Genetics studies are used by wildlife managers and researchers to gain inference into a population of a species of interest. To gain these insights, microsatellites have been the primary method; however, there currently is a shift from microsatellites to single nucleotide polymorphisms (SNPs). With the different DNA requirements between microsatellites and SNPs, an investigation into which samples can provide adequate DNA yield is warranted. Using samples that were collected from previous genetic projects from regions in the USA from 2014 to 2021, we investigated the DNA yield of eight sample categories to gain insights into which provided adequate DNA to be used in ddRADseq or already developed high- or medium-density SNP panels. We found seven sample categories that met the DNA requirements for use in all three panels, and one sample category that did not meet any of the three panels requirements; however, DNA integrity was highly variable and not all sample categories that met panel DNA requirements could be considered high quality DNA. Additionally, we used linear random-effects models to determine which covariates would have the greatest influence on DNA yield. We determined that all covariates (tissue type, storage method, preservative, DNA quality, time until DNA extraction and time after DNA extraction) could influence DNA yield.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-024-56128-9","usgsCitation":"Pearce, D.L., Edson, J., Jennelle, C.S., and Walter, W., 2024, Evaluation of DNA yield from various tissue and sampling sources for use in single nucleotide polymorphism panels: Scientific Reports, v. 14, 11340, 8 p., https://doi.org/10.1038/s41598-024-56128-9.","productDescription":"11340, 8 p.","ipdsId":"IP-155452","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439581,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-56128-9","text":"Publisher Index Page"},{"id":433560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, New York, 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\"}}]}","volume":"14","noUsgsAuthors":false,"publicationDate":"2024-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearce, David L.","contributorId":342950,"corporation":false,"usgs":false,"family":"Pearce","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":910530,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edson, Jessie E.","contributorId":342951,"corporation":false,"usgs":false,"family":"Edson","given":"Jessie E.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":910531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jennelle, Chris S.","contributorId":342952,"corporation":false,"usgs":false,"family":"Jennelle","given":"Chris","email":"","middleInitial":"S.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":910532,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910533,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254910,"text":"70254910 - 2024 - Modeling coupled dynamics of an empirical predator-prey system to predict top predator recovery","interactions":[],"lastModifiedDate":"2024-06-10T14:49:13.1874","indexId":"70254910","displayToPublicDate":"2024-05-16T09:42:26","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Modeling coupled dynamics of an empirical predator-prey system to predict top predator recovery","docAbstract":"Limited data, time, and funding lead conservation managers to make difficult choices in managing species recovery. Coupled dynamical models are relied upon for decision support, but their application to empirical predator-prey systems has generally been restricted to small, tractable species. To broaden their use in conservation decision-making, we developed a model suitable for predicting the population dynamics of a larger apex carnivore and its prey. We selected southern sea otters (Enhydra lutris nereis) and their primary estuarine prey as our case study and parameterized the dynamical model with data on sea otter, clam, and crab abundances; predator-prey interactions; and sea otter bioenergetics collected from Elkhorn Slough, CA. Our model, having integrated all these salient factors, was able to successfully reproduce trends in taxa abundance as well as shifts in sea otter diet composition and energy intake rates. Rich data inputs allow the model to predict population dynamics over realistic temporal scales not only for the site of data collection, but also for similar estuaries uncolonized by sea otters. Based on model projections parameterized with prey survey data from two such estuaries, Tomales Bay and Drakes Estero, we predict the sites could support over 160 sea otters and may hold potential to further species recovery. In systems with good data availability, the model has high predictive power and can provide multi-taxa projections useful for making informed management decisions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110623","usgsCitation":"Hamilton, S.N., Tinker, M.T., Jackson, J., Tomoleoni, J.A., Kenner, M.C., Yee, J.L., Bell, T., Castorani, M.C., Becker, B.H., and Hughes, B.B., 2024, Modeling coupled dynamics of an empirical predator-prey system to predict top predator recovery: Biological Conservation, v. 294, https://doi.org/10.1016/j.biocon.2024.110623.","productDescription":"110623, 10 p.","startPage":"110623","ipdsId":"IP-161954","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":439583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2024.110623","text":"Publisher Index Page"},{"id":429752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Drakes Estero, Tomales Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.74955788944419,\n 38.00758882778453\n ],\n [\n -122.74955788944419,\n 38.30127856996327\n ],\n [\n -123.07749717586825,\n 38.30127856996327\n ],\n [\n -123.07749717586825,\n 38.00758882778453\n ],\n [\n -122.74955788944419,\n 38.00758882778453\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"294","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hamilton, Samantha N. M.","contributorId":337990,"corporation":false,"usgs":false,"family":"Hamilton","given":"Samantha","email":"","middleInitial":"N. M.","affiliations":[{"id":81062,"text":"Sonoma State University and Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":902846,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. T. 0000-0002-3314-839X","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":54152,"corporation":false,"usgs":false,"family":"Tinker","given":"M.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":902847,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Joseph","contributorId":337995,"corporation":false,"usgs":false,"family":"Jackson","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":902848,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tomoleoni, Joseph A. 0000-0001-6980-251X jtomoleoni@usgs.gov","orcid":"https://orcid.org/0000-0001-6980-251X","contributorId":167551,"corporation":false,"usgs":true,"family":"Tomoleoni","given":"Joseph","email":"jtomoleoni@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":902849,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":902850,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":902851,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bell, Tomoko","contributorId":211310,"corporation":false,"usgs":false,"family":"Bell","given":"Tomoko","email":"","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":902852,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Castorani, Max C. N.","contributorId":337991,"corporation":false,"usgs":false,"family":"Castorani","given":"Max","email":"","middleInitial":"C. N.","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":902853,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Becker, Benjamin H.","contributorId":207275,"corporation":false,"usgs":false,"family":"Becker","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":37509,"text":"Point Reyes National Seashore, Point Reyes Station, CA","active":true,"usgs":false}],"preferred":true,"id":902854,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hughes, Brent B.","contributorId":201240,"corporation":false,"usgs":false,"family":"Hughes","given":"Brent","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":902855,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70254235,"text":"cir1517 - 2024 - U.S. Geological Survey data strategy 2023–33","interactions":[],"lastModifiedDate":"2024-08-09T20:12:16.982203","indexId":"cir1517","displayToPublicDate":"2024-05-15T12:45:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1517","displayTitle":"U.S. Geological Survey Data Strategy 2023–33","title":"U.S. Geological Survey data strategy 2023–33","docAbstract":"The U.S. Geological Survey (USGS) has long recognized the strategic importance and value of well-managed data assets as an integral component of scientific integrity and foundational to the advancement of scientific research, decision making, and public safety. The USGS investment in the science lifecycle, including collection of unbiased data assets, interpretation, peer review, interpretive publications, and data release, ultimately contributes to the transparency and availability of science. Foundational Government directives and laws, such as the Foundations for Evidence-Based Policymaking Act of 2018 (Public Law 115–435, 132 Stat. 5529) as well as Executive Order 13642, “Making Open and Machine Readable the New Default for Government Information,” provide a framework for addressing strategic data management. The USGS Data Strategy builds on that framework by outlining high-level goals and objectives that serve as a long-term, decadal guide toward achieving a broad, data-focused vision.
