{"pageNumber":"244","pageRowStart":"6075","pageSize":"25","recordCount":68807,"records":[{"id":70210141,"text":"70210141 - 2020 - Evaluation of uncertainty intervals for daily, statistically derived streamflow estimates at ungaged basins across the continental U.S.","interactions":[],"lastModifiedDate":"2020-05-15T13:59:00.848318","indexId":"70210141","displayToPublicDate":"2020-05-14T08:54:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of uncertainty intervals for daily, statistically derived streamflow estimates at ungaged basins across the continental U.S.","docAbstract":"Streamflow estimation methods that transfer information from an index gage to an ungaged site are commonly used; however, uncertainty in daily streamflow estimates are often not adequately quantified.  In this study, daily streamflow was simulated at 1,331 validation streamgages across the continental United States using four transfer-based streamflow estimation methods.  Empirical 95 percent uncertainty intervals were computed for estimated daily streamflows.  Uncertainty intervals were evaluated for reliability, sharpness, and overall ability to accurately quantify the uncertainty inherent in the estimated daily streamflow.  Uncertainty intervals performed reliably in the Eastern U.S. and Pacific Northwest regions of the country, containing a median of 96 and 99 percent of the observed values respectively.  Uncertainty intervals were less reliable in the Great Plains and arid Southwest regions, where uncertainty intervals contained a median of 83 and 94 percent of the observed streamflows respectively. Uncertainty interval performance was correlated with gage density and hydrologic similarity near the validation site, as well as the aridity and base-flow indices at the site.","language":"English","publisher":"MDPI","doi":"10.3390/w12051390","collaboration":"","usgsCitation":"Levin, S., and Farmer, W.H., 2020, Evaluation of uncertainty intervals for daily, statistically derived streamflow estimates at ungaged basins across the continental U.S.: Water, v. 12, no. 5, 1390, 20 p., https://doi.org/10.3390/w12051390.","productDescription":"1390, 20 p.","ipdsId":"IP-117236","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":456781,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12051390","text":"Publisher Index Page"},{"id":436988,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KCLD9W","text":"USGS data release","linkHelpText":"Performance of 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]\n}","volume":"12","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Levin, Sara B. 0000-0002-2448-3129","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":209947,"corporation":false,"usgs":true,"family":"Levin","given":"Sara B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface 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,{"id":70208647,"text":"ofr20201014 - 2020 - Time-series model, statistical methods, and software documentation for R–QWTREND—An R package for analyzing trends in stream-water quality","interactions":[],"lastModifiedDate":"2023-03-28T15:36:57.475785","indexId":"ofr20201014","displayToPublicDate":"2020-05-13T16:44:02","publicationYear":"2020","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":"2020-1014","displayTitle":"Time-Series Model, Statistical Methods, and Software Documentation for R–QWTREND—An R Package for Analyzing Trends in Stream-Water Quality","title":"Time-series model, statistical methods, and software documentation for R–QWTREND—An R package for analyzing trends in stream-water quality","docAbstract":"<p>As part of a U.S. Geological Survey water-quality study started in 2018, in cooperation with the International Joint Commission, North Dakota Department of Environmental Quality, and Minnesota Pollution Control Agency, a publicly available software package called R–QWTREND was developed for analyzing trends in stream-water quality. The R–QWTREND package is a collection of functions written in R, an open source language and a general environment for statistical computing and graphics. The package uses a parametric time-series model to express logarithmically transformed concentration in terms of flow-related variability, trend, and serially correlated model errors. Flow-related variability captures natural variability in concentration on the basis of concurrent and antecedent streamflow. The trend identifies systematic changes in concentration in terms of potential step trends, piecewise monotonic trends, or user-specified trends. Maximum likelihood estimation is used to estimate model parameters and determine the best-fit trend model. This report describes the time-series model and statistical methodology behind R–QWTREND and provides formal documentation for installing and using the package.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201014","collaboration":"Prepared in cooperation with the International Joint Commission, North Dakota Department of Environmental Quality, and Minnesota Pollution Control Agency","usgsCitation":"Vecchia, A.V., and Nustad, R.A., 2020, Time-series model, statistical methods, and software documentation for R–QWTREND—An R package for analyzing trends in stream-water quality (ver. 1.2, March 2023): U.S. Geological Survey Open-File Report 2020–1014, 51 p., https://doi.org/10.3133/ofr20201014.","productDescription":"Report: viii, 52 p.; Appendix; Dataset","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-109088","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":414697,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1014/versionHist.txt","text":"Version History","size":"2 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":374762,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System","linkHelpText":"USGS water data for the Nation"},{"id":414696,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1014/ofr20201014.pdf","text":"Report","size":"4.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–2014"},{"id":374759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1014/coverthb3.jpg"},{"id":374761,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1014/downloads/","text":"Appendix 1","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2020–2014  Appendix 1","linkHelpText":"R–QWTREND Software Package"}],"edition":"Version 1.0: May 13, 2020; Version 1.1: November 30, 2021; Version 1.2: March 28, 2023","contact":"<p><a data-mce-href=\"mailto:%20dc_nd@usgs.gov\" href=\"mailto:%20dc_nd@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/dakota-water\" href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a> <br>U.S. Geological Survey<br>821 East Interstate Avenue<br>Bismarck, ND 58503<br>1608 Mountain View Road<br>Rapid City, SD 57702</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Time-Series Model</li><li>Statistical Methods</li><li>R–QWTREND Software Documentation</li><li>Summary</li><li>References Cited</li><li>Appendix 1 R–QWTREND Software Package</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-05-13","revisedDate":"2023-03-28","noUsgsAuthors":false,"publicationDate":"2020-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Vecchia, Aldo V. 0000-0002-2661-4401 avecchia@usgs.gov","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":1173,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"avecchia@usgs.gov","middleInitial":"V.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nustad, Rochelle A. 0000-0002-4713-5944 ranustad@usgs.gov","orcid":"https://orcid.org/0000-0002-4713-5944","contributorId":1811,"corporation":false,"usgs":true,"family":"Nustad","given":"Rochelle","email":"ranustad@usgs.gov","middleInitial":"A.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782895,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70210092,"text":"ofr20201040 - 2020 - Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona","interactions":[],"lastModifiedDate":"2020-05-14T11:55:22.364325","indexId":"ofr20201040","displayToPublicDate":"2020-05-13T13:43:13","publicationYear":"2020","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":"2020-1040","displayTitle":"Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona","title":"Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona","docAbstract":"<p>Sustainability of dryland ecosystems depends on the functionality of soil-vegetation feedbacks that affect ecosystem processes, such as nutrient cycling, water capture and retention, soil erosion and deposition, and plant establishment and reproduction. Useful, common indicators can provide information on soil and site stability, hydrologic function, and biotic integrity. Evaluation of rangeland health thus relies on describing the condition and sustainability of these individual, measurable, and observable indicators that are linked to important ecosystem processes. This report focuses on the ~200,000 acres of the Grand Canyon-Parashant National Monument that is administered by the National Park Service (NPS)—one of the largest NPS units where livestock grazing is a permitted land-use activity. Many ecosystems in the monument are characterized by a low degree of resilience to improper grazing because of low and variable precipitation. The monument is marked by a high degree of environmental heterogeneity, including a large elevation gradient, widely differing precipitation patterns, a diversity of geologic substrates, and unique combinations of plant species.</p><p>The objective of this report is to (1) increase our understanding of the underlying landscape, soil, and climate setting factors that affect Grand Canyon-Parashant National Monument dryland ecosystem structure and function (also referred to as land potential) and (2) characterize the condition of monument ecosystems in relation to management concepts, such as rangeland health.</p><p>Data were analyzed by elevation zone using both univariate and multivariate approaches. Survey results document the high level of diversity within the study area, including 15 unique soil taxa and 271 species of plants. We collected three new plant species for Grand Canyon-Parashant National Monument and 17 new species for the NPS portion of the monument. Results also document a strong association between rangeland health indicators and elevation, topographic setting, and soils. Soil factors found to explain important variation across plots include the amount of exposed bedrock, soil rockiness, soil texture (and associated hydrologic properties), and soil depth. We also found that dominant species turnover across elevation may represent species’ differences in adaptation to climates, including <i>Larrea tridentata</i>, <i>Coleogyne ramosissima</i>, and <i>Artemisia </i>spp. <i>Bromus rubens </i>is the most common invasive species of concern recorded in this study, but other common invasive species are <i>Bromus tectorum</i>, <i>Erodium cicutarium</i>, and <i>Schismus arabicus</i>. Correlations between an index of cattle use and indicators of rangeland health suggest that areas with high cattle use have increased bare ground, decreased ground cover, increased frequency of <i>Schismus arabicus</i>, decreased cover of <i>Coleogyne ramosissima </i>and <i>Ephedra </i>spp., and increased cover of <i>Gutierrezia </i>spp. The few strong correlations observed between indicators of vascular plant community cover or abundance and indicators of cattle activity support rangeland assessment and monitoring strategies that do not rely solely on plant-based indicators are needed.</p><p>This work supports management of dryland ecosystems, including Grand Canyon-Parashant National Monument, using concepts of land potential. We conclude the report with recommendations on improving existing land-potential-based classification systems, associated interpretations, and methods for moving forward with a Grand Canyon-Parashant National Monument rangeland monitoring program.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201040","usgsCitation":"Duniway, M.C., and Palmquist, E.C., 2020, Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona: U.S. Geological Survey Open-File Report 2020–1040, 42 p., https://doi.org/10.3133/ofr20201040.","productDescription":"Report: viii, 42 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-106479","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":374803,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJSJHT","linkHelpText":"Rangeland Ecosystem Data, Grand Canyon - Parashant National Monument, AZ, USA"},{"id":374801,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1040/coverthb.jpg"},{"id":374802,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1040/ofr20201040.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon-Parashant National Monument","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.005126953125,\n              35.679609609368576\n            ],\n            [\n              -111.57714843749999,\n              35.679609609368576\n            ],\n            [\n              -111.57714843749999,\n              36.97622678464096\n            ],\n            [\n              -114.005126953125,\n              36.97622678464096\n            ],\n            [\n              -114.005126953125,\n              35.679609609368576\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/sbsc/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/sbsc/connect\">Director</a>,&nbsp;<br><a href=\"https://www.usgs.gov/centers/sbsc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/sbsc\">Southwest Biological Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>2255 N. Gemini Drive<br>Flagstaff, AZ 86001</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Materials and Methods</li><li>Results</li><li>Discussion</li><li>Conclusion</li><li>Appendix</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-05-13","noUsgsAuthors":false,"publicationDate":"2020-05-13","publicationStatus":"PW","contributors":{"authors":[{"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":789072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":789073,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70259109,"text":"70259109 - 2020 - Sources and dynamics of international funding for waterfowl conservation in the Prairie Pothole Region of North America","interactions":[],"lastModifiedDate":"2024-09-27T13:14:57.340674","indexId":"70259109","displayToPublicDate":"2020-05-13T08:10:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Sources and dynamics of international funding for waterfowl conservation in the Prairie Pothole Region of North America","docAbstract":"<p><strong>Context:<span>&nbsp;</span></strong>Funding for habitat-management programs to maintain population viability is critical for conservation of migratory species; however, such financial resources are limited and can vary greatly over time. The Prairie Pothole Region (PPR) of North America is an excellent system for examining spatiotemporal patterns of funding for waterfowl conservation, because this transboundary region is crucial for reproduction and migration of many duck species.</p><p><strong>Aims:<span>&nbsp;</span></strong>We examine large-scale spatiotemporal variation in funding for waterfowl habitat conservation in the PPR during 2007–2016. Specifically, we quantify major sources of funding and how funds were directed towards particular geographies within Canada and the USA. We further examine how sources and magnitude of funding changed over time and in relation to numbers of hunters.</p><p><strong>Methods:<span>&nbsp;</span></strong>We assembled data from multiple sources to quantify funding (in US$, 2016 values) from (1) USA states and non-government organisations (NGOs), (2) Canadian government and NGOs, and (3) major USA-based federal funding sources to the Canadian and US portions of the PPR between 2007 and 2016. We fit linear regressions to examine spatiotemporal variation in funding and in numbers of active waterfowl hunters in the USA.</p><p><strong>Key results:<span>&nbsp;</span></strong>Whereas annual funding for the Canadian portion was comparatively stable throughout the 10 years (range: US$25–41 million), funding for the US portion was dynamic and increased between the first (range: US$36–48 million) and second (range: US$43–117 million) 5-year intervals, despite concurrent declines in the number of active waterfowl hunters in the USA.</p><p><strong>Conclusions:<span>&nbsp;</span></strong>We discovered contrasting trends and dynamics in multiple streams of funding for habitat conservation on each side of the border bisecting the PPR. These findings and approaches warrant closer attention by wildlife professionals. Work is needed to analyse past and future funding for habitat conservation, which can then be used to refine plans for maintaining or recovering populations of migratory species.</p><p><strong>Implications:<span>&nbsp;</span></strong>Although funding for waterfowl habitat conservation in the PPR increased over the past decade, trends were inconsistent among subregions and uncertain for some major funding sources. Better understanding of the complexities in funding will help inform more efficient long-term planning efforts for conservation of waterfowl and other migratory species.