA) results and associated water-quality data for public water-supply system groundwater sources. Data from the Pennsylvania Drinking Water Information System <span>(PADWIS)</span>, which is PADEP’s database for public water-supply systems, were also used for this study. The PADWIS database originally included data for 12,147 groundwater sources (11,812 groundwater sources not under the direct influence of surface water (non-GUDI) wells and 335 GUDI wells). A subset (4,018 wells consisting of 3,842 non-GUDI wells and 175 GUDI wells) of the PADWIS database was created for an analysis and includes only community wells evaluated in accordance with the SWIP. MPA results for 631 community and noncommunity wells were compiled, along with associated water-quality data (alkalinity, chloride, <i>Escherichia coli</i>, fecal coliform, nitrate, pH, sodium, specific conductance, sulfate, total coliform, total dissolved solids, total residue, and turbidity) populated from the PADEP Bureau of Laboratories Sample Information System. Data compiled from sources other than PADEP include spatial data, both naturogenic (for example, average precipitation or distance to closest hydrologic feature) and anthropogenic (for example, percentage of developed or agricultural land cover within a specific vicinity of a public water-supply system well) data representing spatially derived variables.</p><p>Comparison among wells in the PADWIS dataset subset using the nonparametric Kruskal-Wallis test showed that GUDI wells had significantly older median construction years, shallower depths, and static water levels closer to the land surface than non-GUDI wells and that carbonate aquifers had the highest percentages of wells designated as GUDI (12 percent; 57 wells). Further comparison of wells in the PADWIS database subset using the Spearman’s rho monotonic correlation test illustrated that public water-supply wells designated as GUDI largely occur in unconfined aquifers and have high average yield and shallow static water levels. Assessment of the MPA database subset using the Kruskal-Wallis test showed wells with MPA total risk-factor scores that exceeded zero had older median construction years and shallower casing depths than wells with MPA total risk-factor scores of zero and that carbonate aquifers had the highest percentages of wells with MPA total risk-factor scores exceeding zero (30 percent; 63 wells). Spearman’s rho correlations showed that wells completed in aquifers with depths to major water-bearing zones closer to the land-surface had higher total risk-factor scores resulting from MPA samples.</p><p>Based on the results of the analyses described in this report, broad conclusions can be drawn regarding site-specific well characteristics as well as anthropogenic and naturogenic factors that could be responsible for a well being designated as GUDI, but the accuracy of these results is dependent on the quality of the data being analyzed. Ultimately, study results serve as an added resource for initial desktop screening of wells to determine if additional site-specific investigation is warranted and underscore the need for field evaluation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221023","collaboration":"Prepared in cooperation with the Pennsylvania Department of Environmental Protection, Bureau of Safe Drinking Water","usgsCitation":"Gross, E.L., Conlon, M.D., Risser, D.W., and Reisch, C.E., 2022, Compilation and evaluation of data used to identify groundwater sources under the direct influence of surface water in Pennsylvania (ver. 2.0, June 2023): U.S. Geological Survey Open-File Report 2022–1023, 41 p., https://doi.org/10.3133/ofr20221023.","productDescription":"Report: viii, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101611","costCenters":[{"id":532,"text":"Pennsylvania Water Science 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 \"}}]}","edition":"Version 1.0: May 2022; Version 2.0: June 2023","contact":"<p><a href=\"mailto:dc_pa@usgs.gov\" data-mce-href=\"mailto:dc_pa@usgs.gov\">Director</a>, <a href=\"https://usgs.gov/centers/pa-water/\" data-mce-href=\"https://usgs.gov/centers/pa-water/\">Pennsylvania Water Science Center</a><br>U.S. Geological Survey<br>215 Limekiln Road<br>New Cumberland, PA 17070</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Review of Case Files for 43 Wells</li><li>Compilation of Data</li><li>Evaluation of Data</li><li>Limitations of the Data</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2022-05-09","revisedDate":"2023-06-15","noUsgsAuthors":false,"publicationDate":"2022-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Gross, Eliza L. 0000-0002-8835-3382 egross@usgs.gov","orcid":"https://orcid.org/0000-0002-8835-3382","contributorId":430,"corporation":false,"usgs":true,"family":"Gross","given":"Eliza","email":"egross@usgs.gov","middleInitial":"L.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conlon, Matthew D. 0000-0001-8266-9610 mconlon@usgs.gov","orcid":"https://orcid.org/0000-0001-8266-9610","contributorId":201291,"corporation":false,"usgs":true,"family":"Conlon","given":"Matthew","email":"mconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Risser, Dennis W. 0000-0001-9597-5406 dwrisser@usgs.gov","orcid":"https://orcid.org/0000-0001-9597-5406","contributorId":898,"corporation":false,"usgs":true,"family":"Risser","given":"Dennis","email":"dwrisser@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reisch, Chad E.","contributorId":290678,"corporation":false,"usgs":false,"family":"Reisch","given":"Chad","email":"","middleInitial":"E.","affiliations":[{"id":17703,"text":"Pennsylvania Department of Environmental Protection","active":true,"usgs":false}],"preferred":true,"id":841535,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70234568,"text":"70234568 - 2022 - Black carbon dominated dust in recent radiative forcing on Rocky Mountain snowpacks","interactions":[],"lastModifiedDate":"2022-08-12T14:03:20.784711","indexId":"70234568","displayToPublicDate":"2022-05-09T08:50:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Black carbon dominated dust in recent radiative forcing on Rocky Mountain snowpacks","docAbstract":"The vast majority of surface water resources in the semi-arid western United States start as winter snowpack. Solar radiation is a primary driver of snowmelt, making snowpack water resources especially sensitive to even small increases in concentrations of light absorbing particles such as mineral dust and combustion-related black carbon (BC). Here we show, using fresh snow measurements and snowpack modeling at 51 widely distributed sites in the Rocky Mountain region, that BC dominated impurity-driven radiative forcing in 2018. BC contributed three times more radiative forcing on average than dust, and up to 17 times more at individual locations. Evaluation of 2015 to 2018 archived samples from most of the same sites yielded similar results. These findings, together with long-term observations of atmospheric concentrations and atmospheric model studies, indicate that BC rather than dust has dominated radiative forcing by light absorbing impurities on snow for decades, indicating that mitigation strategies to reduce radiative forcing on headwater snow-water resources would need to focus on reducing winter and spring BC emissions.","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ac681b","usgsCitation":"Gleason, K., McConnell, J.R., Arienzo, M., Sexstone, G., and Rahimi, S., 2022, Black carbon dominated dust in recent radiative forcing on Rocky Mountain snowpacks: Environmental Research Letters, v. 17, no. 5, 054045, 10 p., https://doi.org/10.1088/1748-9326/ac681b.","productDescription":"054045, 10 p.","ipdsId":"IP-111766","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":447863,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac681b","text":"Publisher Index Page"},{"id":405116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montana, New Mexico, Utah, Wyoming","otherGeospatial":"Rocky Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.04833984375001,\n              49.009050809382046\n            ],\n            [\n              -117.02636718749999,\n              47.18971246448421\n            ],\n            [\n              -116.16943359374999,\n              46.10370875598026\n            ],\n            [\n              -117.00439453125,\n              46.255846818480315\n            ],\n            [\n              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]\n}","volume":"17","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Gleason, Kelly kgleason@usgs.gov","contributorId":195150,"corporation":false,"usgs":true,"family":"Gleason","given":"Kelly","email":"kgleason@usgs.gov","affiliations":[],"preferred":true,"id":848863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McConnell, Joseph R. 0000-0001-9051-5240","orcid":"https://orcid.org/0000-0001-9051-5240","contributorId":288526,"corporation":false,"usgs":false,"family":"McConnell","given":"Joseph","email":"","middleInitial":"R.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":848864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arienzo, Monica","contributorId":191065,"corporation":false,"usgs":false,"family":"Arienzo","given":"Monica","affiliations":[],"preferred":false,"id":848865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sexstone, Graham A. 0000-0001-8913-0546","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":203850,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":848866,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rahimi, Stefan","contributorId":294813,"corporation":false,"usgs":false,"family":"Rahimi","given":"Stefan","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":848900,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70231478,"text":"70231478 - 2022 - Exposure to crop production alters cecal prokaryotic microbiota, inflates virulome and resistome in wild prairie grouse","interactions":[],"lastModifiedDate":"2022-05-11T11:47:46.072712","indexId":"70231478","displayToPublicDate":"2022-05-08T06:44:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Exposure to crop production alters cecal prokaryotic microbiota, inflates virulome and resistome in wild prairie grouse","docAbstract":"<div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Chemically intensive crop production depletes wildlife food resources, hinders animal development, health, survival, and reproduction, and it suppresses wildlife immune systems, facilitating emergence of infectious diseases with excessive mortality rates. Gut microbiota is crucial for wildlife's response to environmental stressors. Its composition and functionality are sensitive to diet changes and environmental pollution associated with modern crop production. In this study we use shotgun metagenomics (median 8,326,092 sequences/sample) to demonstrate that exposure to modern crop production detrimentally affects cecal microbiota of sharp-tailed grouse (<i>Tympanuchus phasianellus</i>: 9 exposed, 18 unexposed and greater prairie chickens (<i>T. cupido</i>; 11, 11). Exposure to crop production had greater effect on microbiota richness (<i>t</i>&nbsp;=&nbsp;6.675,<span>&nbsp;</span><i>P</i>&nbsp;&lt;&nbsp;0.001) and composition (PERMANOVA<span>&nbsp;</span><i>r</i><sup><i>2</i></sup>&nbsp;=&nbsp;0.212,<span>&nbsp;</span><i>P</i>&nbsp;=&nbsp;0.001) than did the host species (<i>t</i>&nbsp;=&nbsp;4.762,<span>&nbsp;</span><i>P</i>&nbsp;&lt;&nbsp;0.001;<span>&nbsp;</span><i>r</i><sup><i>2</i></sup>&nbsp;=&nbsp;0.070,<span>&nbsp;</span><i>P</i>&nbsp;=&nbsp;0.001) or their interaction (<i>t</i>&nbsp;=&nbsp;3.449;<span>&nbsp;</span><i>r</i><sup><i>2</i></sup>&nbsp;=&nbsp;0.072, both<span>&nbsp;</span><i>P</i>&nbsp;=&nbsp;0.001), whereas sex and age had no effect. Although microbiota richness was greater in exposed (<i>T. cupido</i><span>&nbsp;</span>chao1&nbsp;=&nbsp;152.8&nbsp;±&nbsp;20.5;<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>115.3&nbsp;±&nbsp;17.1) than in unexposed (102.9&nbsp;±&nbsp;15.1 and 101.1&nbsp;±&nbsp;17.2, respectively) birds, some beneficial bacteria dropped out of exposed birds' microbiota or declined and were replaced by potential pathogens. Exposed birds also had higher richness and load of virulome (mean&nbsp;±&nbsp;standard deviation;<span>&nbsp;</span><i>T. cupido</i><span>&nbsp;</span>24.8&nbsp;±&nbsp;10.0 and 10.1&nbsp;±&nbsp;5.5, respectively;<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>13.4&nbsp;±&nbsp;6.8/4.9&nbsp;±&nbsp;2.8) and resistome (<i>T. cupido</i><span>&nbsp;</span>46.8&nbsp;±&nbsp;11.7/28.9&nbsp;±&nbsp;10.2,<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>38.3&nbsp;±&nbsp;16.7/18.9&nbsp;±&nbsp;14.2) than unexposed birds (<i>T. cupido</i><span>&nbsp;</span>virulome: 14.2&nbsp;±&nbsp;13.5, 4.5&nbsp;±&nbsp;4.2;<span>&nbsp;</span><i>T. cupido</i><span>&nbsp;</span>resistome: 31.6&nbsp;±&nbsp;20.2 and 13.1&nbsp;±&nbsp;12.0;<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>virulome: 5.2&nbsp;±&nbsp;4.7 and 1.4&nbsp;±&nbsp;1.5;<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>resistome: 13.7&nbsp;±&nbsp;16.1 and 4.0&nbsp;±&nbsp;6.4).</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2022.119418","usgsCitation":"Drovetski, S.V., Schmidt, B.K., Lai, J.E., Gross, M.S., Hladik, M.L., Matterson, K.O., and Karouna-Renier, N., 2022, Exposure to crop production alters cecal prokaryotic microbiota, inflates virulome and resistome in wild prairie grouse: Environmental Pollution, v. 306, 119418, 10 p., https://doi.org/10.1016/j.envpol.2022.119418.","productDescription":"119418, 10 p.","ipdsId":"IP-136055","costCenters":[{"id":154,"text":"California Water Science 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":447871,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2022.119418","text":"Publisher Index Page"},{"id":400496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.82080078125,\n              43.02071359427862\n            ],\n            [\n              -103.71093749999999,\n              41.062786068733026\n            ],\n            [\n              -102.041015625,\n              40.9964840143779\n            ],\n            [\n              -102.041015625,\n              40.01078714046552\n            ],\n            [\n              -98.67919921875,\n              40.01078714046552\n            ],\n            [\n              -98.85498046875,\n              43.03677585761058\n            ],\n            [\n              -103.82080078125,\n              43.02071359427862\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"306","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drovetski, Sergei V. 0000-0002-1832-5597","orcid":"https://orcid.org/0000-0002-1832-5597","contributorId":229520,"corporation":false,"usgs":true,"family":"Drovetski","given":"Sergei","middleInitial":"V.