{"pageNumber":"220","pageRowStart":"5475","pageSize":"25","recordCount":68807,"records":[{"id":70217119,"text":"70217119 - 2020 - Influence of sediment and stream transport on detecting a source of environmental DNA","interactions":[],"lastModifiedDate":"2021-01-07T12:40:38.448442","indexId":"70217119","displayToPublicDate":"2020-12-28T06:49:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Influence of sediment and stream transport on detecting a source of environmental DNA","docAbstract":"<p><span>Environmental DNA (eDNA) can be used for early detection, population estimations, and assessment of potential spread of invasive species, but questions remain about factors that influence eDNA detection results. Efforts are being made to understand how physical, chemical, and biological factors—settling, resuspension, dispersion, eDNA stability/decay—influence eDNA estimations and potentially population abundance. In a series of field and controlled mesocosm experiments, we examined the detection and accumulation of eDNA in sediment and water and the transport of eDNA in a small stream in the Lake Michigan watershed, using the invasive round goby fish (</span><i>Neogobius melanostomus</i><span>) as a DNA source. Experiment 1: caged fish (average n = 44) were placed in a stream devoid of round goby; water was collected over 24 hours along 120-m of stream, including a simultaneous sampling event at 7 distances from DNA source; stream monitoring continued for 24 hours after fish were removed. Experiment 2: round goby were placed in laboratory tanks; water and sediment were collected over 14 days and for another 150 days post-fish removal to calculate eDNA shedding and decay rates for water and sediment. For samples from both experiments, DNA was extracted, and qPCR targeted a cytochrome oxidase I gene (COI) fragment specific to round goby. Results indicated that eDNA accumulated and decayed more slowly in sediment than water. In the stream, DNA shedding was markedly lower than calculated in the laboratory, but models indicate eDNA could potentially travel long distances (up to 50 km) under certain circumstances. Collectively, these findings show that the interactive effects of ambient conditions (e.g., eDNA stability and decay, hydrology, settling-resuspension) are important to consider when developing comprehensive models. Results of this study can help resource managers target representative sites downstream of potential invasion sites, thereby maximizing resource use.</span></p>","language":"English","publisher":"Public Library of Science (PLoS)","doi":"10.1371/journal.pone.0244086","usgsCitation":"Nevers, M., Przybyla-Kelly, K., Shively, D., Morris, C.C., Dickey, J., and Byappanahalli, M., 2020, Influence of sediment and stream transport on detecting a source of environmental DNA: PLoS ONE, v. 15, no. 12, e0244086, 21 p., https://doi.org/10.1371/journal.pone.0244086.","productDescription":"e0244086, 21 p.","ipdsId":"IP-120509","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":454617,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0244086","text":"Publisher Index Page"},{"id":436691,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HI425V","text":"USGS data release","linkHelpText":"Environmental DNA detection and survival, influence of sediment, and stream transport in a Lake Michigan watershed, 2018"},{"id":381935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Przybyla-Kelly, Katarzyna 0000-0001-9168-3545 kprzybyla-kelly@usgs.gov","orcid":"https://orcid.org/0000-0001-9168-3545","contributorId":201534,"corporation":false,"usgs":true,"family":"Przybyla-Kelly","given":"Katarzyna","email":"kprzybyla-kelly@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shively, Dawn A.","contributorId":247309,"corporation":false,"usgs":false,"family":"Shively","given":"Dawn A.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":807646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morris, Charles C.","contributorId":201532,"corporation":false,"usgs":false,"family":"Morris","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":807647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickey, Joshua","contributorId":201536,"corporation":false,"usgs":false,"family":"Dickey","given":"Joshua","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":807648,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807649,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217713,"text":"70217713 - 2020 - Effects of fish populations on Pacific Loon (Gavia pacifica) and Yellow-billed Loon (G. adamsii) lake occupancy and chick production in northern Alaska","interactions":[],"lastModifiedDate":"2021-02-01T14:24:20.683608","indexId":"70217713","displayToPublicDate":"2020-12-27T07:50:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":894,"text":"Arctic","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of fish populations on Pacific Loon (<i>Gavia pacifica</i>) and Yellow-billed Loon (<i>G. adamsii</i>) lake occupancy and chick production in northern Alaska","title":"Effects of fish populations on Pacific Loon (Gavia pacifica) and Yellow-billed Loon (G. adamsii) lake occupancy and chick production in northern Alaska","docAbstract":"<div class=\"main_entry\"><div class=\"item abstract\"><p>Predator populations are vulnerable to changes in prey distribution or availability. With warming temperatures, lake ecosystems in the Arctic are predicted to change in terms of hydrologic flow, water levels, and connectivity with other lakes. We surveyed lakes in northern Alaska to understand how shifts in the distribution or availability of fish may affect the occupancy and breeding success of Pacific (<i>Gavia pacifica</i>) and Yellow-billed Loons (<i>G. adamsii</i>). We then modeled the influence of the presence and abundance of five fish species and the physical characteristics of lakes (e.g., hydrologic connectivity) on loon lake occupancy and chick production. The presence of Alaska blackfish (<i>Dallia pectoralis</i>) had a positive influence on Pacific Loon occupancy and chick production, which suggests that small-bodied fish species provide important prey for loon chicks. No characteristics of fish species abundance affected Yellow-billed Loon lake occupancy. Instead, Yellow-billed Loon occupancy was influenced by the physical characteristics of lakes that contribute to persistent fish populations, such as the size of the lake and the proportion of the lake that remained unfrozen over winter. Neither of these variables, however, influenced chick production. The probability of an unoccupied territory becoming occupied in a subsequent year by Yellow-billed Loons was low, and no loon chicks were successfully raised in territories that were previously unoccupied. In contrast, unoccupied territories had a much higher probability of becoming occupied by Pacific Loons, which suggests that Yellow-billed Loons have strict habitat requirements and suitable breeding lakes may be limited. Territories that were occupied had high probabilities of remaining occupied for both loon species.</p></div></div>","language":"English","publisher":"Arctic Institute of North America","doi":"10.14430/arctic71533","usgsCitation":"Uher-Koch, B.D., Wright, K.G., Uher-Koch, H.R., and Schmutz, J.A., 2020, Effects of fish populations on Pacific Loon (Gavia pacifica) and Yellow-billed Loon (G. adamsii) lake occupancy and chick production in northern Alaska: Arctic, v. 73, no. 4, p. 405-550, https://doi.org/10.14430/arctic71533.","productDescription":"145 p.","startPage":"405","endPage":"550","ipdsId":"IP-114479","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":454619,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14430/arctic71533","text":"Publisher Index Page"},{"id":436692,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z3AGXS","text":"USGS data release","linkHelpText":"Survey Data for Loon Occupancy in Freshwater Lakes, National Petroleum Reserve-Alaska, 2011-2014"},{"id":382787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -157.027587890625,\n              70.34831755984779\n            ],\n            [\n              -153.61083984374997,\n              70.34831755984779\n            ],\n            [\n              -153.61083984374997,\n              71.41317683396566\n            ],\n            [\n              -157.027587890625,\n              71.41317683396566\n            ],\n            [\n              -157.027587890625,\n              70.34831755984779\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"73","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":809343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Kenneth G.","contributorId":207044,"corporation":false,"usgs":false,"family":"Wright","given":"Kenneth","email":"","middleInitial":"G.","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":809344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Uher-Koch, Hannah R.","contributorId":248541,"corporation":false,"usgs":false,"family":"Uher-Koch","given":"Hannah","email":"","middleInitial":"R.","affiliations":[{"id":37194,"text":"University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":809345,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","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":809346,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70216994,"text":"tm11D3 - 2020 - Procedures and best practices for trigonometric leveling in the U.S. Geological Survey","interactions":[],"lastModifiedDate":"2020-12-24T21:23:26.391083","indexId":"tm11D3","displayToPublicDate":"2020-12-23T10:20:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"11-D3","displayTitle":"Procedures and Best Practices for Trigonometric Leveling in the U.S. Geological Survey","title":"Procedures and best practices for trigonometric leveling in the U.S. Geological Survey","docAbstract":"<p>With the advent of highly precise total stations and modern surveying instrumentation, trigonometric leveling has become a compelling alternative to conventional leveling methods for establishing vertical-control networks and for perpetuating a datum to field sites. Previous studies of trigonometric-leveling measurement uncertainty proclaim that first-, second-, and third-order accuracies may be achieved if strict leveling protocols are rigorously observed. Common field techniques to obtain quality results include averaging zenith angles and slope distances observed in direct and reverse instrument orientation (F1 and F2, respectively), multiple sets of reciprocal observations, quality meteorological observations to correct for the effects of atmospheric refraction, and electronic distance measurements that generally do not exceed 500 feet. In general, third-order specifications are required for differences between F1 and F2 zenith angles and slope distances; differences between redundant instrument-height measurements; section misclosure determined from reciprocal observations; and closure error for closed traverse. For F1 observations such as backsight check and check shots, the construction-grade specification is required for elevation differences between known and observed values.</p><p>Recommended specifications for trigonometric-leveling equipment include a total station instrument with an angular uncertainty specification less than or equal to plus or minus 5 arc-seconds equipped with an integrated electronic distance measurement device with an uncertainty specification of less than or equal to plus or minus 3 millimeters plus 3 parts per million. A paired data collector or integrated microprocessor should have the capability to average multiple sets of measurements in direct and reverse instrument orientation. Redundant and independent measurements by the survey crew and automated or manual reduction of slant heights to the vertical equivalent are recommended to obtain quality instrument heights. Horizontal and vertical collimation tests should be conducted daily during trigonometric-leveling surveys, and electronic distance-measurement instruments should be tested annually on calibrated baselines maintained by the National Geodetic Survey. Specifications that were developed by the National Geodetic Survey for geodetic leveling have been adapted by the U.S. Geological Survey (USGS) for the purpose of developing standards for trigonometric leveling, which are identified as USGS Trigonometric Level I (TL I), USGS Trigonometric Level II (TL II), USGS Trigonometric Level III (TL III), and USGS Trigonometric Level IV (TL IV). TL I, TL II, and TL III surveys have a combination of first, second, and third geodetic leveling specifications that have been modified for plane leveling. The TL III category also has specifications that are adapted from construction-grade standards, which are not recognized by the National Geodetic Survey for geodetic leveling. A TL IV survey represents a leveling approach that does not generally meet criteria of a TL I, TL II, or TL III survey.</p><p>Site conditions, such as highly variable topography, and the need for cost-effective, rapid, and accurate data collection in response to coastal or inland flooding have emphasized the need for an alternative approach to conventional leveling methods. Trigonometric leveling and the quality-assurance methods described in this manual will accommodate most site and environmental conditions, but measurement uncertainty is potentially variable and dependent on the survey method. Two types of closed traverse surveys have been identified as reliable methods to establish and perpetuate vertical control: the single-run loop traverse and double-run spur traverse. Leveling measurements for a double-run spur traverse are made in the forward direction from the origin to the destination and are then retraced along the same leveling route in the backward direction, from the destination to the origin. Every control point in a double-run spur traverse is occupied twice. Leveling measurements for a single-run loop traverse are made in the forward direction from the origin point to the destination, and then from the destination to the origin point, along a different leveling route. The only point that is redundantly occupied for the single-run loop traverse is the origin. An open traverse method is also considered an acceptable approach to establish and perpetuate vertical control if the foresight prism height is changed between measurement sets to ensure at least two independent observations. A modified version of leap-frog leveling is recommended for all traverse surveys because it reduces measurement uncertainty by forcing the surveying instrumentation into a level and centered condition over the ground point as the instrumentation is advanced to the objective. Sideshots are considered any radial measurement made from the total station that is not part of a traverse survey. F1 and F2 observations are recommended for sideshots measurements for projects that require precise elevations. Quality-assurance measurements made in F1 from the station to network-control points should be considered for surveys that require a high quantity of sideshots.</p><p>The accuracy of a trigonometric-leveling survey essentially depends on four components (1) the skill and experience of the surveyor, (2) the environmental or site conditions, (3) the surveying method, and (4) the quality of the surveying instrumentation. Although components one and two can sometimes be difficult to evaluate and be highly variable, the objective of this manual is to disseminate information needed to identify, maintain, and operate quality land-surveying instrumentation, and to document procedures and best practices for preparing and executing precision trigonometric-leveling surveys in the USGS.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm11D3","usgsCitation":"Noll, M.L., and Rydlund, P.H., 2020, Procedures and best practices for trigonometric leveling in the U.S. Geological Survey: U.S. Geological Survey Techniques and Methods, book 11, chap. D3, 94 p., https://doi.org/10.3133/tm11D3.","productDescription":"Report: vii, 93 p.; Appendix","numberOfPages":"94","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-108800","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":381587,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/11d3/coverthb.jpg"},{"id":381588,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/11d3/tm11d3.pdf","text":"Report","size":"6.