Retrospective eruption characterization is valuable for advancing our understanding of volcanic systems and evaluating our observational capabilities, especially with remote technologies (defined here as a space-borne system or non-local, ground-based instrumentation which include regional and remote infrasound sensors). In June 2019, the open-system Ulawun volcano, Papua New Guinea, produced a VEI 4 eruption. We combined data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System infrasound network, and GLD360 globally detected lightning with information from the local authorities and social media to characterize the pre-, syn- and post-eruptive behaviour. The Rabaul Volcano Observatory recorded ~24 h of seismicity and detected SO2 emissions ~16 h before the visually-documented start of the Plinian phase on 26 June at 04:20 UTC. Infrasound and SO2 detections suggest the eruption started during the night on 24 June 2019 at 10:39 UTC ~38 h before ash detections with a gas-dominated jetting phase. Local reports and infrasound detections show that the second phase of the eruption started on 25 June 19:28 UTC with ~6 h of jetting. The first detected lightning occurred on 26 June 00:14 UTC, and ash emissions were first detected by Himawari-8 at 01:00 UTC. Post-eruptive satellite imagery indicates new flow deposits to the south and north of the edifice and ash fall to the west and southwest. In particular, regional infrasound data provided novel insight into eruption onset and syn-eruptive changes in intensity. We conclude that, while remote observations are sufficient for detection and tracking of syn-eruptive changes, key challenges in data latency, acquisition, and synthesis must be addressed to improve future near-real-time characterization of eruptions at minimally-monitored or unmonitored volcanoes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107381","usgsCitation":"McKee, K., Smith, C.M., Reath, K., Snee, E., Maher, S., Matoza, R.S., Carn, S.A., Roman, D., Mastin, L.G., Anderson, K.R., Damby, D., Itikarai, I., Mulina, K., Saunders, S., Assink, J.D., de Negri Levia, R., and Perttu, A., 2021, Evaluating the state-of-the-art in remote volcanic eruption characterization Part II: Ulawun volcano, Papua New Guinea: Journal of Geophysical Research, v. 420, 107381, 14 p., https://doi.org/10.1016/j.jvolgeores.2021.107381.","productDescription":"107381, 14 p.","ipdsId":"IP-131054","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":451112,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://hdl.handle.net/11603/26623","text":"Publisher Index Page"},{"id":389733,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Papua New Guinea","otherGeospatial":"Bismark volcanic arc, New Britain Island, Ulawun volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 151.512451171875,\n -5.637852598770853\n ],\n [\n 151.58660888671875,\n -5.577716982024741\n ],\n [\n 151.78985595703125,\n -5.607785565054955\n ],\n [\n 152.0947265625,\n -5.473831889192786\n ],\n [\n 152.16064453124997,\n -5.328909448322195\n ],\n [\n 151.9683837890625,\n -5.123772299948803\n ],\n [\n 151.99859619140625,\n -4.989713620805972\n ],\n [\n 151.6387939453125,\n -4.784468966579362\n ],\n [\n 151.578369140625,\n -4.913096316540102\n ],\n [\n 151.171875,\n -4.869311036456154\n ],\n [\n 151.0894775390625,\n -4.891204034424394\n ],\n [\n 150.99334716796875,\n -5.307031369598637\n ],\n [\n 150.99884033203125,\n -5.356255950601535\n ],\n [\n 151.512451171875,\n -5.637852598770853\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"420","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKee, Kathleen 0000-0003-3189-9189","orcid":"https://orcid.org/0000-0003-3189-9189","contributorId":265977,"corporation":false,"usgs":false,"family":"McKee","given":"Kathleen","email":"","affiliations":[{"id":54848,"text":"Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC, USA","active":true,"usgs":false}],"preferred":false,"id":823930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Cassandra Marie 0000-0003-2653-4249 cassandrasmith@usgs.gov","orcid":"https://orcid.org/0000-0003-2653-4249","contributorId":257000,"corporation":false,"usgs":true,"family":"Smith","given":"Cassandra","email":"cassandrasmith@usgs.gov","middleInitial":"Marie","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reath, Kevin","contributorId":194091,"corporation":false,"usgs":false,"family":"Reath","given":"Kevin","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":823932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Snee, Eveanjelene 0000-0002-3660-4020","orcid":"https://orcid.org/0000-0002-3660-4020","contributorId":265978,"corporation":false,"usgs":false,"family":"Snee","given":"Eveanjelene","email":"","affiliations":[{"id":54849,"text":"School of Earth and Ocean Sciences, Cardiff University, Cardiff, Wales, UK","active":true,"usgs":false}],"preferred":false,"id":823933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maher, Sean","contributorId":265979,"corporation":false,"usgs":false,"family":"Maher","given":"Sean","affiliations":[{"id":54850,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":823934,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":823935,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carn, Simon A","contributorId":191165,"corporation":false,"usgs":false,"family":"Carn","given":"Simon","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":823936,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roman, Diana","contributorId":237832,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","affiliations":[{"id":47620,"text":"Dept. of Terrestrial Magnetism, Carnegie Institution for Science, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":823937,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823938,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823939,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823940,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Itikarai, Ima","contributorId":265986,"corporation":false,"usgs":false,"family":"Itikarai","given":"Ima","email":"","affiliations":[{"id":54853,"text":"Rabaul Volcano Observatory, Department of Mining and Petroleum, Geological Survey of Papua New Guinea, Rabaul, Papua New Guinea","active":true,"usgs":false}],"preferred":false,"id":823941,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mulina, Kila","contributorId":265987,"corporation":false,"usgs":false,"family":"Mulina","given":"Kila","email":"","affiliations":[{"id":54853,"text":"Rabaul Volcano Observatory, Department of Mining and Petroleum, Geological Survey of Papua New Guinea, Rabaul, Papua New Guinea","active":true,"usgs":false}],"preferred":false,"id":823942,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Saunders, Steve","contributorId":265988,"corporation":false,"usgs":false,"family":"Saunders","given":"Steve","email":"","affiliations":[{"id":54853,"text":"Rabaul Volcano Observatory, Department of Mining and Petroleum, Geological Survey of Papua New Guinea, Rabaul, Papua New Guinea","active":true,"usgs":false}],"preferred":false,"id":823943,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Assink, Jelle D.","contributorId":236650,"corporation":false,"usgs":false,"family":"Assink","given":"Jelle","email":"","middleInitial":"D.","affiliations":[{"id":47493,"text":"R and D Seismology and Acoustics, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA De Bilt, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":823944,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"de Negri Levia, Rodrigo 0000-0003-1283-2579","orcid":"https://orcid.org/0000-0003-1283-2579","contributorId":265983,"corporation":false,"usgs":false,"family":"de Negri Levia","given":"Rodrigo","email":"","affiliations":[{"id":54852,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA; NDC-CTBT of the Chilean Nuclear Energy Commission, Chile","active":true,"usgs":false}],"preferred":false,"id":823953,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Perttu, Anna 0000-0003-3590-1549","orcid":"https://orcid.org/0000-0003-3590-1549","contributorId":265984,"corporation":false,"usgs":false,"family":"Perttu","given":"Anna","email":"","affiliations":[{"id":48937,"text":"Earth Observatory of Singapore, Nanyang Technological University, Singapore","active":true,"usgs":false}],"preferred":false,"id":823946,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70223688,"text":"70223688 - 2021 - National seed strategy progress report, 2015-2020","interactions":[],"lastModifiedDate":"2021-09-02T11:30:49.37028","indexId":"70223688","displayToPublicDate":"2021-08-20T08:36:09","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":9317,"text":"Progress Report","active":true,"publicationSubtype":{"id":9}},"title":"National seed strategy progress report, 2015-2020","docAbstract":"Native plants are the true green infrastructure we rely on for healthy, resilient, and biodiverse ecosystems. They protect us against climate change and natural disasters; create habitat for wildlife, rare species, and pollinators; and are vital for carbon sequestration. Without native plants, especially their seeds, we do not have the ability to restore functional ecosystems after natural disasters and mitigate the effects of climate change. Investing now in coordinated, research-driven native seed production is an efficient and cost-effective nature-based solution for improving ecosystem resilience in the face of the climate and extinction crisis. Federal government agencies (see list on page 13 and their partners are collaborating to increase the supply of native seeds for restoration through the National Seed Strategy for Rehabilitation and Restoration (National Seed Strategy) to get the right seed in the right place at the right time. The National Seed Strategy is a public-private collaboration to increase the supply of native seeds for restoration projects to ensure ecosystem resilience and the health and prosperity of future generations. Developed by the Plant Conservation Alliance (PCA) in 2015, the National Seed Strategy harnesses cross sector botanical expertise, supports rural, agricultural, minority, and tribal livelihoods, and provides training opportunities to our next generation of natural resource professionals to maintain and preserve our iconic habitats. This science-driven national effort is integral to the Nation’s conservation priorities, including the commitment to conserve 30% of America’s lands and waters by 2030 as outlined in Executive Order 14008 on Tackling the Climate Crisis at Home and Abroad. Moreover, the National Seed Strategy is recognized in the objectives of the 2021 DOI Invasive Species Strategic Plan (DOI 2021) and addresses national priorities such as climate change, wildland fire, and tribal engagement. The National Seed Strategy charts a course for federal, tribal, state, local and private partners to increase private and public sector coordination on native seed development, thereby accelerating the pace and scale of restoration. Success is being achieved through the establishment of nationwide networks of seed collectors, researchers to develop seed, farmers to grow native seed, nurseries and seed storage facilities to supply adequate quantities of appropriate seed, and restoration ecologists.
","language":"English","publisher":"Bureau of Land Management (National Operations Center)","usgsCitation":"Mccormick, M.L., Carr, A., DeAngelis, P., Olwell, M., Murray, R., and Park, M., 2021, National seed strategy progress report, 2015-2020: Progress Report, ii, 74 p.","productDescription":"ii, 74 p.","ipdsId":"IP-130943","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":388744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":388718,"type":{"id":11,"text":"Document"},"url":"https://www.blm.gov/sites/blm.gov/files/docs/2021-08/Progress%20Report%2026Jul21.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mccormick, Molly Lutisha 0000-0002-4361-7567","orcid":"https://orcid.org/0000-0002-4361-7567","contributorId":265148,"corporation":false,"usgs":true,"family":"Mccormick","given":"Molly","email":"","middleInitial":"Lutisha","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":822325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Amanda N","contributorId":265150,"corporation":false,"usgs":false,"family":"Carr","given":"Amanda N","affiliations":[{"id":54608,"text":"Chicago Botanic Garden, Glencoe, IL","active":true,"usgs":false}],"preferred":false,"id":822326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Patricia","contributorId":265151,"corporation":false,"usgs":false,"family":"DeAngelis","given":"Patricia","email":"","affiliations":[{"id":54610,"text":"U.S. Fish and Wildlife Service, Falls Church, VA","active":true,"usgs":false}],"preferred":false,"id":822327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olwell, Margaret","contributorId":265152,"corporation":false,"usgs":false,"family":"Olwell","given":"Margaret","email":"","affiliations":[{"id":54611,"text":"Bureau of Land Management, Boise, ID","active":true,"usgs":false}],"preferred":false,"id":822328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, Regan","contributorId":265162,"corporation":false,"usgs":false,"family":"Murray","given":"Regan","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":822359,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Park, Maggie","contributorId":265163,"corporation":false,"usgs":false,"family":"Park","given":"Maggie","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":822360,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70224747,"text":"70224747 - 2021 - Cohesive sediment modeling in a shallow estuary: Model and environmental implications of sediment parameter variation","interactions":[],"lastModifiedDate":"2021-10-04T12:47:21.058229","indexId":"70224747","displayToPublicDate":"2021-08-20T07:44:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9372,"text":"Journal of Geophysical Research--Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Cohesive sediment modeling in a shallow estuary: Model and environmental implications of sediment parameter variation","docAbstract":"Numerical models of sediment transport in estuarine systems rely on parameter values that are often poorly constrained and can vary on timescales relevant to model processes. The selection of parameter values can affect the accuracy of model predictions, while environmental variation of these parameters can impact the temporal and spatial ranges of sediment fluxes, erosion, and deposition in the real world. We implemented a numerical model of San Pablo Bay, an embayment within San Francisco Bay, California, for November–December 2014, and compared model outputs to observations of water level, velocity, wave parameters, salinity, and suspended sediment concentration (SSC) in the shallow regions. Idealized model runs show that wind timing relative to the phase of the tides is the strongest control on sediment fluxes and bed erosion. We varied sediment erodibility in the outflow of the Petaluma River; while this causes erosion and deposition to vary strongly through the shallows system, total export from the shallows does not change. Model runs with realistic winds show that wind likely resuspends faster settling particles or allows for more particle flocculation; particle settling velocity controls system-wide sediment accumulation. At the margins of the system, the magnitude of SSC is closely tied to wind direction when winds occur during flood tide, but sediment deposition is less connected: Both bed evolution and SSC need to be considered in the prediction of marsh fate. Spatial patterns of light attenuation due to SSC is strongly tied to assumed settling velocity.
Wetlands provide ecological functionality by maintaining and promoting regional biodiversity supporting quality habitat for aquatic organisms. Globally, habitat loss, fragmentation and degradation due to increases in agricultural activities and urban development have reduced or altered geographically isolated wetlands, thus reducing biodiversity. The objective of this study was to assess the relative ecological function and integrity of natural ponds, excavated ponds and stormwater basins in the New Jersey Pinelands, located in the northeastern United States by comparing hydrologic conditions, water quality, pesticide concentrations (water, sediment and tissue) and wetland assemblages including amphibians. Twenty-four wetlands were selected based on surrounding land-use and sampled for a variety of abiotic and biotic variables. Abiotic and biotic wetland variables were similar between natural and excavated ponds, with notable differences between the ponds and stormwater basins. Natural and excavated ponds displayed characteristic Pinelands water quality (low pH, high organic carbon, and low pesticide concentrations), exhibited high ecological integrity and supported native ampbibians. Stormwater basins and degraded ponds surrounded by altered land-use exhibited degraded water quality (high pH, high pesticide concentrations) and were dominated by non-native and introduced plants and amphibians. Results from this study can broadly inform resource conservation strategies for amphibians and other communities with a diverse range of habitat requirements, particularly in areas where conservation and development are competing priorities. To conserve biodiversity in changing landscapes, wetlands with similar functionality and land-use characteristics need to be identified and managed to preserve water quality for species of conservation concern.