</p>","language":"English","publisher":"CSIRO","doi":"10.1071/WR19100","usgsCitation":"Mattsson, B.J., Devries, J., Dubovsky, J.A., Semmens, D., Thogmartin, W.E., Derbridge, J.J., and Lopez-Hoffman, L., 2020, Sources and dynamics of international funding for waterfowl conservation in the Prairie Pothole Region of North America: Wildlife Research, v. 47, no. 4, p. 279-295, https://doi.org/10.1071/WR19100.","productDescription":"17 p.","startPage":"279","endPage":"295","ipdsId":"IP-101539","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467290,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wr19100","text":"Publisher Index Page"},{"id":462329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mattsson, Brady J.","contributorId":197269,"corporation":false,"usgs":false,"family":"Mattsson","given":"Brady","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":914175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devries, Jim","contributorId":344571,"corporation":false,"usgs":false,"family":"Devries","given":"Jim","affiliations":[{"id":7182,"text":"Ducks Unlimited Canada","active":true,"usgs":false}],"preferred":false,"id":914176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dubovsky, James A.","contributorId":201247,"corporation":false,"usgs":false,"family":"Dubovsky","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":914177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semmens, Darius J. 0000-0001-7924-6529","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":64201,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":914178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":914179,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Derbridge, Jonathan J. 0000-0003-3074-3166","orcid":"https://orcid.org/0000-0003-3074-3166","contributorId":290285,"corporation":false,"usgs":false,"family":"Derbridge","given":"Jonathan","email":"","middleInitial":"J.","affiliations":[{"id":62394,"text":"The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":914247,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lopez-Hoffman, Laura","contributorId":231064,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":28236,"text":"Univ of Arizona","active":true,"usgs":false}],"preferred":false,"id":914180,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70218691,"text":"70218691 - 2020 - Forecasting the combined effects of anticipated climate change and agricultural conservation practices on fish recruitment dynamics in Lake Erie","interactions":[],"lastModifiedDate":"2021-03-05T13:45:03.459109","indexId":"70218691","displayToPublicDate":"2020-05-13T07:31:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting the combined effects of anticipated climate change and agricultural conservation practices on fish recruitment dynamics in Lake Erie","docAbstract":"<ol class=\"\"><li>Many aquatic ecosystems are experiencing multiple anthropogenic stressors that threaten their ability to support ecologically and economically important fish species. Two of the most ubiquitous stressors are climate change and non‐point source nutrient pollution.</li><li>Agricultural conservation practices (ACPs, i.e. farming practices that reduce runoff, prevent erosion, and curb excessive nutrient loading) offer a potential means to mitigate the negative effects of non‐point source pollution on fish populations. However, our understanding of how ACP implementation amidst a changing climate will affect fish production in large ecosystems that receive substantial upstream sediment and nutrient inputs remains incomplete.</li><li>Towards this end, we explored how anticipated climate change and the implementation of realistic ACPs might alter the recruitment dynamics of three fish populations (native walleye<span>&nbsp;</span><i>Sander vitreus</i><span>&nbsp;</span>and yellow perch<span>&nbsp;</span><i>Perca flavescens</i><span>&nbsp;</span>and invasive white perch<span>&nbsp;</span><i>Morone americana</i>) in the highly productive, dynamic west basin of Lake Erie. We projected future (2020–2065) recruitment under different combinations of anticipated climate change (<i>n</i>&nbsp;=&nbsp;2 levels) and ACP implementation (<i>n</i>&nbsp;=&nbsp;4 levels) in the western Lake Erie catchment using predictive biological models driven by forecasted winter severity, spring warming rate, and Maumee River total phosphorus loads that were generated from linked climate, catchment‐hydrology, and agricultural‐practice‐simulation models.</li><li>In general, our models projected reduced walleye and yellow perch recruitment whereas invasive white perch recruitment was projected to remain stable or increase relative to the recent past. Our modelling also suggests the potential for trade‐offs, as ACP implementation was projected to reduce yellow perch recruitment with anticipated climate change.</li><li>Overall, our study presents a useful modelling framework to forecast fish recruitment in Lake Erie and elsewhere, as well as offering projections and new avenues of research that could help resource management agencies and policy‐makers develop adaptive and resilient management strategies in the face of anticipated climate and land‐management change.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.13515","usgsCitation":"Dippold, D.A., Aloysis, N., Keitzer, S.C., Yen, H., Arnold, J.G., Daggupati, P., Fraker, M.E., Martin, J.F., Robertson, D., Sowa, S.P., Johnson, M.V., White, M.J., and Ludsin, S.A., 2020, Forecasting the combined effects of anticipated climate change and agricultural conservation practices on fish recruitment dynamics in Lake Erie: Freshwater Biology, v. 65, no. 9, p. 1487-1508, https://doi.org/10.1111/fwb.13515.","productDescription":"22 p.","startPage":"1487","endPage":"1508","ipdsId":"IP-117968","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":456791,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fwb.13515","text":"Publisher Index Page"},{"id":384064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Michigan, Ohio, Indiana","otherGeospatial":"Lake Erie Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.111328125,\n              40.3130432088809\n            ],\n            [\n              -82.30957031249999,\n              41.409775832009565\n            ],\n            [\n              -84.3310546875,\n              42.293564192170095\n            ],\n            [\n              -85.5615234375,\n              41.57436130598913\n            ],\n            [\n              -85.078125,\n              40.04443758460856\n            ],\n            [\n              -84.111328125,\n              40.3130432088809\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"65","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Dippold, David A 0000-0002-4240-8704","orcid":"https://orcid.org/0000-0002-4240-8704","contributorId":254340,"corporation":false,"usgs":false,"family":"Dippold","given":"David","email":"","middleInitial":"A","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":811375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aloysis, Noel 0000-0002-9094-427X","orcid":"https://orcid.org/0000-0002-9094-427X","contributorId":254342,"corporation":false,"usgs":false,"family":"Aloysis","given":"Noel","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":811376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keitzer, S. 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,{"id":70208874,"text":"sim3453 - 2020 - Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018","interactions":[],"lastModifiedDate":"2025-05-14T19:57:23.738641","indexId":"sim3453","displayToPublicDate":"2020-05-12T12:23:31","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3453","displayTitle":"Altitude of the Potentiometric Surface in the Mississippi River Valley Alluvial Aquifer, Spring 2018","title":"Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018","docAbstract":"<p><span>A potentiometric-surface map for spring 2018 was created for the Mississippi River Valley alluvial (MRVA) aquifer using available groundwater-altitude data from 1,126 wells completed in the MRVA aquifer and from the altitude of the top of the water surface in area rivers from 66 streamgages. Personnel from Arkansas Natural Resources Commission, Arkansas Department of Health, Arkansas Geological Survey, Illinois Department of Agriculture, Illinois State Water Survey, Louisiana Department of Natural Resources, Louisiana Department of Transportation and Development, Mississippi Department of Environmental Quality, Missouri Department of Natural Resources, Yazoo Mississippi Delta Joint Water Management District, U.S. Department of Agriculture-Natural Resources Conservation Service, and U.S. Geological Survey (USGS) routinely collect groundwater-level data from wells screened in the MRVA aquifer. The USGS and the U.S. Army Corps of Engineers routinely collect data on river stage and streamflow for the rivers overlying the MRVA aquifer area. The potentiometric-surface map for 2018 was created utilizing existing groundwater and surface-water altitudes to support investigations to characterize the MRVA aquifer as part of the USGS Water Availability and Use Science Program.</span><span></span></p><p><span>Sufficient data were available to map the potentiometric surface of the MRVA aquifer for spring 2018 for about 87 percent of the aquifer area. The potentiometric contours ranged from 10 to 340 feet above North American Vertical Datum of 1988. The regional direction of groundwater flow was generally to the south-southwest, except in areas of groundwater-altitude depressions, where groundwater flowed into the depression, and near rivers, where flow can be from aquifer to the river or from the river into the aquifer. There are large depressions in the potentiometric-surface map in the lower one-half of the Cache region and in most of the Grand Prairie and Delta regions.</span><br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3453","programNote":"Water Availability and Use Science Program","usgsCitation":"McGuire, V.L., Seanor, R.C., Asquith, W.H., Nottmeier, A.M., Smith, D.C., Tollett, R.W., Kress, W.H., and Strauch, K.R., 2020, Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018: U.S. Geological Survey Scientific Investigations Map 3453, 13 p., 5 sheets, https://dx.doi.org/10.3133/sim3453.","productDescription":"Pamphlet: vi, 13 p.; 5 Sheets: 30.00 x 46.00 inches or smaller; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-107434","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":374521,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet2.pdf","text":"Sheet 2—St. Francis and Cache MAP regions","size":"3.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 2"},{"id":374552,"rank":8,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3453/coverthb4.jpg"},{"id":374524,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet5.pdf","text":"Sheet 5—Atchafalaya and Deltaic and Chenier Plain MAP regions","size":"6.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 5"},{"id":374523,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet4.pdf","text":"Sheet 4—Delta MAP region","size":"1.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 4"},{"id":374522,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet3.pdf","text":"Sheet 3—Boeuf and Grand Prairie MAP regions","size":"2.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 3"},{"id":374520,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet1.pdf","text":"Sheet 1—All Mississippi Alluvial Plain (MAP) regions","size":"14.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 1"},{"id":374519,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_pamphlet.pdf","text":"Pamphlet","size":"5.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM Pamphlet 3453"},{"id":374525,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P992HD1R","text":"USGS data release","linkHelpText":"Datasets used to map the potentiometric surface, Mississippi River Valley alluvial aquifer, spring 2018"}],"country":"United States","otherGeospatial":"Mississippi River Valley alluvial aquifer","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.4287109375,\n              37.09023980307208\n            ],\n            [\n              -90.087890625,\n              36.31512514748051\n            ],\n            [\n              -91.318359375,\n              34.92197103616377\n            ],\n            [\n              -91.8896484375,\n              33.50475906922609\n            ],\n            [\n              -92.3291015625,\n              30.826780904779774\n            ],\n            [\n              -91.0986328125,\n              29.76437737516313\n            ],\n            [\n              -89.56054687499999,\n              28.92163128242129\n            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,{"id":70209977,"text":"ofr20201036 - 2020 - Water-table elevation maps for 2008 and 2016 and water-table elevation changes in the aquifer system underlying eastern Albuquerque, New Mexico","interactions":[],"lastModifiedDate":"2020-05-13T11:50:00.644538","indexId":"ofr20201036","displayToPublicDate":"2020-05-12T11:13:22","publicationYear":"2020","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":"2020-1036","displayTitle":"Water-Table Elevation Maps for 2008 and 2016 and Water-Table Elevation Changes in the Aquifer System Underlying Eastern Albuquerque, New Mexico","title":"Water-table elevation maps for 2008 and 2016 and water-table elevation changes in the aquifer system underlying eastern Albuquerque, New Mexico","docAbstract":"<p>The addition of surface water from the San Juan-Chama Drinking Water Project to the Albuquerque water supply and the reduction in per capita water use has led to decreased groundwater withdrawals. This decrease in withdrawals has resulted in rising groundwater levels since 2008 in portions of the aquifer underlying Albuquerque. The wells used to assess the Kirtland Air Force Base Bulk Fuels Facility (KAFB BFF) ethylene dibromide (EDB) groundwater contamination were installed with well screens that crossed the water table in order to monitor and sample groundwater within the EDB plume. While replacement wells have been installed, an understanding of the water-table response to decreases in regional groundwater withdrawals is required to evaluate the monitoring well network. Water-table elevation maps of the aquifer underlying the Albuquerque metropolitan area east of the Rio Grande for 2008 and 2016 and a map of the change in elevations in this 8-year period provide an improved understanding of the water-table elevations and the changes that are occurring.</p><p>The water-table elevation contours for both 2008 and 2016 show that groundwater generally flows from the Rio Grande and from the mountain-front recharge in the southeast toward the center of the study area, a major groundwater pumping center. The water-table elevation increased in most of the study area from 2008 to 2016. The area of greatest increase in the water-table elevation covers most of the northeastern part of the study area, where there has historically been pumping-related drawdown and subsequent groundwater-level rises in the production zone of the Santa Fe Group aquifer system.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201036","collaboration":"Prepared in cooperation with Air Force Civil Engineer Center","usgsCitation":"Flickinger, A.K., and Mitchell, A.C., 2020, Water-table elevation maps for 2008 and 2016 and water-table elevation changes in the aquifer system underlying eastern Albuquerque, New Mexico: U.S. Geological Survey Open-File Report 2020–1036, 9 p., https://doi.org/10.3133/ofr20201036.","productDescription":"Report: vi, 9 p.; Data Release; Interactive Map","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-111755 ","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":374556,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://usgs.maps.arcgis.com/home/item.html?id=3b038837dfe347daa8691931182788f5","text":"Interactive map of the study area"},{"id":374553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1036/coverthb.jpg"},{"id":374554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1036/ofr20201036.pdf","text":"Report","size":"2.