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Brian K. 0000-0003-3796-3110","orcid":"https://orcid.org/0000-0003-3796-3110","contributorId":291624,"corporation":false,"usgs":false,"family":"Schmidt","given":"Brian","email":"","middleInitial":"K.","affiliations":[{"id":48006,"text":"National Museum of Natural History, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":842742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lai, Jonas Ethan 0000-0001-5000-338X","orcid":"https://orcid.org/0000-0001-5000-338X","contributorId":291625,"corporation":false,"usgs":true,"family":"Lai","given":"Jonas","email":"","middleInitial":"Ethan","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":842743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gross, Michael S. 0000-0002-2433-166X","orcid":"https://orcid.org/0000-0002-2433-166X","contributorId":213604,"corporation":false,"usgs":true,"family":"Gross","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":205314,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matterson, Kenan Oguz 0000-0003-2989-3685","orcid":"https://orcid.org/0000-0003-2989-3685","contributorId":291628,"corporation":false,"usgs":true,"family":"Matterson","given":"Kenan","email":"","middleInitial":"Oguz","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":842746,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X 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,{"id":70256666,"text":"70256666 - 2022 - Air, land, and water variables associated with the first appearance and current spatial distribution of toxic Prymnesium parvum blooms in reservoirs of the Southern Great Plains, USA","interactions":[],"lastModifiedDate":"2024-08-30T10:59:23.068021","indexId":"70256666","displayToPublicDate":"2022-05-07T11:36:31","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}},"displayTitle":"Air, land, and water variables associated with the first appearance and current spatial distribution of toxic <i>Prymnesium parvum</i> blooms in reservoirs of the Southern Great Plains, USA","title":"Air, land, and water variables associated with the first appearance and current spatial distribution of toxic Prymnesium parvum blooms in reservoirs of the Southern Great Plains, USA","docAbstract":"<p><span>This study examined the association of air, land, and water variables with the first historical occurrence and current distribution of toxic&nbsp;</span><span><i>Prymnesium parvum</i></span><span>&nbsp;blooms in reservoirs of the Brazos River and Colorado River, Texas (USA). One impacted and one reference reservoir were selected per basin.&nbsp;Land cover&nbsp;and use variables were estimated for the whole watershed (WW) and a 0.5-km zone on either side of streams (near field, NF). Variables were expressed in annual values. Principal component and trend analyses were used to determine (1) differences in environmental conditions before and after the 2001 onset of toxic blooms in impacted reservoirs (study period, 1992–2017), and (2) traits that uniquely discriminate impacted from reference reservoirs (2001–2017). Of thirty-three variables examined, two positively aligned with the reoccurring appearance of blooms in impacted reservoirs (air CO</span><sub>2</sub><span>&nbsp;and herbicide Glyphosate) and another two negatively aligned (insecticides&nbsp;Terbufos&nbsp;and Malathion).&nbsp;Glyphosate&nbsp;use was observed throughout the study period but a turning point for an upward trend occurred near the year of first bloom occurrence. While the relevance of the decreased use of insecticides is uncertain, prior experimental studies reported that increasing concentrations of air CO</span><sub>2</sub><span>&nbsp;and water&nbsp;Glyphosate&nbsp;can enhance&nbsp;</span><i>P. parvum</i><span>&nbsp;growth. Consistent with prior findings, impacted reservoirs were of higher&nbsp;salinity&nbsp;than reference reservoirs. In addition, their watersheds had far lower wetland cover at NF and WW scales. The value of wetlands in reducing&nbsp;harmful algal bloom&nbsp;incidence by reducing nutrient inputs has been previously recognized, but wetlands can also capture pesticides. Therefore, a diminished wetland cover could magnify Glyphosate loads flowing into impacted reservoirs. These observations are consistent with a scenario where rising levels of air CO</span><sub>2</sub><span>&nbsp;and Glyphosate use contributed to the establishment of&nbsp;</span><i>P. parvum</i><span>&nbsp;blooms in reservoirs of relatively high salinity and minimal wetland cover over their watersheds.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.155567","usgsCitation":"Tabora-Sarmientoa, S., Patino, R., Portillo-Quintero, C., and Coldren, C., 2022, Air, land, and water variables associated with the first appearance and current spatial distribution of toxic Prymnesium parvum blooms in reservoirs of the Southern Great Plains, USA: Science of the Total Environment, v. 836, 155567, 11 p., https://doi.org/10.1016/j.scitotenv.2022.155567.","productDescription":"155567, 11 p.","ipdsId":"IP-135673","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433321,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -102.79055428065931,\n              33.96150939341686\n            ],\n            [\n              -102.79055428065931,\n              30.40651030229435\n            ],\n            [\n              -95.3521242635305,\n              30.40651030229435\n            ],\n            [\n              -95.3521242635305,\n              33.96150939341686\n            ],\n            [\n              -102.79055428065931,\n              33.96150939341686\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"836","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tabora-Sarmientoa, Shisbeth","contributorId":341529,"corporation":false,"usgs":false,"family":"Tabora-Sarmientoa","given":"Shisbeth","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patino, Reynaldo 0000-0002-4831-8400 r.patino@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":2311,"corporation":false,"usgs":true,"family":"Patino","given":"Reynaldo","email":"r.patino@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Portillo-Quintero, Carlos","contributorId":341530,"corporation":false,"usgs":false,"family":"Portillo-Quintero","given":"Carlos","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coldren, Cade","contributorId":341531,"corporation":false,"usgs":false,"family":"Coldren","given":"Cade","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908568,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231448,"text":"70231448 - 2022 - Incorporating snowmelt into daily estimates of recharge using a state-space model of infiltration","interactions":[],"lastModifiedDate":"2022-11-16T16:23:43.278815","indexId":"70231448","displayToPublicDate":"2022-05-07T06:50:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating snowmelt into daily estimates of recharge using a state-space model of infiltration","docAbstract":"<p><span>A state-space model (SSM) of infiltration estimates daily groundwater recharge using time-series of groundwater-level altitude and meteorological inputs (liquid precipitation, snowmelt, and evapotranspiration). The model includes diffuse and preferential flow through the unsaturated zone, where preferential flow is a function of liquid precipitation and snowmelt rates and a threshold rate, above which there is direct recharge to the water table. Model parameters are estimated over seasonal periods and the SSM is coupled with the Kalman Filter (KF) to assimilate recent observations (hydraulic head) and meteorological inputs into recharge estimates. The approach can take advantage of real-time hydrologic and meteorological data to deliver real-time recharge estimates. The model is demonstrated on daily observations from two bedrock wells in carbonate aquifers of northwestern New York (USA) between 2013 and 2018. Meteorological inputs for liquid precipitation and snowmelt are compiled from SNODAS (2021). Results for recharge during winter and spring seasons show preferential flow events to the water table from liquid precipitation, snowmelt, or a combination of the two. Recharge estimates summed annually are consistent with previous estimates of recharge reported from groundwater flow and surface-process models. Results from the SSM and KF point to errors in meteorological inputs, such as the snowmelt rate, that are not compatible with hydraulic head observations. Whereas liquid and solid precipitation are measured at discrete stations and extrapolated to 1-km</span><sup>2</sup><span>&nbsp;grid cells, snowmelt is a meteorological modeled outcome that may not represent conditions in the vicinity of monitoring well locations.</span></p>","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwat.13206","usgsCitation":"Shapiro, A.M., Day-Lewis, F., Kappel, W.M., and Williams, J., 2022, Incorporating snowmelt into daily estimates of recharge using a state-space model of infiltration: Groundwater, v. 60, no. 6, p. 721-746, https://doi.org/10.1111/gwat.13206.","productDescription":"26 p.","startPage":"721","endPage":"746","ipdsId":"IP-130903","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447877,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13206","text":"Publisher Index Page"},{"id":435854,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MRGR88","text":"USGS data release","linkHelpText":"Algorithms for model parameter estimation and state estimation applied to a state-space model for one-dimensional vertical infiltration incorporating  snowmelt rate as a system input"},{"id":400497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":842636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":842637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, John 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231264,"text":"dr1156 - 2022 - U.S. Geological Survey national shoreline change— Summary statistics for updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida coasts","interactions":[],"lastModifiedDate":"2026-03-18T19:28:05.893773","indexId":"dr1156","displayToPublicDate":"2022-05-06T11:45:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1156","displayTitle":"U.S. Geological Survey National Shoreline Change— Summary Statistics for Updated Vector Shorelines (1800s–2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts","title":"U.S. Geological Survey national shoreline change— Summary statistics for updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida coasts","docAbstract":"<p>Rates of shoreline change have been updated for the open-ocean sandy coastlines of Georgia and Florida as part of the U.S. Geological Survey’s Coastal Change Hazards programmatic focus. This work was formerly within the National Assessment of Shoreline Change project. Shorelines were compiled from the original report published in 2005, recent update reports, and additional light detection and ranging (lidar) shorelines which were extracted from lidar data collected prior to and following Hurricane Irma, which made landfall in September 2017. These shorelines were used to compute long- and short-term rates that incorporate the proxy-datum bias on a transect-by-transect basis. The proxy-datum bias accounts for the unidirectional onshore bias of proxy-based high water line shorelines relative to datum-based mean high water shorelines. In this study, the coast of Georgia exhibited the highest average rates of erosion and accretion in both the long term (approximately 150 years) and the short term (approximately 30 years). Shoreline positions from the mid-1800s through 2018 were used to update the shoreline change rates for Florida and Georgia using the Digital Shoreline Analysis System (DSAS) software.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1156","usgsCitation":"Kratzmann, M.G., 2022, U.S. Geological Survey national shoreline change— Summary statistics for updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida coasts: U.S. Geological Survey Data Report 1156, 8 p., https://doi.org/10.3133/dr1156.","productDescription":"Report: vi, 8 p.; Data Release","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132897","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400139,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1156/dr1156.XML"},{"id":400294,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/dr1156/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1156"},{"id":400136,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J3CVN4","text":"USGS data release","linkHelpText":"USGS national shoreline change—A GIS compilation of updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida Coasts"},{"id":400134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1156/coverthb.jpg"},{"id":400135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1156/dr1156.pdf","text":"Report","size":"1.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1156"},{"id":400138,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1156/images/"},{"id":501269,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112990.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida, Georgia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.71484375,\n              24.287026865376436\n            ],\n            [\n              -78.486328125,\n              24.287026865376436\n            ],\n            [\n              -78.486328125,\n              32.69486597787505\n            ],\n            [\n              -87.71484375,\n              32.69486597787505\n            ],\n            [\n              -87.71484375,\n              24.287026865376436\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:WHSC_science_director@usgs.gov\" data-mce-href=\"mailto:WHSC_science_director@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/whcmsc\" data-mce-href=\"https://www.usgs.gov/centers/whcmsc\">Woods Hole Coastal and Marine Science Center</a><br>U.S. Geological Survey<br>384 Woods Hole Road<br>Quissett Campus<br>Woods Hole, MA 02543–1598</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Results from Historical Shoreline Change Analysis</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-05-06","noUsgsAuthors":false,"publicationDate":"2022-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Kratzmann, Meredith G. 0000-0002-2513-2144 mkratzmann@usgs.gov","orcid":"https://orcid.org/0000-0002-2513-2144","contributorId":4950,"corporation":false,"usgs":true,"family":"Kratzmann","given":"Meredith","email":"mkratzmann@usgs.gov","middleInitial":"G.