{"pageNumber":"45","pageRowStart":"1100","pageSize":"25","recordCount":10954,"records":[{"id":70226808,"text":"70226808 - 2021 - Bar-tailed Godwits Limosa lapponica in Alaska: Revisiting population estimates from the staging grounds","interactions":[],"lastModifiedDate":"2021-12-14T13:24:55.071184","indexId":"70226808","displayToPublicDate":"2021-12-01T07:20:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5557,"text":"Wader Study","active":true,"publicationSubtype":{"id":10}},"title":"Bar-tailed Godwits Limosa lapponica in Alaska: Revisiting population estimates from the staging grounds","docAbstract":"<p>Bar-tailed Godwits Limosa lapponica baueri breed in Alaska and spend the nonbreeding season primarily in eastern Australia and New Zealand. Long-term declines spurred recent surveys at nonbreeding sites that yielded a revised population estimate of ~126,000 godwits. We conducted aerial surveys for Bar-tailed Godwits in 2018 and 2019 at pre-migratory staging sites in western Alaska. Counts from similar surveys in 1997 accorded with counts of baueri from the nonbreeding range. Instead of relying on observer estimates of flock sizes, we enumerated 97% of our survey totals using digital photography. Our survey results differed markedly between 2018 (39,751) and 2019 (100,926), differences that reflected a relatively late autumn survey period in 2018, when some godwits were likely to have left the area, compared to 2019. In contrast to the 1997 surveys, we found few Bar-tailed Godwits at estuaries on the Alaska Peninsula. However, we counted nearly 93,000 godwits (~92% of survey total) along ~60 km of coast at the Kuskokwim River Delta in 2019, a value constituting nearly three-quarters of the subspecies’ current population estimate. Our survey totals for 2019 were in agreement with contemporaneous counts at austral nonbreeding sites, demonstrating how aerial surveys from Alaska can provide useful insights into counts conducted elsewhere in the subspecies’ range. When combined with measures of reproductive output, estimates of seasonal survival, and dedicated studies of the movement and survival of juvenile godwits, future surveys from Alaska can further contribute to efforts to determine mechanisms of population changes in baueri Bar-tailed Godwits.</p>","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00251","usgsCitation":"Ruthrauff, D.R., Pohlen, Z., Wilson, H.M., and Johnson, J., 2021, Bar-tailed Godwits Limosa lapponica in Alaska: Revisiting population estimates from the staging grounds: Wader Study, v. 128, no. 3, p. 255-264, https://doi.org/10.18194/ws.00251.","productDescription":"10 p.","startPage":"255","endPage":"264","ipdsId":"IP-127284","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":436110,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZS5Y6N","text":"USGS data release","linkHelpText":"Aerial surveys of shorebirds at pre-migratory staging sites in western Alaska, 2018-2019"},{"id":392852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70227358,"text":"70227358 - 2021 - California deepwater investigations and groundtruthing (Cal DIG) I: Fault and shallow geohazard analysis offshore Morro Bay","interactions":[],"lastModifiedDate":"2022-01-11T13:36:26.035503","indexId":"70227358","displayToPublicDate":"2021-11-30T07:32:15","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"California deepwater investigations and groundtruthing (Cal DIG) I: Fault and shallow geohazard analysis offshore Morro Bay","docAbstract":"The California Deepwater Investigations and Groundtruthing (Cal DIG) I project focuses on the potential seafloor hazards and impacts of alternative energy infrastructure in the outer continental shelf region offshore of south-central California. This is one of three reports covering a single study area located between Monterey and Point Conception, California in federal waters outside of the State of California three nautical mile limit and in water depths of 400 to 1500 meters. The goal of this report is to provide baseline geologic interpretations of the area for the purpose of improving regional models of shallow geologic hazards and sedimentary processes. Geophysical and geological data from this project will help to address important issues associated with marine spatial planning and potential offshore infrastructure development, such as offshore floating wind turbines. Datasets covered in this report include comprehensive high-resolution sub-bottom (multi-channel and Chirp seismic reflection profiles), seafloor (bathymetry), and sampling (piston, gravity, and vibracore) data collected in 2018-2019 during a series of seven seagoing geological and geophysical surveys. Specifically, this report outlines interpretation of subsurface geologic structure from the geophysical data, details preliminary core analysis results related to fluid, gas, and sediment transport activity, provides interpretations of the current geohazards in the area, and suggests next steps for improving interpretations of geohazard processes.\n\nSpecific targets of geohazard interest in the study area are geological structures such as faults and folds, seafloor pockmarks within a large field (the Big Sur pockmark field), submarine channels, and mass wasting (slope failure) features. The vast majority of faults and other structures in the study occur within sediment and rock formations we interpret to be pre-Quaternary (older than 2.58 Myr BP), and thus we interpret that these structures are unlikely to present significant current hazard to seabed infrastructure, although we note that the numerous structures mapped in the study area may have the potential to become reactivated. Similarly, we find no new evidence of Holocene (younger than 11,650 years BP) fluid or gas advection in the Big Sur pockmark field. However, such fluid and gas hazards are currently difficult to assess, as additional analyses and sampling of existing core data is needed to better understand pockmark formation processes and potential gas accumulations we have mapped in the subsurface. Mass wasting along the eastern and western edges of the Santa Lucia Bank during earthquakes, as well as sediment transport down the Lucia Chica and San Simeon channels, are among the most significant, although still likely infrequent during the Holocene, hazards to seabed stability in the study area. Further analyses of the existing cores, including radiocarbon dating, stable isotope, and compositional analyses, are again needed to better understand the timing and sources of the numerous sand deposits found throughout the study area, which may have been transported downslope due to mass wasting and/or earthquake shaking processes.","language":"English","publisher":"Bureau of Ocean Energy Management","collaboration":"Bureau of Ocean Energy Management (BOEM), Monterey Bay Aquarium Research Institute (MBARI), National Oceanic and Atmospheric Administration (NOAA)","usgsCitation":"Walton, M.A., Paull, C.K., Cochrane, G.R., Addison, J.A., Gwiazda, R., Kennedy, D.J., Lundsten, E.M., and Papesh, A.G., 2021, California deepwater investigations and groundtruthing (Cal DIG) I: Fault and shallow geohazard analysis offshore Morro Bay, v, 47 p.","productDescription":"v, 47 p.","ipdsId":"IP-125021","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":394179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394167,"type":{"id":15,"text":"Index Page"},"url":"https://espis.boem.gov/final%20reports/BOEM_2021-044.pdf"}],"country":"United States","state":"California","otherGeospatial":"Morro Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.92651367187499,\n              35.2899081007595\n            ],\n            [\n              -120.77888488769531,\n              35.2899081007595\n            ],\n            [\n              -120.77888488769531,\n              35.40696093270201\n            ],\n            [\n              -120.92651367187499,\n              35.40696093270201\n            ],\n            [\n              -120.92651367187499,\n              35.2899081007595\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walton, Maureen A. 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L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paull, Charlie K","contributorId":271050,"corporation":false,"usgs":false,"family":"Paull","given":"Charlie","email":"","middleInitial":"K","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":830574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cochrane, Guy R. 0000-0002-8094-4583 gcochrane@usgs.gov","orcid":"https://orcid.org/0000-0002-8094-4583","contributorId":2870,"corporation":false,"usgs":true,"family":"Cochrane","given":"Guy","email":"gcochrane@usgs.gov","middleInitial":"R.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":830576,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gwiazda, Roberto","contributorId":147193,"corporation":false,"usgs":false,"family":"Gwiazda","given":"Roberto","email":"","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":830577,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kennedy, Daniel J. 0000-0002-9118-1243","orcid":"https://orcid.org/0000-0002-9118-1243","contributorId":271051,"corporation":false,"usgs":true,"family":"Kennedy","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830579,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lundsten, Eve M.","contributorId":147191,"corporation":false,"usgs":false,"family":"Lundsten","given":"Eve","email":"","middleInitial":"M.","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":830578,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Papesh, Antoinette Gabrielle 0000-0002-1704-0557","orcid":"https://orcid.org/0000-0002-1704-0557","contributorId":224642,"corporation":false,"usgs":true,"family":"Papesh","given":"Antoinette","email":"","middleInitial":"Gabrielle","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":830580,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70226518,"text":"ofr20211102 - 2021 - Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey","interactions":[],"lastModifiedDate":"2021-11-30T11:35:33.150711","indexId":"ofr20211102","displayToPublicDate":"2021-11-29T09:55:56","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1102","displayTitle":"Capacity Assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and Future Integrated Monitoring and Predictive Science at the U.S. Geological Survey","title":"Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey","docAbstract":"<h1>Executive Summary</h1><p>Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021).</p><p>Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts.</p><p>The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information.</p><p>The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are:</p><p>(1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time.</p><p>Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise.</p><p>(2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced.</p><p>Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate.</p><p>(3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts.</p><p>Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity.</p><p>The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211102","usgsCitation":"Keisman, J.L., Bristol, S., Brown, D.S., Flickinger, A.K., Gunther, G., Murdoch, P.S., Musgrove, M., Nelson, J.C., Steyer, G.D., Thomas, K.A., and Waite, I.R., 2021, Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2021-1102, 110 p., https://doi.org/10.3133/ofr20211102.","productDescription":"Report: v, 110 p.; Data Release","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-129970","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":392008,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BB5NMZ","linkHelpText":"USGS Earthmap Capacity Assessment Dataset"},{"id":392006,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1102/images"},{"id":392005,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1102/ofr20211102.xml"},{"id":392004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1102/ofr20211102.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":392003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1102/covrthb.jpg"}],"contact":"<p><a data-mce-href=\"https://www.usgs.gov/connect/staff-profiles\" href=\"https://www.usgs.gov/connect/staff-profiles\" target=\"_blank\" rel=\"noopener\">Director</a>, <br><a data-mce-href=\"https://www.usgs.gov/\" href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey&nbsp;</a> <br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Executive Summary&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Methods&nbsp;&nbsp;</li><li>Overview of Results&nbsp;&nbsp;</li><li>Key Findings, Lessons Learned, and Recommendations&nbsp;&nbsp;</li><li>Acknowledgments&nbsp;&nbsp;</li><li>References Cited&nbsp;&nbsp;</li><li>Glossary&nbsp;&nbsp;</li><li>Appendixes</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-11-29","noUsgsAuthors":false,"publicationDate":"2021-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Keisman, Jennifer L. 0000-0001-6808-9193 jkeisman@usgs.gov","orcid":"https://orcid.org/0000-0001-6808-9193","contributorId":198107,"corporation":false,"usgs":true,"family":"Keisman","given":"Jennifer","email":"jkeisman@usgs.gov","middleInitial":"L.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827176,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bristol, Sky 0000-0003-1682-4031 sbristol@usgs.gov","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":192087,"corporation":false,"usgs":true,"family":"Bristol","given":"Sky","email":"sbristol@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":827177,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, David S. 0000-0002-0917-6278 dsbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-0917-6278","contributorId":3808,"corporation":false,"usgs":true,"family":"Brown","given":"David","email":"dsbrown@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":827178,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flickinger, Allison K. 0000-0002-8638-2569 aflickinger@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-2569","contributorId":193268,"corporation":false,"usgs":true,"family":"Flickinger","given":"Allison","email":"aflickinger@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":827179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gunther, Gregory L. 0000-0002-1761-1604 ggunther@usgs.gov","orcid":"https://orcid.org/0000-0002-1761-1604","contributorId":1581,"corporation":false,"usgs":true,"family":"Gunther","given":"Gregory","email":"ggunther@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":827180,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murdoch, Peter S. 0000-0001-9243-505X pmurdoch@usgs.gov","orcid":"https://orcid.org/0000-0001-9243-505X","contributorId":2453,"corporation":false,"usgs":true,"family":"Murdoch","given":"Peter","email":"pmurdoch@usgs.gov","middleInitial":"S.","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":827181,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":223710,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827182,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nelson, John C. 0000-0002-7105-0107 jcnelson@usgs.gov","orcid":"https://orcid.org/0000-0002-7105-0107","contributorId":149361,"corporation":false,"usgs":true,"family":"Nelson","given":"John","email":"jcnelson@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":827183,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":827184,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":827185,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827186,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70226743,"text":"70226743 - 2021 - Long-term Pseudogymnoascus destructans surveillance data reveal factors contributing to pathogen presence","interactions":[],"lastModifiedDate":"2023-06-23T13:15:26.338878","indexId":"70226743","displayToPublicDate":"2021-11-25T06:49:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Long-term Pseudogymnoascus destructans surveillance data reveal factors contributing to pathogen presence","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The disease white-nose syndrome (WNS) was first recognized in upstate New York in 2006 and has since spread across much of the United States (U.S.), causing severe mortality in several North American bat species. To aid in the identification and monitoring of at-risk bat populations, we evaluate factors associated with the presence of the causative fungal agent of WNS,<span>&nbsp;</span><i>Pseudogymnoascus destructans</i><span>&nbsp;</span>(<i>Pd</i>), in the continental United States. We obtained<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>samples through hibernaculum surveys conducted from 2013 to 2020, with all samples analyzed at the U.S. Geological Survey National Wildlife Health Center. Using generalized additive models, we estimated the likelihood of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>presence under three different hypotheses: human-mediated, species-mediated, and hibernaculum type. In addition to hypothesis-related predictor variables, a subset of models included a smoothed nonseparable effect of longitude and latitude and a smoothed effect of time since study onset to account for spatial and temporal autocorrelation. Under all hypotheses, models indicated probability of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>detection is best described by the smoothed nonseparable effect of longitude and latitude and a smoothed effect of time since onset of this study. After accounting for spatial and temporal autocorrelations, only hibernaculum type significantly affected<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>presence, with mines and culverts/tunnels less likely to contain<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>compared with caves. Reduced likelihood of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>presence in mines and culverts/tunnels bodes well for bats of the western and southern United States, where use of these hibernaculum types is more common. While our findings can help guide monitoring and management efforts, the potential for long-distance dispersal combined with variation in community composition and hibernation ecology between the western and eastern United States necessitates the continued monitoring of<span>&nbsp;</span><i>Pd</i><span>&nbsp;</span>presence.