{"pageNumber":"109","pageRowStart":"2700","pageSize":"25","recordCount":40783,"records":[{"id":70248277,"text":"sir20235087 - 2023 - Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)","interactions":[],"lastModifiedDate":"2026-03-12T21:08:34.632448","indexId":"sir20235087","displayToPublicDate":"2023-09-12T19:46:00","publicationYear":"2023","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":"2023-5087","displayTitle":"Approaches for Assessing Flows, Concentrations, and Loads of Highway and Urban Runoff and Receiving-Stream Stormwater in Southern New England With the Stochastic Empirical Loading and Dilution Model (SELDM)","title":"Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)","docAbstract":"

The Stochastic Empirical Loading and Dilution Model (SELDM) was designed to help quantify the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks. SELDM is calibrated using representative hydrological and water-quality input statistics. This report by the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation, documents approaches for assessing flows, concentrations, and loads of highway- and urban-runoff and receiving-stream stormwater in southern New England with SELDM. In this report, the term “urban runoff” is used to identify stormwater flows from developed areas with impervious fractions ranging from 10 to 100 percent without regard to the U.S. Census Bureau designation for any given location. There are more than 48,000 delineated road-stream crossings in southern New England, but because there are relatively few precipitation, streamflow, and water-quality monitoring sites in this area, methods were needed to simulate conditions at unmonitored sites. This report documents simulation methods, methods for interpreting stochastic model results, sensitivity analyses to identify the most critical variables of concern, and examples demonstrating how simulation results can be used to inform scientific decision-making processes. Results of 7,511 SELDM simulations were used to do the sensitivity analyses and provide information decisionmakers can use to address runoff-quality issues in southern New England and other areas of the Nation.

The sensitivity analyses indicate the relatively strong effect of input variables on variations in output results. These analyses indicate that highway and urban runoff quality and upstream water-quality statistics that vary considerably from site to site have the greatest effect on simulated results. Further data are needed to improve available water-quality statistics, and because the number of monitored sites will never approach the number of sites of interest for water-quality management, research is needed to identify methods to select statistics for unmonitored sites and quantify the uncertainties in the selection process. Hydrologically, prestorm streamflows with and without zero flows are the most sensitive and therefore the most important hydrologic variables to quantify. Results of analyses also are sensitive to statistics used for simulating structural best management practices.

Although the focus of the report is on data, statistics, simulation methods, and methods to interpret stochastic simulations, the examples in this report provide results that can be used to inform scientific decision-making processes. The results of 441 simulations that provide regional and site-specific highway and urban runoff yields across southern New England can be used for total maximum daily load analyses. The example stormwater load analysis done for 16 tributaries of the Narragansett Bay demonstrates that highway nitrogen loads are a small fraction of stormwater loads (about 3.6 percent), and a much smaller fraction of all nitrogen loads to the bay, primarily because highways have a small footprint on the land. Examples evaluating the potential effectiveness of end-of-pipe treatment indicate that offsite treatment is warranted in developed areas, and land conservation may be an effective mitigation strategy. The results of these analyses are consistent with conclusions from other simulation and monitoring studies.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235087","collaboration":"Prepared in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation","usgsCitation":"Granato, G.E., Spaetzel, A.B., and Jeznach, L.C., 2023, Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2023–5087, 152 p., https://doi.org/10.3133/sir20235087.","productDescription":"Report: xii, 152 p.; Software Release; 4 Data Releases","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-133112","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501050,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115402.htm","linkFileType":{"id":5,"text":"html"}},{"id":420555,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K0Y7XR","text":"USGS data release","linkHelpText":"Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420556,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CZNIH5","text":"USGS data release","linkHelpText":"Model archive for analysis of flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)"},{"id":420554,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B02EUZ","text":"USGS data release","linkHelpText":"Model archive for analysis of long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420557,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VK1MCG","text":"USGS data release","linkHelpText":"Basin characteristics and point locations of road crossings in Connecticut, Massachusetts, and Rhode Island for highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model"},{"id":420548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5087/coverthb.jpg"},{"id":420549,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.pdf","text":"Report","size":"8.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5087"},{"id":420552,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5087/images/"},{"id":420887,"rank":11,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9PYG7T5","text":"USGS software release","linkHelpText":"- Stochastic Empirical Loading and Dilution Model (SELDM) software archive"},{"id":420551,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.XML"},{"id":420553,"rank":10,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9XBPIOB","text":"USGS software release","linkHelpText":"- Best management practices statistical estimator (BMPSE) version 1.2.0"},{"id":420550,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5087"}],"country":"United States","state":"Connecticut, Massachusetts, New Hampshire, Rhode Island, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.28249194123347,\n 42.97558594616143\n ],\n [\n -73.81823969745555,\n 41.00628384122689\n ],\n [\n -69.72117184187273,\n 40.9949482400483\n ],\n [\n -69.72117184187273,\n 42.97558594616143\n ],\n [\n -73.28249194123347,\n 42.97558594616143\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-09-12","noUsgsAuthors":false,"publicationDate":"2023-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":203250,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spaetzel, Alana B. 0000-0002-9871-812X","orcid":"https://orcid.org/0000-0002-9871-812X","contributorId":240935,"corporation":false,"usgs":true,"family":"Spaetzel","given":"Alana","email":"","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeznach, Lillian C. 0000-0002-5476-9232","orcid":"https://orcid.org/0000-0002-5476-9232","contributorId":297153,"corporation":false,"usgs":true,"family":"Jeznach","given":"Lillian","email":"","middleInitial":"C.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882227,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248425,"text":"tm8D2 - 2023 - Design and utility of automatous, floating bait delivery platform for applying fish management baits","interactions":[],"lastModifiedDate":"2023-09-13T13:48:28.142468","indexId":"tm8D2","displayToPublicDate":"2023-09-12T15:12:56","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"8-D2","displayTitle":"Design and Utility of Automatous, Floating Bait Delivery Platform for Applying Fish Management Baits","title":"Design and utility of automatous, floating bait delivery platform for applying fish management baits","docAbstract":"

Using manufactured baits to attract fish to passive gear is common practice in fisheries management. The most common method is using hoop nets baited with soybean cakes or waste cheese to increase captures of multiple catfish species; however, these techniques are limited to how often bait is added, the type of bait, gear compatibility, and oversaturation of bait during soak time. The U.S. Geological Survey developed a technique to deliver various types of manufactured, pelleted baits over multiple scenarios and traditional passive gears. A floating platform designed with a dispenser can be constructed easily and allows for the automatic application of varying quantities and sizes of bait. Bait platforms can be modified for use in lakes and rivers where water fluctuations are common. Unlike traditional baiting techniques, these platforms can be positioned over or near any type of gear and release bait as many as nine times daily. Programmed release of bait multiple time a day can be useful to target fish activity during specific hours and can allow for sustained application without bait oversaturation or deterioration from long soak times. This report describes the design of a bait delivery platform developed for deployment in the Sandusky River in Ohio for the removal of Ctenopharyngodon idella (Valenciennes, 1844; grass carp) during 2021 and 2022.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm8D2","usgsCitation":"Wamboldt, J.J., 2023, Design and utility of automatous, floating bait delivery platform for applying fish management baits: U.S. Geological Survey Techniques and Methods, book 8, chap. D2, 8 p., https://doi.org/10.3133/tm8D2.","productDescription":"vi, 8 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-153329","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":420736,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm8D2/full","linkFileType":{"id":5,"text":"html"}},{"id":420715,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/08/d02/images/"},{"id":420714,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/08/d02/tm8d2.XML","linkFileType":{"id":8,"text":"xml"}},{"id":420713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/08/d02/tm8d2.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 8–D2"},{"id":420712,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/08/d02/coverthb.jpg"}],"contact":"

Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-09-12","noUsgsAuthors":false,"publicationDate":"2023-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Wamboldt, James J. 0000-0003-3043-5198","orcid":"https://orcid.org/0000-0003-3043-5198","contributorId":219060,"corporation":false,"usgs":true,"family":"Wamboldt","given":"James","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":882873,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70250212,"text":"70250212 - 2023 - Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska","interactions":[],"lastModifiedDate":"2023-11-28T17:24:31.851807","indexId":"70250212","displayToPublicDate":"2023-09-12T11:18:25","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska","docAbstract":"The National Hydrography Dataset (NHD) managed by the U.S. Geological Survey (USGS) is being updated with higher-quality feature representations through efforts that derive hydrography from 3DEP HR elevation datasets. Deriving hydrography from elevation through traditional flow routing and interactive methods is a complex, time-consuming process that must be tailored for different hydrogeomorphic conditions. The large volume of surface water features and HR remote sensing data make manual annotation of the water features over the entire nation infeasible. Furthermore, annual and seasonal variations of surface waters warrant some level of periodic updates to hydrography. Advances in deep learning technologies provide an opportunity to automate hydrography extraction and scale up the process to a nationwide level. One major challenge, however, is the effect of spatial heterogeneity due to the wide variety of hydrogeomorphic conditions in the United States. In other words, it is unclear how a deep learning model pre-trained in one set of hydrogeomorphic conditions can be effectively applied to other conditions for hydrographic feature extraction. This paper aims to provide some clarity in this regard by testing automated deep learning and its transferability to the extraction of hydrography from digital elevation model (DEM) data spanning a range of hydrogeomorphic conditions in Alaska. In transfer learning, the knowledge (e.g., neural network weights) from one domain is transferred to other domains and thereby decrease training requirements in the target domain.","conferenceTitle":"GIScience 2023 Workshop on CartoAI: AI for cartography","conferenceDate":"September 12-15, 2023","conferenceLocation":"Leeds, United Kingdom","language":"English","publisher":"ICA Commission on Multiscale Cartography","usgsCitation":"Stanislawski, L.V., Jaroenchai, N., Wang, S., Shavers, E.J., Duffy, A., Thiem, P.T., Jiang, Z., and Camerer, A., 2023, Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska, GIScience 2023 Workshop on CartoAI: AI for cartography, Leeds, United Kingdom, September 12-15, 2023, 3 p.","productDescription":"3 p.","ipdsId":"IP-156657","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":423015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423004,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cartoai.github.io/giscience2023/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154.78252936612796,\n 71.06703147535433\n ],\n [\n -160.1834860755645,\n 68.98584856236955\n ],\n [\n -158.7680908656647,\n 63.65325869193444\n ],\n [\n -142.69648224587866,\n 62.32431074447908\n ],\n [\n -142.64727236190666,\n 70.42721281931796\n ],\n [\n -154.78252936612796,\n 71.06703147535433\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaroenchai, Nattapon","contributorId":267318,"corporation":false,"usgs":false,"family":"Jaroenchai","given":"Nattapon","email":"","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":888922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Shaowen","contributorId":198966,"corporation":false,"usgs":false,"family":"Wang","given":"Shaowen","email":"","affiliations":[],"preferred":false,"id":888923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duffy, Alexander 0000-0001-6036-0583","orcid":"https://orcid.org/0000-0001-6036-0583","contributorId":299070,"corporation":false,"usgs":false,"family":"Duffy","given":"Alexander","email":"","affiliations":[{"id":64752,"text":"University of Missouri Science & Technology","active":true,"usgs":false}],"preferred":false,"id":888925,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thiem, Philip T. 0000-0002-3324-2589","orcid":"https://orcid.org/0000-0002-3324-2589","contributorId":287990,"corporation":false,"usgs":true,"family":"Thiem","given":"Philip","email":"","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888926,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jiang, Zhe","contributorId":267317,"corporation":false,"usgs":false,"family":"Jiang","given":"Zhe","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":888927,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Camerer, Adam","contributorId":331850,"corporation":false,"usgs":false,"family":"Camerer","given":"Adam","email":"","affiliations":[{"id":26996,"text":"Missouri University of Science & Technology","active":true,"usgs":false}],"preferred":false,"id":888928,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70248283,"text":"cir1510 - 2023 - Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) pilot project progress toward an information management and technology plan","interactions":[],"lastModifiedDate":"2023-09-12T18:55:36.46567","indexId":"cir1510","displayToPublicDate":"2023-09-12T10:25:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1510","displayTitle":"Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) Pilot Project Progress Toward an Information Management and Technology Plan","title":"Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) pilot project progress toward an information management and technology plan","docAbstract":"