Benefits of the USGS Data Strategy are many. The USGS will contribute to open science by increasing efficiencies in the consistent management of valuable data assets; driving innovation that results in modernized capabilities to ensure data are analysis ready; increasing data skills across the Bureau to enhance workforce data literacy; broadening capacity to understand and address needs of stakeholders; and measuring progress in producing findable, accessible, interoperable, and reusable (FAIR) data products.
The major goals and objectives of the USGS Data Strategy promote maximizing the utility of USGS data based on stakeholder needs, promoting data innovation, coordinating common data practices, modernizing our USGS enterprise data architecture, and enhancing our data-centric culture. The goals and objectives in the strategy align with other Bureau strategic plans, guidance, and directives from the Department of the Interior and the Federal Government. This strategy is a key component to strengthen the Bureau’s data ecosystem to ensure a relevant, long-term capacity that supports internal needs and achieves its scientific mission in the most efficient and effective manner.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1517","usgsCitation":"Hutchison, V.B., Burley, T.E., Blasch, K.W., Exter, P.E., Gunther, G.L., Shipman, A.J., Kelley, C.M., and Morris, C.A., 2024, U.S. Geological Survey data strategy 2023–33: U.S. Geological Survey Circular 1517, 7 p., https://doi.org/10.3133/cir1517.","productDescription":"v, 7 p.","onlineOnly":"Y","ipdsId":"IP-154183","costCenters":[{"id":5071,"text":"Office of Administration","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true},{"id":80860,"text":"Office of the Associate Chief Information Officer","active":true,"usgs":true}],"links":[{"id":428771,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1517/full"},{"id":428770,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1517/cir1517.xml"},{"id":428769,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1517/images"},{"id":428707,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1517/cir1517.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1517"},{"id":428706,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1517/coverthb.jpg"}],"contact":"Director, USGS Science Analytics and Synthesis
U.S. Geological Survey
Box 25046, MS 302
Denver, CO 80225
Groundwater quality in the western part of the Mojave Desert in San Bernardino County, California, was investigated in 2018 as part of the California State Water Resources Control Board Groundwater Ambient Monitoring and Assessment Program Priority Basin Project. The Mojave Basin Domestic-Supply Aquifer study unit (MOBS) region was divided into two study areas—floodplain and regional—to assess differences between the two major aquifers used for drinking water supply in the area. This assessment characterized the quality of ambient groundwater and not the quality of treated drinking water.
The study included three components: (1) a status assessment, which characterized the quality of groundwater resources used for domestic drinking-water supply in the floodplain and regional study areas; (2) a brief understanding assessment, which evaluated factors that could potentially affect the quality of groundwater used by domestic wells in the region; and (3) a comparative assessment between the groundwater resources used by domestic wells and public-supply wells in the two study areas. The domestic-well assessment was based on data collected by the U.S. Geological Survey from 48 domestic wells in January–May 2018. The public-supply assessment was based on data for samples from 322 public-supply wells in 2008–18, either collected by the U.S. Geological Survey or compiled from the California State Water Resources Control Boards Division of Drinking Water publicly available database.
Concentrations of water-quality constituents in ambient groundwater were compared to regulatory and non-regulatory benchmarks typically used by the State of California and Federal agencies as health-based or aesthetic standards for public drinking water. Relative concentrations, defined as the measured concentration divided by the benchmark concentration, were classified as high (greater than 1.0), moderate (greater than 0.5 for inorganic constituents or 0.1 for organic and special-interest constituents, and not high), or low (concentrations lower than moderate). The floodplain and regional study areas were divided into 15 and 35 grid cells, respectively, and grid-based methods were used to compute the areal proportions of the two study areas with high, moderate, or low relative concentrations of individual constituents and classes of constituents.
For the domestic-supply assessment, one or more inorganic constituents with health-based benchmarks were detected at high relative concentrations in 58 percent of the regional study area and 13 percent of the floodplain study area. The inorganic constituents with health-based benchmarks detected at high relative concentrations in the regional study area were arsenic, chromium and hexavalent chromium, fluoride, adjusted gross alpha particle activity, uranium, molybdenum, strontium, and nitrate; only arsenic was detected at high relative concentrations in the floodplain study area. One or more inorganic constituents with secondary maximum contaminant level benchmarks were detected at high concentrations in 15 and 6.7 percent of the regional and floodplain study areas, respectively. The constituents detected at high relative concentrations in the regional study area were total dissolved solids, chloride, sulfate, and iron; only total dissolved solids and sulfate were detected at high relative concentrations in the floodplain study area.
Organic constituents were not detected at moderate or high relative concentrations in either the regional or floodplain study areas. Volatile organic compounds were detected at low relative concentrations in 21 and 27 percent of the regional and floodplain study areas, respectively, and pesticides were detected at low relative concentrations in 9.1 and 20 percent of the regional and floodplain study areas, respectively. The only individual organic constituent detected in more than 10 percent of either study area was the trihalomethane trichloromethane. Total coliform bacteria were detected in 15 and 27 percent of the grid wells in the regional and floodplain study areas, respectively.
The greater prevalence of high relative concentrations of many inorganic constituents in the regional study area compared to the floodplain area likely indicates the greater diversity of geologic material at depth in aquifer material and generally finer-grained alluvium compared to the floodplain study area combined with generally older groundwater that has had more contact time with aquifer materials. In general, trace element concentrations (1) increased with increasing groundwater age, (2) increased with distance from recharge sources in the mountains, and (3) increased with closer proximity to some types of geological units. In general, groundwater from domestic wells in the floodplain study area is young, with most samples containing a component of modern groundwater based on tritium and unadjusted carbon-14 activities, whereas groundwater from domestic wells in the regional study area generally is old, with most samples having unadjusted carbon-14 ages of 5,000–40,000 years.