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842158,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70255103,"text":"70255103 - 2022 - The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts","interactions":[],"lastModifiedDate":"2024-06-17T15:10:24.743676","indexId":"70255103","displayToPublicDate":"2022-05-06T09:57:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts","docAbstract":"<p><span>Methods are being developed to capitalize on citizen science data for research and monitoring, but these data are rarely used within established decision-making frameworks of wildlife agencies. Citizen science data are often collected at higher resolution and extent than targeted monitoring programs, and may provide complementary information. Here, we demonstrate that carefully filtered semi-structured citizen science observations, when paired with targeted survey data, can produce ecological predictions at higher resolution and extent than targeted surveys alone, and both datasets can represent complementary aspects of species' ecology. We present case studies demonstrating how citizen science data can enhance or supplement decision-making of government and conservation organizations. First, we show how the continuous spatial coverage of citizen science projects, when coupled with targeted surveys, can improve estimates of metrics used by the U.S. Fish and Wildlife Service in regulatory processes to estimate population size, and inform take limits of federally managed species nationwide. Second, we show that the spatial coverage of citizen science accommodates dynamic avian space use patterns during key times of the year, relative to standardized monitoring protocols carried out by the Illinois Natural History Survey. Lastly, we demonstrate that citizen science information can replicate estimates of migratory chronologies for the Illinois Natural History Survey and the U.S. Fish and Wildlife Service for some waterfowl species, and in some contexts can supplement missing data on abundance. These findings illustrate the value of integrating validated information from semi-structured citizen science into the current evidence base used to justify, inform, and evaluate conservation decision-making.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2022.109556","usgsCitation":"Stuber, E.F., Robinson, O., Bjerre, E.R., Otto, M.C., Millsap, B., Zimmerman, G., Brasher, M., Ringelman, K., Fournier, A., Yetter, A., Isola, J., and Ruiz-Gutierrez, V., 2022, The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts: Biological Conservation, v. 270, 109556, 11 p., https://doi.org/10.1016/j.biocon.2022.109556.","productDescription":"109556, 11 p.","ipdsId":"IP-134088","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":488728,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2022.109556","text":"Publisher Index Page"},{"id":430277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Illinois, Iowa, Missouri","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.49828581034168,\n              39.76455400687408\n            ],\n            [\n              -122.49828581034168,\n              38.81660641718298\n            ],\n            [\n              -121.0222303704384,\n              38.81660641718298\n            ],\n            [\n              -121.0222303704384,\n              39.76455400687408\n            ],\n   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0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":903404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Orin","contributorId":338622,"corporation":false,"usgs":false,"family":"Robinson","given":"Orin","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":903405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bjerre, Emily R.","contributorId":338623,"corporation":false,"usgs":false,"family":"Bjerre","given":"Emily","email":"","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Otto, Mark C.","contributorId":338624,"corporation":false,"usgs":false,"family":"Otto","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Millsap, Brian A.","contributorId":338625,"corporation":false,"usgs":false,"family":"Millsap","given":"Brian A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmerman, Guthrie S.","contributorId":338626,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903409,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brasher, Michael G.","contributorId":338627,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael G.","affiliations":[{"id":81180,"text":"Ducks Unlimited, Inc","active":true,"usgs":false}],"preferred":false,"id":903410,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ringelman, Kevin M.","contributorId":338628,"corporation":false,"usgs":false,"family":"Ringelman","given":"Kevin M.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":903411,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fournier, Auriel","contributorId":338631,"corporation":false,"usgs":false,"family":"Fournier","given":"Auriel","email":"","affiliations":[{"id":81181,"text":"University of Illinois at Urbana-Champaign, Havana","active":true,"usgs":false}],"preferred":false,"id":903412,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yetter, Aaron","contributorId":338634,"corporation":false,"usgs":false,"family":"Yetter","given":"Aaron","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":903413,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Isola, Jennifer","contributorId":242027,"corporation":false,"usgs":false,"family":"Isola","given":"Jennifer","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":904306,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ruiz-Gutierrez, Viviana","contributorId":261212,"corporation":false,"usgs":false,"family":"Ruiz-Gutierrez","given":"Viviana","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":904307,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70231315,"text":"70231315 - 2022 - Compression behavior of hydrate-bearing sediments","interactions":[],"lastModifiedDate":"2022-05-06T14:27:50.929128","indexId":"70231315","displayToPublicDate":"2022-05-06T09:22:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Compression behavior of hydrate-bearing sediments","docAbstract":"<p class=\"abstractnoin\">This work experimentally explores porosity, compressibility, and the ratio of horizontal to vertical effective stress (<i>K</i><sub>0</sub>) in hydrate-bearing sandy silts from Green Canyon Block 955 in the deep-water Gulf of Mexico. The samples have an in situ porosity of 0.38 to 0.40 and a hydrate saturation of more than 80%. The hydrate-bearing sediments are stiffer than the equivalent hydrate-free sediments; the<span>&nbsp;</span><i>K</i><sub>0</sub><span>&nbsp;</span>stress ratio is greater for hydrate-bearing sediments relative to the equivalent hydrate-free sediments. The porosity decreases by 0.01 to 0.02 when the hydrate is dissociated at the in situ effective stress. We interpret that the hydrate in the sediment pores is a viscoelastic material that behaves like a fluid over experimental time scales, yet it cannot escape the sediment skeleton. During compression, the hydrate bears a significant fraction of the applied vertical load and transfers this load laterally, resulting in the apparent increased stiffness and a larger apparent<span>&nbsp;</span><i>K</i><sub>0</sub><span>&nbsp;</span>stress ratio. When dissociation occurs, the load carried by the hydrate is transferred to the sediment skeleton, resulting in further compaction and a decrease in the lateral stress. The viewpoint that the hydrate is a trapped viscous phase provides a mechanism for how stiffness and stress ratio (<i>K</i><sub>0</sub>) are greater when hydrate is present in the porous media. This study provides insight into the initial stress state of hydrate-bearing reservoirs and the geomechanical evolution of these reservoirs during production.</p>","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/01132221002","usgsCitation":"Fang, Y., Flemings, P., Germaine, J., Daigle, H., Phillips, S.C., and O’Connell, J., 2022, Compression behavior of hydrate-bearing sediments: AAPG Bulletin, v. 106, no. 5, p. 1101-1126, https://doi.org/10.1306/01132221002.","productDescription":"26 p.","startPage":"1101","endPage":"1126","ipdsId":"IP-125588","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Green Canyon Block 955, Green Knoll, Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.417236328125,\n              26.82407078047018\n            ],\n            [\n              -89.527587890625,\n              26.82407078047018\n            ],\n            [\n              -89.527587890625,\n              28.497660832963472\n            ],\n            [\n              -91.417236328125,\n              28.497660832963472\n            ],\n            [\n              -91.417236328125,\n              26.82407078047018\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"106","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fang, Yi","contributorId":138799,"corporation":false,"usgs":false,"family":"Fang","given":"Yi","email":"","affiliations":[{"id":6727,"text":"Pacific Northwest National Laboratory, Richland, WA","active":true,"usgs":false}],"preferred":false,"id":842295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flemings, Peter","contributorId":198205,"corporation":false,"usgs":false,"family":"Flemings","given":"Peter","affiliations":[{"id":13127,"text":"Jackson School of Geosciences, University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":842296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Germaine, John","contributorId":291403,"corporation":false,"usgs":false,"family":"Germaine","given":"John","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":842298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daigle, Hugh","contributorId":291400,"corporation":false,"usgs":false,"family":"Daigle","given":"Hugh","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":842297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842299,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Connell, Joshua","contributorId":239907,"corporation":false,"usgs":false,"family":"O’Connell","given":"Joshua","email":"","affiliations":[{"id":48038,"text":"Institute for Geophysics and Department of Geological Sciences, Jackson School of Geosciences, University of Texas","active":true,"usgs":false}],"preferred":false,"id":842300,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70231312,"text":"70231312 - 2022 - Permeability of methane hydrate-bearing sandy silts in the deep-water Gulf of Mexico (Green Canyon Block 955)","interactions":[],"lastModifiedDate":"2022-05-06T14:20:14.06089","indexId":"70231312","displayToPublicDate":"2022-05-06T09:17:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Permeability of methane hydrate-bearing sandy silts in the deep-water Gulf of Mexico (Green Canyon Block 955)","docAbstract":"<p class=\"abstractnoin\">Permeability is one of the most crucial properties governing fluid flow in methane hydrate reservoirs. This paper presents a comprehensive permeability analysis of hydrate-bearing sandy silt pressure-cored from Green Canyon Block 955 (GC 955) in the deep-water Gulf of Mexico. We developed an experimental protocol to systematically characterize the transport and petrophysical properties in pressure cores. The in situ effective permeability ranges from 0.1 md (1.0 × 10<sup>−16</sup> m<sup>2</sup>) to 2.4 md (2.4 × 10<sup>−15</sup> m<sup>2</sup>) in these natural sandy silts cores with hydrate occupying 83%–93% of the pore space. When hydrate dissociates from these cores, the measured intrinsic permeability (<i>k<sub>0</sub></i>) is 0.3 md (3.0 × 10<sup>−16</sup> m<sup>2</sup>) to 9.3 md (9.3 × 10<sup>−15</sup> m<sup>2</sup>); these results are affected by fines migration during hydrate dissociation. We analyzed samples reconstituted from these sandy silts and found<span>&nbsp;</span><i>k<sub>0</sub></i><span>&nbsp;</span>to range from ∼12 md (∼1.2 × 10<sup>−14</sup> m<sup>2</sup>) to ∼41 md (∼4.1 × 10<sup>−14</sup> m<sup>2</sup>). The water relative permeabilities (<i>k<sub>rw</sub></i>) of GC 955 pressure cores are large relative to other natural pressure cores from offshore Japan, offshore India, and onshore Alaska. These<span>&nbsp;</span><i>k<sub>rw</sub></i><span>&nbsp;</span>values are also higher than predicted by current conceptual relative permeability models where hydrate fills the pores or coats the grains of the sediments. This fundamental conundrum requires further study. Our work provides essential parameters to reservoir simulation models seeking to predict hydrate formation in geological systems, evaluate the gas production potential, and explore the best way to produce this energy resource in sandy silt reservoirs.