Executive Summary

The U.S. Geological Survey carries out a wide variety of multidisciplinary science projects through the Bureau’s regions, mission areas, programs, and science centers. However, this structure can limit interactions among individual scientists, segregate data holdings, and make it difficult to apply holistic, interdisciplinary science. In addition, technological advances in sensors, data storage and analysis, computing power, and networking have resulted in an exponential growth in the volume, variety, and complexity of data. To address some of these challenges, the U.S. Geological Survey initiated the Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) pilot project to facilitate interdisciplinary science in the drought-stricken basin and apply information management and technology (IMT) resources that can be used to deliver actionable science efficiently and effectively.

In fiscal year 2021, the Data Management and Advanced Technology subgroup of the ASIST pilot project worked toward developing an IMT plan that includes several advanced IMT solutions that are being implemented Bureau-wide by the Office of the Associate Chief Information Officer. This plan identifies applications, opportunities, and steps to leverage new and existing technologies, data, models, and knowledge to support integrated science projects across the Colorado River Basin. The subgroup also created an inventory of available IMT resources and their locations. The Colorado River Basin ASIST pilot project also developed a multiyear approach to build capacity for supporting integrated science projects in the Colorado River Basin, which provides an advanced IMT framework for expediting the production of interdisciplinary science related to the basin.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/cir1510","usgsCitation":"Anderson, E.D., Erxleben, J.R., Qi, S.L., Monroe, A.P., and Dahm, K.G., 2023, Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) pilot project progress toward an information management and technology plan: U.S. Geological Survey Circular 1510, 11 p., https://doi.org/10.3133/cir1510.","productDescription":"viii, 10 p.","onlineOnly":"Y","ipdsId":"IP-131022","costCenters":[{"id":64844,"text":"Rocky Mountain Region Director’s Office","active":true,"usgs":true}],"links":[{"id":420721,"rank":9,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1510/images"},{"id":420626,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221040","text":"USGS Open-File Report 2022-1040","linkHelpText":"Presented Abstracts from the U.S. Geological Survey 2020 Rocky Mountain Region Science Exchange (September 15–17, 2020)"},{"id":420625,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20223051","text":"USGS Fact Sheet 2022-3051","linkHelpText":"U.S. Geological Survey Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)—Information Management Technology Plan"},{"id":420590,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20223016","text":"USGS Fact Sheet 2022-3016","linkHelpText":"Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)"},{"id":420589,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20223010","text":"USGS Fact Sheet 2022-3010","linkHelpText":"Addressing Stakeholder Science Needs for Integrated Drought Science in the Colorado River Basin"},{"id":420624,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/cir1502","text":"USGS Circular 1502","linkHelpText":"Colorado River Basin Actionable and Strategic Integrated Science and Technology Project—Science Strategy"},{"id":420627,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/cir1483","text":"USGS Circular 1483","linkHelpText":"Rocky Mountain Region Science Exchange 2020—EarthMAP and the Colorado River Basin"},{"id":420588,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1510/cir1510.pdf","text":"Report","size":"4.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1510"},{"id":420587,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1510/coverthb.jpg"},{"id":420735,"rank":11,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1510/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Circular 1510"},{"id":420722,"rank":10,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1510/cir1510.xml"}],"country":"United States","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.50163992210821,\n 41.074060046257415\n ],\n [\n -117.48373547769216,\n 41.074060046257415\n ],\n [\n -117.48373547769216,\n 30.63237394457815\n ],\n [\n -107.50163992210821,\n 30.63237394457815\n ],\n [\n -107.50163992210821,\n 41.074060046257415\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Region 7 - Upper Colorado Basin
U.S. Geological Survey
Box 25046, MS 911
Denver, CO 80225

","tableOfContents":"","publishedDate":"2023-09-12","noUsgsAuthors":false,"publicationDate":"2023-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Eric D. 0000-0002-0138-6166","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":202072,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":882263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erxleben, Jennifer R. 0000-0002-4060-0241","orcid":"https://orcid.org/0000-0002-4060-0241","contributorId":299423,"corporation":false,"usgs":true,"family":"Erxleben","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[{"id":5066,"text":"Office of the Director USGS","active":true,"usgs":true}],"preferred":true,"id":882264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":882266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahm, Katharine G. 0000-0002-4024-8110","orcid":"https://orcid.org/0000-0002-4024-8110","contributorId":299422,"corporation":false,"usgs":true,"family":"Dahm","given":"Katharine","email":"","middleInitial":"G.","affiliations":[{"id":64844,"text":"Rocky Mountain Region Director’s Office","active":true,"usgs":true}],"preferred":true,"id":882267,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248453,"text":"70248453 - 2023 - Comment on “A new decade in seismoacoustics (2010–2022)” by Fransiska Dannemann Dugick, Clinton Koch, Elizabeth Berg, Stephen Arrowsmith, and Sarah Albert","interactions":[],"lastModifiedDate":"2023-12-04T17:15:29.773582","indexId":"70248453","displayToPublicDate":"2023-09-12T08:40:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Comment on “A new decade in seismoacoustics (2010–2022)” by Fransiska Dannemann Dugick, Clinton Koch, Elizabeth Berg, Stephen Arrowsmith, and Sarah Albert","docAbstract":"

An increase in seismic stations also having microbarographs has led to increased interest in the field of seismoacoustics. A review of the recent advances in this field can be found in Dannemann Dugick et al. (2023). The goal of this note is to draw the attention of the readers of Dannemann Dugick et al. (2023) to several additional interactions between the solid Earth and atmosphere that have not been classically considered in the field of seismoacoustics. The 15 January 2022 Hunga Tonga–Hunga Ha‘api eruption produced acoustic gravity waves that were recorded globally. For example, the Lamb wave from this eruption produced early‐arriving and long‐lasting tsunami waves. This eruption also provided globally recorded coupling of atmospheric modes with solid Earth modes, providing another example of the complex interactions that can occur at the boundary between the atmosphere and the solid Earth. Even in the absence of large atmospheric signals, collocated pressure sensors at seismic stations can be a useful tool for estimating the local substructure, such at VS30⁠, the average shear velocity of the upper 30 m. Finally, at low frequencies, it is possible to use pressure records to correct out atmospheric disturbances recorded on seismometers. We briefly review the aforementioned, nontraditional seismoacoustic topics that we feel are important to consider as part of the full suite of interactions occurring between the solid Earth and atmosphere.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230111","usgsCitation":"Ringler, A.T., Anthony, R.E., Shiro, B., Tanimoto, T., and Wilson, D.C., 2023, Comment on “A new decade in seismoacoustics (2010–2022)” by Fransiska Dannemann Dugick, Clinton Koch, Elizabeth Berg, Stephen Arrowsmith, and Sarah Albert: Bulletin of the Seismological Society of America, v. 113, no. 6, p. 2746-2752, https://doi.org/10.1785/0120230111.","startPage":"2746","endPage":"2752","ipdsId":"IP-154575","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":420788,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":882970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":882971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shiro, Brian 0000-0001-8756-288X","orcid":"https://orcid.org/0000-0001-8756-288X","contributorId":204040,"corporation":false,"usgs":true,"family":"Shiro","given":"Brian","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":882972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tanimoto, Toshiro","contributorId":303974,"corporation":false,"usgs":false,"family":"Tanimoto","given":"Toshiro","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":882973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":882974,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248757,"text":"70248757 - 2023 - Application of a catch multiple survey analysis for Atlantic horseshoe crab Limulus polyphemus in the Delaware Bay","interactions":[],"lastModifiedDate":"2023-09-20T15:08:03.924703","indexId":"70248757","displayToPublicDate":"2023-09-12T07:03:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Application of a catch multiple survey analysis for Atlantic horseshoe crab Limulus polyphemus in the Delaware Bay","title":"Application of a catch multiple survey analysis for Atlantic horseshoe crab Limulus polyphemus in the Delaware Bay","docAbstract":"

Objective

This paper applies a catch multiple survey analysis (CMSA) to Atlantic horseshoe crabs Limulus polyphemus in the Delaware Bay to generate robust population estimates for harvest management. Currently, horseshoe crabs along the U.S. Atlantic coast are harvested as bait for other fisheries and collected for their blood, which is used in a biomedical industry. The Delaware Bay is home to the largest population of horseshoe crabs and is a significant stopover for shorebirds to rebuild energy by consuming horseshoe crab eggs prior to completing their northward migration. To address this interrelationship, the Adaptive Resource Management (ARM) Framework has been used since 2013 to ensure that horseshoe crab harvest within the region takes into account the forage needs of migratory birds. Since its inception, the ARM Framework has used a single trawl survey's swept area-based population estimates of horseshoe crab relative abundance and a theoretical population model developed primarily from literature-derived values. With more data collected in the region in recent years and other sources of mortality that can now be quantified, a catch survey model can provide horseshoe crab population estimates going forward.

Methods

A CMSA was used to estimate male and female horseshoe crab population size for 2003–2021 using all quantifiable sources of mortality and three fishery-independent indices of abundance.

Result

The CMSA results indicated that adult abundance of male and female horseshoe crabs was stable from 2003 to 2013 and then began to increase through 2017, a result that is consistent with stock rebuilding following a period of harvest restrictions as recommended by the ARM Framework. Population estimates were lower in recent years but remained above the levels estimated before implementation of the ARM Framework. In 2021, the CMSA estimated that there were over 6 million mature females and nearly 16 million mature male horseshoe crabs in the region.