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3808","usgsCitation":"Grider, J., Russell, R., Ballmann, A., and Hefley, T.J., 2021, Long-term Pseudogymnoascus destructans surveillance data reveal factors contributing to pathogen presence: Ecosphere, v. 12, no. 11, e03808, 10 p.; Data release, https://doi.org/10.1002/ecs2.3808.","productDescription":"e03808, 10 p.; Data release","ipdsId":"IP-127581","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":490086,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70233614,"text":"70233614 - 2021 - Gene expression profiles in two razor clam populations: Discerning drivers of population status","interactions":[],"lastModifiedDate":"2022-07-27T11:53:13.903306","indexId":"70233614","displayToPublicDate":"2021-11-24T06:50:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10135,"text":"Life","active":true,"publicationSubtype":{"id":10}},"title":"Gene expression profiles in two razor clam populations: Discerning drivers of population status","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">With rapidly changing marine ecosystems, shifts in abundance and distribution are being documented for a variety of intertidal species. We examined two adjacent populations of Pacific razor clams (<span class=\"html-italic\">Siliqua patula</span>) in lower Cook Inlet, Alaska. One population (east) supported a sport and personal use fishery, but this has been closed since 2015 due to declines in abundance, and the second population (west) continues to support commercial and sport fisheries. We used gene expression to investigate potential causes of the east side decline, comparing razor clam physiological responses between east and west Cook Inlet. The target gene profile used was developed for razor clam populations in Alaska based on physiological responses to environmental stressors. In this study, we identified no differences of gene expression between east and west populations, leading to two potential conclusions: (1) differences in factors capable of influencing physiology exist between the east and west and are sufficient to influence razor clam populations but are not detected by the genes in our panel, or (2) physiological processes do not account for the differences in abundance, and other factors such as predation or changes in habitat may be impacting the east Cook Inlet population.<span>&nbsp;</span></div>","language":"English","publisher":"MDPI","doi":"10.3390/life11121288","usgsCitation":"Coletti, H.A., Bowen, L., Ballachey, B., Wilson, T.L., Waters-Dynes, S.C., Booz, M., Counihan, K.L., Hollmen, T.E., and Pister, B., 2021, Gene expression profiles in two razor clam populations: Discerning drivers of population status: Life, v. 11, no. 12, 1288, 16 p., https://doi.org/10.3390/life11121288.","productDescription":"1288, 16 p.","ipdsId":"IP-136116","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":450145,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/life11121288","text":"Publisher Index Page"},{"id":404480,"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              -155.390625,\n              59.265880628258095\n            ],\n            [\n              -149.23828125,\n              59.265880628258095\n            ],\n            [\n              -149.23828125,\n              61.270232790000634\n            ],\n            [\n              -155.390625,\n              61.270232790000634\n            ],\n            [\n              -155.390625,\n              59.265880628258095\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-11-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Coletti, Heather A.","contributorId":187561,"corporation":false,"usgs":false,"family":"Coletti","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":847614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":847615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballachey, Brenda 0000-0003-1855-9171","orcid":"https://orcid.org/0000-0003-1855-9171","contributorId":264735,"corporation":false,"usgs":false,"family":"Ballachey","given":"Brenda","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":847616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Tammy L. 0000-0002-3672-8277","orcid":"https://orcid.org/0000-0002-3672-8277","contributorId":293684,"corporation":false,"usgs":true,"family":"Wilson","given":"Tammy","email":"","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":847617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":847618,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Booz, Michael","contributorId":293685,"corporation":false,"usgs":false,"family":"Booz","given":"Michael","email":"","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":847619,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Counihan, Katrina L","contributorId":293687,"corporation":false,"usgs":false,"family":"Counihan","given":"Katrina","email":"","middleInitial":"L","affiliations":[{"id":16211,"text":"Alaska SeaLife Center","active":true,"usgs":false}],"preferred":false,"id":847620,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hollmen, Tuula E.","contributorId":211728,"corporation":false,"usgs":false,"family":"Hollmen","given":"Tuula","email":"","middleInitial":"E.","affiliations":[{"id":16211,"text":"Alaska SeaLife Center","active":true,"usgs":false}],"preferred":false,"id":847621,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pister, Benjamin","contributorId":219669,"corporation":false,"usgs":false,"family":"Pister","given":"Benjamin","email":"","affiliations":[{"id":40046,"text":"Ocean Alaska Science and Learning Center, National Park Service","active":true,"usgs":false}],"preferred":false,"id":847622,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70226889,"text":"70226889 - 2021 - Crustal seismic attenuation of the central United States and Intermountain West","interactions":[],"lastModifiedDate":"2021-12-20T12:49:32.93433","indexId":"70226889","displayToPublicDate":"2021-11-23T06:47:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Crustal seismic attenuation of the central United States and Intermountain West","docAbstract":"<div class=\"article-section__content en main\"><p>Seismic attenuation is generally greater in the western United States (WUS) than the central and eastern United States (CEUS), but the nature of this transition or location of this boundary is poorly constrained. We conduct crustal seismic (Lg) attenuation tomography across a region that stretches from the CEUS across the Rocky Mountains to the Basin and Range using a total of 115,870 amplitude measurements from 106 earthquakes recorded on 544 stations across five frequency bands spanning 0.5–16&nbsp;Hz. Similar to previous studies, we find higher attenuation in the WUS (<i>Q</i><sub>0</sub>&nbsp;∼&nbsp;190) than the nominally CEUS (<i>Q</i><sub>0</sub>&nbsp;∼&nbsp;250) and comparatively high attenuation on the Gulf Coast (<i>Q</i><sub>0</sub>&nbsp;∼&nbsp;175). Our models defy simple east versus west regionalization, however. Heterogeneity within the Rocky Mountain region—low attenuation in the Colorado Plateau interior and Wyoming Craton (<i>Q</i><sub>0</sub>&nbsp;∼&nbsp;230) compared to high attenuation in the southern Rockies (<i>Q</i><sub>0</sub>&nbsp;∼&nbsp;110)—exceeds the gross differences between the CEUS and western United States. These province-scale patterns are readily interpreted in terms of intrinsic attenuation. The boundary between the Colorado Plateau and Basin and Range hosts the highest attenuation imaged in the study area (<i>Q</i><sub>0</sub>&nbsp;∼&nbsp;90), consistent with localized scattering across contrasting crustal structure. Focused high attenuation in the southern Rockies may represent the effects of represent<span>&nbsp;</span><i>in situ</i><span>&nbsp;</span>partial crustal melt. Within the CEUS, second-order bands of comparatively high attenuation align with the Proterozoic Yavapai-Mazatzal suture zone and Midcontinent Rift. This complex attenuation structure defies broad regionalization and suggests a need for path-specific models near these boundaries and for critical infrastructure.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JB022097","usgsCitation":"Levandowski, W., Boyd, O.S., AbdelHameid, D., and McNamara, D., 2021, Crustal seismic attenuation of the central United States and Intermountain West: Journal of Geophysical Research: Solid Earth, v. 126, no. 12, e2021JB022097, 22 p., https://doi.org/10.1029/2021JB022097.","productDescription":"e2021JB022097, 22 p.","ipdsId":"IP-128679","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":393092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.89453125,\n              25.24469595130604\n            ],\n            [\n              -91.23046875,\n              25.24469595130604\n            ],\n            [\n              -91.23046875,\n              49.439556958940855\n            ],\n            [\n              -116.89453125,\n              49.439556958940855\n            ],\n            [\n              -116.89453125,\n              25.24469595130604\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"126","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Levandowski, Will 0000-0003-4903-5012","orcid":"https://orcid.org/0000-0003-4903-5012","contributorId":218205,"corporation":false,"usgs":false,"family":"Levandowski","given":"Will","affiliations":[{"id":37163,"text":"Colorado College","active":true,"usgs":false}],"preferred":false,"id":828655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":828656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"AbdelHameid, Danya","contributorId":270201,"corporation":false,"usgs":false,"family":"AbdelHameid","given":"Danya","email":"","affiliations":[{"id":56106,"text":"The College of William and Mary","active":true,"usgs":false}],"preferred":false,"id":828657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNamara, Daniel 0000-0001-6860-0350","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":265165,"corporation":false,"usgs":false,"family":"McNamara","given":"Daniel","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":828658,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70256774,"text":"70256774 - 2021 - Comparing harvest management alternatives for Eastern Wild Turkeys in Alabama","interactions":[],"lastModifiedDate":"2024-09-06T15:53:28.030104","indexId":"70256774","displayToPublicDate":"2021-11-19T10:48:39","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"137-2021","title":"Comparing harvest management alternatives for Eastern Wild Turkeys in Alabama","docAbstract":"<p>Eastern wild turkey (<i>Meleagris gallopavo silvestris</i>; hereafter turkey) is an important game species that is pursued by thousands of Alabama hunters each spring. Biologists in Alabama and other parts of the southeastern U.S. believe that turkey populations have been declining for at least two decades. Managers in many state agencies and organizations believe that liberal spring bag limits and the timing of hunting seasons are contributing to this decline. We used an expert-driven approach to develop models of turkey populations that predicted the outcomes of spring harvest management alternatives. The models were based on recent research and expert judgement regarding the effects of spring hunting regulations on turkey vital rates. We then used the relationship between the expected spring density of adult males and expected harvest elicited from experts to compare the values of the alternatives over a 30-year period. Our model suggests that if later opening dates result in increased turkey productivity and increased harvest, the result will be larger turkey populations, increased harvest, and greater value to stakeholders. In 84% of deterministic projections from 27,951 different initial populations, the highest valued alternative was to open seasons later, reduce bag limits, and shorten the season. This alternative also was best in 48% of projections that included parametric uncertainty. These results were used to produce a decision-support tool, that could be used to guide decisions about spring hunting regulations for turkeys in Alabama, and updated using the results of monitoring programs. Further research is needed to more precisely estimate the causes and effects of spring hunting seasons on turkey vital rates.</p>","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Grand, J.B., Silvano, A., Barnett, S., Moore, C., and Stewart, B., 2021, Comparing harvest management alternatives for Eastern Wild Turkeys in Alabama: Cooperator Science Series 137-2021, ii, 37 p.","productDescription":"ii, 37 p.","ipdsId":"IP-125260","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432130,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/comparing-harvest-management-alternatives-eastern-wild-turkeys-alabama","linkFileType":{"id":5,"text":"html"}},{"id":433564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70220289,"text":"70220289 - 2021 - Arctic Alaska Basin, Hanna Trough and Beaufortian Rifted Margin Composite Tectono-Sedimentary Elements","interactions":[],"lastModifiedDate":"2025-02-04T16:09:58.361136","indexId":"70220289","displayToPublicDate":"2021-11-17T10:04:25","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Arctic Alaska Basin, Hanna Trough and Beaufortian Rifted Margin Composite Tectono-Sedimentary Elements","docAbstract":"The Arctic Alaska Composite Tectono-Sedimentary Element (AA CTSE) as defined for this volume comprises Mississippian to Lower Cretaceous strata beneath the Alaska North Slope and the Beaufort and Chukchi Seas of the Arctic Ocean. The AA CTSE rests on Devonian and older sedimentary and metasedimentary rocks, considered economic basement for petroleum, and is overlain by Cretaceous to Cenozoic syntectonic strata deposited in the foreland of the Chukotka and Brooks Range orogens. The Mississippian – Triassic part of the AA CTSE is divided into a fold-and-thrust belt in the south and a relatively undeformed platform in the north. The Jurassic – Lower Cretaceous part of the AA CTSE is divided into synrift basins in the north and rift-shoulder deposits in the south. The AA CTSE includes oil-prone source rocks in the Triassic, Jurassic, and Cretaceous and proven reservoir rocks spanning the Mississippian to Lower Cretaceous. Much of the central part of the AA CTSE lies in the oil window whereas the northern and southern parts are mainly in the gas window. Known hydrocarbon accumulations in the AA CTSE total more than 30 billion barrels of oil equivalent and yet-to-find estimates suggest a similar volume remains to be discovered","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geological Society, London, Memoirs","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"The Geological Society of London","doi":"10.1144/m57-2018-26","usgsCitation":"Houseknecht, D.W., 2021, Arctic Alaska Basin, Hanna Trough and Beaufortian Rifted Margin Composite Tectono-Sedimentary Elements, chap. <i>of</i> Geological Society, London, Memoirs, v. 57, 18 p., https://doi.org/10.1144/m57-2018-26.","productDescription":"18 p.","ipdsId":"IP-097477","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":490072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/m57-2018-26","text":"Publisher Index Page"},{"id":481671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -136.5744800240832,\n              73.48129004791153\n            ],\n            [\n              -138.2471596101051,\n              75.08779606716953\n            ],\n            [\n              -155.01532165240496,\n              76.6720069019496\n            ],\n            [\n              -173.46045058586498,\n              72.51742405199943\n            ],\n            [\n              -166.78189271016328,\n              68.39273635171199\n            ],\n            [\n              -134.69076739237028,\n              68.41381738362409\n            ],\n            [\n              -136.5744800240832,\n              73.48129004791153\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"57","noUsgsAuthors":false,"publicationDate":"2021-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":815020,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70225532,"text":"sir20215109 - 2021 - Documentation and mapping of flooding from the January and March 2018 nor’easters in coastal New England","interactions":[],"lastModifiedDate":"2021-11-23T13:06:28.021637","indexId":"sir20215109","displayToPublicDate":"2021-11-17T07:15:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5109","displayTitle":"Documentation and Mapping of Flooding From the January and March 2018 Nor’easters in Coastal New England","title":"Documentation and mapping of flooding from the January and March 2018 nor’easters in coastal New England","docAbstract":"<p>In January and March 2018, coastal Massachusetts experienced flooding from two separate nor’easters. To put the January and March floods into historical context, the USGS computed statistical stillwater elevations. Stillwater elevations recorded in January 2018 in Boston (9.66 feet relative to the North American Vertical Datum of 1988) have an annual exceedance probability of between 2 and 1 percent (between a 50- and 100-year recurrence interval). Stillwater elevations recorded in March 2018 in Boston (9.17 feet relative to the North American Vertical Datum of 1988) have an annual exceedance probability of between 4 and 2 percent (between a 25- and 50-year recurrence interval). Flood maps show that the area inundated by the January storm is slightly more extensive than that of the March storm, reflecting the respective profiles of the two storms. On the basis of a limited dataset, the attenuation of peak water levels was estimated as a function of the hydraulic distance inland and the starting stillwater elevation computed for the flood within 0.6 foot of what was measured in the field. A simple one-dimensional model was calibrated using flood elevation data collected after the January flood, and the results of the model were validated using flood elevation data collected after the March flood to model the attenuation of the flood elevations as the storms move inland.