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 11-D3"},{"id":381589,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/11d3/tm11d3_appendix1.pdf","text":"Appendix 1","size":"207 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Standard Field Form for Running Trigonometric Levels"}],"contact":"<p><a href=\"mailto:dc_ny@usgs.gov\" data-mce-href=\"mailto:dc_ny@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ny-water\" data-mce-href=\"https://www.usgs.gov/centers/ny-water\">New York Water Science Center</a><br>U.S. Geological Survey<br>425 Jordan Road<br>Troy, NY 12180–8349</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Trigonometric-Leveling Equipment</li><li>Preparing for Trigonometric Leveling</li><li>Sources of Measurement Uncertainty for Trigonometric Leveling</li><li>Trigonometric Leveling</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Standard Field Form for Running Trigonometric Levels</li><li>Glossary</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-12-23","noUsgsAuthors":false,"publicationDate":"2020-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Noll, Michael L. 0000-0003-2050-3134 mnoll@usgs.gov","orcid":"https://orcid.org/0000-0003-2050-3134","contributorId":4652,"corporation":false,"usgs":true,"family":"Noll","given":"Michael","email":"mnoll@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807195,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70219429,"text":"70219429 - 2020 - Forest management under megadrought: Urgent actions needed at finer-scale and higher intensity","interactions":[],"lastModifiedDate":"2021-04-05T13:05:06.636393","indexId":"70219429","displayToPublicDate":"2020-12-23T08:03:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"title":"Forest management under megadrought: Urgent actions needed at finer-scale and higher intensity","docAbstract":"<div class=\"JournalAbstract\"><p>Drought and warming increasingly are causing widespread tree die-offs and extreme wildfires. Forest managers are struggling to improve anticipatory forest management practices given more frequent, extensive, and severe wildfire and tree die-off events triggered by “hotter drought”—drought under warmer than historical conditions. Of even greater concern is the increasing probability of multi-year droughts, or “megadroughts”—persistent droughts that span years to decades, and that under a still-warming climate, will also be hotter than historical norms. Megadroughts under warmer temperatures are disconcerting because of their potential to trigger more severe forest die-off, fire cycles, pathogens, and insect outbreaks. In this Perspective, we identify potential anticipatory and/or concurrent options for non-timber forest management actions under megadrought, which by necessity are focused more at finer spatial scales such as the stand level using higher-intensity management. These management actions build on silvicultural practices focused on growth and yield (but not harvest). Current management options that can be focused at finer scales include key silvicultural practices: selective thinning; use of carefully selected forward-thinking seed mixes; site contouring; vegetation and pest management; soil erosion control; and fire management. For the extreme challenges posed by megadroughts, management will necessarily focus even more on finer-scale, higher-intensity actions for priority locations such as fostering stand refugia; assisted stand recovery via soil amendments; enhanced root development; deep soil water retention; and shallow water impoundments. Drought-induced forest die-off from megadrought likely will lead to fundamental changes in the structure, function, and composition of forest stands and the ecosystem services they provide.</p></div>","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffgc.2020.502669","usgsCitation":"Field, J.P., Breshears, D.D., Bradford, J., Law, D.J., Feng, X., and Allen, C.D., 2020, Forest management under megadrought: Urgent actions needed at finer-scale and higher intensity: Frontiers in Forests and Global Change, v. 3, 502669, 10 p., https://doi.org/10.3389/ffgc.2020.502669.","productDescription":"502669, 10 p.","ipdsId":"IP-124850","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454622,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2020.502669","text":"Publisher Index Page"},{"id":384864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2020-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Field, Jason P.","contributorId":216389,"corporation":false,"usgs":false,"family":"Field","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":39400,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":813526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breshears, David D.","contributorId":51620,"corporation":false,"usgs":false,"family":"Breshears","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":813527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":813528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Law, Darin J.","contributorId":216390,"corporation":false,"usgs":false,"family":"Law","given":"Darin","email":"","middleInitial":"J.","affiliations":[{"id":39400,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":813529,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feng, Xiaohui","contributorId":196416,"corporation":false,"usgs":false,"family":"Feng","given":"Xiaohui","email":"","affiliations":[],"preferred":false,"id":813530,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":813531,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70216973,"text":"sir20205127 - 2020 - Hydrogeology and groundwater geochemistry of till confining units and confined aquifers in glacial deposits near Litchfield, Cromwell, Akeley, and Olivia, Minnesota, 2014–18","interactions":[],"lastModifiedDate":"2020-12-22T22:54:07.952364","indexId":"sir20205127","displayToPublicDate":"2020-12-22T10:12:27","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":"2020-5127","displayTitle":"Hydrogeology and Groundwater Geochemistry of Till Confining Units and Confined Aquifers in Glacial Deposits near Litchfield, Cromwell, Akeley, and Olivia, Minnesota, 2014–18","title":"Hydrogeology and groundwater geochemistry of till confining units and confined aquifers in glacial deposits near Litchfield, Cromwell, Akeley, and Olivia, Minnesota, 2014–18","docAbstract":"<p>Confined (or buried) aquifers of glacial origin overlain by till confining units provide drinking water to hundreds of thousands of Minnesota residents. The sustainability of these groundwater resources is not well understood because hydraulic properties of till that control vertical groundwater fluxes (leakage) to underlying aquifers are largely unknown. The U.S. Geological Survey, Iowa State University, Minnesota Geological Survey, and Minnesota Department of Health investigated hydraulic properties and groundwater flow through till confining units using field studies and heuristic MODFLOW simulations. Till confining units in the following late-Wisconsinan stratigraphic units (with locations in parentheses) were characterized: Des Moines lobe till of the New Ulm Formation (Litchfield, Minnesota), Superior lobe till of the Cromwell and Aitkin Formations (Cromwell, Minn.), and Wadena lobe till of the Hewitt Formation (hydrogeology field camp [HFC] near Akeley, Minn.). Pre-Illinoian till of the Good Thunder formation (Olivia, Minn.) was also characterized.</p><p>Hydraulic and geochemical field data were collected from sediment cores and a series of five piezometer nests. Each nest consisted of five to eight piezometers screened at short vertical intervals in hydrostratigraphic units including (if present) surficial aquifers, till confining units, confined/buried aquifers, and underlying bedrock. Till hydraulic conductivity was estimated from slug tests (horizontal [<i>K<sub>h</sub></i>]) and constant-rate aquifer tests in the confined aquifer (vertical [<i>K<sub>v</sub></i>]). Travel times through the till were evaluated with Darcy’s law and stable isotope concentrations. A series of heuristic MODFLOW simulations were used to evaluate groundwater fluxes through till across the range of till hydraulic properties and pumping rates observed at the field sites.</p><p>The field data demonstrated variability in hydraulic properties between and within till stratigraphic units horizontally and vertically. The variability in hydraulic properties within and between sites resulted in substantial differences in groundwater flux through till. A conceptual understanding that emerges from the vertical till profiles is that they are not homogeneous hydrostratigraphic units with uniform properties; rather, each vertical sequence is a heterogeneous mixture of glacial sediment with differing abilities to transmit water.</p><p>Till thicknesses varied from 60 to 166 feet, and till textures ranged from a sandy loam (Hewitt Formation, HFC site) to a silt loam/clay loam (Good Thunder formation, Olivia site). Till Kh varied by one to three orders of magnitude within each piezometer nest. Four piezometer nests had downward hydraulic gradients ranging from 0.04 to 0.56, and one nest had a slight upward hydraulic gradient of 0.02. The Cromwell, HFC, and Litchfield 1 sites were examples of “leaky” tills with high Kv (0.001 to 1.1 feet per day [ft/d]) and geometric mean Kh (0.03 to 0.07 ft/d) and extensive vertical hydraulic connectivity between the confined aquifer and the overlying till. Estimated groundwater travel times through these sites ranged from 1 to 81 years, and two of these sites had tritium throughout their till profiles. The tills at the other two sites, Olivia and Litchfield 2, were effective confining units that had low Kv (0.001 to 0.0005 ft/d) and geometric mean Kh (0.0002 to 0.004 ft/d). The till piezometers at these sites had no drawdown response to short-term (up to 10 hours for Olivia and up to 5 days for Litchfield) high-capacity pumping from the confined aquifer. Estimated groundwater travel times through the tills at these sites ranged from 165 to nearly 1,800 years, and tritium was only detected in the upper one-third of these till profiles. Across all sites, the till vertical anisotropy (ratio of <i>K<sub>h</sub></i> to <i>K<sub>v</sub></i>) ranged by four orders of magnitude from 0.05 at the Cromwell nest to 70 at the Litchfield 1 nest. Stable isotopes of oxygen and hydrogen indicate that groundwater throughout all five till profiles is younger than the last glacial advance into Minnesota at about 11,000 years ago.</p><p>The heuristic modeling demonstrated that, for understanding sustainability of groundwater pumping from confined aquifers, knowledge of till hydraulic properties is just as important as knowledge of aquifer hydraulic properties. Substantial differences in groundwater fluxes into and through till were observed across hydrogeologic settings representative of the field sites. Over long periods of time (hundreds of years), pumping-induced hydraulic gradients are established in confined aquifer systems and, even in low hydraulic conductivity tills, these pumping-induced hydraulic gradients increase leakage into and through till compared to ambient conditions.</p><p>In conclusion, groundwater flowing vertically downward through till confining units (leakage) replenishes water pumped from confined aquifers. Till hydraulic properties, such as those presented in this report, provide important information that can be used to quantify leakage rates through till. Till hydraulic properties are variable over short distances and profoundly affect leakage rates, demonstrating the importance of site-specific till hydraulic data for evaluating the sustainability of groundwater withdrawals from confined aquifers.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205127","collaboration":"Prepared in cooperation with the Legislative-Citizen Commission on Minnesota Resources and in collaboration with Iowa State University and the Minnesota Department of Health","usgsCitation":"Trost, J.J., Maher, A., Simpkins, W.W., Witt, A.N., Stark, J.R., Blum, J., and Berg, A.M., 2020, Hydrogeology and groundwater geochemistry of till confining units and confined aquifers in glacial deposits near Litchfield, Cromwell, Akeley, and Olivia, Minnesota, 2014–18: U.S. Geological Survey Scientific Investigations Report 2020–5127, 80 p., https://doi.org/10.3133/sir20205127.","productDescription":"Report: ix, 80 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and slug test analysis results from till confining units and confined aquifers in glacial deposits near Akeley, Cromwell, Litchfield, and Olivia, Minnesota, 2015–2018"},{"id":381537,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KOI6T3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Heuristic MODFLOW models used to evaluate the effects of pumping groundwater from confined aquifers overlain by till confining units"}],"country":"United States","state":"Minnesota","city":"Akeley, Cromwell, Litchfield, Olivia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.5758056640625,\n              45.084672408703945\n            ],\n            [\n              -94.48173522949219,\n              45.084672408703945\n   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Information</li><li>Appendix 3 Quality Assurance for Water-Quality Samples</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-12-22","noUsgsAuthors":false,"publicationDate":"2020-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","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":807134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maher, Anna-Turi 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R.","contributorId":245836,"corporation":false,"usgs":false,"family":"Stark","given":"James R.","affiliations":[],"preferred":false,"id":807138,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blum, Justin","contributorId":245835,"corporation":false,"usgs":false,"family":"Blum","given":"Justin","email":"","affiliations":[],"preferred":false,"id":807139,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Berg, Andrew M. 0000-0001-9312-240X aberg@usgs.gov","orcid":"https://orcid.org/0000-0001-9312-240X","contributorId":5642,"corporation":false,"usgs":true,"family":"Berg","given":"Andrew","email":"aberg@usgs.gov","middleInitial":"M.","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":807140,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70216967,"text":"fs20203066 - 2020 - Maine and Landsat","interactions":[],"lastModifiedDate":"2026-02-04T20:22:00.663948","indexId":"fs20203066","displayToPublicDate":"2020-12-21T17:11:26","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":"2020-3066","displayTitle":"Maine and Landsat","title":"Maine and Landsat","docAbstract":"<p>Maine is a place of rocky coastlines, of rich maritime history symbolized by lighthouses dotting the ocean bluffs, and of wondrous nature areas like the granite and spruce islands of Acadia National Park. But Maine is a place of changes, too. Climate variability has brought the state heavier and more frequent rainstorms. Summers are hotter and drier. With sea levels rising, severe storms increasingly cause floods that damage property and infrastructure. In the coming decades, Landsat satellite systems can be valuable tools in monitoring those changes and their effects on the land and in the water.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203066","usgsCitation":"U.S. Geological Survey, 2020, Maine and Landsat (ver. 1.2, May 2023): U.S. Geological Survey Fact Sheet 2020–3066, 2 p., https://doi.org/10.3133/fs20203066.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-123291","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":381524,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3066/coverthb4.jpg"},{"id":402769,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2020/3066/fs20203066.