Conclusion

The CMSA provides the best and most comprehensive population estimates of horseshoe crabs in Delaware Bay and will improve modeling efforts within the ARM Framework going forward.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10250","usgsCitation":"Anstead, K.A., Sweka, J., Barry, L., Hallerman, E., Smith, D.R., Ameral, N., Schmidtke, M., and Wong, R.A., 2023, Application of a catch multiple survey analysis for Atlantic horseshoe crab Limulus polyphemus in the Delaware Bay: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 15, no. 5, e10250, 16 p., https://doi.org/10.1002/mcf2.10250.","productDescription":"e10250, 16 p.","ipdsId":"IP-154235","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":442129,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10250","text":"Publisher Index Page"},{"id":420973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.0255903899312,\n 40.963933240903344\n ],\n [\n -76.0255903899312,\n 37.040030719320384\n ],\n [\n -73.65356124067296,\n 37.040030719320384\n ],\n [\n -73.65356124067296,\n 40.963933240903344\n ],\n [\n -76.0255903899312,\n 40.963933240903344\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Anstead, Kristen A.","contributorId":329847,"corporation":false,"usgs":false,"family":"Anstead","given":"Kristen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":883459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweka, John A.","contributorId":288581,"corporation":false,"usgs":false,"family":"Sweka","given":"John A.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":883460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barry, Linda","contributorId":329848,"corporation":false,"usgs":false,"family":"Barry","given":"Linda","email":"","affiliations":[],"preferred":false,"id":883461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hallerman, Eric M.","contributorId":279474,"corporation":false,"usgs":false,"family":"Hallerman","given":"Eric M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":883462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, David R. 0000-0001-9560-5210 dvsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-9560-5210","contributorId":329849,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"dvsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":883463,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ameral, Natalie","contributorId":329850,"corporation":false,"usgs":false,"family":"Ameral","given":"Natalie","email":"","affiliations":[],"preferred":false,"id":883464,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidtke, Michael","contributorId":329851,"corporation":false,"usgs":false,"family":"Schmidtke","given":"Michael","email":"","affiliations":[],"preferred":false,"id":883465,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wong, Richard A.","contributorId":329852,"corporation":false,"usgs":false,"family":"Wong","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":883466,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70248365,"text":"ofr20231065 - 2023 - Status, trend, and monitoring effectiveness of Marbled Murrelet (Brachyramphus marmoratus) at sea abundance and reproductive output off central California, 1999–2021","interactions":[],"lastModifiedDate":"2023-09-12T13:52:06.86719","indexId":"ofr20231065","displayToPublicDate":"2023-09-11T15:19:44","publicationYear":"2023","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":"2023-1065","displayTitle":"Status, Trend, and Monitoring Effectiveness of Marbled Murrelet (Brachyramphus marmoratus) at Sea Abundance and Reproductive Output off Central California, 1999–2021","title":"Status, trend, and monitoring effectiveness of Marbled Murrelet (Brachyramphus marmoratus) at sea abundance and reproductive output off central California, 1999–2021","docAbstract":"

Marbled Murrelets (Brachyramphus marmoratus) have been listed as “endangered” by the State of California and “threatened” by the U.S. Fish and Wildlife Service since 1992 in California, Oregon, and Washington. Information regarding murrelet abundance, distribution, and habitat associations is critical for risk assessment, effective management, evaluation of conservation efficacy, and ultimately, the meeting of Federal- and State-mandated recovery efforts. From 1999 to present, line-transect surveys have been performed to estimate at-sea abundance and reproductive output of Marbled Murrelets in the marine environment in U.S. Fish and Wildlife Service Conservation Zone 6 (San Francisco Bay to Point Sur in central California). Using this long-term annual time series, we developed a new and comprehensive analytical framework to estimate annual murrelet abundance and trend at sea, evaluated the effectiveness of spatial and temporal components of the monitoring study design, assessed two measures of annual murrelet reproductive output, and developed new spatial models to map murrelet at-sea density and estimate model-based annual at-sea abundances. The long-term average, design-based after-hatch-year (AHY) abundance estimate for the study area was 376 murrelets (range: 163–586 annually), and we did not detect any significant trend during the 23 years of monitoring. Spatial-model-based AHY abundance estimates were similar to design-based estimates but with smaller estimated variance. The AHY murrelets were most abundant nearshore, with little annual variation; alongshore, distribution was more annually variable, and some long-term hotspots occurred, particularly around Point Año Nuevo. The AHY murrelet densities were greatest in July and least in June and August. The long-term average hatch-year (HY) abundance estimate was 13 murrelets (range: 0–31 annually), and the long-term average HY:AHY ratio was 0.052; both metrics indicated similar interannual patterns. Evidence of a significant trend in either metric of reproductive output was not detected; although large overlap among interannual abundance and ratio estimates at the 95-percent confidence interval level made it difficult to evaluate interannual differences. Despite the apparent long-term stability in murrelet abundance in this region from 1999 to 2021, future long-term annual monitoring at sea will be critical to determine if the large-scale August 2020 CZU Santa Cruz Mountain wildfire that occurred adjacent to our study area affects local murrelet at-sea abundance and distribution. We also evaluated potential changes to survey and analytical design that could benefit this monitoring program in the future. Results indicated that eliminating the offshore stratum, focusing more effort on the nearshore stratum, and doing fewer surveys focused on a narrower timeframe could maintain or improve AHY trend estimates while preserving the ability to compare them to past years.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231065","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Felis, J., Adams, J., and Becker, B., 2023, Status, trend, and monitoring effectiveness of Marbled Murrelet (Brachyramphus marmoratus) at sea abundance and reproductive output off central California, 1999–2021: U.S. Geological Survey Open-File Report 2023–1065, 47 p., https://doi.org/10.3133/ofr20231065.","productDescription":"Report: viii, 47 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-147273","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":420681,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75B01RW","text":"USGS Data Release","description":"Felis, J.J., Adams, J., Peery, M.Z., Henry, R.W., Henkel, L.A., Becker, B.H., and Halbert, P., 2022, Annual marbled murrelet abundance and productivity surveys off central California (Zone 6), 1999–2021 (ver. 4.0, May 2022): U.S. Geological Survey data release, https://doi.org/10.5066/F75B01RW.","linkHelpText":"Annual marbled murrelet abundance and productivity surveys off central California (Zone 6), 1999–2021 (ver. 4.0, May 2022)"},{"id":420675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1065/covrthb.jpg"},{"id":420676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1065/ofr20231065.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420677,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1065/ofr20231065.xml"},{"id":420678,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1065/images"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.02806862776823,\n 36.92229477756594\n ],\n [\n -121.92468779073133,\n 36.98296517484485\n ],\n [\n -122.46905251075435,\n 37.54475259884556\n ],\n [\n -122.79696360323157,\n 37.35110782152849\n ],\n [\n -122.23483030184242,\n 36.782698937994695\n ],\n [\n -122.02806862776823,\n 36.92229477756594\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-09-11","noUsgsAuthors":false,"publicationDate":"2023-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Felis, Jonathan 0000-0003-3056-925X jfelis@usgs.gov","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":174518,"corporation":false,"usgs":true,"family":"Felis","given":"Jonathan","email":"jfelis@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":882705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Josh 0000-0003-3056-925X josh_adams@usgs.gov","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":2422,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","email":"josh_adams@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":882706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Becker, Benjamin H.","contributorId":207275,"corporation":false,"usgs":false,"family":"Becker","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":37509,"text":"Point Reyes National Seashore, Point Reyes Station, CA","active":true,"usgs":false}],"preferred":true,"id":882707,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256430,"text":"70256430 - 2023 - Prioritization of species status assessments for decision support","interactions":[],"lastModifiedDate":"2024-08-01T16:21:36.448455","indexId":"70256430","displayToPublicDate":"2023-09-11T11:17:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14243,"text":"Decision Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Prioritization of species status assessments for decision support","docAbstract":"

Species status assessments are used to inform U.S. Fish and Wildlife Service (USFWS) decision making for Endangered Species Act (ESA) classification decisions, recovery planning, and more. The large number of species that require assessment and uncertainty in the data available impede the process of assigning and completing the assessments, which makes creating a multiyear work plan extremely difficult. An optimized triaging system that maximizes the use of the best available information while managing the complex ESA workload and meeting deadlines is necessary. We used a structured decision-making framework to approach the problem with the goal of creating a prioritization tool that would be effective at scheduling assessments, given the best information available and priorities of the USFWS. We collected data on the species awaiting assessment and developed a value function that incorporates existing deadlines, taxonomic uncertainty, controversy of the species, and population and habitat data availability and quality. We used a constrained linear optimization algorithm to maximize the value function and ensure that workload capacity was not exceeded. A comparison of model scenarios indicates that imposed deadlines impact the model more than capacity constraints. Additionally, differential weighting of the metrics significantly affected the outcome of the model. In the future, elicitation of metric weights should be done routinely before the model is run for use in official planning to ensure alignment with current USFWS priorities. Output from this optimization can be used to inform a five-year work plan, allocate resources, and discuss workforce decisions.

","language":"English","publisher":"Informs","doi":"10.1287/deca.2023.0026","usgsCitation":"Goode, A.B., Rivenbark, E., Gilbert, J.A., and McGowan, C., 2023, Prioritization of species status assessments for decision support: Decision Analysis, v. 20, no. 4, p. 311-325, https://doi.org/10.1287/deca.2023.0026.","productDescription":"15 p.","startPage":"311","endPage":"325","ipdsId":"IP-151407","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Goode, Ashley B.C.","contributorId":332463,"corporation":false,"usgs":false,"family":"Goode","given":"Ashley","middleInitial":"B.C.","affiliations":[{"id":33268,"text":"USDA-ARS Aquatic Weed Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":907349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rivenbark, Erin","contributorId":340546,"corporation":false,"usgs":false,"family":"Rivenbark","given":"Erin","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":907350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilbert, Jessica A.","contributorId":340547,"corporation":false,"usgs":false,"family":"Gilbert","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":907351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":907352,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248680,"text":"70248680 - 2023 - A synergistic future for AI and ecology","interactions":[],"lastModifiedDate":"2023-09-18T14:17:54.235709","indexId":"70248680","displayToPublicDate":"2023-09-11T09:13:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A synergistic future for AI and ecology","docAbstract":"

Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a century of independent, asynchronous advances in computational and ecological research, we foresee a critical need for intentional synergy to meet current societal challenges against the backdrop of global change. These challenges include understanding the unpredictability of systems-level phenomena and resilience dynamics on a rapidly changing planet. Here, we spotlight both the promise and the urgency of a convergence research paradigm between ecology and AI. Ecological systems are a challenge to fully and holistically model, even using the most prominent AI technique today: deep neural networks. Moreover, ecological systems have emergent and resilient behaviors that may inspire new, robust AI architectures and methodologies. We share examples of how challenges in ecological systems modeling would benefit from advances in AI techniques that are themselves inspired by the systems they seek to model. Both fields have inspired each other, albeit indirectly, in an evolution toward this convergence. We emphasize the need for more purposeful synergy to accelerate the understanding of ecological resilience whilst building the resilience currently lacking in modern AI systems, which have been shown to fail at times because of poor generalization in different contexts. Persistent epistemic barriers would benefit from attention in both disciplines. The implications of a successful convergence go beyond advancing ecological disciplines or achieving an artificial general intelligence—they are critical for both persisting and thriving in an uncertain future.