Public-supply wells in MOBS generally were deeper than domestic wells and presumably are in contact with older, more weathered alluvium that may have more mobile trace elements, such as arsenic or uranium. However, only 26 percent of the public-supply regional study area had high relative concentrations of inorganic constituents, compared to 58 percent for the domestic regional study area. The percentages of the public-supply and domestic floodplain study areas with high relative concentrations of inorganic constituents were 11 and 13 percent, respectively. The ages of groundwater used by public-supply and domestic wells in each study area were similar, which was not expected given the greater depth of the public-supply wells. Three potential factors may contribute to these results: (1) greater spatial footprint of domestic well network, which may result in domestic wells pumping groundwater from fractured bedrock or mineralized areas not used by public-supply wells; (2) greater pumping rates in public-supply wells, resulting in more water being withdrawn from coarse-grained, heterogeneous alluvium than finer-grained layers, which may have higher concentrations of (or more mobile) inorganic constituents; and (3) a greater degree of well management with public-supply wells, which may include pausing use of or decommissioning wells if treating or blending water is not feasible to lower constituent concentrations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245019","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","usgsCitation":"Groover, K.D., Fram, M.S., and Levy, Z.F., 2024, Status and understanding of groundwater quality in the Mojave Basin Domestic-Supply Aquifer study unit, 2018—California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2024–5019, 62 p., https://doi.org/10.3133/sir20245019.","productDescription":"x, 62 p.","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-110004","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499448,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116979.htm","linkFileType":{"id":5,"text":"html"}},{"id":428611,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5019/sir20245019.XML"},{"id":428610,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5019/images"},{"id":428608,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245019/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5019"},{"id":428607,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5019/sir20245019.pdf","text":"Report","size":"14.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5019"},{"id":428606,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5019/sir20245019.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.51859835894652,\n 35.183647408915874\n ],\n [\n -117.51859835894652,\n 34.28986048082601\n ],\n [\n -116.15629367144663,\n 34.28986048082601\n ],\n [\n -116.15629367144663,\n 35.183647408915874\n ],\n [\n -117.51859835894652,\n 35.183647408915874\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Thirty‐seven portable accelerometers were deployed in the eastern San Francisco Bay communities of Walnut Creek and Concord to study site response in a fault‐bounded, urban, sedimentary basin. Local earthquakes were recorded for a period of two years from 2017 to 2019 resulting in 101 well‐recorded events. Site response is estimated by two methods: the reference site spectral ratio method and a source‐site spectral inversion method. The reference site spectral ratio method allows investigation of the variability of site amplification with source azimuth and frequency. The source‐site spectral inversion method yields the best least‐squares fit to site response for a database of ground‐motion records. Both methods show substantial amplification in the Walnut Creek–Concord basin below 2 Hz indicating strong surface‐wave development. Greater amplification is seen for sources aligned along the long axis of the basin. Inversion using close‐in sources at short distances yields lower amplification at longer periods than the entire data set due to reduced surface‐wave generation for steeper angles of incidence. Inversion of site response spectra for shallow shear‐wave velocity using a global search algorithm yields VS30 values consistent with generalized mapping results based on geology and topography but with greater variability due to local site variations. 3D finite‐element modeling shows greater amplification in the Walnut Creek–Concord basin with a basin‐edge effect likely contributing to higher ground motions. Topography is also seen to lead to increased scattering and shadowing effects.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230309","usgsCitation":"Hartzell, S.H., Leeds, A.L., Ramirez-Guzman, L., Langenheim, V., and Schmitt, R.G., 2024, Site response in the Walnut Creek–Concord region of the San Francisco Bay, California: Ground motion amplification in a fault-bounded basin: Bulletin of the Seismological Society of America, v. 114, no. 5, p. 2668-2686, https://doi.org/10.1785/0120230309.","productDescription":"18 p.","startPage":"2668","endPage":"2686","ipdsId":"IP-156595","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":433493,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Walnut Creek–Concord region of San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.15,\n 38.1\n ],\n [\n -122.15,\n 37.85\n ],\n [\n -121.85,\n 37.85\n ],\n [\n -121.85,\n 38.1\n ],\n [\n -122.15,\n 38.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"114","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":912261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leeds, Alena L. 0000-0002-8756-3687 aleeds@usgs.gov","orcid":"https://orcid.org/0000-0002-8756-3687","contributorId":4077,"corporation":false,"usgs":true,"family":"Leeds","given":"Alena","email":"aleeds@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":912262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramirez-Guzman, Leonardo","contributorId":175444,"corporation":false,"usgs":false,"family":"Ramirez-Guzman","given":"Leonardo","email":"","affiliations":[],"preferred":false,"id":912263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langenheim, Victoria 0000-0003-2170-5213","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":206990,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria","affiliations":[],"preferred":true,"id":912264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmitt, Robert G. 0000-0001-8060-1954 rschmitt@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-1954","contributorId":5611,"corporation":false,"usgs":true,"family":"Schmitt","given":"Robert","email":"rschmitt@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":912265,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254331,"text":"70254331 - 2024 - Translocation in a fragmented river provides demographic benefits for imperiled fishes","interactions":[],"lastModifiedDate":"2024-05-17T13:52:52.822292","indexId":"70254331","displayToPublicDate":"2024-05-14T08:47:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Translocation in a fragmented river provides demographic benefits for imperiled fishes","docAbstract":"Fragmentation isolates individuals and restricts access to valuable habitat with severe consequences