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":402771,"rank":4,"type":{"id":25,"text":"Version 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 \"}}]}","edition":"Version 1.0: December 21, 2020; Version 1.1: July 1, 2022; Version 1.2: May 16, 2023","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a>&nbsp;<br>U.S. Geological Survey&nbsp;<br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Forest Health and Changes</li><li>Fishing and Farms</li><li>Coastlines and Wetlands</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-12-21","revisedDate":"2023-05-16","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":210377,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":807116,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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 \"}}]}","edition":"Version 1.0: December 21, 2020; Version 1.1: October 17, 2022; Version 1.2: November 26, 2024","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a>&nbsp;<br>U.S. Geological Survey&nbsp;<br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Smart Urban Development</li><li>Water-Quality Monitoring</li><li>Precision Agriculture</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-12-21","revisedDate":"2024-11-26","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128215,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":807087,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70216977,"text":"fs20203053 - 2020 - Water resources of Red River Parish, Louisiana","interactions":[],"lastModifiedDate":"2020-12-22T12:40:42.536859","indexId":"fs20203053","displayToPublicDate":"2020-12-21T17:09:07","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":"2020-3053","displayTitle":"Water Resources of Red River Parish, Louisiana","title":"Water resources of Red River Parish, Louisiana","docAbstract":"<p>Information concerning the availability, use, and quality of water in Red River Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 5.76 million gallons per day (Mgal/d) of water were withdrawn in Red River Parish: about 4.23 Mgal/d from groundwater sources and 1.54 Mgal/d from surface-water sources. Withdrawals for agricultural use, composed of general irrigation, rice irrigation, and livestock uses, accounted for about 72 percent (4.15 Mgal/d) of the total water withdrawn. Other categories of use included public supply (about 18 percent of the total water withdrawn, or 1.03 Mgal/d), industry (about 7 percent, or 0.39 Mgal/d), and rural domestic (about 4 percent, or 0.20 Mgal/d). Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 1975 at more than 7.3 Mgal/d.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203053","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Robinson, A.L., and White, V.E., 2020, Water resources of Red River Parish, Louisiana: U.S. Geological Survey Fact Sheet 2020–3053, 6 p., https://doi.org/10.3133/fs20203053.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-103355","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":381549,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3053/coverthb.jpg"},{"id":381550,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3053/fs20203053.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3053"},{"id":381551,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78051VM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water withdrawals by source and category in Louisiana Parishes, 2014–2015"}],"country":"United States","state":"Louisiana","county":"Red River Parish","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-93.6149,32.2376],[-93.5347,32.2377],[-93.5325,32.2378],[-93.4713,32.237],[-93.4355,32.2358],[-93.4333,32.2359],[-93.4284,32.236],[-93.4057,32.2363],[-93.3959,32.236],[-93.3558,32.2363],[-93.3417,32.236],[-93.2475,32.2362],[-93.2139,32.2358],[-93.2127,32.2308],[-93.212,32.2258],[-93.213,32.2207],[-93.2123,32.2144],[-93.2116,32.2066],[-93.2097,32.1934],[-93.202,32.1885],[-93.1987,32.1872],[-93.1954,32.1832],[-93.1937,32.18],[-93.1924,32.17],[-93.1917,32.1632],[-93.1889,32.1568],[-93.186,32.1487],[-93.1744,32.1365],[-93.1643,32.1203],[-93.1576,32.1122],[-93.1565,32.1076],[-93.1526,32.1049],[-93.1563,32.0976],[-93.1589,32.0957],[-93.1636,32.0865],[-93.1608,32.0816],[-93.1521,32.0785],[-93.1444,32.0713],[-93.1393,32.0614],[-93.138,32.0518],[-93.1422,32.0449],[-93.1432,32.0399],[-93.1469,32.0375],[-93.1506,32.0343],[-93.1554,32.0278],[-93.1557,32.0201],[-93.1556,32.0146],[-93.1582,32.0082],[-93.1522,32.0037],[-93.146,31.9942],[-93.1383,31.9866],[-93.1306,31.9803],[-93.1213,31.9727],[-93.2131,31.9732],[-93.2342,31.9733],[-93.2385,31.9728],[-93.2389,31.9682],[-93.2403,31.9071],[-93.2452,31.9084],[-93.2479,31.9101],[-93.2523,31.911],[-93.2592,31.91],[-93.2639,31.8989],[-93.2713,31.8938],[-93.2777,31.891],[-93.2799,31.8909],[-93.2852,31.8895],[-93.2933,31.8898],[-93.2993,31.8925],[-93.301,31.8956],[-93.3075,31.8964],[-93.3187,31.889],[-93.3208,31.8885],[-93.3317,31.8924],[-93.3415,31.8954],[-93.3507,31.8989],[-93.3508,31.9016],[-93.3526,31.9103],[-93.3527,31.9144],[-93.3528,31.919],[-93.3548,31.9321],[-93.3532,31.9354],[-93.3554,31.9367],[-93.3679,31.942],[-93.3696,31.9433],[-93.3692,31.9501],[-93.3748,31.9569],[-93.3727,31.962],[-93.3766,31.966],[-93.3803,31.965],[-93.3814,31.9659],[-93.4034,31.981],[-93.4079,31.9887],[-93.4139,31.9891],[-93.4175,31.9831],[-93.4229,31.9839],[-93.424,31.9853],[-93.4231,31.9903],[-93.4328,31.9897],[-93.4376,31.9887],[-93.4431,31.9904],[-93.4437,31.994],[-93.4476,31.999],[-93.452,32.0003],[-93.4558,32.0034],[-93.4597,32.0061],[-93.4609,32.0111],[-93.4621,32.017],[-93.4638,32.022],[-93.4672,32.026],[-93.4769,32.0272],[-93.4802,32.0299],[-93.4814,32.0335],[-93.479,32.0472],[-93.4798,32.0568],[-93.4848,32.0604],[-93.4896,32.0603],[-93.5049,32.0641],[-93.5071,32.0673],[-93.5068,32.075],[-93.5139,32.0804],[-93.5135,32.0858],[-93.525,32.0911],[-93.53,32.0969],[-93.541,32.104],[-93.5411,32.1068],[-93.5384,32.1082],[-93.5369,32.1132],[-93.5295,32.1166],[-93.5227,32.1258],[-93.5129,32.1264],[-93.5098,32.1297],[-93.5099,32.1333],[-93.521,32.145],[-93.5225,32.1614],[-93.5215,32.1669],[-93.5249,32.1704],[-93.5261,32.1763],[-93.5312,32.1854],[-93.5379,32.1926],[-93.5525,32.1936],[-93.5547,32.1927],[-93.5672,32.1952],[-93.5809,32.2018],[-93.594,32.2061],[-93.5985,32.2124],[-93.5969,32.2147],[-93.5982,32.2215],[-93.6049,32.2269],[-93.6061,32.2319],[-93.6132,32.2349],[-93.6149,32.2376]]]},\"properties\":{\"name\":\"Red River\",\"state\":\"LA\"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/lmg-water/\" data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>3535 S. Sherwood Forest Blvd., Suite 120 <br>Baton Rouge, LA 70816</p>","tableOfContents":"<ul><li>Introduction</li><li>Groundwater Resources</li><li>Surface-Water Resources</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-12-21","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Angela L. 0000-0001-5845-4847","orcid":"https://orcid.org/0000-0001-5845-4847","contributorId":206329,"corporation":false,"usgs":true,"family":"Robinson","given":"Angela","email":"","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807145,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216978,"text":"fs20203052 - 2020 - Water resources of Bienville Parish, Louisiana","interactions":[],"lastModifiedDate":"2020-12-22T12:43:18.405991","indexId":"fs20203052","displayToPublicDate":"2020-12-21T17:08:47","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":"2020-3052","displayTitle":"Water Resources of Bienville Parish, Louisiana","title":"Water resources of Bienville Parish, Louisiana","docAbstract":"<p>Information concerning the availability, use, and quality of water in Bienville Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 13.03 million gallons per day (Mgal/d) of water were withdrawn in Bienville Parish, including about 12.88 Mgal/d from groundwater sources and 0.15 Mgal/d from surface-water sources. Withdrawals for industrial use accounted for about 78 percent (10.18 Mgal/d) of the total water withdrawn. Other categories of use included public supply, which accounted for about 18 percent of the total water withdrawn (2.33 Mgal/d); agriculture, composed of general irrigation and livestock, which accounted for about 1 percent (0.18 Mgal/d); and rural domestic (0.33 Mgal/d), which accounted for about 2&nbsp;percent. Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 1995 at more than 17 Mgal/d.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203052","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Robinson, A.L., and White, V.E., 2020, Water resources of Bienville Parish, Louisiana: U.S. Geological Survey Fact Sheet 2020–3052, 6 p., https://doi.org/10.3133/fs20203052.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-103354","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":381552,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3052/coverthb.jpg"},{"id":381553,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3052/fs20203052.pdf","text":"Report","size":"875 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3052"},{"id":381554,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78051VM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water withdrawals by source and category in Louisiana Parishes, 2014–2015"}],"country":"United States","state":"Louisiana","county":"Bienville Parish","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.8807,32.5853],[-92.8779,32.5202],[-92.8795,32.4541],[-92.8078,32.4545],[-92.7768,32.4548],[-92.7752,32.3865],[-92.7749,32.371],[-92.7746,32.3181],[-92.7739,32.3077],[-92.7732,32.2648],[-92.7751,32.2429],[-92.7739,32.2366],[-92.7824,32.2283],[-92.7861,32.2191],[-92.7963,32.214],[-92.8011,32.2085],[-92.8004,32.1984],[-92.7986,32.1916],[-92.8018,32.1866],[-92.8038,32.1783],[-92.8081,32.1742],[-92.8177,32.165],[-92.8198,32.1604],[-92.8207,32.149],[-92.9376,32.148],[-92.9407,32.148],[-93.0837,32.1488],[-93.186,32.1487],[-93.1889,32.1568],[-93.1917,32.1632],[-93.1924,32.17],[-93.1937,32.18],[-93.1954,32.1832],[-93.1987,32.1872],[-93.202,32.1885],[-93.2097,32.1934],[-93.2116,32.2066],[-93.2123,32.2144],[-93.213,32.2207],[-93.212,32.2258],[-93.2127,32.2308],[-93.2139,32.2358],[-93.2475,32.2362],[-93.3417,32.236],[-93.3558,32.2363],[-93.3959,32.236],[-93.4057,32.2363],[-93.4284,32.236],[-93.4269,32.2387],[-93.4193,32.2393],[-93.4125,32.2485],[-93.4111,32.2599],[-93.413,32.2713],[-93.4126,32.2763],[-93.4101,32.2832],[-93.4155,32.2854],[-93.4204,32.284],[-93.4226,32.2871],[-93.4228,32.2944],[-93.4302,32.3089],[-93.4244,32.314],[-93.4213,32.3227],[-93.4111,32.3493],[-93.4037,32.3572],[-93.4023,32.3649],[-93.4056,32.3703],[-93.4176,32.3729],[-93.4248,32.3773],[-93.4288,32.3854],[-93.4273,32.3923],[-93.4215,32.3997],[-93.4162,32.4016],[-93.3981,32.3951],[-93.3916,32.3947],[-93.3729,32.4105],[-93.324,32.4104],[-93.3186,32.4101],[-93.2811,32.4102],[-93.242,32.4099],[-93.2371,32.41],[-93.2366,32.4114],[-93.237,32.4273],[-93.2371,32.4346],[-93.2371,32.4555],[-93.2083,32.4555],[-93.1485,32.4564],[-93.1491,32.4587],[-93.1518,32.4595],[-93.1514,32.4627],[-93.1503,32.465],[-93.1504,32.4669],[-93.1488,32.4705],[-93.1466,32.4715],[-93.1473,32.4783],[-93.1474,32.4801],[-93.1533,32.48],[-93.1561,32.4823],[-93.1535,32.4887],[-93.1558,32.4932],[-93.1586,32.4982],[-93.1608,32.5],[-93.1642,32.5036],[-93.1671,32.5117],[-93.1666,32.5158],[-93.1695,32.5254],[-93.1714,32.5354],[-93.1721,32.5431],[-93.1684,32.5522],[-93.1696,32.5563],[-93.1724,32.5577],[-93.18,32.5863],[-93.063,32.5852],[-92.9998,32.5838],[-92.8965,32.5846],[-92.8807,32.5853]]]},\"properties\":{\"name\":\"Bienville\",\"state\":\"LA\"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/lmg-water/\" data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>3535 S. Sherwood Forest Blvd., Suite 120 <br>Baton Rouge, LA 70816</p>","tableOfContents":"<ul><li>Introduction</li><li>Groundwater Resources</li><li>Surface-Water Resources</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-12-21","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Angela L. 0000-0001-5845-4847","orcid":"https://orcid.org/0000-0001-5845-4847","contributorId":206329,"corporation":false,"usgs":true,"family":"Robinson","given":"Angela","email":"","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807150,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208328,"text":"sir20205007 - 2020 - Optimization assessment of a groundwater-level observation network in the Middle Rio Grande Basin, New Mexico","interactions":[],"lastModifiedDate":"2022-04-25T21:17:00.184426","indexId":"sir20205007","displayToPublicDate":"2020-12-21T08:28:55","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":"2020-5007","displayTitle":"Optimization Assessment of a Groundwater-Level Observation Network in the Middle Rio Grande Basin, New Mexico","title":"Optimization assessment of a groundwater-level observation network in the Middle Rio Grande Basin, New Mexico","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Albuquerque Bernalillo County Water Utility Authority (ABCWUA), measures groundwater levels continuously (hourly) and discretely (semiannually and annually) at a network of wells and piezometers (hereafter called the observation network) within the Middle Rio Grande Basin in central New Mexico. Groundwater levels that are measured in this observation network provide a long-term hydrologic dataset that is heavily relied upon to make water management decisions. The desire to upgrade and perform maintenance on this observation network initiated this study, which assesses the spatial and temporal importance of measurements towards optimization of monitoring the observation network to reduce or redirect monitoring costs. This report describes the methods and results of the optimization assessment of this observation network, which included separate spatial and temporal methodologies and an evaluation using principal component analysis (PCA).</p><p>Results from the spatial optimization assessment can be used to help identify observation network sites that do not significantly affect the generation of winter groundwater-elevation contour maps of the production zone. Results from the temporal optimization assessment and PCA can also be consulted when deciding which sites to remove from the network, especially for sites that are monitored more frequently than annually. Results from the temporal optimization assessment can be used to inform the minimum monitoring frequency at the observation network required to capture the trends shown in higher frequency monitoring. The PCA results distinguish spatially distributed characteristic water-level trends that can inform the management decisions that are made when using the spatial and temporal optimization assessment results. Reducing the temporal frequency or spatial density of monitoring is ultimately a management decision that depends on the amount of data loss or degradation that is deemed acceptable while still meeting the network objectives of the ABCWUA. This study can also serve as a starting point to a data gap analysis of local aquifer characteristics and help guide enhanced observation network design as needs arise or in advance of future water management decisions.</p><p>The results of the spatial optimization assessment indicate that as many as about 20 specified sites can be removed from the observation network with a relatively small loss in the ability to represent the kriged groundwater-elevation surfaces of the production zone that were generated by using median groundwater elevations for two periods: the 2001 time interval and 2015 time interval. This analysis also demonstrated the importance of wells at the margin of the study area and in areas where there are large hydrologic gradients. At many of the 47 hourly monitored sites analyzed in the temporal optimization assessment, temporal trends were well represented for at least one of the reduced monitoring frequencies tested, indicating that a reduced frequency may be sufficient to adequately characterize seasonal and long-term trends. PCA and k-means clustering analysis of the 15 hourly monitored sites that are screened within the production zone indicate that the sites can be categorized into four groups, or clusters, of differing groundwater-level hydrograph characteristics. Except for one cluster, all of the clusters have the potential to be well represented by fewer index monitoring sites.