TopoBuilder is a public web application from the National Geospatial Program that enables anyone to create customized digital U.S. Geological Survey (USGS) topographic maps, called OnDemand Topos, with the best available, most up-to-date data from The National Map (nationalmap.gov). OnDemand Topos can be made at different scales or quadrangles and can cover anywhere within the United States and its territories.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243041","usgsCitation":"Guidero, E.M., Doumbouya, A.T., Adkins, K.F., and Urban-Mathieux, B., 2024, topoBuilder quick start guide: U.S. Geological Survey Fact Sheet 2024–3041, 2 p., https://doi.org/10.3133/fs20243041.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-167174","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":464566,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3041/coverthb.jpg"},{"id":464567,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3041/fs20243041.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":464568,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3041/fs20243041.XML"},{"id":464569,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3041/images"},{"id":464570,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243041/full"}],"contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
The “National Field Manual for the Collection of Water-Quality Data” (NFM) provides guidelines and procedures for U.S. Geological Survey (USGS) personnel who collect data used to assess the quality of the Nation’s surface-water and groundwater resources. This chapter, NFM A6.1, provides guidance and protocols for the measurement of temperature of air, of a surface-water body or in groundwater, which include the scientific basis of the measurement, selection and maintenance of equipment, calibration verification, troubleshooting, and procedures for measurement and reporting. It updates and supersedes USGS Techniques of Water-Resources Investigations, book 9, chapter A6.1, version 2.0, by Franceska D. Wilde.
Temperature of air and water is routinely measured when water samples are collected, is often measured continually at USGS streamgages, and is a parameter regularly measured during laboratory and field experiments. The field method for measuring temperature described in this chapter is applicable to air and most natural waters.
Before 2017, the NFM chapters were released in the USGS Techniques of Water-Resources Investigations series. Effective in 2018, new and revised NFM chapters are being released in the USGS Techniques and Methods series; this series change does not affect the content and format of the NFM. More information is in the general introduction to the NFM (USGS Techniques and Methods, book 9, chapter A0) at https://doi.org/10.3133/tm9A0. The authoritative current versions of NFM chapters are available in the USGS Publications Warehouse at https://pubs.usgs.gov/. Comments, questions, and suggestions related to the NFM can be addressed to nfm@usgs.gov.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm9A6.1","usgsCitation":"U.S. Geological Survey, 2024, Temperature: U.S. Geological Survey Techniques and Methods, book 9, chap. A6.1, 14 p., https://doi.org/10.3133/tm9A6.1. [Supersedes USGS Techniques of Water-Resources Investigations, book 9, chap. A6.1, version 2.0.]","productDescription":"v, 14 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-157281","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":465033,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/09/a6.1/images"},{"id":465035,"rank":7,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/mission-areas/water-resources/science/national-field-manual-collection-water-quality-data-nfm","text":"National Field Manual for the Collection of Water-Quality Data (NFM)"},{"id":465029,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/09/a6.1/coverthb.jpg"},{"id":465030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/09/a6.1/tm9a6.1.pdf","text":"Report","size":"940 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 9-A6.1 PDF"},{"id":465031,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm9A6.1/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"TM 9-A6.1 HTML"},{"id":465032,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/09/a6.1/tm9a6.1.XML","linkFileType":{"id":8,"text":"xml"},"description":"TM 9-A6.1 XML"},{"id":465034,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm9A0","text":"Techniques and Methods 9-A0","linkHelpText":"- General introduction for the “National Field Manual for the Collection of Water-Quality Data”"}],"contact":"Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Email: nfm@usgs.gov
","tableOfContents":"The Colorado River is an important water source in the southwestern United States and northern Mexico. High concentrations of dissolved solids in the river, sourced mainly from the Upper Colorado River Basin (UCOL), cause hundreds of millions of dollars in damages annually to crops and infrastructure. Determinations of total dissolved solids (TDS) in river and tributary samples often rely on summed concentrations of constituents in solution reported as the sum of constituents (SOC), which includes the bicarbonate concentration converted to the equivalent carbonate mass that would be present as a residue after drying. Alternatively, salinity, similar to SOC but including the entire concentration of bicarbonate in solution, may be used as a measure of dissolved solids. Use of SOC results may under-represent actual dissolved-solids concentrations and loads in streams where bicarbonate is a substantial component of the dissolved solids in solution. The objective of this manuscript is to evaluate the differences between the SOC and salinity determinations of dissolved solids in UCOL streams and rivers. Water-quality data from the U.S. Geological Survey were used to compute salinity concentrations at UCOL stream sites for comparison with SOC determinations. Results from 8,001 samples at 418 UCOL sites indicate a median increase in dissolved solids of 20% (13% and 30%, 25th and 75th percentiles, respectively) using the salinity method compared with SOC results. Differences in dissolved solids attributable to the computational approach for handling bicarbonate at UCOL sites were significantly greater than laboratory variability based on results from 890 replicate analyses. Salinity may be a more useful indicator of water quality than SOC in systems with substantial proportions of bicarbonate in the composition of dissolved solids, including the Colorado River and UCOL sites.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pwat.0000310","usgsCitation":"Tillman, F.D., Miller, M., Wise, D., McCleskey, R., and Day, N.K., 2024, Salinity or sum of constituents— Methods comparison for computing dissolved solids concentrations in streams of the Upper Colorado River Basin: PLOS Water, v. 3, no. 12, e0000310, 13 p., https://doi.org/10.1371/journal.pwat.0000310.","productDescription":"e0000310, 13 p.","ipdsId":"IP-151803","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":466711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pwat.0000310","text":"Publisher Index Page"},{"id":465280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.07478126793694,\n 37.362761189486605\n ],\n [\n -110.7918874182937,\n 35.77503910288557\n ],\n [\n -106.92482149871722,\n 35.26377010349002\n ],\n [\n -105.78177189040801,\n 37.551686330409765\n ],\n [\n -106.7657709766068,\n 38.233772867977024\n ],\n [\n -105.31950823092234,\n 38.84018310941224\n ],\n [\n -104.67840732485422,\n 40.36065226066836\n ],\n [\n -106.71988351439666,\n 42.913593391958784\n ],\n [\n -109.98783943768271,\n 43.360892248620246\n ],\n [\n -110.9078832909733,\n 40.740953521572834\n ],\n [\n -112.07478126793694,\n 37.362761189486605\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wise, Daniel 0000-0002-1215-9612","orcid":"https://orcid.org/0000-0002-1215-9612","contributorId":217259,"corporation":false,"usgs":true,"family":"Wise","given":"Daniel","email":"","affiliations":[],"preferred":true,"id":921474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":921475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":921476,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261814,"text":"70261814 - 2024 - Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations","interactions":[],"lastModifiedDate":"2024-12-26T15:14:45.383291","indexId":"70261814","displayToPublicDate":"2024-12-17T08:05:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations","docAbstract":"Climate-induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector-borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecast of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits which may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life-history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait-based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi-scale forecasts of mosquito population dynamics and phenology for diverse stakeholders.","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.70074","usgsCitation":"Mcdevitt-Galles, T., DeGaetano, A., Elmendorf, S., Foster, J., Ginsberg, H., Hooten, M.B., LaDeau, S., McClure, K.M., Paull, S.H., Posthumus, E.E., Rochlin, I., and Grear, D.A., 2024, Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations: Ecosphere, v. 15, no. 12, e70074, 17 p., https://doi.org/10.1002/ecs2.70074.","productDescription":"e70074, 17 p.","ipdsId":"IP-155775","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":466713,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70074","text":"Publisher Index Page"},{"id":465460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.66548403699112,\n 47.19667094970478\n ],\n [\n -88.50420169961106,\n 44.205989638511255\n ],\n [\n -87.90485319328981,\n 41.39073197003515\n ],\n [\n -82.86371026854579,\n 41.70904546715229\n ],\n [\n -82.40184439476982,\n 43.538614110411345\n ],\n [\n -83.49315804844203,\n 46.63943412739803\n ],\n [\n -86.86116175538491,\n 47.49199734956696\n ],\n [\n -88.28863179000962,\n 47.61050307535439\n ],\n [\n -89.66548403699112,\n 47.19667094970478\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Mcdevitt-Galles, Travis 0000-0002-4929-5431","orcid":"https://orcid.org/0000-0002-4929-5431","contributorId":315374,"corporation":false,"usgs":true,"family":"Mcdevitt-Galles","given":"Travis","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":921903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeGaetano, Arthur 0000-0002-0183-1346","orcid":"https://orcid.org/0000-0002-0183-1346","contributorId":347511,"corporation":false,"usgs":false,"family":"DeGaetano","given":"Arthur","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":921904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elmendorf, Sarah 0000-0003-1085-8521","orcid":"https://orcid.org/0000-0003-1085-8521","contributorId":347512,"corporation":false,"usgs":false,"family":"Elmendorf","given":"Sarah","affiliations":[{"id":83184,"text":"University of Colorado: Boulder","active":true,"usgs":false}],"preferred":false,"id":921905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, John R. 0000-0002-7526-3177","orcid":"https://orcid.org/0000-0002-7526-3177","contributorId":347513,"corporation":false,"usgs":false,"family":"Foster","given":"John R.","affiliations":[],"preferred":false,"id":921906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":347514,"corporation":false,"usgs":false,"family":"Ginsberg","given":"Howard S.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":921907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooten, Mevin B. 0000-0002-1614-723X","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":292295,"corporation":false,"usgs":false,"family":"Hooten","given":"Mevin","email":"","middleInitial":"B.