</p>","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/08102121001","usgsCitation":"Fang, Y., Flemings, P., Daigle, H., Phillips, S.C., and O’Connell, J., 2022, Permeability of methane hydrate-bearing sandy silts in the deep-water Gulf of Mexico (Green Canyon Block 955): AAPG Bulletin, v. 106, no. 5, p. 1071-1100, https://doi.org/10.1306/08102121001.","productDescription":"30 p.","startPage":"1071","endPage":"1100","ipdsId":"IP-125587","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Green Canyon Block 955, Green Knoll, Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.417236328125,\n              26.82407078047018\n            ],\n            [\n              -89.527587890625,\n              26.82407078047018\n            ],\n            [\n              -89.527587890625,\n              28.497660832963472\n            ],\n            [\n              -91.417236328125,\n              28.497660832963472\n            ],\n            [\n              -91.417236328125,\n              26.82407078047018\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"106","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fang, Yi","contributorId":138799,"corporation":false,"usgs":false,"family":"Fang","given":"Yi","email":"","affiliations":[{"id":6727,"text":"Pacific Northwest National Laboratory, Richland, WA","active":true,"usgs":false}],"preferred":false,"id":842290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flemings, Peter","contributorId":198205,"corporation":false,"usgs":false,"family":"Flemings","given":"Peter","affiliations":[{"id":13127,"text":"Jackson School of Geosciences, University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":842291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daigle, Hugh","contributorId":291400,"corporation":false,"usgs":false,"family":"Daigle","given":"Hugh","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":842292,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842293,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Connell, Joshua","contributorId":239907,"corporation":false,"usgs":false,"family":"O’Connell","given":"Joshua","email":"","affiliations":[{"id":48038,"text":"Institute for Geophysics and Department of Geological Sciences, Jackson School of Geosciences, University of Texas","active":true,"usgs":false}],"preferred":false,"id":842294,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70231324,"text":"70231324 - 2022 - Assessing conservation and management actions with ecosystem services better communicates conservation value to the public","interactions":[],"lastModifiedDate":"2022-05-06T14:14:23.881476","indexId":"70231324","displayToPublicDate":"2022-05-06T09:08:02","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":"Assessing conservation and management actions with ecosystem services better communicates conservation value to the public","docAbstract":"Fish and wildlife populations are under unprecedented threats from changes in land use and climate. With increasing threats comes a need for an expanded constituency that can contribute to the public support and financial capital needed for habitat conservation and management. Using an ecosystem services approach can provide a framework for a more holistic accounting of conservation benefits. Our objective here is to provide a greater understanding of the role that taking an ecosystem services approach can have in expanding the public constituency that supports the use of financial capital required to conserve and manage the nation’s natural capital. To demonstrate a methodology and the usefulness of taking an ecosystem services approach when communicating the value of conserving and managing fish and wildlife habitats, we performed an evaluation of U.S. Fish and Wildlife Service-owned Waterfowl Production Areas, National Wildlife Refuges, and easement lands (both wetland and grassland) in Stutsman County, North Dakota. We quantified amphibian habitat, grassland bird habitat, floral resources for pollinators, and carbon storage services under various scenarios of conservation. While we did not include all possible ecosystem services in our model, our case study shows how this process can provide a more complete picture of the collateral benefits of conservation directed primarily toward waterfowl. Using this ecosystem services approach, we documented marked losses in all services modeled if current conservation lands were developed for the production of agricultural crops. By having access to a more complete picture of benefits provided by conservation lands, decision makers can better communicate their value. By garnering greater public support through a more accurate accounting of societal benefits, conservation and management of dwindling natural capital may someday attain the same level of thought and consideration that is put into the conservation and management of the nation’s financial capital.","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-21-083","usgsCitation":"Mushet, D., Post van der Burg, M., and Anteau, M.J., 2022, Assessing conservation and management actions with ecosystem services better communicates conservation value to the public: Journal of Fish and Wildlife Management, v. 13, no. 1, 13 p., https://doi.org/10.3996/JFWM-21-083.","productDescription":"13 p.","ipdsId":"IP-126556","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":447884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-083","text":"Publisher Index Page"},{"id":400280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Stutsman County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.2669,47.3268],[-98.8466,47.327],[-98.8392,47.327],[-98.8232,47.3272],[-98.8152,47.3271],[-98.4991,47.327],[-98.467,47.3266],[-98.4677,47.2402],[-98.4685,46.9788],[-98.4412,46.9789],[-98.4396,46.6296],[-98.7894,46.6294],[-99.0379,46.6309],[-99.1616,46.6317],[-99.4122,46.6316],[-99.4498,46.6319],[-99.4477,46.8044],[-99.4476,46.9788],[-99.4821,46.9795],[-99.4824,47.0089],[-99.4822,47.0162],[-99.4821,47.0249],[-99.4826,47.0396],[-99.4827,47.1558],[-99.4801,47.3267],[-99.2669,47.3268]]]},\"properties\":{\"name\":\"Stutsman\",\"state\":\"ND\"}}]}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":248468,"corporation":false,"usgs":true,"family":"Mushet","given":"David M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842307,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231309,"text":"70231309 - 2022 - Integrated geochemical approach to determine the source of methane in gas hydrate from Green Canyon Block 955 in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2022-05-06T14:07:26.017969","indexId":"70231309","displayToPublicDate":"2022-05-06T09:01:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Integrated geochemical approach to determine the source of methane in gas hydrate from Green Canyon Block 955 in the Gulf of Mexico","docAbstract":"<p class=\"abstractnoin\">Massive volumes of gas are sequestered within gas hydrate in subsurface marine sediments in the Gulf of Mexico. Methane associated with gas hydrate is a potentially important economic resource and a significant reservoir of carbon within the global carbon cycle. Nevertheless, uncertainties remain about the genetic source (e.g., microbial, thermogenic) and possible migration history of natural gas incorporated into hydrate. Previous studies have primarily used the hydrocarbon molecular (CH<sub>4</sub>/C<sub>2</sub>H<sub>6</sub>+) and isotopic (δ<sup>13</sup>C-CH<sub>4</sub>, δ<sup>2</sup>H-CH<sub>4</sub>) compositions of natural gas to address these uncertainties. However, hydrocarbon tracers are altered by mixing, oxidation, secondary methanogenesis, or fluid migration, which presents challenges when deciphering the mechanisms responsible for methane formation and accumulation. To evaluate the genetic source of natural gases from Green Canyon Block 955 (GC 955), east of the Sigsbee escarpment, we collected and analyzed samples from the first pressurized hydrate-bearing sediment cores collected from a coarse-grained hydrate reservoir in the Gulf of Mexico. Gas samples were analyzed for hydrocarbon gas (C<sub>1</sub>–C<sub>5</sub>), major gas (e.g., N<sub>2</sub>, CO<sub>2</sub>), and noble gas (He-Xe) abundance and isotopic (e.g., δ<sup>13</sup>C-CH<sub>4</sub>, δ<sup>2</sup>H-CH<sub>4</sub>, δ<sup>13</sup>C-CO<sub>2</sub>, δ<sup>15</sup>N-N<sub>2</sub>,<span>&nbsp;</span><sup>3</sup>He/<sup>4</sup>He,<span>&nbsp;</span><sup>4</sup>He/<sup>20</sup>Ne) compositions. We determined that natural gas in hydrates from this location are predominantly of primary microbial origin (conservatively at least 76%) and are formed by the hydrogenotrophic (CO<sub>2</sub><span>&nbsp;</span>reduction) methanogenesis pathway. We also note increased thermogenic proportions (∼6%) in a hydrate-bearing layer below the main hydrate-bearing interval (separated by a 5-m water-bearing layer). Our results suggest that microbial methane may be abundant below the base of gas hydrate stability at GC 955.</p>","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/05272120087","usgsCitation":"Moore, M.T., Phillips, S.C., Cook, A., and Darrah, T.H., 2022, Integrated geochemical approach to determine the source of methane in gas hydrate from Green Canyon Block 955 in the Gulf of Mexico: AAPG Bulletin, v. 106, no. 5, p. 949-980, https://doi.org/10.1306/05272120087.","productDescription":"32 p.","startPage":"949","endPage":"980","ipdsId":"IP-125029","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":400279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Green Canyon Block 955, Green Knoll, Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.417236328125,\n              26.82407078047018\n            ],\n            [\n              -89.527587890625,\n              26.82407078047018\n            ],\n            [\n              -89.527587890625,\n              28.497660832963472\n            ],\n            [\n              -91.417236328125,\n              28.497660832963472\n            ],\n            [\n              -91.417236328125,\n              26.82407078047018\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"106","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Myles T. 0000-0002-4405-8349","orcid":"https://orcid.org/0000-0002-4405-8349","contributorId":291397,"corporation":false,"usgs":true,"family":"Moore","given":"Myles","email":"","middleInitial":"T.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Ann","contributorId":242644,"corporation":false,"usgs":false,"family":"Cook","given":"Ann","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":842288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Darrah, Thomas H.","contributorId":145769,"corporation":false,"usgs":false,"family":"Darrah","given":"Thomas","email":"","middleInitial":"H.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":842289,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231649,"text":"70231649 - 2022 - A forested wetland at a climate-induced tipping-point: 17-year demographic evidence of widespread tree recruitment failure","interactions":[],"lastModifiedDate":"2022-05-18T13:55:43.960202","indexId":"70231649","displayToPublicDate":"2022-05-06T08:46:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"A forested wetland at a climate-induced tipping-point: 17-year demographic evidence of widespread tree recruitment failure","docAbstract":"<p><span>Regeneration and survival of forested wetlands are affected by environmental variables related to the hydrologic regime. Climate change, specifically alterations to precipitation patterns, may have outsized effects on these forests. In Tennessee, USA, precipitation has increased by 15% since 1960. The goal of our research was to assess the evidence for whether this change in precipitation patterns resulted in shorter growing seasons and recruitment failure in common canopy trees for a forest wetland. In 2001 and 2018, the density of&nbsp;</span><i>Quercus lyrata</i><span>&nbsp;(overcup oak),&nbsp;</span><i>Liquidambar styraciflua</i><span>&nbsp;(sweetgum),&nbsp;</span><i>Quercus phellos</i><span>&nbsp;(willow oak), and&nbsp;</span><i>Betula nigra</i><span>&nbsp;(river birch) seedling, sapling and adult density were mapped in an area of 2.3&nbsp;ha within a seasonally flooded karst depression. Overall, the percentage of the growing season experiencing inundation was 26% greater in the deep than in shallow areas between 2001 and 2018. Saplings and small adults of all four species were restricted to shallow areas, and their abundance has declined substantially. Overcup oak and sweetgum individuals that were recruited into the adult life history stage were repelled from the deep zone. Overcup oak and sweetgum adults experienced lower mortality across the 2.3-ha study area (11% and 26%, respectively) relative to willow oak (56%) and river birch (64%) over the 17-year study. Growing-season inundation showed no relation to mortality in adult sweetgum and willow oak, a positive relation to mortality among adult river birch across size classes and among small adult overcup oak, and an inverse relation to mortality among large adult overcup oak. In shallow regions, overcup oak and sweetgum adults had greater basal area increment relative to the intermediate and deep regions of the pond. Results of hydrologic modeling for the study area, based on rainfall and temperature records covering 1855–2019, show ponding durations after 1970 considerably longer than the historical baseline, across ponding-depth classes. Our results strongly suggest that climate change is a driving factor suppressing tree regeneration since 1970 in this seasonally flooded karst depression.