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205007","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Ritchie, A.B., and Pepin, J.D., 2020, Optimization assessment of a groundwater-level observation network in the Middle Rio Grande Basin, New Mexico (ver. 2, December 2020): U.S. Geological Survey Scientific Investigations Report 2020–5007, 113 p., https://doi.org/10.3133/sir20205007.","productDescription":"Report: vii, 113 p.; 2 Figures","numberOfPages":"125","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-102753","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":373207,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5007/sir20205007.pdf","text":"Report","size":"7.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5007"},{"id":399629,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109787.htm"},{"id":381500,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2020/5007/versionHist.txt","text":"Version History","description":"SIR 2020–5007 Version History"},{"id":373209,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5007/sir20205007_figure23B.pdf","text":"Figure 23B","size":"170 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5007 Figure 23B","linkHelpText":"Clustered monthly median hydrographs plotted using an independent y-axis range for all plots"},{"id":373208,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5007/sir20205007_figure23A.pdf","text":"Figure 23A","size":"163 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5007 Figure 23A","linkHelpText":"Clustered monthly median hydrographs plotted using the same fixed y-axis range for all plots"},{"id":373206,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5007/coverthb2.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Middle Rio Grande Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.8517,\n              34.9064\n            ],\n            [\n              -106.4542,\n              34.9064\n            ],\n            [\n              -106.4542,\n              35.4011\n            ],\n            [\n              -106.8517,\n              35.4011\n            ],\n            [\n              -106.8517,\n              34.9064\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: March 17, 2020; Version 2.0: December 21, 2020","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>Abstract</li><li>Introduction</li><li>Methods</li><li>Optimization Assessment of the Observation Network</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-03-17","revisedDate":"2020-12-21","noUsgsAuthors":false,"publicationDate":"2020-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Ritchie, Andre B. 0000-0003-1289-653X","orcid":"https://orcid.org/0000-0003-1289-653X","contributorId":214611,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andre","email":"","middleInitial":"B.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pepin, Jeff D. 0000-0002-7410-9979","orcid":"https://orcid.org/0000-0002-7410-9979","contributorId":222161,"corporation":false,"usgs":true,"family":"Pepin","given":"Jeff","email":"","middleInitial":"D.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781427,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216954,"text":"sim3467 - 2020 - Bathymetric map, surface area, and capacity of Grand Lake O’ the Cherokees, northeastern Oklahoma, 2019","interactions":[],"lastModifiedDate":"2020-12-22T12:34:16.328212","indexId":"sim3467","displayToPublicDate":"2020-12-21T05:56:20","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":"3467","displayTitle":"Bathymetric Map, Surface Area, and Capacity of Grand Lake O’ the Cherokees, Northeastern Oklahoma, 2019","title":"Bathymetric map, surface area, and capacity of Grand Lake O’ the Cherokees, northeastern Oklahoma, 2019","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the Grand River Dam Authority, completed a high-resolution multibeam bathymetric survey to compute a new area and capacity table for Grand Lake O’ the Cherokees in northeastern Oklahoma. Area and capacity tables identify the relation between the elevation of the water surface and the volume of water that can be impounded at each water-surface elevation. The area and capacity of Grand Lake O’ the Cherokees were computed from a triangular irregular network surface created in Global Mapper Version 21.0.1. The triangular irregular network surface was created from three datasets: (1) a multibeam mapping system bathymetric survey of Grand Lake O’ the Cherokees completed during April–July 2019, (2) a previous bathymetric survey of the Neosho, Spring, and Elk Rivers, and (3) a 2010 USGS lidar-derived digital elevation model. The digital elevation model data were used in areas with land-surface elevations greater than 744 feet above the North American Vertical Datum of 1988 where the multibeam sonar data could not be collected. The 2019 multibeam sonar data were the predominant data used to compute the new area and capacity table for Grand Lake O’ the Cherokees.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3467","collaboration":"Prepared in cooperation with the Grand River Dam Authority","usgsCitation":"Hunter, S.L., Trevisan, A.R., Villa, J., and Smith, K.A., 2020, Bathymetric map, surface area, and capacity of Grand Lake O’ the Cherokees, northeastern Oklahoma, 2019: U.S. Geological Survey Scientific Investigations Map 3467, 2 sheets, https://doi.org/10.3133/sim3467.","productDescription":"2 Sheets: 36.00 x 42.00 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-116457","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":381444,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3467/coverthb.jpg"},{"id":381448,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3467/sim3467_sheet1.pdf","text":"Sheet 1","size":"5.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3467 Sheet 1"},{"id":381449,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3467/sim3467_sheet2.pdf","text":"Sheet 2","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3467 Sheet 2"},{"id":381450,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KA2T3Z","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data release of bathymetric map, surface area, and capacity of Grand Lake O’ the Cherokees, northeastern Oklahoma, 2019"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Grand Lake O’ the Cherokees","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.10589599609375,\n              36.436751611390264\n            ],\n            [\n              -94.60601806640625,\n              36.436751611390264\n            ],\n            [\n              -94.60601806640625,\n              36.8510544475565\n            ],\n            [\n              -95.10589599609375,\n              36.8510544475565\n            ],\n            [\n              -95.10589599609375,\n              36.436751611390264\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/tx-water/\" href=\"https://www.usgs.gov/centers/tx-water/\">Oklahoma-Texas Water Science Center</a><br>U.S. Geological Survey<br>1505 Ferguson Lane <br>Austin, Texas 78754–4501 </p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Description of the Study Area</li><li>Methods of Bathymetric Survey and Data Analysis</li><li>Bathymetric Data-Collection Quality Assurance</li><li>Bathymetric Surface and Contour Quality Assurance</li><li>Bathymetry, Surface Area, and Capacity Results</li><li>References</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-12-21","noUsgsAuthors":false,"publicationDate":"2020-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Hunter, Shelby L. 0000-0002-3049-7498 slhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-3049-7498","contributorId":196727,"corporation":false,"usgs":true,"family":"Hunter","given":"Shelby","email":"slhunter@usgs.gov","middleInitial":"L.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trevisan, A.R. 0000-0002-7295-145X","orcid":"https://orcid.org/0000-0002-7295-145X","contributorId":220399,"corporation":false,"usgs":true,"family":"Trevisan","given":"A.R.","email":"","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villa, Jennifer 0000-0002-4774-7166","orcid":"https://orcid.org/0000-0002-4774-7166","contributorId":245824,"corporation":false,"usgs":true,"family":"Villa","given":"Jennifer","email":"","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Kevin A. 0000-0001-6846-5929","orcid":"https://orcid.org/0000-0001-6846-5929","contributorId":50612,"corporation":false,"usgs":true,"family":"Smith","given":"Kevin","email":"","middleInitial":"A.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807069,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70219507,"text":"70219507 - 2020 - Subsea permafrost carbon stocks and climate change sensitivity estimated by expert assessment","interactions":[],"lastModifiedDate":"2021-04-13T12:19:18.267915","indexId":"70219507","displayToPublicDate":"2020-12-20T11:37:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Subsea permafrost carbon stocks and climate change sensitivity estimated by expert assessment","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>The continental shelves of the Arctic Ocean and surrounding seas contain large stocks of organic matter (OM) and methane (CH<sub>4</sub>), representing a potential ecosystem feedback to climate change not included in international climate agreements. We performed a structured expert assessment with 25 permafrost researchers to combine quantitative estimates of the stocks and sensitivity of organic carbon in the subsea permafrost domain (i.e. unglaciated portions of the continental shelves exposed during the last glacial period). Experts estimated that the subsea permafrost domain contains ~560 gigatons carbon (GtC; 170–740, 90% confidence interval) in OM and 45 GtC (10–110) in CH<sub>4</sub>. Current fluxes of CH<sub>4</sub><span>&nbsp;</span>and carbon dioxide (CO<sub>2</sub>) to the water column were estimated at 18 (2–34) and 38 (13–110) megatons C yr<sup>−1</sup>, respectively. Under Representative Concentration Pathway (RCP) RCP8.5, the subsea permafrost domain could release 43 Gt CO<sub>2</sub>-equivalent (CO<sub>2</sub>e) by 2100 (14–110) and 190 Gt CO<sub>2</sub>e by 2300 (45–590), with ~30% fewer emissions under RCP2.6. The range of uncertainty demonstrates a serious knowledge gap but provides initial estimates of the magnitude and timing of the subsea permafrost climate feedback.</p></div>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/abcc29","usgsCitation":"Sayedi, S., Thornton, B., Abbott, B., Frederick, J.M., Vonk, J.E., Overduin, P., Schadel, C., Schuur, E., Bourbonnais, A., Demidova, N., Gavrilov, A., He, S., Gustaf Hugelius, G., Jakobsson, M., Jones, M.C., Joung, D., Kraev, G., Macdonald, R.W., McGuire, A.D., Mu, C., O’Regan, M., Schreiner, K.M., Stranne, C., Pizhankova, E., Vasiliev, A., Westermann, S., Zarnetske, J.P., Zhang, T., Ghandehari, M., Baeumler, S., Brown, B.C., and Frei, R.J., 2020, Subsea permafrost carbon stocks and climate change sensitivity estimated by expert assessment: Environmental Research Letters, v. 15, no. 12, 124075, 13 p., https://doi.org/10.1088/1748-9326/abcc29.","productDescription":"124075, 13 p.","ipdsId":"IP-118667","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":454630,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/abcc29","text":"Publisher Index Page"},{"id":385030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Sayedi, Sara 0000-0001-5272-4383","orcid":"https://orcid.org/0000-0001-5272-4383","contributorId":257232,"corporation":false,"usgs":false,"family":"Sayedi","given":"Sara","email":"","affiliations":[{"id":48387,"text":"BYU","active":true,"usgs":false}],"preferred":false,"id":813833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thornton, B.F. 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0000-0003-2414-778X","orcid":"https://orcid.org/0000-0003-2414-778X","contributorId":208631,"corporation":false,"usgs":false,"family":"Frederick","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[{"id":37851,"text":"Sandia National Laboratories, Albuquerque, New Mexico, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":814014,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vonk, Jorien E.","contributorId":150794,"corporation":false,"usgs":false,"family":"Vonk","given":"Jorien","email":"","middleInitial":"E.","affiliations":[{"id":18101,"text":"Utrecht University, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":814015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Overduin, Paul","contributorId":248328,"corporation":false,"usgs":false,"family":"Overduin","given":"Paul","email":"","affiliations":[{"id":49850,"text":"Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":814016,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schadel, Christina","contributorId":202385,"corporation":false,"usgs":false,"family":"Schadel","given":"Christina","email":"","affiliations":[{"id":36405,"text":"University of Northern Arizona","active":true,"usgs":false}],"preferred":false,"id":814017,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schuur, E.A.G.","contributorId":199638,"corporation":false,"usgs":false,"family":"Schuur","given":"E.A.G.","email":"","affiliations":[],"preferred":false,"id":814018,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bourbonnais, A.","contributorId":248726,"corporation":false,"usgs":false,"family":"Bourbonnais","given":"A.","email":"","affiliations":[{"id":49991,"text":"University of South Carolina, School of the Earth, Ocean and Environment, South Carolina","active":true,"usgs":false}],"preferred":false,"id":814019,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Demidova, N.","contributorId":61659,"corporation":false,"usgs":true,"family":"Demidova","given":"N.","email":"","affiliations":[],"preferred":false,"id":814020,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gavrilov, Anatoly","contributorId":209709,"corporation":false,"usgs":false,"family":"Gavrilov","given":"Anatoly","email":"","affiliations":[{"id":37971,"text":"Directorate of Taimyrsky Reserves","active":true,"usgs":false}],"preferred":false,"id":814021,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"He, Shengping 0000-0003-4245-357X","orcid":"https://orcid.org/0000-0003-4245-357X","contributorId":257293,"corporation":false,"usgs":false,"family":"He","given":"Shengping","email":"","affiliations":[{"id":28158,"text":"University of Bergen","active":true,"usgs":false}],"preferred":false,"id":814022,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Gustaf Hugelius, Gustaf 0000-0002-8096-1594","orcid":"https://orcid.org/0000-0002-8096-1594","contributorId":202100,"corporation":false,"usgs":false,"family":"Gustaf Hugelius","given":"Gustaf","affiliations":[{"id":36343,"text":"Department of Physical Geography, Stockholm University, Stockholm, Sweden","active":true,"usgs":false}],"preferred":false,"id":814023,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Jakobsson, Martin","contributorId":166854,"corporation":false,"usgs":false,"family":"Jakobsson","given":"Martin","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":814024,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"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":814025,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Joung, DoongJoo 0000-0002-2711-3780","orcid":"https://orcid.org/0000-0002-2711-3780","contributorId":245909,"corporation":false,"usgs":false,"family":"Joung","given":"DoongJoo","email":"","affiliations":[{"id":37381,"text":"University of Rochester","active":true,"usgs":false}],"preferred":false,"id":814026,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Kraev, Gleb","contributorId":257294,"corporation":false,"usgs":false,"family":"Kraev","given":"Gleb","email":"","affiliations":[{"id":12544,"text":"Russian Academy of Sciences, Moscow, Russia","active":true,"usgs":false},{"id":28162,"text":"Vrije University Amsterdam","active":true,"usgs":false}],"preferred":false,"id":814027,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Macdonald, Robie W.","contributorId":167171,"corporation":false,"usgs":false,"family":"Macdonald","given":"Robie","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":814028,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":814029,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Mu, Cuicui","contributorId":168877,"corporation":false,"usgs":false,"family":"Mu","given":"Cuicui","email":"","affiliations":[{"id":25375,"text":"Lanzhou University, PR China","active":true,"usgs":false}],"preferred":false,"id":814030,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"O’Regan, M.","contributorId":38361,"corporation":false,"usgs":true,"family":"O’Regan","given":"M.","email":"","affiliations":[],"preferred":false,"id":814031,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Schreiner, Kathryn M.","contributorId":201540,"corporation":false,"usgs":false,"family":"Schreiner","given":"Kathryn","email":"","middleInitial":"M.","affiliations":[{"id":36192,"text":"Large Lakes Observatory, University of Minnesota Duluth, Duluth, Minnesota, USA.","active":true,"usgs":false}],"preferred":false,"id":814032,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Stranne, Christian","contributorId":166862,"corporation":false,"usgs":false,"family":"Stranne","given":"Christian","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":814033,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Pizhankova, Elena","contributorId":257306,"corporation":false,"usgs":false,"family":"Pizhankova","given":"Elena","email":"","affiliations":[{"id":16615,"text":"Moscow State University","active":true,"usgs":false}],"preferred":false,"id":814034,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Vasiliev, A.","contributorId":216063,"corporation":false,"usgs":false,"family":"Vasiliev","given":"A.","email":"","affiliations":[],"preferred":false,"id":814035,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Westermann, S.","contributorId":216066,"corporation":false,"usgs":false,"family":"Westermann","given":"S.","email":"","affiliations":[],"preferred":false,"id":814036,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Zarnetske, Jay P.","contributorId":210073,"corporation":false,"usgs":false,"family":"Zarnetske","given":"Jay","email":"","middleInitial":"P.