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1036"},{"id":374555,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OHR8Z2","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-tables elevations and other well construction data for 2008 and 2016 in eastern Albuquerque, New Mexico"}],"country":"United States","state":"New Mexico","city":"Albuquerque","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.6607666015625,\n              34.836349990763864\n            ],\n            [\n              -105.9521484375,\n              34.836349990763864\n            ],\n            [\n              -105.9521484375,\n              35.27701633139884\n            ],\n            [\n              -106.6607666015625,\n              35.27701633139884\n            ],\n            [\n              -106.6607666015625,\n              34.836349990763864\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/nm-water\" href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd. NE<br>Albuquerque, NM 87113<br></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Santa Fe Group Aquifer System</li><li>Study Methods</li><li>Estimated 2008 and 2016 Water-Table Elevation Contours and Change</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-05-12","noUsgsAuthors":false,"publicationDate":"2020-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Flickinger, Allison K. 0000-0002-8638-2569 aflickinger@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-2569","contributorId":193268,"corporation":false,"usgs":true,"family":"Flickinger","given":"Allison","email":"aflickinger@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":788702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Aurelia C. 0000-0003-3302-4546","orcid":"https://orcid.org/0000-0003-3302-4546","contributorId":222580,"corporation":false,"usgs":true,"family":"Mitchell","given":"Aurelia C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788703,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70214028,"text":"70214028 - 2020 - Using multiple environmental proxies and hydrodynamic modeling to investigate Late Holocene climate and coastal change within a large Gulf of Mexico estuarine system (Mobile Bay, Alabama, USA)","interactions":[],"lastModifiedDate":"2025-05-13T16:09:23.411011","indexId":"70214028","displayToPublicDate":"2020-05-12T10:39:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Using multiple environmental proxies and hydrodynamic modeling to investigate Late Holocene climate and coastal change within a large Gulf of Mexico estuarine system (Mobile Bay, Alabama, USA)","docAbstract":"<p><span>A high degree of uncertainty exists for understanding and predicting coastal estuarine response to changing climate, land-use, and sea-level conditions, leaving geologic records as a best-proxy for constraining potential outcomes. With the majority of the world's population focused in coastal regions, understanding how local systems respond to global, regional, and even local pressures is key in developing mitigation, adaptation, and management plans. The geomorphology of Mobile Bay in southeast Alabama (USA) has evolved considerably (e.g., bayhead delta back-stepping) over the late Holocene in response to global and regional sea-level and climate change. Smaller-scale geomorphic changes (e.g., spit and beach ridge development) have also had a significant influence on the evolution of the estuary. Organic matter characteristics, inorganic sediment geochemistry, benthic microfossils, and pollen in a&nbsp;~&nbsp;3500&nbsp;cal&nbsp;yr BP sediment sequence recovered in a gravity core (20GC) from Bon Secour Bay, a small sub-bay in the southeast corner of Mobile Bay, record time-varying marine influence. Increases in marine influence during ~3500 to 2300&nbsp;cal&nbsp;yr BP and 1930 to 1160&nbsp;cal&nbsp;yr BP are defined as zones with high-density and pre-dominantly calcareous foraminiferal species, abundant sand (&gt;10%) and more marine-like geochemical signatures, which contrast the low-density and pre-dominantly agglutinated foraminiferal and more terrestrially influenced estuarine muds observed in other intervals of the sedimentary record (2300–1930 and 1160–400&nbsp;cal&nbsp;yr BP) and the modern bay. Hydrodynamic models constrained by geomorphic boundary conditions for the time&nbsp;~&nbsp;3500&nbsp;cal&nbsp;yr BP, consistent with the most prominent marine-influenced sediment, provide insight to potential coastal configuration that might have permitted such marine water intrusion into the bay. Of several scenarios evaluated, a breach in Morgan Peninsula produces tidal circulation within the basin supportive of persistent marine incursions in the bay between ~3500 to 2300&nbsp;cal&nbsp;yr BP. The findings show that slight variations in coastal configuration can have broad-scale effects on bays and estuaries with consequences that may relate to water quality, vertebrate and invertebrate habitat, and coastal vulnerability to episodic events like (extra)tropical storms.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2020.106218","usgsCitation":"Smith, C., Jones, M.C., Osterman, L., and Passeri, D., 2020, Using multiple environmental proxies and hydrodynamic modeling to investigate Late Holocene climate and coastal change within a large Gulf of Mexico estuarine system (Mobile Bay, Alabama, USA): Marine Geology, v. 427, 106218, 12 p., https://doi.org/10.1016/j.margeo.2020.106218.","productDescription":"106218, 12 p.","ipdsId":"IP-112885","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":456795,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2020.106218","text":"Publisher Index Page"},{"id":378618,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":436990,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WGJO0S","text":"USGS data release","linkHelpText":"Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results"}],"country":"United States","state":"Alabama, Mississippi","otherGeospatial":"Mobile Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.14306640625,\n              30.107117887092357\n            ],\n            [\n              -87.60498046875,\n              30.107117887092357\n            ],\n            [\n              -87.60498046875,\n              30.95876857077987\n            ],\n            [\n              -89.14306640625,\n              30.95876857077987\n            ],\n            [\n              -89.14306640625,\n              30.107117887092357\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"427","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":799272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Miriam C. 0000-0002-6650-7619 miriamjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":4056,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"miriamjones@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":799273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osterman, Lisa 0000-0002-8603-5217 osterman@usgs.gov","orcid":"https://orcid.org/0000-0002-8603-5217","contributorId":218441,"corporation":false,"usgs":true,"family":"Osterman","given":"Lisa","email":"osterman@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":799275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":799274,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70210041,"text":"70210041 - 2020 - Inventory and analysis of groundwater resources: Theodore Roosevelt National Park, North Dakota","interactions":[],"lastModifiedDate":"2020-05-12T12:54:58.884549","indexId":"70210041","displayToPublicDate":"2020-05-12T07:51:44","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Inventory and analysis of groundwater resources: Theodore Roosevelt National Park, North Dakota","docAbstract":"Industrial and commercial developments in western North Dakota potentially could affect the sources of water that contribute to wells, spring flow, and seeps within Theodore Roosevelt National Park. Without basic water resources data, accurately predicting the effects of water withdrawals and water quality concerns related to industrial and commercial developments near the park would be challenging. Water resources in the park include surface water and groundwater. The Little Missouri River and its tributaries cross all three Theodore Roosevelt National Park units and are the primary surface-water features in the park. Groundwater resources include well discharges, springs, and seeps. The geology and hydrogeology of Theodore Roosevelt National Park are defined by the surrounding Williston Basin. Four aquifers are sources of groundwater to the park: unconsolidated aquifers including alluvial systems, the upper Fort Union aquifer, the lower Fort Union aquifer, and the Fox Hills-lower Hell Creek aquifer. \n\nData used for wells, springs, seeps, and water quality in this report were compiled from the U.S.\nGeological Survey National Water Information System or from the North Dakota State Water\nCommission. An inventory of 16 wells was completed for sites within the boundaries of the park. In addition to well data, an inventory of 11 springs and seeps was completed. The groundwater-quality analysis had two objectives: (1) to characterize the groundwater chemistry in aquifers underlying the park and (2) to spatially map selected physical properties and chemical constituents of interest. Groundwater-quality data from the North Dakota State Water Commission were summarized, mapped, and used to characterize groundwater for each aquifer in the study area. Spatial concentration distribution maps were constructed for selected physical properties and chemical constituents using summary statistics and exceedances. Piper diagrams were used to classify and characterize groundwater for each aquifer. \n\nFuture research to help fill data gaps in water resources information for Theodore Roosevelt National Park, including recommendations from previous studies, consists of the following: (1) evaluating the variability in discharge from springs and seeps in comparison to changes in precipitation or other recharge sources, (2) evaluating flow control measures for flowing artesian wells, (3) completing a water rights review, and (4) performing routine water-quality monitoring for wells and springs.","language":"English","publisher":"National Park Service","collaboration":"National Park Service Water Rights Division","usgsCitation":"Eldridge, W.G., and Medler, C.J., 2020, Inventory and analysis of groundwater resources: Theodore Roosevelt National Park, North Dakota, xviii, 125 p.","productDescription":"xviii, 125 p.","ipdsId":"IP-114231","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":374650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":374643,"type":{"id":11,"text":"Document"},"url":"https://irma.nps.gov/DataStore/DownloadFile/639871"}],"country":"United States","state":"North Dakota","otherGeospatial":"Theodore Roosevelt National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.77685546875,\n              46.832012719114765\n            ],\n            [\n              -103.13415527343749,\n              46.832012719114765\n            ],\n            [\n              -103.13415527343749,\n              47.65058757118734\n            ],\n            [\n              -103.77685546875,\n              47.65058757118734\n            ],\n            [\n              -103.77685546875,\n              46.832012719114765\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eldridge, William G. 0000-0002-3562-728X","orcid":"https://orcid.org/0000-0002-3562-728X","contributorId":208529,"corporation":false,"usgs":true,"family":"Eldridge","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medler, Colton J. 0000-0001-6119-5065","orcid":"https://orcid.org/0000-0001-6119-5065","contributorId":201463,"corporation":false,"usgs":true,"family":"Medler","given":"Colton","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788909,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70211035,"text":"70211035 - 2020 - Resource allocation for coastal wetland management: Confronting uncertainty about sea level rise","interactions":[],"lastModifiedDate":"2020-07-13T12:49:43.365018","indexId":"70211035","displayToPublicDate":"2020-05-12T07:46:26","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"10","title":"Resource allocation for coastal wetland management: Confronting uncertainty about sea level rise","docAbstract":"Coastal wetlands are rich and diverse ecosystems with a wide variety of birdlife and other natural resources.  Decision making for coastal wetland management is difficult given the complex nature of these ecological systems and the frequent need to meet multiple objectives for varied resources.  Management challenges in the coastal zone are exacerbated by uncertainty about sea level rise and impacts on infrastructure, particularly the levees and structures which provide managers the ability to manipulate water levels in managed wetlands and create high quality habitat for birds and other wildlife.  The most challenging decisions in coastal wetland management involve resource allocation for habitat manipulations and longer-term investments to maintain management control in wetlands that are increasingly compromised by sea level rise and increasing storm frequency and intensity associated with a changing climate.\nWe used multi-criteria decision analysis to create a resource allocation framework for managed wetlands that identifies the most effective and efficient management strategies that are robust to uncertainty about sea level rise.  The prototype framework includes a small number of managed wetlands, for which subject matter experts articulated potential management and restoration actions.  The consequences of these actions were predicted using expert elicitation with the subject matter experts; furthermore, expert judgment was used to articulate expected outcomes with two hypotheses about the rate of sea level rise.  We used a constrained optimization (integer linear programming) to find optimal resource allocation strategies given a range of budget constraints; we also used a Pareto efficiency analysis for a graphical solution to the problem if the exact budget constraint is not known.  Finally, given the importance of preference weights in a multi-criteria decision analysis, we also evaluated sensitivity to objective weights.  With this resource allocation framework, we showed how to identify optimal combinations of management and restoration actions to maximize benefits in terms of stated objectives.  We show how multiple working hypotheses about sea level rise can be incorporated into decisions for coastal wetland management.  Our resource allocation approach can be modified for a wide variety of natural resource management settings.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Structured decision making: Case studies in natural resource management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins Press","usgsCitation":"Lyons, J., Kalasz, K., Breese, G., and Boal, C.W., 2020, Resource allocation for coastal wetland management: Confronting uncertainty about sea level rise, chap. 10 <i>of</i> Structured decision making: Case studies in natural resource management, p. 108-123.","productDescription":"16 p.","startPage":"108","endPage":"123","ipdsId":"IP-102721","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":376271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":376270,"type":{"id":15,"text":"Index Page"},"url":"https://jhupbooks.press.jhu.edu/title/structured-decision-making/table-of-contents"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":228916,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":792525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalasz, Kevin S.","contributorId":228917,"corporation":false,"usgs":false,"family":"Kalasz","given":"Kevin S.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":792526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breese, Gregory","contributorId":228918,"corporation":false,"usgs":false,"family":"Breese","given":"Gregory","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":792527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":792528,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70210018,"text":"fs20203030 - 2020 - Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana","interactions":[],"lastModifiedDate":"2020-05-12T11:33:15.420536","indexId":"fs20203030","displayToPublicDate":"2020-05-11T15:05:45","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3030","displayTitle":"Trends in Streamflow, Nutrients, and Total Suspended Solids in the Upper White River Basin, Indiana","title":"Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana","docAbstract":"<p>The U.S. Geological Survey, in partnership with The Nature Conservancy, analyzed existing water-quality and streamflow data from three locations in the Upper White River Basin, Indiana, to estimate annual mean concentrations and fluxes and to identify and quantify changes in water quality and streamflow over time. Water-quality data used in the analyses were collected between water years 1992 and 2017. Annual mean-daily concentrations and fluxes of total suspended solids, total phosphorus as phosphorus, nitrate plus nitrite as nitrogen, and total Kjeldahl nitrogen as nitrogen were estimated for U.S.&nbsp;Geological Survey streamgage locations in Indiana on the Upper White River at Muncie, near Nora, and near Centerton. In addition, flow-normalized annual mean-daily concentrations and fluxes of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen were estimated and used to assess changes in these constituents between water years 1997 and 2017. Flow normalization is a process that attempts to remove the effects of year-to-year variation in streamflow on concentrations and fluxes without removing the effects associated with seasonal and long-term (multiyear) trends in streamflow.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203030","collaboration":"Prepared in cooperation with The Nature Conservancy with generous support from the Nina Mason Pulliam Charitable Trust","usgsCitation":"Koltun, G.F., and Hauswald, C., 2020, Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana: U.S. Geological Survey Fact Sheet 2020–3030, 6 p., https://doi.org/10.3133/fs20203030.