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":921908,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LaDeau, Shannon 0000-0003-4825-5435","orcid":"https://orcid.org/0000-0003-4825-5435","contributorId":347515,"corporation":false,"usgs":false,"family":"LaDeau","given":"Shannon","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":921909,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McClure, Katherine Maria 0000-0001-8595-7677","orcid":"https://orcid.org/0000-0001-8595-7677","contributorId":332279,"corporation":false,"usgs":true,"family":"McClure","given":"Katherine","email":"","middleInitial":"Maria","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":921910,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Paull, S. H. 0000-0001-5589-9568","orcid":"https://orcid.org/0000-0001-5589-9568","contributorId":292340,"corporation":false,"usgs":false,"family":"Paull","given":"S.","email":"","middleInitial":"H.","affiliations":[{"id":62877,"text":"Battelle, National Ecological Observatory Network, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":921911,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Posthumus, Erin E. 0000-0003-3855-2380","orcid":"https://orcid.org/0000-0003-3855-2380","contributorId":204418,"corporation":false,"usgs":false,"family":"Posthumus","given":"Erin","email":"","middleInitial":"E.","affiliations":[{"id":40537,"text":"USA National Phenology Network, National Coordinating Office; University of Arizona, School of Natural Resources and the Environment","active":true,"usgs":false}],"preferred":false,"id":921912,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rochlin, Ilia 0000-0001-7680-6965","orcid":"https://orcid.org/0000-0001-7680-6965","contributorId":347516,"corporation":false,"usgs":false,"family":"Rochlin","given":"Ilia","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":921913,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":921914,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70261417,"text":"sim3530 - 2024 - Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts","interactions":[],"lastModifiedDate":"2026-04-02T18:59:12.90477","indexId":"sim3530","displayToPublicDate":"2024-12-16T15:35:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3530","displayTitle":"Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 2 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts","title":"Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts","docAbstract":"The U.S. Geological Survey, in cooperation with the National Marine Sanctuary Program of the National Oceanic and Atmospheric Administration, has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The area being mapped using geophysical and geological data includes the SBNMS and the surrounding region, which totals approximately 3,700 square kilometers (km2) and is subdivided into 18 quadrangles. The seabed is a glaciated terrain that is topographically and texturally diverse. Quadrangle 2, the subject of this scientific investigations map, has a mapped area of 209 km2 and has water depths that range from about 19 meters (m) on the Stellwagen Bank crest to about 68 m in the Stellwagen Basin. Seven map types, each at a scale of 1:25,000, depict seabed topography, ruggedness, backscatter intensity, distribution of geologic substrates, sediment mobility, distribution of fine- and coarse-grained sand, and substrate mud content. These maps show the distribution of geologic substrates across the southwestern part of Stellwagen Bank, in Stellwagen Basin to the west and southwest of the bank, and in Little Stellwagen Basin and the western part of Race Point Channel to the south of the bank. Interpretations of multibeam sonar bathymetric and seabed backscatter imagery, photographs, video imagery, and grain-size analyses were used to create the geology-based maps. Data from 733 stations were analyzed, including 656 sediment samples. The geologic substrate maps of quadrangle 2 show the distribution of 19 geologic substrates that represent a wide range of textures, such as rippled and immobile sand, immobile muddy sand and sandy mud, sand that partially veneers gravel, and a boulder ridge. Mapped substrates are characterized by sediment grain-size composition, surface morphology, substrate layering, the mobility or immobility of substrate surfaces, and water depth range. This scientific investigations map portrays the major geological elements (substrates, topographic features, and processes) of environments in quadrangle 2. It is intended to provide a foundation for research into present and past sediment transport processes in a complex terrain, provide insights into the ecological requirements of invertebrate and vertebrate species that utilize the various substrates, and support seabed management in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3530","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","programNote":"Coastal/Marine Hazards and Resources Program","usgsCitation":"Valentine, P.C., and Cross, V.A., 2024, Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts: U.S. Geological Survey Scientific Investigations Map 3530, 8 sheets, scale 1:25,000, 27-p. pamphlet, https://doi.org/10.3133/sim3530.","productDescription":"Pamphlet: v, 27 p.; 8 Sheets: 26.98 x 35.69 inches or smaller; Data Release","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-153982","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science 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Massachusetts"},{"id":465080,"rank":13,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapF.pdf","text":"Map F","size":"876 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map F","linkHelpText":"- Distribution of Fine- and Coarse-Grained Sand and Boulder Ridges"},{"id":465079,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapE.pdf","text":"Map E","size":"882 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map E","linkHelpText":"- Sediment Mobility"},{"id":465078,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapD2.pdf","text":"Map D, Sheet 2","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map D2","linkHelpText":"- Distribution of Geologic Substrates: Seabed geology and sun-illuminated topography"},{"id":502036,"rank":18,"type":{"id":22,"text":"Related 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PDF"},{"id":464922,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3530/coverthb2.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Stellwagen Bank National Marine Sanctuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.19346273969718,\n 42.097308493871026\n ],\n [\n -70.19346273969718,\n 42.21157101051443\n ],\n [\n -70.35655387736588,\n 42.21157101051443\n ],\n [\n -70.35655387736588,\n 42.097308493871026\n ],\n [\n -70.19346273969718,\n 42.097308493871026\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
Objective: Understanding angler responses to fisheries management actions such as regulation changes have important implications for the effectiveness and efficacy of such management strategies. We examined the ability of remote vehicle counters to provide a relative index of angler effort and present a case study demonstrating use of vehicle counters to assess potential changes in angler effort associated with implementation of more restrictive panfish regulations in a subset of Wisconsin lakes.
Methods: We compared vehicle counts with compulsory creel and game-camera based estimates of angler hours and number of angling parties. During 2016, a series of more restrictive panfish regulations were implemented across 132 Wisconsin lakes. We deployed vehicle counters at a subset of lakes within each regulation type during pre- (2015 and 2016) and post-regulation time periods (2021 and 2022) to assess whether the distribution of angler effort (as indexed using vehicle counters) among regulation types may have shifted in response to regulation implementation.
Result: At lakes with paired vehicle counters and compulsory creel data, vehicle counts explained 57-72% of variation in daily angler effort (h) and 65-85% of variation in daily number of angling parties. Across lakes with paired vehicle counters and game cameras, vehicle counters explained 77% of variation in the number of apparent angling parties; however, effectiveness of vehicle counters for explaining variation in number of apparent angling parties varied among lakes. Vehicle counters explained 63-74% of variation in number of apparent angling parties when considering paired vehicle counter-game camera observations pooled within regulation types. We did not observe any systematic shifts in effort indicative of redistribution of angler effort in response to panfish regulations.
Conclusion: Results suggest that, given appropriate validation measures, vehicle counters could be used as a cost-effective tool to index angler effort, particularly when interest lies in understanding effort dynamics over large spatial scales. Our findings suggest a localized scale for implementation of specialized regulations may be appropriate given angler behaviors and preferences for Wisconsin panfish.
","language":"English","publisher":"American Fisheries society","doi":"10.1002/nafm.11054","usgsCitation":"Dembkowski, D., Latzka, A., Feiner, Z., and Isermann, D.A., 2024, Use of vehicle counters to index and evaluate potential shifts in angler effort following implementation of more restrictive panfish regulations in Wisconsin lakes: North American Journal of Fisheries Management, v. 44, no. 6, p. 1342-1357, https://doi.org/10.1002/nafm.11054.","productDescription":"16 p.","startPage":"1342","endPage":"1357","ipdsId":"IP-163236","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Vilas County","otherGeospatial":"Escanaba Lake, Nebish Lake, Northern Highland Fishery Research Area","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.9879,46.0971],[-88.9329,46.0746],[-88.9332,45.9822],[-89.0478,45.9822],[-89.0477,45.8953],[-89.1091,45.8973],[-89.1752,45.8993],[-89.1754,45.859],[-89.3008,45.8606],[-89.3007,45.9014],[-89.3628,45.8987],[-89.4256,45.8987],[-89.5498,45.8988],[-89.6741,45.8987],[-89.7571,45.8985],[-89.797,45.898],[-89.8199,45.8984],[-89.9212,45.8981],[-89.9846,45.8974],[-90.0428,45.8972],[-90.0442,45.9823],[-90.0134,45.9824],[-89.9853,45.9821],[-89.9289,45.9818],[-89.9282,46.0693],[-89.9288,46.1558],[-89.9287,46.2428],[-89.929,46.3],[-89.7599,46.268],[-89.7368,46.2636],[-89.5829,46.2347],[-89.5331,46.2252],[-89.5133,46.2215],[-89.4272,46.2048],[-89.3759,46.1949],[-89.2666,46.1737],[-89.2302,46.1662],[-89.0854,46.1365],[-88.9879,46.0971]]]},\"properties\":{\"name\":\"Vilas\",\"state\":\"WI\"}}]}","volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Dembkowski, Daniel J.","contributorId":275009,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":923832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Latzka, Alexander W.","contributorId":348855,"corporation":false,"usgs":false,"family":"Latzka","given":"Alexander W.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feiner, Zachary S.","contributorId":348857,"corporation":false,"usgs":false,"family":"Feiner","given":"Zachary S.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":923834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923835,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261871,"text":"70261871 - 2024 - Concordant signal of genetic variation across marker densities in the desert annual Chylismia brevipes is linked with timing of winter precipitation","interactions":[],"lastModifiedDate":"2024-12-31T16:35:23.672067","indexId":"70261871","displayToPublicDate":"2024-12-16T11:35:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Concordant signal of genetic variation across marker densities in the desert annual Chylismia brevipes is linked with timing of winter precipitation","title":"Concordant signal of genetic variation across marker densities in the desert annual Chylismia brevipes is linked with timing of winter precipitation","docAbstract":"Climate change coupled with large-scale surface disturbances necessitate active restoration strategies to promote resilient and genetically diverse native plant communities. However, scarcity of native plant materials hinders restoration efforts, leading practitioners to choose from potentially viable but nonlocal seed sources. Genome scans for genetic variation linked with selective environmental gradients have become a useful tool in such efforts, allowing rapid delineation of seed transfer zones along with predictions of genomic vulnerability to climate change. When properly applied, genome scans can reduce the risk of maladaptation due to mismatches between seed source and planting site. However, results are rarely replicated among complimentary data sources. Here, we compared RAD-seq datasets with 819 and 2699 SNPs (in 625 and 356 individuals, respectively) from the Mojave Desert winter annual Chylismia brevipes. Overall, we found that the datasets consistently characterized both neutral population structure and genetic–environmental associations. Ancestry analyses indicated consistent spatial genetic structuring into four regional populations. We also detected a marked signal of isolation by resistance (IBR), wherein spatial genetic structure was better explained by habitat resistance than by geographic distance. Potentially adaptive loci identified from genome scans were associated with the same environmental gradients—fall precipitation, winter minimum temperature, and precipitation timing—regardless of dataset. Paired with our finding that habitat resistance best explained genetic divergence, our results suggest that isolation of populations within environmentally similar habitats—and subsequent local adaption along gradients parallel to these habitats—drive genome-wide divergence in this species. Moreover, strong genetic associations with winter precipitation timing, along with forecasted shifts in precipitation regime due to midcentury climate change, could impact future population dynamics, habitat distribution, and genetic connectivity for C. brevipes populations within the Mojave Desert.