for populations, such as reduced gene flow, disruption of recolonization dynamics, reduced resiliency to disturbance, and changes in aquatic community structure. Translocations to mitigate the effects of fragmentation and habitat loss are common, but few are rigorously evaluated, particularly for fishes. Over six years, we translocated 1215 individuals of four species of imperiled fish isolated below a barrier on the San Juan River, Utah, USA, that restricts access to upstream habitat. We used re-encounter data (both passive integrated transponder tag and telemetry detections and physical recaptures) collected between 2016 and 2023, to inform a spatially explicit multistate mark–recapture model that estimated survival and transition probabilities of translocated and non-translocated individuals, both below and above the barrier. Individuals of all four species moved large (>200 km) distances upstream following translocation, with the maximum upstream encounter distance varying by species. Results from the multistate mark–recapture model suggested translocated fish survived at a higher rate compared with non-translocated fish below the barrier for three of the four species. Above the barrier, translocated individuals survived at similar rates as non-translocated fish for bluehead sucker (Catostomus discobolus) and flannelmouth sucker (Catostomus latipinnis), while survival rates of translocated endangered Colorado pikeminnow (Ptychocheilus lucius; mean, 95% CI: 0.75, 0.55–0.88) and endangered razorback sucker (Xyrauchen texanus; 0.86, 0.75–0.92) were higher relative to non-translocated individuals (Colorado pikeminnow: 0.52, 0.51–0.54; razorback sucker: 0.75, 0.74–0.75). Transition probabilities from above the barrier to below the barrier were generally low for three of the four species (all upper 95% CI ≤ 0.23), but they were substantially higher for razorback sucker. Our results suggest translocation to mitigate fragmentation and habitat loss can have demographic benefits for large-river fish species by allowing movements necessary to complete their life history in heterogeneous riverscapes. Further, given the costs or delays in providing engineered fish passage structures or in achieving dam removal, we suggest translocations may provide an alternative conservation strategy in fragmented river systems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4874","usgsCitation":"Pennock, C., Healy, B.D., Bogaard, M.R., McKinstry, M.C., Gido, K.B., Cathcart, C.N., and Hines, B., 2024, Translocation in a fragmented river provides demographic benefits for imperiled fishes: Ecosphere, v. 15, no. 5, e4874, 18 p., https://doi.org/10.1002/ecs2.4874.","productDescription":"e4874, 18 p.","ipdsId":"IP-157286","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":439600,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4874","text":"Publisher Index Page"},{"id":428797,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico, Utah","otherGeospatial":"San Juan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.19795244457669,\n 37.464337921724805\n ],\n [\n -110.39339902199882,\n 37.464337921724805\n ],\n [\n -110.39339902199882,\n 36.58940165978096\n ],\n [\n -107.19795244457669,\n 36.58940165978096\n ],\n [\n -107.19795244457669,\n 37.464337921724805\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Pennock, Casey A.","contributorId":287044,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":900989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":900990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bogaard, Matthew R.","contributorId":317815,"corporation":false,"usgs":false,"family":"Bogaard","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":900991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKinstry, Mark C.","contributorId":301155,"corporation":false,"usgs":false,"family":"McKinstry","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":65322,"text":"Upper Colorado Regional Office","active":true,"usgs":false}],"preferred":false,"id":900992,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gido, Keith B.","contributorId":198487,"corporation":false,"usgs":false,"family":"Gido","given":"Keith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":900993,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cathcart, C. Nathan","contributorId":214105,"corporation":false,"usgs":false,"family":"Cathcart","given":"C.","email":"","middleInitial":"Nathan","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":900994,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hines, Brian","contributorId":336773,"corporation":false,"usgs":false,"family":"Hines","given":"Brian","email":"","affiliations":[{"id":80857,"text":"U.S. Bureau of Reclamation, Upper Colorado Regional Office, Salt Lake City, Utah, USA","active":true,"usgs":false}],"preferred":false,"id":900995,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70258633,"text":"70258633 - 2024 - Infectivity of wild-bird origin Influenza A viruses in Minnesota wetlands across seasons","interactions":[],"lastModifiedDate":"2024-09-19T12:09:47.45247","indexId":"70258633","displayToPublicDate":"2024-05-14T07:07:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9113,"text":"Pathogens","active":true,"publicationSubtype":{"id":10}},"title":"Infectivity of wild-bird origin Influenza A viruses in Minnesota wetlands across seasons","docAbstract":"Image-based algorithms have become a powerful tool for estimating flow velocities in rivers. In this study, we generalize the space-time image velocimetry (STIV) framework for reach-scale application rather than along a cross section. The new algorithm provides information on both the magnitude and orientation of velocity vectors, and we refer to the algorithm as two-dimensional STIV, or 2D-STIV. The workflow involves setting up a grid, using centreline tangent vectors as initial estimates of flow direction, and then extracting space-time images (STIs) along search lines radiating from each grid node. The autocorrelation function is used to infer the inclination of streak lines present in STIs, which represents the advection of water surface features. Information on flow direction is obtained by evaluating various candidate search lines and identifying that which yields the highest velocity. This search can be performed exhaustively or via optimization. We applied the new 2D-STIV algorithm to three test cases, one simulated data set and two natural channels, and compared image-derived velocities to modelled or measured values. We also applied two established particle image velocimetry (PIV) algorithms to the same data sets. 2D-STIV performed as well as the two PIV algorithms for simulated images. For a natural river with distinct water surface features, 2D-STIV was effective for much of the channel but also led to a more patchy, irregular velocity field than the two PIV algorithms. For a site lacking obvious surface features, exhaustive 2D-STIV led to velocity estimates uncorrelated with field data while the optimization-based version produced erratic flow directions. 2D-STIV also required greater image sequence durations, higher frame rates, and generally longer computational run times. Overall, ensemble PIV was the most reliable algorithm.