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2022.120247","usgsCitation":"Evans, J., McCarthy-Neumann, S., Pritchard, A., Cartwright, J.M., and Wolfe, W., 2022, A forested wetland at a climate-induced tipping-point: 17-year demographic evidence of widespread tree recruitment failure: Forest Ecology and Management, v. 517, 120247, 12 p., https://doi.org/10.1016/j.foreco.2022.120247.","productDescription":"120247, 12 p.","ipdsId":"IP-135244","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":447887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2022.120247","text":"Publisher Index Page"},{"id":400755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Arnold Engineering Development Complex, Sinking Pond","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.09521865844725,\n              35.38932985634939\n            ],\n            [\n              -86.04337692260742,\n              35.38932985634939\n            ],\n            [\n              -86.04337692260742,\n              35.42151066245934\n            ],\n            [\n              -86.09521865844725,\n              35.42151066245934\n            ],\n            [\n              -86.09521865844725,\n              35.38932985634939\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"517","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Jonathan","contributorId":291851,"corporation":false,"usgs":false,"family":"Evans","given":"Jonathan","affiliations":[{"id":62773,"text":"University of the South at Sewanee","active":true,"usgs":false}],"preferred":false,"id":843227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy-Neumann, Sarah","contributorId":291852,"corporation":false,"usgs":false,"family":"McCarthy-Neumann","given":"Sarah","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":843228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pritchard, Angus","contributorId":291853,"corporation":false,"usgs":false,"family":"Pritchard","given":"Angus","email":"","affiliations":[{"id":62773,"text":"University of the South at Sewanee","active":true,"usgs":false}],"preferred":false,"id":843229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolfe, William J. 0000-0002-3292-051X","orcid":"https://orcid.org/0000-0002-3292-051X","contributorId":224729,"corporation":false,"usgs":false,"family":"Wolfe","given":"William J.","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":843231,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70231303,"text":"70231303 - 2022 - Toxicity of wildland fire-fighting chemicals in pulsed exposures to rainbow trout and fathead minnows","interactions":[],"lastModifiedDate":"2022-07-07T16:56:12.985464","indexId":"70231303","displayToPublicDate":"2022-05-06T08:43:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Toxicity of wildland fire-fighting chemicals in pulsed exposures to rainbow trout and fathead minnows","docAbstract":"<p>Intrusions of fire-fighting chemicals in streams can result from containment and suppression of wildfires and may be harmful to native biota. We investigated the toxicity of seven current-use fire-fighting chemicals to juvenile rainbow trout (<i>Oncorhynchus mykiss</i>) and fathead minnows (<i>Pimephales promelas</i>) by simulating chemical intrusions under variable field conditions to provide insight on the potential damage these chemicals may cause in waterways. We manipulated water flow rate, water hardness, and concentration of the chemicals in three separate attenuated exposure assays where chemical concentrations decreased throughout the 96-hour exposure period. Concentration of retardant, temperature, duration of chemical exposure, and the number of exposures were manipulated in four pulsed assays where up to one-hour exposures were followed by an observation period in control water to determine delayed toxicity or recovery. Mortality of rainbow trout was higher across treatments at a warmer temperature and also increased with increasing concentration rate, increasing exposure duration, and with sequential exposures across assays. For fathead minnows, mortality increased with increasing concentration of fire retardant and longer exposure durations. Chemical exposure can exert additional stress during wildfire events that may impact stream fishes. Since the ratio of toxic unionized ammonia to ionized ammonia is greater with increasing temperature and pH, future studies could investigate the effects of water temperature and pH on native fishes under environmentally relevant concentrations of fire-fighting chemicals.</p>","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/etc.5347","usgsCitation":"Puglis, H.J., Iacchetta, M.G., and Mackey, C.M., 2022, Toxicity of wildland fire-fighting chemicals in pulsed exposures to rainbow trout and fathead minnows: Environmental Toxicology and Chemistry, v. 41, no. 7, p. 1711-1720, https://doi.org/10.1002/etc.5347.","productDescription":"10 p.","startPage":"1711","endPage":"1720","ipdsId":"IP-132944","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":447890,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5347","text":"Publisher Index Page"},{"id":435855,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TY8ZRG","text":"USGS data release","linkHelpText":"Biological and chemical data from attenuated and pulsed exposures of fire chemical to fish"},{"id":400277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":842275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iacchetta, Michael G. 0000-0001-9459-1435","orcid":"https://orcid.org/0000-0001-9459-1435","contributorId":291394,"corporation":false,"usgs":true,"family":"Iacchetta","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":842276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mackey, Christina M. 0000-0003-1737-2698","orcid":"https://orcid.org/0000-0003-1737-2698","contributorId":243574,"corporation":false,"usgs":true,"family":"Mackey","given":"Christina","email":"","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":842277,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231342,"text":"70231342 - 2022 - Statewide quantitative microbial risk assessment for waterborne viruses, bacteria, and protozoa in public water supply wells in Minnesota","interactions":[],"lastModifiedDate":"2022-06-01T15:29:50.641732","indexId":"70231342","displayToPublicDate":"2022-05-06T08:22:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Statewide quantitative microbial risk assessment for waterborne viruses, bacteria, and protozoa in public water supply wells in Minnesota","docAbstract":"<p class=\"articleBody_abstractText\">Infection risk from waterborne pathogens can be estimated via quantitative microbial risk assessment (QMRA) and forms an important consideration in the management of public groundwater systems. However, few groundwater QMRAs use site-specific hazard identification and exposure assessment, so prevailing risks in these systems remain poorly defined. We estimated the infection risk for 9 waterborne pathogens based on a 2-year pathogen occurrence study in which 964 water samples were collected from 145 public wells throughout Minnesota, USA. Annual risk across all nine pathogens combined was 3.3 × 10<sup>–1</sup><span>&nbsp;</span>(95% CI: 2.3 × 10<sup>–1</sup><span>&nbsp;</span>to 4.2 × 10<sup>–1</sup>), 3.9 × 10<sup>–2</sup><span>&nbsp;</span>(2.3 × 10<sup>–2</sup><span>&nbsp;</span>to 5.4 × 10<sup>–2</sup>), and 1.2 × 10<sup>–1</sup><span>&nbsp;</span>(2.6 × 10<sup>–2</sup><span>&nbsp;</span>to 2.7 × 10<sup>–1</sup>) infections person<sup>–1</sup><span>&nbsp;</span>year<sup>–1</sup><span>&nbsp;</span>for noncommunity, nondisinfecting community, and disinfecting community wells, respectively. Risk estimates exceeded the U.S. benchmark of 10<sup>–4</sup><span>&nbsp;</span>infections person<sup>–1</sup><span>&nbsp;</span>year<sup>–1</sup><span>&nbsp;</span>in 59% of well-years, indicating that the risk was widespread. While the annual risk for all pathogens combined was relatively high, the average daily doses for individual pathogens were low, indicating that significant risk results from sporadic pathogen exposure.<span>&nbsp;</span><i>Cryptosporidium</i><span>&nbsp;</span>dominated annual risk, so improved identification of wells susceptible to<span>&nbsp;</span><i>Cryptosporidium</i><span>&nbsp;</span>contamination may be important for risk mitigation.</p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.1c06472","usgsCitation":"Burch, T., Stokdyk, J.P., Rice, N., Anderson, A., Walsh, J.F., Spencer, S., Firnstahl, A.D., and Borchardt, M.A., 2022, Statewide quantitative microbial risk assessment for waterborne viruses, bacteria, and protozoa in public water supply wells in Minnesota: Environmental Science & Technology, v. 56, no. 10, p. 6315-6324, https://doi.org/10.1021/acs.est.1c06472.","productDescription":"10 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Nancy","contributorId":291417,"corporation":false,"usgs":false,"family":"Rice","given":"Nancy","email":"","affiliations":[],"preferred":false,"id":842331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Anita C.","contributorId":214336,"corporation":false,"usgs":false,"family":"Anderson","given":"Anita C.","affiliations":[],"preferred":false,"id":842332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, James F.","contributorId":214333,"corporation":false,"usgs":false,"family":"Walsh","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":842333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Sue","contributorId":291418,"corporation":false,"usgs":false,"family":"Spencer","given":"Sue","email":"","affiliations":[],"preferred":false,"id":842334,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Firnstahl, Aaron D. 0000-0003-2686-7596 afirnstahl@usgs.gov","orcid":"https://orcid.org/0000-0003-2686-7596","contributorId":168296,"corporation":false,"usgs":true,"family":"Firnstahl","given":"Aaron","email":"afirnstahl@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842335,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":151033,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":842336,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70232355,"text":"70232355 - 2022 - Laboratory simulation of groundwater along uranium-mining-affected flow paths near the Grand Canyon, Arizona, USA","interactions":[],"lastModifiedDate":"2022-06-29T12:12:57.807473","indexId":"70232355","displayToPublicDate":"2022-05-06T07:09:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2745,"text":"Mine Water and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Laboratory simulation of groundwater along uranium-mining-affected flow paths near the Grand Canyon, Arizona, USA","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Mining of volumetrically small, but relatively enriched (average 0.6% U<sub>3</sub>O<sub>8</sub>) breccia pipe uranium (BPU) deposits near the Grand Canyon, Arizona, USA has the potential to affect groundwater and springs in the area. Such deposits also contain base metal sulfides that can oxidize to generate acid mine drainage and release trace metals. In this study, sequential batch experiments were conducted to simulate the geochemistry of local shallow groundwater that contacts BPU ore and then moves downgradient through sedimentary strata. The experiments simulated shallow groundwater in a carbonate aquifer followed by contact with BPU ore. The experiments subsequently simulated contact with sedimentary rocks and changing oxygen availability. Concentrations of several contaminants of potential concern became substantially elevated in the waters exposed to BPU ore, including As, Co, Ni, U, and Zn, and to a lesser extent, Mo. Of these, Co, Mo, Ni, and U were minimally attenuated by downgradient processes, whereas Zn was partially attenuated. Sb and Tl concentrations were more moderately elevated but also generally minimally attenuated. Although the mixture of elements is particular to these BPU ore deposits, sulfide oxidation in the ore and carbonate buffering of pH by sedimentary rocks generates patterns of water chemistry common in acid mine drainage settings. Ultimately, downgradient concentrations of elements sourced from BPU ore will also be strongly influenced by non-geochemical factors such as the quantities of water contacting BPU materials, heterogeneity of materials along flow paths, and mixing with waters that have not contacted BPU materials.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10230-022-00872-9","usgsCitation":"Bern, C.R., Campbell, K.M., Walton-Day, K., and Van Gosen, B.S., 2022, Laboratory simulation of groundwater along uranium-mining-affected flow paths near the Grand Canyon, Arizona, USA: Mine Water and the Environment, v. 41, p. 370-386, https://doi.org/10.1007/s10230-022-00872-9.","productDescription":"17 p.","startPage":"370","endPage":"386","ipdsId":"IP-125192","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":447894,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10230-022-00872-9","text":"Publisher Index Page"},{"id":402668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.04907226562499,\n              35.69299463209881\n            ],\n            [\n              -111.324462890625,\n              35.69299463209881\n            ],\n            [\n              -111.324462890625,\n              36.98500309285596\n            ],\n            [\n              -114.04907226562499,\n              36.98500309285596\n            ],\n            [\n              -114.04907226562499,\n              35.69299463209881\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"41","noUsgsAuthors":false,"publicationDate":"2022-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Bern, Carleton R. 0000-0002-8980-1781 cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":201152,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":845332,"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":845333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":845334,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231680,"text":"70231680 - 2022 - Major point and nonpoint sources of nutrient pollution to surface water have declined throughout the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2022-05-20T11:55:42.439649","indexId":"70231680","displayToPublicDate":"2022-05-06T06:53:36","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10763,"text":"Environmental Research Communications","active":true,"publicationSubtype":{"id":10}},"title":"Major point and nonpoint sources of nutrient pollution to surface water have declined throughout the Chesapeake Bay watershed","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Understanding drivers of water quality in local watersheds is the first step for implementing targeted restoration practices. Nutrient inventories can inform water quality management decisions by identifying shifts in nitrogen (N) and phosphorus (P) balances over space and time while also keeping track of the likely urban and agricultural point and nonpoint sources of pollution. The Chesapeake Bay Program's Chesapeake Assessment Scenario Tool (CAST) provides N and P balance data for counties throughout the Chesapeake Bay watershed, and these data were leveraged to create a detailed nutrient inventory for all the counties in the watershed from 1985–2019. This study focuses on three primary watershed nutrient balance components—agricultural surplus, atmospheric deposition, and point source loads—which are thought to be the leading anthropogenic drivers of nutrient loading trends across the watershed. All inputs, outputs, and derived metrics (n=53) like agricultural surplus and nutrient use efficiency, were subjected to short- and long-term trend analyses to discern how sources of pollution to surface water have changed over time. Across the watershed from 1985–2019, downward trends in atmospheric deposition were ubiquitous. Though there are varying effects, long-term declines in agricultural surplus were observed, likely because nutrients are being managed more efficiently. Multiple counties' point source loads declined, primarily associated with upgrades at major cities that discharge treated wastewater directly to tidal waters. Despite all of these positive developments, recent increases in agricultural surpluses from 2009–2019 highlight that water quality gains may soon be reversed in many agricultural areas of the basin. Besides tracking progress and jurisdictional influence on pollution sources, the nutrient inventory can be used for retrospective water quality analysis to highlight drivers of past improvement/degradation of water quality trends and for decision makers to develop and track their near- and long-term watershed restoration strategies.