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-114324","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":374596,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3030/coverthb.jpg"},{"id":374597,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3030/fs20203030.pdf","text":"Report","size":"9.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3030"}],"country":"United States","state":"Indiana","otherGeospatial":"Upper White River Basin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-86.6546,39.6001],[-86.6522,39.6087],[-86.6463,39.6128],[-86.6403,39.6201],[-86.6404,39.6305],[-86.6654,39.6305],[-86.6858,39.63],[-86.6853,39.6884],[-86.6849,39.7773],[-86.6845,39.8648],[-86.6929,39.8643],[-86.6937,39.9228],[-86.6938,39.9528],[-86.6946,40.0402],[-86.6961,40.1282],[-86.6962,40.1785],[-86.2424,40.1807],[-86.2435,40.2152],[-86.242,40.3013],[-86.2423,40.3734],[-86.2429,40.3884],[-86.2422,40.4029],[-85.8624,40.407],[-85.8621,40.3784],[-85.5784,40.3794],[-85.4451,40.3792],[-85.2205,40.379],[-85.2182,40.3073],[-85.1302,40.3082],[-85.0186,40.3092],[-84.901,40.3096],[-84.8064,40.3102],[-84.8079,40.1741],[-84.8106,40.1351],[-84.8112,40.1265],[-84.8131,40.006],[-84.8603,40.0066],[-84.8952,40.0061],[-85.2014,40.0042],[-85.2013,39.875],[-85.2133,39.8751],[-85.2205,39.8748],[-85.2214,39.7895],[-85.243,39.7902],[-85.3017,39.789],[-85.3519,39.7894],[-85.4651,39.7886],[-85.5765,39.7858],[-85.5968,39.786],[-85.6333,39.7862],[-85.6338,39.6987],[-85.6876,39.6987],[-85.7993,39.6993],[-85.913,39.6976],[-85.9518,39.6969],[-85.9523,39.638],[-85.9521,39.347],[-85.9812,39.3466],[-85.9902,39.3467],[-86.0247,39.3464],[-86.0854,39.3452],[-86.0919,39.3452],[-86.1008,39.3453],[-86.1377,39.3445],[-86.249,39.342],[-86.3566,39.3404],[-86.3816,39.3399],[-86.4631,39.3391],[-86.5732,39.3395],[-86.6309,39.3413],[-86.6309,39.3481],[-86.6323,39.4696],[-86.6859,39.47],[-86.686,39.5144],[-86.6861,39.5262],[-86.6706,39.5339],[-86.6533,39.5475],[-86.6491,39.5552],[-86.6528,39.5666],[-86.6546,39.5865],[-86.6552,39.5965],[-86.6546,39.6001]]]},\"properties\":{\"name\":\"Boone\",\"state\":\"IN\"}}]}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/oki-water\" href=\"https://www.usgs.gov/centers/oki-water\">Ohio-Kentucky-Indiana Water Science Center</a> <br>U.S. Geological Survey <br>6460 Busch Blvd., Suite 100 <br>Columbus, OH 43229</p>","tableOfContents":"<ul><li>Introduction</li><li>Estimated Mean Concentrations and Flux of Sediment and Nutrients</li><li>Trends in Streamflow</li><li>Changes in Flow-Normalized Concentration and Flux between Water Years 1997 and 2017</li><li>References Cited</li></ul>","publishedDate":"2020-05-11","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":140048,"corporation":false,"usgs":true,"family":"Koltun","given":"G.","email":"gfkoltun@usgs.gov","middleInitial":"F.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hauswald, Cassie 0000-0002-9265-0603","orcid":"https://orcid.org/0000-0002-9265-0603","contributorId":224621,"corporation":false,"usgs":false,"family":"Hauswald","given":"Cassie","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":true,"id":788823,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209985,"text":"sir20205035 - 2020 - Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13","interactions":[],"lastModifiedDate":"2020-05-12T11:44:31.472549","indexId":"sir20205035","displayToPublicDate":"2020-05-11T11:54:36","publicationYear":"2020","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":"2020-5035","displayTitle":"Ecological Status of Aquatic Communities in Selected Streams in the Milwaukee Metropolitan Sewerage District Planning Area of Wisconsin, 2004–13","title":"Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13","docAbstract":"<p>A total of 14 wadable streams in urban or urbanizing watersheds near Milwaukee, Wisconsin, were sampled in 2004, 2007, 2010, and 2013 to assess the ecological status of aquatic communities (biota), including benthic algae and invertebrates, and fish. To assess temporal variation, additional community sampling was also done at a subset of three sites in 2011 and 2012. Relative abundances of each type of organism were used to calculate biological metrics, such as richness and diversity, percentages of intolerant and tolerant organisms, and indexes of biotic integrity for invertebrates and fish. Selected environmental (physical and chemical) data in the streams were collected to evaluate potential relations to the biota and the ecological health of the stream. Physical and chemical data included land use/land cover, stream discharge from U.S. Geological Survey (USGS) streamgages (except at 2 creeks that were not gaged), stream habitat, microhabitat at invertebrate collection locations, water quality (except at 2 creeks that were not gaged), field measurements of several water-quality constituents, measures of benthic algal biomass, and toxicity and chemical tests on extracts from passive samplers deployed at a subset of 6 sites. Relative abundances of organisms and biological metrics were compared among sampling years and with environmental metrics to evaluate the ecological status of these streams and determine primary stressors on the aquatic communities, with the aim of helping resource managers understand and work toward improving the ecological health of these and other urban and urbanizing rivers in the study area.</p><p>Biological metrics for most sites indicated some level of diminished ecological status when compared across all sampled sites and when compared with rating scales for selected metrics. The least degraded sites among all those sampled—indicated by aggregate bioassessments for algae, invertebrates, and fish metrics and in order starting with the best overall condition—were the Milwaukee River near Cedarburg, Menomonee River at Menomonee Falls, Jewel Creek, and Milwaukee River at Milwaukee. The most degraded sites were Menomonee River at Wauwatosa, Root River at Greenfield, Lincoln Creek, and the Kinnickinnic River. Differences in aggregate bioassessments indicate that aquatic communities at the Menomonee River at Wauwatosa site and the Root River at Greenfield site were worse in 2013 than in 2004; however, Oak Creek and Honey Creek sites were better. In 2013, several sites had less than 30-percent pollution-sensitive diatoms indicating degraded algal assemblages. Invertebrate metrics for most of the 14 sites in 2013 were lower than in 2004 and indicate that invertebrate assemblages at most sampled sites were more degraded in 2013. Tolerant fish taxa made up more than 40 percent of assemblages at most sites and nearly 100 percent of assemblages at four sites. At times, in some smaller streams, too few fish were captured to compute an Index of Biotic Integrity with confidence, and invertebrates provided a better means for assessing the ecological status and water quality. With these few exceptions, the use of all three groups of biota provided the most robust assessments at the 14 sites in 2004–13.</p><p>Physical and chemical stressors were correlated to adverse effects on aquatic biota at the sampled streams. Passive samplers were deployed at a subset of six sites in 2013. Microtox results indicated there was little or no toxicity at the Milwaukee River near Cedarburg site and at the Oak Creek site, slight toxicity at the Lincoln Creek and Honey Creek sites, and moderate toxicity at the Milwaukee River at Milwaukee site and the Little Menomonee River site; however, based on cytochrome-P450 reporter gene system toxicity tests, potential toxicity from hydrophobic organic contaminants was measured at all six sites. For all 14 sites, physical and chemical stressors related to urbanization correlated with biological metrics for algae, invertebrates, and fish. Most stressors for aquatic biota reflected an urban signature. Stressors related to ecological condition in our study were chemical and physical, such as developed land, impervious surface in the watershed, urban land in a buffer area around the stream (a 100-foot [30-meter]-wide area on each side of the stream, and maximum instantaneous discharge normalized by drainage area (a measure of flood and scour effects). Chemical stressors included low waterborne concentrations of dissolved oxygen and high concentrations of chloride, zinc and other metals, nutrients (nitrite and phosphorus), and fecal coliform bacteria.</p><p>Although algae, invertebrates, and fish did not always demonstrate a significant response to the same stressors, higher abundances of high total phosphorus-indicator diatoms, lower ratings for invertebrate biotic integrity indexes and percentages of mayflies-stoneflies-caddisflies, and lower values for fish biotic integrity indexes underscored possible adverse effects of even low levels of developed land. Developed land is typically associated with more rapid runoff, which washes chemicals from impervious surfaces into area waterways and degrades stream habitat for aquatic communities. However, with respect to at least chloride from road salt, diatoms tolerant to dissolved salts were significantly lower with as little as 1-percent mixed forest in the watershed. Lower percentages of urban land in the stream buffer correlated with healthier aquatic assemblages of algae, invertebrates, and fish. The assessment of algal, invertebrate, and fish assemblages coupled with physical and chemical data were highly useful in evaluating the ecological status of aquatic communities at the 14 sites and for determining environmental stressors that may be contributing to reduced stream condition. Some of the stressors could potentially be removed or lessened with stream rehabilitation or changes in watershed management.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205035","collaboration":"Prepared in cooperation with the Milwaukee Metropolitan Sewerage District","usgsCitation":"Scudder Eikenberry, B.C., Nott, M.A., Stewart, J.S., Sullivan, D.J., Alvarez, D.A., Bell, A.H., and Fitzpatrick, F.A., 2020, Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13: U.S. Geological Survey Scientific Investigations Report 2020–5035, 84 p., https://doi.org/10.3133/sir20205035.","productDescription":"Report: viii, 84 p.; Data Release; Dataset","numberOfPages":"96","onlineOnly":"Y","ipdsId":"IP-106552","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374557,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5035/coverthb.jpg"},{"id":374558,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5035/sir20205035.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5035"},{"id":374559,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FWMODL","text":"USGS data release","linkHelpText":"Aquatic community and environmental data for 14 rivers and streams in the Milwaukee Metropolitan Sewerage District Planning Area, 2004-13"},{"id":374560,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System—","linkHelpText":"USGS water data for the Nation"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Milwaukee Metropolitan Sewerage District Planning Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.187255859375,\n              42.512601715736665\n            ],\n            [\n              -87.81372070312499,\n              42.512601715736665\n            ],\n            [\n              -87.81372070312499,\n              43.15710884095329\n            ],\n            [\n              -88.187255859375,\n              43.15710884095329\n            ],\n            [\n              -88.187255859375,\n              42.512601715736665\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/umid-water\" href=\"https://www.usgs.gov/centers/umid-water\">Upper Midwest Water Science Center</a> <br>U.S. Geological Survey<br>8505 Research Way <br>Middleton, WI 53562</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Assessment of Aquatic Communities in Relation to Stream Condition</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-05-11","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Eikenberry, Barbara C. Scudder 0000-0001-8058-1201 beikenberry@usgs.gov","orcid":"https://orcid.org/0000-0001-8058-1201","contributorId":172148,"corporation":false,"usgs":true,"family":"Eikenberry","given":"Barbara C. Scudder","email":"beikenberry@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":788704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nott, Michelle A. 0000-0003-3968-7586","orcid":"https://orcid.org/0000-0003-3968-7586","contributorId":221766,"corporation":false,"usgs":true,"family":"Nott","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Jana S. 0000-0002-8121-1373 jsstewar@usgs.gov","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":539,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","email":"jsstewar@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Daniel J. 0000-0003-2705-3738","orcid":"https://orcid.org/0000-0003-2705-3738","contributorId":204322,"corporation":false,"usgs":true,"family":"Sullivan","given":"Daniel","email":"","middleInitial":"J.","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":788707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarez, David A. 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":1369,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":788708,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788709,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788710,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70209987,"text":"ds1124 - 2020 - Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015","interactions":[],"lastModifiedDate":"2020-05-11T20:21:59.676539","indexId":"ds1124","displayToPublicDate":"2020-05-11T11:20:43","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1124","displayTitle":"Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January through December 2016, and Previously Unpublished Data from 2013 to 2015","title":"Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015","docAbstract":"<p>Environmental groundwater-quality data were collected from 648 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program and are included in this report. Most of the wells (514) were sampled from January through December 2016, and 60 of them were sampled in 2013 and 74 in 2014. The data were collected from seven types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public-water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths; flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths over a horizontal distance; and modeling support studies, which are used to provide data to support groundwater modeling. Groundwater samples were analyzed for many water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic speciation, chromium [VI], and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release. Some data from environmental samples collected in 2013–14 and quality-control samples collected in 2012–15 also are included in the associated data release. Data from samples collected in 2016 are associated with networks described in this report and have not been published previously; data from samples collected between 2012 and 2015 are associated with networks described in previous reports in this data series.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1124","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Arnold, T.L., Bexfield, L.M., Musgrove, M., Erickson, M.L., Kingsbury, J.A., Degnan, J.R., Tesoriero, A.J., Kulongoski, J.T., and Belitz, K., 2020, Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015: U.S. Geological Survey Data Series 1124, 135 p., https://doi.org/10.3133/ds1124.  ","productDescription":"Report: ix, 135 p.; Data Release; Dataset","numberOfPages":"150","onlineOnly":"Y","ipdsId":"IP-111772","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374561,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1124/coverthb.jpg"},{"id":374562,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1124/ds1124.pdf","text":"Report","size":"20.