","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2220283120","usgsCitation":"Han, B.A., Varshney, K.R., LaDeau, S.L., Subramaniam, A., Weathers, K.C., and Zwart, J.A., 2023, A synergistic future for AI and ecology: Proceedings of the National Academy of Sciences, v. 120, no. 38, 2220283120, 7 p., https://doi.org/10.1073/pnas.2220283120.","productDescription":"2220283120, 7 p.","ipdsId":"IP-151656","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":442131,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2220283120","text":"Publisher Index Page"},{"id":420890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"38","noUsgsAuthors":false,"publicationDate":"2023-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Han, Barbara A. 0000-0002-9948-3078","orcid":"https://orcid.org/0000-0002-9948-3078","contributorId":329744,"corporation":false,"usgs":false,"family":"Han","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":883187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varshney, Kush R.","contributorId":329746,"corporation":false,"usgs":false,"family":"Varshney","given":"Kush","email":"","middleInitial":"R.","affiliations":[{"id":78709,"text":"IBM Research - T. J. Watson Research Center","active":true,"usgs":false}],"preferred":false,"id":883188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaDeau, Shannon L.","contributorId":172640,"corporation":false,"usgs":false,"family":"LaDeau","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":883189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Subramaniam, Ajit 0000-0003-1316-5827","orcid":"https://orcid.org/0000-0003-1316-5827","contributorId":329748,"corporation":false,"usgs":false,"family":"Subramaniam","given":"Ajit","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":883190,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weathers, Kathleen C.","contributorId":202417,"corporation":false,"usgs":false,"family":"Weathers","given":"Kathleen","email":"","middleInitial":"C.","affiliations":[{"id":36424,"text":"Cary Institute of Ecosystems Studies","active":true,"usgs":false}],"preferred":false,"id":883191,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":883192,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262059,"text":"70262059 - 2023 - Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal","interactions":[],"lastModifiedDate":"2025-01-10T18:31:23.287244","indexId":"70262059","displayToPublicDate":"2023-09-10T11:42:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5936,"text":"People and Nature","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal","title":"Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal","docAbstract":"
  1. The negative impact of large carnivore presence in human-dominated landscapes manifests as livestock depredation and in extreme cases as attacks on humans. In the case of conflict with leopards in Nepal, attacks resulting in human fatality have become more frequent over time, thus creating an urgent socio-ecological and management issue.
  2. We estimated the occurrence of leopard attacks in Nepal from human-leopard conflict cases reported in the media. We used occupancy models to analyse data collected from online news reports on incidents of leopard attacks on humans to explore drivers of leopard attacks on a landscape scale. Our results suggest that the probability of occurrence of leopard attack is associated with human population density, terrain ruggedness and livestock density.
  3. The human population density effect may be indicative of a density-dependent relationship, where attacks are more likely in areas where an increased abundance of humans increases encounter rates with leopards. The positive effect of livestock density suggests that livestock may be drawing leopards into human settlements, and consequently increasing the likelihood of attacks on humans. Terrain ruggedness might be offering ideal conditions to facilitate attacks on humans, for example remoteness and high amounts of cover to launch ambush attacks.
  4. We provide inference and insights into key determinants of leopard attacks on humans on a landscape scale. These insights can be used to guide future research, inform mitigation measures to reduce leopard attacks and foster a better understanding of the interaction between people and leopards.
  5. This study demonstrates the applicability and novelty of using a hierarchical modelling framework applied to freely and publicly available media reports to inform the applied management of human-wildlife conflict at a national scale.
","language":"English","publisher":"British Ecological Society","doi":"10.1002/pan3.10536","usgsCitation":"Poudel, S., Twining, J., Stedman, R., Ghimire, S., and Fuller, A.K., 2023, Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal: People and Nature, v. 5, no. 6, p. 177-188, https://doi.org/10.1002/pan3.10536.","productDescription":"12 p.","startPage":"177","endPage":"188","ipdsId":"IP-130714","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467093,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/pan3.10536","text":"Publisher Index Page"},{"id":466016,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 79.92780335815291,\n 28.803692392786957\n ],\n [\n 82.71145675855735,\n 27.422532855103327\n ],\n [\n 85.79994047161551,\n 26.519692535546156\n ],\n [\n 88.21732200599081,\n 26.28592528048857\n ],\n [\n 88.23034164615058,\n 28.015630040007878\n ],\n [\n 86.47325630501331,\n 28.11386705824934\n ],\n [\n 82.25297495008891,\n 30.33864883355747\n ],\n [\n 81.61483198209362,\n 30.552482869451012\n ],\n [\n 80.31771509103879,\n 29.885911968905162\n ],\n [\n 79.92780335815291,\n 28.803692392786957\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Poudel, Shashank","contributorId":348087,"corporation":false,"usgs":false,"family":"Poudel","given":"Shashank","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Twining, Joshua P.","contributorId":342747,"corporation":false,"usgs":false,"family":"Twining","given":"Joshua P.","affiliations":[{"id":81920,"text":"Cornell Universtity","active":true,"usgs":false}],"preferred":false,"id":922997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stedman, Richard C.","contributorId":348088,"corporation":false,"usgs":false,"family":"Stedman","given":"Richard C.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ghimire, Shravan Kumar","contributorId":348089,"corporation":false,"usgs":false,"family":"Ghimire","given":"Shravan Kumar","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":922930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922927,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248707,"text":"70248707 - 2023 - ENSO and NAO linkages to interannual salinity variability in north central Gulf of Mexico estuaries through teleconnections with precipitation","interactions":[],"lastModifiedDate":"2023-09-18T15:48:27.486866","indexId":"70248707","displayToPublicDate":"2023-09-10T10:48:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"ENSO and NAO linkages to interannual salinity variability in north central Gulf of Mexico estuaries through teleconnections with precipitation","docAbstract":"

Though the importance of Earth's internal climate modes such as the El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) to regional-scale climate variability is well recognized, the degree to which these oscillations are reflected by spatio-temporal salinity variability over interannual timescales in estuaries is less understood. Here an 11-year continuous salinity monitoring dataset spanning 223 stations across Louisiana's coastal wetlands along the northern Gulf of Mexico is examined with empirical orthogonal function (EOF) analysis to identify dominant modes of interannual variability in the salinity field. The first EOF mode accounts for 72% of the variance in the salinity field and captures a domain-wide pattern where salinities vary in-phase through space in response to local precipitation anomalies occurring in the vicinity of the study area. This local precipitation anomaly is positively correlated with ENSO (Nino3.4 index), consistent with the El Niño – wet (La Niña – dry) precipitation teleconnection that is prevalent throughout the northern Gulf of Mexico coast. The second EOF mode, which accounts for 13% of the variance in the salinity field, is expressed primarily in the marshes across the lower reaches of the Mississippi River deltaic plain (MRDP). EOF2 is anticorrelated with annual Mississippi River discharge anomaly such that salinities in the lower MRDP decrease as discharge increases, pointing to enhanced advection of fresh river plume waters over the shelf into the estuary via estuary-ocean exchange during years of anomalously high river discharge. Mississippi River discharge anomaly is positively correlated with the NAO at a one-year time lag, through a teleconnection with precipitation throughout much of the central region of the Mississippi River drainage basin. Together, these findings indicate that most of the interannual salinity variability across Louisiana's coastal wetlands can be linked to climate variability through teleconnections with precipitation. Incorporating these dynamics into restoration planning, monitoring, and adaptive management efforts may help constrain background environmental variation and better isolate restoration effects.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2023.108487","usgsCitation":"Snedden, G., 2023, ENSO and NAO linkages to interannual salinity variability in north central Gulf of Mexico estuaries through teleconnections with precipitation: Estuarine, Coastal and Shelf Science, v. 293, 108487, 9 p., https://doi.org/10.1016/j.ecss.2023.108487.","productDescription":"108487, 9 p.","ipdsId":"IP-140302","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":420905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.7941680074912,\n 30.932276934300717\n ],\n [\n -93.76673369766087,\n 30.932276934300717\n ],\n [\n -93.76673369766087,\n 28.810632610138626\n ],\n [\n -89.7941680074912,\n 28.810632610138626\n ],\n [\n -89.7941680074912,\n 30.932276934300717\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"293","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Snedden, Gregg 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":216669,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":883269,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70248366,"text":"ofr20231063 - 2023 - Summary of the history and research of the U.S. Geological Survey gas hydrate properties laboratory in Menlo Park, California, active from 1993 to 2022","interactions":[],"lastModifiedDate":"2023-09-11T10:52:43.087532","indexId":"ofr20231063","displayToPublicDate":"2023-09-08T15:16:47","publicationYear":"2023","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":"2023-1063","displayTitle":"Summary of the History and Research of the U.S. Geological Survey Gas Hydrate Properties Laboratory in Menlo Park, California, Active from 1993 to 2022","title":"Summary of the history and research of the U.S. Geological Survey gas hydrate properties laboratory in Menlo Park, California, active from 1993 to 2022","docAbstract":"

The U.S. Geological Survey (USGS) Clathrate Hydrate Properties Project, active from 1993 to 2022 in Menlo Park, California, stemmed from an earlier project on the properties of planetary ices supported by the National Aeronautics and Space Administration’s (NASA’s) Planetary Geology and Geophysics Program. We took a material science approach in both projects, emphasizing chemical purity of samples, having controlled grain size and grain texture, and having verified crystal structures and phase relations. A foundational contribution from our USGS Gas Hydrate Properties Laboratory (GHPL) was in demonstrating the ability to reproducibly create such pure clathrate hydrate samples for study. Clathrate sample synthesis was achieved by heating sieved and weighed pure granular water ice in the presence of cold clathrate-forming gas or liquid. During heating, the ice melts at the grain scale and reacts with the gas to form clathrate. The resulting material has the desired uniformity and purity, with known intergranular porosity; our subsequent measurements showed that these clathrates exhibited the established clathrate structures and phase relations. This novel synthesis method was successful in creating clathrates of pure methane, ethane, propane, carbon dioxide, and multi-component gases. By mixing sand or silt with granular ice, we were also able to make clathrate-sediment aggregates with controlled grain textures. This simple method, adopted by many others in the community, permitted us to measure the physical and chemical properties of well-characterized and well-crystallized clathrates and clathrate/sediment aggregates. At about the same time, we adapted conventional scanning electron microscopy to cryogenic conditions for analysis of grain-scale characteristics of clathrates made in the GHPL as well as those collected from nature by drill core. The uniformity and reproducibility of our samples also allowed us to investigate how clathrates respond to environmental changes in chemistry, temperature, and pressure: we measured chemical exchange rates with dissolved gas species—such as noble gases and chlorofluorocarbons—as well as rates of clathrate dissolution and decomposition. These advances include the first accurate mapping of the conditions that promote the remarkable process of “anomalous preservation” at room pressure, a metastability that offers potential application for low-cost and safe transportation of natural gas from gas fields far from pipelines.

Another advancement stemming from the GHPL was the compaction of as-synthesized porous clathrates to nearly full density by applying external pressure using three different techniques. Compaction allows for high-accuracy measurements of many fundamental physical and chemical properties of these materials, such as elastic wavespeeds and moduli, complete thermal properties, decomposition rates, thermal expansion, and clathrate equations of state. These properties and others, in turn, have helped USGS scientists to interpret geophysical well logs and active geophysical surveys, as well as model the rates of gas production from hydrate deposits in nature.