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":814043,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Zhang, Tingjun","contributorId":66600,"corporation":false,"usgs":false,"family":"Zhang","given":"Tingjun","affiliations":[{"id":28117,"text":"Lanzhou University, Lanzhou, China","active":true,"usgs":false}],"preferred":false,"id":814044,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Ghandehari, M","contributorId":196539,"corporation":false,"usgs":false,"family":"Ghandehari","given":"M","email":"","affiliations":[],"preferred":false,"id":814045,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Baeumler, Sarah 0000-0003-1772-8180","orcid":"https://orcid.org/0000-0003-1772-8180","contributorId":257317,"corporation":false,"usgs":false,"family":"Baeumler","given":"Sarah","email":"","affiliations":[{"id":32910,"text":"Ludwig-Maximilians-Universität Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":814046,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Brown, Brian C.","contributorId":257319,"corporation":false,"usgs":false,"family":"Brown","given":"Brian","email":"","middleInitial":"C.","affiliations":[{"id":48387,"text":"BYU","active":true,"usgs":false}],"preferred":false,"id":814047,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Frei, Rebecca J.","contributorId":247665,"corporation":false,"usgs":false,"family":"Frei","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":814048,"contributorType":{"id":1,"text":"Authors"},"rank":32}]}}
,{"id":70216971,"text":"70216971 - 2020 - Potomac tributary report: A summary of trends in tidal water quality and associated factors","interactions":[],"lastModifiedDate":"2023-08-22T13:01:40.234084","indexId":"70216971","displayToPublicDate":"2020-12-18T13:14:18","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Potomac tributary report: A summary of trends in tidal water quality and associated factors","docAbstract":"The Potomac Tributary Report summarizes change over time in a suite of monitored tidal water quality parameters and associated potential drivers of those trends for the time period 1985 – 2018, and provides a brief description of the current state of knowledge explaining these observed changes. Water quality parameters described include surface total nitrogen (TN), surface total phosphorus (TP), spring and summer surface chlorophyll a, summer bottom dissolved oxygen (DO) concentrations, and Secchi disk depth (a measure of water clarity). Results for annual surface water temperature, bottom TP, bottom TN, surface ortho-phosphate (PO4), surface dissolved inorganic nitrogen (DIN), surface total suspended solids (TSS), and summer surface DO concentrations are provided in an Appendix.  Drivers discussed include physiographic watershed characteristics, changes in N, P, and sediment loads from the watershed to tidal waters, expected effects of changing land use, and implementation of nutrient management and natural resource conservation practices.  Factors internal to estuarine waters that also play a role as drivers are described including biogeochemical processes, physical forces such as wind-driven mixing of the water column, and biological factors such as phytoplankton biomass and the presence of submersed aquatic vegetation.\n\nTotal nutrient concentrations have been decreasing at most stations in the Potomac River over the long-term, with improvements persisting in the last 10 years as well. These trends follow from the decreasing discharge from TN and TP sources in the watershed. The TP source reductions are not as apparent in the direct loads to the river, which may be part of the reason that tidal nutrient concentrations are not decreasing at as many stations in the short-term as the long-term.  While degrading chlorophyll a and Secchi depth trends at several Potomac monitoring stations are concerning, recent improvements in summer oxygen concentrations are promising. The findings that chlorophyll a concentrations in the lower Potomac have either leveled out or improved may suggest a smaller amount of phytoplankton biomass available to fuel summer oxygen depletion. The responses of chlorophyll a, Secchi depth, and bottom DO are mixed in the Potomac tidal waters, but there are multiple possible reasons for this lag in response. Continuing to track water quality response and investigating these possibilities are important steps to understanding water quality patterns and changes in the Potomac River.","language":"English","publisher":"Chesapeake Bay Program Office","usgsCitation":"Keisman, J.L., Murphy, R., Devereux, O., Harcum, J., Karrh, R., Lane, M., Perry, E., Webber, J.S., Wei, Z., Zhang, Q., and Petenbrink, M.N., 2020, Potomac tributary report: A summary of trends in tidal water quality and associated factors, 48 p.","productDescription":"48 p.","ipdsId":"IP-116578","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":420011,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://cast-content.chesapeakebay.net/documents/TribSummaries%2FPotomac%20Tidal%20Tributary%20Report%20Final%202020-12-18.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":382768,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387867,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://cast.chesapeakebay.net/Home/TMDLTracking#tributaryRptsSection","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Pennsylvania, Virginia, West Viginia","otherGeospatial":"Potomic River watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.1123046875,\n              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Center","active":true,"usgs":true}],"preferred":true,"id":807119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Rebecca 0000-0003-3391-1823","orcid":"https://orcid.org/0000-0003-3391-1823","contributorId":199777,"corporation":false,"usgs":false,"family":"Murphy","given":"Rebecca","email":"","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":true,"id":807120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Devereux, Olivia H. 0000-0002-3911-3307","orcid":"https://orcid.org/0000-0002-3911-3307","contributorId":198108,"corporation":false,"usgs":false,"family":"Devereux","given":"Olivia H.","affiliations":[],"preferred":false,"id":807121,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harcum, J.","contributorId":248519,"corporation":false,"usgs":false,"family":"Harcum","given":"J.","affiliations":[],"preferred":false,"id":809301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karrh, R.","contributorId":248520,"corporation":false,"usgs":false,"family":"Karrh","given":"R.","affiliations":[],"preferred":false,"id":809302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, M.","contributorId":248521,"corporation":false,"usgs":false,"family":"Lane","given":"M.","affiliations":[],"preferred":false,"id":809303,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Perry, E.","contributorId":248522,"corporation":false,"usgs":false,"family":"Perry","given":"E.","email":"","affiliations":[],"preferred":false,"id":809304,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Webber, James S. 0000-0001-6636-1368","orcid":"https://orcid.org/0000-0001-6636-1368","contributorId":222000,"corporation":false,"usgs":true,"family":"Webber","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807122,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wei, Zhaoying","contributorId":245828,"corporation":false,"usgs":false,"family":"Wei","given":"Zhaoying","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":807123,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhang, Qian 0000-0003-0500-5655","orcid":"https://orcid.org/0000-0003-0500-5655","contributorId":174393,"corporation":false,"usgs":false,"family":"Zhang","given":"Qian","email":"","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":807124,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Petenbrink, Meghan Nicole 0000-0002-2944-9691","orcid":"https://orcid.org/0000-0002-2944-9691","contributorId":245829,"corporation":false,"usgs":true,"family":"Petenbrink","given":"Meghan","email":"","middleInitial":"Nicole","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807125,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70216992,"text":"70216992 - 2020 - Fish out of water: Insights from a case study of a highly social animal that failed the mirror self-recognition test","interactions":[],"lastModifiedDate":"2020-12-22T13:25:52.080479","indexId":"70216992","displayToPublicDate":"2020-12-18T07:25:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7476,"text":"International Journal of Comparative Psychology","active":true,"publicationSubtype":{"id":10}},"title":"Fish out of water: Insights from a case study of a highly social animal that failed the mirror self-recognition test","docAbstract":"<div id=\"main\"><div data-reactroot=\"\"><div class=\"body\"><div><div class=\"c-columns--sticky-sidebar\"><div class=\"c-tabs\"><div class=\"c-tabs__content\"><div class=\"c-tabcontent\"><div id=\"details-content\"><div class=\"c-clientmarkup\"><p>Mirror self-recognition (MSR) tests have been conducted with a variety of species with the aim of examining whether subject animals have the capacity for self-awareness. To date, the majority of animals that have convincingly passed are highly social mammals whose wild counterparts live in complex societies, though there is much debate concerning what constitutes passing and what passing means in terms of self-awareness. Amid recent reports that a fish (cleaner wrasse,<span>&nbsp;</span><i>Labroides dimidiatus</i>) passed, it is intriguing that a mammal as highly social, tolerant, attentive, and cooperative as the grey wolf (<i>Canis lupus</i>) reportedly failed the test. Given the many possible reasons for failure, we aimed to elucidate the wolves’ responses at various stages of the MSR test to pinpoint potential problem areas where species-appropriate modifications to the test may be needed. Thus, we evaluated 6 socialized, captive grey wolves as a case study of failed MSR in socially complex canids. At a minimum, wolves did not respond to their reflection as an unfamiliar conspecific. Unfortunately, the wolves rapidly lost interest in the mirror and were uninterested in the applied marks. We note limitations of the MSR test for this species, recommend changes for future MSR tests of wolves, discuss other emerging self-cognizance methods for socially complex canids, and highlight the need for a suite of ecologically relevant, potentially scalable self-cognizance methods. Our findings and recommendations may aid in understanding self-cognizance in other untested highly social, cooperatively-hunting, coursing, terrestrial carnivores such as African wild dogs (<i>Lycaon pictus</i>), spotted hyenas (<i>Crocuta crocuta</i>), and African lions (<i>Panthera leo</i>).</p></div></div></div></div></div></div></div></div></div></div>","language":"English","publisher":"UCLA","usgsCitation":"Barber-Meyer, S., and Schmidt, L.J., 2020, Fish out of water: Insights from a case study of a highly social animal that failed the mirror self-recognition test: International Journal of Comparative Psychology, v. 33, 16 p.","productDescription":"16 p.","ipdsId":"IP-090921","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":381567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381566,"type":{"id":15,"text":"Index Page"},"url":"https://escholarship.org/uc/item/0bk066tc"}],"volume":"33","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barber-Meyer, Shannon 0000-0002-3048-2616","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":217941,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":807184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Lori J.","contributorId":245856,"corporation":false,"usgs":false,"family":"Schmidt","given":"Lori","email":"","middleInitial":"J.","affiliations":[{"id":49346,"text":"International Wolf Center, Ely, MN","active":true,"usgs":false}],"preferred":false,"id":807185,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216898,"text":"sim3458 - 2020 - Geologic map and borehole stratigraphy of Hinkley Valley and vicinity, San Bernardino County, California","interactions":[],"lastModifiedDate":"2021-01-04T19:40:40.811178","indexId":"sim3458","displayToPublicDate":"2020-12-18T06:45:39","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":"3458","displayTitle":"Geologic Map and Borehole Stratigraphy of Hinkley Valley and Vicinity, San Bernardino County, California","title":"Geologic map and borehole stratigraphy of Hinkley Valley and vicinity, San Bernardino County, California","docAbstract":"<p>Hinkley Valley, in the central to western Mojave Desert of southeastern California, has a long historical record owing to its position as a crossroads for rail and road traffic and its position adjacent to the Mojave River. Subflow in the Mojave River provided groundwater recharge that maintained water consumption and demand by way of shallow wells for local agriculture in the valley. Its crossroads position led to construction of several power-transmission lines, pipeline, and communications cable routes that transect Hinkley Valley. One of these, a natural gas pipeline and its associated compressor station, was the locus of hexavalent chromium, Cr(VI), released into, and consequent contamination of, groundwater. Understanding the movement and fate of the contaminants is a complex hydrologic and geochemical problem. Geologic mapping of the Hinkley Valley area provides framework elements for use in resolving this problem. This report provides new information on surface and subsurface geology to better constrain the origin and geometry of hydrologically important deposits in the Hinkley Valley area and describes youthful faults that may control sediment distribution and groundwater flow. The geologic map (sheet 1) presents substantial new information on surficial geology, including Pliocene deposits, but does not contain significant new work on bedrock. Bedrock investigations were specific to identifying youthful faults and representative outcrops for rocks that were penetrated by boreholes in the valley. Special attention was placed on locating and describing youthful faults. In addition, we analyzed gravity data to (1) map horizontal gradients that we interpret to reflect long-term fault traces and to (2) estimate the depth to bedrock, which is defined as Miocene and older intrusive and metamorphic rocks for the purposes of this report. The subsurface geology of Hinkley Valley was investigated by examining borehole sediment cores and rock encountered at the base of the sediment section. We analyzed the core to determine depositional environments, provenance, and age of the sediment that infilled the valley. Valleys, mountains, and basins in the Hinkley Valley area are topographically complex and incompletely named. The nearly flat floored Hinkley Valley slopes gently northward. It is framed by Mount General and the informally named “Hinkley hills” (southeast of Mount General) on the northeast and by Iron Mountain and Lynx Cat Mountain on the southwest, although breaks in the western mountains allow stream connections between Hinkley Valley and another valley to the west that is herein referred to as Hawes valley. At its south end, Hinkley Valley is traversed by the entrenched Mojave River, which passes east out of the valley past Barstow. North of Hinkley Valley, a few low hills (including Red Hill) separate the valley from a broad west-sloping piedmont that is part of the physiographic Harper Basin (of which the Harper Lake playa is the center). The lower part of this piedmont, however, is referred to as Water Valley, although it is not a distinct valley. The name derives from groundwater sourced from subflow in the Mojave River, which caused shallow water and even artesian flow in Water Valley but not in other parts of the Harper Basin. When water filled the Harper Basin to form Pleistocene Lake Harper it not only submerged Water Valley but also northern Hinkley Valley.