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.70046","usgsCitation":"Shryock, D., Lê, N., DeFalco, L., and Esque, T., 2024, Concordant signal of genetic variation across marker densities in the desert annual Chylismia brevipes is linked with timing of winter precipitation: Conservation Genetics, v. 17, no. 12, e70046, 18 p., https://doi.org/10.1111/eva.70046.","productDescription":"e70046, 18 p.","ipdsId":"IP-159454","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.70046","text":"Publisher Index Page"},{"id":465575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.2859722224079,\n 38.02841230408214\n ],\n [\n -120.2859722224079,\n 33.84962249242069\n ],\n [\n -113.08194078286547,\n 33.84962249242069\n ],\n [\n -113.08194078286547,\n 38.02841230408214\n ],\n [\n -120.2859722224079,\n 38.02841230408214\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Shryock, Daniel F. 0000-0003-0330-9815 dshryock@usgs.gov","orcid":"https://orcid.org/0000-0003-0330-9815","contributorId":208659,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel F.","email":"dshryock@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lê, Nila","contributorId":347238,"corporation":false,"usgs":false,"family":"Lê","given":"Nila","affiliations":[{"id":83101,"text":"California Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":922100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeFalco, Lesley A. 0000-0002-7542-9261","orcid":"https://orcid.org/0000-0002-7542-9261","contributorId":208658,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261618,"text":"70261618 - 2024 - Antibodies to influenza A virus in Lesser (Aythya affinis) and Greater Scaup (Aythya marila) in the USA","interactions":[],"lastModifiedDate":"2024-12-17T15:50:15.832349","indexId":"70261618","displayToPublicDate":"2024-12-16T09:39:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Antibodies to influenza A virus in Lesser (Aythya affinis) and Greater Scaup (Aythya marila) in the USA","title":"Antibodies to influenza A virus in Lesser (Aythya affinis) and Greater Scaup (Aythya marila) in the USA","docAbstract":"Scaup, including both Lesser and Greater (Aythya affinis and Aythya marila, respectively), are a grouping of populous and widespread North American diving ducks. Few influenza type A viruses (IAV) have been reported from these species despite a high prevalence of antibodies to IAV being reported. Existing virologic and serologic data indicate that IAV infection routinely occurs in scaup, yet it is unknown which IAV subtypes are linked to these infections. In this study, we aimed to gain a more complete picture of IAV natural history in Lesser and Greater Scaup from two coastal flyways in North America in 2015–18 (302 samples from California in the Pacific Flyway and 471 samples from Maryland in the Atlantic Flyway). Low prevalence of active IAV infection was detected by real-time reverse-transcription PCR in Lesser Scaup sampled in Maryland and California (2.8% and 8.1%, respectively). A single IAV (H1N1) was isolated in embryonated chicken eggs from a bird sampled in California. Similarly low levels were observed in Greater Scaup in California (3.3%). Antibodies to the nucleoprotein as detected with a commercial blocking ELISA were observed in all species and flyway combinations. Antibody seroprevalence estimates were higher in adult Lesser Scaup than in juveniles at both the ≤0.5 (P<0.001, z=–3.582) and ≤0.7 serum-sample-to-negative-control absorbance thresholds (P=0.003, z=–2.996). Neutralizing antibodies to H1–H12, H14, and H15 were detected using a microtiter virus neutralization assay, with the highest prevalence of antibodies against H1 (38%), H6 (36%), and H11 (35%). The high prevalence of antibodies to IAV and evidence of previous exposure to numerous subtypes are consistent with a high level of population immunity and a low prevalence of infection. These results must be interpreted in the context of season (winter sampling), as results may vary with the annual influx of naïve juvenile birds.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-24-00021","usgsCitation":"Huang, H., Poulson, R., Sullivan, J.D., De La Cruz, S.E., Walbridge, H., Stallknecht, D., and Prosser, D., 2024, Antibodies to influenza A virus in Lesser (Aythya affinis) and Greater Scaup (Aythya marila) in the USA: Journal of Wildlife Diseases, v. 60, no. 4, p. 940-949, https://doi.org/10.7589/JWD-D-24-00021.","productDescription":"10 p.","startPage":"940","endPage":"949","ipdsId":"IP-141598","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":465195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Maryland","county":"Dorchester County","otherGeospatial":"Eden Landing Ecological Reserve, Suisun Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"id\": 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]\n}","volume":"60","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Huang, Harrison","contributorId":344295,"corporation":false,"usgs":false,"family":"Huang","given":"Harrison","email":"","affiliations":[{"id":26951,"text":"The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":921216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":921217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Jeffery D. 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near Independence, Ohio, 2024","interactions":[],"lastModifiedDate":"2024-12-16T14:39:31.386387","indexId":"sir20245122","displayToPublicDate":"2024-12-16T08:30:00","publicationYear":"2024","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":"2024-5122","displayTitle":"Flood-Inundation Maps for the Cuyahoga River in and Near Independence, Ohio, 2024","title":"Flood-inundation maps for the Cuyahoga River in and near Independence, Ohio, 2024","docAbstract":"Digital flood-inundation maps for a 9.9-mile reach of the Cuyahoga River in and near Independence, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the Northeast Ohio Regional Sewer District Board of Trustees. Water-surface profiles were computed for the stream reach by using a one-dimensional steady-state step-backwater model. The model was calibrated to the current (2024) stage-streamflow relation (rating curve 43.0) for the USGS streamgage 04208000, Cuyahoga River at Independence, Ohio. The resulting hydraulic model was then used to compute 13 water-surface profiles for water levels (flood stages) ranging from 14.00 to 26.00 feet. The flood stages range from “action stage” to above “major flood stage” as reported by the National Weather Service. The simulated water-surface profiles were then used in combination with a digital elevation model derived from light detection and ranging data to map the inundated areas associated with each flood profile.
The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood mitigation strategies and to define flood hazard areas to protect life and property, to coordinate flood response activities such as evacuations and road closures, and to aid postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245122","collaboration":"Prepared in cooperation with the Northeast Ohio Regional Sewer District Board of Trustees","usgsCitation":"Ostheimer, C.J., and Whitehead, M.T., 2024, Flood-inundation maps for the Cuyahoga River in and near Independence, Ohio, 2024: U.S. Geological Survey Scientific Investigations Report 2024–5122, 16 p., https://doi.org/10.3133/sir20245122.","productDescription":"Report: vi, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158401","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":464970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5122/coverthb.jpg"},{"id":464971,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5122/sir20245122.pdf","text":"Report","size":"1.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5122 PDF"},{"id":464972,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245122/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5122 HTML"},{"id":464976,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20245115","text":"Scientific Investigations Report 2024–5115","linkHelpText":"Flood-Inundation Maps for the Cuyahoga River at Jaite, Ohio, 2024"},{"id":464973,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5122/sir20245122.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5122 XML"},{"id":464974,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5122/images/"},{"id":464975,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZFZK0L","text":"USGS data release","linkHelpText":"Geospatial data sets and hydraulic model for the Cuyahoga River in and near the city of Independence, Ohio"}],"country":"United States","state":"Ohio","city":"Independence","otherGeospatial":"Cuyahoga River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.7238278506537,\n 41.48\n ],\n [\n -81.7238278506537,\n 41.373775959357204\n ],\n [\n -81.61067566475016,\n 41.373775959357204\n ],\n [\n -81.61067566475016,\n 41.48\n ],\n [\n -81.7238278506537,\n 41.48\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
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6460 Busch Blvd, Suite 100
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Background: Although the rate of emerging infectious diseases that originate in wildlife has been increasing globally in recent decades, there is currently a lack of epidemiological data from wild animals.
Methodology: We used serology to determine prior exposure to foot-and-mouth disease virus (FMDV), Brucella spp., and Coxiella burnetii and used genetic testing to detect blood-borne parasitic infections in the genera Ehrlichia, Anaplasma, Theileria, and Babesia from wildlife in two national parks, Kruger National Park (KNP), South Africa, and Etosha National Park (ENP), Namibia. Serum and whole blood samples were obtained from free-roaming plains zebra (Equus quagga), greater kudu (Tragelaphus strepsiceros), impala (Aepyceros melampus), and blue wildebeest (Connochaetes taurinus). Risk factors (host species, sex, and sampling park) for infection with each pathogen were assessed, as well as the prevalence and distribution of co-occurring infections.
Results: In KNP 13/29 (45%; confidence interval [CI]: 26%–64%) kudus tested positive for FMD, but none of these reacted to SAT serotypes. For brucellosis, seropositive results were obtained for 3/29 (10%; CI: 2%–27%) kudu samples. Antibodies against C. burnetii were detected in 6/29 (21%; CI: 8%–40%) kudus, 14/21 (67%; CI: 43%–85%) impalas, and 18/39 (46%; CI: 30%–63%) zebras. A total of 28/28 kudus tested positive for Theileria spp. (100%; CI: 88%–100%) and 27/28 for Anaplasma/Ehrlichia spp. (96%; CI: 82%–100%), whereas 12/19 impalas (63%) and 2/39 zebra (5%) tested positive for Anaplasma centrale. In ENP, only 1/29 (3%; CI: 0%–18%) wildebeest samples tested positive for FMD. None of the samples tested positive for brucellosis, while C. burnetii antibodies were detected in 26/30 wildebeests (87%; CI: 69%–96%), 16/40 kudus (40%; CI: 25%–57%), and 26/26 plains zebras (100%; CI: 87%–100%). A total of 60% Anaplasma/Ehrlichia spp. and 35% Theileria/Babesia spp. in kudu and 37% wildebeest tested positive to Theileria sp. (sable), 30% to Babesia occultans, and 3%–7% to Anaplasma spp. The seroprevalence of Q fever was significantly higher in ENP, while Brucella spp., Anaplasma, Ehrlichia, Theileria, and Babesia species were significantly higher in KNP. Significant coinfections were also identified.