Studying this class of icy minerals that occur in abundance on Earth and in the outer solar system has been a fascinating laboratory journey. Here, we summarize the history and major findings of the USGS GHPL in Menlo Park, including both in-house research as well as findings from the synergistic collaborations with other agencies and institutes that were key to the success of our laboratory. The Menlo Park GHPL was more formally incorporated within the USGS Gas Hydrates Project, a collaboration among multiple USGS Science Centers, in the early 2000s under the leadership of Deborah Hutchinson, and now under the leadership of Carolyn Ruppel and Timothy Collett.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231063","usgsCitation":"Stern, L.A., and Kirby, S.H., 2023, Summary of the history and research of the U.S. Geological Survey gas hydrate properties laboratory in Menlo Park, California, active from 1993 to 2022: U.S. Geological Survey Open-File Report 2023–1063, 29 p., https://doi.org/10.3133/ofr20231063.","productDescription":"v, 29 p.","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-140366","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":420685,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1063/images"},{"id":420683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1063/ofr20231063.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1063/covrthb.jpg"}],"contact":"

Earthquake Science Center
U.S. Geological Survey
350 N. Akron Road
Moffett Field, CA 94035

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-09-08","noUsgsAuthors":false,"publicationDate":"2023-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Laura A. 0000-0003-3440-5674 lstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3440-5674","contributorId":1197,"corporation":false,"usgs":true,"family":"Stern","given":"Laura","email":"lstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":882708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirby, Stephen H. 0000-0003-1636-4688 skirby@usgs.gov","orcid":"https://orcid.org/0000-0003-1636-4688","contributorId":2752,"corporation":false,"usgs":true,"family":"Kirby","given":"Stephen","email":"skirby@usgs.gov","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":882709,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70248279,"text":"ofr20231064 - 2023 - California State waters map series—Benthic habitat characterization in the region offshore of Morro Bay, California","interactions":[],"lastModifiedDate":"2026-02-11T21:39:00.871652","indexId":"ofr20231064","displayToPublicDate":"2023-09-06T15:22:48","publicationYear":"2023","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":"2023-1064","displayTitle":"California State Waters Map Series—Benthic Habitat Characterization in the Region Offshore of Morro Bay, California","title":"California State waters map series—Benthic habitat characterization in the region offshore of Morro Bay, California","docAbstract":"

Coastal and Marine Ecological Classification Standard geoform, substrate, and biotic component geographic information system products were developed for the California State waters of south-central California in the region offshore of Morro Bay. The study was motivated by interest in development of offshore wind-energy capacity and infrastructure in Federal waters offshore. The Bureau of Ocean Energy Management, in coordination with the State of California and many other members of the California Intergovernmental Renewable Energy Task Force, issued calls for information in 2018 for the study area offshore of Morro Bay, California. The study area is adjacent to a nuclear power plant (currently scheduled for decommissioning) with a developed electric grid connection, and in an area of high wind resource potential. The Bureau of Ocean Energy Management is the lead agency responsible for planning and leasing in the U.S. Exclusive Economic Zone and funded this project to assess baseline conditions of, and the potential effects on, the seafloor environment. This project, carried out by the U.S. Geological Survey, resulted in three data releases for individual map blocks that are part of the California State Waters Map Series: (1) Offshore of Point Estero, (2) Offshore of Morro Bay, and (3) Offshore of Point Buchon. The study area consists of 341 square kilometers (km2) of multibeam echo sounder (MBES) data acquired by Fugro, Inc., in 2010. Towed camera-sled video was acquired in 2012 to supervise the classification of the MBES data into habitats. There were 935 annotations of organisms and habitat made from 22 video transects. Using video observations of habitat as ground truth, derivatives of the MBES data were classified into 3 seafloor character types (hard-rugged, hard-flat, and soft-flat), 25 modifier groups, and 9 geoforms. The study area substrate is predominantly soft-flat sediment (mud and fine sand) covering 191.3 km2 (56.1 percent) of the area. Hard-flat substrate areas, predominantly coarse sediment in scour depressions, cover 52.2 km2 (15.3 percent) of the study area. The hard-rugged substrate areas are primarily outcrops of layered sedimentary bedrock and constitute 97.5 km2 of the study area (28.6 percent). After classification of bathymetry and backscatter raster images according to substrate, false-positive hard areas produced by noise artifacts were removed by manual editing. Nine geoforms were then identified in the analysis. The predominant geoforms mirror the seafloor character results, shelf geoforms (flat areas covered in soft sediment), rock outcrop geoforms (hard, rugged areas), and scour depression geoforms (flat areas covered in coarse sediment formed by bottom currents).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231064","collaboration":"Prepared in cooperation with California State University Monterey Bay, University of California Santa Cruz, the Bureau of Ocean Energy Management, and the California Ocean Protection Council","usgsCitation":"Cochrane, G.R., Kvitek, R., Cole, A., Sherrier, M., Roca-Lezra, A., Hallahan, S., and Dartnell, P., 2023, California State waters map series—Benthic habitat characterization in the region offshore of Morro Bay, California: U.S. Geological Survey Open-File Report 2023–1064, 14 p., https://doi.org/10.3133/ofr20231064.","productDescription":"Report: vii, 14 p.; 3 Data Releases","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-142408","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":420580,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZSTUK1","text":"USGS Data Release","description":"Cochrane, G.R., Cole, A., Sherrier, M., and Hallahan, S., 2022, Bathymetry, backscatter intensity, and benthic habitat offshore of Point Estero, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZSTUK1.","linkHelpText":"Bathymetry, backscatter intensity, and benthic habitat offshore of Point Estero, California"},{"id":420579,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HEZNRO","text":"USGS Data Release","description":"Cochrane, G.R., Cole, A., Sherrier, M., and Roca-Lezra, A., 2022, Bathymetry, backscatter intensity, and benthic habitat offshore of Morro Bay, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9HEZNRO.","linkHelpText":"Bathymetry, backscatter intensity, and benthic habitat offshore of Morro Bay, California"},{"id":499787,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115244.htm","linkFileType":{"id":5,"text":"html"}},{"id":420582,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231064/full"},{"id":420581,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KBGELE","text":"USGS Data Release","description":"Cochrane, G.R., Cole, A., and Sherrier, M., 2022, Bathymetry, backscatter intensity, and benthic habitat offshore of Point Buchon, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9KBGELE.","linkHelpText":"Bathymetry, backscatter intensity, and benthic habitat offshore of Point Buchon, California"},{"id":420575,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1064/covrthb.jpg"},{"id":420576,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1064/ofr20231064.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420577,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1064/ofr20231064.xml"},{"id":420578,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1064/images"}],"country":"United States","state":"California","otherGeospatial":"Morro Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.14748785119099,\n 35.56953868165078\n ],\n [\n -121.14748785119099,\n 35.15085512961322\n ],\n [\n -120.69449617338131,\n 35.15085512961322\n ],\n [\n -120.69449617338131,\n 35.56953868165078\n ],\n [\n -121.14748785119099,\n 35.56953868165078\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-09-06","noUsgsAuthors":false,"publicationDate":"2023-09-06","publicationStatus":"PW","contributors":{"authors":[{"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":882231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kvitek, Rikk","contributorId":203977,"corporation":false,"usgs":false,"family":"Kvitek","given":"Rikk","affiliations":[{"id":36778,"text":"California State University at Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":882232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cole, Aaron","contributorId":214198,"corporation":false,"usgs":false,"family":"Cole","given":"Aaron","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":882233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherrier, Meghan 0000-0002-7857-7737","orcid":"https://orcid.org/0000-0002-7857-7737","contributorId":292303,"corporation":false,"usgs":false,"family":"Sherrier","given":"Meghan","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":882234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roca-Lezra, Alia 0000-0001-6450-3684","orcid":"https://orcid.org/0000-0001-6450-3684","contributorId":329415,"corporation":false,"usgs":false,"family":"Roca-Lezra","given":"Alia","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":true,"id":882235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hallahan, Sean","contributorId":292304,"corporation":false,"usgs":false,"family":"Hallahan","given":"Sean","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":882236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":882237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70250820,"text":"70250820 - 2023 - 3-D wave propagation simulations of Mw 6.5+ earthquakes on the Tacoma Fault, Washington state, considering the effects of topography, a geotechnical gradient, and a fault damage zone","interactions":[],"lastModifiedDate":"2024-01-08T15:59:46.001103","indexId":"70250820","displayToPublicDate":"2023-09-06T09:53:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"3-D wave propagation simulations of Mw 6.5+ earthquakes on the Tacoma Fault, Washington state, considering the effects of topography, a geotechnical gradient, and a fault damage zone","docAbstract":"

We simulate shaking in Tacoma, Washington, and surrounding areas from Mw 6.5 and 7.0 earthquakes on the Tacoma fault. Ground motions are directly modeled up to 2.5 Hz using kinematic, finite‐fault sources; a 3D seismic velocity model considering regional geology; and a model mesh with 30 m sampling at the ground surface. In addition, we explore how adjustments to the seismic velocity model affect predicted shaking over a range of periods. These adjustments include the addition of a region‐specific geotechnical gradient, surface topography, and a fault damage zone. We find that the simulated shaking tends to be near estimates from empirical ground‐motion models (GMMs). However, long‐period (T = 5.0 s) shaking within the Tacoma basin is typically underpredicted by the GMMs. The fit between simulated and GMM‐derived short‐period (T = 0.5 s) shaking is significantly improved with the addition of the geotechnical gradient. From comparing different Mw 6.5 earthquake scenarios, we also find that the response of the Tacoma basin is sensitive to the azimuth of incoming seismic waves. In adding surface topography to the simulation, we find that average ground motion is similar to that produced from the nontopography model. However, shaking is often amplified at topographic highs and deamplified at topographic lows, and the wavefield undergoes extensive scattering. Adding a fault damage zone has the effect of amplifying short‐period shaking adjacent to the fault, while reducing far‐field shaking. Intermediate‐period shaking is amplified within the Tacoma basin, likely due to enhanced surface‐wave generation attributable to the fault damage zone waveguide. When applied in the same model, the topography and fault damage zone adjustments often enhance or reduce the effects of one another, adding further complexity to the wavefield. These results emphasize the importance of improving near‐surface velocity model resolution as waveform simulations progress toward higher frequencies.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230083","usgsCitation":"Stone, I.P., Wirth, E.A., Grant, A.R., and Frankel, A.D., 2023, 3-D wave propagation simulations of Mw 6.5+ earthquakes on the Tacoma Fault, Washington state, considering the effects of topography, a geotechnical gradient, and a fault damage zone: Bulletin of the Seismological Society of America, v. 113, no. 6, p. 2519-2542, https://doi.org/10.1785/0120230083.","productDescription":"24 p.","startPage":"2519","endPage":"2542","ipdsId":"IP-151026","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":424180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","city":"Tacoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.94849646816715,\n 47.52066759288792\n ],\n [\n -122.94849646816715,\n 47.09223788435119\n ],\n [\n -121.84278435348952,\n 47.09223788435119\n ],\n [\n -121.84278435348952,\n 47.52066759288792\n ],\n [\n -122.94849646816715,\n 47.52066759288792\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"113","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Stone, Ian P. 0000-0003-2622-2691","orcid":"https://orcid.org/0000-0003-2622-2691","contributorId":293630,"corporation":false,"usgs":true,"family":"Stone","given":"Ian","middleInitial":"P.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":891672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":891673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":891674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":891675,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248856,"text":"70248856 - 2023 - Upscaling wetland methane emissions from the FLUXNET-CH4 Eddy Covariance Network (UpCH4 v1.0): Model development, network assessment, and budget comparison","interactions":[],"lastModifiedDate":"2023-09-25T14:13:49.241689","indexId":"70248856","displayToPublicDate":"2023-09-06T08:13:10","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7751,"text":"AGU Advances","active":true,"publicationSubtype":{"id":10}},"title":"Upscaling wetland methane emissions from the FLUXNET-CH4 Eddy Covariance Network (UpCH4 v1.0): Model development, network assessment, and budget comparison","docAbstract":"

Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH4 emissions of 146 ± 43 TgCH4 y−1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH4 y−1) and overlaps with top-down atmospheric inversion models (155–200 TgCH4 y−1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023AV000956","usgsCitation":"McNicol, G., Fluet-Chouinard, E., Ouyang, Z., Knox, S., Zhen, Z., Aalto, T., Bansal, S., Chang, K., Chen, M., Delwiche, K., Feron, S., Goeckede, M., Liu, J., Malhotra, A., Melton, J.R., Riley, W., Vargas, R., Yuan, K., Yang, Q., Zhu, Q., Alekseychik, P., Aurela, M., Billesbach, D., Campbell, D.I., Chen, J., Chu, H., Desai, A., Euskirchen, E., Goodrich, J., Griffis, T., Helbig, M., Hirano, T., Iwata, H., Jurasinski, G., King, J., Koebsch, F., Kolka, R., Krauss, K., Lohila, A., Ivan Mammarella, Nilson, M., Noormets, A., Oechel, W., Peichl, M., Sachs, T., Sakabe, A., Schulze, C., Sonnentag, O., Sullivan, R., Tuittila, E., Ueyama, M., Vesala, T., Ward, E., Wille, C., Wong, G.X., Zona, D., Windham-Myers, L., Poulter, B., and Jackson, R., 2023, Upscaling wetland methane emissions from the FLUXNET-CH4 Eddy Covariance Network (UpCH4 v1.0): Model development, network assessment, and budget comparison: AGU Advances, v. 4, no. 5, e2023AV000956, 24 p., https://doi.org/10.1029/2023AV000956.","productDescription":"e2023AV000956, 24 p.","ipdsId":"IP-139161","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":442175,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023av000956","text":"Publisher Index Page"},{"id":421127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"McNicol, Gavin 0000-0002-6655-8045","orcid":"https://orcid.org/0000-0002-6655-8045","contributorId":260536,"corporation":false,"usgs":false,"family":"McNicol","given":"Gavin","email":"","affiliations":[],"preferred":false,"id":883903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fluet-Chouinard, Etienne","contributorId":217392,"corporation":false,"usgs":false,"family":"Fluet-Chouinard","given":"Etienne","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":883904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ouyang, Zutao","contributorId":260556,"corporation":false,"usgs":false,"family":"Ouyang","given":"Zutao","email":"","affiliations":[],"preferred":false,"id":883905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knox, Sarah 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":167493,"corporation":false,"usgs":false,"family":"Knox","given":"Sarah","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":883906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhen, Zhang","contributorId":126792,"corporation":false,"usgs":false,"family":"Zhen","given":"Zhang","email":"","affiliations":[{"id":6616,"text":"Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730060, China","active":true,"usgs":false}],"preferred":false,"id":883907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aalto, Tuula","contributorId":330041,"corporation":false,"usgs":false,"family":"Aalto","given":"Tuula","email":"","affiliations":[{"id":51882,"text":"Finnish Meteorological Institute, Finland","active":true,"usgs":false}],"preferred":false,"id":883908,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":883909,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chang, Kuang-Yu 0000-0002-7859-5871","orcid":"https://orcid.org/0000-0002-7859-5871","contributorId":260439,"corporation":false,"usgs":false,"family":"Chang","given":"Kuang-Yu","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":883910,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chen, Min","contributorId":330043,"corporation":false,"usgs":false,"family":"Chen","given":"Min","affiliations":[{"id":78773,"text":"University of Wisconsin-Madison, Wisconsin, USA","active":true,"usgs":false}],"preferred":false,"id":883911,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Delwiche, Kyle","contributorId":330044,"corporation":false,"usgs":false,"family":"Delwiche","given":"Kyle","affiliations":[{"id":36942,"text":"University of California, 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The dynamics of wintering waterfowl populations at the landscape scale are the result of complex interactions of environmental, behavioral and energetic drivers. Agent-based models provide a method to directly link these factors in a spatially explicit framework and allow the emergence of patterns from the aggregation of individual agent actions. We adapted the Spatially-explicit Waterbird Agent-based Model Program (SWAMP), originally developed for waterfowl in central California, to simulate a basin-scale population of mallards (A. platyrhynchos) wintering in the Mississippi Alluvial Valley over a four-month period (November–February). Simulated agents move within the landscape, foraging on areas made available based on a probabilistic inundation status, and converting food resources to endogenous energy. The model uses a high-resolution map of eastern Arkansas waterfowl habitats and incorporates a hierarchical habitat selection system that enables mallards to relocate at increasing scales in response to changing food availability. We validated the performance of modeled mallard body condition and behavioral metrics under a range of environmental conditions against expected outcomes derived from empirical data and found that the simulation produced realistic representations of changes in flight distances, energy expenditure, lipid storage, and foraging habitat use in response to depleting food resources over time. We discuss the model's applicability as a tool to quantify waterfowl response to a range of environmental conditions and to evaluate scenarios of landscape composition and configuration in the context of waterfowl population management.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2023.110488","usgsCitation":"Weller, F.G., Webb, E.B., Fogenburg, S., Beatty, W., Kesler, D., Blenk, R.H., Ringelman, K.M., Miller, M.L., and Eadie, J., 2023, An agent-based model to quantify energetics, movement and habitat selection of mid-continent mallards in the Mississippi Alluvial Valley: Ecological Modelling, v. 485, 110488, https://doi.org/10.1016/j.ecolmodel.2023.110488.","productDescription":"110488","ipdsId":"IP-151506","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":442176,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://repository.lsu.edu/agrnr_pubs/679","text":"Publisher Index Page"},{"id":432333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"485","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weller, Florian G.","contributorId":341013,"corporation":false,"usgs":false,"family":"Weller","given":"Florian","email":"","middleInitial":"G.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":907803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fogenburg, Sean","contributorId":341014,"corporation":false,"usgs":false,"family":"Fogenburg","given":"Sean","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":907805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":224795,"corporation":false,"usgs":true,"family":"Beatty","given":"William S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":907806,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kesler, Dylan","contributorId":341015,"corporation":false,"usgs":false,"family":"Kesler","given":"Dylan","affiliations":[{"id":37290,"text":"The Institute for Bird Populations","active":true,"usgs":false}],"preferred":false,"id":907807,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blenk, Robert H.","contributorId":341016,"corporation":false,"usgs":false,"family":"Blenk","given":"Robert","email":"","middleInitial":"H.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":907808,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ringelman, Kevin M.","contributorId":341017,"corporation":false,"usgs":false,"family":"Ringelman","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":907809,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Matt L.","contributorId":341018,"corporation":false,"usgs":false,"family":"Miller","given":"Matt","email":"","middleInitial":"L.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":907810,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Eadie, John M.","contributorId":341020,"corporation":false,"usgs":false,"family":"Eadie","given":"John M.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":907811,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70250860,"text":"70250860 - 2023 - Seasonal differences and grazing pressure alter the fate of gold nanoparticles in a microcosm experiment","interactions":[],"lastModifiedDate":"2024-01-10T16:36:51.665148","indexId":"70250860","displayToPublicDate":"2023-09-05T10:31:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal differences and grazing pressure alter the fate of gold nanoparticles in a microcosm experiment","docAbstract":"

Gold nanoparticles (AuNPs) are used as models to track and predict NP fates and effects in ecosystems. Previous work found that aquatic macrophytes and their associated biofilm primarily drove the fate of AuNPs within aquatic ecosystems and that seasonality was an important abiotic factor in the fate of AuNPs. Therefore, the present work aims to study if grazers, by feeding on these interfaces, modify the AuNP fate and if this is altered by seasonal fluctuations. Microcosms were dosed with 44.8 μg/L of AuNP weekly for 4 weeks and maintained in environmental chambers simulating Spring and Fall light and temperature conditions. We discovered that seasonal changes and the presence of grazers significantly altered the fate of Au. Higher temperatures in the warmer season increased dissolved organic carbon (DOC) content in the water column, leading to stabilization of Au in the water column. Additionally, snail grazing on biofilm growing on the Egeria densa surface led to a transfer of Au from macrophytes to the organic matter above the sediments. These results demonstrate that climate and grazers significantly impacted the fate of Au from AuNPs, highlighting the role that grazers might have in a large and biologically more complex ecosystem.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.3c01839","usgsCitation":"Bergemann, C.M., Avellan, A., Perrotta, B.G., Bernhardt, E.S., and Simonin, M., 2023, Seasonal differences and grazing pressure alter the fate of gold nanoparticles in a microcosm experiment: Environmental Science & Technology, v. 57, no. 37, p. 13970-13979, https://doi.org/10.1021/acs.est.3c01839.","productDescription":"10 p.","startPage":"13970","endPage":"13979","ipdsId":"IP-155275","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":442179,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-04208811","text":"External Repository"},{"id":424283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"37","noUsgsAuthors":false,"publicationDate":"2023-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Bergemann, Christina M.","contributorId":333057,"corporation":false,"usgs":false,"family":"Bergemann","given":"Christina","email":"","middleInitial":"M.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":891815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Avellan, Astrid","contributorId":333058,"corporation":false,"usgs":false,"family":"Avellan","given":"Astrid","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":891816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perrotta, Brittany G. 0000-0003-2669-3047","orcid":"https://orcid.org/0000-0003-2669-3047","contributorId":301929,"corporation":false,"usgs":true,"family":"Perrotta","given":"Brittany","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":891817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernhardt, Emily S.","contributorId":173736,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily","email":"","middleInitial":"S.","affiliations":[{"id":27285,"text":"Duke Univerisity","active":true,"usgs":false}],"preferred":false,"id":891818,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simonin, Marie 0000-0003-1493-881X","orcid":"https://orcid.org/0000-0003-1493-881X","contributorId":304843,"corporation":false,"usgs":false,"family":"Simonin","given":"Marie","email":"","affiliations":[{"id":66161,"text":"Université d’Angers","active":true,"usgs":false}],"preferred":false,"id":891819,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248027,"text":"sir20235085 - 2023 - Updates to CE-QUAL-W2 models for select U.S. Army Corps of Engineers reservoirs in the Willamette Valley Project and an inter-reservoir reach of the Middle Fork Willamette River, northwestern Oregon","interactions":[],"lastModifiedDate":"2025-08-14T19:42:16.158318","indexId":"sir20235085","displayToPublicDate":"2023-09-05T09:38:18","publicationYear":"2023","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":"2023-5085","displayTitle":"Updates to CE-QUAL-W2 Models for Select U.S. Army Corps of Engineers Reservoirs in the Willamette Valley Project and an Inter-Reservoir Reach of the Middle Fork Willamette River, Northwestern Oregon","title":"Updates to CE-QUAL-W2 models for select U.S. Army Corps of Engineers reservoirs in the Willamette Valley Project and an inter-reservoir reach of the Middle Fork Willamette River, northwestern Oregon","docAbstract":"