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3458","collaboration":"Prepared in cooperation with the Lahontan Regional Water Quality Control Board and the State Water Resources Control Board","usgsCitation":"Miller, D.M., Langenheim, V.E., and Haddon, E.K., 2020, Geologic map and borehole stratigraphy of Hinkley Valley and vicinity, San Bernardino County, California: U.S. Geological Survey Scientific Investigations Map 3458, pamphlet 23 p., 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3458.","productDescription":"Pamphlet,: iv, 23 p.; 2 Sheets ; 2 Tables; Database; Data Release; Metadata","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102109","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":381271,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_sheet2.pdf","text":"Sheet 2","size":"32 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381270,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_sheet1.pdf","text":"Sheet 1","size":"40 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381269,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_database.zip","text":"Database","size":"7.5 MB","linkFileType":{"id":6,"text":"zip"}},{"id":381268,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_base.zip","text":"Base","size":"1.25 GB","linkFileType":{"id":6,"text":"zip"}},{"id":381267,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_metadata.txt","size":"10 KB","linkFileType":{"id":2,"text":"txt"}},{"id":381266,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_pamphlet.pdf","text":"Pamphlet","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381451,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FV5LG5","linkHelpText":"Gravity data of the Hinkley area, southern California"},{"id":381273,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_table_7.xlsx","text":"Table 7","size":"60 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":381265,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3458/covrthb.jpg"},{"id":381272,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3458/sim3458_table_3.xlsx","text":"Table 3","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","state":"California","county":"San Bernadino County","otherGeospatial":"Hinkley Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.26257324218749,\n              34.80647431931937\n            ],\n            [\n              -117.06619262695312,\n              34.80647431931937\n            ],\n            [\n              -117.06619262695312,\n              35.060352812431496\n            ],\n            [\n              -117.26257324218749,\n              35.060352812431496\n            ],\n            [\n              -117.26257324218749,\n              34.80647431931937\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg/employee-directory\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg/employee-directory\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Menlo Park, California</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>345 Middlefield Road<br>Menlo Park, CA 94025-3591</p>","tableOfContents":"<ul><li>Introduction</li><li>Geologic Setting</li><li>Methods</li><li>Previous Work</li><li>Stratigraphy and Structure</li><li>Borehole Stratigraphy</li><li>Hydrologic Implications</li><li>Geologic Map</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-12-17","noUsgsAuthors":false,"publicationDate":"2020-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":806859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langenheim, Victoria E. 0000-0003-2170-5213","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":206978,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":806860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haddon, Elizabeth K. 0000-0001-7601-7755","orcid":"https://orcid.org/0000-0001-7601-7755","contributorId":238720,"corporation":false,"usgs":true,"family":"Haddon","given":"Elizabeth K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":806861,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70216956,"text":"70216956 - 2020 - Permafrost mapping with electrical resistivity tomography in two wetland systems north of the Tanana River, Interior Alaska","interactions":[],"lastModifiedDate":"2022-11-14T16:56:56.383567","indexId":"70216956","displayToPublicDate":"2020-12-17T19:02:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Permafrost mapping with electrical resistivity tomography in two wetland systems north of the Tanana River, Interior Alaska","docAbstract":"<p><span>Surface-based 2D electrical resistivity tomography (ERT) surveys were used to characterize permafrost distribution at wetland sites on the alluvial plain north of the Tanana River, 20 km southwest of Fairbanks, Alaska, in June and September 2014. The sites were part of an ecologically-sensitive research area characterizing biogeochemical response of this region to warming and permafrost thaw, and the site contained landscape features characteristic of interior Alaska, including thermokarst bog, forested permafrost plateau, and a rich fen. The results show how vegetation reflects shallow (0–10 m depth) permafrost distribution. Additionally, we saw shallow (0–3 m depth) low resistivity areas in forested permafrost plateau potentially indicating the presence of increased unfrozen water content as a precursor to ground instability and thaw. Time-lapse study from June to September suggested a depth of seasonal influence extending several meters below the active layer, potentially as a result of changes in unfrozen water content. A comparison of several electrode geometries (dipole-dipole, extended dipole-dipole, Wenner-Schlumberger) showed that for depths of interest to our study (0–10 m) results were similar, but data acquisition time with dipole-dipole was the shortest, making it our preferred geometry. The results show the utility of ERT surveys to characterize permafrost distribution at these sites, and how vegetation reflects shallow permafrost distribution. These results are valuable information for ecologically sensitive areas where ground-truthing can cause excessive disturbance. ERT data can be used to characterize the exact subsurface geometry of permafrost such that over time an understanding of changing permafrost conditions can be made in great detail. Characterizing the depth of thaw and thermal influence from the surface in these areas also provides important information as an indication of the depth to which carbon storage and microbially-mediated carbon processing may be affected.</span></p>","language":"English","publisher":"Environmental & Engineering Geophysical Society","doi":"10.2113/JEEG19-091","usgsCitation":"Conaway, C., Johnson, C., Lorenson, T., Turetsky, M.R., Euskirchen, E., Waldrop, M., and Swarzenski, P.W., 2020, Permafrost mapping with electrical resistivity tomography in two wetland systems north of the Tanana River, Interior Alaska: Journal of Environmental & Engineering Geophysics, v. 2, no. 25, p. 199-209, https://doi.org/10.2113/JEEG19-091.","productDescription":"11 p.","startPage":"199","endPage":"209","ipdsId":"IP-102186","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":436695,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KTHH8X","text":"USGS data release","linkHelpText":"Permafrost Mapping in Two Wetland Systems North of the Tanana River in Interior Alaska 2014"},{"id":381485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Tanana River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -148.19732666015625,\n              64.72374428370091\n            ],\n            [\n              -148.4197998046875,\n              64.86527470612393\n            ],\n            [\n              -149.117431640625,\n              64.83959712503844\n            ],\n            [\n              -149.095458984375,\n              64.63564536799623\n            ],\n            [\n              -149.07073974609375,\n              64.57321597426092\n            ],\n            [\n              -148.7274169921875,\n              64.59561280029605\n            ],\n            [\n              -148.66973876953125,\n              64.63917482390902\n            ],\n            [\n              -148.392333984375,\n              64.66621875267623\n            ],\n            [\n              -148.19732666015625,\n              64.72374428370091\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"2","issue":"25","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Conaway, Christopher H. 0000-0002-0991-033X","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":201932,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":807080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Cordell 0000-0001-8353-8030","orcid":"https://orcid.org/0000-0001-8353-8030","contributorId":212817,"corporation":false,"usgs":true,"family":"Johnson","given":"Cordell","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807082,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Turetsky, Merritt R.","contributorId":169398,"corporation":false,"usgs":false,"family":"Turetsky","given":"Merritt","email":"","middleInitial":"R.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":807083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Euskirchen, Eugénie S.","contributorId":83378,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugénie S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":807084,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":807085,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":189823,"corporation":false,"usgs":false,"family":"Swarzenski","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":807086,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70217102,"text":"70217102 - 2020 - Diet and bathymetric distribution of juvenile Lake Trout Salvelinus namaycush in Lake Huron","interactions":[],"lastModifiedDate":"2021-01-06T13:22:37.723352","indexId":"70217102","displayToPublicDate":"2020-12-17T07:18:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Diet and bathymetric distribution of juvenile Lake Trout <i>Salvelinus namaycush</i> in Lake Huron","title":"Diet and bathymetric distribution of juvenile Lake Trout Salvelinus namaycush in Lake Huron","docAbstract":"Rehabilitation efforts for Lake Trout Salvelinus namaycush in Lake Huron have resulted in increased capture of young wild Lake Trout in annual bottom trawl surveys conducted by the U.S. Geological Survey. To better understand the ecology of juvenile (<400mm) Lake Trout, we summarized the spatial distribution of their capture in bottom trawls at six ports in Lake Huron during October/November 20082017 and analyzed diets of wild (n = 306 of 337 total) and hatchery-origin (n = 18 of 30 total) fish captured. Lake Trout ranged in size from 27 to 399mm, representing at least three age-classes, and 92% were wild origin. Most wild juvenile Lake Trout (83%) were captured at 4664 m depths at the two northernmost ports, typically below the thermocline. Mysis diluviana was the most prevalent prey type, found in 75% of wild fish with non-empty stomachs, followed by two non-native species: Spiny Water Flea Bythotrephes longimanus (31%) and Round Goby Neogobius melanostomus (12%). Small Lake Trout (<185mm) consumed invertebrates but transitioned to mostly fish-based diets by >185mm (age 2). The variety of taxa consumed by young Lake Trout increased with length. Further declines in Mysis populations due to increased predation pressure after the loss of Diporeia from the system may hinder the recovery of wild Lake Trout, and although they have been able to utilize invasive species as prey, impacts to Lake Trout growth remain unknown. Additional research on the habitat use and diets of wild juvenile Lake Trout may provide insight into the reasons behind the recent successful natural reproduction and recruitment of Lake Trout in Lake Huron.","language":"English","publisher":"Taylor Francis","doi":"10.1080/14634988.2020.1826158","usgsCitation":"Roseman, E., Riley, S., Tucker, T., Farha, S., Jackson, S., and Bowser, D., 2020, Diet and bathymetric distribution of juvenile Lake Trout Salvelinus namaycush in Lake Huron: Aquatic Ecosystem Health & Management, v. 23, no. 3, p. 350-365, https://doi.org/10.1080/14634988.2020.1826158.","productDescription":"16 p.","startPage":"350","endPage":"365","ipdsId":"IP-113585","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":381942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States, Canada","otherGeospatial":"Lake Huron","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.0673828125,\n              46.34692761055676\n            ],\n            [\n              -84.72656249999999,\n              46.057985244793024\n            ],\n            [\n              -84.72656249999999,\n              45.79816953017265\n            ],\n            [\n              -83.69384765625,\n              43.5326204268101\n            ],\n            [\n              -82.37548828125,\n              43.052833917627936\n            ],\n            [\n              -81.67236328125,\n              43.42100882994726\n            ],\n            [\n              -80.0244140625,\n              44.62175409623324\n            ],\n            [\n              -79.8046875,\n              44.824708282300236\n            ],\n            [\n              -80.70556640625,\n              46.057985244793024\n            ],\n            [\n              -84.0673828125,\n              46.34692761055676\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"23","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riley, Stephen 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":169479,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, Taaja 0000-0003-1534-4677","orcid":"https://orcid.org/0000-0003-1534-4677","contributorId":217908,"corporation":false,"usgs":true,"family":"Tucker","given":"Taaja","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farha, Steve A. 0000-0001-9953-6996 sfarha@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-6996","contributorId":5170,"corporation":false,"usgs":true,"family":"Farha","given":"Steve A.","email":"sfarha@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Scott 0000-0003-1272-9918","orcid":"https://orcid.org/0000-0003-1272-9918","contributorId":208420,"corporation":false,"usgs":false,"family":"Jackson","given":"Scott","affiliations":[],"preferred":false,"id":807617,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bowser, Dustin 0000-0001-5674-8016 dbowser@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-8016","contributorId":223117,"corporation":false,"usgs":true,"family":"Bowser","given":"Dustin","email":"dbowser@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807618,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70219575,"text":"70219575 - 2020 - Assessing contributions of cold-water refuges to reproductive migration corridor conditions for adult salmon and steelhead trout in the Columbia River, USA","interactions":[],"lastModifiedDate":"2021-04-14T12:03:12.831455","indexId":"70219575","displayToPublicDate":"2020-12-17T06:59:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5513,"text":"Journal of Ecohydraulics","active":true,"publicationSubtype":{"id":10}},"title":"Assessing contributions of cold-water refuges to reproductive migration corridor conditions for adult salmon and steelhead trout in the Columbia River, USA","docAbstract":"<p><span>Diadromous fish populations face multiple challenges along their migratory routes. These challenges include suboptimal water quality, harvest, and barriers to longitudinal and lateral connectivity. Interactions among factors influencing migration success make it challenging to assess management options for improving migratory fish conditions along riverine migration corridors. We describe a spatially explicit simulation model that integrates complex individual behaviors of fall-run Chinook Salmon (</span><i>Oncorhynchus tshawytscha</i><span>) and summer-run steelhead trout (</span><i>O. mykiss</i><span>) during migration, responds to variable habitat conditions over a large extent of the Columbia River, and links migration corridor conditions to fish condition outcomes. The model is built around a mechanistic behavioral decision tree that drives individual interactions of fish within their simulated environments. By simulating several thermalscapes with alternative scenarios of thermal refuge availability, we examined how behavioral thermoregulation in cold-water refuges influenced migrating fish conditions. Outcomes of the migration corridor simulation model show that cold-water refuges can provide relief from exposure to high water temperatures, but do not substantially contribute to energy conservation by migrating adults. Simulated cooling of the Columbia River decreased reliance on cold-water refuges and there were slight reductions in migratory energy expenditure. This modeling of simulated thermalscapes provides a framework for assessing the contribution of cold-water refuges to the success of migrating fishes, but any final determination will depend on analyzing fish survival and health for their entire migration, water temperature management goals and species recovery targets.