Freshwater mussels (Bivalvia: Unionida) are an ecologically important faunal group. Excessive sediments, both in suspended and deposited formats, are believed to have negative effects on survival of freshwater mussels. However, there is a lack of quantitative tools for assessing the impact of abrupt and excessive sedimentation on freshwater mussel habitats. This gap in knowledge poses challenges for construction planning that necessitates evaluating sedimentation effects on mussels. In this paper, we present a simple Lagrangian particle tracking (LPT) model designed to investigate the downstream distances from the sediment release point where mussels may face risks of sediment exposure and burial during episodic sedimentation events. We validated the model in predicting the deposition of sands ranging from 125 to
Shallow, tropical coral reefs face compounding threats from climate change, habitat degradation due to coastal development and pollution, impacts from storms and sea-level rise, and pulse disturbances like blast fishing, mining, dredging, and ship groundings that reduce reef height and complexity. One approach toward restoring coral reef physical structure from such impacts is deploying built structures of artificial, natural, or hybrid (both artificial and natural) origin. Built structures range from designed modules and repurposed materials to underwater sculptures and intentionally placed natural rocks. Restoration practitioners and coastal managers increasingly consider incorporating – and in many cases have already begun to incorporate – built structures into coral reef-related applications, yet synthesized evidence on the ecological (coral-related; e.g., coral growth, coral survival) and physical performance of built structures in coral ecosystems across a variety of contexts (e.g., restoration, coastal protection, mitigation, tourism) is not readily available to guide decisions. To help fill this gap and inform management decisions, we systematically mapped the global distribution and abundance of published evidence on the ecological (coral-related) and physical performance of built structure interventions in shallow (≤ 30 m), tropical (35°N to 35°S) coral ecosystems.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s13750-024-00336-3","usgsCitation":"Paxton, A., Foxfoot, I.R., Cutshaw, C., Steward, D., Poussard, L., Riley, T., Swannack, T.M., Piercy, C., Altman, S., Puckett, B., Storlazzi, C.D., and Viehman, S., 2024, Evidence on the ecological and physical effects of built structures in shallow, tropical coral reefs: A systematic map: Environmental Evidence, v. 13, 12, 26 p., https://doi.org/10.1186/s13750-024-00336-3.","productDescription":"12, 26 p.","ipdsId":"IP-161299","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":439609,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13750-024-00336-3","text":"Publisher Index Page"},{"id":428970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2024-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Paxton, Avery 0000-0002-4871-9167","orcid":"https://orcid.org/0000-0002-4871-9167","contributorId":331325,"corporation":false,"usgs":false,"family":"Paxton","given":"Avery","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foxfoot, Iris R.","contributorId":336806,"corporation":false,"usgs":false,"family":"Foxfoot","given":"Iris","middleInitial":"R.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":901088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cutshaw, Christina","contributorId":336808,"corporation":false,"usgs":false,"family":"Cutshaw","given":"Christina","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steward, D’amy","contributorId":336809,"corporation":false,"usgs":false,"family":"Steward","given":"D’amy","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poussard, Leanne","contributorId":331346,"corporation":false,"usgs":false,"family":"Poussard","given":"Leanne","email":"","affiliations":[],"preferred":false,"id":901091,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riley, Trevor","contributorId":336811,"corporation":false,"usgs":false,"family":"Riley","given":"Trevor","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901092,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swannack, Todd M.","contributorId":336813,"corporation":false,"usgs":false,"family":"Swannack","given":"Todd","middleInitial":"M.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":901093,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Piercy, Candice","contributorId":331327,"corporation":false,"usgs":false,"family":"Piercy","given":"Candice","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":901094,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Altman, Safra","contributorId":331328,"corporation":false,"usgs":false,"family":"Altman","given":"Safra","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":901095,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Puckett, Brandon 0000-0001-9615-6242","orcid":"https://orcid.org/0000-0001-9615-6242","contributorId":331329,"corporation":false,"usgs":false,"family":"Puckett","given":"Brandon","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901096,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":901097,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Viehman, Shay","contributorId":336815,"corporation":false,"usgs":false,"family":"Viehman","given":"Shay","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":901098,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70257445,"text":"70257445 - 2024 - Unexpected effect of geographic origin on post-translocation survival in a long-lived reptile, the gopher tortoise","interactions":[],"lastModifiedDate":"2024-10-23T16:06:45.667726","indexId":"70257445","displayToPublicDate":"2024-05-13T09:51:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Unexpected effect of geographic origin on post-translocation survival in a long-lived reptile, the gopher tortoise","docAbstract":"Mitigation translocations move wildlife from specific areas due to conflict with humans over land use at the site. A critical decision when carrying out mitigation translocation is the acceptable distance across which animals can be moved. This decision trades off logistical expediency of unrestricted translocation with the risk of reducing translocation success due to environmental mismatch between origin and translocation site conditions. In this study, we used a large dataset of 502 individually identifiable carcasses to examine the role of geographic origin and translocation distance in the relative survival of 2822 translocated subadult and adult gopher tortoises (Gopherus polyphemus), a species experiencing large-scale mitigation translocation, at a recipient site in the Florida panhandle, USA. We hypothesized that if climate or habitat differences between the origin and translocation site influenced survival, tortoises translocated from within the Florida panhandle would have the highest survival. To the contrary, we found that survival slightly increased with increasing climatic difference between origin and recipient site, driven by higher survival of tortoises coming from central Florida sites compared to those from the panhandle and north Florida. This suggests that environmental mismatch due to long-distance translocation is not a main driver of mortality. These models also indicated an effect of season, with a survival advantage to tortoises translocated in the spring and late fall, relative to summer translocations, and a negative effect of initial density on survival. Finally, we also estimated the upper bound on annual survival in three well-monitored groups to be quite low (92–95%) for several years following release, suggesting caution when considering large translocated populations to be viable without first assessing adult survival. Our unexpected results highlight the importance of investigating species-specific sensitivities to translocation distances and indicate the limitations of assumed linear effects of translocation distance on outcomes.