</p></div>","language":"English","publisher":"IOP Publishing","doi":"10.1088/2515-7620/ac5db6","usgsCitation":"Sabo, R.D., Sullivan, B.M., Wu, C., Trentacoste, E.M., Zhang, Q., Shenk, G.W., Bhatt, G., and Linker, L.C., 2022, Major point and nonpoint sources of nutrient pollution to surface water have declined throughout the Chesapeake Bay watershed: Environmental Research Communications, v. 4, no. 4, 045012, 11 p., https://doi.org/10.1088/2515-7620/ac5db6.","productDescription":"045012, 11 p.","ipdsId":"IP-139189","costCenters":[{"id":37759,"text":"VA/WV Water Science 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State University","active":true,"usgs":false}],"preferred":false,"id":843393,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Linker, Lewis C. 0000-0002-3456-3659","orcid":"https://orcid.org/0000-0002-3456-3659","contributorId":252964,"corporation":false,"usgs":false,"family":"Linker","given":"Lewis","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":843394,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70256662,"text":"70256662 - 2022 - Movement and habitat use by smallmouth bass Micropterus dolomieu velox in a dynamic Ozark Highlands riverscape","interactions":[],"lastModifiedDate":"2024-08-29T15:54:25.647648","indexId":"70256662","displayToPublicDate":"2022-05-05T10:48:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Movement and habitat use by smallmouth bass <i>Micropterus dolomieu velox</i> in a dynamic Ozark Highlands riverscape","title":"Movement and habitat use by smallmouth bass Micropterus dolomieu velox in a dynamic Ozark Highlands riverscape","docAbstract":"<p><span>Stream fish movement in response to changing resource availability and habitat needs is important for fish growth, survival and reproduction. The authors used radio telemetry to evaluate individual movements, daily movement rates, home ranges and habitat-use characteristics of adult (278–464 mm&nbsp;</span><i>L</i><sub>T</sub><span>) Neosho smallmouth bass&nbsp;</span><i>Micropterus dolomieu velox</i><span>&nbsp;in three Ozark Highlands streams from June 2016 to February 2018. The authors quantified variation in movement and habitat use among seasons and streams and examined relations with select environmental cues (</span><i>i.e.</i><span>, temperature and discharge), fish size and sex. Maximum movement distances were an order of magnitude greater in the larger Elk River (17.0 km) and Buffalo Creek (12.9 km) than in the smaller Sycamore Creek (1.71 km), were similar in both upstream and downstream directions and typically occurred during the spring. Most movement rates were ≤10 m day</span><sup>−1</sup><span>&nbsp;in all streams and seasons, except for Elk River during spring. Ranking of linear mixed-effects models using AIC</span><sub><i>c</i></sub><span>&nbsp;supported that movement rates were much greater in spring and increased with stream size. Spring movement rate increased with discharge and water temperature; only weak relationships were apparent during other seasons. Increased variation in water temperature had a small negative effect on movement rate. Home range size was highly variable among individuals, ranging 45–15,061 m (median: 773 m), and was not related to fish size, sex, season or stream. Although some fish moved between rivers, this study's tagged fish did not use reservoir or associated interface habitat. Water temperatures used by this study's tagged fish followed seasonal patterns but indicated the use of thermal refugia during summer and winter. Deeper-water habitats were used in Buffalo Creek and in winter across all study streams, whereas greater velocities used in the Elk River likely reflect the increased use of run habitats. Use of pool habitats predominated among tagged fish, particularly in smaller streams. The results of this study indicate considerable heterogeneity in movement and habitat use within and among lotic populations of Neosho smallmouth bass. These findings suggest that population-specific management may be appropriate and highlight the importance of natural flow conditions (</span><i>i.e.</i><span>, spring high flows) and connected habitats for this endemic sport fish, particularly in smaller streams.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jfb.15076","usgsCitation":"Miller, A., and Brewer, S.K., 2022, Movement and habitat use by smallmouth bass Micropterus dolomieu velox in a dynamic Ozark Highlands riverscape: Journal of Fish Biology, v. 101, no. 1, p. 100-114, https://doi.org/10.1111/jfb.15076.","productDescription":"15 p.","startPage":"100","endPage":"114","ipdsId":"IP-133584","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447901,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jfb.15076","text":"External Repository"},{"id":433317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Oklahoma","otherGeospatial":"Brush Creek, Elk River, Sycamore Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -95.00337991937396,\n              36.9787447036027\n            ],\n            [\n              -95.00337991937396,\n              36.50639274310335\n            ],\n            [\n              -94.07756711091189,\n              36.50639274310335\n            ],\n            [\n              -94.07756711091189,\n              36.9787447036027\n            ],\n            [\n              -95.00337991937396,\n              36.9787447036027\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"101","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Andrew D.","contributorId":341518,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew D.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":908548,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70232248,"text":"70232248 - 2022 - Supporting the development and use of native plant materials for restoration on the Colorado Plateau (Fiscal Year 2021 Report)","interactions":[],"lastModifiedDate":"2022-06-17T14:21:51.237888","indexId":"70232248","displayToPublicDate":"2022-05-05T09:21:04","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":10936,"text":"Fiscal Year Report","active":true,"publicationSubtype":{"id":1}},"title":"Supporting the development and use of native plant materials for restoration on the Colorado Plateau (Fiscal Year 2021 Report)","docAbstract":"<p>A primary focus of the Colorado Plateau Native Plant Program (CPNPP) is to identify and develop appropriate native plant materials (NPMs) for current and future restoration projects. Multiple efforts have characterized the myriad challenges inherent in providing appropriate seed resources to enable effective, widespread restoration and have identified a broad suite of research activities to provide the information necessary to overcome those challenges (e.g., Plant Conservation Alliance 2015; Breed et al. 2018; Winkler et al. 2018; McCormick et al. 2021). Many of the most complex information needs relate to identifying the appropriate sources of plant species that can successfully establish in dryland environments, like the Colorado Plateau, where low and highly variable precipitation is standard. Providing this information requires synergistic research efforts in which results from earlier investigations inform the design of subsequent investigations. The U.S. Geological Survey (USGS) Southwest Biological Science Center’s (SBSC’s) research activities to support CPNPP in FY21 followed the FY21 Statement of Work to support a research framework that is continually adapting based on the needs of the restoration community and results from previous investigations; the long-term research framework is outlined in the 2019-2023 5-Year Research Strategy (hereafter referred to as the 5-year plan). This research framework provides support for the National Seed Strategy for Rehabilitation and Restoration (Plant Conservation Alliance 2015), Biden-Harris Administration Executive Order 14008 (Tackling the Climate Crisis at Home and Abroad), and Department of Interior Priority #4 (Working to conserve at least 30% each of our lands and waters by the year 2030). </p><p>Research activities in FY21 centered on landscape genomics, implementing and monitoring a common garden experiment near Vernal, UT, conducting experimental treatments using the GRID (Germination for Restoration Information and Decision-making) framework, and initiating new genetics projects to investigate the impact of production techniques on plant materials and restoration treatments on native plant communities. These activities were supported by four biological science technicians. The SARS-CoV-2 pandemic delayed some aspects of the FY21 workplan, especially for outside laboratory services. However, goals were largely met, and the overall progress of research remains on track with respect to the 5-year plan. While Dr. Rob Massatti was the only scientist supported by the SBSC-CPNPP agreement in FY21, other scientists, including Drs. John Bradford, Seth Munson, Mike Duniway, Sasha Reed, and Daniel Winkler, spent a considerable amount of time providing expertise and support for individual projects. Work activities performed in support of each 5-year plan goal are discussed in turn. Products resulting from FY21 research activities are reported in Appendix 1.</p>","language":"English","publisher":"Bureau of Land Management","collaboration":"Bureau of Land Management","usgsCitation":"Massatti, R., Winkler, D.E., Reed, S., Duniway, M.C., Munson, S.M., and Bradford, J., 2022, Supporting the development and use of native plant materials for restoration on the Colorado Plateau (Fiscal Year 2021 Report): Fiscal Year Report, 19 p.","productDescription":"19 p.","ipdsId":"IP-139434","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":402326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":402322,"type":{"id":15,"text":"Index Page"},"url":"https://www.blm.gov/sites/blm.gov/files/docs/2022-06/CPNPP_USGS_FY21_AnnualReport.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.02734374999999,\n              31.87755764334002\n            ],\n            [\n              -104.765625,\n              31.87755764334002\n            ],\n            [\n              -104.765625,\n              40.17887331434696\n            ],\n            [\n              -113.02734374999999,\n              40.17887331434696\n            ],\n            [\n              -113.02734374999999,\n              31.87755764334002\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":844799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844800,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70231182,"text":"tm4D3 - 2022 - U.S. Geological Survey Hydrologic Toolbox — A graphical and mapping interface for analysis of hydrologic data","interactions":[],"lastModifiedDate":"2022-05-05T13:50:19.759656","indexId":"tm4D3","displayToPublicDate":"2022-05-04T13:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-D3","displayTitle":"U.S. Geological Survey Hydrologic Toolbox — A Graphical and Mapping Interface for Analysis of Hydrologic Data","title":"U.S. Geological Survey Hydrologic Toolbox — A graphical and mapping interface for analysis of hydrologic data","docAbstract":"<p>The Hydrologic Toolbox is a Windows-based desktop software program that provides a graphical and mapping interface for analysis of hydrologic time-series data with a set of widely used and standardized computational methods. The software combines the analytical and statistical functionality provided in the U.S. Geological Survey Groundwater and Surface-Water Toolboxes and provides several enhancements to these programs. The main analytical methods are the computation of hydrologic-frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10); the computation of design flows, including biologically based flows; the computation of flow-duration curves and duration hydrographs; eight computer-programming methods for hydrograph separation of a streamflow time series, including the Base-Flow Index (BFI), HYSEP, PART, and SWAT Bflow methods and Eckhardt’s two-parameter digital-filtering method; and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater-recharge values from streamflow data. Several of the statistical methods provided in the Hydrologic Toolbox are used primarily for computation of critical low-flow statistics. The Hydrologic Toolbox also facilitates retrieval of streamflow and groundwater-level time-series data from the U.S. Geological Survey National Water Information System and outputs text reports that describe their analyses.</p><p>The Hydrologic Toolbox was developed by use of the DotSpatial geographic information system (GIS) programming library, which is part of the MapWindow project. DotSpatial is a nonproprietary, open-source program written for the .NET framework that includes a spatial data viewer and GIS capabilities. Advantages of the DotSpatial system include its pure .NET implementation for both the user interface and the GIS mapping engine, and thus the DotSpatial system simplifies software deployment and installation. In addition to combining the functionality of the separate Groundwater and Surface-Water Toolboxes, the Hydrologic Toolbox also organizes the functionality by theme (Groundwater Tools, Surface-Water Tools, and general Time-Series Tools).</p><p>This report provides a description of how to build a Hydrologic Toolbox project and to download and manage hydrologic time-series data. It includes an overview of the analytical and statistical capabilities of the Hydrologic Toolbox and highlights the primary differences between the Hydrologic Toolbox and the Groundwater and Surface-Water Toolboxes. The report supplements information available in an extensive online Help manual and is intended to provide a set of instructions that will allow users to quickly develop skills to use the mapping, data-retrieval, and computational tools of the program.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Book 4, Hydrologic Analysis and Interpretation","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4D3","programNote":"Water Availability and Use Science Program","usgsCitation":"Barlow, P.M., McHugh, A.R., Kiang, J.E., Zhai, T., Hummel, P., Duda, P., and Hinz, S., 2022, U.S. Geological Survey Hydrologic Toolbox — A graphical and mapping interface for analysis of hydrologic data: U.S. Geological Survey Techniques and Methods, book 4, chap. D3, 23 p., https://doi.org/10.3133/tm4D3.","productDescription":"Report: vi, 23 p.; Software release","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-130481","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":400024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/d03/tm4d3.pdf","text":"Report","size":"4.