Conclusion: This work provided baseline serological and molecular data on 40+ pathogens in four wildlife species from two national parks in southern Africa.
","language":"English","publisher":"Wiley","doi":"10.1155/tbed/2417717","usgsCitation":"Cossu, C., Ochai, S., Troskie, M., Hartmann, A., Godfroid, J., de Klerk, L., Turner, W.C., Kamath, P., van Schalkwyk, O., Cassini, R., Bhoora, R., and van Heerden, H., 2024, Detection of tick-borne pathogen coinfections and coexposures to foot-and-mouth disease, brucellosis, and Q fever in selected wildlife from Kruger National Park, South Africa, and Etosha National Park, Namibia: Transboundary and Emerging Diseases, v. 2024, no. 1, 417717, 17 p., https://doi.org/10.1155/tbed/2417717.","productDescription":"417717, 17 p.","ipdsId":"IP-164915","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481044,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/tbed/2417717","text":"Publisher Index 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Such data may also be used as a proxy for breeding activity, but links between presence-absence data and higher-order processes must be validated to determine their reliability. The Marbled Murrelet (Brachyramphus marmoratus) is a threatened seabird that nests in older-aged forests along the Pacific Coast. Its nests are exceptionally difficult to find, so we tested whether presence-absence surveys can help identify nesting sites. Between 2018 and 2022 we located 17 trees containing active murrelet nests in the Oregon Coast Range (USA) and 38 trees that purportedly contained no active nests (26 in occupied murrelet stands and 12 in unoccupied stands). Observers surveyed within 200 m of focal trees using standard presence-absence surveys, and we modeled the effects of site status (active nest or control) and distance from the focal tree on probability of recording murrelets. We never detected murrelets in unoccupied control sites. We found some evidence that the probability of recording presence was higher at active nesting sites (0.81, 95% CI: 0.71, 0.88) than at occupied control sites (0.71, 95% CI: 0.64, 0.78) although a null model had similar support. The probability of recording murrelet breeding behaviors in nesting and occupied control sites was 0.20 (95% CI: 0.14, 0.27) regardless of distance to a known active nest. These results suggest that presence-absence surveys may be useful for identifying plausible murrelet nesting habitat, but they are ineffective for identifying active nesting sites. Moreover, we estimated that 20 repeated surveys at a point in space are required to reasonably conclude there are no active nesting sites within 200 m. These findings serve as an important reminder of the limitations that can come with relying on presence-absence data alone to identify breeding sites.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0315531","usgsCitation":"Spurgeon, J.J., Adrean, L., Nelson, S., Betts, M., Roby, D., and Rivers, J., 2024, Presence-absence surveys yield spatially imprecise information about nesting sites of an endangered, forest-nesting seabird: PLoS ONE, v. 19, no. 12, e0315531, 13 p., https://doi.org/10.1371/journal.pone.0315531.","productDescription":"e0315531, 13 p.","ipdsId":"IP-167025","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":488480,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0315531","text":"Publisher Index Page"},{"id":484839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.5,\n 45.6\n ],\n [\n -124.1,\n 45.6\n ],\n [\n -124.1,\n 43.9\n ],\n [\n -123.5,\n 43.9\n ],\n [\n -123.5,\n 45.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Spurgeon, Jonathan J. 0000-0002-6888-5867","orcid":"https://orcid.org/0000-0002-6888-5867","contributorId":304259,"corporation":false,"usgs":true,"family":"Spurgeon","given":"Jonathan","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adrean, Lindsay J.","contributorId":353648,"corporation":false,"usgs":false,"family":"Adrean","given":"Lindsay J.","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":934231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, S. Kim","contributorId":353649,"corporation":false,"usgs":false,"family":"Nelson","given":"S. Kim","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":934232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Betts, Matthew G.","contributorId":353650,"corporation":false,"usgs":false,"family":"Betts","given":"Matthew G.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":934233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roby, Daniel D.","contributorId":353651,"corporation":false,"usgs":false,"family":"Roby","given":"Daniel D.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":934234,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rivers, James W.","contributorId":353652,"corporation":false,"usgs":false,"family":"Rivers","given":"James W.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":934235,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261672,"text":"70261672 - 2024 - Ungulate personality and the human shield contribute to long-distance migration loss","interactions":[{"subject":{"id":70261672,"text":"70261672 - 2024 - Ungulate personality and the human shield contribute to long-distance migration loss","indexId":"70261672","publicationYear":"2024","noYear":false,"title":"Ungulate personality and the human shield contribute to long-distance migration loss"},"predicate":"SUPERSEDED_BY","object":{"id":70269975,"text":"70269975 - 2025 - Elk personality and anthropogenic food subsidy: Managing conflict and migration loss","indexId":"70269975","publicationYear":"2025","noYear":false,"title":"Elk personality and anthropogenic food subsidy: Managing conflict and migration loss"},"id":1}],"supersededBy":{"id":70269975,"text":"70269975 - 2025 - Elk personality and anthropogenic food subsidy: Managing conflict and migration loss","indexId":"70269975","publicationYear":"2025","noYear":false,"title":"Elk personality and anthropogenic food subsidy: Managing conflict and migration loss"},"lastModifiedDate":"2025-08-19T15:36:16.359859","indexId":"70261672","displayToPublicDate":"2024-12-12T09:25:07","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"Ungulate personality and the human shield contribute to long-distance migration loss","docAbstract":"Long-distance ungulate migrations are declining and past research has focused on preserving migration paths where habitat fragmentation and loss disrupts movement corridors. However, changing residency-migration tradeoffs are the stronger driver of long-distance migration loss in some populations. The human shield effect relative to predation risk and anthropogenic food resources likely shapes these tradeoffs, but individual animals also vary in their propensity to tolerate proximity to humans and developed areas. We investigated how personality relative to human-habituation affects migration behavior. We categorized elk as bold or shy based on use of anthropogenic food resources identified through a clustering algorithm applied to GPS collar data. Bold elk were 4 times more likely to select wintering areas close to human activity and migrated 60% shorter distances compared to shy elk. As a result, elk wintering grounds were spatially structured such that conflict- and disease-prone individuals selected areas adjacent to human activity. Our results suggest that bold personality traits act as a precursor to human-habituation, which permits bold elk to reap the forage and predation rewards that occur in suburban landscapes. A multi-pronged approach beyond just maintaining habitat corridors may be necessary to conserve long-distance migrations for species that can become human-habituated.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2024.12.10.627781","usgsCitation":"Cotterill, G.G., Cross, P., Cole, E.K., Dewey, S., Wise, B.L., and Graves, T., 2024, Ungulate personality and the human shield contribute to long-distance migration loss: BioRxiv, https://doi.org/10.1101/2024.12.10.627781.","productDescription":"29 p.","ipdsId":"IP-173154","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":465269,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466718,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2024.12.10.627781","text":"External Repository"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cotterill, Gavin G. 0000-0002-1408-778X","orcid":"https://orcid.org/0000-0002-1408-778X","contributorId":346534,"corporation":false,"usgs":true,"family":"Cotterill","given":"Gavin","middleInitial":"G.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":921381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":921382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cole, Eric K 0000-0002-2229-5853","orcid":"https://orcid.org/0000-0002-2229-5853","contributorId":248406,"corporation":false,"usgs":false,"family":"Cole","given":"Eric","email":"","middleInitial":"K","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":921383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dewey, Sarah R.","contributorId":342391,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":921384,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wise, Benjamin L.","contributorId":347330,"corporation":false,"usgs":false,"family":"Wise","given":"Benjamin","email":"","middleInitial":"L.","affiliations":[{"id":83136,"text":"Wyoming Game & Fish Department","active":true,"usgs":false}],"preferred":false,"id":921385,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":921386,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265038,"text":"70265038 - 2024 - A multidisciplinary approach that considers occurrence, geochemistry, bioavailability, and toxicity to prioritize critical minerals for environmental research","interactions":[],"lastModifiedDate":"2025-03-31T14:20:59.282076","indexId":"70265038","displayToPublicDate":"2024-12-12T09:17:46","publicationYear":"2024","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":"A multidisciplinary approach that considers occurrence, geochemistry, bioavailability, and toxicity to prioritize critical minerals for environmental research","docAbstract":"Critical minerals (or critical elements) are minerals or elements that are essential to global security and development and have supply chains vulnerable to disruption. In general, knowledge of the environmental behavior and health effects of critical elements is needed to support the development of safe and environmentally responsible supplies. This knowledge includes identifying potential consequences of increased critical element production and use, alternative critical element sources such as mine wastes, and adverse effects of critical elements on ecosystem condition and organismal health. Here we identify significant data gaps in the understanding of critical elements in surficial and aquatic environments, and the need, given the large number of commodities (50) identified on the 2022 critical minerals list for the United States, for an approach to prioritize them for study of their environmental fate and effects. We propose a multidisciplinary approach for this prioritization, considering measures of occurrence, geochemistry, bioavailability, and toxicity. We describe relatively easy-to-obtain metrics for each of these topic areas and demonstrate the utility of this integrated prioritization approach using indium and zinc as examples. This approach facilitates prioritizing research with a focus on those critical elements that are most mobile in the environment, bioavailable, toxic, or simply lacking data in these categories.