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215109","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Lombard, P.J., Olson, S.A., Sturtevant, L.P., and Kalmon, R.D., 2021, Documentation and mapping of flooding from the January and March 2018 nor’easters in coastal New England: U.S. Geological Survey Scientific Investigations Report 2021–5109, 13 p., https://doi.org/10.3133/sir20215109.","productDescription":"Report: iv, 13 p.; Data Release","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125348","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":390667,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RINQ4B","text":"USGS data release","linkHelpText":"Data and shapefiles used to document the floods associated with the January and March 2018 nor’easters for coastal areas of New England"},{"id":390669,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5109/sir20215109.XML"},{"id":390668,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5109/images/"},{"id":390666,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://wim.usgs.gov/geonarrative/newenglandnoreaster2018dashboard","text":"USGS web page","linkHelpText":"- Nor’easter storm events in coastal New England—January 4 and March 2–4, 2018"},{"id":390665,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://wim.usgs.gov/geonarrative/newenglandnoreaster2018","text":"USGS web page","linkHelpText":"- The January and March 2018 nor'easters—Flood documentation and mapping of two large storm events in coastal Massachusetts"},{"id":390664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5109/sir20215109.pdf","text":"Report","size":"5.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5109"},{"id":390663,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5109/coverthb.jpg"}],"country":"United States","state":"Connecticut, Massachusetts, Maine, New Hampshire,  Rhode 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 \"}}]}","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>Abstract</li><li>Introduction</li><li>Stillwater Elevations</li><li>Mapping of Coastal Flooding</li><li>Attenuation of Flood Water-Surface Elevations</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-11-17","noUsgsAuthors":false,"publicationDate":"2021-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":203509,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sturtevant, Luke P. 0000-0001-8983-8210 lsturtevant@usgs.gov","orcid":"https://orcid.org/0000-0001-8983-8210","contributorId":4969,"corporation":false,"usgs":true,"family":"Sturtevant","given":"Luke","email":"lsturtevant@usgs.gov","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalmon, Rena D. 0000-0002-3210-3210","orcid":"https://orcid.org/0000-0002-3210-3210","contributorId":206320,"corporation":false,"usgs":true,"family":"Kalmon","given":"Rena","email":"","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825468,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70226182,"text":"70226182 - 2021 - Context dependency of disease-mediated competitive release in bat assemblages following white-nose syndrome","interactions":[],"lastModifiedDate":"2021-11-16T12:58:22.531567","indexId":"70226182","displayToPublicDate":"2021-11-14T06:56:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Context dependency of disease-mediated competitive release in bat assemblages following white-nose syndrome","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>White-nose syndrome (WNS) has caused dramatic declines of several cave-hibernating bat species in North America since 2006, which has increased the activity of non-susceptible species in some geographic areas or during times of night formerly occupied by susceptible species—indicative of disease-mediated competitive release (DMCR). Yet, this pattern has not been evaluated across multiple bat assemblages simultaneously or across multiple years since WNS onset. We evaluated whether WNS altered spatial and temporal niche partitioning in bat assemblages at four locations in the eastern United States using long-term datasets of bat acoustic activity collected before and after WNS arrival. Activity of WNS-susceptible bat species decreased by 79–98% from pre-WNS levels across the four study locations, but only one of our four study sites provided strong evidence supporting the DMCR hypothesis in bats post-WNS. These results suggest that DMCR is likely dependent on the relative difference in activity by susceptible and non-susceptible species groups pre-WNS and the relative decline of susceptible species post-WNS allowing for competitive release, as well as the amount of time that had elapsed post-WNS. Our findings challenge the generality of WNS-mediated competitive release between susceptible and non-susceptible species and further highlight declining activity of some non-susceptible species, especially<span>&nbsp;</span><i>Lasiurus borealis</i>, across three of four locations in the eastern United States. These results underscore the broader need for conservation efforts to address the multiple potential interacting drivers of bat declines on both WNS-susceptible and non-susceptible species.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3825","usgsCitation":"Bombaci, S., Russell, R., St. Germain, M.J., Dobony, C., Ford, W., Loeb, S., and Jachowski, D., 2021, Context dependency of disease-mediated competitive release in bat assemblages following white-nose syndrome: Ecosphere, v. 12, no. 11, e03825, 15 p., https://doi.org/10.1002/ecs2.3825.","productDescription":"e03825, 15 p.","ipdsId":"IP-111761","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":450204,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecs2.3825","text":"External Repository"},{"id":391739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Bombaci, Sara","contributorId":268816,"corporation":false,"usgs":false,"family":"Bombaci","given":"Sara","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":826736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":826740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"St. Germain, Michael J.","contributorId":25959,"corporation":false,"usgs":false,"family":"St. Germain","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":826737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dobony, Christopher A.","contributorId":264897,"corporation":false,"usgs":false,"family":"Dobony","given":"Christopher A.","affiliations":[{"id":54576,"text":"DoD","active":true,"usgs":false}],"preferred":false,"id":826741,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":826738,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loeb, Susan","contributorId":204263,"corporation":false,"usgs":false,"family":"Loeb","given":"Susan","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":826739,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jachowski, David S.","contributorId":228814,"corporation":false,"usgs":false,"family":"Jachowski","given":"David S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":826742,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70226147,"text":"70226147 - 2021 - Recent nitrogen storage and accumulation rates in mangrove soils exceed historic rates in the urbanized San Juan Bay Estuary (Puerto Rico, United States)","interactions":[],"lastModifiedDate":"2021-11-15T12:30:33.841543","indexId":"70226147","displayToPublicDate":"2021-11-12T06:27:15","publicationYear":"2021","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":"Recent nitrogen storage and accumulation rates in mangrove soils exceed historic rates in the urbanized San Juan Bay Estuary (Puerto Rico, United States)","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb0\">Tropical mangrove forests have been described as “coastal kidneys,” promoting sediment deposition and filtering contaminants, including excess nutrients. Coastal areas throughout the world are experiencing increased human activities, resulting in altered geomorphology, hydrology, and nutrient inputs. To effectively manage and sustain coastal mangroves, it is important to understand nitrogen (N) storage and accumulation in systems where human activities are causing rapid changes in N inputs and cycling. We examined N storage and accumulation rates in recent (1970 – 2016) and historic (1930 – 1970) decades in the context of urbanization in the San Juan Bay Estuary (SJBE, Puerto Rico), using mangrove soil cores that were radiometrically dated. Local anthropogenic stressors can alter N storage rates in peri-urban mangrove systems either directly by increasing N soil fertility or indirectly by altering hydrology (e.g., dredging, filling, and canalization). Nitrogen accumulation rates were greater in recent decades than historic decades at Piñones Forest and Martin Peña East. Martin Peña East was characterized by high urbanization, and Piñones, by the least urbanization in the SJBE. The mangrove forest at Martin Peña East fringed a poorly drained canal and often received raw sewage inputs, with N accumulation rates ranging from 17.7 to 37.9 g m<sup>–2</sup><span>&nbsp;</span>y<sup>–1</sup><span>&nbsp;</span>in recent decades. The Piñones Forest was isolated and had low flushing, possibly exacerbated by river damming, with N accumulation rates ranging from 18.6 to 24.2 g m<sup>–2</sup><span>&nbsp;</span>y<sup>–1</sup><span>&nbsp;</span>in recent decades. Nearly all (96.3%) of the estuary-wide mangrove N (9.4 Mg ha<sup>–1</sup>) was stored in the soils with 7.1 Mg ha<sup>–1</sup><span>&nbsp;</span>sequestered during 1970–2017 (0–18 cm) and 2.3 Mg ha<sup>–1</sup><span>&nbsp;</span>during 1930–1970 (19–28 cm). Estuary-wide mangrove soil N accumulation rates were over twice as great in recent decades (0.18 ± 0.002 Mg ha<sup>–1</sup>y<sup>–1</sup>) than historically (0.08 ± 0.001 Mg ha<sup>–1</sup>y<sup>–1</sup>). Nitrogen accumulation rates in SJBE mangrove soils in recent times were twofold larger than the rate of human-consumed food N that is exported as wastewater (0.08 Mg ha<sup>–1</sup><span>&nbsp;</span>y<sup>–1</sup>), suggesting the potential for mangroves to sequester human-derived N. Conservation and effective management of mangrove forests and their surrounding watersheds in the Anthropocene are important for maintaining water quality in coastal communities throughout tropical regions.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/ffgc.2021.765896","usgsCitation":"Wigand, C., Oczkowski, A., Branoff, B., Eagle, M.J., Hanson, A., Martin, R.M., Balogh, S., Miller, K., Huertas, E., Loffredo, J., and Watson, E., 2021, Recent nitrogen storage and accumulation rates in mangrove soils exceed historic rates in the urbanized San Juan Bay Estuary (Puerto Rico, United States): Frontiers in Forests and Global Change, v. 4, 765896, 16 p., https://doi.org/10.3389/ffgc.2021.765896.","productDescription":"765896, 16 p.","ipdsId":"IP-133587","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450222,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2021.765896","text":"Publisher Index Page"},{"id":391677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, San Juan Bay Estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -66.1761474609375,\n              18.357132362517966\n            ],\n            [\n              -65.93650817871094,\n              18.357132362517966\n            ],\n            [\n              -65.93650817871094,\n              18.48807496255878\n            ],\n            [\n              -66.1761474609375,\n              18.48807496255878\n            ],\n            [\n              -66.1761474609375,\n              18.357132362517966\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2021-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Wigand, Cathleen","contributorId":260715,"corporation":false,"usgs":false,"family":"Wigand","given":"Cathleen","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oczkowski, Autumn","contributorId":260719,"corporation":false,"usgs":false,"family":"Oczkowski","given":"Autumn","email":"","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Branoff, Benjamin","contributorId":216871,"corporation":false,"usgs":false,"family":"Branoff","given":"Benjamin","affiliations":[{"id":39539,"text":"University of Puerto Rico, San Juan, PR","active":true,"usgs":false}],"preferred":false,"id":826644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hanson, Alana","contributorId":260718,"corporation":false,"usgs":false,"family":"Hanson","given":"Alana","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826646,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Rose M.","contributorId":211671,"corporation":false,"usgs":false,"family":"Martin","given":"Rose","email":"","middleInitial":"M.","affiliations":[{"id":38313,"text":"Atlantic Ecology Division, Environmental Protection Agency, 27 Tarzwell Dr. Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826647,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Balogh, Stephen","contributorId":260716,"corporation":false,"usgs":false,"family":"Balogh","given":"Stephen","email":"","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826648,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Kenneth","contributorId":260717,"corporation":false,"usgs":false,"family":"Miller","given":"Kenneth","affiliations":[{"id":52655,"text":"General Dynamics Information Technology, 6361 Walker Lane, Suite 300 Alexandria, VA","active":true,"usgs":false}],"preferred":false,"id":826649,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huertas, Evelyn","contributorId":260720,"corporation":false,"usgs":false,"family":"Huertas","given":"Evelyn","email":"","affiliations":[{"id":52656,"text":"US EPA, Caribbean Environmental Protection Division, Guaynabo, PR","active":true,"usgs":false}],"preferred":false,"id":826650,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Loffredo, Joseph","contributorId":260721,"corporation":false,"usgs":false,"family":"Loffredo","given":"Joseph","email":"","affiliations":[{"id":52652,"text":"US EPA, Atlantic Coastal Environmental Sciences Division, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":826651,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Watson, Elizabeth","contributorId":260722,"corporation":false,"usgs":false,"family":"Watson","given":"Elizabeth","affiliations":[{"id":52657,"text":"Department of Biodiversity, Earth & Environmental Sciences and The Academy of Natural Sciences, Drexel University, 1900 Benjamin Franklin Pkwy, Philadelphia, PA,","active":true,"usgs":false}],"preferred":false,"id":826652,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70228954,"text":"70228954 - 2021 - Food habits of American Kestrels in the Southern High Plains of Texas","interactions":[],"lastModifiedDate":"2022-02-25T12:33:54.81349","indexId":"70228954","displayToPublicDate":"2021-11-09T06:31:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Food habits of American Kestrels in the Southern High Plains of Texas","docAbstract":"<div class=\"div0\"><div class=\"row ArticleContentRow\"><p id=\"ID0EF\" class=\"first\">The American Kestrel (<i>Falco sparverius</i>) is in general decline across its North American distribution. In contrast to widespread patterns of decline, kestrel populations appear stable in the southern Great Plains region. Historically, this region had a very low occurrence of kestrels, and their current abundance is highly likely due to vegetation and structures associated with settlement by people of European descent. To determine prey use by breeding kestrels, we placed motion-activated video cameras at preexisting kestrel nest boxes located in the Southern High Plains in 2017. We recorded over 4200 prey deliveries during 1748 hr of observation at five nests over the 4-wk brood-rearing period. On basis of frequency, these deliveries were dominated by reptiles (74.8%), with invertebrates (18.2%), mammals (4.4%), birds (2.9%), and unidentified (1.2%) prey used to lesser extents. Prey delivery rates were high relative to other studies; across the brood-rearing period we recorded an average of 2.3 deliveries/hr, equating to an average of 0.49 deliveries and 3.85 g of prey/nestling/hr. Because invertebrates dominate the diet reported in most kestrel food habit studies, the volume of reptiles captured as prey was unexpected. Even more unanticipated was the number of large prey captured, including juvenile eastern cottontails (<i>Sylvilagus floridanus</i>) and ground squirrels (<i>Ictidomys tridecemlineatus</i>,<span>&nbsp;</span><i>Xerospermophilus spilosoma</i>). We suspect the proportion of vertebrate prey captured during the nesting season may explain the local high rates of nesting success and number of young fledged.</p></div></div>","language":"English","publisher":"BioOne","doi":"10.3356/JRR-20-75","usgsCitation":"Boal, C.W., Thornely, M., and Mullican, S., 2021, Food habits of American Kestrels in the Southern High Plains of Texas: Journal of Raptor Research, v. 55, no. 4, p. 574-583, https://doi.org/10.3356/JRR-20-75.","productDescription":"10 p.","startPage":"574","endPage":"583","ipdsId":"IP-119424","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Southern High Plains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.4033203125,\n              32.69486597787505\n            ],\n            [\n              -99.1845703125,\n              32.69486597787505\n            ],\n            [\n              -99.1845703125,\n              36.98500309285596\n            ],\n            [\n              -103.4033203125,\n              36.98500309285596\n            ],\n            [\n              -103.4033203125,\n              32.69486597787505\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"55","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":836023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thornely, M.A.","contributorId":280096,"corporation":false,"usgs":false,"family":"Thornely","given":"M.A.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":836024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullican, S.D.","contributorId":280097,"corporation":false,"usgs":false,"family":"Mullican","given":"S.D.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":836025,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70225704,"text":"ofr20211100 - 2021 - Shoreface and Holocene sediment thickness offshore of Rockaway Peninsula, New York","interactions":[],"lastModifiedDate":"2022-04-14T16:03:17.800312","indexId":"ofr20211100","displayToPublicDate":"2021-11-05T13:15:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1100","displayTitle":"Shoreface and Holocene Sediment Thickness Offshore of Rockaway Peninsula, New York","title":"Shoreface and Holocene sediment thickness offshore of Rockaway Peninsula, New York","docAbstract":"<p>During September and October 2019, the U.S. Geological Survey mapped the shoreface and inner continental shelf offshore of the Rockaway Peninsula in New York using high-resolution chirp seismic reflection and single-beam bathymetry geophysical techniques. The results from this study are important for assessing the Quaternary evolution of the Rockaway Peninsula and determining coastal sediment availability, which is crucial for establishing sediment budgets, understanding sediment dispersal, and managing coastlines. This report presents preliminary interpretations of seismic profiles and maps of shoreface and Holocene sediment thickness from the shoreline to about 2 kilometers offshore. The results indicate that shoreface and Holocene sediment thickness demonstrates zonal variability because of underlying geology and sediment availability. Based on geomorphic features and underlying stratigraphy, the study area is separated into west, west-central, east-central, and east zones. Holocene sediment, which includes the shoreface and seafloor features with positive morphology (for example, nearshore bars, ebb-tide deltas, and sorted bedforms), thickens to the west and may be related to accommodation and westward dip of the regional unconformity. Shoreface units, which are thought to represent the active volume of littoral sediment, are thickest in the west-central peninsula where the geologic base of the shoreface is deeper. Shoreface units with moderate thickness are in the western and eastern peninsula where there are positive morphological features (for example, deposits accumulating updrift from the jetty, ebb-tide deltas, and so on). The thinnest shorefaces are in the east-central Rockaway Peninsula because of less accommodation caused by the shoaling regional unconformity.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211100","collaboration":"Prepared in cooperation with the National Fish and Wildlife Foundation","usgsCitation":"Wei, E.A., Miselis, J.L., and Forde, A.S., 2021, Shoreface and Holocene sediment thickness offshore of Rockaway Peninsula, New York: U.S. Geological Survey Open-File Report 2021–1100, 14 p., https://doi.org/10.3133/ofr20211100.","productDescription":"Report: iv, 14 p.; 2 Data Releases","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125818","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":391426,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211100/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":391345,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1100/images/"},{"id":391343,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZO8QKJ","linkHelpText":"Archive of chirp subbottom profile data collected in 2019 from Rockaway Peninsula, New York"},{"id":391346,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.XML"},{"id":391344,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WNJSFN","linkHelpText":"Coastal bathymetry and backscatter data collected in September and October 2019 from Rockaway Peninsula, New York"},{"id":391342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.pdf","text":"Report","size":"11.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1100"},{"id":391341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1100/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Rockaway Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.76152038574219,\n              40.57067539946112\n            ],\n            [\n              -73.74229431152344,\n              40.593620934177494\n            ],\n            [\n              -73.76083374023438,\n              40.59414233212419\n            ],\n            [\n              -73.82469177246094,\n              40.58527801407785\n            ],\n            [\n              -73.8885498046875,\n              40.563372896916164\n            ],\n            [\n              -73.92974853515625,\n              40.549287249082035\n            ],\n            [\n              -73.94622802734375,\n              40.53937335015618\n            ],\n            [\n              -73.9441680908203,\n              40.529979881843865\n            ],\n            [\n              -73.92974853515625,\n              40.526326510744006\n            ],\n            [\n              -73.883056640625,\n              40.53311118427234\n            ],\n            [\n              -73.83018493652344,\n              40.54772199417569\n            ],\n            [\n              -73.77388000488281,\n              40.56389453066509\n            ],\n            [\n              -73.76152038574219,\n              40.57067539946112\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/spcmsc\" data-mce-href=\"https://www.usgs.gov/centers/spcmsc\">St. Petersburg Coastal and Marine Science Center</a><br>U.S. Geological Survey<br>600 4th Street South<br>St. Petersburg, FL 33701</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Regional Geologic Setting</li><li>Data Collection and Processing</li><li>Seismic Stratigraphy</li><li>Discussion</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2021-11-05","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Wei, Emily A. 0000-0003-4008-0933","orcid":"https://orcid.org/0000-0003-4008-0933","contributorId":223488,"corporation":false,"usgs":true,"family":"Wei","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826344,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70226820,"text":"70226820 - 2021 - Testing models of Laramide orogenic initiation by investigation of Late Cretaceous magmatic-tectonic evolution of the central Mojave sector of the California arc","interactions":[],"lastModifiedDate":"2021-12-14T12:55:19.654772","indexId":"70226820","displayToPublicDate":"2021-11-05T06:53:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Testing models of Laramide orogenic initiation by investigation of Late Cretaceous magmatic-tectonic evolution of the central Mojave sector of the California arc","docAbstract":"<p>The Mojave Desert region is in a critical position for assessing models of Laramide orogenesis, which is hypothesized to have initiated as one or more seamounts subducted beneath the Cretaceous continental margin. Geochronological and geochemical characteristics of Late Cretaceous magmatic products provide the opportunity to test the validity of Laramide orogenic models. Laramide-aged plutons are exposed along a transect across the Cordilleran Mesozoic magmatic system from Joshua Tree National Park in the Eastern Transverse Ranges eastward into the central Mojave Desert. A transect at latitude ∼33.5°N to 34.5°N includes: (1) the large upper-crustal Late Cretaceous Cadiz Valley batholith, (2) a thick section of Proterozoic to Jurassic host rocks, (3) Late Cretaceous stock to pluton-sized bodies at mesozonal depths, and (4) a Jurassic to Late Cretaceous midcrustal sheeted complex emplaced at ∼20 km depth that transitions into a migmatite complex truncated along the San Andreas fault. This magmatic section is structurally correlative with the Big Bear Lake intrusive suite in the San Bernardino Mountains and similar sheeted rocks recovered in the Cajon Pass Deep Scientific Drillhole.</p><p>Zircon U-Pb geochronology of 12 samples via secondary ionization mass spectrometry (SIMS) (six from the Cadiz Valley batholith and six from the Cajon Pass Deep Scientific Drillhole) indicates that all Cretaceous igneous units investigated were intruded between 83 and 74 Ma, and Cajon Pass samples include a Jurassic age component. A compilation of new and published SIMS geochronological data demonstrates that voluminous magmatism in the Eastern Transverse Ranges and central Mojave Desert was continuous throughout the period suggested for the intersection and flat-slab subduction of the Shatsky Rise conjugate deep into the interior of western North America.</p><p>Whole-rock major-element, trace-element, and isotope geochemistry data from samples from a suite of 106 igneous rocks represent the breadth of Late Cretaceous units in the transect. Geochemistry indicates an origin in a subduction environment and intrusion into a crust thick enough to generate residual garnet. The lack of significant deflections of compositional characteristics and isotopic ratios in igneous products through space and time argues against a delamination event prior to 74 Ma.</p><p>We argue that Late Cretaceous plutonism from the Eastern Transverse Ranges to the central Mojave Desert represents subduction zone arc magmatism that persisted until ca. 74 Ma. This interpretation is inconsistent with the proposed timing of the docking of the Shatsky Rise conjugate with the margin of western North America, particularly models in which the leading edge of the Shatsky Rise was beneath Wyoming at 74 Ma. Alternatively, the timing of cessation of plutonism precedes the timing of the passage of the Hess Rise conjugate beneath western North America at ca. 70–65 Ma. The presence, geochemical composition, and age of arc products in the Eastern Transverse Ranges and central Mojave Desert region must be accounted for in any tectonic model of the transition from Sevier to Laramide orogenesis.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02225.1","usgsCitation":"Economos, R., Barth, A.P., Wooden, J., Paterson, S.R., Friesenhahn, B., Weigand, B., Anderson, J., Roell, J., Palmer, E., Ianno, A., and Howard, K.A., 2021, Testing models of Laramide orogenic initiation by investigation of Late Cretaceous magmatic-tectonic evolution of the central Mojave sector of the California arc: Geosphere, v. 17, no. 6, p. 2042-2061, https://doi.org/10.1130/GES02225.1.","productDescription":"20 p.","startPage":"2042","endPage":"2061","ipdsId":"IP-114848","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450270,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02225.1","text":"Publisher Index Page"},{"id":392846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.597412109375,\n              32.98102014898148\n            ],\n            [\n              -114.5599365234375,\n              32.98102014898148\n            ],\n            [\n              -114.5599365234375,\n              35.074964853989556\n            ],\n            [\n              -118.597412109375,\n              35.074964853989556\n            ],\n            [\n              -118.597412109375,\n              32.98102014898148\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"17","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Economos, R.C","contributorId":270083,"corporation":false,"usgs":false,"family":"Economos","given":"R.C","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":828384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Andrew P.","contributorId":214136,"corporation":false,"usgs":false,"family":"Barth","given":"Andrew","email":"","middleInitial":"P.","affiliations":[{"id":38983,"text":"Indiana University - Purdue University","active":true,"usgs":false}],"preferred":false,"id":828385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wooden, J.L.","contributorId":192664,"corporation":false,"usgs":false,"family":"Wooden","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":828386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paterson, S. 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,{"id":70227100,"text":"70227100 - 2021 - Monitoring and modeling tree bat (Genera: Lasiurus, Lasionycteris) occurrence using acoustics on structures off the mid-Atlantic coast—Implications for offshore wind development","interactions":[],"lastModifiedDate":"2021-12-29T14:27:45.567844","indexId":"70227100","displayToPublicDate":"2021-11-04T08:17:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring and modeling tree bat (Genera: Lasiurus, Lasionycteris) occurrence using acoustics on structures off the mid-Atlantic coast—Implications for offshore wind development","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">In eastern North America, “tree bats” (Genera:<span>&nbsp;</span><span class=\"html-italic\">Lasiurus</span><span>&nbsp;</span>and<span>&nbsp;</span><span class=\"html-italic\">Lasionycteris</span>) are highly susceptible to collisions with wind energy turbines and are known to fly offshore during migration. This raises concern about ongoing expansion of offshore wind-energy development off the Atlantic Coast. Season, atmospheric conditions, and site-level characteristics such as local habitat (e.g., forest coverage) have been shown to influence wind turbine collision rates by bats onshore, and therefore may be related to risk offshore. Therefore, to assess the factors affecting coastal presence of bats, we continuously gathered tree bat occurrence data using stationary acoustic recorders on five structures (four lighthouses on barrier islands and one light tower offshore) off the coast of Virginia, USA, across all seasons, 2012–2019. We used generalized additive models to describe tree bat occurrence on a nightly basis. We found that sites either indicated maternity or migratory seasonal occurrence patterns associated with local roosting resources, i.e., presence of trees. Across all sites, nightly occurrence was negatively related to wind speed and positively related to temperature and visibility. Using predictive performance metrics, we concluded that our model was highly predictive for the Virginia coast. Our findings were consistent with other studies—tree bat occurrence probability and presumed mortality risk to offshore wind-energy collisions is highest on low wind speed nights, high temperature and visibility nights, and during spring and fall. The high predictive model performance we observed provides a basis for which managers, using a similar monitoring and modeling regime, could develop an effective curtailment-based mitigation strategy.