","language":"English","publisher":"Zoological Society of London","doi":"10.1111/acv.12946","usgsCitation":"Loope, K.J., Cozad, R.A., Breakfield, D.B., Aresco, M.J., and Hunter, E.A., 2024, Unexpected effect of geographic origin on post-translocation survival in a long-lived reptile, the gopher tortoise: Animal Conservation, v. 27, no. 5, p. 685-697, https://doi.org/10.1111/acv.12946.","productDescription":"13 p.","startPage":"685","endPage":"697","ipdsId":"IP-155162","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439612,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/acv.12946","text":"Publisher Index Page"},{"id":433572,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"27","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Loope, Kevin J.","contributorId":342810,"corporation":false,"usgs":false,"family":"Loope","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":910417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cozad, Rebecca A.","contributorId":342813,"corporation":false,"usgs":false,"family":"Cozad","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":81935,"text":"Nokuse","active":true,"usgs":false}],"preferred":false,"id":910418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breakfield, Derek. B.","contributorId":342814,"corporation":false,"usgs":false,"family":"Breakfield","given":"Derek.","email":"","middleInitial":"B.","affiliations":[{"id":81935,"text":"Nokuse","active":true,"usgs":false}],"preferred":false,"id":910419,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aresco, Matthew J.","contributorId":342815,"corporation":false,"usgs":false,"family":"Aresco","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":81935,"text":"Nokuse","active":true,"usgs":false}],"preferred":false,"id":910420,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910421,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254879,"text":"70254879 - 2024 - Geochemical and geochronologic evidence for a contiguous northeastern Wyoming Province","interactions":[],"lastModifiedDate":"2024-06-10T14:23:07.364235","indexId":"70254879","displayToPublicDate":"2024-05-11T09:09:14","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical and geochronologic evidence for a contiguous northeastern Wyoming Province","docAbstract":"The extent and nature of the Wyoming Province, an Archean craton in southwestern Laurentia, are poorly understood due to limited exposure between spatially isolated basement-cored uplifts. This lack of exposure has led to debate about whether the northeastern Wyoming Province is underlain by contiguous Archean crust or Proterozoic rocks and suture zone associated with the Trans-Hudson orogeny. To assess these models we analyzed samples recovered from drill cores in the buried northeastern Wyoming Province that straddle the proposed Proterozoic suture. Whole-rock geochemical and Nd-Pb-O isotopic data suggest the rocks formed by partial melting of > 3.5 Ga hydrated mafic to tonalitic sources similar to elsewhere in the northern Wyoming Province. Zircon U-Pb dates record Mesoarchean magmatism and metamorphism (3.0–2.8 Ga). Published whole-rock Rb-Sr, hornblende and biotite K-Ar, and apatite fission track dates suggest these rocks have not been heated above 300 °C since 2.5–2.1 Ga. Geophysical potential field data are consistent across northeastern Wyoming contrasting with major discontinuities associated with documented Proterozoic orogens on all other margins of the Wyoming Province. Hence, geochemical, isotopic, and geochronologic data along with geophysical imaging can be most simply interpreted in terms of continuous Archean crust in the northeastern Wyoming Province. A geophysically-imaged reflector east of the Bighorn Mountains may juxtapose Archean terranes with similar ages and sources, similar to the boundary between the Montana metasedimentary terrane and Beartooth-Bighorn magmatic zone in the northwestern Wyoming Province. This work emphasizes the value of integrating geologic and geophysical constraints to constrain Archean provinces and their tectonic evolution.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2024.107419","usgsCitation":"Hillenbrand, I.W., Gilmer, A.K., Souders, A., and Bindeman, I.N., 2024, Geochemical and geochronologic evidence for a contiguous northeastern Wyoming Province: Precambrian Research, v. 407, 107419, 16 p., https://doi.org/10.1016/j.precamres.2024.107419.","productDescription":"107419, 16 p.","ipdsId":"IP-160491","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":488283,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.precamres.2024.107419","text":"Publisher Index Page"},{"id":434962,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13B3LZ9","text":"USGS data release","linkHelpText":"Data release of zircon U-Pb geochronology and whole-rock isotope geochemistry for drill core samples from Montana, Nebraska, Nevada, and Wyoming"},{"id":429747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montana, Nebraska, North Dakota, South Dakota, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102,\n 49\n ],\n [\n -115,\n 49\n ],\n [\n -115,\n 40.5\n ],\n [\n -102,\n 40.5\n ],\n [\n -102,\n 49\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"407","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":902760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":902761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Souders, Amanda Kate 0000-0002-1367-8924","orcid":"https://orcid.org/0000-0002-1367-8924","contributorId":296423,"corporation":false,"usgs":true,"family":"Souders","given":"Amanda Kate","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":902762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bindeman, Ilya N.","contributorId":175500,"corporation":false,"usgs":false,"family":"Bindeman","given":"Ilya","email":"","middleInitial":"N.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":902763,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257529,"text":"70257529 - 2024 - Vulnerability assessment of groundwater influenced ecosystems in the Northeastern United States","interactions":[],"lastModifiedDate":"2024-09-09T15:10:39.193067","indexId":"70257529","displayToPublicDate":"2024-05-11T08:01:11","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability assessment of groundwater influenced ecosystems in the Northeastern United States","docAbstract":"Groundwater-influenced ecosystems (GIEs) are increasingly vulnerable due to groundwater extraction, land-use practices, and climate change. These ecosystems receive groundwater inflow as a portion of their baseflow or water budget, which can maintain water levels, water temperature, and chemistry necessary to sustain the biodiversity that they support. In some systems (e.g., springs, seeps, fens), this connection with groundwater is central to the system’s integrity and persistence. Groundwater management decisions for human use often do not consider the ecological effects of those actions on GIEs. This disparity can be attributed, in part, to a lack of information regarding the physical relationships these systems have with the surrounding landscape and climate, which may influence the environmental conditions and associated biodiversity. We estimate the vulnerability of areas predicted to be highly suitable for the presence of GIEs based on watershed (U.S. Geological Survey Hydrologic Unit Code 12 watersheds: 24–100 km2) and pixel (30 m × 30 m pixels) resolution in the Atlantic Highlands and Mixed Wood Plains EPA Level II Ecoregions in the northeastern United States. We represent vulnerability with variables describing adaptive capacity (topographic wetness index, hydric soil, physiographic diversity), exposure (climatic niche), and sensitivity (aquatic barriers, proportion urbanized or agriculture). Vulnerability scores indicate that ~26% of GIEs were within 30 m of areas with moderate vulnerability. Within these GIEs, climate exposure is an important contributor to vulnerability of 40% of the areas, followed by land use (19%, agriculture or urbanized). There are few areas predicted to be suitable for GIEs that are also predicted to be highly vulnerable, and of those, climate exposure is the most important contributor to their vulnerability. Persistence of GIEs in the northeastern United States may be challenged as changes in the amount and timing of precipitation and increasing air temperatures attributed to climate change affect the groundwater that sustains these systems.