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.4c11211","usgsCitation":"White, S.J., Kane, T., Campbell, K.M., Croteau, M.N., Iacchetta, M.G., Blake, J., Cravotta, C., Kunz, B.K., Alpers, C.N., Jenkins, J., and Walton-Day, K., 2024, A multidisciplinary approach that considers occurrence, geochemistry, bioavailability, and toxicity to prioritize critical minerals for environmental research: Environmental Science & Technology, v. 58, no. 51, p. 22519-22527, https://doi.org/10.1021/acs.est.4c11211.","productDescription":"9 p.","startPage":"22519","endPage":"22527","ipdsId":"IP-159036","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":488921,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.4c11211","text":"Publisher Index Page"},{"id":484016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"51","noUsgsAuthors":false,"publicationDate":"2024-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Sarah Jane 0000-0002-4055-8207","orcid":"https://orcid.org/0000-0002-4055-8207","contributorId":216796,"corporation":false,"usgs":true,"family":"White","given":"Sarah","email":"","middleInitial":"Jane","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":932371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kane, Tyler 0000-0003-2511-7312 tkane@usgs.gov","orcid":"https://orcid.org/0000-0003-2511-7312","contributorId":195588,"corporation":false,"usgs":true,"family":"Kane","given":"Tyler","email":"tkane@usgs.gov","affiliations":[],"preferred":true,"id":932372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":932373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":932374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iacchetta, Michael G. 0000-0001-9459-1435","orcid":"https://orcid.org/0000-0001-9459-1435","contributorId":291394,"corporation":false,"usgs":true,"family":"Iacchetta","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":932375,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blake, Johanna 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":217272,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932376,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":338312,"corporation":false,"usgs":false,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":81112,"text":"Cravotta Geochemical Consulting","active":true,"usgs":false}],"preferred":false,"id":932377,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kunz, Bethany K. 0000-0002-7193-9336 bkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-7193-9336","contributorId":3798,"corporation":false,"usgs":true,"family":"Kunz","given":"Bethany","email":"bkunz@usgs.gov","middleInitial":"K.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":932378,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932379,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jenkins, Jill 0000-0002-5087-0894","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":222865,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932380,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Walton-Day, Katherine 0000-0002-9146-6193","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":336569,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932381,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70261450,"text":"sir20245100 - 2024 - Evidence of nitrate attenuation in intertidal and subtidal groundwater in a subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts, 2015–16","interactions":[],"lastModifiedDate":"2025-09-02T14:41:05.735212","indexId":"sir20245100","displayToPublicDate":"2024-12-11T15:00:00","publicationYear":"2024","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":"2024-5100","displayTitle":"Evidence of Nitrate Attenuation in Intertidal and Subtidal Groundwater in a Subterranean Estuary at a Cape Cod Embayment, East Falmouth, Massachusetts, 2015–16","title":"Evidence of nitrate attenuation in intertidal and subtidal groundwater in a subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts, 2015–16","docAbstract":"Nitrogen dynamics in intertidal and nearshore subtidal groundwater (subterranean estuary) adjacent to the Seacoast Shores peninsula, Falmouth, Massachusetts, were investigated during 2015–16 by the U.S. Geological Survey. The peninsula is a densely populated residential area with septic systems and cesspools that are substantial sources of nitrogen to groundwater. The study area is in the Eel River, an estuarine saltwater embayment connected to the ocean adjacent to the western shore of the peninsula, that was the subject of an earlier study by Colman and others (2018, https://doi.org/10.3133/sir20185095) on nitrogen transport and transformations in groundwater between onshore and offshore locations. The previous study documented the distribution of nitrate concentrations and nitrate attenuation reactions in fresh groundwater beneath the peninsula and the estuary. The current study extended those observations with more detailed sampling and analysis of shallow groundwater from wells near discharge sites beneath the estuary. The current field investigation included sampling of existing wells and installation and sampling of clusters of wells and temporary sampling points in the subterranean estuary, including (1) shallow transects 0.3 to 1.2 meters (m) deep extending from 1 to 13.5 m offshore and (2) deeper wells (from 1.83 to 4.88 m deep) extending from 4.3 to 14.3 m offshore.
Measurements of hydraulic-head gradients 2–5 m below the sediment/water interface in the intertidal and nearshore subtidal zones indicated that groundwater flow generally was upwards (towards the estuary) under all tide conditions in October 2016. The magnitude of the gradient was greatest during low tide conditions, indicating that groundwater discharge likely decreased during high tides.
Measurements of specific conductance in shallow groundwater in the subterranean estuary in three transects perpendicular to shore were consistent with the existence of saltwater flow cells (infiltration of overlying saline water, mixing with fresh groundwater, and discharge to the overlying saline water) in the intertidal and nearshore subtidal regions. The size of these flow cells was variable in space and time and dependent on the elevation of the tide (spring or neap). At this location in the Eel River subterranean estuary, and offshore to at least 13.5 m, offshore flow of fresh groundwater apparently prevented a deeper saltwater wedge from discharging to the surface.
Nitrate concentrations in shallow groundwater (30 to 122 centimeters [cm] depth) were variable in space and time, ranging from not detectable to 600 micromoles per liter (μmol/L) (8.4 milligrams per liter as N), and were highest in June 2016 at depths from 61 to 122 cm below the sediment/water interface and from 4 to 9 m offshore. Nitrate generally was not detectable in saline shallow groundwater at 30-cm depth or at any depth from 30 to 122 cm from 10 to 13.5 m offshore. Dissolved oxygen concentrations were suboxic (less than 16 μmol/L) in 60 percent of the sampled subterranean groundwater beneath the intertidal and subtidal zones. In the remaining sites, the range of dissolved oxygen concentrations was from 18 to 272 μmol/L and the median concentration was 43 μmol/L.
Evidence for microbial nitrate reduction (denitrification and possibly anammox) was provided by the distribution of the reaction product nitrogen gas (excess N2, or N2MIC), as determined from analysis of the dissolved nitrogen gas and argon gas (Ar) concentrations in groundwater samples. Excess nitrogen gas provided evidence for nitrate reduction in shallow groundwater below the subtidal and, to a lesser extent, intertidal zones adjacent to the Seacoast Shores peninsula. These zones, where evidence for nitrate reduction was detected, were in fresh and brackish groundwater near subtidal or intertidal saltwater cells where discharging fresh groundwater mixed with infiltrating saline water. Infiltrating seawater may have supplied organic carbon, one of several potential electron donors that are required for denitrification. Other potential electron donors, such as organic carbon, iron, manganese, hydrogen, methane, ammonium, elemental sulfur, or sulfide phases, may have been supplied by the estuarine sediments. Drainage from surface runoff near the shore also may have supplied organic carbon to fresh groundwater near the intertidal saltwater cell.
The highest amounts of nitrate converted to excess nitrogen gas were estimated to be in the range of 230 to 430 μmol/L in nearly fresh groundwater near the subtidal saltwater cell at depths of 61 to 122 cm below the sediment/water interface and from 10 to 13.5 m offshore. Evidence of denitrification within 10 m of the shore was sparse (generally limited to less than 50 μmol/L of N2-N) despite the presence of high nitrate concentrations. The spatial distribution of estimated nitrate reduction in the intertidal and nearshore subtidal fresh and brackish groundwater may be related to local variability in the distribution of reactive electron donors in those zones. Variations in the amount of nitrate reduction to nitrogen gas were not clearly related to potential aqueous electron donors such as dissolved organic carbon, nor to potential reaction products such as alkalinity, but may have been controlled by combinations of aqueous and solid-phase reactants. The distribution of relatively shallow fresh groundwater containing nitrate could indicate potential nitrate discharge areas in the lower intertidal zone and uncertain locations farther offshore; however, the data did not extend all the way to the sediment/water interface or to the offshore freshwater limit. This study confirmed substantial loss of nitrate from some of the fresh and brackish groundwater in shallow subestuarine sediments prior to discharge but did not quantify how much nitrate eventually discharged to the estuary.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245100","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Office of Research and Development and Region 1 (New England)","programNote":"Environmental Health Program, Coastal/Marine Hazards and Resources Program","usgsCitation":"Huntington, T.G., Kroeger, K.D., McCobb, T.D., Böhlke, J.K., Colman, J.A., Brooks, T.W., and Szymczycha, B., 2024, Evidence of nitrate attenuation in intertidal and subtidal groundwater in a subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts, 2015–16: U.S. Geological Survey Scientific Investigations Report 2024–5100, 45 p., https://doi.org/10.3133/sir20245100.","productDescription":"Report: ix, 45 p.; Data Release","numberOfPages":"45","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-128353","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":495118,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118080.htm","linkFileType":{"id":5,"text":"html"}},{"id":464963,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20185095","text":"Scientific Investigations Report 2018–5095","linkHelpText":"Geochemical conditions and nitrogen transport in nearshore groundwater and the subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts, 2013–14"},{"id":464958,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5100/sir20245100.pdf","text":"Report","size":"8.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5100 PDF"},{"id":464961,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5100/images/"},{"id":464962,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13LGNTT","text":"USGS data release","linkHelpText":"Geochemical data supporting analysis of fate and transport of nitrogen in the nearshore groundwater and subterranean estuary near East Falmouth, Massachusetts, 2015–2016"},{"id":464960,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5100/sir20245100.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5100 XML"},{"id":464959,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245100/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5100 HTML"},{"id":464957,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5100/coverthb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod Embayment, East Falmouth","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.5439543201461,\n 41.57096045380911\n ],\n [\n -70.5439543201461,\n 41.5648296072948\n ],\n [\n -70.53931798288792,\n 41.5648296072948\n ],\n [\n -70.53931798288792,\n 41.57096045380911\n ],\n [\n -70.5439543201461,\n 41.57096045380911\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
As New Jersey’s population density remains high, so does its requirements for water management. Understanding the streamflow conditions throughout the state and how they may have changed over time is an important part of managing the water resources within the state. The New Jersey Department of Environmental Protection has many responsibilities related to protecting the environment and natural resources and among them is protecting the waters in the lakes, rivers, and streams of New Jersey for current and future use. To support this mission, the U.S. Geological Survey updated high- and low-streamflow statistics for 97 continuous-record streamgages and low-streamflow statistics for 719 partial-record streamgages throughout the state. The continuous-record streamgages included in the study had a minimum of 20 years of record, spanning from 1903 to 2017.
This study is an update to previous studies that documented the high- and low-streamflow statistics for New Jersey streams in the 1970s and in 2005. The 1982 report by Gillespie and Schopp documented low-flow characteristics and flow duration for about 400 continuous and partial-record streamgages. The U.S. Geological Survey computed streamflow statistics including, but not limited to, maximum, minimum, and means for period of record, flow durations, nonexceedance high- and low-flow frequencies, base flow, runoff, peak-to-mean flow ratios, and September median streamflow.