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1124"},{"id":374563,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W4RR74","text":"USGS data release","linkHelpText":"Datasets from groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 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data-mce-href=\"mailto:%20dc_il@usgs.gov\" href=\"mailto:%20dc_il@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/cm-water\" href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a> <br>U.S. Geological Survey<br>405 North Goodwin <br>Urbana, IL 61801 <br></p>","tableOfContents":"<ul><li>Foreword</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Groundwater Study Design</li><li>Sample Collection and Analysis</li><li>Data Reporting</li><li>Quality-Assurance and Quality-Control Methods</li><li>Groundwater-Quality Data</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. Information Contained in Previous Reports in This Series</li><li>Appendix 2. Well Depth and Open Interval by Study Network</li><li>Appendix 3. High-Frequency Data from Enhanced Trends Networks</li><li>Appendix 4. Quality-Control Samples and Data Analysis</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-05-11","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Arnold, Terri 0000-0003-1406-6054 tlarnold@usgs.gov","orcid":"https://orcid.org/0000-0003-1406-6054","contributorId":1598,"corporation":false,"usgs":false,"family":"Arnold","given":"Terri","email":"tlarnold@usgs.gov","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":788711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":1316,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":788713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","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},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":788715,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Degnan, James R. 0000-0002-5665-9010 jrdegnan@usgs.gov","orcid":"https://orcid.org/0000-0002-5665-9010","contributorId":498,"corporation":false,"usgs":true,"family":"Degnan","given":"James","email":"jrdegnan@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788716,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":2693,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788717,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788718,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":788719,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70210175,"text":"70210175 - 2020 - Fluoride occurrence in United States groundwater","interactions":[],"lastModifiedDate":"2020-05-19T13:38:58.950932","indexId":"70210175","displayToPublicDate":"2020-05-11T08:30:10","publicationYear":"2020","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":"Fluoride occurrence in United States groundwater","docAbstract":"Data from 38,105 wells were used to characterize fluoride (F) occurrence in untreated United States (U.S.) groundwater. For domestic wells (n = 11,032), water from which is generally not purposely fluoridated or monitored for quality, 10.9% of the samples have F concentrations >0.7 mg/L (U.S. Public Health Service recommended optimal F concentration in drinking water for preventing tooth decay) (87% are <0.7 mg/L); 2.6% have F > 2 mg/L (EPA Secondary Maximum Contaminant Level, SMCL); and 0.6% have F > 4 mg/L (EPA MCL). The data indicate the biggest concern with F in domestic wells at the national scale could be one of under consumption of F with respect to the oral-health benchmark (0.7 mg/L). Elevated F concentrations relative to the SMCL and MCL are regionally important, particularly in the western U.S. Statistical comparisons of potentially important controlling factors in four F-concentration categories (<0.1–0.7 mg/L; >0.7–2 mg/L; >2–4 mg/L; >4 mg/L) at the national scale indicate the highest F-concentration category is associated with groundwater that has significantly greater pH values, TDS and alkalinity concentrations, and well depths, and lower Ca/Na ratios and mean annual precipitation, than the lowest F-concentration category. The relative importance of the controlling factors appears to be regionally variable. Three case studies illustrate the spatial variability in controlling factors using groundwater-age (groundwater residence time), water-isotope (evaporative concentration), and water-temperature (geothermal processes) data. Populations potentially served by domestic wells with F concentrations <0.7, >0.7, >2, and >4 mg/L are estimated to be ~28,200,000, ~3,110,000; ~522,000; and ~172,000 people, respectively, in 40 principal aquifers with at least 25 F analyses per aquifer.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.139217","collaboration":"","usgsCitation":"McMahon, P.B., Brown, C., Johnson, T., Belitz, K., and Lindsey, B.D., 2020, Fluoride occurrence in United States groundwater: Science of the Total Environment, v. 732, https://doi.org/10.1016/j.scitotenv.2020.139217.","productDescription":"139217, 15 p.","startPage":"","ipdsId":"IP-114693","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":456808,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.139217","text":"Publisher Index Page"},{"id":436992,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CUPRIP","text":"USGS data release","linkHelpText":"Data for Fluoride Occurrence in United States Groundwater"},{"id":374917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n    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          47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"732","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Craig J. 0000-0002-3858-3964","orcid":"https://orcid.org/0000-0002-3858-3964","contributorId":210450,"corporation":false,"usgs":true,"family":"Brown","given":"Craig J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Tyler D. 0000-0002-7334-9188","orcid":"https://orcid.org/0000-0002-7334-9188","contributorId":201888,"corporation":false,"usgs":true,"family":"Johnson","given":"Tyler D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":213728,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":789430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":789431,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209808,"text":"sir20205037 - 2020 - Compositional analysis of formation water geochemistry and microbiology of commercial and carbon dioxide-rich wells in the southwestern United States","interactions":[],"lastModifiedDate":"2020-05-11T11:42:40.648542","indexId":"sir20205037","displayToPublicDate":"2020-05-08T14:55:00","publicationYear":"2020","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":"2020-5037","displayTitle":"Compositional Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells in the Southwestern United States","title":"Compositional analysis of formation water geochemistry and microbiology of commercial and carbon dioxide-rich wells in the southwestern United States","docAbstract":"<p>Studies of naturally occurring subsurface carbon dioxide (CO<sub>2</sub>) accumulations can provide useful information for potential CO<sub>2</sub> injection projects; however, the microbial communities and formation water geochemistry of most reservoirs are understudied. Formation water and microbial biomass were sampled at four CO<sub>2</sub>-rich reservoir sites: two within Bravo Dome, a commercial CO<sub>2</sub> field in New Mexico; one northwest of Bravo Dome in Colorado (Oakdale Field); and one southwest of Bravo Dome in New Mexico (Rafter “K” Ranch). Aside from the Rafter “K” Ranch site, minor differences were observed in the geochemistry of formation water collected from these sites compared to historical data. No organisms were significantly associated with Oakdale Field compared to the other three sites, nor were any hydrogeochemical or gas geochemical parameters (for example, CO<sub>2</sub> concentration) found to have significant associations with the microbial ecology of these four sites. Microorganisms from these sites were metabolically diverse and had the potential to (1) generate methane, (2) produce corrosive hydrogen sulfide (H<sub>2</sub>S), and (3) rapidly biofoul and (or) clog pore spaces by shifting microbial communities with changes in salinity or nutrient supply. This study demonstrates that high concentrations of CO<sub>2</sub> in subsurface reservoirs apparently have not imparted a distinct geochemical or microbiological signature on the associated formation waters and that the microorganisms in these reservoirs are metabolically diverse and could adapt to geochemical changes in the subsurface.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205037","usgsCitation":"Shelton, J.L., Andrews, R.S., Akob, D.M., DeVera, C.A., Mumford, A.C., Engle, M., Plampin, M.R., and Brennan, S.T., 2020, Compositional analysis of formation water geochemistry and microbiology of commercial and carbon dioxide-rich wells in the southwestern United States: U.S. Geological Survey Scientific Investigations Report 2020–5037, 26 p., https://doi.org/10.3133/sir20205037.","productDescription":"viii, 26 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098514","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":374365,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5037/sir20205037.pdf","text":"Report","size":"1.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5037"},{"id":374364,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5037/coverthb.jpg"}],"country":"United States","state":"Colorado, New Mexico, Texas, Oklahoma","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.16064453125,\n              34.07086232376631\n            ],\n            [\n              -102.919921875,\n              34.07086232376631\n            ],\n            [\n              -102.919921875,\n              37.43997405227057\n            ],\n            [\n              -107.16064453125,\n              37.43997405227057\n            ],\n            [\n              -107.16064453125,\n              34.07086232376631\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eersc\" data-mce-href=\"https://www.usgs.gov/centers/eersc\">Eastern Energy Resources Science Center</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>956 National Center<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Background and Study Sites</li><li>Methods</li><li>Produced Fluid Geochemistry</li><li>Microbial Community Composition and Diversity</li><li>Growth and Activity of Microbial Functional Groups in the Rafter “K” Ranch and Oakdale Field Samples</li><li>Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2020-05-08","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Shelton, Jenna L. 0000-0002-1377-0675 jlshelton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-0675","contributorId":5025,"corporation":false,"usgs":true,"family":"Shelton","given":"Jenna L.","email":"jlshelton@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":788114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrews, Robert S. 0000-0002-6166-720X","orcid":"https://orcid.org/0000-0002-6166-720X","contributorId":204981,"corporation":false,"usgs":true,"family":"Andrews","given":"Robert","email":"","middleInitial":"S.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":788115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Akob, Denise M. 0000-0003-1534-3025 dakob@usgs.gov","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":4980,"corporation":false,"usgs":true,"family":"Akob","given":"Denise","email":"dakob@usgs.gov","middleInitial":"M.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":788116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeVera, Christina A. 0000-0002-4691-6108 cdevera@usgs.gov","orcid":"https://orcid.org/0000-0002-4691-6108","contributorId":3845,"corporation":false,"usgs":true,"family":"DeVera","given":"Christina","email":"cdevera@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":788117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mumford, Adam C. 0000-0002-8082-8910 amumford@usgs.gov","orcid":"https://orcid.org/0000-0002-8082-8910","contributorId":197795,"corporation":false,"usgs":true,"family":"Mumford","given":"Adam","email":"amumford@usgs.gov","middleInitial":"C.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":788118,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Engle, Mark 0000-0001-5258-7374","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":222085,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":788119,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Plampin, Michelle R. 0000-0003-4068-5801 mplampin@usgs.gov","orcid":"https://orcid.org/0000-0003-4068-5801","contributorId":204983,"corporation":false,"usgs":true,"family":"Plampin","given":"Michelle","email":"mplampin@usgs.gov","middleInitial":"R.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":788120,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brennan, Sean T. 0000-0002-7102-9359 sbrennan@usgs.gov","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":559,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean","email":"sbrennan@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":788121,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70210138,"text":"70210138 - 2020 - Species richness responses to water withdrawal scenarios and minimum flow levels:  Evaluating presumptive standards in the Tennessee and Cumberland River basins","interactions":[],"lastModifiedDate":"2020-05-15T14:06:18.349418","indexId":"70210138","displayToPublicDate":"2020-05-08T08:59:49","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Species richness responses to water withdrawal scenarios and minimum flow levels:  Evaluating presumptive standards in the Tennessee and Cumberland River basins","docAbstract":"Water resource managers are challenged to balance growing water demand with protecting aquatic ecosystems and biodiversity. Management decisions can benefit from improved understanding of water withdrawal impacts on hydrologic regimes and ecological assemblages. This study used Ecological Limit Functions for fish groups within the Tennessee and Cumberland river basins to predict species richness responses under simulated constant-rate (CR) and percent-of-flow (POF) withdrawals and for different minimum flow level protections. Streamflow characteristics (SFC) and richness were generally less sensitive to POF withdrawals than CR withdrawals among sites, fish groups, and ecoregions. Species richness generally declined with increasing withdrawals, but responses were variable depending on site-specific departures of SFCs from reference conditions, drainage area, fish group, ecoregion, and minimum flow level. Under POF withdrawals, 10% and 20% daily flow reductions often resulted in loss of <1 species and/or ≤5% richness among fish groups. Median ecological withdrawal thresholds ranged from 3.5-31% for POF withdrawals and from 0.01-0.92 m3/s for CR withdrawals across fish groups and ecoregions. Application of minimum flow level cutoffs often resulted in damping effects on SFC and richness responses, indicating that protection of low streamflows may mitigate hydrologic alteration and fish species richness loss related to water withdrawals. Site-specific and regionally summarized responses of flow regimes and fish assemblages under alternative withdrawal strategies in this study may be useful in informing water management decisions regarding streamflow allocation and maintaining ecological flows.","language":"English","publisher":"MDPI","doi":"10.3390/w12051334","collaboration":"","usgsCitation":"Driver, L., Cartwright, J.M., Knight, R., and Wolfe, W., 2020, Species richness responses to water withdrawal scenarios and minimum flow levels:  Evaluating presumptive standards in the Tennessee and Cumberland River basins: Water, v. 12, no. 5, https://doi.org/10.3390/w12051334.","productDescription":"1334, 24 p.","startPage":"","ipdsId":"IP-113154","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":456820,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12051334","text":"Publisher Index Page"},{"id":436994,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q23Z4B","text":"USGS data release","linkHelpText":"Ecological flow analyses of surface water withdrawal scenarios in the Cumberland and Tennessee River basins"},{"id":374871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"","otherGeospatial":"Cumberland River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.857421875,\n              35.06597313798418\n            ],\n            [\n              -82.705078125,\n              34.77771580360469\n            ],\n            [\n              -80.771484375,\n              37.43997405227057\n            ],\n            [\n              -86.66015624999999,\n              37.64903402157866\n            ],\n            [\n              -88.857421875,\n              35.06597313798418\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Driver, Lucas 0000-0003-2549-1849","orcid":"https://orcid.org/0000-0003-2549-1849","contributorId":219176,"corporation":false,"usgs":true,"family":"Driver","given":"Lucas","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":789270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Rodney 0000-0001-9588-0167 rrknight@usgs.gov","orcid":"https://orcid.org/0000-0001-9588-0167","contributorId":152422,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney","email":"rrknight@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":789272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208798,"text":"sir20205015 - 2020 - Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17","interactions":[],"lastModifiedDate":"2020-05-08T11:50:49.347355","indexId":"sir20205015","displayToPublicDate":"2020-05-07T15:47:32","publicationYear":"2020","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":"2020-5015","displayTitle":"Pilot-Scale Testing of Dairy Manure Treatments to Reduce Nutrient Transport from Land Application, Northwest Ohio, 2015–17","title":"Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17","docAbstract":"<p>Manure and wastewater from large livestock operations have the potential to negatively affect surface water and groundwater, including the eutrophication of surface waters and harmful algal blooms. In the Western Lake Erie Basin, where there is a high density of animal agriculture, harmful algal blooms have been attributed, in part, to phosphorus loading from dairy manure and fertilizer applications. Liquid lagoon manure produced by dairy operations typically has low nutrient concentrations and high-water content, so transportation costs are high relative to the value of the nutrients when applied to fields. Treatment systems are needed to transform manure into a dewatered product that is more economical to transport greater distances and that slows and (or) reduces the release of nutrients in soil, allowing nutrients to remain available for crop growth.