No abstract available.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EO162330","usgsCitation":"Pratt, T.L., Chapman, M.C., Shah, A.K., Horton,, J., and Boyd, O.S., 2021, Ten years on from the quake that shook the nation’s capital: EOS, Transactions AGU, HTML Document, https://doi.org/10.1029/2021EO162330.","productDescription":"HTML Document","ipdsId":"IP-131539","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":451117,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021eo162330","text":"Publisher Index Page"},{"id":392849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Washington, D.C.","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.519287109375,\n 37.94419750075404\n ],\n [\n -75.421142578125,\n 37.94419750075404\n ],\n [\n -75.421142578125,\n 39.62261494094297\n ],\n [\n -78.519287109375,\n 39.62261494094297\n ],\n [\n -78.519287109375,\n 37.94419750075404\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":828371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Martin C.","contributorId":139348,"corporation":false,"usgs":false,"family":"Chapman","given":"Martin","email":"","middleInitial":"C.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":828372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":828373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horton,, J. Wright Jr. 0000-0001-6756-6365","orcid":"https://orcid.org/0000-0001-6756-6365","contributorId":219824,"corporation":false,"usgs":true,"family":"Horton,","given":"J. Wright","suffix":"Jr.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":828374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":828375,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223197,"text":"sir20205142 - 2021 - Regional regression equations based on channel-width characteristics to estimate peak-flow frequencies at ungaged sites in Montana using peak-flow frequency data through water year 2011","interactions":[],"lastModifiedDate":"2021-09-21T11:36:03.273884","indexId":"sir20205142","displayToPublicDate":"2021-08-19T15:56:48","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5142","displayTitle":"Regional Regression Equations Based on Channel-Width Characteristics to Estimate Peak-Flow Frequencies at Ungaged Sites in Montana Using Peak-Flow Frequency Data through Water Year 2011","title":"Regional regression equations based on channel-width characteristics to estimate peak-flow frequencies at ungaged sites in Montana using peak-flow frequency data through water year 2011","docAbstract":"The U.S. Geological Survey, in cooperation with the Montana Department of Transportation, developed regression equations based on channel width to estimate peak-flow frequencies at ungaged sites in Montana. The equations are based on peak-flow data at streamgages through September 2011 (end of water year 2011), and channel widths measured in the field and from aerial photographs.
Active-channel width and bankfull width (channel widths) were measured in the field at 64 sites across Montana in 2017. Channel widths also were measured near 515 streamgages from aerial photographs. These new channel-width data, along with more than 438 historical channel-width measurements, are published in a separate data release.
Regression equations were developed using generalized least squares regression or weighted least squares regression. The channel-width regression equations can be used to estimate peak-flow frequencies (peak-flow magnitudes associated with annual exceedance probabilities of 66.7, 50, 42.9, 20, 10, 4, 2, 1, 0.5, and 0.2 percent) at ungaged sites in each of the eight hydrologic regions in Montana. Methods are presented for weighting estimates from the channel-width equations with estimates from equations using basin characteristics. The weighting technique can be used to reduce the standard error of prediction relative to that obtained using a single method. Several example problems covering a range of estimation scenarios also are included.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205142","collaboration":"Prepared in cooperation with Montana Department of Transportation","usgsCitation":"Chase, K.J., Sando, R., Armstrong, D.W., and McCarthy, P., 2021, Regional regression equations based on channel-width characteristics to estimate peak-flow frequencies at ungaged sites in Montana using peak-flow frequency data through water year 2011 (ver. 1.1, September 2021): U.S. Geological Survey Scientific Investigations Report 2020–5142, 49 p., https://doi.org/10.3133/sir20205142.","productDescription":"Report: vi, 49 p.; Data Release; Dataset; Version History","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-102009","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":436235,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D7MEB1","text":"USGS data release","linkHelpText":"StreamStats Channel Width Weighting Services"},{"id":387993,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5142/coverthb2.jpg"},{"id":387995,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CCGJ0I","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Channel width measurements for selected streamgage sites in Montana"},{"id":387996,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":389479,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5142/sir20205142.pdf","text":"Report","size":"4.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5142"},{"id":389480,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2020/5142/versionHist.txt","text":"Version History","size":"2.05 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"}],"country":"United States","state":"Montana","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-105.038405,45.000345],[-105.848065,45.000396],[-105.913382,45.000941],[-105.914258,44.999986],[-105.928184,44.993647],[-106.263586,44.993788],[-107.050801,44.996424],[-107.074996,44.997004],[-107.084939,44.996599],[-107.105685,44.998734],[-107.125633,44.999388],[-107.13418,45.000109],[-107.351441,45.001407],[-107.49205,45.00148],[-107.608854,45.00086],[-107.750654,45.000778],[-107.997353,45.001565],[-108.000663,45.001223],[-108.14939,45.001062],[-108.218479,45.000541],[-108.238139,45.000206],[-108.249345,44.999458],[-108.271201,45.000251],[-108.500679,44.999691],[-108.565921,45.000578],[-109.08301,44.99961],[-109.103445,45.005904],[-109.375713,45.00461],[-109.386432,45.004887],[-109.574321,45.002631],[-109.663673,45.002536],[-109.75073,45.001605],[-109.875735,45.003275],[-109.99505,45.003174],[-110.026347,45.003665],[-110.110103,45.003905],[-110.199503,44.996188],[-110.28677,44.99685],[-110.324441,44.999156],[-110.342131,44.999053],[-110.362698,45.000593],[-110.402927,44.99381],[-110.48807,44.992361],[-110.552433,44.992237],[-110.705272,44.992324],[-110.750767,44.997948],[-110.761554,44.999934],[-110.785008,45.002952],[-111.055199,45.001321],[-111.056207,44.935901],[-111.055629,44.933578],[-111.056888,44.866658],[-111.056416,44.749928],[-111.055511,44.725343],[-111.055208,44.624927],[-111.048974,44.474072],[-111.062729,44.476073],[-111.122654,44.493659],[-111.131379,44.499925],[-111.139455,44.517112],[-111.143557,44.535732],[-111.15959,44.546376],[-111.166892,44.54722],[-111.175747,44.552219],[-111.182551,44.566874],[-111.189617,44.571062],[-111.201459,44.575696],[-111.225208,44.581006],[-111.23018,44.587025],[-111.231227,44.606915],[-111.224161,44.623402],[-111.25268,44.651092],[-111.262839,44.649658],[-111.276956,44.655626],[-111.26875,44.668279],[-111.29626,44.702271],[-111.323669,44.724474],[-111.341351,44.7293],[-111.348184,44.725459],[-111.355768,44.727602],[-111.366723,44.738361],[-111.36627,44.742234],[-111.37476,44.750295],[-111.385005,44.755128],[-111.393854,44.752549],[-111.397805,44.746738],[-111.394459,44.744578],[-111.398575,44.723343],[-111.414271,44.710741],[-111.424214,44.714024],[-111.429604,44.720149],[-111.438793,44.720546],[-111.486019,44.707654],[-111.489339,44.704946],[-111.490228,44.700221],[-111.484898,44.687578],[-111.47798,44.682393],[-111.468833,44.679335],[-111.473178,44.665479],[-111.50494,44.635746],[-111.521688,44.613371],[-111.525764,44.604883],[-111.524213,44.595585],[-111.519126,44.582916],[-111.492024,44.56081],[-111.469185,44.552044],[-111.467736,44.544521],[-111.471682,44.540824],[-111.500792,44.540062],[-111.518095,44.544177],[-111.524006,44.548385],[-111.546637,44.557099],[-111.556577,44.554495],[-111.562814,44.555209],[-111.585763,44.562843],[-111.591768,44.561502],[-111.601249,44.55421],[-111.614405,44.548991],[-111.681571,44.559864],[-111.704218,44.560205],[-111.709553,44.550206],[-111.715474,44.543543],[-111.737191,44.54306],[-111.746401,44.540766],[-111.758966,44.533766],[-111.761904,44.529841],[-111.806512,44.516264],[-111.807914,44.511716],[-111.821488,44.509286],[-111.842542,44.526069],[-111.849293,44.539837],[-111.870504,44.564033],[-111.887852,44.563413],[-111.903566,44.55723],[-111.947941,44.556776],[-111.951522,44.550062],[-111.980833,44.536682],[-111.995231,44.535444],[-112.01385,44.542348],[-112.032707,44.546642],[-112.035025,44.542691],[-112.034133,44.537716],[-112.036943,44.530323],[-112.053434,44.535089],[-112.069011,44.537104],[-112.093304,44.530002],[-112.096299,44.523212],[-112.101564,44.520847],[-112.106755,44.520829],[-112.125101,44.528527],[-112.129078,44.5363],[-112.136454,44.539911],[-112.164597,44.541666],[-112.179703,44.533021],[-112.183937,44.533067],[-112.221698,44.543519],[-112.229477,44.549494],[-112.226841,44.555239],[-112.230117,44.562759],[-112.242785,44.568091],[-112.258665,44.569516],[-112.286187,44.568472],[-112.307642,44.557651],[-112.312899,44.553536],[-112.315047,44.550049],[-112.315008,44.5419],[-112.319198,44.53911],[-112.348794,44.538691],[-112.35421,44.535638],[-112.358917,44.528847],[-112.3566,44.493127],[-112.358926,44.48628],[-112.368764,44.467153],[-112.387389,44.448058],[-112.435342,44.462216],[-112.460347,44.47571],[-112.473207,44.480027],[-112.50031,44.463051],[-112.511713,44.466445],[-112.512036,44.47042],[-112.518871,44.475784],[-112.541989,44.483971],[-112.550557,44.484928],[-112.573513,44.480983],[-112.584197,44.481368],[-112.601863,44.491015],[-112.660696,44.485756],[-112.664485,44.48645],[-112.671169,44.491265],[-112.707815,44.503023],[-112.71911,44.504344],[-112.735084,44.499159],[-112.749011,44.491233],[-112.781294,44.484888],[-112.797863,44.466112],[-112.828191,44.442472],[-112.836034,44.422653],[-112.821896,44.407436],[-112.812608,44.392275],[-112.81324,44.378103],[-112.820489,44.370946],[-112.844859,44.358221],[-112.855395,44.359975],[-112.881769,44.380315],[-112.886041,44.395874],[-112.915602,44.402699],[-112.951146,44.416699],[-112.981682,44.434279],[-113.003544,44.450814],[-113.020917,44.493827],[-113.018636,44.520064],[-113.019777,44.528505],[-113.032722,44.537137],[-113.04282,44.546757],[-113.042363,44.565237],[-113.061071,44.577329],[-113.083819,44.60222],[-113.07376,44.613928],[-113.065593,44.617391],[-113.05677,44.618657],[-113.053529,44.621187],[-113.049349,44.62938],[-113.051504,44.63695],[-113.065589,44.649371],[-113.068306,44.656374],[-113.07042,44.667844],[-113.067756,44.672807],[-113.06776,44.679474],[-113.081906,44.691392],[-113.098064,44.697477],[-113.101154,44.708578],[-113.102138,44.729027],[-113.116874,44.738104],[-113.134824,44.752763],[-113.137704,44.760109],[-113.131387,44.764738],[-113.131453,44.772837],[-113.140618,44.776698],[-113.158206,44.780847],[-113.163806,44.778921],[-113.179366,44.787142],[-113.183395,44.793565],[-113.19436,44.802151],[-113.209624,44.80907],[-113.238729,44.814144],[-113.247166,44.82295],[-113.278382,44.812706],[-113.29683,44.803358],[-113.301508,44.798985],[-113.341704,44.784853],[-113.354034,44.791745],[-113.354763,44.795468],[-113.346692,44.798898],[-113.3461,44.800611],[-113.356062,44.819798],[-113.377153,44.834858],[-113.383984,44.8374],[-113.422376,44.842595],[-113.455071,44.865424],[-113.474573,44.910846],[-113.491121,44.927548],[-113.498745,44.942314],[-113.494446,44.948597],[-113.480836,44.95031],[-113.474781,44.948795],[-113.467467,44.948061],[-113.448958,44.953544],[-113.443782,44.95989],[-113.444862,44.976141],[-113.447013,44.984637],[-113.446884,44.998545],[-113.437726,45.006967],[-113.449909,45.035167],[-113.44912,45.046098],[-113.45197,45.059247],[-113.460578,45.064879],[-113.465073,45.062755],[-113.47377,45.0617],[-113.485278,45.063519],[-113.520134,45.093033],[-113.510819,45.099902],[-113.506638,45.107288],[-113.513342,45.115225],[-113.538037,45.11503],[-113.546488,45.112285],[-113.554744,45.112901],[-113.57467,45.128411],[-113.594632,45.166034],[-113.589891,45.176986],[-113.599506,45.191114],[-113.636889,45.212983],[-113.647399,45.228282],[-113.650064,45.23471],[-113.657027,45.241436],[-113.665633,45.246265],[-113.674409,45.249411],[-113.678749,45.24927],[-113.684946,45.253706],[-113.692039,45.265191],[-113.691557,45.270912],[-113.688077,45.276407],[-113.689359,45.28355],[-113.735601,45.325265],[-113.738729,45.329741],[-113.7402,45.34559],[-113.73553,45.364738],[-113.73239,45.385058],[-113.733092,45.390173],[-113.734402,45.392353],[-113.750546,45.40272],[-113.760924,45.406501],[-113.765203,45.410601],[-113.