Overall, both high and low flows are generally increasing in New Jersey, though the results are not uniform across the State. Streamflow trends and changes to duration and frequency statistics can be influenced by local water use, in addition to climate variables. The resulting computations at some streamgages indicated considerable positive change while others showed considerable negative change. Water managers and regulators can use the data provided here and in the companion data release to assess individual stream reaches and watershed management areas to evaluate the available resources and changes, which may have developed during the periods for which streamflow statistics are available.
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Jersey\",\"nation\":\"USA \"}}]}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Freshwater harmful algal blooms (HABs) formed by blue-green algae, or cyanobacteria, have emerged as a global environmental problem. Their negative impacts on aquatic ecosystems can affect the benefits nature provides to human society by reducing water quality; inhibiting aquatic recreation; killing fish, wildlife, and pets; and posing a risk to human health. To manage harmful algal blooms, the Engineer Research and Development Center of the U.S. Army Corps of Engineers is developing an advanced technology called the Harmful Algal Bloom Interception, Treatment, and Transformation System (HABITATS), which has been tested in pilot demonstrations upstream of spillways at HAB-affected waterbodies in Florida.
The U.S. Geological Survey and cooperators from the U.S. Department of the Interior Office of Policy Analysis investigated the societal benefits of HABITATS technology by using data from an actual 2018 harmful algal bloom in Lake Okeechobee to characterize the observed societal impacts and then comparing observed effects to hypothetical scenarios of HABITATS deployment. This study estimated an economic value of $5.5 million in foregone recreation as a result of closed boating ramp facilities and other restrictions on aquatic recreation such as fishing and swimming during the 2018 cyanobacteria harmful algal bloom outbreak. The change in housing sales prices that could have resulted from murky water or bad odor during that outbreak was estimated as $2.3 million. The team also investigated drinking water contamination and human illness but did not find significant societal impacts in this case. If HABITATS had been deployed, the avoided losses less the cost of management could have provided net societal benefits that ranged between negative $2.1 million and positive $0.8 million, depending on the vertical distribution of algae in the water column and the HABITATS version used. The study’s estimated societal benefit is undoubtedly a lower bound estimate because current scientific knowledge is inadequate to characterize, or monetize, all the impacts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245091","collaboration":"Prepared in cooperation with the U.S. Department of the Interior Office of Policy Analysis","usgsCitation":"Boubacar, I., Pindilli, E., Brown, E., Simon, B., Skrabis, K., and Luby, I., 2024, Societal benefits of cyanobacteria harmful algal bloom management in Lake Okeechobee in Florida—Potential damages avoided during the 2018 event under U.S. Army Corps of Engineers Harmful Algal Bloom Interception, Treatment, and Transformation System scenarios: U.S. Geological Survey Scientific Investigations Report 2024–5091, 45 p., https://doi.org/10.3133/sir20245091.","productDescription":"viii, 45 p.","numberOfPages":"45","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-150304","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":463780,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5091/coverthb.jpg"},{"id":463781,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5091/sir20245091.pdf","text":"Report","size":"3.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5091 PDF"},{"id":465046,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245091/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5091 HTML"},{"id":465047,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5091/sir20245091.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5091 XML"},{"id":465048,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5091/images/"}],"country":"United States","state":"Florida","otherGeospatial":"Lake Okeechobee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.71054671420583,\n 26.687775426716726\n ],\n [\n -80.58954039907944,\n 26.917874571459976\n ],\n [\n -80.63426012423493,\n 27.05617802730012\n ],\n [\n -80.68424099352616,\n 27.141653409197076\n ],\n [\n -80.7920944483125,\n 27.21419764747064\n ],\n [\n -80.88416447069157,\n 27.15803848776676\n ],\n [\n -81.13538410318226,\n 26.9729819104991\n ],\n [\n -81.08671851992459,\n 26.83105527322678\n ],\n [\n -80.98412620927402,\n 26.7958392807315\n ],\n [\n -80.8960020449971,\n 26.737121664610214\n ],\n [\n -80.81050845278828,\n 26.686600255683558\n ],\n [\n -80.74737472315748,\n 26.68189945039616\n ],\n [\n -80.71054671420583,\n 26.687775426716726\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Mail Stop 913
Reston, VA 20192
Unoccupied aerial systems (UASs) are increasingly being deployed in coastal environments to rapidly map and monitor changes to geomorphology, vegetation, and infrastructure, particularly in difficult to access areas. UAS data, relative to airplane or satellite data, typically have higher spatial resolution, sensor customization, and increased flexibility in temporal resolution, which benefits monitoring applications. UAS data have been used to map and monitor invasive species occurrence and expansion, such as Phragmites australis, a reed species in wetlands throughout the eastern United States. To date, the work on this species has been largely opportunistic or ad hoc. Here, we statistically and qualitatively compare results from several sensors and classification workflows to develop baseline understanding of the accuracy of different approaches used to map Phragmites. Two types of UAS imagery were collected in a Phragmites-invaded salt marsh setting—natural color red-green-blue (RGB) imagery and multispectral imagery spanning visible and near infrared wavelengths. We evaluated whether one imagery type provided significantly better classification results for mapping land cover than the other, also considering trade-offs like overall accuracy, financial costs, and effort. We tested the transferability of classification workflows that provided the highest thematic accuracy to another barrier island environment with known Phragmites stands. We showed that both UAS sensor types were effective in classifying Phragmites cover, with neither resulting in significantly better classification results than the other for Phragmites detection (overall accuracy up to 0.95, Phragmites recall up to 0.86 at the pilot study site). We also found the highest accuracy workflows were transferrable to sites in a barrier island setting, although the quality of results varied across these sites (overall accuracy up to 0.97, Phragmites recall up to 0.90 at the additional study sites).
","language":"English","publisher":"MDPI","doi":"10.3390/rs16244691","usgsCitation":"Evans, A.D., Cramer, J.M., Scholl, V.M., and Lentz, E.E., 2024, Pragmatically mapping Phragmites with unoccupied aerial systems: A comparison of invasive species land cover classification using RGB and multispectral imagery: Remote Sensing, v. 16, no. 24, 4691, 29 p., https://doi.org/10.3390/rs16244691.","productDescription":"4691, 29 p.","ipdsId":"IP-169125","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16244691","text":"Publisher Index Page"},{"id":465289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Dog Head Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.5,\n 41.5556\n ],\n [\n -70.5,\n 41.551111\n ],\n [\n -70.505556,\n 41.551111\n ],\n [\n -70.505556,\n 41.5556\n ],\n [\n -70.5,\n 41.5556\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"24","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Alexandra Danielle 0000-0001-8224-2318","orcid":"https://orcid.org/0000-0001-8224-2318","contributorId":303770,"corporation":false,"usgs":true,"family":"Evans","given":"Alexandra","email":"","middleInitial":"Danielle","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cramer, Jennifer Marie 0000-0002-5899-8809","orcid":"https://orcid.org/0000-0002-5899-8809","contributorId":303769,"corporation":false,"usgs":true,"family":"Cramer","given":"Jennifer","email":"","middleInitial":"Marie","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scholl, Victoria Mary 0000-0002-2085-1449","orcid":"https://orcid.org/0000-0002-2085-1449","contributorId":295713,"corporation":false,"usgs":true,"family":"Scholl","given":"Victoria","email":"","middleInitial":"Mary","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":921389,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921390,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261250,"text":"dr1203 - 2024 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2021","interactions":[],"lastModifiedDate":"2025-12-22T20:37:57.872296","indexId":"dr1203","displayToPublicDate":"2024-12-09T10:05:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1203","displayTitle":"Streamflow, Water Quality, and Constituent Loads and Yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2021","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2021","docAbstract":"As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey in cooperation with Providence Water (formerly Providence Water Supply Board) collected streamflow and water-quality data in tributaries to the Scituate Reservoir, Rhode Island. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance for 16 tributaries were used to calculate loads of chloride and sodium during water year 2021 (October 1, 2020, through September 30, 2021). Water-quality samples were collected by Providence Water at 36 sampling stations on tributaries to the Scituate Reservoir during water year 2021. These water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields of selected water-quality constituents for water year 2021.
Annual mean streamflows for monitoring stations in this study ranged from 0.37 to 32.4 cubic feet per second during water year 2021. At the 16 continuous-record streamgages, tributaries transported about 2,900 metric tons (t) of chloride and 1,800 t of sodium to the Scituate Reservoir; annual chloride yields for the tributaries ranged from 15 to 110 metric tons per square mile (t/mi2), and annual sodium yields ranged from 10 to 68 t/mi2. At the stations where water-quality samples were collected by Providence Water, the medians of the median daily loads were 180 kilograms per day for chloride, 12 grams per day as nitrogen for nitrite, less than 700 grams per day as nitrogen for nitrate, 410 grams per day as orthophosphate for phosphate, 71,000 million colony forming units per day for coliform bacteria, and less than 2,000 million colony forming units per day for Escherichia coli. The medians of the median yields were 67 kilograms per day per square mile for chloride, 4.2 grams per day per square mile as nitrogen for nitrite, 400 grams per day per square mile as nitrogen for nitrate, 180 grams per day per square mile as orthophosphate as phosphate, 46,000 million colony forming units per day per square mile for coliform bacteria, and 1,000 million colony forming units per day per square mile for Escherichia coli.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1203","collaboration":"Prepared in cooperation with Providence Water","usgsCitation":"Smith, K.P., and Spaetzel, A.B., 2024, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2021: U.S. Geological Survey Data Report 1203, 34 p., https://doi.org/10.3133/dr1203.","productDescription":"Report: vi, 34 p.; Data Release","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-157776","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":497894,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118078.htm","linkFileType":{"id":5,"text":"html"}},{"id":464722,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WK8N0F","text":"USGS data release","linkHelpText":"Water-quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir (ver. 3.0, 2023)"},{"id":464720,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1203/dr1203.XML","linkFileType":{"id":8,"text":"xml"},"description":"DR 1203 XML"},{"id":464719,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1203/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1203 HTML"},{"id":464717,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1203/coverthb.jpg"},{"id":464718,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1203/dr1203.pdf","text":"Report","size":"3.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1203 PDF"},{"id":464721,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1203/images/"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.6124559054163,\n 41.732581620415004\n ],\n [\n -71.57280936185028,\n 41.74634136521371\n ],\n [\n -71.53961690677208,\n 41.77247675758633\n ],\n [\n -71.53777288148986,\n 41.842577016973706\n ],\n [\n -71.6032357790058,\n 41.91671720431131\n ],\n [\n -71.6557904995461,\n 41.894072384442495\n ],\n [\n -71.65210244898232,\n 41.858373339441414\n ],\n [\n -71.70834522008708,\n 41.87416576105147\n ],\n [\n -71.7516798142176,\n 41.85013226656352\n ],\n [\n -71.74245968780639,\n 41.79653941237348\n ],\n [\n -71.68621691670165,\n 41.749780840744904\n ],\n [\n -71.6124559054163,\n 41.732581620415004\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
The U.S. Geological Survey, in cooperation with Providence Water (formerly Providence Water Supply Board), conducted a long-term program to monitor water quality in the Scituate Reservoir drainage area in Rhode Island to collect streamflow and water-quality data from 16 tributaries to the reservoir during the water year 2021. These data were used to estimate loads of chloride and sodium. Additionally, water-quality samples were collected at 36 sampling stations on the tributaries, and the data were summarized using central tendency values.