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/ani11113146","usgsCitation":"True, M., Reynolds, R., and Ford, W., 2021, Monitoring and modeling tree bat (Genera: Lasiurus, Lasionycteris) occurrence using acoustics on structures off the mid-Atlantic coast—Implications for offshore wind development: Animals, v. 11, no. 11, 3146, 18 p., https://doi.org/10.3390/ani11113146.","productDescription":"3146, 18 p.","ipdsId":"IP-133484","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":450276,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani11113146","text":"Publisher Index Page"},{"id":393573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.10504150390625,\n              37.05736900011469\n            ],\n            [\n              -75.22613525390625,\n              37.05736900011469\n            ],\n            [\n              -75.22613525390625,\n              38.02213147353745\n            ],\n            [\n              -76.10504150390625,\n              38.02213147353745\n            ],\n            [\n              -76.10504150390625,\n              37.05736900011469\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"True, Michael C.","contributorId":270631,"corporation":false,"usgs":false,"family":"True","given":"Michael C.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":829630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reynolds, Richard J.","contributorId":270633,"corporation":false,"usgs":false,"family":"Reynolds","given":"Richard J.","affiliations":[{"id":56188,"text":"Virginia Department of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":829631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":829629,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70225710,"text":"70225710 - 2021 - Growth of the wildland-urban interface within and around U.S. National Forests and Grasslands, 1990-2010","interactions":[],"lastModifiedDate":"2021-11-04T13:55:02.047378","indexId":"70225710","displayToPublicDate":"2021-11-01T08:51:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2603,"text":"Landscape and Urban Planning","active":true,"publicationSubtype":{"id":10}},"title":"Growth of the wildland-urban interface within and around U.S. National Forests and Grasslands, 1990-2010","docAbstract":"<p><span>The wildland-urban interface (WUI), where housing is in close proximity to or intermingled with wildland vegetation, is widespread throughout the United States, but it is unclear how this type of housing development affects public lands. We used a national dataset to examine WUI distribution and growth (1990–2010) in proximity to National Forests and created a typology to characterize each National Forest’s combination of WUI area and housing growth. We found that National Forests are hotspots for WUI growth, with a 38% increase in WUI area and 46% growth in WUI houses from 1990 to 2010, in excess of WUI growth for the conterminous U.S. Growth within National Forests was higher than the surrounding area. Diffuse intermix WUI, where houses are intermingled with wildland vegetation, is common within National Forests, but WUI houses around National Forests were primarily in denser interface WUI areas, which lack substantial wildland vegetation. WUI was more prevalent within and around National Forests in the East, while National Forests in the West experienced higher rates of WUI growth. National Forests with the most challenging WUI issues—extensive WUI area and rapid growth in intermix and interface—were found primarily in the South and interior West. Given the diversity of WUI landscapes, effectively responding to current and future WUI challenges will require both engagement with individual homeowners dispersed throughout National Forests, as well as increased emphasis on mitigating denser interface development around National Forests. At a time when wildfire risks are expected to intensify due to climate change, and 75% of privately owned land within and around National Forests is not yet WUI, understanding WUI growth patterns in proximity to public lands is vital for land management and human well-being.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.landurbplan.2021.104283","usgsCitation":"Mockrin, M.H., Helmers, D., Martinuzzi, S., Hawbaker, T., and Radeloff, V.C., 2021, Growth of the wildland-urban interface within and around U.S. National Forests and Grasslands, 1990-2010: Landscape and Urban Planning, v. 218, 104283, 13 p., https://doi.org/10.1016/j.landurbplan.2021.104283.","productDescription":"104283, 13 p.","ipdsId":"IP-121616","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":391382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Forest Service","active":true,"usgs":false}],"preferred":false,"id":826375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helmers, Dave","contributorId":268299,"corporation":false,"usgs":false,"family":"Helmers","given":"Dave","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":826377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martinuzzi, Sebastian","contributorId":268298,"corporation":false,"usgs":false,"family":"Martinuzzi","given":"Sebastian","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":826376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawbaker, Todd 0000-0003-0930-9154 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,{"id":70225674,"text":"70225674 - 2021 - Potential effects of climate change on tick-borne diseases in Rhode Island","interactions":[],"lastModifiedDate":"2021-11-02T14:40:27.923932","indexId":"70225674","displayToPublicDate":"2021-11-01T08:13:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3295,"text":"Rhode Island Medical Journal","active":true,"publicationSubtype":{"id":10}},"title":"Potential effects of climate change on tick-borne diseases in Rhode Island","docAbstract":"Human cases of tick-borne diseases have been increasing in the United States. In particular, the incidence of Lyme disease, the major vector-borne disease in Rhode Island, has risen, along with cases of babesiosis and anaplasmosis, all vectored by the blacklegged tick. These increases might relate, in part, to climate change, although other environmental changes in the northeast (land use as it relates to habitat; vertebrate host populations for tick reproduction and enzootic cycling) also contribute. Lone star ticks, formerly southern in distribution, have been spreading northward, including expanded distributions in Rhode Island. Illnesses associated with this species include ehrlichiosis and alpha-gal syndrome, which are expected to increase. Ranges of other tick species have also been expanding in southern New England, including the Gulf Coast tick and the introduced Asian longhorned tick. These ticks can carry human pathogens, but the implications for human disease in Rhode Island are unclear.","language":"English","publisher":"Rhode Island Medical Society","usgsCitation":"Ginsberg, H., Couret, J., Garrett, J., Mather, T.N., and LeBrun, R.A., 2021, Potential effects of climate change on tick-borne diseases in Rhode Island: Rhode Island Medical Journal, v. 104, no. 9, p. 29-33.","productDescription":"5 p.","startPage":"29","endPage":"33","numberOfPages":"5","ipdsId":"IP-131427","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":391265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391253,"type":{"id":15,"text":"Index Page"},"url":"https://rimed.org/rimedicaljournal-2021-11.asp"}],"country":"United States","state":"Rhode 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,{"id":70229480,"text":"70229480 - 2021 - Northern bobwhite occupancy patterns on multiple spatial scales across Arkansas","interactions":[],"lastModifiedDate":"2022-03-09T15:02:05.293524","indexId":"70229480","displayToPublicDate":"2021-10-28T08:59:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Northern bobwhite occupancy patterns on multiple spatial scales across Arkansas","docAbstract":"<p><span>Northern bobwhite&nbsp;</span><i>Colinus virginianus</i><span>&nbsp;populations have been rapidly declining in the eastern, central, and southern United States for decades. Land use change and an incompatibility between northern bobwhite resource needs and human land use practices have driven declines. Here, we applied occupancy analyses on two spatial scales (state level and ecoregion level) to more than 5,000 northern bobwhite surveys conducted over 6 y across the entire state of Arkansas to explore patterns in occupancy and land use variables, and to identify priority areas for management and conservation. At the state level, northern bobwhite occupied 29% of sites and northern bobwhite were most likely to occur in areas with a high percentage of early successional habitat (grassland, pasture, and shrubland). The statewide model predicted that northern bobwhite were likely to occur (≥ 75% predicted occupancy) in &lt; 20% of the state. Arkansas is comprised of five distinct ecoregions, and analyses at the ecoregion spatial scale showed that habitat associations of northern bobwhite could vary between ecoregions. For example, early successional habitat best predicted northern bobwhite occupancy in both the Arkansas River Valley and Ozark Mountains ecoregions, and other habitat associations such as the proportion of herbaceous habitat and hay-pasture habitat, respectively, further refined predictions. Contrastingly, richness of land cover classes alone best predicted northern bobwhite occupancy in the Ouachita Mountains ecoregion. Ecoregion-level models were thus more discerning than the state-level model and should be more helpful to managers in identifying priority conservation areas. However, in two of five ecoregions, surveys too rarely encountered northern bobwhite to accurately predict their occurrence. We found that likely occupied northern bobwhite habitat lay primarily on private properties (95%), but that numerous public entities own and manage land identified as suitable or likely occupied. We conclude that management of northern bobwhite in Arkansas could benefit from cooperation among state, federal, and military partners, as well as surrounding private landowners and that ecoregion-specific models may be more useful in identifying priority areas for management. Our approach incorporates multiple landscape scales when using remote sensing technology in conjunction with monitoring data and could have important application for the management of northern bobwhite and other grassland bird species.</span></p>","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-21-002","usgsCitation":"Lassiter, E.V., Asher, M., Christie, G., Gale, C., Massey, A., Massery, C., MIddaugh, C., Veon, J., and DeGregorio, B.A., 2021, Northern bobwhite occupancy patterns on multiple spatial scales across Arkansas: Journal of Fish and Wildlife Management, v. 12, no. 2, p. 502-512, https://doi.org/10.3996/JFWM-21-002.","productDescription":"11 p.","startPage":"502","endPage":"512","ipdsId":"IP-125981","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450328,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-002","text":"Publisher Index 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R.","contributorId":288241,"corporation":false,"usgs":false,"family":"MIddaugh","given":"C. R.","affiliations":[{"id":37007,"text":"Arkansas Game and Fish Commission","active":true,"usgs":false}],"preferred":false,"id":837584,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veon, J.","contributorId":288245,"corporation":false,"usgs":false,"family":"Veon","given":"J.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":837585,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837586,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70225582,"text":"sir20215020 - 2021 - Geologic and hydrogeologic characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, northern greater Denver Basin, southeastern Laramie County, Wyoming","interactions":[],"lastModifiedDate":"2022-06-16T19:45:30.631881","indexId":"sir20215020","displayToPublicDate":"2021-10-27T10:00:17","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5020","displayTitle":"Geologic and Hydrogeologic Characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, Northern Greater Denver Basin, Southeastern Laramie County, Wyoming","title":"Geologic and hydrogeologic characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, northern greater Denver Basin, southeastern Laramie County, Wyoming","docAbstract":"<p>In cooperation with the Wyoming State Engineer’s Office, the U.S. Geological Survey studied the geologic and hydrogeologic characteristics of Cenozoic and Upper Cretaceous strata at a location in southeastern Laramie County within the Wyoming part of the Cheyenne Basin, the northern subbasin of the greater Denver Basin. The study aimed to improve understanding of the aquifers/aquifer systems in these strata, motivated in part by declining groundwater levels and interest in exploring future groundwater supplies. Based on detailed geologic characterization using information obtained by drilling and coring a 960-foot-(ft) deep exploratory borehole, and comparisons with previously published descriptions, identified Cenozoic lithostratigraphic units included 40 ft of Quaternary older alluvial fan deposits consisting of an unconsolidated mixture of sand and gravel with lesser quantities of silt and clay in varying proportions and the underlying 407.3-ft-thick White River Formation of late Eocene-Oligocene age consisting largely of mudrocks with sparse thin beds of sandstone, muddy gravel, and conglomeratic mudrocks. Identified Upper Cretaceous lithostratigraphic units included the 351.6-ft-thick Lance Formation, consisting of terrestrial sedimentary rocks including mudrocks (muddy shale and silty and sandy shale, siltstone, claystone, and mudstone) interbedded with much smaller quantities of very fine- to medium-grained muddy and silty sandstone and coal; the 79.6-ft-thick Fox Hills Sandstone, consisting of a transitional marine sequence of muddy or silty sandstone present in five individual beds; and 86.7 ft of the upper transition member of the Pierre Shale, consisting largely of marine sedimentary rocks such as muddy shale. Beds of the upper and lower Fox Hills Sandstone were separated by tongues of the Lance Formation and upper transition member of the Pierre Shale, respectively.</p><p>The White River hydrogeologic unit, consisting of the entire White River Formation or Group at the study site, did not contain any substantial secondary permeability features in the mudrocks that composed almost all the unit. A monitoring well (BR–1) was completed in the White River aquifer with the well screen open to the only coarse-grained unit (muddy sandstone) that had sufficient thickness and permeability to be considered as an aquifer. Sampling of the well for a broad suite of constituents indicated groundwater generally was of excellent quality except dissolved arsenic was detected at a concentration greater than the U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level, and dissolved sodium was measured at a concentration greater than several EPA Drinking Water Advisory Levels (DWAs) for the constituent. Well development, well purging for groundwater sampling, and calculated aquifer properties indicated the sandstone aquifer screened by monitoring well BR–1 was not very productive. Analysis of the well water-level responses in BR–1 to atmospheric loading and Earth tides indicated the responses were consistent with a confined-aquifer response with wellbore-storage effects. Hydraulic properties estimated based on these responses yielded values of hydraulic conductivity (<i>K</i>, 0.057 foot per day [ft/d]), specific storage (<i>Ss</i>, 1.6×10<sup>−6</sup> per foot [ft<sup>−1</sup>]) and porosity (<i>n</i>, 0.43). Water levels filtered to remove the effects of atmospheric loading and Earth tides indicated an upward trend (+1.13 foot per year [ft/yr]) during the period analyzed, September 5, 2014, to September 30, 2017.