</p><p>This study was designed to pilot test a treatment solution in the Western Lake Erie Basin. The U.S. Geological Survey and Bowling Green State University field tested a dewatering treatment process (coagulant/polymer mixture) for dairy manure at pilot-scale test plots at The Ohio State University Agricultural Research and Development Center Northwest Agricultural Research Station. Automatic samplers were used to collect samples during 13 baseline and 9 post-manure application rainfall events that resulted in substantial surface runoff and (or) tile flow from October 2015 through early November 2017. Results are reported for three test plots that received liquid lagoon manure (raw manure) and three test plots that received polymer-treated manure (treated manure).</p><p>Nutrient concentrations and flow volumes in surface runoff and tile flow were determined in baseline and post-manure application rainfall events. Nutrient concentration ranges are reported for 9 baseline and 9 post-manure application events as follows: dissolved reactive phosphorus, less than (&lt;) 0.013−2.16 milligrams per liter (mg/L); nitrate plus nitrite, filtered, 0.32−77 mg/L; ammonia, filtered, &lt;0.05−2.6 mg/L; total phosphorus, &lt;0.01−12.8 mg/L; and total nitrogen, 1.49−77.2 mg/L. Volumes are reported for 6 baseline and 9 post-manure application rainfall events. None of the post-manure application runoff volumes were significantly different by plot or by treatment type (raw manure versus treated manure).</p><p>Because concentrations alone do not reflect the true effects of different manure treatments, loads and flow-weighted mean concentrations of nutrients during post-manure application rainfall events were compared between plots with treated manure and those with raw manure. Loads of dissolved reactive phosphorus, total phosphorus, nitrate plus nitrite, and total nitrogen were calculated using the U.S. Geological Survey Graphical Constituent Loading and Analysis System. Loads of ammonia were not calculated because many of the ammonia concentrations were below the reporting limit.</p><p>During the post-manure application period, higher nitrogen loads resulted from tile flow than surface runoff. For phosphorus, the opposite was true in that higher loads resulted from surface runoff than tile flow. Combined loads (surface runoff and tile flow) of dissolved reactive phosphorus were significantly different between raw manure and treated manure plots, but there was no significant difference in combined loads of total phosphorus, nitrate plus nitrite, or total nitrogen between raw manure and treated manure plots. Flow-weighted mean concentrations were calculated for the combined loads for the post-manure application rainfall events. Flow-weighted mean concentrations of dissolved reactive phosphorus and, to a lesser extent, total phosphorus were significantly different between raw manure and treated manure plots. Flow-weighted mean concentrations of nitrate plus nitrite and total nitrogen were not significantly different between raw manure and treated manure plots. The differences in loads and flow-weighted mean concentrations between raw manure and treated manure plots indicate that dissolved reactive phosphorus was likely retained in the soil and hydrological transport was reduced for the plots amended with the treated manure as compared to raw manure. Although confirmation field testing needs to be done, these results indicate that the use of this coagulant/polymer mixture shows potential in helping to reduce flow of dissolved phosphorus from agricultural fields with applied manure.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205015","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Francy, D.S., Brady, A.M.G., Ash, B.L., and Midden, W.R., 2020, Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17: U.S. Geological Survey Scientific Investigations Report 2020–5015, 31 p., https://doi.org/10.3133/sir20205015.","productDescription":"Report: viii, 31 p.; Appendix Tables","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-095889","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science 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<a data-mce-href=\"https://www.usgs.gov/centers/oki-water\" href=\"https://www.usgs.gov/centers/oki-water\">Ohio-Kentucky-Indiana Water Science Center</a> <br>U.S. Geological Survey <br>6460 Busch Boulevard Suite 100 <br>Columbus, OH 43229–1737 </p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Methods of Study</li><li>Quality-Control Measures of Bias and Variability</li><li>Sampling Events and Concentrations of Nutrients in Surface Runoff and Tile Flow Samples</li><li>Water Volumes</li><li>Comparisons of Nutrient Loads and Flow-Weighted Mean Concentrations from Raw Manure and Treated Manure Plots</li><li>Corn Yields</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. Sample Processing Cheat Sheet</li><li>Appendix 2. Data Tables</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2020-05-07","noUsgsAuthors":false,"publicationDate":"2020-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Francy, Donna S. 0000-0001-9229-3557 dsfrancy@usgs.gov","orcid":"https://orcid.org/0000-0001-9229-3557","contributorId":1853,"corporation":false,"usgs":true,"family":"Francy","given":"Donna","email":"dsfrancy@usgs.gov","middleInitial":"S.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brady, Amie M.G. 0000-0002-7414-0992 amgbrady@usgs.gov","orcid":"https://orcid.org/0000-0002-7414-0992","contributorId":2544,"corporation":false,"usgs":true,"family":"Brady","given":"Amie","email":"amgbrady@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ash, Bethany L. 0000-0003-0590-882X","orcid":"https://orcid.org/0000-0003-0590-882X","contributorId":222890,"corporation":false,"usgs":false,"family":"Ash","given":"Bethany","email":"","middleInitial":"L.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":783433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Midden, W. Robert 0000-0002-1838-1046","orcid":"https://orcid.org/0000-0002-1838-1046","contributorId":222889,"corporation":false,"usgs":false,"family":"Midden","given":"W.","email":"","middleInitial":"Robert","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":783432,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209328,"text":"ofr20201032 - 2020 - Simulation of the probabilistic plume extent for a potential replacement wastewater-infiltration lagoon, and probabilistic contributing areas for supply wells for the Town of Lac du Flambeau, Vilas County, Wisconsin","interactions":[],"lastModifiedDate":"2020-05-08T11:44:10.706967","indexId":"ofr20201032","displayToPublicDate":"2020-05-07T14:53:18","publicationYear":"2020","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":"2020-1032","displayTitle":"Simulation of the Probabilistic Plume Extent for a Potential Replacement Wastewater-Infiltration Lagoon, and Probabilistic Contributing Areas for Supply Wells for the Town of Lac du Flambeau, Vilas County, Wisconsin","title":"Simulation of the probabilistic plume extent for a potential replacement wastewater-infiltration lagoon, and probabilistic contributing areas for supply wells for the Town of Lac du Flambeau, Vilas County, Wisconsin","docAbstract":"<p>An existing two-dimensional, steady-state groundwater-flow model of the shallow groundwater-flow system of the Lac du Flambeau Reservation in Vilas County, Wisconsin, originally developed by the U.S. Geological Survey, was used to simulate the potential for wastewater from a proposed relocation of a wastewater lagoon to contaminate the Lac du Flambeau Band of Lake Superior Chippewa’s drinking-water-supply wells. This simulation was completed by the U.S. Geological Survey in cooperation with the Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service. The simulated scenarios consisted of removing wastewater infiltration from existing lagoons and re-applying that infiltration at the proposed location. Two analyses were performed for the scenarios. First, the probable extent of the plume discharging from the proposed infiltration lagoons was mapped with a Monte Carlo algorithm that used uncertainty identified during the calibration process to simulate thousands of possible outcomes. Second, the Monte Carlo method was again used to simulate a probabilistic contributing area for the Tribe’s nearby “Main Pumphouse” supply wells. The purpose of the simulations was to evaluate the potential for infiltrated wastewater to be captured by the public-supply wells.</p><p>Most features of the previously developed model remained unchanged, including calibrated parameters such as hydraulic conductivity and recharge. Thus, the same covariance distributions that were generated during calibration of the regional model (Juckem and others, 2014) remained unchanged and were used to inform the Monte Carlo simulations for the scenario simulations described in this report. The reader is encouraged to read the full report by Juckem and others (available at <a data-mce-href=\"https://doi.org/10.3133/sir20145020\" href=\"https://doi.org/10.3133/sir20145020\">https://doi.org/10.3133/sir20145020</a>) for a detailed description of the model design and calibration, as well as a description of the Monte Carlo method, its limitations, and the original results.</p><p>Results for these new scenarios indicate that the probabilistic plume extent for the proposed infiltration lagoons does not reach the Main Pumphouse wells using pumping rates and wastewater volumes estimated for 2010. Similarly, the contributing area for the Main Pumphouse wells does not capture water from within the proposed infiltration lagoon footprint. However, at higher pumping rates and wastewater volumes, as projected by the Tribe for about 2035, the contributing area for the Main Pumphouse wells do include particles that originated within the proposed lagoon footprint, albeit at low probabilities. That is, for a few of the thousands of simulations that represented a range of calibration-informed parameter covariances, some amount of infiltrated wastewater was captured by the Main Pumphouse wells under projected 2035 conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201032","collaboration":"Prepared in cooperation with the Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service","usgsCitation":"Juckem, P.F., and Fienen, M.N., 2020, Simulation of the probabilistic plume extent for a potential replacement wastewater-infiltration lagoon, and probabilistic contributing areas for supply wells for the Town of Lac du Flambeau, Vilas County, Wisconsin: U.S. Geological Survey Open-File Report 2020–1032, 10 p., https://doi.org/10.3133/ofr20201032.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-109305","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374398,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1032/coverthb.jpg"},{"id":374399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1032/ofr20201032.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1032"},{"id":374400,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z2YUW5","text":"USGS data release","description":"USGS Data Release","linkHelpText":"GFLOW model files used to generate probabilistic waste-water plume extents and contributing areas to supply wells for a proposed waste-water infil-tration lagoon scenario, Lac du Flambeau, Wisconsin"}],"country":"United States","state":"Wisconsin ","county":"Vilas County","city":"Lac du Flambeau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.92378234863281,\n              45.94386878224691\n            ],\n            [\n              -89.85013961791992,\n              45.94386878224691\n            ],\n            [\n              -89.85013961791992,\n              45.98408084285212\n            ],\n            [\n              -89.92378234863281,\n              45.98408084285212\n            ],\n            [\n              -89.92378234863281,\n              45.94386878224691\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/umid-water\" href=\"https://www.usgs.gov/centers/umid-water\">Upper Midwest Water Science Center</a><br>U.S. Geological Survey<br>8505 Research Way <br>Middleton, WI 55562<br></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Simulation of the Wastewater Plume Extent from Proposed Infiltration Lagoons</li><li>Simulation of Areas Contributing Recharge to the Main Pumphouse Wells</li><li>Assumptions and Limitations</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2020-05-07","noUsgsAuthors":false,"publicationDate":"2020-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","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":786106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":171511,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","middleInitial":"N.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786107,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209795,"text":"sir20205043 - 2020 - Chemical evaluation of water and gases collected from hydrothermal systems located in the central Aleutian arc, August 2015","interactions":[],"lastModifiedDate":"2020-05-07T19:58:50.668535","indexId":"sir20205043","displayToPublicDate":"2020-05-07T10:17:43","publicationYear":"2020","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":"2020-5043","displayTitle":"Chemical Evaluation of Water and Gases Collected from Hydrothermal Systems Located in the Central Aleutian Arc, August 2015","title":"Chemical evaluation of water and gases collected from hydrothermal systems located in the central Aleutian arc, August 2015","docAbstract":"<p>Five volcanic-hydrothermal systems in the central Aleutians Islands were sampled for water and gas geochemistry in 2015 to provide baseline data to help predict future volcanic unrest. Some areas had not been sampled in 20–30 years (Makushin volcano, Geyser Bight), and other areas had minimal to no prior sampling (Tana volcano and Fisher Caldera). The chemical and isotopic data of the waters show a wide variety of characteristics typical of hydrothermal settings. Stable isotopic analyses of the waters show no evidence for primary magmatic water, rather that waters have a meteoric origin that is variably influenced by boiling and evaporation processes. The carbon and helium isotopic analyses of gases suggest they contain a primary magmatic component typical of the upper mantle at most locations, and the CO<sub>2</sub>/S ratios show that these gases have been modified by interactions with groundwater along the flow paths. Some areas demonstrate stable compositions since the last sampling (for example, Akutan hydrothermal areas), with some being remarkably steady over very long periods (for example, Geyser Bight). Other areas show modifications because of either lower amounts of upwelling from hydrothermal sources or lower amounts of magmatic influence on the surface chemistry (for example, Upper Glacial valley of Makushin, an informally named valley leading south of the volcano toward Makushin Bay to the south). Finally, this report highlights that previously unsampled regions in the Aleutian Islands, such as Tana volcano and Fisher Caldera (the latter found to have one of the highest helium isotopic signatures ever measured in the Aleutian Islands), show evidence of ongoing subsurface magmatism that warrants continued investigation in terms of volcanic hazard.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205043","collaboration":"","usgsCitation":"Werner, C., Kern, C., and Kelly, P. K., 2020, Chemical evaluation of water and gases collected from hydrothermal systems located in the central Aleutian arc, August 2015: U.S. Geological Survey Scientific Investigations Report 2020–5043, 35 p., https://doi.org/10.3133/sir20205043.","productDescription":"Report: viii, 35 p.; 2 Tables","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118716","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":374537,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5043/coverthb.jpg"},{"id":374538,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5043/sir20205043.