768058,45.418147],[-113.763368,45.427732],[-113.764591,45.431403],[-113.783272,45.451839],[-113.78416,45.454946],[-113.759986,45.480735],[-113.766022,45.520621],[-113.778361,45.523415],[-113.796579,45.523462],[-113.802849,45.523159],[-113.809144,45.519908],[-113.834555,45.520729],[-113.819868,45.566326],[-113.804796,45.580358],[-113.803261,45.584193],[-113.802955,45.592631],[-113.806729,45.602146],[-113.823068,45.612486],[-113.861404,45.62366],[-113.886006,45.61702],[-113.904691,45.622007],[-113.902539,45.636945],[-113.898883,45.644167],[-113.900588,45.648259],[-113.903582,45.651165],[-113.919752,45.658536],[-113.930403,45.671878],[-113.93422,45.682232],[-113.971565,45.700636],[-113.986656,45.704564],[-114.015633,45.696127],[-114.019315,45.692937],[-114.020533,45.681223],[-114.02007,45.670332],[-114.013786,45.658238],[-114.014973,45.654008],[-114.018731,45.648616],[-114.033456,45.648629],[-114.067619,45.627706],[-114.08179,45.611329],[-114.083149,45.603996],[-114.0821,45.596958],[-114.086584,45.59118],[-114.100308,45.586354],[-114.122322,45.58426],[-114.131469,45.574444],[-114.132359,45.572531],[-114.128601,45.568996],[-114.129099,45.565491],[-114.135249,45.557465],[-114.154837,45.552916],[-114.180043,45.551432],[-114.18647,45.545539],[-114.192802,45.536596],[-114.203665,45.53557],[-114.227942,45.546423],[-114.248121,45.545877],[-114.251836,45.537812],[-114.248183,45.533226],[-114.247824,45.524283],[-114.261616,45.495816],[-114.270717,45.486116],[-114.279217,45.480616],[-114.333218,45.459316],[-114.345019,45.459916],[-114.360719,45.474116],[-114.36562,45.490416],[-114.36852,45.492716],[-114.388618,45.502903],[-114.415804,45.509753],[-114.438991,45.536076],[-114.450863,45.54253],[-114.456764,45.543983],[-114.460542,45.561283],[-114.473759,45.563278],[-114.498176,45.555473],[-114.506341,45.559216],[-114.517761,45.568129],[-114.526075,45.570771],[-114.549508,45.56059],[-114.559038,45.565706],[-114.558253,45.585104],[-114.553999,45.591279],[-114.538132,45.606834],[-114.544905,45.616673],[-114.553937,45.619299],[-114.563305,45.631612],[-114.563652,45.637412],[-114.561046,45.639906],[-114.53577,45.650613],[-114.529678,45.65232],[-114.522142,45.64934],[-114.507645,45.658949],[-114.499637,45.669035],[-114.495421,45.703321],[-114.497553,45.710677],[-114.504869,45.722176],[-114.535634,45.739095],[-114.566172,45.773864],[-114.562509,45.779927],[-114.555487,45.786249],[-114.544692,45.791447],[-114.512973,45.828825],[-114.51704,45.833148],[-114.517143,45.835993],[-114.514596,45.840785],[-114.509303,45.845531],[-114.498809,45.850676],[-114.470296,45.851343],[-114.455532,45.855012],[-114.44868,45.858891],[-114.422963,45.855381],[-114.409477,45.85164],[-114.388243,45.88234],[-114.387166,45.889164],[-114.395059,45.901458],[-114.404314,45.903497],[-114.413168,45.911479],[-114.431159,45.935737],[-114.431328,45.938023],[-114.427717,45.939625],[-114.423681,45.9441],[-114.415977,45.947891],[-114.411933,45.952358],[-114.404708,45.9559],[-114.402261,45.961489],[-114.403712,45.967049],[-114.409353,45.97141],[-114.411892,45.977883],[-114.419899,45.981106],[-114.425843,45.984984],[-114.470965,45.995742],[-114.47729,46.000802],[-114.477922,46.009025],[-114.473811,46.016614],[-114.480241,46.030325],[-114.485793,46.030022],[-114.490572,46.032427],[-114.493418,46.03717],[-114.494683,46.042546],[-114.492153,46.04729],[-114.468529,46.062484],[-114.461864,46.078571],[-114.460049,46.097104],[-114.474415,46.112515],[-114.488303,46.113106],[-114.5213,46.125287],[-114.527096,46.146218],[-114.514706,46.167726],[-114.489254,46.167684],[-114.478333,46.160876],[-114.472643,46.162202],[-114.457549,46.170231],[-114.445928,46.173933],[-114.443215,46.202943],[-114.445497,46.220227],[-114.449819,46.237119],[-114.451912,46.241253],[-114.468254,46.248796],[-114.470479,46.26732],[-114.465024,46.273127],[-114.453257,46.270939],[-114.441326,46.2738],[-114.43544,46.27661],[-114.427309,46.283624],[-114.425587,46.287899],[-114.433478,46.305502],[-114.431708,46.310744],[-114.413758,46.335945],[-114.410682,46.360673],[-114.411592,46.366688],[-114.422458,46.387097],[-114.408974,46.400438],[-114.384756,46.411784],[-114.376413,46.442983],[-114.379338,46.460166],[-114.383051,46.466402],[-114.394447,46.469549],[-114.400068,46.47718],[-114.403019,46.498675],[-114.400257,46.502143],[-114.395204,46.503148],[-114.385871,46.50437],[-114.375348,46.501855],[-114.35874,46.505306],[-114.351655,46.508119],[-114.342072,46.519679],[-114.349208,46.529514],[-114.348733,46.533792],[-114.34534,46.548444],[-114.339533,46.564039],[-114.33175,46.571914],[-114.331338,46.577781],[-114.333931,46.582732],[-114.334992,46.588154],[-114.333931,46.592162],[-114.322519,46.611066],[-114.322912,46.642938],[-114.320665,46.646963],[-114.32456,46.653579],[-114.332887,46.660756],[-114.360709,46.669059],[-114.394514,46.664846],[-114.403383,46.659633],[-114.410907,46.657466],[-114.424424,46.660648],[-114.453239,46.649266],[-114.45425,46.640974],[-114.466902,46.631695],[-114.486218,46.632829],[-114.498007,46.637655],[-114.547321,46.644485],[-114.561582,46.642043],[-114.583385,46.633227],[-114.593292,46.632848],[-114.615036,46.639733],[-114.616354,46.643646],[-114.611676,46.647704],[-114.614716,46.655256],[-114.621483,46.658143],[-114.635713,46.659375],[-114.642713,46.673145],[-114.641745,46.679286],[-114.631898,46.68397],[-114.623198,46.691511],[-114.620859,46.707415],[-114.626695,46.712889],[-114.632954,46.715495],[-114.649388,46.73289],[-114.696656,46.740572],[-114.699008,46.740223],[-114.710425,46.717704],[-114.713516,46.715138],[-114.727445,46.714604],[-114.740115,46.711771],[-114.747758,46.702649],[-114.749257,46.699688],[-114.751921,46.697207],[-114.76689,46.696901],[-114.787065,46.711255],[-114.788656,46.714033],[-114.779668,46.730411],[-114.773765,46.731805],[-114.76718,46.738828],[-114.765127,46.745383],[-114.765106,46.758153],[-114.79004,46.778729],[-114.808587,46.78235],[-114.818161,46.781139],[-114.829117,46.782503],[-114.835917,46.791111],[-114.844794,46.794305],[-114.856874,46.801633],[-114.860067,46.804988],[-114.861376,46.81196],[-114.864342,46.813858],[-114.880588,46.811791],[-114.888146,46.808573],[-114.897857,46.813184],[-114.904505,46.822851],[-114.920459,46.827697],[-114.927837,46.83599],[-114.92845,46.843242],[-114.92349,46.847594],[-114.928615,46.854815],[-114.940398,46.85605],[-114.947413,46.859324],[-114.943281,46.867971],[-114.938713,46.869021],[-114.931608,46.876799],[-114.931058,46.882108],[-114.936805,46.897378],[-114.935035,46.901749],[-114.927948,46.909948],[-114.927432,46.914185],[-114.929997,46.919625],[-114.960597,46.93001],[-114.986539,46.952099],[-115.00091,46.967703],[-115.001274,46.971901],[-115.028386,46.975659],[-115.028994,46.973159],[-115.031651,46.971548],[-115.047857,46.969533],[-115.049538,46.970774],[-115.057098,46.986758],[-115.066223,46.996375],[-115.071254,47.022083],[-115.087806,47.045519],[-115.098136,47.048897],[-115.102681,47.047239],[-115.107132,47.049041],[-115.120917,47.061237],[-115.136671,47.078276],[-115.139515,47.08456],[-115.140375,47.093013],[-115.170436,47.106265],[-115.172938,47.112881],[-115.189451,47.131032],[-115.200547,47.139154],[-115.223246,47.148974],[-115.243707,47.150347],[-115.255146,47.162876],[-115.255786,47.174725],[-115.261885,47.181742],[-115.286353,47.18327],[-115.300504,47.188139],[-115.300805,47.19393],[-115.295986,47.205658],[-115.29211,47.209861],[-115.294785,47.220914],[-115.298794,47.225245],[-115.307239,47.229892],[-115.311875,47.229673],[-115.317124,47.233305],[-115.324832,47.244841],[-115.326903,47.255912],[-115.339201,47.261623],[-115.3593,47.259461],[-115.36628,47.261485],[-115.371825,47.265213],[-115.410685,47.264228],[-115.421645,47.271736],[-115.423173,47.276222],[-115.428359,47.278722],[-115.443566,47.277309],[-115.457077,47.277794],[-115.470959,47.284873],[-115.487314,47.286518],[-115.51186,47.295219],[-115.526751,47.303219],[-115.531971,47.314121],[-115.548658,47.332213],[-115.551079,47.349856],[-115.556318,47.353076],[-115.564766,47.353476],[-115.570887,47.356375],[-115.578619,47.367007],[-115.609492,47.380799],[-115.617247,47.382521],[-115.639186,47.378605],[-115.644341,47.381826],[-115.648479,47.390293],[-115.657681,47.400651],[-115.69057,47.415059],[-115.71034,47.417784],[-115.718934,47.420967],[-115.72148,47.424469],[-115.728801,47.428925],[-115.731348,47.433381],[-115.728801,47.445159],[-115.718247,47.45316],[-115.69293,47.457237],[-115.671188,47.45439],[-115.663867,47.456936],[-115.654318,47.468077],[-115.653044,47.476035],[-115.655272,47.477944],[-115.686704,47.485596],[-115.694106,47.498634],[-115.708748,47.51264],[-115.71034,47.52951],[-115.717024,47.532693],[-115.741371,47.538645],[-115.747263,47.543197],[-115.748536,47.549245],[-115.746945,47.555293],[-115.734674,47.567401],[-115.721207,47.576323],[-115.706473,47.577299],[-115.689404,47.595402],[-115.694284,47.62346],[-115.708537,47.635356],[-115.715193,47.63634],[-115.72993,47.642442],[-115.73627,47.654762],[-115.726613,47.672093],[-115.72377,47.696671],[-115.730764,47.704426],[-115.752349,47.716743],[-115.758623,47.719041],[-115.763424,47.717313],[-115.77177,47.717412],[-115.776219,47.719818],[-115.783504,47.729305],[-115.780441,47.743447],[-115.797299,47.75752],[-115.803917,47.75848],[-115.824597,47.752154],[-115.831755,47.755785],[-115.835365,47.760957],[-115.835069,47.77006],[-115.837438,47.774846],[-115.84044,47.780172],[-115.847487,47.785227],[-115.848509,47.809331],[-115.845474,47.814967],[-115.852291,47.827991],[-115.870861,47.834939],[-115.875262,47.843272],[-115.881522,47.849672],[-115.900934,47.843064],[-115.906409,47.846261],[-115.919291,47.857406],[-115.939993,47.883153],[-115.959946,47.898142],[-115.965153,47.910131],[-115.969076,47.914256],[-115.982791,47.915994],[-115.993678,47.926183],[-115.995121,47.933827],[-115.998236,47.938779],[-116.007246,47.950087],[-116.030751,47.973349],[-116.03834,47.971318],[-116.04882,47.97716],[-116.049153,47.999923],[-116.048739,48.060093],[-116.04932,48.066644],[-116.049415,48.07722],[-116.048911,48.12493],[-116.049977,48.237604],[-116.049353,48.249936],[-116.049735,48.274668],[-116.048948,48.309847],[-116.050003,48.413492],[-116.049155,48.481247],[-116.049193,49.000912],[-116.00103,49.00127],[-115.990685,49.000909],[-115.501016,49.000694],[-115.207912,48.999228],[-114.375977,49.00139],[-114.250971,49.000905],[-114.224912,48.999687],[-114.201107,48.999249],[-114.180211,48.999703],[-114.059188,48.998856],[-113.907487,48.998858],[-113.864127,48.998276],[-113.692982,48.997632],[-113.576118,48.998478],[-113.375925,48.998562],[-113.356874,48.998224],[-113.19474,48.998909],[-113.116356,48.998462],[-112.143769,48.998917],[-112.003866,48.99857],[-112.000878,48.998921],[-111.761679,48.997614],[-111.500812,48.996963],[-111.003916,48.997537],[-110.592465,48.999012],[-110.531615,48.99839],[-110.438151,48.999188],[-109.500737,49.00044],[-109.454023,49.001132],[-109.437397,49.000631],[-109.384068,49.000374],[-109.285975,49.000479],[-109.250722,49.000011],[-109.000708,48.999234],[-107.704696,48.999872],[-107.441017,48.999363],[-107.363582,49.000019],[-106.050543,48.999207],[-105.612577,48.999703],[-104.875527,48.998991],[-104.048736,48.999877],[-104.0489,48.847387],[-104.047582,48.633984],[-104.048212,48.599055],[-104.047876,48.530798],[-104.047513,48.525913],[-104.048054,48.500025],[-104.047555,48.49414],[-104.046969,48.390675],[-104.046371,48.374154],[-104.046039,48.256761],[-104.045645,48.246179],[-104.044162,47.992836],[-104.041662,47.862282],[-104.043242,47.747106],[-104.043742,47.625016],[-104.044241,47.612288],[-104.043912,47.603229],[-104.044109,47.523595],[-104.045333,47.343452],[-104.045057,47.266868],[-104.045517,47.215666],[-104.044788,47.12743],[-104.045018,47.081202],[-104.045354,47.078574],[-104.045052,47.040863],[-104.045901,46.83079],[-104.045045,46.509788],[-104.046103,46.383916],[-104.045481,46.366871],[-104.045237,46.125002],[-104.045759,46.123946],[-104.046822,46.000199],[-104.04403,45.881975],[-104.042597,45.749998],[-104.041937,45.557915],[-104.041145,45.503367],[-104.041764,45.490789],[-104.040816,45.462708],[-104.040114,45.374214],[-104.039977,45.124988],[-104.039563,45.124039],[-104.040128,44.999987],[-104.039681,44.998041],[-104.057698,44.997431],[-104.250145,44.99822],[-104.665171,44.998618],[-104.72637,44.999518],[-104.759855,44.999066],[-105.038405,45.000345]]]},\"properties\":{\"name\":\"Montana\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: August 19, 2021; Version 1.1: September 20, 2021","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
We created this guide to introduce the user to the San Francisco Volcanic Field as a terrestrial analog site for planetary volcanic processes. For decades, the San Francisco Volcanic Field has been used to teach scientists to recognize the products of common types of volcanic eruptions and associated volcanic features. The volcanic processes and products observed in this volcanic field are like those observed on lunar and Martian surfaces. As a result, this region has been a favored location for training National Aeronautics and Space Administration astronauts and engineers since the Apollo missions.