</p><p>Lithologic characteristics of the Lance hydrogeologic unit, consisting of the entire Lance Formation at the study site, indicated a potential aquifer in a “sandy” interval in the upper part of the unit. Most of the Lance hydrogeologic unit below the “sandy” interval consisted of various low-permeability lithologies unlikely to yield substantial quantities of water. This lower part of the hydrogeologic unit likely functions as a confining unit separating the underlying Lance-Fox Hills aquifer. A geologic cross section constructed for this study indicated fine-grained sediments composed most of the Lance Formation/hydrogeologic unit not only at the study location, but also throughout southern Laramie County along the line of section and throughout the Wyoming and Colorado parts of the Cheyenne Basin. A monitoring well (LN–1) completed in a sandstone bed in the “sandy” interval of the Lance hydrogeologic unit produced a mean of about 23 gallons per minute (gal/min) during well development, indicating sandstone beds can form moderately productive confined subaquifers in this part of the hydrogeologic unit. Analysis of the well water-level responses in well LN–1 to atmospheric loading and Earth tides indicated the responses were consistent with a confined-aquifer response. Hydraulic properties estimated based on these responses yielded values for a lower bounding <i>K</i> of 0.60 ft/d, <i>Ss</i> of 1.6×10<sup>−6</sup> ft<sup>−1</sup>, and <i>n</i> of 0.38. Water levels filtered to remove the effects of atmospheric loading and Earth tides indicated a downward trend (−0.86 ft/yr) during the period analyzed (November 8, 2014, to September 30, 2017). Analyses for a broad suite of constituents in samples from well LN–1 indicated groundwater quality generally was excellent, although dissolved sodium was measured at a concentration greater than two EPA DWA levels for the constituent.</p><p>Because of the absence of any overlying or intertonguing sandstone beds belonging to the lower/basal part of the Lance Formation, the Lance-Fox Hills aquifer at the study site consisted only of the five sandstone beds of the Fox Hills Sandstone. The cross section constructed for this study illustrated how the Fox Hills Sandstone, and thus, most of the Lance-Fox Hills aquifer, consists of a series of sandstone bodies that overlap (shingle) upward to the east across southern Laramie County. These bodies collectively form a fairly continuous body of sandstone, thus potentially forming an areally extensive aquifer across southern Laramie County, and by extension, throughout most of the formation’s extent in the Wyoming part of the Cheyenne Basin, as is the case in the Colorado part of the basin. A monitoring well (FH–1) completed in part of the thickest sandstone bed of the Lance-Fox Hills aquifer was moderately to highly productive and easily produced 25 to 30 gal/min after development. Substantially larger water production rates likely could be obtained by penetrating the full thickness of this bed and by completing a well open to the other overlying and underlying sandstone beds of the aquifer. Analysis of the water-level responses in well FH–1 to atmospheric loading and Earth tides indicated the responses were consistent with a confined-aquifer response. Hydraulic properties computed based on these responses yielded values for a lower bounding estimate for <i>K</i> of 0.26 ft/d, for <i>Ss</i> of 1.0×10<sup>−6</sup> ft<sup>−1</sup>, and for <i>n</i> of 0.41. Water levels filtered to remove the effects of atmospheric loading and Earth tides indicated a downward trend (−1.74 ft/yr) during the period analyzed, December 19, 2014, to September 30, 2017. Sampling of monitoring well FH–1 and two production wells completed in the Fox Hills Sandstone in other parts of Laramie County indicated groundwater quality generally is excellent, although pH exceeded a recommended EPA aesthetic drinking-water standard (Secondary Maximum Contaminant Level) in two of three sampled wells, total dissolved solids concentrations exceeded the Secondary Maximum Contaminant Level in one of the two sampled production wells, and dissolved sodium was measured in all three sampled wells at a concentration greater than two EPA DWA levels for the constituent. The Wyoming Class II agricultural (irrigation) sodium adsorption ratio standard of 8 was exceeded in all three sampled wells, indicating these waters are not suitable for irrigation use.</p><p>Computed vertical hydraulic gradients indicated a strong potential for downward flow throughout the groundwater system at the study site, including from the low-yielding aquifer in the upper White River Formation/hydrogeologic unit (monitoring well BR–1) to the sandstone subaquifer in the Lance Formation/hydrogeologic unit (monitoring well LN–1), and from the Lance subaquifer (monitoring well LN–1) to the sandstone bed/aquifer that composes much of the Lance-Fox Hills aquifer thickness at the study site (monitoring well FH–1). However, large hydraulic-head differences between wells indicated high resistance to vertical flow attributable to the low vertical hydraulic conductivity of intervening strata, which consisted almost entirely of low-permeability mudrocks. The confined nature of the sandstone aquifers monitored by the various wells coupled with dissimilarities between groundwater-level fluctuations and trends in groundwater levels indicated downward flow through the intervening strata (primarily mudrocks in the various lithostratigraphic/hydrogeologic units) between the examined sets of wells likely was small.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215020","collaboration":"Prepared in cooperation with the Wyoming State Engineer’s Office","usgsCitation":"Bartos, T.T., Galloway, D.L., Hallberg, L.L., Dechesne, M., Diehl, S.F., and Davidson, S.L., 2021, Geologic and hydrogeologic characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, northern greater Denver Basin, southeastern Laramie County, Wyoming: U.S. Geological Survey Scientific Investigations Report 2021–5020, 219 p., 1 pl., https://doi.org/10.3133/sir20215020.","productDescription":"Report: xvii, 219 p.; Appendix Table; Plate: 42.00 x 63.00 inches; Data Release; Dataset","numberOfPages":"242","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-110049","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":390939,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS groundwater data for Wyoming, in USGS water data for the Nation"},{"id":390938,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PPLA74","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Atmospheric-loading frequency response functions and groundwater levels filtered for the effects of atmospheric loading and solid Earth tides for three USGS monitoring wells, southeastern Laramie County, Wyoming, 2014–2017"},{"id":390936,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5020/sir20215020_plate.pdf","text":"Plate","size":"2.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5020 Plate","linkHelpText":"— Construction of monitoring wells BR–1, LN–1, and FH–1, and geophysical logs, generalized lithology, and interpreted lithostratigraphy for exploratory borehole LC–F1, southeastern Laramie County, Wyoming"},{"id":390937,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5020/sir20215020_table1.1.pdf","text":"Table 1.1","size":"500 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5020 Appendix Table","linkHelpText":"— Description of core collected from exploratory borehole LC–F1, southeastern Laramie County, Wyoming"},{"id":390934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5020/coverthb.jpg"},{"id":390935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5020/sir20215020.pdf","text":"Report","size":"26.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5020"}],"country":"United States","state":"Wyoming","county":"Laramie County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.6506,41.651],[-104.6491,41.5656],[-104.0521,41.5654],[-104.052,41.3949],[-104.0526,41.0236],[-104.0528,41.0017],[-104.1399,41.0019],[-104.4725,41.0027],[-104.4875,41.0027],[-104.5606,41.0028],[-104.5679,41.0028],[-104.6087,41.0046],[-104.6134,41.0048],[-104.6337,41.0056],[-104.6648,41.0047],[-104.6837,41.0041],[-104.7013,41.0035],[-104.83,40.9996],[-104.8341,40.9996],[-104.9385,40.9995],[-104.9425,40.9995],[-105.1109,40.9993],[-105.2763,40.9998],[-105.2774,41.6567],[-105.1706,41.6535],[-105.0575,41.6537],[-104.9419,41.6537],[-104.6506,41.651]]]},\"properties\":{\"name\":\"Laramie\",\"state\":\"WY\"}}]}","contact":"<p><a data-mce-href=\"mailto:%20dc_wy@usgs.gov\" href=\"mailto:%20dc_wy@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/wy-mt-water/\" href=\"https://www.usgs.gov/centers/wy-mt-water/\">Wyoming-Montana Water Science Center</a> <br>U.S. Geological Survey<br>3162 Bozeman Avenue<br>Helena, MT 59601</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Description of Study Area</li><li>Geologic Setting of Study Area</li><li>Groundwater Resources in Study Area</li><li>Methods of Study<br></li><li>Geologic Characteristics of Study Site Strata</li><li>Hydrogeologic Characteristics of Study Site Strata</li><li>Summary</li><li>References Cited</li><li>Appendix 1</li><li>Appendix 2</li><li>References Cited</li><li>Appendix 3</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-10-27","noUsgsAuthors":false,"publicationDate":"2021-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Bartos, Timothy T. 0000-0003-1803-4375 ttbartos@usgs.gov","orcid":"https://orcid.org/0000-0003-1803-4375","contributorId":1826,"corporation":false,"usgs":true,"family":"Bartos","given":"Timothy","email":"ttbartos@usgs.gov","middleInitial":"T.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":825673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":825674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallberg, Laura L. 0000-0001-9983-8003 lhallber@usgs.gov","orcid":"https://orcid.org/0000-0001-9983-8003","contributorId":1825,"corporation":false,"usgs":true,"family":"Hallberg","given":"Laura","email":"lhallber@usgs.gov","middleInitial":"L.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dechesne, Marieke 0000-0002-4468-7495","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":267950,"corporation":false,"usgs":false,"family":"Dechesne","given":"Marieke","affiliations":[],"preferred":true,"id":825676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diehl, Sharon F. diehl@usgs.gov","contributorId":1089,"corporation":false,"usgs":true,"family":"Diehl","given":"Sharon","email":"diehl@usgs.gov","middleInitial":"F.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":825677,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davidson, Seth L. 0000-0002-9548-468X sdavids@usgs.gov","orcid":"https://orcid.org/0000-0002-9548-468X","contributorId":3626,"corporation":false,"usgs":true,"family":"Davidson","given":"Seth","email":"sdavids@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":825678,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70225686,"text":"70225686 - 2021 - Telemetry reveals migratory drivers and disparate space use across seasons and age-groups in American horseshoe crabs","interactions":[],"lastModifiedDate":"2021-11-03T13:06:09.653159","indexId":"70225686","displayToPublicDate":"2021-10-27T08:03:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Telemetry reveals migratory drivers and disparate space use across seasons and age-groups in American horseshoe crabs","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Identifying mechanisms that underpin animal migration patterns and examining variability in space use within populations is crucial for understanding population dynamics and management implications. In this study, we quantified the migration rates, seasonal changes in migratory connectivity, and residency across population demographics (age and sex) to understand the proximate cues of migration timing in American horseshoe crabs (<i>Limulus polyphemus</i>). Juvenile (<i>n</i>&nbsp;=&nbsp;25) and adult (<i>n</i>&nbsp;=&nbsp;70) horseshoe crabs were tracked with acoustic telemetry techniques for a 3-yr period in Moriches Bay, NY. Connectivity metrics and residency probability were quantified through spatial network analysis and empirically derived Markov Chain models (EDMC), respectively. The migratory probability of adult horseshoe crabs between Moriches Bay and the Atlantic Ocean was estimated to be 41.0% (95% CI: 34.0–59.8); in contrast, only 8% (95% CI: 1.2–31.6) of juveniles migrated into the ocean. Migration timing was influenced by the interaction of photoperiod and temperature, revealing seasonal differences in migration timing and a 50% narrower range of photoperiod and temperature over which fall migrations occurred compared to spring. Sex-specific differences in space use and connectivity within each season were largely absent; however, centralized habitats were important for maintaining connectivity across all seasons. EDMC results revealed that when standardized to the number of horseshoe crab detections on each receiver, the centrally located habitats in Moriches Bay and Inlet accounted for &gt;50% of the total relative residency probability within most seasons, indicating these areas may be preferred by adult horseshoe crabs. Ontogenetic differences in maximum spatial extent, space use, and connectivity were observed in the bay, as juveniles exhibited lower linkages between locations (<i>n</i>&nbsp;=&nbsp;4) relative to adults (<i>n</i>&nbsp;=&nbsp;13) during the same temporal period. Our work highlights the application of novel quantitative approaches for addressing the movement dynamics of horseshoe crabs that can be readily applied to other taxa in the context of wildlife conservation.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3811","usgsCitation":"Bopp, J.J., Sclafani, M., Frisk, M.G., McKown, K., Zeigler, C., Smith, D.R., and Cerrato, R., 2021, Telemetry reveals migratory drivers and disparate space use across seasons and age-groups in American horseshoe crabs: Ecosphere, v. 12, no. 10, e03811, 22 p., https://doi.org/10.1002/ecs2.3811.","productDescription":"e03811, 22 p.","ipdsId":"IP-123155","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":450342,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3811","text":"Publisher Index Page"},{"id":391313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island, Moriches Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.8839874267578,\n              40.72540497175607\n            ],\n            [\n              -72.58186340332031,\n              40.72540497175607\n            ],\n            [\n              -72.58186340332031,\n              40.84134650558101\n            ],\n            [\n              -72.8839874267578,\n              40.84134650558101\n            ],\n            [\n              -72.8839874267578,\n              40.72540497175607\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Bopp, Justin J.","contributorId":238554,"corporation":false,"usgs":false,"family":"Bopp","given":"Justin","email":"","middleInitial":"J.","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":826251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sclafani, Matthew","contributorId":238556,"corporation":false,"usgs":false,"family":"Sclafani","given":"Matthew","email":"","affiliations":[{"id":47742,"text":"Cornell Cooperative Extension","active":true,"usgs":false}],"preferred":false,"id":826252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frisk, Michael G.","contributorId":268238,"corporation":false,"usgs":false,"family":"Frisk","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":826253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKown, Kim","contributorId":238557,"corporation":false,"usgs":false,"family":"McKown","given":"Kim","email":"","affiliations":[{"id":47744,"text":"New York Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":826254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zeigler, Catherine","contributorId":268239,"corporation":false,"usgs":false,"family":"Zeigler","given":"Catherine","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":826255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":826256,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cerrato, Robert","contributorId":238559,"corporation":false,"usgs":false,"family":"Cerrato","given":"Robert","email":"","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":826257,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70246522,"text":"70246522 - 2021 - Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska","interactions":[],"lastModifiedDate":"2023-07-10T13:20:53.475537","indexId":"70246522","displayToPublicDate":"2021-10-27T06:37:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska","docAbstract":"<p>Mineralogical and geochemical studies of interbedded black and gray mudstones in the Triassic part of the Triassic-Jurassic Otuk Formation (northern Alaska) document locally abundant barite and pyrite plus diverse redox signatures. These strata, deposited in an outer shelf setting at paleolatitudes of ~45 to 60°N, show widespread sedimentological evidence for bioturbation. Barite occurs preferentially in black mudstones (TOC = 0.93–6.46 wt%), forming displacive euhedral crystals with pyrite inclusions and rims, and late albite inclusions or intergrowths. Pyrite also occurs as small (3–20 μm) framboids, discontinuous laminae, euhedral and anhedral crystals, and replacements of barite and fossils (mainly radiolarians). Paragenetically early wurtzite is present as clusters of very small (1–3 μm) aggregates of radiating crystals 0.5 to 1.0 μm long with cores of organic matter that overgrow framboidal pyrite; later wurtzite forms 10- to 30-μm bladed crystals. Equant grains (3–30 μm) and small (20 μm) angular clusters of zinc sulfide that include &lt;1-μm-long, comb-like structures are sphalerite or wurtzite, or both. Minor siderite forms euhedral crystals intergrown with albite that enclose wurtzite and barite. Illite shows intergrowths with sphalerite; rare K-feldspar is intergrown with barite. Formation of these minerals and assemblages is attributed to early diagenetic processes.