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/24705357.2020.1855086","usgsCitation":"Snyder, M.N., Schumaker, N.H., Dunham, J.B., Keefer, M., Leinenbach, P., Brookes, A., Palmer, J., Wu, J., Keenan, D.M., and Ebersole, J.L., 2020, Assessing contributions of cold-water refuges to reproductive migration corridor conditions for adult salmon and steelhead trout in the Columbia River, USA: Journal of Ecohydraulics, 14 p., https://doi.org/10.1080/24705357.2020.1855086.","productDescription":"14 p.","onlineOnly":"Y","ipdsId":"IP-122783","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":454644,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8059528","text":"External Repository"},{"id":385075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Washington, Oregon, Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.65234374999999,\n              44.02442151965934\n            ],\n            [\n              -114.78515624999999,\n              44.02442151965934\n            ],\n            [\n              -114.78515624999999,\n              46.73986059969267\n            ],\n            [\n              -118.65234374999999,\n              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Agency","active":true,"usgs":false}],"preferred":false,"id":814221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":814222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keefer, Matthew","contributorId":217975,"corporation":false,"usgs":false,"family":"Keefer","given":"Matthew","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":814223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leinenbach, P.T.","contributorId":217976,"corporation":false,"usgs":false,"family":"Leinenbach","given":"P.T.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":814224,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brookes, Allen","contributorId":217977,"corporation":false,"usgs":false,"family":"Brookes","given":"Allen","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":814225,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Palmer, John","contributorId":217980,"corporation":false,"usgs":false,"family":"Palmer","given":"John","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":814226,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wu, Jennifer","contributorId":217979,"corporation":false,"usgs":false,"family":"Wu","given":"Jennifer","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":814227,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Keenan, Druscilla M","contributorId":257427,"corporation":false,"usgs":false,"family":"Keenan","given":"Druscilla","email":"","middleInitial":"M","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":814228,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ebersole, Joseph L.","contributorId":146938,"corporation":false,"usgs":false,"family":"Ebersole","given":"Joseph","email":"","middleInitial":"L.","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":814229,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70218474,"text":"70218474 - 2020 - Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology","interactions":[],"lastModifiedDate":"2021-03-01T15:53:30.188709","indexId":"70218474","displayToPublicDate":"2020-12-16T09:44:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology","docAbstract":"<p><span>Samples from eight species of corals (</span><i>Colpophyllia natans</i><span>,&nbsp;</span><i>Dendrogyra cylindrus</i><span>,&nbsp;</span><i>Diploria labyrinthiformis</i><span>,&nbsp;</span><i>Meandrina meandrites</i><span>,&nbsp;</span><i>Montastraea cavernosa</i><span>,&nbsp;</span><i>Orbicella faveolata, Pseudodiploria strigosa</i><span>, and&nbsp;</span><i>Siderastrea siderea</i><span>) that exhibited gross clinical signs of acute, subacute, or chronic tissue loss attributed to stony coral tissue loss disease (SCTLD) were collected from the Florida Reef Tract during 2016–2018 and examined histopathologically. The hallmark microscopic lesion seen in all eight species was focal to multifocal lytic necrosis (LN) originating in the gastrodermis of the basal body wall (BBW) and extending to the calicodermis, with more advanced lesions involving the surface body wall. This was accompanied by other degenerative changes in host cells such as mucocyte hypertrophy, degradation and fragmentation of gastrodermal architecture, and disintegration of the mesoglea. Zooxanthellae manifested various changes including necrosis (cytoplasmic hypereosinophilia, pyknosis); peripheral nuclear chromatin condensation; cytoplasmic vacuolation accompanied by deformation, swelling, or atrophy; swollen accumulation bodies; prominent pyrenoids; and degraded chloroplasts. Polyhedral intracytoplasmic eosinophilic periodic acid–Schiff-positive crystalline inclusion bodies (∼1–10 μm in length) were seen only in&nbsp;</span><i>M. cavernosa</i><span>&nbsp;and&nbsp;</span><i>P. strigosa</i><span>&nbsp;BBW gastrodermis in or adjacent to active lesions and some unaffected areas (without surface lesions) of diseased colonies. Coccoidlike or coccobacilloidlike structures (Gram-neutral) reminiscent of microorganisms were occasionally associated with LN lesions or seen in apparently healthy tissue of diseased colonies along with various parasites and other bacteria all considered likely secondary colonizers. Of the 82 samples showing gross lesions of SCTLD, 71 (87%) were confirmed histologically to have LN. Collectively, pathology indicates that SCTLD is the result of a disruption of host–symbiont physiology with lesions originating in the BBW leading to detachment and sloughing of tissues from the skeleton. Future investigations could focus on identifying the cause and pathogenesis of this process.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2020.576013","usgsCitation":"Landsberg, J., Kiryu, Y., Peters, E., Wilson, P., Waters, Y., Maxwell, K., Huebner, L., and Work, T.M., 2020, Stony coral tissue loss disease in Florida is associated with disruption of host–zooxanthellae physiology: Frontiers in Marine Science, v. 7, 576013, 24 p., https://doi.org/10.3389/fmars.2020.576013.","productDescription":"576013, 24 p.","ipdsId":"IP-122466","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":454646,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2020.576013","text":"Publisher Index Page"},{"id":383688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.167236328125,\n              27.371767300523047\n            ],\n            [\n              -80.386962890625,\n              27.225325836903373\n            ],\n            [\n              -80.15625,\n              26.470573022375085\n            ],\n            [\n              -80.26611328125,\n              25.839449402063185\n            ],\n            [\n              -80.44189453125,\n              25.27450351782018\n            ],\n            [\n              -80.716552734375,\n              24.91633140459907\n            ],\n            [\n              -82.08984375,\n              24.627044746156027\n            ],\n            [\n              -81.88110351562499,\n              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Yasu","contributorId":252920,"corporation":false,"usgs":false,"family":"Kiryu","given":"Yasu","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Esther","contributorId":252921,"corporation":false,"usgs":false,"family":"Peters","given":"Esther","affiliations":[{"id":50470,"text":"George Masson University","active":true,"usgs":false}],"preferred":false,"id":811124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Patrick","contributorId":252922,"corporation":false,"usgs":false,"family":"Wilson","given":"Patrick","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waters, Yvonne","contributorId":252923,"corporation":false,"usgs":false,"family":"Waters","given":"Yvonne","email":"","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811126,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maxwell, Kerry","contributorId":252924,"corporation":false,"usgs":false,"family":"Maxwell","given":"Kerry","email":"","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811127,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huebner, Lindsay","contributorId":252925,"corporation":false,"usgs":false,"family":"Huebner","given":"Lindsay","affiliations":[{"id":18903,"text":"Florida FWC","active":true,"usgs":false}],"preferred":false,"id":811128,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife 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,{"id":70216871,"text":"sir20205091 - 2020 - Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15","interactions":[],"lastModifiedDate":"2021-04-08T21:42:55.915848","indexId":"sir20205091","displayToPublicDate":"2020-12-16T09:00:00","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":"2020-5091","displayTitle":"Simulation of Groundwater Flow in the Regional Aquifer System on Long Island, New York, for Pumping and Recharge Conditions in 2005–15","title":"Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15","docAbstract":"<p>A three-dimensional groundwater-flow model was developed for the aquifer system of Long Island, New York, to evaluate (1) responses of the hydrologic system to changes in natural and anthropogenic hydraulic stresses, (2) the subsurface distribution of groundwater age, and (3) the regional-scale distribution of groundwater travel times and the source of water to fresh surface waters and coastal receiving waters. The model also provides the groundwater flow components used to define model boundaries for possible inset models used for local-scale analyses.</p><p>The three-dimensional, groundwater flow model developed for this investigation uses the numerical code MODFLOW–NWT to represent steady-state conditions for average groundwater pumping and aquifer recharge for 2005–15. The particle-tracking algorithm MODPATH, which simulates advective transport in the aquifer, was used to estimate groundwater age, delineate the areas at the water table that contribute recharge to coastal and freshwater bodies, and estimate total travel times of water from the water table to discharge locations.</p><p>A three-dimensional, 1-meter (3.3-foot) topobathymetric model was used to determine land-surface altitudes for the island and seabed altitudes for the surrounding coastal waters. The mapped extents and surface altitudes of major geologic units were compiled and used to develop a three-dimensional hydrogeologic framework of the aquifer system, including aquifers and confining units. Lithologic data from deep boreholes and previous aquifer-test results were used to estimate the three-dimensional distribution of hydraulic conductivity in principal aquifers. Natural recharge from precipitation was estimated for 2005–15 using a modified Thornthwaite-Mather methodology as implemented in a soil-water balance model. Components of anthropogenic recharge—wastewater return flow, storm water inflow, and inflow from leaky infrastructure—also were estimated for 2005–15. Groundwater withdrawals for various sources, including public water supply, industrial, remediation, and agricultural, were compiled or estimated for the same period.</p><p>These data were incorporated into the model development to represent the aquifer system geometry, boundaries, and initial hydraulic properties of the regional aquifers and confining units within the Long Island aquifer system. Average hydraulic conditions—water levels and streamflows—for 2005–15 were estimated using existing data from the U.S. Geological Survey National Water Information System database. Model inputs were adjusted to best match average hydrologic conditions using inverse methods as implemented in the parameter-estimating software PEST. The calibrated model was used to simulate average hydrologic conditions in the aquifer system for 2005–15.</p><p>About 656 cubic feet per second of water was withdrawn on average annually for 2005–15 for water supply and an average of about 349 cubic feet per second of water recharged the aquifer annually from return flow and leaky infrastructure. Parts of New York City have drawdowns exceeding 25 feet, mostly because of urbanization and associated large decreases in recharge rates. Large areas in the western part of the island have drawdowns exceeding 10 feet, mostly from large groundwater withdrawals and sewering, which largely eliminates wastewater return flow. Water-table altitudes in eastern parts of the island increased by more than 2 feet in some areas as a result of wastewater return flow in unsewered areas and changes in land use. Changes in streamflows show a similar pattern as water-table altitudes. Streamflows generally decrease in western parts of the island where there are large drawdowns and increase in eastern parts of the island where water-table altitudes increase.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205091","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Walter, D.A., Masterson, J.P., Finkelstein, J.S., Monti, J., Jr., Misut, P.E., and Fienen, M.N., 2020, Simulation of groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15: U.S. Geological Survey Scientific Investigations Report 2020–5091, 75 p., https://doi.org/10.3133/sir20205091.","productDescription":"Report: ix, 75 p.; 3 Data Releases","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-112206","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":381521,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5091/images/"},{"id":381195,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5091/sir20205091.