Objective:
T-bar anchor tags can be used to obtain recapture data from anglers, directly estimate exploitation, and evaluate population dynamics. Unfortunately, their use by biologists to study anadromous salmonid fisheries is limited. Two hurdles to adoption include the functional difficulty of tagging large anadromous salmonids using conventional tagging equipment and a lack of information on tag loss by large anadromous salmonids and how it changes over time. As such, our objectives were to (1) describe a T-bar anchor tagging system modified to study adult steelhead Oncorhynchus mykiss (i.e., anadromous Rainbow Trout) and (2) present an instantaneous tag loss model for steelhead that allows estimation of tag loss over time.
Methods: First, we developed a modified tagging system by tagging hatchery-obtained steelhead carcasses and live, resident Rainbow Trout >500 mm using a variety of hardware and tag dimensions. Next, we double-tagged adult steelhead captured at the Lower Granite Dam adult fish trap, Washington, USA. We then used data from 182 recaptured steelhead to fit an instantaneous tag loss model. Last, we investigated whether steelhead tag loss was related to body length.
Result: Tag loss was generally low within the time period under study (i.e., up to 221 days between release and recapture). The estimated probability of tag loss was 0.034 at release, 0.044 at one month, and 0.113 at eight months. We failed to detect significant differences in tag loss parameters between two subsets of small (<720 mm) and large (≥720 mm) steelhead.
Conclusion: T-bar anchor tags are useful external tags for studying adult steelhead during their upstream migration. Because anglers can be used to provide recapture data, T-bar anchor tags may be particularly useful where angler effort is high or direct estimation of fishery exploitation is desired.
","language":"English","publisher":"Oxford Academic","doi":"10.1002/nafm.11055","usgsCitation":"Voss, N.S., McCormick, J., Lubenau, W., Bowersox, B.J., Copeland, T., and Quist, M.C., 2024, Retention of T‐bar anchor tags by adult steelhead during their upstream migration: North American Journal of Fisheries Management, v. 44, no. 6, p. 1385-1391, https://doi.org/10.1002/nafm.11055.","productDescription":"7 p.","startPage":"1385","endPage":"1391","ipdsId":"IP-162952","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lower Granite Dam, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.7515022516423,\n 47.195723484659\n ],\n [\n -119.7515022516423,\n 46.04149363558699\n ],\n [\n -117.09892399655794,\n 46.04149363558699\n ],\n [\n -117.09892399655794,\n 47.195723484659\n ],\n [\n -119.7515022516423,\n 47.195723484659\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Voss, Nicholas S.","contributorId":300117,"corporation":false,"usgs":false,"family":"Voss","given":"Nicholas","email":"","middleInitial":"S.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":935996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Joshua L.","contributorId":354615,"corporation":false,"usgs":false,"family":"McCormick","given":"Joshua L.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":935997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lubenau, William J.","contributorId":354616,"corporation":false,"usgs":false,"family":"Lubenau","given":"William J.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bowersox, Brett J.","contributorId":265299,"corporation":false,"usgs":false,"family":"Bowersox","given":"Brett","email":"","middleInitial":"J.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":935999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Copeland, Timothy","contributorId":265301,"corporation":false,"usgs":false,"family":"Copeland","given":"Timothy","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":936000,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936001,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262028,"text":"70262028 - 2024 - Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii)","interactions":[],"lastModifiedDate":"2025-01-10T16:25:20.923883","indexId":"70262028","displayToPublicDate":"2024-12-06T10:17:51","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7509,"text":"The Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii)","title":"Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii)","docAbstract":"The Henslow's Sparrow (Centronyx henslowii) is a grassland bird species that overwinters in the southeastern United States and is a species of conservation concern due to population declines primarily caused by habitat loss. Henslow's Sparrows often overwinter in marginal habitats, such as powerline rights-of-way (ROWs), clear cuts, and field edges that provide some of their desired habitat characteristics, such as low-to-no tree cover and a diverse herbaceous understory. Using remote sensing methods, we evaluated the habitat characteristics of Henslow's Sparrow–occupied ROWs in southeastern Georgia. We calculated 22 satellite imagery metrics from Sentinel 2-L2 10 m resolution imagery, including single-pixel variables (e.g., Enhanced Vegetation Index, EVI) as well as “image texture” metrics that represent spatial heterogeneity. Using Random Forest models, we evaluated whether satellite imagery metrics could be used to discriminate between Henslow's Sparrow used areas (delineated from telemetry data) and surrounding available areas. Satellite imagery metrics were successful in predicting habitat characteristics in the ROWs (as evaluated by out-of-bag error and 3 goodness-of-fit tests), with image texture metrics performing better than single-pixel metrics. Image texture metrics were 9 of the top 10 most important predictors of habitat use in the best performing model that had a 500 m available buffer around use areas (out-of-bag error rate 21.21%). The most important image texture metric, cluster shade, was positively correlated with tree cover; Henslow's Sparrows were more likely to use areas with intermediate levels of cluster shade. From our results, we concluded that image texture metrics derived from 10 m satellite imagery could be used to predict sites that have suitable overwintering habitat for Henslow's Sparrows, but only at coarse resolutions and broader extents (hundreds of meters to kilometers). Therefore, this tool could be used to identify other ROWs (and possibly non-ROWs) with habitat that may support this and other declining grassland species.
","language":"English","publisher":"Wilson Ornithological Society","doi":"10.1676/23-00049","usgsCitation":"Moore, S., Dwire, A., Prebyl, T., Schneider, T., and Hunter, E.A., 2024, Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii): The Wilson Journal of Ornithology, v. 136, no. 4, p. 436-447, https://doi.org/10.1676/23-00049.","productDescription":"12 p.","startPage":"436","endPage":"447","ipdsId":"IP-154594","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":465994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Moody Forest Wildlife Management Area, Townsend Wildlife Management Area, Paulks Pasture Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.57525588321172,\n 32.48251517887438\n ],\n [\n -82.66578654540206,\n 31.015534685580576\n ],\n [\n -81.36949067181612,\n 30.978771137717928\n ],\n [\n -80.93094224410345,\n 32.04324987692853\n ],\n [\n -82.57525588321172,\n 32.48251517887438\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"136","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Sierra A.","contributorId":347927,"corporation":false,"usgs":false,"family":"Moore","given":"Sierra A.","affiliations":[{"id":81880,"text":"Department of Fish and Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":922751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dwire, Abigail W.","contributorId":347929,"corporation":false,"usgs":false,"family":"Dwire","given":"Abigail W.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":922752,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prebyl, Thomas J.","contributorId":347930,"corporation":false,"usgs":false,"family":"Prebyl","given":"Thomas J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":922753,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schneider, Todd M.","contributorId":347932,"corporation":false,"usgs":false,"family":"Schneider","given":"Todd M.","affiliations":[{"id":36378,"text":"Georgia Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":922754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922755,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264044,"text":"70264044 - 2024 - Structured decision-making workshop: Chronic wasting disease management in free-ranging cervids in Massachusetts","interactions":[],"lastModifiedDate":"2025-03-05T16:27:26.437342","indexId":"70264044","displayToPublicDate":"2024-12-06T10:17:30","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-161-2024","title":"Structured decision-making workshop: Chronic wasting disease management in free-ranging cervids in Massachusetts","docAbstract":"This document describes the results of a 2.5-day rapid decision prototype workshop that evaluated management activities for chronic wasting disease (CWD) in Massachusetts (MA) that were either proactive (i.e., actions taken prior to CWD arrival/detection) or reactive (i.e., actions taken after CWD arrival/detection). The workshop was led by members of the Wildlife Section of the MA Division of Fisheries and Wildlife (hereafter referred to as MassWildlife) and included a group of agency communications specialists and district managers. U. S. Geological Survey staff and a volunteer acted as decision facilitators and led the analysis of the decision.
Chronic wasting disease is an always fatal neurological disease that has spread across much of North America and threatens the health of deer populations in locations where it occurs (reviewed by Escobar et al. 2020). CWD can spread into new areas via two general mechanisms: (1) natural spread (e.g., dispersal of CWD-infected male white-tailed deer [Odocoileus virginianus]), and (2) anthropogenic spread (e.g., CWD spread facilitated by human intervention; Leiss et al. 2017, Escobar et al. 2020). Once CWD arrives in a state, natural resources agencies spend eight times more on CWD than agencies with no known cases; to cover these new CWD-related management activities, the natural resources agencies are typically forced to reallocate money from existing conservation priorities (Chiavacci, 2022). As of May 2024, there were 34 U.S. states and five Canadian provinces that had detected CWD positive free-ranging and/or captive animals in the family Cervidae (collectively referred to as ‘cervid’ hereafter), and the number of new states/provinces that are detecting CWD for the first time continues to grow (U. S. Geological Survey, May 2024). As of February 2024, the closest CWD positive state to MA with CWD detected in free-ranging white-tailed deer is Pennsylvania. To date, there have been no detections of CWD in MA, but testing has been limited in MA since 2012. The growing number of CWD positive states suggests that there may be increasing risk of CWD entering and establishing in MA as the number of CWD cases increases across North America.