Though the San Francisco Volcanic Field has more than 600 volcanic vents and flows, this guide will focus on S P Mountain (known locally as S P Crater, located ~30 miles north of Flagstaff, Arizona), one of the best preserved and most accessible of the volcanic cones and lava flows. S P Mountain presents both major types of basaltic eruptions—explosive and effusive—as well as some commonly associated tectonic landforms.
We assume that the user has a basic understanding of geologic concepts and terminology. For more specialized terminology, we include tables showing the classification scheme for lava compositions, styles of eruptions, and tephra sizes (tables 1, 2, and 3). If a further introduction or refresher in volcanological terminology is desired, we suggest reviewing such terms on the U.S. Geological Survey Volcano Science Center’s online glossary (https://volcanoes.usgs.gov/vsc/glossary/).
One term requires clarification at the start of this guide—the term cinder. The terms cinder and cinder cone are widely used to describe the material and edifice produced by lava fountains. However, the term comes from the mining and construction industries and has no clear or formal definition. The international committees in geology and volcanology have chosen the term tephra to be the general term to describe pyroclasts (material ejected through a volcanic explosion or from a volcanic vent). Therefore, in this guide, we use the term tephra rather than cinder.
This guide is outlined as follows:
Contact Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
The Little Colorado River is a major tributary to the Colorado River with a confluence at the boundary between Marble and Grand Canyons within Grand Canyon National Park, Arizona. The bedrock gorge of the lower Little Colorado River is home to the largest known population of Gila cypha (humpback chub), an endangered fish endemic to the Colorado River Basin. Channel conditions might affect the spawning success of the humpback chub. Perennial base flow in the lower Little Colorado River deposits travertine, which forms dams and cascades. Geomorphic change in the lower Little Colorado River is controlled by the growth and collapse of travertine dams, debris flows from tributaries, and reworking of dams and debris fans by Little Colorado River floods.
A study was conducted by the U.S. Geological Survey, in cooperation with the Glen Canyon Dam Adaptive Management Program and the U.S. Fish and Wildlife Service, to document historical floods and geomorphic change in the lower Little Colorado River. For this study, we used historical and gaging records and hydraulic modeling of surveyed high-water marks from historical Little Colorado River floods to construct a peak-flow history of the lower Little Colorado River. We analyzed base-flow longitudinal profiles and historical photographs to determine changes in the longitudinal profile of the lower Little Colorado River from 1909 to 2019. The peak-flow magnitudes and the frequency of larger floods have declined since the late 1800s, and the longitudinal profile of the Little Colorado River has substantially changed between 1909 and 2019. Aggradation of as much as 6 meters in some reaches occurred between 1926 and 1992, mostly before the 1950s. This aggradation was caused largely by the documented growth of travertine dams continuing through at least 2013 at several locations. Other reaches were incised by as much as 10 meters between 1926 and 1992, but mostly before the 1950s, largely from the breaching of travertine dams. Travertine dams in the Little Colorado River have survived large flooding events and then later collapsed during floods of lower streamflow or even periods of base flow. The decline in peak-flow magnitude and frequency has changed the dominant geomorphic processes in this formerly dynamic reach. Large incision events have not been documented since the early 1950s; for this reason, the reach has only aggraded or remained stable since that time. This loss of geomorphic disturbance has likely affected, and will likely continue to affect, the spawning habitat of the endangered humpback chub in the lower Little Colorado River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215049","usgsCitation":"Unema, J.A., Topping, D.J., Kohl, K.A., Pillow, M.J., and Caster, J.J., 2021, Historical floods and geomorphic change in the lower Little Colorado River during the late 19th to early 21st centuries: U.S. Geological Survey Scientific Investigations Report 2021–5049, 34 p., https://doi.org/10.3133/sir20215049.","productDescription":"Report: vii, 34 p.; Data Release","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-113057","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":388147,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5049/covrthb.jpg"},{"id":388148,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5049/sir20215049.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":388149,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VGWRV1","linkHelpText":"Topographic data, historical peak-stage data, and 2D flow models for the lowermost Little Colorado River, Arizona, USA, 2017"}],"country":"United States","state":"Arizona, Utah, New Mexico, Utah","otherGeospatial":"Lower Little Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.236328125,\n 33.247875947924385\n ],\n [\n -107.666015625,\n 33.247875947924385\n ],\n [\n -107.666015625,\n 37.33522435930639\n ],\n [\n -112.236328125,\n 37.33522435930639\n ],\n [\n -112.236328125,\n 33.247875947924385\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
The U.S. Geological Survey, with the support of the International Joint Commission, and in cooperation with Alberta Environment and Parks, Blackfeet Nation, Environment and Climate Change Canada, and Montana Department of Natural Resources and Conservation, is leading a project that should improve information available to apportion water between Canada and the United States in the St. Mary and Milk River Basins. One component of the water budget, consumptive use of irrigation water (the amount of supplemental water used by crops), can be estimated at 100-meter resolution almost every week using imagery recorded by satellites from 1985 to present (2021) and weather data, when conditions permit. Better estimates of consumptive water use should improve understanding of water availability and use in the basin and should assist with water apportionment procedures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213042","collaboration":"Prepared in cooperation with Alberta Environment and Parks, Blackfeet Nation, Environment and Climate Change Canada, and Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, R., Friedrichs, M., and Senay, G.B., 2021, Using satellite imagery to estimate consumptive water use from irrigated lands in the Milk River Basin, United States and Canada: U.S. Geological Survey Fact Sheet 2021–3042, 2 p., https://doi.org/10.3133/fs20213042.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-130575","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":388101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3042/coverthb.jpg"},{"id":388102,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3042/fs20213042.pdf","text":"Report","size":"11.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"fs 2021–3042"}],"country":"Canada, United States","state":"Alberta, Montana, Saskatchewan","otherGeospatial":"Milk River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.851318359375,\n 48.07807894349862\n ],\n [\n -106.424560546875,\n 48.07807894349862\n ],\n [\n -106.424560546875,\n 49.7173764049358\n ],\n [\n -113.851318359375,\n 49.7173764049358\n ],\n [\n -113.851318359375,\n 48.07807894349862\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Along the coast of the U.S. Gulf of Mexico, the eastern oyster (Crassostrea virginica) plays important ecological and economic roles. Commercial landings from this region account for more than 50 percent of all U.S. landings; these oyster reefs also provide varied ecosystem services, including nursery habitat for many fish and macroinvertebrate species, shoreline protection, and water-quality maintenance. Declining trends in both total oyster production and functional reef area across this region have spurred investment in restoration of oyster resources, with specific calls for restoration projects to develop a network of reefs and identify broodstock and sanctuary reef restoration sites. Decision making related to restoration and establishment of a network of oyster reefs in the Gulf of Mexico requires information on both the environment and the effects of the environment on the oyster life cycle (including larval movement, survival, oyster recruitment, reproduction, growth, and mortality). Here, we examined the current state of data and model development in this region with the goal of providing an overview of oyster modeling approaches and an inventory of available data and existing oyster models. This report is meant to provide an overview to managers for understanding existing efforts and identify a path forward to most efficiently inform oyster resource management and restoration planning in moving from a single reef management approach to a reef network management approach.
Numerous models related to some aspect of the oyster life cycle have been built, calibrated, and validated for various Gulf of Mexico estuaries over the last few decades (over 30 models identified). These models, which could inform site restoration, can be classified into four approaches: (1) oyster Habitat Suitability Index (HSI) models; (2) larval transport models; (3) on-reef oyster models that may include oyster growth, mortality and reproduction, and substrate persistence; and (4) coupled larval transport on-reef metapopulation models that simulate the entire oyster life cycle. The data requirements, model complexity and assumptions, and transferability vary by approach. Specifically, some approaches may offer greater accessibility, flexibility, and transferability spatially or temporally, with minimal data input, but only provide broad information to support site selection. In contrast, other approaches may require significant site-specific data for their construction and validation but may provide more accurate and location-specific data to support site selection for broodstock reefs.
Regardless of modeling approach used, data on environmental drivers, such as salinity, water temperature, or water flow impacting oyster metabolism and movement, are required at appropriate spatial and temporal scales. While numerous data collection platforms, environmental models, and research products exist within Gulf of Mexico estuaries to provide important environmental data to use as drivers in the oyster models, significant variability in temporal and spatial coverage of the data, and variation in the availability of future condition models, exists across estuaries. This variation influences the spatial and temporal scales at which oyster models may be developed and impacts the calibration and validation of the oyster models within a given estuary, affecting its potential ability to address specific management or restoration questions.
While multiple modeling approaches exist for informing site selection of broodstock or sanctuary oyster reefs, the development, calibration, and validation of a single modeling platform presents the most efficient, transferable, and useful tool for managers across the Gulf of Mexico. The development of a single modeling platform would involve using standardized input variables, governing equations, and assumptions for the modeled oyster processes and outputs, and for standardized calibration and validation procedures that could be applied within each estuary. The differences among estuary applications would require substituting only estuary-specific environmental data, and calibrating and validating the modeling approach with local oyster data.
Two modeling approaches likely to be useful include (1) development of a general geospatial HSI modeling framework that could be applied consistently across estuaries and (2) a mechanistic coupled larval transport on-reef metapopulation model requiring only estuarine specific calibration and hydrodynamic models. Both approaches benefit from existing work across multiple Gulf of Mexico estuaries and could provide valuable support for oyster restoration, but may differ in their ability to address specific questions related to oyster restoration. HSI models specifically guide restoration practitioners in determining suitable habitat based on available data. The HSI approach, while currently more widely used and accessible, requires more development of larval suitability and larval input and output components in order to inform reef connectivity. A metapopulation approach considering the full oyster life cycle that simulates both on-reef oyster growth, mortality, reproduction, substrate persistence, and larval transport (ideally with larval growth and mortality) would provide the greatest detail and level of understanding but requires significant up-front investment. The larval oyster model and on-reef oyster model are usually developed independently for systems, although the two approaches can be coupled to represent the entire oyster life cycle in order to characterize and assess a reef metapopulation. This approach may be less accessible and much more data-intensive, however, and it requires some expertise to run and apply to inform oyster resource management.