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 4-D3"},{"id":400023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/d03/coverthb.jpg"},{"id":400027,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9DBLL43","text":"USGS software release","linkHelpText":"- U.S. Geological Survey Hydrologic Toolbox software archive"}],"contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Building, Saving, and Reopening a Hydrologic Toolbox Project</li><li>Downloading, Opening, and Managing Data</li><li>Time-Series Tools</li><li>Groundwater (GW) Tools</li><li>Surface-Water (SW) Tools</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-05-04","noUsgsAuthors":false,"publicationDate":"2022-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Barlow, Paul M. 0000-0003-4247-6456 pbarlow@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6456","contributorId":1200,"corporation":false,"usgs":true,"family":"Barlow","given":"Paul","email":"pbarlow@usgs.gov","middleInitial":"M.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":841871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McHugh, Amy R. 0000-0002-7745-9886","orcid":"https://orcid.org/0000-0002-7745-9886","contributorId":205491,"corporation":false,"usgs":true,"family":"McHugh","given":"Amy R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":841873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhai, Tong","contributorId":291242,"corporation":false,"usgs":false,"family":"Zhai","given":"Tong","affiliations":[{"id":36536,"text":"RESPEC","active":true,"usgs":false}],"preferred":false,"id":841874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hummel, Paul","contributorId":291243,"corporation":false,"usgs":false,"family":"Hummel","given":"Paul","affiliations":[{"id":36536,"text":"RESPEC","active":true,"usgs":false}],"preferred":false,"id":841875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duda, Paul","contributorId":291244,"corporation":false,"usgs":false,"family":"Duda","given":"Paul","email":"","affiliations":[{"id":36536,"text":"RESPEC","active":true,"usgs":false}],"preferred":false,"id":841876,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hinz, Scott","contributorId":291245,"corporation":false,"usgs":false,"family":"Hinz","given":"Scott","email":"","affiliations":[{"id":18005,"text":"LimnoTech","active":true,"usgs":false}],"preferred":false,"id":841877,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70231288,"text":"70231288 - 2022 - Implementing landscape connectivity with topographic filtering model: A simulation of suspended sediment delivery in an agricultural watershed","interactions":[],"lastModifiedDate":"2022-05-13T15:24:40.403273","indexId":"70231288","displayToPublicDate":"2022-05-04T08:57:49","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":"Implementing landscape connectivity with topographic filtering model: A simulation of suspended sediment delivery in an agricultural watershed","docAbstract":"<p><span>The widespread availability of high-fidelity topography combined with advances in geospatial analysis offer the opportunity to reimagine approaches to the difficult problem of predicting sediment delivery from watersheds. Here we present a model that uses high-resolution topography to filter sediment sources to quantify sediment delivery to the watershed outlet. It is a reduced-complexity, top-down model that defines transfer functions—topographic filters—between spatially distributed sediment sources and spatially integrated sediment delivery. The goal of the model is to forecast changes in watershed suspended sediment delivery in response to spatially distributed changes in sediment source magnitude or delivery, whether a result of watershed drivers or intentional management actions. Such an application requires the context of a watershed model that accounts for all sediment sources, enforces sediment mass balance throughout the spatial domain, and accommodates sediment storage and delivery over time. The model is developed for a HUC-8 watershed with a flat upland dominated by corn-soybean agriculture and deeply incised valleys near the watershed outlet with large sediment contributions from near-channel sources. Topofilter computes delivery and storage of field-derived sediment according to its spatial and structural connectivity to the stream channel network; subsequently, delivery of both field- and near-channel-derived sediment along with floodplain storage are computed in the stream channel network to the watershed outlet. The model outputs provide a spatially rich representation of sediment delivery and storage on field and along the stream that is consistent with available independent information on sediment accumulations and fluxes. Rather than a single best-calibrated solution, Topofilter uses the Generalized Likelihood Uncertainty Estimate (GLUE) approach to develop many possible solutions with sediment delivery rates expressed as probability distributions across the watershed. The ensemble of simulation outputs provides a useful basis for estimating uncertainty in sediment delivery and the effectiveness of different landscape management allocation across a watershed.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.155701","usgsCitation":"Cho, J., Wilcock, P.R., and Gran, K.B., 2022, Implementing landscape connectivity with topographic filtering model: A simulation of suspended sediment delivery in an agricultural watershed: Science of the Total Environment, v. 836, 155701, 16 p., https://doi.org/10.1016/j.scitotenv.2022.155701.","productDescription":"155701, 16 p.","ipdsId":"IP-127448","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447923,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2022.155701","text":"Publisher Index Page"},{"id":400202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Le Sueur River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.46868896484375,\n              43.61619382369185\n            ],\n            [\n              -93.087158203125,\n              43.61619382369185\n            ],\n            [\n              -93.087158203125,\n              44.27273816279087\n            ],\n            [\n              -94.46868896484375,\n              44.27273816279087\n            ],\n            [\n              -94.46868896484375,\n              43.61619382369185\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"836","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cho, Jong 0000-0001-5514-6056","orcid":"https://orcid.org/0000-0001-5514-6056","contributorId":291384,"corporation":false,"usgs":true,"family":"Cho","given":"Jong","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":842241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilcock, Peter R 0000-0001-5756-9829","orcid":"https://orcid.org/0000-0001-5756-9829","contributorId":291385,"corporation":false,"usgs":false,"family":"Wilcock","given":"Peter","email":"","middleInitial":"R","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":842242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gran, Karen B.","contributorId":288093,"corporation":false,"usgs":false,"family":"Gran","given":"Karen","email":"","middleInitial":"B.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":true,"id":842243,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231257,"text":"70231257 - 2022 - Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics","interactions":[],"lastModifiedDate":"2022-05-04T13:25:52.650064","indexId":"70231257","displayToPublicDate":"2022-05-04T08:09:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics","docAbstract":"<p>Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.</p>","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.abj2479","usgsCitation":"Uhlemann, S., Dafflon, B., Wainwright, H.M., Williams, K.H., Minsley, B.J., Zamudio, K.D., Carr, B., Falco, N., Ulrich, C., and Hubbard, S.S., 2022, Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics: Science Advances, v. 8, no. 12, 15 p., https://doi.org/10.1126/sciadv.abj2479.","productDescription":"15 p.","ipdsId":"IP-134172","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":447933,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1126/sciadv.abj2479","text":"External Repository"},{"id":400125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"East River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.02726364135741,\n              38.86671143315032\n            ],\n            [\n              -106.9134521484375,\n              38.86671143315032\n            ],\n            [\n              -106.9134521484375,\n              38.97595868249733\n            ],\n            [\n              -107.02726364135741,\n              38.97595868249733\n            ],\n            [\n              -107.02726364135741,\n              38.86671143315032\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Uhlemann, Sebastian","contributorId":291360,"corporation":false,"usgs":false,"family":"Uhlemann","given":"Sebastian","email":"","affiliations":[{"id":36254,"text":"LBNL","active":true,"usgs":false}],"preferred":false,"id":842137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dafflon, Baptiste","contributorId":245441,"corporation":false,"usgs":false,"family":"Dafflon","given":"Baptiste","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":842138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wainwright, Haruko Murakami","contributorId":291362,"corporation":false,"usgs":false,"family":"Wainwright","given":"Haruko","email":"","middleInitial":"Murakami","affiliations":[{"id":36254,"text":"LBNL","active":true,"usgs":false}],"preferred":false,"id":842139,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Kenneth Hurst","contributorId":291364,"corporation":false,"usgs":false,"family":"Williams","given":"Kenneth","email":"","middleInitial":"Hurst","affiliations":[{"id":62696,"text":"LBNL, Rocky Mountain Biological Lab","active":true,"usgs":false}],"preferred":false,"id":842140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minsley, Burke J. 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":248573,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"","middleInitial":"J.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":842141,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zamudio, Katrina D. 0000-0003-0278-0154","orcid":"https://orcid.org/0000-0003-0278-0154","contributorId":203252,"corporation":false,"usgs":true,"family":"Zamudio","given":"Katrina","email":"","middleInitial":"D.","affiliations":[],"preferred":true,"id":842142,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carr, Bradley","contributorId":175482,"corporation":false,"usgs":false,"family":"Carr","given":"Bradley","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":842143,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Falco, Nicola","contributorId":245431,"corporation":false,"usgs":false,"family":"Falco","given":"Nicola","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":842144,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ulrich, Craig","contributorId":175248,"corporation":false,"usgs":false,"family":"Ulrich","given":"Craig","email":"","affiliations":[],"preferred":false,"id":842145,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hubbard, Susan S.","contributorId":175249,"corporation":false,"usgs":false,"family":"Hubbard","given":"Susan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":842146,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70231037,"text":"sir20225012 - 2022 - Refining sources of polychlorinated biphenyls in the Back River watershed, Baltimore, Maryland, 2018–2020","interactions":[],"lastModifiedDate":"2026-04-08T17:25:50.545381","indexId":"sir20225012","displayToPublicDate":"2022-05-03T13:30:00","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":"2022-5012","displayTitle":"Refining Sources of Polychlorinated Biphenyls in the Back River Watershed, Baltimore, Maryland, 2018–2020","title":"Refining sources of polychlorinated biphenyls in the Back River watershed, Baltimore, Maryland, 2018–2020","docAbstract":"<p>Older urban landscapes present unique and complex stressors to urban streams and their habitats through the introduction of legacy and emerging toxic contaminants. Contaminant sources are often associated with various developed land uses such as older residential areas, active and former industrial sites, contaminated sites, and effluents from municipal wastewater treatment plant discharges. These landscapes have a history of legacy contaminant use such as polychlorinated biphenyls (PCBs) resulting in impacts to sediment and water in these complex environments. Despite the ban of PCBs in new commercial use in 1979, PCB contamination is still widespread in the environment, with many fish consumption advisories throughout the Chesapeake Bay region based on elevated PCBs. Several watersheds in the Baltimore region have mandated reductions in PCBs per total maximum daily loads in tidal waters of the watersheds in order to promote compliance with water quality standards. Some of these mandated reductions (for example, regulated watershed runoff) specified in the total maximum daily loads are the responsibility of the local jurisdictions as part of their phase 1 National Pollutant Discharge Elimination System municipal separate storm sewer system permit. In cooperation with the Baltimore City Department of Public Works and Maryland Department of the Environment, the U.S. Geological Survey and University of Maryland, Baltimore County conducted a study from 2018 to 2020 to refine the sources of PCBs from the City of Baltimore into Back River and to use the results to improve the conceptual site model of PCBs in the Back River watershed.</p><p>PCB concentrations in the water column of the nontidal streams in Back River watershed are relatively consistent throughout both tributaries, with greater concentrations detected in samples collected from Moores Run but greater loads estimated in samples collected from Herring Run. PCB concentrations measured in the bed sediments and analysis of the flux between sediment porewater (hereafter porewater) and surface water within the tributaries suggest that there are no stationary legacy sources within the stream channels.