According to a 2023 survey of hunters in MA conducted by MassWildlife, 68% of hunters were concerned about CWD entering MA, and 88% of respondents said that it was at least moderately important to keep CWD out of MA; these survey results indicate that most hunters may support CWD risk reduction actions (Martin Feehan, Massachusetts Division of Fisheries and Wildlife, oral communication, 12 Feb 2024). In addition, 23.1% of responding deer hunters in MA have hunted for cervids in CWD-positive states/provinces in the last five years (not including states/provinces that have been able to successfully eradicate CWD following a positive detection). Participants of the survey were also asked, “how many deer have you harvested that tested positive for CWD?”. A total of three respondents said that they had one deer test positive for CWD, which, when extended to the whole population of MA deer hunters, results in an estimated 32 CWD positive deer harvested in CWD-positive states and imported into MA in the last five years. When asked about how they transport harvested deer from out of state into MA, the three participants indicated either “already processed & packaged” or “not applicable.” Note, that in MA, it is a violation of regulation to import whole carcasses or high-risk parts (e.g., head, brain, spinal tissues, bones) of any member of the Cervidae family (wild or captive) from a state/province that has detected CWD; it is legal to bring in deboned meat, cleaned skull caps, hides without the head, or a fixed taxidermy mount (Massachusetts Division of Fisheries and Wildlife, 2024a).
To date, testing for CWD has been limited in MA since 2012. However, the data collected from the 2023 MA hunter survey suggests that there is a real risk of CWD being imported by a MA resident who has hunted in a CWD positive state. Therefore, given the higher costs of CWD management post arrival, the potential natural spread of CWD from nearby states, and the risk of CWD introduction via humanmediated cervid movement, MassWildlife is motivated to take actions that minimize the risk of CWD introduction and spread in MA with the ultimate goal of managing thriving wildlife populations and maximizing hunter and general public satisfaction, which are both parts of the MassWildlife mission.
A 2.5-day rapid prototyping structured decision making workshop was held with MassWildlife staff to develop a decision framework for CWD management in MA. During the workshop, we defined the context and extent of CWD management activities in MA. Next, we identified four fundamental objectives that help achieve the mission of MassWildlife and that address stakeholder concerns. The fundamental objectives included: (1) maximizing hunter satisfaction and participation, (2) maximizing public satisfaction (non-consumptive), (3) maximizing health and sustainability of cervids, and (4) maximizing the efficiency of CWD management. Then, we generated a list of five alternatives (i.e., strategies) that varied the intensity of proactive and reactive actions. The five strategies were: (1) minimal proactive and minimal reactive actions, (2) intermediate proactive and intermediate reactive actions, (3) intensive proactive and intermediate reactive actions, (4) minimal proactive and intensive reactive actions, and (5) intensive proactive and intensive reactive actions. Lastly, we estimated the performance of each strategy on the fundamental objectives and assessed the overall performance of strategies relative to one another. We did so by first estimating the consequences of each alternative strategy on fundamental objectives using expert elicitation, and then, we elicited objective weights from MassWildlife staff to incorporate the relative importance of different fundamental objectives.
Given that it is unknown when CWD will arrive in MA, we evaluated the performance of alternative strategies against fundamental objectives given three distinct scenarios for time to arrival of CWD: introduction in 2.5, 7.5, or 10+ years. The preliminary results of the rapid prototype indicate that the performance of the CWD management strategies that we evaluated depends on when CWD first arrives in MA. If CWD were to arrive in 2.5 or 7.5 years from now (February, 2024), then the ‘minimal proactive and minimal reactive’ strategy performs the best on both the deer population and cost fundamental objectives (fundamental objectives 3 & 4), but the ‘intensive proactive and intensive reactive’ strategy performs best on both of the human dimensions fundamental objectives (fundamental objectives 1 & 2) as well as the minimize CWD prevalence objective (also related to fundamental objective 3). We also found that public trust is likely to remain high across all five alternative strategies if CWD arrives after year 10, but public trust decreases if CWD arrives in year 2.5 or 7.5. After incorporating objective weights, we found that in scenarios where CWD arrives in the near-term (in years 2.5 or 7.5), an intermediate strategy (e.g., ‘intermediate proactive and intermediate reactive’ or ‘intensive proactive and intermediate reactive’) performed best, and the ‘minimal proactive and intensive reactive’ strategy performed worst. Conversely, if CWD were to arrive after 10 years, then the ‘minimal proactive and minimal reactive’ and ‘minimal proactive and intensive reactive’ strategies performed best. Collectively, these results suggest that the decision on which alternative strategy to employ is sensitive to when CWD arrives in MA. Following the discussion of the preliminary results, we identified the following four next steps. First, we discussed how a more detailed communications plan is needed and would likely alter the performance estimates of the alternative strategies on fundamental objectives 1 & 2, which were hunter and public satisfaction, respectively. The development of the communication plan would likely be easier once the alternative actions have been identified along with the audience and message. Second, a surveillance plan could be a useful tool to inform CWD management. Surveillance for CWD was performed in MA annually from 2002 to 2012 (n = 4,356 wild white-tailed deer and moose [Alces alces] samples). Limited surveillance was conducted from 2013 to 2022; and in 2023, 242 wild samples were collected. It is not clear whether MA needs a robust or minimal surveillance plan (e.g., is a minimal surveillance plan enough to detect the pathogen at the threshold that would trigger action?), or what type of invasion event the surveillance plan should target (e.g., natural vs anthropogenic spread events). The use of decision trees and a formal risk assessment may help answer these questions. Third, some of the elicited estimates from experts during this rapid prototype could be replaced with empirical data. Lastly, given that the decision was sensitive to when CWD arrived in MA and a surveillance plan would rely on the mode of introduction, forecasting and predicting the CWD invasion front and/or the likelihood of different incursion events across MA would provide valuable insights.
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Such diversity has implications for survivability, adaptability, and resiliency of a species. This study aimed to determine levels of genetic diversity and population genetic structure in the Northern Black Swift (Cypseloides niger borealis). This species nests across western North America as far north as Canada and south into Mexico, migrating annually to wintering areas in western Brazil. Colonies occur in isolated areas where appropriate nesting habitat is available, and in many cases, colonies are widely separated from each other. Banding data revealed that adults of this long-lived species return to their same breeding colony annually for many years. Additionally, some females exhibit natal philopatry, returning to and successfully raising offspring at the colony where they were hatched. This allowed us to hypothesize that we might expect some amount of genetic structure in the samples we studied. The life history characteristics of this species suggest that breeding colonies might be more genetically differentiated than other migratory birds that tend to have limited population genetic structure across their ranges. We used newly developed species-specific microsatellite primers to examine levels of genetic diversity and connectivity among 6 Black Swift colonies in the western United States. Levels of genetic diversity were generally high (expected heterozygosity ranging from 0.67 to 0.75) and comparable across 3 breeding sites with sufficient sample sizes (N > 5). Principal coordinates analysis and STRUCTURE analysis showed no real clustering of individuals in regard to colonies, suggesting one panmictic metapopulation rather than multiple populations that are genetically distinct as we had previously hypothesized based on banding data. This is the first study to elucidate the genetic structure among colonies of Black Swift.
","language":"English","publisher":"Wilson Ornithological Society","doi":"10.1676/23-00043","usgsCitation":"Gunn, C., Potter, K., Fike, J., and Oyler-McCance, S.J., 2024, High genetic diversity, low population genetic structure, strong natal philopatry, and longevity revealed in the Black Swift (Cypseloides niger borealis): The Wilson Journal of Ornithology, v. 136, no. 4, p. 448-457, https://doi.org/10.1676/23-00043.","productDescription":"11 p.","startPage":"448","endPage":"457","ipdsId":"IP-154645","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":464920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, New 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0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":920481,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261288,"text":"ofr20211030R - 2024 - System characterization report on the Earth Surface Mineral Dust Source Investigation (EMIT) sensor","interactions":[{"subject":{"id":70261288,"text":"ofr20211030R - 2024 - System characterization report on the Earth Surface Mineral Dust Source Investigation (EMIT) sensor","indexId":"ofr20211030R","publicationYear":"2024","noYear":false,"chapter":"R","displayTitle":"System Characterization Report on the Earth Surface Mineral Dust Source Investigation (EMIT) Sensor","title":"System characterization report on the Earth 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Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1030","chapter":"R","displayTitle":"System Characterization Report on the Earth Surface Mineral Dust Source Investigation (EMIT) Sensor","title":"System characterization report on the Earth Surface Mineral Dust Source Investigation (EMIT) sensor","docAbstract":"This report addresses system characterization of the Earth Surface Mineral Dust Source Investigation (EMIT) sensor, an imaging spectrometer developed by the National Aeronautics and Space Administration. This report is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior) and radiometric performances. Results of these analyses indicate that the EMIT sensor has a band-to-band geometric performance in the range of −0.355 to 0.210 pixel with a few exceptions of shortwave infrared channels. Geometric offset relative to the Landsat 8 Operational Land Imager ranged from −15.966 meters (−0.266 pixel) to 43.844 meters (0.731 pixel). Offset of a radiometric comparison ranged from −0.016 to 0.025, and slope of a radiometric comparison ranged from 0.837 to 0.985. EMIT agreed with Radiometric Calibration Network measurements within 5 percent across most of the spectral channels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030R","usgsCitation":"Shrestha, M., Sampath, A., Kim, M., and Park, S., 2024, System characterization report on the Earth Surface Mineral Dust Source Investigation (EMIT) sensor, chap. R of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 27 p., https://doi.org/10.3133/ofr20211030R.","productDescription":"vi, 27 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-167707","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":464759,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030R/full"},{"id":464758,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/r/images/"},{"id":464755,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/r/coverthb.jpg"},{"id":464756,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/r/ofr20211030r.pdf","text":"Report","size":"6.35 MB","description":"OFR 2021–1030–R"},{"id":464757,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/r/ofr20211030r.XML"}],"contact":"Director, Earth Resources Observation and Science Center
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