Ultimately, the development of single modeling platforms for each of these approaches would provide flexible tools applicable across all Gulf of Mexico oyster supporting estuaries. By using a single platform for model development, testing, calibrating and validating, and evaluation of modeled future scenarios, oyster restoration scientists and managers would not only be able to examine different scenario outcomes within a single estuary, but could also have comparable modeled results to evaluate potential outcomes, across estuaries and regions, that are not confounded by varying modeled data inputs, governing equations, assumptions, or user judgement.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211063","usgsCitation":"La Peyre, M.K., Marshall, D.A., and Sable, S.E., 2021, Oyster model inventory: Identifying critical data and modeling approaches to support restoration of oyster reefs in coastal U.S. Gulf of Mexico waters: U.S. Geological Survey\nOpen-File Report 2021–1063, 40 p., https://doi.org/10.3133/ofr20211063.","productDescription":"Report: viii, 40p.; 3 Appendix Tables","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-126014","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":388074,"rank":9,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1063/images"},{"id":388041,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1063/coverthb.jpg"},{"id":388042,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1063/ofr20211063.pdf","text":"Report","size":"37.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1063"},{"id":388043,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1063/ofr20211063_table_1.1.csv","text":"Table 1.1 (.csv)","size":"5.07 kB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2021–1063 Table 1.1","linkHelpText":"— Discrete water-quality data sources"},{"id":388044,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1063/ofr20211063_table_2.1.csv","text":"Table 2.1 (.csv)","size":"5.40 kB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2021–1063 Table 2.1","linkHelpText":"— Modeled water quality and physical data sources"},{"id":388045,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1063/ofr20211063_table_3.1.csv","text":"Table 3.1 (.csv)","size":"63.8 kB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2021–1063 Table 3.1","linkHelpText":"— Oyster model inventory"},{"id":388046,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1063/ofr20211063_table_1.1.xlsx","text":"Table 1.1 (.xlsx)","size":"14.8 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2021–1063 Table 1.1","linkHelpText":"— Discrete water-quality data sources"},{"id":388047,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1063/ofr20211063_table_2.1.xlsx","text":"Table 2.1 (.xlsx)","size":"13.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2021–1063 Table 2.1","linkHelpText":"— Modeled water quality and physical data sources"},{"id":388048,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1063/ofr20211063_table_3.1.xlsx","text":"Table 3.1 (.xlsx)","size":"46.9 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2021–1063 Table 3.1","linkHelpText":"— Oyster model inventory"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.177734375,\n 27.527758206861886\n ],\n [\n -82.6171875,\n 29.267232865200878\n ],\n [\n -83.8916015625,\n 30.372875188118016\n ],\n [\n -85.078125,\n 30.259067203213018\n ],\n [\n -86.7919921875,\n 30.826780904779774\n ],\n [\n -88.681640625,\n 30.675715404167743\n ],\n [\n -90.263671875,\n 30.486550842588485\n ],\n [\n -90.3076171875,\n 29.649868677972304\n ],\n [\n -91.62597656249999,\n 30.14512718337613\n ],\n [\n -94.3505859375,\n 29.916852233070173\n ],\n [\n -96.45996093749999,\n 29.036960648558267\n ],\n [\n -97.470703125,\n 27.800209937418252\n ],\n [\n -97.734375,\n 26.78484736105119\n ],\n [\n -97.0751953125,\n 25.918526162075153\n ],\n [\n -96.767578125,\n 27.01998400798257\n ],\n [\n -96.0205078125,\n 28.34306490482549\n ],\n [\n -94.39453125,\n 29.075375179558346\n ],\n [\n -92.94433593749999,\n 29.34387539941801\n ],\n [\n -92.2412109375,\n 29.075375179558346\n ],\n [\n -90.9228515625,\n 28.806173508854776\n ],\n [\n -89.033203125,\n 28.613459424004414\n ],\n [\n -88.59374999999999,\n 29.267232865200878\n ],\n [\n -88.9013671875,\n 29.916852233070173\n ],\n [\n -87.4951171875,\n 29.80251790576445\n ],\n [\n -86.17675781249999,\n 29.99300228455108\n ],\n [\n -85.341796875,\n 29.19053283229458\n ],\n [\n -84.0673828125,\n 29.57345707301757\n ],\n [\n -83.4521484375,\n 28.998531814051795\n ],\n [\n -83.3642578125,\n 27.72243591897343\n ],\n [\n -82.4853515625,\n 26.667095801104814\n ],\n [\n -82.177734375,\n 27.527758206861886\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, Cooperative Fish and Wildlife Research Units
U.S. Geological Survey
MS 303
12201 Sunrise Valley Drive
Reston, VA 20192
Recreational angling in the United States (US) is largely a personal hobby that scales up to a multibillion-dollar economic activity. Given dramatic changes to personal decisions and behaviors resulting from the COVID-19 pandemic, we surveyed recreational anglers across the US to understand how the pandemic may have affected their fishing motivations and subsequent activities. Nearly a quarter million anglers from 10 US states were invited to participate in the survey, and almost 18,000 responded. Anglers reported numerous effects of the pandemic, including fishing access restrictions. Despite these barriers, we found that the amount of fishing in the spring of 2020 was significantly greater—by about 0.2 trips per angler—than in non-pandemic springs. Increased fishing is likely associated with our result that most respondents considered recreational angling to be a COVID-19 safe activity. Nearly a third of anglers reported changing their motivation for fishing during the pandemic, with stress relief being more popular during the pandemic than before. Driven partly by the perceived safety of social fishtancing, recreational angling remained a popular activity for many US anglers during spring 2020.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0254652","usgsCitation":"Midway, S.R., Lynch, A.J., Peoples, B.K., Dance, M.A., and Caffey, R., 2021, COVID-19 influences on US recreational angler behavior: PLoS ONE, v. 16, no. 8, https://doi.org/10.1371/journal.pone.0254652.","productDescription":"e0254652, 16 p.","startPage":"e0254652","ipdsId":"IP-125141","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":451125,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0254652","text":"Publisher Index Page"},{"id":388585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.67138671875,\n 54.686534234529695\n ],\n [\n -129.9462890625,\n 55.36662484928637\n ],\n [\n -130.1220703125,\n 56.145549500679074\n ],\n [\n -131.9677734375,\n 56.9449741808516\n ],\n [\n -135.3076171875,\n 59.833775202184206\n ],\n [\n -136.38427734375,\n 59.65664225341022\n ],\n [\n -136.6259765625,\n 59.23217626921806\n ],\n [\n -137.52685546875,\n 58.938673187948304\n ],\n [\n -137.65869140625,\n 59.33318942659219\n ],\n [\n -138.8232421875,\n 60.009970961180386\n ],\n [\n -139.21874999999997,\n 60.108670463036\n ],\n [\n -139.04296875,\n 60.403001945865476\n ],\n [\n -139.85595703125,\n 60.337823495982015\n ],\n [\n -140.99853515625,\n 60.337823495982015\n ],\n [\n -141.15234374999997,\n 69.71810669906763\n ],\n [\n -143.4375,\n 70.17020068549206\n ],\n [\n -145.1953125,\n 70.08056215839737\n ],\n [\n -149.765625,\n 70.58341752317065\n ],\n [\n -152.40234375,\n 70.61261423801925\n ],\n [\n -152.314453125,\n 70.95969716686398\n ],\n [\n -157.1484375,\n 71.35706654962706\n ],\n [\n -159.9609375,\n 70.8734913192635\n ],\n [\n -162.0703125,\n 70.31873847853124\n ],\n [\n -163.916015625,\n 69.06856318696033\n ],\n [\n -166.376953125,\n 68.942606818121\n ],\n [\n -166.376953125,\n 68.26938680456564\n ],\n [\n -163.30078125,\n 66.86108230224609\n ],\n [\n -161.982421875,\n 66.47820814385636\n ],\n [\n -163.564453125,\n 66.08936427047088\n ],\n [\n -163.564453125,\n 66.6181218846659\n ],\n [\n -165.76171875,\n 66.40795547978848\n ],\n [\n -168.0908203125,\n 65.69447579373418\n ],\n [\n -166.55273437499997,\n 65.14611484756372\n ],\n [\n -166.904296875,\n 65.05360170595502\n ],\n [\n -166.3330078125,\n 64.41592147626879\n ],\n [\n -162.861328125,\n 64.39693778132846\n ],\n [\n -160.927734375,\n 64.90491004905083\n ],\n [\n -161.0595703125,\n 64.47279382008166\n ],\n [\n -161.4990234375,\n 64.49172504435471\n ],\n [\n -160.8837890625,\n 63.87939001720202\n ],\n [\n -161.1474609375,\n 63.470144746565424\n ],\n [\n -162.6416015625,\n 63.64625919492172\n ],\n [\n -163.212890625,\n 63.05495931065107\n ],\n [\n -164.2236328125,\n 63.37183226679281\n ],\n [\n -166.1572265625,\n 61.75233128411639\n ],\n [\n -165.3662109375,\n 60.54377524118842\n ],\n [\n -167.431640625,\n 60.326947742998414\n ],\n [\n -167.255859375,\n 59.866883195210214\n ],\n [\n -165.8935546875,\n 59.7563950493563\n ],\n [\n -162.68554687499997,\n 59.734253447591364\n ],\n [\n -162.3779296875,\n 60.174306261926034\n ],\n [\n -161.806640625,\n 59.46740794183739\n ],\n [\n -162.0263671875,\n 59.108308258604964\n ],\n [\n -161.806640625,\n 58.768200159239576\n ],\n [\n -162.20214843749997,\n 58.65408464530598\n ],\n [\n -160.83984375,\n 58.44773280389084\n ],\n [\n -159.9609375,\n 58.6769376725869\n ],\n [\n -159.08203125,\n 58.309488840677645\n ],\n [\n -156.88476562499997,\n 58.92733441827545\n ],\n [\n -157.5,\n 58.516651799363785\n ],\n [\n -157.8076171875,\n 57.61010702068388\n ],\n [\n -161.54296875,\n 56.022948079627454\n ],\n [\n -168.6181640625,\n 53.4357192066942\n ],\n [\n -174.9462890625,\n 52.26815737376817\n ],\n [\n -178.2421875,\n 51.83577752045248\n ],\n [\n -173.1884765625,\n 51.590722643120145\n ],\n [\n -162.5537109375,\n 54.23955053156177\n ],\n [\n -155.302734375,\n 55.52863052257191\n ],\n [\n -151.4794921875,\n 57.51582286553883\n ],\n [\n -146.9970703125,\n 60.08676274626006\n ],\n [\n -145.546875,\n 60.21799073323445\n ],\n [\n -144.228515625,\n 59.689926220143356\n ],\n [\n -142.3828125,\n 59.93300042374631\n ],\n [\n -138.3837890625,\n 58.83649009392136\n ],\n [\n -135.6591796875,\n 56.31653672211301\n ],\n [\n -133.2421875,\n 54.521081495443596\n ],\n [\n -130.67138671875,\n 54.686534234529695\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.796875,\n 44.902577996288876\n ],\n [\n -67.67578124999999,\n 45.583289756006316\n ],\n [\n -67.939453125,\n 47.57652571374621\n ],\n [\n -69.2578125,\n 47.338822694822\n ],\n [\n -71.19140625,\n 45.27488643704891\n ],\n [\n -75.146484375,\n 44.96479793033101\n ],\n [\n -78.046875,\n 43.644025847699496\n ],\n [\n -79.1015625,\n 43.51668853502906\n ],\n [\n -79.1015625,\n 42.87596410238256\n ],\n [\n -82.68310546875,\n 41.65649719441145\n ],\n [\n -83.14453125,\n 42.049292638686836\n ],\n [\n -83.07861328125,\n 42.374778361114195\n ],\n [\n -82.529296875,\n 42.601619944327965\n ],\n [\n -82.24365234375,\n 43.6599240747891\n ],\n [\n -82.41943359375,\n 45.058001435398275\n ],\n [\n -83.60595703125,\n 45.85941212790755\n ],\n [\n -83.49609375,\n 46.027481852486645\n ],\n [\n -83.7158203125,\n 46.164614496897094\n ],\n [\n -83.95751953125,\n 46.07323062540835\n ],\n [\n -84.24316406249999,\n 46.558860303117164\n ],\n [\n -84.72656249999999,\n 46.558860303117164\n ],\n [\n -84.90234375,\n 46.92025531537451\n ],\n [\n -88.41796875,\n 48.3416461723746\n ],\n [\n -89.3408203125,\n 47.96050238891509\n ],\n [\n -90.76904296874999,\n 48.122101028190805\n ],\n [\n -90.87890625,\n 48.22467264956519\n ],\n [\n -91.51611328125,\n 48.10743118848039\n ],\n [\n -92.2412109375,\n 48.37084770238366\n ],\n [\n -92.39501953125,\n 48.23930899024907\n ],\n [\n -92.94433593749999,\n 48.61838518688487\n ],\n [\n -93.44970703125,\n 48.63290858589535\n ],\n [\n -94.7021484375,\n 48.748945343432936\n ],\n [\n -94.833984375,\n 49.23912083246698\n ],\n [\n -95.1416015625,\n 49.396675075193976\n ],\n [\n -95.20751953125,\n 49.009050809382046\n ],\n [\n -123.22265625000001,\n 48.99463598353405\n ],\n [\n -123.0908203125,\n 48.80686346108517\n ],\n [\n -123.24462890625,\n 48.66194284607006\n ],\n [\n -123.1787109375,\n 48.32703913063476\n ],\n [\n -124.78271484375,\n 48.472921272487824\n ],\n [\n -124.93652343749999,\n 48.16608541901253\n ],\n [\n -124.365234375,\n 46.58906908309182\n ],\n [\n -124.541015625,\n 44.15068115978094\n ],\n [\n -124.93652343749999,\n 42.69858589169842\n ],\n [\n -124.541015625,\n 41.22824901518529\n ],\n [\n -124.73876953125,\n 40.43022363450862\n ],\n [\n -124.03564453125,\n 39.35129035526705\n ],\n [\n -124.01367187499999,\n 38.8225909761771\n ],\n [\n -122.05810546875,\n 36.12012758978146\n ],\n [\n -120.95947265624999,\n 34.88593094075317\n ],\n [\n -120.80566406250001,\n 34.08906131584994\n ],\n [\n -118.21289062499999,\n 32.2313896627376\n ],\n [\n -117.22412109375,\n 32.54681317351514\n ],\n [\n -114.78515624999999,\n 32.713355353177555\n ],\n [\n -114.78515624999999,\n 32.491230287947594\n ],\n [\n -110.98388671874999,\n 31.3348710339506\n ],\n [\n -108.21533203125,\n 31.297327991404266\n ],\n [\n -108.2373046875,\n 31.765537409484374\n ],\n [\n -106.435546875,\n 31.765537409484374\n ],\n [\n -104.9853515625,\n 30.600093873550072\n ],\n [\n -104.47998046875,\n 29.592565403314087\n ],\n [\n -103.20556640625,\n 28.94086176940557\n ],\n [\n -102.65625,\n 29.76437737516313\n ],\n [\n -102.3486328125,\n 29.84064389983441\n ],\n [\n -101.49169921875,\n 29.7453016622136\n ],\n [\n -100.83251953125,\n 29.267232865200878\n ],\n [\n -100.30517578125,\n 28.246327971048842\n ],\n [\n -99.60205078124999,\n 27.586197857692664\n ],\n [\n -99.47021484375,\n 27.31321389856826\n ],\n [\n -99.228515625,\n 26.52956523826758\n ],\n [\n -98.2177734375,\n 26.05678288577881\n ],\n [\n -97.75634765625,\n 26.03704188651584\n ],\n [\n -97.44873046875,\n 25.839449402063185\n ],\n [\n -97.20703125,\n 25.93828707492375\n ],\n [\n -96.8994140625,\n 26.194876675795218\n ],\n [\n -96.78955078125,\n 27.858503954841247\n ],\n [\n -93.75732421875,\n 29.420460341013133\n ],\n [\n -90.2197265625,\n 28.998531814051795\n ],\n [\n -88.22021484375,\n 29.05616970274342\n ],\n [\n -87.91259765625,\n 30.14512718337613\n ],\n [\n -86.5283203125,\n 30.183121842195515\n ],\n [\n -85.2978515625,\n 29.49698759653577\n ],\n [\n -84.13330078125,\n 29.80251790576445\n ],\n [\n -82.81494140625,\n 28.555576049185973\n ],\n [\n -83.21044921875,\n 27.800209937418252\n ],\n [\n -82.77099609375,\n 26.941659545381516\n ],\n [\n -82.08984375,\n 25.878994400196202\n ],\n [\n -81.5625,\n 25.264568475331583\n ],\n [\n -82.28759765625,\n 24.467150664739002\n ],\n [\n -82.0458984375,\n 24.046463999666567\n ],\n [\n -80.6396484375,\n 24.56710835257599\n ],\n [\n -79.78271484375,\n 25.34402602913433\n ],\n [\n -79.60693359375,\n 27.27416111737468\n ],\n [\n -80.68359375,\n 30.713503990354965\n ],\n [\n -80.66162109375,\n 31.50362930577303\n ],\n [\n -76.81640625,\n 34.07086232376631\n ],\n [\n -75.16845703124999,\n 35.263561862152095\n ],\n [\n -75.498046875,\n 37.055177106660814\n ],\n [\n -73.58642578125,\n 39.90973623453719\n ],\n [\n -71.3671875,\n 40.84706035607122\n ],\n [\n -69.63134765625,\n 40.9964840143779\n ],\n [\n -70.0048828125,\n 42.342305278572816\n ],\n [\n -70.3564453125,\n 42.89206418807337\n ],\n [\n -67.2802734375,\n 44.37098696297173\n ],\n [\n -67.0166015625,\n 44.69989765840318\n ],\n [\n -66.796875,\n 44.902577996288876\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.2308349609375,\n 17.96305758238804\n ],\n [\n -67.2198486328125,\n 17.910795834978483\n ],\n [\n -66.5716552734375,\n 17.866361230891894\n ],\n [\n -66.16790771484375,\n 17.90556881196468\n ],\n [\n -65.85205078125,\n 17.973508079068797\n ],\n [\n -65.7861328125,\n 18.04142122189195\n ],\n [\n -65.50323486328125,\n 18.06231230454674\n ],\n [\n -65.2587890625,\n 18.114529138838503\n ],\n [\n -65.269775390625,\n 18.15629140283545\n ],\n [\n -65.4400634765625,\n 18.18238775108558\n ],\n [\n -65.51422119140625,\n 18.14324176648384\n ],\n [\n -65.5609130859375,\n 18.40665471391907\n ],\n [\n -65.64880371093749,\n 18.404048629104647\n ],\n [\n -65.77789306640625,\n 18.417078658661257\n ],\n [\n -65.9124755859375,\n 18.46918890441719\n ],\n [\n -66.24755859375,\n 18.510865709091377\n ],\n [\n -66.4837646484375,\n 18.503052080569763\n ],\n [\n -66.98638916015625,\n 18.51347017266187\n ],\n [\n -67.115478515625,\n 18.534304453676864\n ],\n [\n -67.181396484375,\n 18.48742375381096\n ],\n [\n -67.16217041015625,\n 18.432713391700858\n ],\n [\n -67.2637939453125,\n 18.375379094031825\n ],\n [\n -67.19238281249999,\n 18.2397859708389\n ],\n [\n -67.2308349609375,\n 17.96305758238804\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Midway, Stephen R.","contributorId":172159,"corporation":false,"usgs":false,"family":"Midway","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":822089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":204271,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":822090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peoples, Brandon K.","contributorId":177551,"corporation":false,"usgs":false,"family":"Peoples","given":"Brandon","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":822091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dance, Michael