Mechanistic models capable of simulating hydrodynamics and water temperature in rivers and reservoirs are valuable tools for investigating thermal conditions and their relation to dam operations and streamflow in river basins where upstream water storage and management decisions have an important influence on river reaches with threatened fish populations. In particular, models allow managers to investigate how new, untried operations or hypothetical structures might influence streamflow and temperature conditions downstream. CE-QUAL-W2 is a two-dimensional (laterally averaged) hydrodynamic water-quality model that has previously been used to investigate the downstream effects of dam operations and other anthropogenic influences on stream temperature in the Willamette River Basin in northwestern Oregon, a region with two populations of fish species designated as threatened under the Endangered Species Act. By linking CE-QUAL-W2 river models to models of upstream, large Willamette Valley Project dams and reservoirs, these models can be used to investigate how dam operations at individual dams can influence streamflow and thermal conditions in downstream river reaches as an integrated system. Integrated model simulations that include the large dams and reservoirs linked to downstream river reaches can help managers develop a better understanding of tradeoffs associated with potential retrofits or operational changes across the multipurpose dams in the Willamette Valley Project, the effect of dam management on downstream tributaries and the Willamette River, and the resulting potential effect on threatened fish populations and habitat conditions.

River models capable of simulating river corridors downstream from U.S. Army Corps of Engineers dams were previously updated and integrated to simulate conditions that occurred from March through October of 2011 (a cool and wet year), 2015 (a hot and dry year), and 2016 (a moderately hot and dry year) using CE-QUAL-W2 version 4.2. These river models encompass the following:

This report documents model modifications, boundary condition data sources or estimation methods, and goodness-of-fit statistics for six CE-QUAL-W2 reservoir models and one river model upstream from the existing river models. These models simulate (1) Hills Creek Lake; (2) Lookout Point Lake and Dexter Reservoir on the Middle Fork Willamette River; (3) the Middle Fork Willamette River reach between Hills Creek Dam upstream and Lookout Point Lake downstream; (4) Cougar Reservoir on the South Fork McKenzie River; (5) Green Peter Lake on the Middle Santiam River and Foster Lake on the South Santiam River; and (6) Detroit Lake and (7) Big Cliff Reservoir on the North Santiam River. These CE-QUAL-W2 models were built by a variety of researchers to simulate a range of conditions in past years; this report documents their upgrade to U.S. Geological Survey (USGS) edition 7 of version 4.2 of CE-QUAL-W2 and updates each model to simulate conditions from January through December of 2011, 2015, and 2016. Also included in this report is an explanation of modifications to the CE-QUAL-W2 source code that constitute USGS edition 7 of CE-QUAL-W2 version 4.2. Each of the models described in this report can be run in isolation or linked to downstream models as a “system model” to simulate conditions in tributaries and (or) in the Willamette Valley Project as a whole.

As part of the model updates described in this report, some model parameters were adjusted to improve stability or decrease model error, and boundary conditions including meteorological, hydrologic, and temperature inputs were developed and updated for model years 2011, 2015, and 2016, as necessary. In some cases, the data sources used to drive previous model versions were no longer available, which required the development and checking of new data sources or estimation techniques. Goodness-of-fit statistics for outflow from the dams and in simulated river reaches generally show a good model fit, with the models simulating subdaily water temperatures at most comparable locations with a mean absolute error of generally less than 1 degree Celsius (°C) and a reasonably low bias. Model simulation of the thermal vertical profiles in each reservoir also produced an overall mean absolute error of generally less than 1 °C for all 3 years, with the exception of the Hills Creek Lake Model and the Cougar Reservoir Model in years when the reservoirs did not fill (2015 and 2016). Both of these models have known calibration issues and tend to be sensitive to the choice of certain structural parameters in the model. Overall, the calibration process was focused on obtaining model settings that led to realistic water temperature predictions in all 3 years (2011, 2015, and 2016) without over-calibrating specifically to any single year. A complete investigation of model error for these reservoir submodels was beyond the scope of this investigation but could be undertaken in the future if better model performance for these two reservoirs is desired.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235085","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Stratton Garvin, L.E., Buccola, N.L., and Rounds, S.A., 2023, Updates to CE-QUAL-W2 models for select U.S. Army Corps of Engineers reservoirs in the Willamette Valley Project and an inter-reservoir reach of the Middle Fork Willamette River, northwestern Oregon (ver. 1.1, June 2025): U.S. Geological Survey Scientific Investigations Report 2023–5085, 89 p., https://doi.org/10.3133/sir20235085.","productDescription":"Report: xii, 89 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-141377","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":494149,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115245.htm","linkFileType":{"id":5,"text":"html"}},{"id":420372,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5085/sir20235085.XML"},{"id":420371,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5085/images"},{"id":420373,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UJFXA5","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 models for select U.S. Army Corps of Engineers reservoirs in the Willamette Valley Project and an inter-reservoir reach of the Middle Fork Willamette River, northwestern Oregon, 2011, 2015, and 2016 (ver. 1.1, May 2025)"},{"id":491287,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2023/5085/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}},{"id":420368,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5085/coverthb2.jpg"},{"id":420369,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5085/sir20235085.pdf","text":"Report","size":"24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5085"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.45633507532085,\n 45.58946612874976\n ],\n [\n -122.9361641346579,\n 46.04098363545978\n ],\n [\n -123.5145410212395,\n 45.5627587310459\n ],\n [\n -123.63148629596873,\n 44.60670825289975\n ],\n [\n -123.5623951104441,\n 43.59496378124939\n ],\n [\n -123.05635970383773,\n 43.13379451064938\n ],\n [\n -121.74055049946932,\n 42.79157283626091\n ],\n [\n -121.20756798908744,\n 43.3534143414802\n ],\n [\n -121.15566880710551,\n 44.42799279254055\n ],\n [\n -121.3336847614029,\n 45.19900479802473\n ],\n [\n -121.88806972979938,\n 45.53916954884161\n ],\n [\n -122.45633507532085,\n 45.58946612874976\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: September 5, 2023; Version 1.1: June 27, 2025","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
601 SW Second Avenue, Suite 1950
Portland, Oregon 97204

","tableOfContents":"","publishedDate":"2023-09-05","revisedDate":"2025-06-27","noUsgsAuthors":false,"publicationDate":"2023-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Stratton Garvin, Laurel E. 0000-0001-8567-8619 lstratton@usgs.gov","orcid":"https://orcid.org/0000-0001-8567-8619","contributorId":270182,"corporation":false,"usgs":true,"family":"Stratton Garvin","given":"Laurel","email":"lstratton@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buccola, Norman L. 0000-0002-9590-2458 nbuccola@usgs.gov","orcid":"https://orcid.org/0000-0002-9590-2458","contributorId":139096,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman","email":"nbuccola@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881557,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248306,"text":"70248306 - 2023 - Informing management of recovering predators and their prey with ecological diffusion models","interactions":[],"lastModifiedDate":"2023-12-04T17:13:19.395597","indexId":"70248306","displayToPublicDate":"2023-09-05T08:25:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Informing management of recovering predators and their prey with ecological diffusion models","docAbstract":"

The reintroduction and recovery of predators can be ecologically beneficial as well as socially and economically controversial. However, the growth and expansion of predator populations, and thus their ecological, social, and economic impacts, are not static but rather they vary in space and time. We propose a spatiotemporal statistical modeling framework based on ecological diffusion to better inform the ecology and management of recovering predators and their prey. We demonstrate its utility by applying it to a recovering sea otter (Enhydra lutris) population in Southeast Alaska, where sea otters were reintroduced in the late 1960s and have exhibited unprecedented population growth. Estimated parameters yield inferences about movement and population ecology, and our approach provides useful derived quantities, such as local abundance and carrying capacity as well as a quantity we term the equilibrium differential. We used our model to examine how density dependence and carrying capacity of sea otters vary spatially across a region. The diffusion modeling approach we present can be generalized for use in other instances of (re)colonization across taxa to inform management and conservation efforts.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.2673","usgsCitation":"Eisaguirre, J.M., Williams, P.J., Lu, X., Kissling, M.L., Schutte, P.A., Weitzman, B.P., Beatty, W., Esslinger, G.G., Womble, J., and Hooten, M.B., 2023, Informing management of recovering predators and their prey with ecological diffusion models: Frontiers in Ecology and the Environment, v. 21, no. 10, p. 479-488, https://doi.org/10.1002/fee.2673.","productDescription":"10 p.","startPage":"479","endPage":"488","ipdsId":"IP-139715","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":420618,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"http://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 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A Eurasian lineage highly pathogenic avian influenza virus (HPAIV) of the clade 2.3.4.4b (Goose/Guangdong lineage) was detected in migratory bird populations in North America in December 2021, and it, along with its reassortants, have since caused wild and domestic bird outbreaks across the continent. Relative to previous outbreaks, HPAIV cases among wild birds in 2022 exhibited wider geographic extent within North America and higher levels of mortality, suggesting the potential for population-level impacts. Given the possible conservation implications of HPAIV in wild birds, natural resource managers have sought guidance on actions that may mitigate negative effects of disease among North American bird populations, including modification of existing management practices. Banding of waterfowl is a critical tool for population management for several harvested species in North America, but some banding techniques, such as bait trapping, can lead to increased congregation of waterfowl, potentially altering HPAIV transmission. We used an expert opinion exercise to assess how bait trapping of dabbling ducks in Canada may influence HPAIV transmission and wild bird health. The expert group found that it is moderately likely that bait trapping of dabbling ducks in wetlands will significantly increase the transmission of HPAIV among individual ducks, but there is a low probability that this will result in significant population-level effects on North American dabbling ducks. Considering the lack of empirical work studying how capture and handling methods may change transmission of HPAIV among waterfowl, as well as the importance of bait trapping for waterfowl management in North America, future work should focus on filling knowledge gaps pertaining to the influence of baiting on HPAIV occurrence to better inform banding procedures and management decision making.