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":374539,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5043/sir20205043_table1.pdf","text":"Table 1","size":"200 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":374540,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5043/sir20205043_table2.pdf","text":"Table 2","size":"130 KB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Alaska","county":"","city":"","otherGeospatial":"Aleutian Islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -169.2333984375,\n              52.81604319154934\n            ],\n            [\n              -168.96972656249997,\n              52.669720383688166\n            ],\n            [\n              -168.4423828125,\n              52.8691297276852\n            ],\n            [\n              -168.28857421875,\n              53.08082737207479\n            ],\n            [\n              -167.62939453124997,\n              53.1335898292448\n            ],\n            [\n              -166.75048828125,\n              53.30462107510271\n            ],\n            [\n              -166.13525390625,\n              53.657661020298\n            ],\n            [\n              -164.99267578125,\n              54.00776876193478\n            ],\n            [\n              -164.11376953125,\n              54.23955053156177\n            ],\n            [\n              -164.33349609375,\n              54.67383096593114\n            ],\n            [\n              -164.68505859375,\n              54.88924640307589\n            ],\n            [\n              -165.41015625,\n              54.648412502316695\n            ],\n            [\n              -166.57470703125,\n              54.316523240258256\n            ],\n            [\n              -168.77197265625,\n              53.605544099238\n            ],\n            [\n              -169.2333984375,\n              52.81604319154934\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:tlmurray@usgs.gov\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"mailto:tlmurray@usgs.gov\">Director</a>,<br><a href=\"https://volcanoes.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://volcanoes.usgs.gov/\">Volcano Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>4210 University Drive<br>Anchorage, AK 99508</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Makushin Volcano</li><li>Akutan Volcano</li><li>Tana Volcano</li><li>Fisher Caldera</li><li>Geyser Bight Hydrothermal Area</li><li>Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-04-24","noUsgsAuthors":false,"publicationDate":"2020-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Werner, Cynthia A. cwerner@usgs.gov","contributorId":2540,"corporation":false,"usgs":true,"family":"Werner","given":"Cynthia","email":"cwerner@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":788058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":788059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":788060,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70216725,"text":"70216725 - 2020 - History and evolution of seepage meters for quantifying flow between groundwater and surface water: Part 1 – Freshwater settings","interactions":[],"lastModifiedDate":"2020-12-03T12:48:45.492738","indexId":"70216725","displayToPublicDate":"2020-05-06T17:01:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"History and evolution of seepage meters for quantifying flow between groundwater and surface water: Part 1 – Freshwater settings","docAbstract":"More than 75 years after its introduction, the seepage meter remains the only device for directly quantifying exchange across the sediment-water interface between groundwater and surface water.  This device, first presented in the literature in the 1940s, has been in a state of near-constant improvement and design change, necessitating a review of the history and evolution of the device and a description of current best-measurement practices.  Part 1 of this two-part review documents the evolution of seepage meters deployed in freshwater settings, including a listing of suggestions for best-measurement and deployment practices.  Part 2 covers the same scope for seepage meters deployed in marine settings.  Traditional seepage meters isolate a portion of the sediment bed; seepage commonly is determined by routing the volume of flow across that isolated interface to or from a submerged measurement bag over a known time interval.  The time-integrated volume is then divided by the bed area covered by the meter to obtain a seepage flux expressed in distance per time.  Both the instrument and the measurement are deceptively simple, leading some early users to question the viability of the measurement.  Numerous sources of error have been identified and addressed over the decades, resulting in large improvements in measurement consistency and accuracy.  Duration of each measurement depends on the seepage rate and can vary from minutes to days, leading to the erroneous and yet common assumption that seepage is relatively stable over time.  Designs that replace the measurement bag with a flowmeter eliminate bag-related errors and provide much finer temporal resolution.  Resulting data indicate seepage is highly variable in many settings and responds to numerous sub-daily processes, including evapotranspiration, rainfall, seiches and waves.  Combining direct measurements from seepage meters with other measurements, such as vertical hydraulic gradients and vertical temperature profiles, provides far better understanding of the processes that control exchange between groundwater and surface water.","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2020.103167","usgsCitation":"Rosenberry, D.O., Duque, C., and Lee, D.R., 2020, History and evolution of seepage meters for quantifying flow between groundwater and surface water: Part 1 – Freshwater settings: Earth-Science Reviews, v. 204, 103167, 13 p., https://doi.org/10.1016/j.earscirev.2020.103167.","productDescription":"103167, 13 p.","ipdsId":"IP-113122","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":380934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"204","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":805993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duque, Carlos 0000-0001-5833-8483","orcid":"https://orcid.org/0000-0001-5833-8483","contributorId":245349,"corporation":false,"usgs":false,"family":"Duque","given":"Carlos","email":"","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":805994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, David R.","contributorId":176828,"corporation":false,"usgs":false,"family":"Lee","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":805995,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70211980,"text":"70211980 - 2020 - Isolating anthropogenic wetland loss by concurrently tracking inundation and land cover disturbance across the Mid-Atlantic Region, U.S.","interactions":[],"lastModifiedDate":"2020-08-12T23:12:31.627153","indexId":"70211980","displayToPublicDate":"2020-05-05T18:02:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Isolating anthropogenic wetland loss by concurrently tracking inundation and land cover disturbance across the Mid-Atlantic Region, U.S.","docAbstract":"<p><span>Global trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from climate-driven variability in wetland extent. We present an approach to concurrently track land cover disturbance and inundation extent across the Mid-Atlantic region, United States, using the Landsat archive in Google Earth Engine. Disturbance was identified as a change in greenness, using a harmonic linear regression approach, or as a change in growing season brightness. Inundation extent was mapped using a modified version of the U.S. Geological Survey’s Dynamic Surface Water Extent (DSWE) algorithm. Annual (2015–2018) disturbance averaged 0.32% (1095 km</span><sup>2</sup><span>&nbsp;year</span><sup>-1</sup><span>) of the study area per year and was most common in forested areas. While inundation extent showed substantial interannual variability, the co-occurrence of disturbance and declines in inundation extent represented a minority of both change types, totaling 109 km</span><sup>2</sup><span>&nbsp;over the four-year period, and 186 km</span><sup>2</sup><span>, using the National Wetland Inventory dataset in place of the Landsat-derived inundation extent. When the annual products were evaluated with permitted wetland and stream fill points, 95% of the fill points were detected, with most found by the disturbance product (89%) and fewer found by the inundation decline product (25%). The results suggest that mapping inundation alone is unlikely to be adequate to find and track anthropogenic wetland loss. Alternatively, remotely tracking both disturbance and inundation can potentially focus efforts to protect, manage, and restore wetlands.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs12091464","usgsCitation":"Vanderhoof, M.K., Christensen, J.R., Beal, Y.G., DeVries, B., Lang, M.W., Hwang, N., Mazzarella, C., and Jones, J., 2020, Isolating anthropogenic wetland loss by concurrently tracking inundation and land cover disturbance across the Mid-Atlantic Region, U.S.: Remote Sensing, v. 12, no. 9, 1464, 29 p., https://doi.org/10.3390/rs12091464.","productDescription":"1464, 29 p.","ipdsId":"IP-116446","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35993,"text":"Hydrologic Investigations and Research Section","active":true,"usgs":true}],"links":[{"id":456841,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12091464","text":"Publisher Index Page"},{"id":437000,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ODILGN","text":"USGS data release","linkHelpText":"Tracking disturbance and inundation to identify wetland loss"},{"id":377459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, MarylandPennsylvania, Virginia, West Virginia","otherGeospatial":"Mid-Atlantic Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.70703125,\n              41.44272637767212\n            ],\n            [\n              -75.05859375,\n              41.77131167976407\n            ],\n            [\n              -75.41015624999999,\n              42.09822241118974\n            ],\n            [\n              -79.5849609375,\n              42.06560675405716\n            ],\n            [\n              -79.9365234375,\n              42.293564192170095\n            ],\n            [\n              -80.6396484375,\n              41.672911819602085\n            ],\n            [\n              -80.6396484375,\n              40.1452892956766\n            ],\n            [\n              -81.474609375,\n              39.232253141714885\n            ],\n            [\n              -81.8701171875,\n              38.92522904714054\n            ],\n            [\n              -82.5732421875,\n              38.44498466889473\n            ],\n            [\n              -82.2216796875,\n              37.43997405227057\n            ],\n            [\n              -83.5400390625,\n              36.63316209558658\n            ],\n            [\n              -76.2451171875,\n              36.56260003738545\n            ],\n            [\n              -73.47656249999999,\n              34.30714385628804\n            ],\n            [\n              -70.6640625,\n              35.137879119634185\n            ],\n            [\n              -72.333984375,\n              40.212440718286466\n            ],\n            [\n              -73.8720703125,\n              40.48038142908172\n            ],\n            [\n              -74.6630859375,\n              39.027718840211605\n            ],\n            [\n              -75.6298828125,\n              39.470125122358176\n            ],\n            [\n              -75.5859375,\n              39.90973623453719\n            ],\n            [\n              -74.92675781249999,\n              40.1452892956766\n            ],\n            [\n              -75.234375,\n              40.48038142908172\n            ],\n            [\n              -74.70703125,\n              41.44272637767212\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - 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Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":796087,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70209111,"text":"sir20205028 - 2020 - Simulation of discharge, water-surface elevations, and water temperatures for the St. Louis River estuary, Minnesota-Wisconsin, 2016–17","interactions":[],"lastModifiedDate":"2020-05-06T11:32:05.924687","indexId":"sir20205028","displayToPublicDate":"2020-05-05T14:18:55","publicationYear":"2020","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":"2020-5028","displayTitle":"Simulation of Discharge, Water-Surface Elevations, and Water Temperatures for the St. Louis River Estuary, Minnesota-Wisconsin, 2016–17","title":"Simulation of discharge, water-surface elevations, and water temperatures for the St. Louis River estuary, Minnesota-Wisconsin, 2016–17","docAbstract":"<p>The St. Louis River estuary is a large freshwater estuary, next to Duluth, Minnesota, that encompasses the headwaters of Lake Superior. The St. Louis River estuary is one of the most complex and compromised near-shore systems in the upper Great Lakes with a long history of environmental contamination caused by logging, mining, paper mills, and other heavy industrial activities. Presently (2020), a widely available, science-based assessment tool capable of evaluating ecosystem-level responses to remediation and restoration projects has not existed for the estuary. To address this need, the U.S. Geological Survey (USGS) built a predictive, mechanistic, three-dimensional hydrodynamic model for the estuary using the Environmental Fluid Dynamics Code framework. In the current version, the model can simulate continuous discharge, water-surface elevations, water temperature, and flow velocity, although the modular framework allows for future additions of water-quality modeling.</p><p>The model was calibrated using data collected from April 2016 through November 2016 and validated with data collected from April 2017 through November 2017. The four types of data used to evaluate model performance were water-surface elevations, discharge, water temperature, and flow velocities. Streamflow and temperature boundary condition data included a mixture of USGS streamgage data, Minnesota Department of Natural Resources gage data, and estimates derived from the gage data.</p><p>The model was able to simulate the water-surface elevations with generally good agreement between the simulated and measured values for both years at the daily time step. Specifically, the model was able to demonstrate excellent<br>agreement with the measured data with Nash-Sutcliffe efficiency coefficients greater than 0.8 for all three locations; however, the model was unable to produce hourly water-surface elevations with such accuracy for 2016–17.</p><p>Discharge was more dynamic than the water-surface elevations, both for the measured and simulated data. Generally, most of the discharge ranged from −650 to 1,200 cubic meters per second, but the constantly changing flux exiting the estuary into Lake Superior (positive flows) and entering the estuary from Lake Superior (negative flows) occurred throughout the year. Even upstream at the St. Louis River at Oliver, Wisconsin, gage (USGS station 0402403250), the effect of flows into the estuary from Lake Superior did occur, demonstrating the strong effect of the Lake Superior seiche on flows for the estuary.</p><p>From a performance standpoint, the model was able to simulate discharge with generally good agreement in both years, although the 2017 validation was better than the 2016 calibration period. For the daily Nash-Sutcliffe efficiency coefficients, the simulated values were 0.98, 0.62, 0.49, and 0.71 for the Oliver gage; the Superior Bay entry channel at Superior, Wisc., (USGS station 464226092005600); the Superior Bay Duluth Ship Canal at Duluth, Minn., (USGS station 464646092052900); and total entries (combination of the Superior entry and Duluth entry), respectively. For the hourly evaluation criteria, the model performed poorly, with Nash-Sutcliffe efficiency coefficients less than 0 for the two entries into Lake Superior; therefore, as a predictor of discharge at the hourly scale, the model performed worse than using the measured data average. Similar to discharge, the model was a good predictor of flow velocity at the daily time scale but had difficulty matching the measured data at the hourly scale. For discharge and flow velocity, matching at subdaily time steps for a system as complicated as the St. Louis River estuary is considered difficult because the match is highly sensitive to coordinating the exact measurement location to the simulated value.</p><p>The final calibration target was water temperature, calibrated for the Oliver gage and the Duluth entry. For calibration purposes, the Duluth entry was the more important water temperature target because the Oliver gage was more of an internal check on the model. The Nash-Sutcliffe efficiency coefficients for the Duluth entry were high; hourly Nash-Sutcliffe efficiency coefficients at the Duluth entry were either at or greater than 0.7 for both years, and daily values were 0.84 and 0.82 for 2016 and 2017, respectively.