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5091"},{"id":381194,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5091/coverthb2.jpg"},{"id":381192,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P954DLLC","text":"USGS data release","linkHelpText":"Aquifer texture data describing the Long Island aquifer system"},{"id":381191,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KWQSEJ","text":"USGS data release","linkHelpText":"MODFLOW–NWT and MODPATH6 used to simulate groundwater flow in the regional aquifer system on Long Island, New York, for pumping and recharge conditions in 2005–15"},{"id":381190,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90B6OTX","text":"USGS data release","linkHelpText":"Time domain electromagnetic surveys collected to estimate the extent of saltwater intrusion in Nassau and Queens Counties, New York, October-November 2017"},{"id":381520,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5091/sir20205091.XML"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.102783203125,\n              40.55554790286311\n            ],\n            [\n              -73.7017822265625,\n              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        ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ nweng@usgs.gov\" data-mce-href=\"mailto:dc_ nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Data Compilation and Analysis</li><li>Development and Calibration of the Numerical Model</li><li>Simulation of Groundwater Flow</li><li>Limitations of Analysis</li><li>Summary</li><li>Selected References</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-12-16","noUsgsAuthors":false,"publicationDate":"2020-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Walter, Donald A. 0000-0003-0879-4477 dawalter@usgs.gov","orcid":"https://orcid.org/0000-0003-0879-4477","contributorId":1101,"corporation":false,"usgs":true,"family":"Walter","given":"Donald","email":"dawalter@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masterson, John P. 0000-0003-3202-4413 jpmaster@usgs.gov","orcid":"https://orcid.org/0000-0003-3202-4413","contributorId":150532,"corporation":false,"usgs":true,"family":"Masterson","given":"John P.","email":"jpmaster@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":806664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finkelstein, Jason S. 0000-0002-7496-7236","orcid":"https://orcid.org/0000-0002-7496-7236","contributorId":202452,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Jason S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monti 0000-0001-9389-5891 jmonti@usgs.gov","orcid":"https://orcid.org/0000-0001-9389-5891","contributorId":174700,"corporation":false,"usgs":true,"family":"Monti","email":"jmonti@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806666,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Misut, Paul E. 0000-0002-6502-5255 pemisut@usgs.gov","orcid":"https://orcid.org/0000-0002-6502-5255","contributorId":1073,"corporation":false,"usgs":true,"family":"Misut","given":"Paul","email":"pemisut@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":806668,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70219092,"text":"70219092 - 2020 - Environmental contamination and unusual snake mortality in an urban national wildlife refuge","interactions":[],"lastModifiedDate":"2021-03-23T13:02:13.658097","indexId":"70219092","displayToPublicDate":"2020-12-16T07:58:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"title":"Environmental contamination and unusual snake mortality in an urban national wildlife refuge","docAbstract":"The National Wildlife Refuge (NWR) System protects ~150 million acres of land and water in the United States and provides habitat for >2,000 native vertebrates species. Although legally protected, wildlife populations within these refuges can be threatened by anthropogenic activities. The lack of knowledge about such threats has the potential to undermine biodiversity conservation. \nWe investigated patterns of wildlife mortality among three NWRs in the northern U.S. Gulf Coast. Visual surveys (958 total search-hours) were conducted for live or dead amphibians and reptiles at Big Branch, Bogue Chitto, and Bayou Sauvage NWRs. An exceptionally high incidence of snake mortality (>800% above background, P < 0.001) was observed at one site (Haul Road, Bayou Sauvage NWR). Mortality affected seven species and recurred for 29 months. Intact carcasses were subject to histopathological examination and diagnostic testing. Cause of death was undetermined (n = 9) or attributed to various pathogens (n = 5). \nTo investigate possible underlying causes of this unusual mortality, water exposure challenges and soil toxicological analyses (n = 6 and 11 sites, respectively) were conducted on samples from Bayou Sauvage NWR, given the known potential for anthropogenic contamination in the refuge.\nIn a controlled experiment, survival of Anaxyrus fowlerii embryos exposed to water from Recovery Road (i.e., 250m from a landfill) and Haul Road was reduced 92% and 48%, respectively, compared to four reference sites in the refuge.  \nSediment analyses suggested at least seven distinct sources of contaminants in Bayou Sauvage NWR. Potential sources included a landfill, illegal dumping, vehicle emissions, pesticide migration, and an active hydrocarbon pipeline leak discovered 600 m from Haul Road.\nSynthesis and applications: Although further research is needed to determine whether the observed mortality and contamination are related, these collective findings suggest that anthropogenic factors may threaten the ecological integrity of one of the United States largest urban wildlife refuges. More broadly, our study highlights the critical need for species inventories, baseline data, and systematic monitoring in NWRs. Such information is essential to detecting and mitigating anthropogenic threats to biodiversity conservation in protected areas.","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Terrell, K.A., Ballmann, A., Brown, A., Childers, C., Knowles, S., Meredith, A., and Sparks, D., 2020, Environmental contamination and unusual snake mortality in an urban national wildlife refuge: Herpetological Conservation and Biology, v. 15, no. 3, p. 652-665.","productDescription":"14 p.","startPage":"652","endPage":"665","ipdsId":"IP-099236","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":384575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":384568,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/Volume_15/Issue_3/Terrell_etal_2020.pdf"}],"country":"United States","state":"Louisiana","otherGeospatial":"Bayou Sauvage National Wildlife Refuge, Big Branch Marsh National Wildlife Refuge, Bogue Chitto National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.01074218749999,\n              28.94086176940557\n            ],\n            [\n              -88.9617919921875,\n              28.94086176940557\n            ],\n            [\n              -88.9617919921875,\n              30.585908257485578\n            ],\n            [\n              -91.01074218749999,\n              30.585908257485578\n            ],\n            [\n              -91.01074218749999,\n              28.94086176940557\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"15","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Terrell, Kimberly A.","contributorId":255639,"corporation":false,"usgs":false,"family":"Terrell","given":"Kimberly","email":"","middleInitial":"A.","affiliations":[{"id":51622,"text":"School of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA 70803","active":true,"usgs":false}],"preferred":false,"id":812701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":812702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Ashli","contributorId":255640,"corporation":false,"usgs":false,"family":"Brown","given":"Ashli","email":"","affiliations":[{"id":51623,"text":"Mississippi State Chemical Laboratory, P.O. Box CR, Mississippi State, MS 39762","active":true,"usgs":false}],"preferred":false,"id":812703,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Childers, Christina","contributorId":255641,"corporation":false,"usgs":false,"family":"Childers","given":"Christina","email":"","affiliations":[{"id":51623,"text":"Mississippi State Chemical Laboratory, P.O. 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Box CR, Mississippi State, MS 39762","active":true,"usgs":false}],"preferred":false,"id":812706,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sparks, Darrell","contributorId":255643,"corporation":false,"usgs":false,"family":"Sparks","given":"Darrell","email":"","affiliations":[{"id":51623,"text":"Mississippi State Chemical Laboratory, P.O. Box CR, Mississippi State, MS 39762","active":true,"usgs":false}],"preferred":false,"id":812707,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70217141,"text":"70217141 - 2020 - Ecological interfaces between land and flowing water: Themes and trends in riparian research and management","interactions":[],"lastModifiedDate":"2021-01-07T13:18:35.639856","indexId":"70217141","displayToPublicDate":"2020-12-16T07:17:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Ecological interfaces between land and flowing water: Themes and trends in riparian research and management","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>This paper provides an overview of past, present and future themes for research and management of riparian zones, often relating to papers within this<span>&nbsp;</span><i>Wetlands</i><span>&nbsp;</span>Special Feature. Riparian research expanded in the United States around 1980 with themes that recognized (1) damage from excessive livestock, or (2) damage from river damming and diversion, and (3) the beneficial capacity of riparian buffers to intercept and assimilate nutrients and other water contaminants. Research expanded globally in the 1990s, with themes including (4) plant life history requirements and (5) reliance on fluvial geomorphic dynamics that enable riparian rejuvenation. Resource managers recognized that riparian areas provide (6) rich wildlife habitats (7) along with valued ecosystem services, (8) which encouraged conservation and restoration initiatives, (9) including environmental flow regimes. Floodplains are (10) vulnerable to invasive plants and management has included biocontrol such as for<span>&nbsp;</span><i>Tamarix</i><span>&nbsp;</span>in the American Southwest. Into the twenty-first century, (11) climate change is advancing, and riparian ecosystems may be especially impacted due to the compound challenges from increasing water demand and declining summer flows. As an emerging opportunity, (12) while reservoirs submerge floodplain vegetation, reservoir deltas may support compensatory riparian wetlands. (13) Studies increasingly utilize remote sensing tools including satellite imagery, LiDAR and unmanned aircraft systems, and (14) the coordination of large data sets invites digital ecology, including artificial intelligence and machine learning. Since riparian zones are centres for human activities, (15) there are opportunities for citizen science, social media and internet applications, which will increasingly democratize riparian research and management.</p></div></div><div id=\"cobranding-and-download-availability-text\" class=\"note test-pdf-link\"><br></div>","language":"English","publisher":"Springer","doi":"10.1007/s13157-020-01392-4","usgsCitation":"Rood, S.B., Scott, M.L., Dixon, M., Gonzalez, E., Marks, C.O., Shafroth, P., and Volk, M., 2020, Ecological interfaces between land and flowing water: Themes and trends in riparian research and management: Wetlands, v. 40, no. 6, p. 1801-1811, https://doi.org/10.1007/s13157-020-01392-4.","productDescription":"11 p.","startPage":"1801","endPage":"1811","ipdsId":"IP-123954","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":381987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Rood, Stewart B.","contributorId":169010,"corporation":false,"usgs":false,"family":"Rood","given":"Stewart","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":807726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Michael L.","contributorId":204827,"corporation":false,"usgs":false,"family":"Scott","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":807727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dixon, Mark","contributorId":247476,"corporation":false,"usgs":false,"family":"Dixon","given":"Mark","affiliations":[{"id":16684,"text":"University of South Dakota","active":true,"usgs":false}],"preferred":false,"id":807728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzalez, Eduardo","contributorId":225181,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Eduardo","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":807729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marks, Christian O","contributorId":247477,"corporation":false,"usgs":false,"family":"Marks","given":"Christian","email":"","middleInitial":"O","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":807730,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":807731,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Volk, Martin 0000-0003-0064-8133","orcid":"https://orcid.org/0000-0003-0064-8133","contributorId":247479,"corporation":false,"usgs":false,"family":"Volk","given":"Martin","email":"","affiliations":[{"id":13477,"text":"Washington Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":807732,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70216908,"text":"fs20203057 - 2020 - Streamflow—Water year 2019","interactions":[],"lastModifiedDate":"2020-12-16T00:07:24.231222","indexId":"fs20203057","displayToPublicDate":"2020-12-15T15:58:48","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":"2020-3057","displayTitle":"Streamflow—Water Year 2019","title":"Streamflow—Water year 2019","docAbstract":"<p>The maps and graphs in this summary describe national streamflow conditions for water year 2019 (October 1, 2018, to September 30, 2019) in the context of streamflow ranks relative to the 90-year period of water years 1930–2019. Annual runoff in the Nation’s rivers and streams during water year 2019 (13.62 inches) was much higher than the long-term (1930–2019) mean annual runoff of 9.37 inches for the contiguous United States. Nationwide, the 2019 streamflow ranked the highest out of the 90 years.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203057","usgsCitation":"Jian, X., Wolock, D.M., Lins, H.F., and Brady, S.J., 2020, Streamflow—Water year 2019: U.S. Geological Survey Fact Sheet 2020–3057, 6 p., https://doi.org/10.3133/fs20203057.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-119900","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":381393,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3057/coverthb.jpg"},{"id":381394,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3057/fs20203057.pdf","text":"Report","size":"3.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3057"}],"country":"United 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          -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","contact":"<p><a data-mce-href=\"https://www.usgs.gov/mission-areas/water-resources\" href=\"https://www.usgs.gov/mission-areas/water-resources\">U.S. Geological Survey</a> <br>415 National Center <br>Reston, VA 20192 </p>","tableOfContents":"<ul><li>Introduction</li><li>National Overview</li><li>Regional Patterns</li><li>Seasonal Characteristics</li><li>High and Low Flows</li><li>Additional Information</li><li>References</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-12-15","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Jian, Xiaodong 0000-0002-9173-3482 xjian@usgs.gov","orcid":"https://orcid.org/0000-0002-9173-3482","contributorId":1282,"corporation":false,"usgs":true,"family":"Jian","given":"Xiaodong","email":"xjian@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":806912,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction 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":806913,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lins, Harry F. 0000-0001-5385-9247 hlins@usgs.gov","orcid":"https://orcid.org/0000-0001-5385-9247","contributorId":1505,"corporation":false,"usgs":true,"family":"Lins","given":"Harry","email":"hlins@usgs.gov","middleInitial":"F.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":806914,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brady, Steven J. 0000-0002-8527-5227 sbrady@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-5227","contributorId":4071,"corporation":false,"usgs":true,"family":"Brady","given":"Steven","email":"sbrady@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":806915,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}