</p><p>The bulk of PCB mass entering the system from these nontidal tributaries appears to be introduced primarily during storm events. While only one storm event was sampled and concentrations were quantified only in Herring Run, solids captured during the storm were characterized by increases in PCB mass and overall suspended solids concentrations. Although the bioavailability of the PCB-associated sediment is unknown, this mechanism appears to warrant additional attention to better understand how concentrations vary under different storm conditions and temporally. The importance of contaminated stormwater in loading to Herring Run is further supported by the PCB concentrations in storm drain sediments collected near the tributary, which were present in higher concentrations and were characterized by different homolog signatures compared to that in bed sediments.</p><p>The observations in the tributaries differed from PCB concentrations and sediment characteristics downstream from the City of Baltimore boundary, in the upper tidal area of the main stem of Back River, particularly at the passive sampler locations BRT–1 and BRT–3. This depositional environment is characterized by higher organic content in sediments and higher concentrations of PCBs in porewater, which result in the possible flux of contaminants from sediment to the water column. This flux is generally opposite of that observed in the nontidal tributaries and the farthest upstream tidal site (BRT–2) and may be a result of the possible settling of sediment particles introduced via suspended solids in stormwater.</p><p>Despite an observed considerable reduction in overall PCB mass loading to and from the Back River Wastewater Treatment Plant (BRWWTP) (and similar reductions observed in biosolids) compared to the estimates previously reported from 2015, effluent from the BRWWTP continues to be a primary source of PCBs to Back River. The current study confirmed the likeliness of fat, oil, and grease deposits within the miles of sewer pipe as a source of PCBs to the BRWWTP influent. The differences between PCB concentrations in fat, oil, and grease deposits found in pipes (during replacement) compared to that of the BRWWTP suggest that legacy deposits may contain higher PCB concentrations and may act as a source of PCBs to passing sewage, eventually entering the BRWWTP. Variation in freely dissolved concentrations in the sewer system was apparent through the analysis of PCBs in the primary pump stations using passive sampling, with the largest contribution to the influent attributed to a single pump station and associated piping.</p><p>The contribution of PCBs to Herring Run and Moores Run via sanitary sewer overflows compared to the BRWWTP effluent is negligible, similar to reports from another large urban wastewater treatment plant. Therefore, decreased occurrence of sanitary sewer overflows is not expected to largely decrease PCB loads.</p><p>Results of this study suggest that targeted, sediment-capture best management practices in Back River watershed could be an effective way to reduce PCB mass loading assuming that deposited contaminated sediments are effectively isolated. Recent studies of some common urban best management practices such as bioretention have shown removal of PCBs within the stormwater control structures. In addition, appropriately timed street sweeping practices with appropriate collection equipment may be an effective way to reduce contaminants such as PCBs from road runoff sources. Reductions in concentrations and mass loading within the sewer system measured in this study compared to that estimated 5 years prior reflect the possible success of ongoing gray infrastructure management actions. Reductions may be attributable to enhanced nutrient reduction upgrades to the BRWWTP and extensive capital improvements and maintenance to the sewer system.</p><p>This study employed a combined sampling approach and a variety of sampling methods to include low-density polyethylene passive samplers, high-volume water samples, and grab samples of both water and sediment to characterize the PCB inputs to Herring Run, Moores Run, and Back River. Incorporating the passive samplers provided a time-weighted average of the freely dissolved concentration in the surface water, porewater, WWTP influent and effluent, and pump station influent over the deployment period with picogram per liter detection limits. A similar monitoring approach from this study could be implemented within other subwatersheds or municipal separate storm sewer system jurisdictions to assist in refining primary sources of PCBs in order to inform appropriate mitigation approaches.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225012","collaboration":"Prepared in cooperation with Baltimore City Department of Public Works and Maryland Department of the Environment","usgsCitation":"Majcher, E., Ghosh, U., Needham, T., Lombard, N., Foss, E., Bokare, M., Joshee, S., Cheung, L., Damond, J., and Lorah, M., 2022, Refining sources of polychlorinated biphenyls in the Back River watershed, Baltimore, Maryland, 2018–2020: U.S. Geological Survey Scientific Investigations Report 2022–5012, 58 p., https://doi.org/10.3133/sir20225012.","productDescription":"Report: x, 58 p.; Data Release","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123587","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":399906,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WFDIBM","text":"USGS data release","linkHelpText":"Polychlorinated Biphenyl (PCB) Concentrations of Passive Samplers, Solids, Fat, Oil, and Greases (FOG), and Road Sediments; and Dissolved Organic Carbon (DOC), Total Suspended Solids (TSS), and Particulate Organic Carbon (POC) Concentrations in the Back River Watershed, Baltimore City, Maryland, 2018–2020"},{"id":399905,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5012/sir20225012.pdf","text":"Report","size":"79.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5012"},{"id":399904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5012/coverthb.jpg"},{"id":502298,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112977.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Maryland","city":"Baltimore","otherGeospatial":"Back River watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.84112548828125,\n              39.18969082109678\n            ],\n            [\n              -76.32202148437499,\n              39.18969082109678\n            ],\n            [\n              -76.32202148437499,\n              39.51675478434244\n            ],\n            [\n              -76.84112548828125,\n              39.51675478434244\n            ],\n            [\n              -76.84112548828125,\n              39.18969082109678\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_md@usgs.gov\" data-mce-href=\"mailto:dc_md@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/md-de-dc-water\" data-mce-href=\"https://www.usgs.gov/centers/md-de-dc-water\">Maryland-Delaware-D.C. Water Science Center</a><br>U.S. Geological Survey<br>5522 Research Park Drive<br>Catonsville, MD 21228</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods to Assess PCB Sources in Back River Watershed</li><li>Summary of Known PCB Sources to Back River</li><li>Assessment of PCBs Under Low-Flow Conditions</li><li>Assessment of PCBs Under Stormflow Conditions</li><li>Assessment of PCBs in Wastewater</li><li>Conceptual Model of PCBs in Back River and Implications for Management</li><li>Conclusions and Summary</li><li>References Cited</li><li>Appendix 1. 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 \"}}]}","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/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>Watching the Water</li><li>Monitoring Threats to Sagebrush</li><li>Characterizing Urban Areas</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-05-03","noUsgsAuthors":false,"publicationDate":"2022-05-03","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":202815,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":842075,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70231236,"text":"ofr20221038 - 2022 - Monitoring fish abundance and behavior, using multi-beam acoustic imaging sonar, at a Selective Water Withdrawal structure in Lake Billy Chinook, Deschutes River, Oregon, 2020","interactions":[],"lastModifiedDate":"2022-05-04T14:05:27.413531","indexId":"ofr20221038","displayToPublicDate":"2022-05-03T09:07:57","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1038","displayTitle":"Monitoring Fish Abundance and Behavior, Using Multi-Beam Acoustic Imaging Sonar, at a Selective Water Withdrawal Structure in Lake Billy Chinook, Deschutes River, Oregon, 2020","title":"Monitoring fish abundance and behavior, using multi-beam acoustic imaging sonar, at a Selective Water Withdrawal structure in Lake Billy Chinook, Deschutes River, Oregon, 2020","docAbstract":"<p class=\"p1\">Collection of juvenile salmonids at Round Butte Dam is a critical part of the effort to enhance populations of anadromous fish species in the upper Deschutes River because fish that are not collected at the dam may either incur increased mortality during dam passage or remain landlocked and lost to the anadromous fish population. Adaptive resolution imaging sonar systems were used to assess the behavior, abundance, and timing of fish at the entrance to the Selective Water Withdrawal (SWW) intake and fish collection structure located in the forebay of Round Butte Dam during the spring of 2020. The purpose of the SWW is to direct surface currents in the forebay to attract and collect downriver migrating juvenile salmonid smolts (Chinook salmon [<i>Oncorhynchus tshawytscha</i>], sockeye salmon [<i>O. nerka</i>], and steelhead [<i>O. mykiss</i>]) from Lake Billy Chinook and to enable operators of the SWW to withdraw water from surface and benthic elevations in the reservoir to manage downriver water temperatures. The objective of this study was to assess the abundance and behaviors of smolt-size fish (95–300 millimeters) observed near the SWW and to determine if the presence of bull trout (<i>Salvelinus confluentus; </i>&gt;350 millimeters), the predominant predator of juvenile salmonids, influenced the behavior of downriver migrants.</p><p class=\"p1\">Two imaging sonar units were deployed during the spring of 2020 smolt out-migration period. One unit monitored fish movements near the entrances and one unit monitored in one of the collection flumes of the SWW. The imaging sonar technology was informative for assessing abundance and spatial and temporal behaviors of smolt and bull trout-size fish. Smolt and bull trout-size fish were regularly observed near the entrance to and in the collection flume. Increased abundances were observed during the night, with corresponding increased discharge through the SWW, compared to during the day when discharge was reduced. Behavioral differences also were observed at different discharge rates, with smolt-size fish exhibiting more directed movement toward the collector during periods of increased discharge. Additionally, the presence of bull trout-size fish may have affected the behavior of smolt-size fish because a greater percentage of smolt-size fish were observed traveling away from the SWW when bull trout-size fish were present than when bull trout-size fish were absent. Increased counts of bull trout-size fish coincided with the increased abundances of smolt-size fish. Overall, the results indicate that smolt-size fish are more abundant near the entrance and in the flume of the SWW during periods of increased discharge, and bull trout-size fish were present at the SWW and may have affected smolt collection.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221038","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., Hatton, T.W., and Adams, N.S., 2022, Monitoring fish abundance and behavior, using multi-beam acoustic imaging sonar, at a Selective Water Withdrawal structure in Lake Billy Chinook, Deschutes River, Oregon, 2020: U.S. Geological Survey Open-File Report 2022–1038, 31 p., https://doi.org/10.3133/ofr20221038.","productDescription":"viii, 31 p.","onlineOnly":"Y","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":400087,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1038/coverthb.jpg"},{"id":400088,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1038/ofr20221038.pdf","text":"Report","size":"12.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1038"},{"id":400089,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1038/images"},{"id":400090,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1038/ofr20221038.XML"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Billy Chinook, Round Butte Dam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.56990051269533,\n              44.43623132529392\n            ],\n            [\n              -121.07414245605469,\n              44.43623132529392\n            ],\n            [\n              -121.07414245605469,\n              44.73454012555642\n            ],\n            [\n              -121.56990051269533,\n              44.73454012555642\n            ],\n            [\n              -121.56990051269533,\n              44.43623132529392\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wfrc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/wfrc\">Western Fisheries Research Center</a><br>U.S. Geological Survey<br>6505 NE 65th Street<br>Seattle, Washington 98115-5016</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>References Cited</li></ul>","publishedDate":"2022-05-03","noUsgsAuthors":false,"publicationDate":"2022-05-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":7915,"corporation":false,"usgs":true,"family":"Smith","given":"Collin D.","email":"cdsmith@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":842111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatton, Tyson W. 0000-0002-2874-0719","orcid":"https://orcid.org/0000-0002-2874-0719","contributorId":9112,"corporation":false,"usgs":true,"family":"Hatton","given":"Tyson W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":842112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":842113,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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