","language":"English","publisher":"MDPI","doi":"10.3390/w16101366","usgsCitation":"Snyder, S.D., Loftin, C., and Reeve, A., 2024, Vulnerability assessment of groundwater influenced ecosystems in the Northeastern United States: Water, v. 16, no. 10, 1366, 23 p., https://doi.org/10.3390/w16101366.","productDescription":"1366, 23 p.","ipdsId":"IP-156998","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439625,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w16101366","text":"Publisher Index Page"},{"id":433619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, District of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont, Virginia, West Virginia","otherGeospatial":"Northeastern United 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\"}}]}","volume":"16","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Snyder, Shawn D.","contributorId":343132,"corporation":false,"usgs":false,"family":"Snyder","given":"Shawn","email":"","middleInitial":"D.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":910638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeve, Andrew S.","contributorId":343135,"corporation":false,"usgs":false,"family":"Reeve","given":"Andrew S.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":910640,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70254502,"text":"70254502 - 2024 - Elastic stress coupling between supraglacial lakes","interactions":[],"lastModifiedDate":"2024-05-29T15:29:31.662063","indexId":"70254502","displayToPublicDate":"2024-05-10T10:20:41","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7357,"text":"JGR Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Elastic stress coupling between supraglacial lakes","docAbstract":"Supraglacial lakes have been observed to drain within hours of each other, leading to the hypothesis that stress transmission following one drainage may be sufficient to induce hydro-fracture-driven drainages of other nearby lakes. However, available observations characterizing drainage-induced stress perturbations have been insufficient to evaluate this hypothesis. Here, we use ice-sheet surface-displacement observations from a dense global positioning system array deployed in the Greenland Ice Sheet ablation zone to investigate elastic stress transmission between three neighboring supraglacial lake basins. We find that drainage of a central lake can place neighboring basins in either tensional or compressional stress relative to their hydro-fracture scarp orientations, either promoting or inhibiting hydro-fracture initiation beneath those lakes. For two lakes located within our array that drain close in time, we identify tensional surface stresses caused by ice-sheet uplift due to basal-cavity opening as the physical explanation for these lakes' temporally clustered hydro-fracture-driven drainages and frequent triggering behavior. However, lake-drainage-induced stresses in the up-flowline direction remain low beyond the margins of the drained lakes. This short stress-coupling length scale is consistent with idealized lake-drainage scenarios for a range of lake volumes and ice-sheet thicknesses. Thus, on elastic timescales, our observations and idealized-model results support a stress-transmission hypothesis for inducing hydro-fracture-driven drainage of lakes located within the region of basal cavity opening produced by the initial drainage, but refute this hypothesis for distal lakes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JF007481","usgsCitation":"Stevens, L., Das, S., Behn, M.D., McGuire, J., Lai, C., Joughin, I., LaRochelle, S., and Nettles, M., 2024, Elastic stress coupling between supraglacial lakes: JGR Earth Surface, e2023JF007481, 25 p., https://doi.org/10.1029/2023JF007481.","productDescription":"e2023JF007481, 25 p.","ipdsId":"IP-134467","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":439627,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jf007481","text":"Publisher Index Page"},{"id":429350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -49.75,\n 68.8\n ],\n [\n -49.75,\n 68.6\n ],\n [\n -49.25,\n 68.6\n ],\n [\n -49.25,\n 68.8\n ],\n [\n -49.75,\n 68.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2024-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Stevens, L.","contributorId":336976,"corporation":false,"usgs":false,"family":"Stevens","given":"L.","affiliations":[{"id":80935,"text":"Univ. of Oxford","active":true,"usgs":false}],"preferred":false,"id":901651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Das, S.","contributorId":336977,"corporation":false,"usgs":false,"family":"Das","given":"S.","email":"","affiliations":[],"preferred":false,"id":901652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Behn, M. D.","contributorId":238863,"corporation":false,"usgs":false,"family":"Behn","given":"M.","email":"","middleInitial":"D.","affiliations":[{"id":13422,"text":"Boston College","active":true,"usgs":false}],"preferred":false,"id":901653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":901654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lai, Ching-Yao","contributorId":336978,"corporation":false,"usgs":false,"family":"Lai","given":"Ching-Yao","email":"","affiliations":[],"preferred":false,"id":901655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Joughin, I.","contributorId":336979,"corporation":false,"usgs":false,"family":"Joughin","given":"I.","affiliations":[],"preferred":false,"id":901656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LaRochelle, S","contributorId":336980,"corporation":false,"usgs":false,"family":"LaRochelle","given":"S","email":"","affiliations":[{"id":49192,"text":"Stanford","active":true,"usgs":false}],"preferred":false,"id":901657,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nettles, M.","contributorId":336981,"corporation":false,"usgs":false,"family":"Nettles","given":"M.","affiliations":[],"preferred":false,"id":901658,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70259404,"text":"70259404 - 2024 - Pulsing in the Ahu‘ailaʻau pond-spillway system during the 2018 Kilauea Eruption: A dynamical systems perspective","interactions":[],"lastModifiedDate":"2024-10-07T14:57:01.33837","indexId":"70259404","displayToPublicDate":"2024-05-10T09:53:16","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2290,"text":"Journal of Fluid Mechanics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Pulsing in the Ahu‘ailāʻau Pond-Spillway System during the 2018 Kīlauea Eruption: A dynamical systems perspective","title":"Pulsing in the Ahu‘ailaʻau pond-spillway system during the 2018 Kilauea Eruption: A dynamical systems perspective","docAbstract":"During the 2018 K
Much of what is known about the effects of the 1886 Charleston, South Carolina, earthquake throughout the epicentral region can be attributed to meticulous field investigations by an individual with training in geology and engineering, Earle Sloan (Clendenin, 1926). In a recent study, Bilham and Hough (2024) undertook a detailed analysis of the effects of the earthquake on railroads in the Charleston region, drawing heavily from Sloan’s reports. This exercise identified several inconsistencies in Sloan’s field reports, including understandable measurement imprecision, inferred data entry mistakes, and transcription errors. The study also begged the question, where was Sloan at the time of the mainshock and over the following week? And to what extent did he draw from secondhand information in compiling his reports? On this question Sloan’s reports were sometimes enigmatic, lending themselves to misinterpretation in contemporaneous as well as modern interpretations. Beyond the details that were germane for, and briefly summarized by, the studies of Bilham and Hough (2023, 2024), in this report we don our historical seismologist caps to chronicle Sloan’s activities following the earthquake. We summarize our inferences here for the benefit of future scholars who might attempt to retrace either Sloan’s footsteps or our own. This study also serves to highlight Sloan’s singular contributions to earthquake science, which were never published separately.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240055","usgsCitation":"Hough, S.E., and Bilham, R., 2024, On the provenance of field reports of the 1886 Charleston, South Carolina, earthquake: A seismo-historical whodunnit: Seismological Research Letters, v. 95, no. 4, p. 2527-2537, https://doi.org/10.1785/0220240055.","productDescription":"11 p.","startPage":"2527","endPage":"2537","ipdsId":"IP-162654","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","city":"Charleston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.13297882942096,\n 33.016985369462645\n ],\n [\n -80.13297882942096,\n 32.63864581856026\n ],\n [\n -79.78369938078559,\n 32.63864581856026\n ],\n [\n -79.78369938078559,\n 33.016985369462645\n ],\n [\n -80.13297882942096,\n 33.016985369462645\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"95","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bilham, Roger","contributorId":225117,"corporation":false,"usgs":false,"family":"Bilham","given":"Roger","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":927587,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70254042,"text":"sir20235145 - 2024 - Assessment and characterization of ephemeral stream channel stability and mechanisms affecting erosion in Grand Valley, western Colorado, 2018–21","interactions":[],"lastModifiedDate":"2026-01-30T19:59:39.060515","indexId":"sir20235145","displayToPublicDate":"2024-05-06T13:30:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5145","displayTitle":"Assessment and Characterization of Ephemeral Stream Channel Stability and Mechanisms Affecting Erosion in Grand Valley, Western Colorado, 2018–21","title":"Assessment and characterization of ephemeral stream channel stability and mechanisms affecting erosion in Grand Valley, western Colorado, 2018–21","docAbstract":"The Grand Valley in western Colorado is in the semiarid Southwest United States. The north side of the Grand Valley has many ungaged ephemeral streams, which are of particular interest because (1) the underlying bedrock geology, Late Cretaceous Mancos Shale, is a sedimentary rock deposit identified as a major salinity contributor to the Colorado River and (2) despite infrequent streamflows of short duration, monsoon-derived floods in these ephemeral streams can carry substantial amounts of sediment downstream, affecting upstream and downstream banks and channel cross sections. The study area is of interest, because salinity, or the total dissolved solids concentration, in the Colorado River causes an estimated $300 million to $400 million per year in economic damages in the United States, and it is estimated 62 percent of the Upper Colorado River Basin’s total dissolved solid loads originate from geologic sources. In an effort to minimize salt contributions to the Colorado River from public lands administered by the Bureau of Land Management, a comprehensive salinity control approach is typically used to reduce nonpoint sources of salinity through land management techniques and practices.