A.","contributorId":213049,"corporation":false,"usgs":false,"family":"Dance","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":822092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caffey, Rex","contributorId":264849,"corporation":false,"usgs":false,"family":"Caffey","given":"Rex","email":"","affiliations":[{"id":54570,"text":"Louisiana State U.","active":true,"usgs":false}],"preferred":false,"id":822093,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225617,"text":"70225617 - 2021 - Comparative effects of energy-related saline wastewaters and sodium chloride on hatching, survival, and fitness-associated traits of two amphibian species","interactions":[],"lastModifiedDate":"2021-10-28T13:38:24.352676","indexId":"70225617","displayToPublicDate":"2021-08-18T08:24:03","publicationYear":"2021","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":"Comparative effects of energy-related saline wastewaters and sodium chloride on hatching, survival, and fitness-associated traits of two amphibian species","docAbstract":"Salinity (sodium chloride [NaCl]) is a prevalent and persistent contaminant that negatively affects freshwater ecosystems. Although most studies focus on effects of salinity from road salts (primarily NaCl), high-salinity wastewaters from energy extraction (wastewaters) could be more harmful because they contain NaCl and other toxic components. Many amphibians are sensitive to salinity, and their eggs are thought to be the most sensitive life-history stage. However, there are few investigations with salinity that include eggs and larvae sequentially in long-term exposures. We investigated the relative effects of wastewaters from a large energy reserve, the Williston Basin (USA), and NaCl on northern leopard (Rana pipiens) and boreal chorus (Pseudacris maculata) frogs. We exposed eggs and tracked responses through larval stages (for 24 days). Wastewaters and NaCl caused similar reductions in hatching and larval survival, growth, development, and activity, while also increasing deformities. Chorus frog eggs and larvae were more sensitive to salinity than leopard frogs, suggesting species-specific responses. Contrary to previous studies, eggs of both species were less sensitive to salinity than larvae. Our ecologically relevant exposures suggest that accumulating effects can reduce survival relative to starting experiments with unexposed larvae. Alternatively, egg casings of some species may provide some protection against salinity. Notably, effects of wastewaters on amphibians were predominantly due to NaCl rather than other components. Therefore, findings from studies with other sources of increased salinity (e.g., road salts) could guide management of wastewater-contaminated ecosystems, and vice versa, to mitigate effects of salinization.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.5193","usgsCitation":"Tornabene, B., Breuner, C., and Hossack, B., 2021, Comparative effects of energy-related saline wastewaters and sodium chloride on hatching, survival, and fitness-associated traits of two amphibian species: Environmental Science & Technology, v. 40, no. 11, p. 3137-3147, https://doi.org/10.1002/etc.5193.","productDescription":"11 p.","startPage":"3137","endPage":"3147","ipdsId":"IP-129251","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":391083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","city":"Dagmar, Moran","otherGeospatial":"Pary Waterfowl Production Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.600830078125,\n 48.29781249243716\n ],\n [\n -104.04739379882812,\n 48.29781249243716\n ],\n [\n -104.04739379882812,\n 48.67101262432597\n ],\n [\n -104.600830078125,\n 48.67101262432597\n ],\n [\n -104.600830078125,\n 48.29781249243716\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.58151245117188,\n 43.717519867330765\n ],\n [\n -110.32882690429688,\n 43.717519867330765\n ],\n [\n -110.32882690429688,\n 43.89591323557617\n ],\n [\n -110.58151245117188,\n 43.89591323557617\n ],\n [\n -110.58151245117188,\n 43.717519867330765\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Tornabene, Brian J.","contributorId":200041,"corporation":false,"usgs":false,"family":"Tornabene","given":"Brian J.","affiliations":[],"preferred":false,"id":825937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breuner, Creagh","contributorId":268148,"corporation":false,"usgs":false,"family":"Breuner","given":"Creagh","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":825938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":825939,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223506,"text":"70223506 - 2021 - Genetic sequencing of Attwater's prairie chicken avian poxvirus and evaluation of its potential role in reticuloendotheliosis virus outbreaks","interactions":[],"lastModifiedDate":"2021-08-31T13:19:42.87042","indexId":"70223506","displayToPublicDate":"2021-08-18T08:15:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":948,"text":"Avian Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Genetic sequencing of Attwater's prairie chicken avian poxvirus and evaluation of its potential role in reticuloendotheliosis virus outbreaks","docAbstract":"Efforts to breed Attwater's prairie chickens (APC; Tympanuchus cupido attwateri) in captivity to supplement wild populations of this endangered bird have been negatively affected by infections with Avipoxvirus and reticuloendotheliosis virus (REV). Because REV can be integrated into the genome of fowlpox virus (FPV) and may be transmitted in that manner, identifying the source of avipox disease in APC is important to mitigate the impact of this virus. Tissue samples from APC were collected from breeding programs in Texas from 2016 to 2020. These samples consisted of 11 skin lesions and three internal organs from a total of 14 different birds that died of unknown causes or were euthanized. Avipoxvirus was detected by PCR and isolation in embryonating chicken eggs in all skin lesion samples but was not detected in internal organs. Using sequence analysis of FPV polymerase and 4b genes, we determined that 10 out of 11 Avipoxvirus detections resided within the fowlpox clade and a single sample resided within the canarypox clade. REV sequences were detected in all FPV positive samples and in all internal organ tissues but were not detected in the sample matching the canarypox clade. Analysis of REV sequences and PCR detection showed the REV infecting APC was consistent with REV-A and had little variability on analysis of the U3 region of the long terminal repeat. The results of this study indicate control of REV in APC breeding colonies may benefit by a vaccination program targeting FPV and REV. However, a commercially available vaccine for REV is not available at this time.
Throughout a 20 year biosurveillance period, viral hemorrhagic septicemia virus was isolated in low titers from only 6/7355 opportunistically sampled adult Pacific herring, reflecting the typical endemic phase of the disease when the virus persists covertly. However, more focused surveillance efforts identified the presence of disease hot spots occurring among juvenile life history stages from certain nearshore habitats. These outbreaks sometimes recurred annually in the same temporal and spatial patterns and were characterized by infection prevalence as high as 96%. Longitudinal sampling indicated that some epizootics were relatively transient, represented by positive samples on a single sampling date, and others were more protracted, with positive samples occurring throughout the first 10 weeks of the juvenile life history phase. These results indicate that viral hemorrhagic septicemia (VHS) epizootics in free-ranging Pacific herring C. pallasii are more common than previously appreciated; however, they are easily overlooked if biosurveillance efforts are not designed around times and locations with high disease potential.
","language":"English","publisher":"MDPI","doi":"10.3390/ani11082426","usgsCitation":"Hershberger, P., Meyers, T.R., Gregg, J.L., Groner, M., Hall, S.A., Jayasekera, H.T., MacKenzie, A., Neat, A.S., Piatt, E.N., and Garver, K.A., 2021, Annual recurrences of viral hemorrhagic septicemia epizootics in age 0 Pacific herring Clupea pallasii Valenciennes, 1847: Animals, v. 11, no. 8, 2426, 13 p., https://doi.org/10.3390/ani11082426.","productDescription":"2426, 13 p.","ipdsId":"IP-131055","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":451132,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani11082426","text":"Publisher Index Page"},{"id":436239,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F55KEO","text":"USGS data release","linkHelpText":"Survey of viral hemorrhagic septicemia virus in Pacific herring throughout the North Pacific Ocean"},{"id":389945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":824173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyers, Theodore R.","contributorId":173262,"corporation":false,"usgs":false,"family":"Meyers","given":"Theodore","email":"","middleInitial":"R.","affiliations":[{"id":27204,"text":"Alaska Department of Fish and Game, Juneau, Alaska","active":true,"usgs":false}],"preferred":false,"id":824174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gregg, Jacob L. 0000-0001-5328-5482 jgregg@usgs.gov","orcid":"https://orcid.org/0000-0001-5328-5482","contributorId":203912,"corporation":false,"usgs":true,"family":"Gregg","given":"Jacob","email":"jgregg@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":824175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Groner, Maya 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":220169,"corporation":false,"usgs":true,"family":"Groner","given":"Maya","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":824176,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Sophie Amanda 0000-0002-1907-0637","orcid":"https://orcid.org/0000-0002-1907-0637","contributorId":266032,"corporation":false,"usgs":true,"family":"Hall","given":"Sophie","email":"","middleInitial":"Amanda","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":824177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jayasekera, Hiruni T.","contributorId":266033,"corporation":false,"usgs":false,"family":"Jayasekera","given":"Hiruni","email":"","middleInitial":"T.","affiliations":[{"id":54866,"text":"Previously USGS, Western Fisheries Research Center, Marrowstone Marine Field Station","active":true,"usgs":false}],"preferred":false,"id":824178,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"MacKenzie, Ashley 0000-0002-7402-7877 amackenzie@usgs.gov","orcid":"https://orcid.org/0000-0002-7402-7877","contributorId":150817,"corporation":false,"usgs":true,"family":"MacKenzie","given":"Ashley","email":"amackenzie@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":824179,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Neat, Abigail S.","contributorId":266034,"corporation":false,"usgs":false,"family":"Neat","given":"Abigail","email":"","middleInitial":"S.","affiliations":[{"id":54867,"text":"Previously USGS, Western Fisheries Research Center, Marrowstone Marine Field Station, now Oregon State University","active":true,"usgs":false}],"preferred":false,"id":824180,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Piatt, Ella N.","contributorId":266035,"corporation":false,"usgs":false,"family":"Piatt","given":"Ella","email":"","middleInitial":"N.","affiliations":[{"id":54868,"text":"Previously USGS, Western Fisheries Research Center, Marrowstone Marine Field Station, now NOAA – Auke Bay Labs","active":true,"usgs":false}],"preferred":false,"id":824181,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Garver, Kyle A.","contributorId":149992,"corporation":false,"usgs":false,"family":"Garver","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":17880,"text":"Fisheries and Oceans, Canada, Pacific Biological Station, Nanaimo, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":824182,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70223174,"text":"sir20215048 - 2021 - Strandlines from large floods on the Colorado River in Grand Canyon National Park, Arizona","interactions":[],"lastModifiedDate":"2021-09-14T19:41:55.81256","indexId":"sir20215048","displayToPublicDate":"2021-08-18T08:08:16","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5048","displayTitle":"Strandlines from Large Floods on the Colorado River in Grand Canyon National Park, Arizona","title":"Strandlines from large floods on the Colorado River in Grand Canyon National Park, Arizona","docAbstract":"Strandlines of peak-stage indicators (such as driftwood logs, woody debris, and trash) provide valuable data for understanding the maximum stage and extent of inundation during floods. A series of seven strandlines have been preserved along the Colorado River in Grand Canyon National Park, Arizona, USA. A survey and analysis of these strandlines was completed from the Colorado River at Lees Ferry, Ariz., gaging station to the Colorado River near Grand Canyon, Ariz., gaging station. Owing to the longitudinally discontinuous nature of the strandlines, several lines of evidence were used to determine the year of the flood associated with each strandline segment. This evidence included strandline relative vertical position, degree of peak-stage indicator weathering, datable trash drift, and map-view location. The seven distinct strandlines identified were deposited during floods with the following peak discharges (in cubic feet per second [ft3/s]) at the Colorado River at Lees Ferry, Ariz., gaging station (year of flood in parentheses): 210,000 ft3/s (1884), 170,000 ft3/s (1921), 125,000 ft3/s (1957), 108,000 ft3/s (1958), 97,000 ft3/s (1983), 52,500 ft3/s (1986), and 45,000 ft3/s (multiple events between 1996 and 2012). Stage-discharge relations were developed in areas where all, or most of the strandlines were present, and were compared to predicted stage-discharge relations from a one-dimensional flow model. River width exerted a strong control on these relations, with much greater stage change occurring for a given discharge change in narrower bedrock-dominated reaches than in wider reaches with more extensive channel-margin alluvium. This comprehensive dataset allows for the verification of model-predicted flood stage along the Colorado River in Grand Canyon National Park.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215048","usgsCitation":"Sabol, T.A., Griffiths, R.E., Topping, D.J., Mueller, E.R., Tusso, R.B., and Hazel, J.E., Jr., 2021, Strandlines from large floods on the Colorado River in Grand Canyon National Park, Arizona: U.S. Geological Survey Scientific Investigations Report 2021-5048, 41 p., https://doi.org/10.3133/sir20215048.","productDescription":"Report: vi, 41 p.; Data Release; Version History","numberOfPages":"41","onlineOnly":"Y","ipdsId":"IP-118687","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":388103,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GIQ9ZN","linkHelpText":"Surveyed peak-stage elevations, coordinates, and indicator data of strandlines from large floods on the Colorado River in Grand Canyon National Park, Arizona"},{"id":388754,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5048/versionhist.txt","size":"5 KB","linkFileType":{"id":2,"text":"txt"}},{"id":387949,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5048/covrthb.jpg"},{"id":388753,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5048/sir20215048.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.027099609375,\n 35.78662688467009\n ],\n [\n -111.37390136718749,\n 35.78662688467009\n ],\n [\n -111.37390136718749,\n 36.98500309285596\n ],\n [\n -114.027099609375,\n 36.98500309285596\n ],\n [\n -114.027099609375,\n 35.78662688467009\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Various ecomorphs of shallow-water Cisco Coregonus artedi were the dominant fish planktivores in each of the Great Lakes until invasive species and over fishing resulted in extirpations and extinctions. In this paper we describe the present morphological diversity and distribution of shallow-water Ciscoes in each of Lake Huron’s three basins: the main basin, Georgian Bay, and North Channel. Typical artedi, a formerly widespread ecomorph, which had supported the lake’s largest fishery, appears to have been extirpated from all three basins. Three types of shorthead ciscoes, a recently described and variable ecomorph, were extant. One type was morphologically robust and abundant along the north rim of the lake. The second type was large bodied, terete, short finned, and collected at only one location in the main basin. The third type consisted of putative shorthead cisco × typical artedi hybrids, which were widespread in Georgian Bay and the North Channel. Only the putative hybrids were regularly collected in midwater trawls, suggesting they were more-pelagic, which we attribute to an inferred partial ancestry with typical artedi. The putative shorthead cisco × typical artedi hybrids of Georgian Bay and the North Channel have replaced typical artedi to some degree, while shorthead ciscoes in the main basin, though possibly more abundant now than in the past, have not measurably replaced typical artedi. Even with the apparent extirpation of typical artedi, Lake Huron has a greater diversity of shallow-water Ciscoes than any of the other Great Lakes, which we attribute to its more-complex topography.