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Agricultural headwater streams and ditches commonly host dense stands of aquatic vegetation that grow and decay over seasons and exert physical and biological controls on the transport of nutrients from cropland to larger rivers. This study examined changes in the transport of phosphorus (P) in an agricultural drainage ditch in the Maumee River Basin (Ohio, USA) by conducting constant rate injections of a novel tracer mixture (conservative salt [Cl as NaCl], dissolved P [KH2PO4], and a fluorescent fine particle) in spring, summer, and fall. We quantified transport behavior for solutes and particles using a traditional transient storage modeling framework consisting of mobile and immobile storage zones connected by a first-order exchange rate constant. Transient storage was greatest during the spring, when thicker vegetation caused more pooling and flow stagnation, and decreased through fall, as vegetation thinned. Soluble P uptake lengths were 8.7 times longer in fall than spring, likely due to declines in biological uptake rates with colder temperatures and immobile zone storage with thinning vegetation. Particle capture lengths also decreased by a factor of 4.3 from fall to spring. With the increasing eutrophication of Lake Erie and waterbodies around the world that lie downstream from agricultural landscapes, it is beneficial to understand nutrient transport across watersheds, including small agricultural streams. This study highlights the physical and biological roles that aquatic vegetation plays in small agricultural streams by creating seasonally variable immobile zones that slow the flow of nutrients, providing surface area for biofilms, and capturing particles that bind nutrients.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR033782","usgsCitation":"Field, H.R., Sawyer, A.H., Welch, S.A., Benefiel, R.K., Mathie, D.M., Hood, J.M., Pawlowski, E.D., Karwan, D.L., Kreiling, R.M., Johnson, Z.I., Hanrahan, B.R., and King, K.W., 2023, Importance of dense aquatic vegetation in seasonal phosphate and particle transport in an agricultural headwater stream: Water Resources Research, v. 59, no. 9, e2022WR033782, 17 p., https://doi.org/10.1029/2022WR033782.","productDescription":"e2022WR033782, 17 p.","ipdsId":"IP-145730","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":442192,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr033782","text":"Publisher Index Page"},{"id":421126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Field, Hannah R.","contributorId":330103,"corporation":false,"usgs":false,"family":"Field","given":"Hannah","email":"","middleInitial":"R.","affiliations":[{"id":78811,"text":"The Ohio State University, School of Earth Sciences, Columbus, OH, United States","active":true,"usgs":false}],"preferred":false,"id":883999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sawyer, Audrey H.","contributorId":330104,"corporation":false,"usgs":false,"family":"Sawyer","given":"Audrey","email":"","middleInitial":"H.","affiliations":[{"id":78811,"text":"The Ohio State University, School of Earth Sciences, Columbus, OH, United States","active":true,"usgs":false}],"preferred":false,"id":884000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welch, Susan A.","contributorId":330105,"corporation":false,"usgs":false,"family":"Welch","given":"Susan","email":"","middleInitial":"A.","affiliations":[{"id":78811,"text":"The Ohio State University, School of Earth Sciences, Columbus, OH, United States","active":true,"usgs":false}],"preferred":false,"id":884001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benefiel, Ryan K.","contributorId":330106,"corporation":false,"usgs":false,"family":"Benefiel","given":"Ryan","email":"","middleInitial":"K.","affiliations":[{"id":78811,"text":"The Ohio State University, School of Earth Sciences, Columbus, OH, United States","active":true,"usgs":false}],"preferred":false,"id":884002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mathie, Devan M.","contributorId":330107,"corporation":false,"usgs":false,"family":"Mathie","given":"Devan","email":"","middleInitial":"M.","affiliations":[{"id":78811,"text":"The Ohio State University, School of Earth Sciences, Columbus, OH, United States","active":true,"usgs":false}],"preferred":false,"id":884003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hood, James M.","contributorId":267332,"corporation":false,"usgs":false,"family":"Hood","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":884004,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pawlowski, Ethan D.","contributorId":218062,"corporation":false,"usgs":false,"family":"Pawlowski","given":"Ethan","email":"","middleInitial":"D.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":884005,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Karwan, Diana L.","contributorId":207315,"corporation":false,"usgs":false,"family":"Karwan","given":"Diana","email":"","middleInitial":"L.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":884006,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kreiling, Rebecca M. 0000-0002-9295-4156","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":202193,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":884007,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Zackary I.","contributorId":330108,"corporation":false,"usgs":false,"family":"Johnson","given":"Zackary","email":"","middleInitial":"I.","affiliations":[{"id":78814,"text":"Duke University, Nicholas School of the Environment, Duke Marine Laboratory, Beaufort, NC, United States","active":true,"usgs":false}],"preferred":false,"id":884008,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hanrahan, Brittany R.","contributorId":330109,"corporation":false,"usgs":false,"family":"Hanrahan","given":"Brittany","email":"","middleInitial":"R.","affiliations":[{"id":78815,"text":"U.S. Department of Agriculture, Agricultural Research Service, Columbus, OH, United States","active":true,"usgs":false}],"preferred":false,"id":884009,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"King, Kevin W.","contributorId":330110,"corporation":false,"usgs":false,"family":"King","given":"Kevin","email":"","middleInitial":"W.","affiliations":[{"id":78815,"text":"U.S. Department of Agriculture, Agricultural Research Service, Columbus, OH, United States","active":true,"usgs":false}],"preferred":false,"id":884010,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70248272,"text":"70248272 - 2023 - Wind-modulated groundwater discharge along a microtidal Arctic coastline","interactions":[],"lastModifiedDate":"2023-09-06T11:47:24.361413","indexId":"70248272","displayToPublicDate":"2023-09-05T06:35:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Wind-modulated groundwater discharge along a microtidal Arctic coastline","docAbstract":"

Groundwater discharge transports dissolved constituents to the ocean, affecting coastal carbon budgets and water quality. However, the magnitude and mechanisms of groundwater exchange along rapidly transitioning Arctic coastlines are largely unknown due to limited observations. Here, using first-of-its-kind coastal Arctic groundwater timeseries data, we evaluate the magnitude and drivers of groundwater discharge to Alaska's Beaufort Sea coast. Darcy flux calculations reveal temporally variable groundwater fluxes, ranging from −6.5 cm d−1 (recharge) to 14.1 cm d−1 (discharge), with fluctuations in groundwater discharge or aquifer recharge over diurnal and multiday timescales during the open-water season. The average flux during the monitoring period of 4.9 cm d−1 is in line with previous estimates, but the maximum discharge exceeds previous estimates by over an order-of-magnitude. While the diurnal fluctuations are small due to the microtidal conditions, multiday variability is large and drives sustained periods of aquifer recharge and groundwater discharge. Results show that wind-driven lagoon water level changes are the dominant mechanism of fluctuations in land–sea hydraulic head gradients and, in turn, groundwater discharge. Given the microtidal conditions, low topographic relief, and limited rainfall along the Beaufort Sea coast, we identify wind as an important forcing mechanism of coastal groundwater discharge and aquifer recharge with implications for nearshore biogeochemistry. This study provides insights into groundwater flux dynamics along this coastline over time and highlights an oft overlooked discharge and circulation mechanism with implications towards refining solute export estimates to coastal Arctic waters.

","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/acf0d8","usgsCitation":"Guimond, J., Demir, C., Kurylyk, B.L., Walvoord, M.A., McClelland, J., and Cardenas, M.B., 2023, Wind-modulated groundwater discharge along a microtidal Arctic coastline: Environmental Research Letters, v. 18, 094042, 10 p., https://doi.org/10.1088/1748-9326/acf0d8.","productDescription":"094042, 10 p.","ipdsId":"IP-155579","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":442198,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/acf0d8","text":"Publisher Index Page"},{"id":420538,"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 -149.8787190288838,\n 70.63569535875706\n ],\n [\n -149.8787190288838,\n 70.39401335666025\n ],\n [\n -148.90750421618975,\n 70.39401335666025\n ],\n [\n -148.90750421618975,\n 70.63569535875706\n ],\n [\n -149.8787190288838,\n 70.63569535875706\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","noUsgsAuthors":false,"publicationDate":"2023-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Guimond, Julia","contributorId":266043,"corporation":false,"usgs":false,"family":"Guimond","given":"Julia","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":882179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demir, Casu","contributorId":329392,"corporation":false,"usgs":false,"family":"Demir","given":"Casu","email":"","affiliations":[{"id":29861,"text":"The University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":882180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":882181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":882182,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McClelland, James W.","contributorId":255074,"corporation":false,"usgs":false,"family":"McClelland","given":"James W.","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":882183,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cardenas, M. Bayani","contributorId":181932,"corporation":false,"usgs":false,"family":"Cardenas","given":"M.","email":"","middleInitial":"Bayani","affiliations":[],"preferred":false,"id":882184,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70249543,"text":"70249543 - 2023 - Using airborne electromagnetics to improve depth to bedrock estimates in Wisconsin","interactions":[],"lastModifiedDate":"2026-03-19T15:28:47.349369","indexId":"70249543","displayToPublicDate":"2023-09-04T10:21:36","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Using airborne electromagnetics to improve depth to bedrock estimates in Wisconsin","docAbstract":"

Depth to bedrock is an important factor in hydrologic systems. The thickness of glacial sediments overlying bedrock in Wisconsin controls the routing of groundwater in surficial aquifers and its Depth to bedrock is often an important factor in hydrologic systems because hydraulic properties of bedrock and overlying sediments are typically appreciably different. For example, the thickness of glacial sediments overlying bedrock in Wisconsin controls the routing of groundwater in surficial aquifers and its connection with surface water bodies such as lakes and wetlands. In fractured bedrock environments, shallow bedrock can be vulnerable to degraded water quality when contaminants at the surface infiltrate quickly through permeable formations. Here, airborne electromagnetic surveys were acquired in three different parts of Wisconsin, totalling more than 5,700 flight line-kilometers, to improve understanding of depth to bedrock, the lithologic composition of overlying sediments, and as input structure for groundwater model development.

","conferenceTitle":"AEM2023 8th International Airborne Electromagnetics Workshop","conferenceDate":"September 3-7, 2023","conferenceLocation":"Fitzroy Island, Queensland, Australia","language":"English","publisher":"Australian Society of Exploration Geophysicists","doi":"10.5281/zenodo.10067960","usgsCitation":"Minsley, B.J., Crosbie, K.J., Duncker, J.J., Feinstein, D.T., Haas, L., Hart, D., Hunt, R.J., and Komiskey, M.J., 2023, Using airborne electromagnetics to improve depth to bedrock estimates in Wisconsin, AEM2023 8th International Airborne Electromagnetics Workshop, Fitzroy Island, Queensland, Australia, September 3-7, 2023, Extended abstract for AEM 2023 conference, https://doi.org/10.5281/zenodo.10067960.","productDescription":"Extended abstract for AEM 2023 conference","ipdsId":"IP-151339","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science 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Rangelands comprise 40% of the conterminous United States and they supply essential ecosystem services to society. A scenario assessment was conducted to determine how accelerating biophysical and societal drivers may modify their future availability. Four scenarios emerged: two may maintain rural communities by sustaining the prevailing ecosystem service of beef cattle production, and two may transform rural communities through expansion of renewable energy technologies and infusion of external capital from amenity land sales. Collaborative organizations representing diverse societal sectors may most effectively identify and manage trade-offs among ecosystem service availability, and equitably prioritize food and energy security, environmental quality and cultural identity.

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