</p><p>Whole-rock geochemical data for 15 samples show large ranges in redox proxies including Post Archean Average Shale (PAAS)-normalized enrichment factors (EFs) for V, U, Mo, and Re, and Al-normalized ratios for V, U, and Mo. Results for most black mudstones, with or without abundant barite and/or pyrite, suggest deposition within an oxygen minimum zone. Cerium anomalies, PAAS-normalized and calculated on a detrital-free basis, range widely from 0.49 to 0.96 and may reflect diagenetic overprinting by Ce-depleted fluids. Considering data for both black and gray mudstones, the overall geochemical pattern together with evidence from pyrite framboid sizes suggest that redox conditions fluctuated greatly from euxinic to oxic, like the redox profiles reported for modern shelf sediments offshore Peru and Namibia. The euxinic redox signatures in some Otuk black mudstones may correlate with widespread Early to Middle Triassic ocean anoxic events proposed for other regions.</p><p>Calculations of median EFs for trace elements in Otuk black mudstones reveal both enrichments and depletions. Normalizations to the median composition of the three least-mineralized black mudstones show that barite- and/or pyrite-rich samples display large (&gt;50%) positive changes for Li (+80.4%), V (+75.6%), Sr (+75.9%), Ba (+790%), Cu (+92.1%), Ni (+169%), Ag (+156%), Au (+3091%), As (+109%), Sb (+476%), and Se (+205%); Zn shows a moderate positive change of +42.1%. Moderate negative changes are evident only for Ge (−47.2%) and W (−30.6%). The local enrichments may reflect one or more factors including redox variations in bottom waters and pore fluids, element mobility during diagenesis, and selective fractionation into minerals such as barite, pyrite, and wurtzite. Anomalously low U/Al and UEF values, compared to those for other modern and ancient organic-rich sediments and sedimentary rocks, are attributed to increased solubility and loss of U during bioturbation-related oxygenation in the subsurface.</p><p>Physicochemical constraints on barite, pyrite, and wurtzite formation are informed by use of a pH-fO2 plot constructed at 10 °C. Based on paragenetic evidence for multistage deposition of these three minerals, together with the presence of illite intergrown with ZnS and K-feldspar with barite, proposed diagenetic trends involve an increase in pH and fO2 related to the ingress of sulfate-rich pore fluids during bioturbation, followed by a return to lower then higher pH and fO2 conditions linked to carbon, sulfur, barium, and iron cycling during diagenesis. Labile Ba of marine pelagic origin was mobilized from organic-rich sediment upward to the sulfate-methane transition zone where barite precipitated during the interaction of reduced Ba- and CH4-rich fluids with sulfate-bearing pore fluids. The formation of paragenetically early wurtzite (ZnS) crystals, as well as locally high EF values for Cu, Ni, Ag, and Au, is attributed to metal enrichment of pore fluids, with sources being derived in part from water-column deposition from hydrothermal plumes related to coeval Triassic seafloor vent systems including a volcanogenic massive sulfide deposit in British Columbia and the Wrangellia Large Igneous Province in Alaska.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2021.120568","usgsCitation":"Slack, J.F., McAleer, R.J., Shanks, W., and Dumoulin, J.A., 2021, Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska: Chemical Geology, v. 585, 120568, 22 p., https://doi.org/10.1016/j.chemgeo.2021.120568.","productDescription":"120568, 22 p.","ipdsId":"IP-130237","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":450344,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2021.120568","text":"Publisher Index Page"},{"id":418739,"rank":1,"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        \"coordinates\": [\n          [\n            [\n              -168.604267717169,\n              71.70733094087223\n            ],\n            [\n              -168.604267717169,\n              67.12370451837805\n            ],\n            [\n              -140.49132965188403,\n              67.12370451837805\n            ],\n            [\n              -140.49132965188403,\n              71.70733094087223\n            ],\n            [\n              -168.604267717169,\n              71.70733094087223\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"585","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":877040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":877041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanks, Wayne (Pat)","contributorId":240838,"corporation":false,"usgs":true,"family":"Shanks","given":"Wayne (Pat)","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":877042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":877043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70225547,"text":"sir20215096 - 2021 - Effects of culvert construction on streams and macroinvertebrate communities at selected sites in the East Gulf Coastal Plain of Alabama, 2010–19","interactions":[],"lastModifiedDate":"2023-10-23T20:08:40.929938","indexId":"sir20215096","displayToPublicDate":"2021-10-25T20:04:17","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5096","displayTitle":"Effects of Culvert Construction on Streams and Macroinvertebrate Communities at Selected Sites in the East Gulf Coastal Plain of Alabama, 2010–19","title":"Effects of culvert construction on streams and macroinvertebrate communities at selected sites in the East Gulf Coastal Plain of Alabama, 2010–19","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Alabama Department of Transportation, evaluated the role of culvert construction in altering streams and habitats of benthic macroinvertebrate communities at selected study sites in the northern East Gulf Coastal Plain of Alabama during 2011–19. Analysis included examinations of changes in stream channel geometry, suspended sediment, turbidity, and benthic macroinvertebrate communities.</p><p>Topographic surveys of stream channel cross sections, upstream and downstream of the culvert, were conducted before and after construction. Changes in channel geometry (cross-sectional area, top width, mean depth, and thalweg slope) were assessed by using paired sample t-tests to compare before- and after-construction channel geometry measurements. Statistically significant changes in stream channel geometry between the before- and after-construction measurements were observed at four of the six study sites. Analysis of the channel geometry data indicates that 1 site had no measured changes, and thalweg reach slopes were inverted at 4 of the 12 study reaches—2 measured in before-construction reaches and 2 measured in after-construction reaches.</p><p>Surface-water samples were collected during selected storm events for suspended sediment and turbidity analyses. Samples were simultaneously collected upstream and downstream of the culvert construction reaches during all three phases of construction (before, during, and after). Analysis focused on the parity of upstream to downstream simultaneous samples. The mean upstream to downstream paired ratios of sediment concentrations and turbidity from the after-construction phase indicate that colloidal and noncolloidal sediments were passing through the construction reaches at two of the six sites, noncolloidal sediments were being trapped in the construction reaches at two sites, and colloidal and noncolloidal sediments were being removed from the construction reach at two sites.</p><p>Benthic macroinvertebrates were collected and identified at five of the six sites from instream habitats that were available in sampled areas both upstream and downstream of the culvert construction reaches. Differences between upstream and downstream reaches and the Wilcoxon rank sum statistic were used to examine changes in metrics of benthic macroinvertebrate communities between before- and after-construction phases. Benthic macroinvertebrate sampling results did not indicate that culvert construction caused impairment to communities at study sites. No tolerance metrics suggested a major change in the pollution tolerance of the communities. The same upstream to downstream patterns in abundance-weighted tolerance values were observed in the before- and after-construction periods at each site. At one site, the difference between upstream and downstream richness-based tolerance values increased, but the after-construction upstream and downstream richness-based tolerance values were lower (indicating a less pollution-tolerant macroinvertebrate community) than in the before-construction period.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215096","collaboration":"Prepared in cooperation with the Alabama Department of Transportation","usgsCitation":"Pugh, A.L., and Gill, A.C., 2021, Effects of culvert construction on streams and macroinvertebrate communities at selected sites in the East Gulf Coastal Plain of Alabama, 2010–19: U.S. Geological Survey Scientific Investigations Report 2021–5096, 52 p., https://doi.org/10.3133/sir20215096.","productDescription":"Report: vii, 52 p.; Data Release; Dataset","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-097029","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":390797,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P906BOVO","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Aerial imagery, benthic macroinvertebrate, topographic survey, and soil survey datasets collected for a study of effects of culverts on the natural conditions of streams in the East Gulf Coastal Plain of Alabama, 2010–2019"},{"id":390796,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5096/sir20215096.pdf","text":"Report","size":"15.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5096"},{"id":390795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5096/coverthb.jpg"},{"id":390798,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Alabama","otherGeospatial":"East Gulf Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.08837890625,\n              34.69646117272349\n            ],\n            [\n              -88.165283203125,\n              34.69646117272349\n            ],\n            [\n              -88.505859375,\n              31.98012335736804\n            ],\n            [\n              -88.363037109375,\n              30.315987718557867\n            ],\n            [\n              -88.121337890625,\n              30.268556249047727\n            ],\n            [\n              -87.747802734375,\n              30.173624550358536\n            ],\n  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Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Physical Parameters Analysis</li><li>Benthic Macroinvertebrate Analysis</li><li>Limitations of This Study and Lessons Learned</li><li>Summary</li><li>Acknowledgments</li><li>References</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-10-25","noUsgsAuthors":false,"publicationDate":"2021-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Pugh, Aaron L. 0000-0003-3945-5750 apugh@usgs.gov","orcid":"https://orcid.org/0000-0003-3945-5750","contributorId":214343,"corporation":false,"usgs":true,"family":"Pugh","given":"Aaron","email":"apugh@usgs.gov","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gill, Amy C. 0000-0002-5738-9390 acgill@usgs.gov","orcid":"https://orcid.org/0000-0002-5738-9390","contributorId":220,"corporation":false,"usgs":true,"family":"Gill","given":"Amy","email":"acgill@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":825530,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70225560,"text":"fs20213054 - 2021 - The HayWired Earthquake Scenario—Societal Consequences","interactions":[],"lastModifiedDate":"2022-01-28T17:47:13.53462","indexId":"fs20213054","displayToPublicDate":"2021-10-22T17:14:42","publicationYear":"2021","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":"2021-3054","displayTitle":"The HayWired Earthquake Scenario—Societal Consequences","title":"The HayWired Earthquake Scenario—Societal Consequences","docAbstract":"<p>The HayWired earthquake scenario, led by the U.S. Geological Survey (USGS), anticipates the impacts of a hypothetical moment magnitude 7.0 earthquake on the Hayward Fault. The fault runs along the east side of California’s San Francisco Bay and is among the most active and dangerous in the United States, passing through a densely urbanized and interconnected region. A scientifically realistic scenario is one way to learn from a large earthquake before one occurs in the bay region. The USGS and its partners in the HayWired Coalition are working to energize residents and businesses to engage in new and ongoing efforts to prepare the region for such a future earthquake.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213054","usgsCitation":"Wein, A.M., Jones, J.L., Johnson, L.A., Kroll, C., Strauss, J., Witkowski, D., Cox, D.A., 2021, The HayWired Earthquake Scenario—Societal Consequences: U.S. Geological Survey Fact Sheet 2021–3054, 6 p., https://doi.org/10.3133/fs20213054.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-132490","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":553,"text":"Science Application for Risk Reduction (SAFRR)","active":false,"usgs":true}],"links":[{"id":390874,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20183016","text":"Fact Sheet 2018-3016","linkHelpText":"– The HayWired Earthquake Scenario—We Can Outsmart Disaster"},{"id":390873,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013V3","text":"Scientific Investigations Report 2017-5013 Volume 3","linkHelpText":"– The HayWired Earthquake Scenario—Societal Consequences"},{"id":390872,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013v2","text":"Scientific Investigations Report 2017-5013 Volume 2","linkHelpText":"– The HayWired Earthquake Scenario—Engineering Implications"},{"id":390871,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013v1","text":"Scientific Investigations Report 2017-5013 Volume 1","linkHelpText":"– The HayWired Earthquake Scenario—Earthquake Hazards"},{"id":390870,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3054/fs20213054.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":390869,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3054/covrthb.jpg"},{"id":395080,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://geonarrative.usgs.gov/liquefactionandsealevelrise/","text":"Liquefaction and Sea-Level Rise","linkHelpText":"–  A USGS storymap presenting the impacts of sea-level rise on liquefaction severity around the San Francisco Bay Area, California for the M7.0 ‘HayWired’ earthquake scenario along the Hayward Fault"},{"id":392899,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013","text":"Scientific Investigations Report 2017-5013","linkHelpText":"– The HayWired Earthquake Scenario"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.0908203125,\n              37.24782120155428\n            ],\n            [\n              -121.26708984374999,\n              37.24782120155428\n            ],\n            [\n              -121.26708984374999,\n              38.37611542403604\n            ],\n            [\n              -123.0908203125,\n              38.37611542403604\n            ],\n            [\n              -123.0908203125,\n              37.24782120155428\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/natural-hazards/earthquake-hazards/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/natural-hazards/earthquake-hazards/connect\">Contact Information</a>, Menlo Park, Calif.<br><a href=\"https://earthquake.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://earthquake.usgs.gov/\">Office—Earthquake Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>345 Middlefield Road, MS 977<br>Menlo Park, CA 94025</p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-10-22","noUsgsAuthors":false,"publicationDate":"2021-10-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Wein, Anne M. 