Sampling rare and clustered populations is challenging because of the effort required to find rare units. Heuristically, a practitioner would prefer to discontinue sampling in areas where rare units of interest are apparently extremely sparse or absent. We take advantage of the characteristics of inverse sampling to adaptively inform practitioners when it is efficient to move on to sample new areas. We introduce Adaptive Two-stage Inverse Sampling (ATIS), which is designed to leave a selected area after observation of an a priori number of only non-rare units and to continue sampling in the area when rare units are observed. ATIS is efficient in many cases and yields more rare units than conventional sampling for a rare and clustered population. We derive unbiased estimators of population total and variance. We also introduce an easy-to-compute estimator, which is nearly as efficient as the unbiased estimator. A simulation study on a rare plant population of buttercups (Ranunculus) shows that ATIS even with the easy-to-compute estimator is more efficient than its conventional sampling counterparts and is more efficient than Two-stage Adaptive Cluster Sampling (TACS) for small and moderate final sample sizes. Additional simulations reveal that ATIS is efficient for binary data (e.g., presence or absence) whereas TACS is inefficient for binary data. The overall results indicate that ATIS is consistently efficient compared to conventional sampling and to adaptive cluster sampling in some important cases.
Since 2017, the orbit of Landsat 7 has drifted outside its nominal mission requirement toward an earlier acquisition time because of limited onboard fuel resources. This makes quantitative analyses from Landsat 7 data potentially unreliable for many scientific studies. To comprehensively understand the effect of ongoing (2018–2020) orbit drift on Landsat 7 data, we compared surface reflectance and Top-Of-Atmosphere (TOA) reflectance of growing season observations (July 1 ± 30 days) from Landsat 7 with orbit drift and Landsat 8 with nominal orbit using a total of 10,000 randomly selected Northern Hemisphere (0–750 N) terrestrial pixels. To evaluate the future (2021–2023) effect of Landsat 7's orbit drift, we analyzed the historical Northern Hemisphere terrestrial growing season Earth Observing-1 (EO-1) TOA reflectance images, which shared a similar orbit drift as Landsat 7 but occurred much earlier. Results suggest that Landsat 7's orbit drift has already led to a general decrease in surface reflectance and TOA reflectance in 2019 and 2020, with a limited impact (overall reflectance changes less than 0.007). The influence of orbit drift is more substantial for the two shortwave infrared (SWIR) bands and the near infrared (NIR) band, but less for the three visible bands (i.e., Red, Green, and Blue). The Normalized Difference Vegetation Index (NDVI), derived from either surface reflectance or TOA reflectance, increased less than 0.003 in 2020. According to the historical EO-1 TOA reflectance data, we estimate that the effect of Landsat 7's orbit drift will be much more dramatic in the future (e.g., the NIR and SWIR bands will decrease more than 0.015 since July 1, 2021), and for different land cover types, the effects of orbit drift are also quite different. To reduce this influence, we examined the c-factor Bidirectional Reflectance Distribution Function (BRDF) normalization approach to correct the orbit drift impact for Landsat 7 surface reflectance data collected between 2019 and 2020. We found that the c-factor BRDF can reduce the data difference substantially, but how this approach works after Landsat 7's orbit drifts further still requires more investigation. Therefore, we determined that Landsat 7 can preserve its science capability until 2020, but will be less reliable for remote sensing applications that need accurate absolute radiometric values after 2020. Correction methods such as c-factor BRDF could be a potential viable approach to maintain its science capability going forward.
The rapidly emerging field of macrogenetics focuses on analysing publicly accessible genetic datasets from thousands of species to explore large-scale patterns and predictors of intraspecific genetic variation. Facilitated by advances in evolutionary biology, technology, data infrastructure, statistics and open science, macrogenetics addresses core evolutionary hypotheses (such as disentangling environmental and life-history effects on genetic variation) with a global focus. Yet, there are important, often overlooked, limitations to this approach and best practices need to be considered and adopted if macrogenetics is to continue its exciting trajectory and reach its full potential in fields such as biodiversity monitoring and conservation. Here, we review the history of this rapidly growing field, highlight knowledge gaps and future directions, and provide guidelines for further research.
Noble gases record fluid interactions in multiphase subsurface environments through fractionation processes during fluid equilibration. Water in the presence of hydrocarbons at the subsurface acquires a distinct elemental signature due to the difference in solubility between these two fluids. We find the atmospheric noble gas signature in produced water is partially preserved after hydrocarbons production and water disposal to unlined ponds at the surface. This signature is distinct from meteoric water and can be used to trace oil-field water seepage into groundwater aquifers. We analyse groundwater (n = 30) and fluid disposal pond (n = 2) samples from areas overlying or adjacent to the Fruitvale, Lost Hills, and South Belridge Oil Fields in the San Joaquin Basin, California, USA. Methane (2.8 × 10−7 to 3 × 10−2 cm3 STP/cm3) was detected in 27 of 30 groundwater samples. Using atmospheric noble gas signatures, the presence of oil-field water was identified in 3 samples, which had equilibrated with thermogenic hydrocarbons in the reservoir. Two (of the three) samples also had a shallow microbial methane component, acquired when produced water was deposited in a disposal pond at the surface. An additional 6 samples contained benzene and toluene, indicative of interaction with oil-field water; however, the noble gas signatures of these samples are not anomalous. Based on low tritium and 14C contents (≤ 0.3 TU and 0.87–6.9 pcm, respectively), the source of oil-field water is likely deep, which could include both anthropogenic and natural processes. Incorporating noble gas analytical techniques into the groundwater monitoring programme allows us to 1) differentiate between thermogenic and microbial hydrocarbon gas sources in instances when methane isotope data are unavailable, 2) identify the carrier phase of oil-field constituents in the aquifer (gas, oil-field water, or a combination), and 3) differentiate between leakage from a surface source (disposal ponds) and from the hydrocarbon reservoir (either along natural or anthropogenic pathways such as faulty wells).
Here we respond to Baveye and colleagues' recent critique of our PROMISE model, describing how this new framework significantly advances our understanding of soil spatial heterogeneity and its influence on organic matter transformations.
The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, collects data pertaining to the surface-water resources of Missouri. Established in 1964, the Ambient Water-Quality Monitoring Network (AWQMN) consisted of 69 sites in 2017. Two additional sites from the National Water-Quality Program are included with the AWQMN sites for the analyses in this report. The sites are sampled typically from 2 to 12 times per year for physical properties, total suspended solids, nutrients, fecal indicator bacteria, and trace elements.
The period of analysis for this study was from 1993 through 2017 and data analysis included 71 sites and 15 water-quality constituents plus discharge. Data analysis involved retrieving the data, conditioning the data for analysis, analyzing the data for trends, and analyzing the monitoring network to determine if potential data gaps or data redundancies exist in the network. Results from these analyses can be used to help manage the monitoring network into the future.
Water-quality data were analyzed using several software packages to provide graphical and statistical information for interpretation of trends in the data at selected sites. Discharge data at selected sites were analyzed to determine the general trends during the analysis period and how the water-quality samples represented the range of daily mean discharges at each site. Water-quality data also were analyzed at selected sites to determine the relative sensitivity of selected sites and constituents to changes in data collection frequency. Trend analysis at selected sites using a simulated reduction in sampling frequency was completed to compare to trends obtained using monthly data to determine the potential degradation in the ability of determining trends from a reduced sampling frequency. The viability of using estimated discharge to evaluate long-term trends for sites with no continuous discharge was investigated. Data from sites were statistically compared in groups to determine the relative similarity (or difference) between sites for each water-quality constituent to identify potentially redundant sites in the monitoring network.
Discharge-weighted long-term trends during 1993 through 2017 were analyzed for 15 water-quality constituents at 58 sites and results indicated there were significant single- or two-period trends in about 17 percent of the analyses. Some trends indicated improvement and some trends indicated deterioration of the general water quality at some sites in the AWQMN. No trend was indicated in about 31 percent of the analyses. The constituents pH, specific conductance, and total phosphorus showed the most frequent significant trends, and each of the 15 constituents examined had a significant trend at one or more sites. A total of 42 sites indicated at least 1 constituent with a significant single- or two-period trend, and 10 sites indicated 6 or more significant trends.
Potential data gaps identified for computing discharge-weighted long-term trends in the monitoring network included the lack of collection of continuous discharge at 23 sites, insufficient sampling frequency for some constituents (dissolved chloride and total and dissolved lead and zinc) at some sites, insufficient temporal sample distribution (lack of at least one sample in each season per year) at some sites, and insufficient sampling frequency for some highly censored constituents (nutrients and total and dissolved lead and zinc) at some sites. Potential data gaps based on site spatial distribution were identified in 7 basins greater than 800 square miles.