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205028","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Smith, E.A., Kiesling, R.L., and Hayter, E.J., 2020, Simulation of discharge, water-surface elevations, and water temperatures for the St. Louis River estuary, Minnesota-Wisconsin, 2016–17: U.S. Geological Survey Scientific Investigations Report 2020–5028, 31 p., https://doi.org/10.3133/sir20205028.","productDescription":"Report: viii, 31 p.; Data Release; Dataset","onlineOnly":"Y","ipdsId":"IP-113167","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":437002,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U1XXG0","text":"USGS data release","linkHelpText":"St. Louis River estuary (Minnesota-Wisconsin) EFDC model scenarios for velocity profiles around Munger Landing, selected years (2012-2019)"},{"id":374450,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5028/coverthb.jpg"},{"id":374451,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5028/sir20205028.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5028"},{"id":374452,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P990OUS6","text":"USGS data release","linkHelpText":"St. Louis River estuary (Minnesota-Wisconsin) EFDC hydrodynamic model for discharge and temperature simulations: 2016–17"},{"id":374455,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System—","linkHelpText":"USGS Water Data for the Nation"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"St. Louis River estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.548828125,\n              46.62869257083747\n            ],\n            [\n              -92.0050048828125,\n              46.62869257083747\n            ],\n            [\n              -92.0050048828125,\n              47.07199249565323\n            ],\n            [\n              -92.548828125,\n              47.07199249565323\n            ],\n            [\n              -92.548828125,\n              46.62869257083747\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/umid-water\" href=\"https://www.usgs.gov/centers/umid-water\">Upper Midwest Water Science Center</a> <br>U.S. Geological Survey <br>2280 Woodale Drive <br>Mounds View, MN 55112</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Model Calibration and Results</li><li>Model Limitations</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2020-05-05","noUsgsAuthors":false,"publicationDate":"2020-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Erik A. 0000-0001-8434-0798 easmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8434-0798","contributorId":1405,"corporation":false,"usgs":true,"family":"Smith","given":"Erik","email":"easmith@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayter, Earl J.","contributorId":223403,"corporation":false,"usgs":false,"family":"Hayter","given":"Earl","email":"","middleInitial":"J.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":784964,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70209891,"text":"ofr20201034 - 2020 - Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska","interactions":[],"lastModifiedDate":"2020-05-06T11:27:56.608874","indexId":"ofr20201034","displayToPublicDate":"2020-05-05T11:48:45","publicationYear":"2020","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":"2020-1034","displayTitle":"Prioritizing Habitats based on Abundance and Distribution of Molting Waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska","title":"Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska","docAbstract":"<p>The National Petroleum Reserve in Alaska (NPR-A) encompasses more than 9.5 million hectares of federally managed land on the Arctic Coastal Plain of northern Alaska, where it supports a diversity of wildlife, including millions of migratory birds. Within the NPR-A, Teshekpuk Lake and the surrounding area provide important habitat for migratory birds, including large numbers of waterfowl and shorebirds that use the area for breeding and molting. This area has been designated by the Bureau of Land Management as the Teshekpuk Lake Special Area (TLSA) and is estimated to host 22 percent of the entire Pacific black brant (<i>Branta bernicla nigricans</i>) population as it undergoes flightless wing molt. Additionally, numerous other waterfowl species use the area for breeding and molting, including greater white-fronted geese (<i>Anser albifrons</i>), snow geese (<i>Chen caerulescens</i>), Canada geese (<i>Branta hutchinsii</i>), and tundra swans (<i>Cygnus columbianus</i>). A data-derived procedure was developed to define important habitats based on recent distributions of molting birds. That procedure was used to identify areas that could be prioritized for exclusion from oil and gas development within a pre-defined “Goose Molting Area” in the TLSA. This analysis was requested by the Bureau of Land Management to provide information for the development of alternative scenarios for an updated NPR-A, Integrated Activity Plan/Environmental Impact Statement. Habitat selections were based on the population densities of Pacific black brant and Canada geese and pre-defined thresholds for the minimum fraction of the population contained within selected areas. Selections were based on long-term records of population density combined with global-positioning system data to reveal small-scale patterns of habitat use. The highest population density of the Pacific black brant was found along the Beaufort Sea coast on the eastern edge of the study area, whereas Canada geese were somewhat more widely distributed. Depending on the selection criteria and width of protective buffers placed around selected habitat units, 52–85 percent of the Goose Molting Area was identified as high-priority habitat. The effectiveness of this approach to habitat protection assumes that buffers around selected habitat units are wide enough to provide adequate protection from disturbance related to oil and gas development. This assumption remained a key source of uncertainty that could be addressed through additional study of disturbance effects on molting waterfowl.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201034","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Flint, P.L., Patil, V., Shults, B., and Thompson, S.J., 2020, Prioritizing habitats based on abundance and distribution of molting waterfowl in the Teshekpuk Lake Special Area of the National Petroleum Reserve, Alaska: U.S. Geological Survey Open-File Report 2020-1034, 16 p., https://doi.org/10.3133/ofr20201034.","productDescription":"Report: iv, 16 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115467","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":374468,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZGNRTB","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Habitat selection scenarios for molting waterfowl in the Goose Molting Area of the Teshekpuk Lake Special Area, for NPR-A Integrated Activity Plan/Environmental Impact Statement (2020)"},{"id":374466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1034/coverthb.jpg"},{"id":374467,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1034/ofr20201034.pdf","text":"Report","size":"3.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1034"}],"country":"United States","state":"Alaska","otherGeospatial":"National Petroleum Reserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154.59411621093747,\n              70.23346027955571\n          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99508</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Objectives</li><li>Description of Available Data</li><li>Methods</li><li>Molt-Unit Buffers</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>References Cited</li></ul>","publishedDate":"2020-05-05","noUsgsAuthors":false,"publicationDate":"2020-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":788496,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patil, Vijay 0000-0002-9357-194X vpatil@usgs.gov","orcid":"https://orcid.org/0000-0002-9357-194X","contributorId":224481,"corporation":false,"usgs":false,"family":"Patil","given":"Vijay","email":"vpatil@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":788497,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shults, Bradley","contributorId":224468,"corporation":false,"usgs":false,"family":"Shults","given":"Bradley","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":788498,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Sarah J. 0000-0002-5733-8198 sjthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-5733-8198","contributorId":5434,"corporation":false,"usgs":true,"family":"Thompson","given":"Sarah","email":"sjthompson@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science 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,{"id":70209896,"text":"70209896 - 2020 - Ringed seal (Pusa hispida) seasonal movements, diving, and haul-out behavior in the Beaufort, Chukchi, and Bering Seas (2011–2017)","interactions":[],"lastModifiedDate":"2020-07-09T14:55:32.503474","indexId":"70209896","displayToPublicDate":"2020-05-05T07:05:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Ringed seal (Pusa hispida) seasonal movements, diving, and haul-out behavior in the Beaufort, Chukchi, and Bering Seas (2011–2017)","docAbstract":"Continued Arctic warming and sea-ice loss will have important implications for the conservation of ringed seals, a highly ice-dependent species. A better understanding of their spatial ecology will help characterize emerging ecological trends and inform management decisions. We deployed satellite transmitters on ringed seals in the summers of 2011, 2014, and 2016 near Utqiaġvik (formerly Barrow), Alaska to monitor their movements, diving, and haul-out behavior. We present analyses of tracking and dive data provided by 17 seals that were tracked until at least January of the following year. Seals mostly ranged north of Utqiaġvik in the Beaufort and Chukchi Seas during summer before moving into the southern Chukchi and Bering Seas during winter. In all seasons, ringed seals occupied a diversity of habitats and spatial distributions; from near shore and localized, to far offshore and wide-ranging in drifting sea-ice. Continental shelf waters were occupied for >96% of tracking-days, during which repetitive-diving (suggestive of foraging) primarily to the seafloor was the most frequent activity. From mid-summer to early-fall, 12 seals made ~ one-week forays off-shelf to the deep Arctic Basin, most reaching the retreating pack-ice, where they spent most of their time hauled out. Diel activity patterns suggested greater allocation of foraging efforts to midday hours. Haul-out patterns were complementary, occurring mostly at night until April-May when midday hours were preferred. Ringed seals captured in 2011—concurrent with an unusual mortality event (UME) that affected all ice seal species—differed morphologically and behaviorally from seals captured in other years. Speculations about the physiology of molting and its role in energetics, habitat use, and behavior are discussed; along with possible evidence of purported ringed seal ecotypes.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.6302","usgsCitation":"Von Duyke, A.L., Douglas, D.C., Herreman, J.K., and Crawford, J.A., 2020, Ringed seal (Pusa hispida) seasonal movements, diving, and haul-out behavior in the Beaufort, Chukchi, and Bering Seas (2011–2017): Ecology and Evolution, v. 10, no. 12, p. 5595-5616, https://doi.org/10.1002/ece3.6302.","productDescription":"21 p.","startPage":"5595","endPage":"5616","ipdsId":"IP-102815","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":456850,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.6302","text":"Publisher Index Page"},{"id":374482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Chukchi Sea, Bering Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -141.50390625,\n              69.59589006237648\n            ],\n            [\n              -141.6796875,\n              70.67088107015755\n            ],\n            [\n              -149.94140625,\n              73.32785809840696\n            ],\n            [\n              -161.19140625,\n              73.02259157147301\n            ],\n            [\n              -168.57421875,\n              71.24435551310674\n            ],\n            [\n              -168.75,\n              64.92354174306496\n            ],\n            [\n              -170.68359375,\n              53.330872983017066\n            ],\n            [\n              -166.9921875,\n              51.6180165487737\n            ],\n            [\n              -158.73046875,\n              55.07836723201515\n            ],\n            [\n              -156.796875,\n              58.81374171570782\n            ],\n            [\n              -158.55468749999997,\n              63.31268278043484\n            ],\n            [\n              -161.89453125,\n              69.16255790810501\n            ],\n            [\n              -157.32421875,\n              71.13098770917023\n            ],\n            [\n              -141.50390625,\n              69.59589006237648\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Von Duyke, Andrew L.","contributorId":214208,"corporation":false,"usgs":false,"family":"Von Duyke","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":38995,"text":"North Slope Borough Department of Wildlife Management","active":true,"usgs":false}],"preferred":false,"id":788535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":788536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herreman, Jason K","contributorId":224482,"corporation":false,"usgs":false,"family":"Herreman","given":"Jason","email":"","middleInitial":"K","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":788537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crawford, Justin A.","contributorId":214225,"corporation":false,"usgs":false,"family":"Crawford","given":"Justin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":788538,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70212539,"text":"70212539 - 2020 - Inland fish and fisheries integral to achieving the Sustainable Development Goals","interactions":[],"lastModifiedDate":"2020-08-20T15:30:23.464971","indexId":"70212539","displayToPublicDate":"2020-05-04T10:25:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5791,"text":"Nature Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Inland fish and fisheries integral to achieving the Sustainable Development Goals","docAbstract":"<p><span>Inland fish provide food for billions and livelihoods for millions of people worldwide and are integral to effective freshwater ecosystem function, yet the recognition of these services is notably absent in development discussions and policies, such as the United Nations Sustainable Development Goals (SDGs). How might the SDGs be enhanced if inland fishery services were integrated into policies and development schemes? Here, we examine the relationships between inland fish, sustainable fisheries, and functioning freshwater systems and the targets of the SDGs. Our goal is to highlight synergies across the SDGs, particularly No Poverty (SDG 1), Zero Hunger (SDG 2), Clean Water and Sanitation (SDG 6), Responsible Consumption and Production (SDG 12) and Life on Land (SDG 15), that can be achieved with the inclusion of these overlooked inland fishery services.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41893-020-0517-6","usgsCitation":"Lynch, A., Elliott, V., Phang, S.C., Claussen, J.E., Harrison, I., Karen J. Murchie, E. Ashley Steel, and Gretchen L. Stokes, 2020, Inland fish and fisheries integral to achieving the Sustainable Development Goals: Nature Sustainability, v. 3, p. 579-587, https://doi.org/10.1038/s41893-020-0517-6.","productDescription":"9 p.","startPage":"579","endPage":"587","ipdsId":"IP-107688","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":467291,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://researchportal.port.ac.uk/portal/en/publications/inland-fish-and-fisheries-integral-to-achieving-the-sustainable-development-goals(c2017764-034f-4133-b092-61756a4409f8).html","text":"External Repository"},{"id":377691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2020-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":220490,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":796751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elliott, Vittoria","contributorId":238852,"corporation":false,"usgs":false,"family":"Elliott","given":"Vittoria","email":"","affiliations":[{"id":47802,"text":"WorldFish","active":true,"usgs":false}],"preferred":false,"id":796752,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phang, Sui C.","contributorId":238853,"corporation":false,"usgs":false,"family":"Phang","given":"Sui","email":"","middleInitial":"C.","affiliations":[{"id":47803,"text":"U. of Portsmouth","active":true,"usgs":false}],"preferred":false,"id":796753,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Claussen, Julie E.","contributorId":238854,"corporation":false,"usgs":false,"family":"Claussen","given":"Julie","email":"","middleInitial":"E.","affiliations":[{"id":47804,"text":"Fisheries Conservation Foundation","active":true,"usgs":false}],"preferred":false,"id":796754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrison, Ian","contributorId":238855,"corporation":false,"usgs":false,"family":"Harrison","given":"Ian","email":"","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":796755,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karen J. 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