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":192951,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":825606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Joseph L. jljones@usgs.gov","contributorId":3492,"corporation":false,"usgs":true,"family":"Jones","given":"Joseph","email":"jljones@usgs.gov","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Laurie A.","contributorId":267933,"corporation":false,"usgs":true,"family":"Johnson","given":"Laurie","email":"","middleInitial":"A.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":825608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kroll, Cynthia","contributorId":220302,"corporation":false,"usgs":false,"family":"Kroll","given":"Cynthia","email":"","affiliations":[{"id":40156,"text":"Association of Bay Area Governments","active":true,"usgs":false}],"preferred":false,"id":825609,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Strauss, Jennifer A.","contributorId":191076,"corporation":false,"usgs":false,"family":"Strauss","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":825610,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Witkowski, David","contributorId":267935,"corporation":false,"usgs":true,"family":"Witkowski","given":"David","email":"","affiliations":[],"preferred":true,"id":825611,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cox, Dale A. dacox@usgs.gov","contributorId":165,"corporation":false,"usgs":true,"family":"Cox","given":"Dale","email":"dacox@usgs.gov","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":825612,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70225544,"text":"sir20215110 - 2021 - Hydrologic and water-quality conditions in the Cedar River alluvial aquifer, Linn County, Iowa, 1990–2019","interactions":[],"lastModifiedDate":"2021-10-22T11:56:04.553594","indexId":"sir20215110","displayToPublicDate":"2021-10-21T21:13:01","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5110","displayTitle":"Hydrologic and Water-Quality Conditions in the Cedar River Alluvial Aquifer, Linn County, Iowa, 1990–2019","title":"Hydrologic and water-quality conditions in the Cedar River alluvial aquifer, Linn County, Iowa, 1990–2019","docAbstract":"<p>Alluvial aquifers in Iowa have more wells with nitrate exceeding drinking-water standards than other aquifers; are susceptible to contamination by organic contaminants; and have high concentrations of naturally occurring iron and manganese in depositional areas that contain abundant organic matter. The U.S. Geological Survey, in cooperation with the City of Cedar Rapids, Iowa, studied the Cedar River alluvial aquifer in Linn County, Iowa, from 1990 to 2019 to understand the effect of municipal pumping on spatial and temporal hydrologic and water-quality variability. The Cedar River alluvial aquifer is the source of water for the city of Cedar Rapids, Iowa. Withdrawal of large quantities of water for municipal and industrial supply has altered the normal flow of water in the alluvial aquifer. Pumping induces flow from the Cedar River and the underlying bedrock aquifer into the alluvial aquifer.</p><p>Water quality in the alluvial aquifer varies along the Cedar River. Changes in nitrate, ammonia, manganese, and iron in the alluvial aquifer are seen as the upstream free-flowing reach of the Cedar River transitions to a partially regulated downstream reach, likely because of differences in reduction-oxidation conditions in the aquifer, which are controlled by infiltration from the Cedar River under normal conditions and when wells are being pumped. Nitrate, normally found in oxygenated environments, had the highest concentrations in the most upstream wells in the Seminole well field and the lowest concentrations in the most downstream wells in the East well field. In contrast, ammonia, manganese, and iron, normally found in greatest abundance in anoxic (reducing) conditions, had the greatest concentrations in the most downstream wells. Additionally, dissolved nitrate plus nitrite nitrogen concentrations in wells were substantially less and manganese concentrations were greater in production wells near backwater wetlands in contrast to wells near the Cedar River.</p><p>Temporal variability in water quality in the alluvial aquifer was driven by pumping that increased flow from the Cedar River into the alluvial aquifer and ultimately led to changes in reduction-oxidation conditions of the aquifer. Increasing dissolved nitrate plus nitrite nitrogen concentrations in the Cedar River from 1990 to 2019 were mirrored in the alluvial aquifer. Anoxic conditions are prevalent in the alluvial aquifer next to the Cedar River when the aquifer is not under pumping stress. However, production well pumping caused induced infiltration of oxygenated river water into the aquifer resulting in increased dissolved nitrate plus nitrite nitrogen concentrations and pesticides and decreased naturally occurring dissolved iron and manganese.</p><p>Hydrologic and water-quality conditions in the Cedar River alluvial aquifer from 1990 to 2019 provide baseline conditions needed to evaluate the effects of current and future nutrient reduction efforts and land-use changes in the Cedar River Basin on water quality of the Cedar River alluvial aquifer and its source water, the Cedar River. This summary and analysis provide information that can assist the City of Cedar Rapids Utilities Water Department in managing groundwater resources, and provides information that could be used develop a groundwater-quality model to characterize variability over larger areas of the alluvial aquifer, allowing water providers to plan for future water needs of their users.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215110","usgsCitation":"Kalkhoff, S.J., 2021, Hydrologic and water-quality conditions in the Cedar River alluvial aquifer, Linn County, Iowa, 1990–2019: U.S. Geological Survey Scientific Investigations Report 2021–5110, 61 p., https://doi.org/10.3133/sir20215110.","productDescription":"Report: ix, 61 p.; Data Release; Dataset","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-121189","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":390747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5110/coverthb.jpg"},{"id":390748,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5110/sir20215110.pdf","text":"Report","size":"16.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5110"},{"id":390749,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z7VKOU","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Hydrologic and water quality data from the Cedar River and Cedar River alluvial aquifer, Linn County, Iowa, 1990–2019"},{"id":390750,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Iowa","county":"Linn County","otherGeospatial":"Cedar River Alluvial Aquifer","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-91.3649,42.2964],[-91.3651,42.2082],[-91.3653,42.1215],[-91.3661,42.0343],[-91.3669,41.948],[-91.3677,41.8603],[-91.4836,41.8608],[-91.5989,41.8612],[-91.716,41.862],[-91.8318,41.8617],[-91.8329,41.9485],[-91.8338,42.0366],[-91.8342,42.1242],[-91.8328,42.2087],[-91.8319,42.2987],[-91.7153,42.2971],[-91.5969,42.2959],[-91.4809,42.296],[-91.3649,42.2964]]]},\"properties\":{\"name\":\"Linn\",\"state\":\"IA\"}}]}","contact":"<p><a data-mce-href=\"mailto:%20dc_mo@usgs.gov\" href=\"mailto:%20dc_mo@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/cm-water\" href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br> U.S. Geological Survey<br>400 South Clinton Street, Suite 269 <br>Iowa City, IA 52240</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Description of the Study Area</li><li>Description of the Alluvial Aquifer</li><li>Methods</li><li>Hydrology of the Alluvial Aquifer</li><li>Water Quality of the Alluvial Aquifer</li><li>Water Quality in Source Waters</li><li>Relation Between Water Quality of the Alluvial Aquifer and the Devonian Aquifer</li><li>Relation Between Water Quality of the Alluvial Aquifer and the Cedar River</li><li>Flooding Effect on Alluvial Water Quality</li><li>Summary and Conclusion</li><li>References Cited</li><li>Appendix 1. Pesticide Compounds Not Detected in the Cedar River Alluvial and Devonian Aquifers and the Cedar River near Cedar Rapids, Linn County, Iowa, 1990–2019</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-10-21","noUsgsAuthors":false,"publicationDate":"2021-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kalkhoff, Stephen J. 0000-0003-4110-1716 sjkalkho@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-1716","contributorId":1731,"corporation":false,"usgs":true,"family":"Kalkhoff","given":"Stephen","email":"sjkalkho@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825524,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70224935,"text":"sir20205100 - 2021 - Hydrology and water quality of the Great Dismal Swamp, Virginia and North Carolina, and implications for hydrologic-management goals and strategies","interactions":[],"lastModifiedDate":"2023-03-03T15:45:09.446861","indexId":"sir20205100","displayToPublicDate":"2021-10-21T08:45:00","publicationYear":"2021","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":"2020-5100","displayTitle":"Hydrology and Water Quality of the Great Dismal Swamp, Virginia and North Carolina, and Implications for Hydrologic-Management Goals and Strategies","title":"Hydrology and water quality of the Great Dismal Swamp, Virginia and North Carolina, and implications for hydrologic-management goals and strategies","docAbstract":"<p>The Great Dismal Swamp is a peat wetland in the Coastal Plain of southeastern Virginia and northeastern North Carolina. Timber harvesting and the construction of ditches to drain the swamp and facilitate the harvesting are collectively implicated in changes that altered the wetland forests, caused subsidence and decomposition of the peat, and increased the risk of fire. In response to these changes, managers have implemented strategies to control water levels and rewet the swamp using a network of 64 adjustable-height, water-control structures on the ditches. Rewetting the swamp is intended to re-establish the original wetland-forest types, reduce the risk of fire, reduce subsidence and decomposition of the peat, enhance peat accretion, and reduce the risk of fire. Knowledge of responses of the swamp to hydrologic controls, however, is critical to developing and implementing effective management goals and strategies. Because the 2008 South One fire reemphasized the need for this knowledge, the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service began studies in 2009 to identify critical hydrologic controls and responses to these controls.</p><p>These studies identified water sources, topography, the two-layered hydraulic characteristics of the peat, the absence of peat in some areas, the ditch and road network, water-control structures on the ditches, the Dismal Swamp Canal and associated infrastructure, and wetland forests as the primary hydrologic controls. Precipitation is the only water source across much of the swamp. The eastward flow of streams and groundwater from the Isle of Wight Plain, across the Suffolk scarp, and into the swamp are additional water sources to the western part of the swamp. Vertical differences in the hydraulic characteristics of the peat reflect an upper peat having a high hydraulic conductivity and specific yield overlying a lower peat and sand having lower hydraulic conductivity and specific yield. The upper peat forms the main aquifer for the storage, flow, and release of water from the swamp. Maintaining water in the upper peat is critical to water availability to the wetland forests because of these properties.</p><p>Groundwater flows from the swamp into the ditches and the Dismal Swamp Canal where it discharges into nearby streams. Discharge typically is to the closest ditch except where a spoil-pile road that impedes flow intervenes between the swamp and the ditch. When groundwater levels in a ditch are about 2 feet lower than levels in the other three ditches surrounding a part of the swamp, however, most groundwater typically discharges to the ditch having the lower level. This occurs even if a spoil-pile road intervenes between the swamp and the ditch having the lower level. Flow to a single ditch shifts watershed boundaries and groundwater divides toward the ditches having higher water levels and demonstrates how flow and discharge are controlled by ditch water levels. Consequently, managing water levels based on these and other hydrologic controls and responses is critical to achieving management objectives.</p><p>The chemistry of water across the swamp shows the effects of the peat. Dissolved organic carbon concentrations in the groundwater are among the highest reported globally, ranging from 55 to 195 milligrams per liter. The pH of groundwater and ditch water is commonly less than 4.0 standard units because of organic acids. A relation between the pH and specific conductance of groundwater and ditch water reflects water sources, flow paths, and the chemical evolution, as waters from the different sources mix and flow along the paths.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205100","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Speiran, G.K., and Wurster, F.C., 2021, Hydrology and water quality of the Great Dismal Swamp, Virginia and North Carolina, and implications for hydrologic-management goals and strategies: U.S. Geological Survey Scientific Investigations Report 2020-5100, 104 p., https://doi.org/10.3133/sir20205100.","productDescription":"xii, 104 p.","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-108950","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":436139,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZVW9C8","text":"USGS data release","linkHelpText":"Hydrologic, water-quality, fire, forest-cover, and other data, the Great Dismal Swamp, Virginia and North Carolina"},{"id":390256,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20205100/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2020-5100"},{"id":390255,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5100/images"},{"id":390252,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5100/coverthb.jpg"},{"id":390253,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5100/sir20205100.pdf","text":"Report","size":"20.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5100"},{"id":390254,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5100/sir20205100.XML"}],"country":"United States","state":"North Carolina, Virginia","otherGeospatial":"Great Dismal Swamp","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.651611328125,\n              36.575835338491736\n            ],\n            [\n              -76.65710449218749,\n              36.41244153535644\n            ],\n            [\n              -76.5142822265625,\n              36.32397712011261\n            ],\n            [\n              -76.3714599609375,\n              36.36822190085109\n            ],\n            [\n              -76.25061035156251,\n              36.4345419190089\n            ],\n            [\n              -76.2835693359375,\n              36.85325222344016\n            ],\n            [\n              -76.4483642578125,\n              36.87522650673951\n            ],\n            [\n              -76.61865234374999,\n              36.84006462037767\n            ],\n            [\n              -76.651611328125,\n              36.575835338491736\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_va@usgs.gov\" data-mce-href=\"mailto:dc_va@usgs.gov\">Center Director</a>, <a href=\"https://www.usgs.gov/centers/va-wv-water\" data-mce-href=\"https://www.usgs.gov/centers/va-wv-water\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, VA 23228</p>","tableOfContents":"<ul><li>Foreword</li><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Description of the Swamp and Surrounding Areas</li><li>Description of Contributing Studies</li><li>Study Methods</li><li>Hydrology</li><li>Management and Research Implications</li><li>Summary and Conclusions</li><li>Selected References</li><li>Appendix 1. Well Construction Methods and Nomenclature</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-10-21","noUsgsAuthors":false,"publicationDate":"2021-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Speiran, Gary K. 0000-0002-6505-1170 gspeiran@usgs.gov","orcid":"https://orcid.org/0000-0002-6505-1170","contributorId":3233,"corporation":false,"usgs":true,"family":"Speiran","given":"Gary","email":"gspeiran@usgs.gov","middleInitial":"K.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wurster, Frederic C. 0000-0002-5393-2878 fred_wurster@fws.gov","orcid":"https://orcid.org/0000-0002-5393-2878","contributorId":204629,"corporation":false,"usgs":false,"family":"Wurster","given":"Frederic C.","email":"fred_wurster@fws.gov","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":824742,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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