Potential site redundancies were identified in 4 basins that had an area greater than 500 square miles with a site density greater than 2 sites per 1,000 square miles. Potential site redundancies also were identified for nine site pairs by observing statistical similarities in the constituent data distributions. Sampling frequency was investigated to determine if reducing the sampling frequency of select constituents could provide a statistically similar data distribution. At 28 of 71 sites, 11 constituents had sufficient data collection frequency (approximately monthly) to allow for the creation of simulated datasets of various reduced data collection frequency. For the selected monitoring network sites analyzed, the data distribution of a simulated sampling frequency of four times per year or greater, roughly evenly distributed over the year, was not significantly different than the data distribution of the original monthly sampling frequency. Sites analyzed using varying simulated sampling frequencies tended to be more sensitive to sampling frequency changes if they were in basins classified as large or very large size and tended to be least sensitive in basins classified as small and medium size in the Ozark Plateaus Province. Simulated reduced frequency sampling analysis indicated that the constituents and measurements most sensitive to changes in sampling frequencies were water temperature, dissolved oxygen, discharge, and dissolved nitrate, and least sensitive were pH, total suspended solids, dissolved phosphorus, and total phosphorus. Discharge-weighted long-term trend analysis was repeated at 22 sites for 11 constituents using a simulated quarterly sampling frequency, and matched about 46 percent of the significant single-period trends identified using monthly data and about 65 percent of the analyses that indicated no trend using the monthly data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215079","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Richards, J.M., and Barr, M.N., 2021, General water-quality conditions, long-term trends, and network analysis at selected sites within the Ambient Water-Quality Monitoring Network in Missouri, water years 1993–2017: U.S. Geological Survey Scientific Investigations Report 2021–5079, 75 p., https://doi.org/10.3133/sir20215079.","productDescription":"Report: xi, 75 p.; Data Release; Dataset; 11 Tables","numberOfPages":"91","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-123674","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":388009,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5079/downloads/xlsx/","text":"Tables 1, 2, 4, 5, 6, 15, 16, 17, 18, 20, and 22 in .xlsx format","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2021–5079 Tables"},{"id":388008,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5079/downloads/csv/","text":"Tables 1, 2, 4, 5, 6, 15, 16, 17, 18, 20, and 22 in .csv format","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2021–5079 Tables"},{"id":388002,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R2R9DF","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Supporting data for analysis of general water-quality conditions, long-term trends, and network analysis at selected sites within the Ambient Water-Quality Monitoring Network in Missouri, water years 1993–2017"},{"id":388000,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5079/coverthb.jpg"},{"id":388001,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5079/sir20215079.pdf","text":"Report","size":"7.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5079"},{"id":388003,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Missouri","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.545006,36.336809],[-89.605668,36.342234],[-89.615841,36.336085],[-89.620255,36.323006],[-89.611819,36.309088],[-89.578492,36.288317],[-89.554289,36.277751],[-89.539487,36.277368],[-89.534507,36.261802],[-89.539229,36.248821],[-89.562206,36.250909],[-89.577544,36.242262],[-89.602374,36.238106],[-89.642182,36.249486],[-89.678046,36.248284],[-89.695235,36.252766],[-89.705328,36.239898],[-89.69263,36.224959],[-89.607004,36.171179],[-89.591605,36.144096],[-89.59307,36.129699],[-89.601936,36.11947],[-89.666598,36.095802],[-89.678821,36.084636],[-89.688577,36.029238],[-89.706932,36.000981],[-90.37789,35.995683],[-90.351732,36.025347],[-90.34909,36.040131],[-90.339343,36.047112],[-90.333261,36.067504],[-90.320746,36.071326],[-90.320662,36.087138],[-90.29991,36.098236],[-90.294492,36.112949],[-90.266256,36.120559],[-90.235585,36.139474],[-90.231386,36.147348],[-90.23537,36.159153],[-90.220425,36.184764],[-90.21128,36.183392],[-90.188189,36.20536],[-90.152497,36.215582],[-90.14224,36.227522],[-90.126366,36.229367],[-90.130114,36.240307],[-90.118219,36.253491],[-90.114922,36.265595],[-90.086471,36.271531],[-90.06398,36.303038],[-90.081961,36.322097],[-90.074074,36.342895],[-90.077695,36.348478],[-90.066297,36.3593],[-90.064514,36.382085],[-90.078671,36.399116],[-90.138512,36.413952],[-90.134231,36.422827],[-90.143743,36.424433],[-90.143798,36.428483],[-90.134136,36.436602],[-90.137323,36.455411],[-90.141101,36.461791],[-90.155804,36.463555],[-90.152888,36.47093],[-90.142222,36.470554],[-90.143683,36.476029],[-90.158838,36.479558],[-90.159305,36.492446],[-90.152481,36.497952],[-94.617919,36.499414],[-94.617975,37.722176],[-94.607354,39.113444],[-94.589933,39.140403],[-94.591933,39.155003],[-94.608834,39.160503],[-94.640035,39.153103],[-94.662435,39.157603],[-94.663835,39.179103],[-94.680336,39.184303],[-94.714137,39.170403],[-94.741938,39.170203],[-94.763138,39.179903],[-94.781518,39.206146],[-94.811663,39.206594],[-94.831679,39.215938],[-94.835056,39.220658],[-94.825663,39.241729],[-94.831471,39.256273],[-94.84632,39.268481],[-94.887056,39.28648],[-94.905329,39.311952],[-94.910017,39.352543],[-94.88136,39.370383],[-94.879281,39.37978],[-94.885026,39.389801],[-94.901823,39.392798],[-94.92311,39.384492],[-94.942039,39.389499],[-94.946293,39.405646],[-94.972952,39.421705],[-94.982144,39.440552],[-95.0375,39.463689],[-95.045716,39.472459],[-95.052177,39.499996],[-95.082714,39.516712],[-95.109304,39.542285],[-95.113077,39.559133],[-95.103228,39.577783],[-95.089515,39.581028],[-95.064519,39.577115],[-95.049277,39.589583],[-95.046361,39.599557],[-95.055152,39.621657],[-95.053367,39.630347],[-95.027644,39.665454],[-95.018318,39.672869],[-94.984149,39.67785],[-94.971317,39.68641],[-94.971206,39.729305],[-94.965318,39.739065],[-94.948726,39.745593],[-94.902612,39.724202],[-94.875643,39.730494],[-94.862943,39.742994],[-94.860743,39.763094],[-94.869644,39.772894],[-94.912293,39.759338],[-94.934262,39.773642],[-94.935206,39.78313],[-94.929654,39.788282],[-94.884084,39.794234],[-94.875944,39.813294],[-94.878677,39.826522],[-94.886933,39.833098],[-94.916918,39.836138],[-94.942567,39.856602],[-94.928466,39.876344],[-94.929574,39.888754],[-94.95154,39.900533],[-94.986975,39.89667],[-95.00844,39.900596],[-95.024389,39.891202],[-95.027931,39.871522],[-95.037767,39.865542],[-95.085003,39.861883],[-95.128166,39.874165],[-95.140601,39.881688],[-95.143802,39.901918],[-95.149657,39.905948],[-95.179453,39.900062],[-95.199347,39.902709],[-95.206326,39.912121],[-95.20069,39.928155],[-95.204428,39.938949],[-95.250254,39.948644],[-95.269886,39.969396],[-95.302507,39.984357],[-95.315271,40.01207],[-95.356876,40.031522],[-95.387195,40.02677],[-95.40726,40.033112],[-95.416824,40.043235],[-95.42164,40.058952],[-95.409856,40.07432],[-95.407591,40.09803],[-95.394216,40.108263],[-95.39284,40.115887],[-95.398667,40.126419],[-95.428749,40.135577],[-95.436348,40.15872],[-95.460746,40.169173],[-95.479193,40.185652],[-95.482757,40.197346],[-95.469718,40.227908],[-95.477501,40.24272],[-95.490333,40.248966],[-95.521925,40.24947],[-95.552473,40.261904],[-95.556325,40.267714],[-95.550966,40.285947],[-95.562157,40.297359],[-95.581787,40.29958],[-95.610439,40.31397],[-95.642262,40.306025],[-95.657328,40.310856],[-95.653729,40.322582],[-95.625204,40.334288],[-95.623728,40.346567],[-95.641027,40.366399],[-95.643934,40.386849],[-95.659134,40.40869],[-95.65819,40.44188],[-95.693133,40.469396],[-95.699969,40.505275],[-95.661687,40.517309],[-95.652262,40.538114],[-95.655848,40.546609],[-95.671754,40.562626],[-95.678718,40.56256],[-95.694147,40.556942],[-95.69505,40.533124],[-95.708591,40.521551],[-95.722444,40.528118],[-95.75711,40.52599],[-95.769281,40.536656],[-95.763366,40.550797],[-95.773549,40.578205],[-95.765645,40.585208],[-94.632035,40.571186],[-94.080463,40.572899],[-92.689854,40.589884],[-91.729115,40.61364],[-91.716769,40.59853],[-91.686357,40.580875],[-91.690804,40.559893],[-91.681714,40.553035],[-91.6219,40.542292],[-91.618028,40.53403],[-91.621353,40.510072],[-91.590817,40.492292],[-91.574746,40.465664],[-91.52509,40.457845],[-91.524053,40.448437],[-91.533623,40.43832],[-91.519935,40.433673],[-91.526555,40.419872],[-91.522333,40.409648],[-91.498093,40.401926],[-91.489816,40.404317],[-91.484507,40.3839],[-91.465116,40.385257],[-91.465009,40.376223],[-91.452458,40.375501],[-91.441243,40.386255],[-91.419422,40.378264],[-91.444833,40.36317],[-91.46214,40.342414],[-91.492727,40.278217],[-91.490524,40.259498],[-91.505828,40.238839],[-91.505495,40.195606],[-91.512974,40.181062],[-91.508224,40.157665],[-91.510322,40.127994],[-91.489606,40.057435],[-91.494878,40.036453],[-91.465315,39.983995],[-91.41936,39.927717],[-91.41988,39.916533],[-91.443513,39.893583],[-91.446922,39.883034],[-91.436051,39.84551],[-91.377971,39.811273],[-91.361571,39.787548],[-91.370009,39.732524],[-91.3453,39.709402],[-91.27614,39.665759],[-91.229317,39.620853],[-91.181936,39.602677],[-91.174651,39.593313],[-91.168419,39.564928],[-91.153628,39.548248],[-91.100307,39.538695],[-91.079769,39.507728],[-91.064305,39.494643],[-91.059439,39.46886],[-91.03827,39.448436],[-90.993789,39.422959],[-90.940766,39.403984],[-90.928745,39.387544],[-90.904862,39.379403],[-90.893777,39.367343],[-90.8475,39.345272],[-90.816851,39.320496],[-90.793461,39.309498],[-90.751599,39.265432],[-90.72996,39.255894],[-90.717113,39.213912],[-90.707902,39.15086],[-90.686051,39.117785],[-90.681086,39.10059],[-90.681994,39.090066],[-90.712541,39.057064],[-90.71158,39.046798],[-90.678193,38.991851],[-90.675949,38.96214],[-90.657254,38.92027],[-90.639917,38.908272],[-90.625122,38.888654],[-90.583388,38.86903],[-90.555693,38.870785],[-90.500117,38.910408],[-90.486974,38.925982],[-90.482419,38.94446],[-90.472122,38.958838],[-90.440078,38.967364],[-90.395816,38.960037],[-90.309454,38.92412],[-90.250248,38.919344],[-90.109407,38.843548],[-90.123107,38.798048],[-90.166409,38.772649],[-90.176309,38.754449],[-90.20991,38.72605],[-90.20921,38.70275],[-90.18641,38.67475],[-90.181325,38.660381],[-90.17801,38.63375],[-90.18451,38.611551],[-90.196011,38.594451],[-90.222112,38.576451],[-90.260314,38.528352],[-90.285215,38.443453],[-90.295316,38.426753],[-90.349743,38.377609],[-90.368219,38.340254],[-90.373929,38.281853],[-90.353902,38.213855],[-90.331554,38.18758],[-90.290765,38.170453],[-90.274928,38.157615],[-90.243116,38.112669],[-90.218708,38.094365],[-90.17222,38.069636],[-90.158533,38.074735],[-90.130788,38.062341],[-90.126612,38.043981],[-90.11052,38.026547],[-90.08826,38.015772],[-90.059367,38.015543],[-90.051357,38.003584],[-90.03241,37.995258],[-90.00011,37.964563],[-89.978919,37.962791],[-89.942099,37.970121],[-89.933797,37.959143],[-89.925085,37.960021],[-89.932467,37.947497],[-89.959646,37.940196],[-89.974918,37.926719],[-89.952499,37.883218],[-89.923185,37.870672],[-89.901832,37.869822],[-89.844786,37.905572],[-89.799333,37.881517],[-89.796087,37.859505],[-89.786369,37.851734],[-89.782035,37.855092],[-89.739873,37.84693],[-89.71748,37.825724],[-89.669644,37.799922],[-89.660227,37.781032],[-89.667993,37.759484],[-89.665546,37.752095],[-89.64953,37.745498],[-89.617278,37.74972],[-89.612478,37.740036],[-89.596566,37.732886],[-89.583316,37.713261],[-89.516685,37.692762],[-89.51204,37.680985],[-89.517718,37.641217],[-89.478399,37.598869],[-89.47603,37.590226],[-89.486062,37.580853],[-89.519808,37.582748],[-89.521925,37.560735],[-89.517051,37.537278],[-89.475525,37.471388],[-89.439769,37.4372],[-89.421054,37.387668],[-89.432836,37.347056],[-89.489005,37.333368],[-89.511842,37.310825],[-89.51834,37.285497],[-89.489915,37.251315],[-89.470525,37.253357],[-89.458827,37.248661],[-89.467631,37.2182],[-89.456105,37.18812],[-89.42558,37.138235],[-89.37871,37.094586],[-89.375712,37.080505],[-89.384681,37.048251],[-89.362397,37.030156],[-89.322982,37.01609],[-89.29213,36.992189],[-89.278628,36.98867],[-89.263527,37.00005],[-89.257608,37.015496],[-89.260003,37.023288],[-89.304752,37.047565],[-89.310819,37.057897],[-89.30829,37.068371],[-89.259936,37.064071],[-89.25493,37.072014],[-89.234053,37.037277],[-89.200793,37.016164],[-89.192097,36.979995],[-89.185491,36.973518],[-89.170008,36.970298],[-89.125069,36.983499],[-89.109498,36.976563],[-89.099594,36.964543],[-89.100762,36.944002],[-89.117567,36.887356],[-89.131944,36.857437],[-89.137969,36.847349],[-89.1704,36.841522],[-89.178888,36.831368],[-89.179229,36.812915],[-89.171069,36.798119],[-89.155891,36.789126],[-89.12353,36.785309],[-89.116563,36.767557],[-89.126134,36.751735],[-89.166888,36.759633],[-89.184523,36.753638],[-89.197808,36.739412],[-89.19948,36.716045],[-89.169522,36.688878],[-89.169467,36.674596],[-89.15908,36.666352],[-89.197654,36.628936],[-89.202607,36.601576],[-89.217447,36.576159],[-89.236542,36.566824],[-89.258318,36.564948],[-89.278935,36.577699],[-89.326731,36.632186],[-89.365548,36.625059],[-89.375453,36.615719],[-89.382762,36.583603],[-89.41977,36.493896],[-89.448468,36.46442],[-89.464153,36.457189],[-89.486215,36.46162],[-89.494248,36.475972],[-89.465888,36.529946],[-89.467761,36.546847],[-89.479093,36.568206],[-89.500076,36.576305],[-89.542459,36.580566],[-89.566817,36.564216],[-89.571241,36.547343],[-89.560344,36.525436],[-89.519501,36.475419],[-89.523427,36.456572],[-89.543406,36.43877],[-89.545255,36.427079],[-89.509722,36.373626],[-89.519,36.3486],[-89.545006,36.336809]]]},\"properties\":{\"name\":\"Missouri\",\"nation\":\"USA \"}}]}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401