In 2018, the U.S. Geological Survey, in cooperation with the Bureau of Land Management, began an assessment of ephemeral streams located on the north side of the Grand Valley, western Colorado, to characterize stream channel stability and identify mechanisms affecting erosion. The U.S. Geological Survey developed a method for automatically extracting channel cross-section geometry from existing remotely sensed terrain models. Based on estimated flood stage and surrogate streamflows, hydraulic characteristics were calculated. Furthermore, the channel geometries and hydraulic characteristics were used to estimate channel stability using a statistical model.
Cross-section stabilities were determined from a stream channel stability assessment for a subset of 1,406 visited (field observed) locations out of 13,415 cross sections, which were delineated from remotely sensed terrain models. The application of Manning’s resistance equation in combination with multiple logistic regression models demonstrated channel stability can be estimated with a 0.845 goodness of fit for a validation dataset when using a combination of drainage area, width-to-depth ratio, sinuosity, and shear stress as the explanatory variables. Stream channel stability was extrapolated for 13,415 unvisited (not field observed) cross sections using the multiple logistic regression model and defined explanatory variables. Mapping of the ephemeral streams and their associated stabilities may be used by the Bureau of Land Management to prioritize areas for remediation or changes in management strategies to reduce sediment and salinity loading to the Colorado River.
The study found channel stability within the ephemeral streams to be spatially variable, longitudinally discontinuous, and dictated by changes in channel bed slope. The stable ephemeral streams were relatively wide and shallow and often had smaller drainage areas with less potential for producing shear stresses capable of overcoming channel adhesion. A change in channel bed slope can provide the means necessary to generate shear stresses appropriate to initiate erosion and a subsequent stability transition to incising channels. Channel widening happens when either or both banks of an incising channel reach a critical height for mass wasting, or when channel curvature causes higher sidewall stress. Regardless, widening channels can promote increases in sinuosity and subsequently reduce steep channel bed slopes. Consequently, stable and widening channels can have comparable bed slopes, making channel bed slope a poor explanatory variable to predict channel stability overall, despite its function to initiate channel instability.
The results were based on a surrogate 0.10 annual exceedance probability (AEP; return period equal to the 10-year flood) interval streamflow, although it was recognized fluctuations in streamflow would also affect channel stability. Past and current changes within the study area affect streamflow; therefore, mechanisms affecting erosion include land use disturbances, soil compaction, loss of vegetation cover, drought, less frequent and more extreme precipitation, and fires—which all intensify the potential runoff and erosion within the study area.
Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, Colorado 80225
Mathematical models are useful for public health planning and response to infectious disease threats. However, different models can provide differing results, which can hamper decision making if not synthesized appropriately. To address this challenge, multi-model hubs convene independent modeling groups to generate ensembles, known to provide more accurate predictions of future outcomes. Yet, these hubs are resource intensive, and how many models are sufficient in a hub is not known. Here, we compare the benefit of predictions from multiple models in different contexts: (1) decision settings that depend on predictions of quantitative outcomes (e.g., hospital capacity planning), where assessments of the benefits of multi-model ensembles have largely focused; and (2) decisions settings that require the ranking of alternative epidemic scenarios (e.g., comparing outcomes under multiple possible interventions and biological uncertainties). We develop a mathematical framework to mimic a multi-model prediction setting, and use this framework to quantify how frequently predictions from different models agree. We further explore multi-model agreement using real-world, empirical data from 14 rounds of U.S. COVID-19 Scenario Modeling Hub projections. Our results suggest that the value of multiple models could be different in different decision contexts, and if only a few models are available, focusing on the rank of alternative epidemic scenarios could be more robust than focusing on quantitative outcomes. Although additional exploration of the sufficient number of models for different contexts is still needed, our results indicate that it may be possible to identify decision contexts where it is robust to rely on fewer models, a finding that can inform the use of modeling resources during future public health crises.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epidem.2024.100767","usgsCitation":"Wade-Malone, L.K., Howerton, E., Probert, W., Runge, M.C., Viboud, C., and Shea, K., 2024, When do we need multiple infectious disease models? Agreement between projection rank and magnitude in a multi-model setting: Epidemics, v. 47, 100767, 14 p., https://doi.org/10.1016/j.epidem.2024.100767.","productDescription":"100767, 14 p.","ipdsId":"IP-158794","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":467011,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epidem.2024.100767","text":"Publisher Index Page"},{"id":465147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wade-Malone, La Keisha","contributorId":347211,"corporation":false,"usgs":false,"family":"Wade-Malone","given":"La","email":"","middleInitial":"Keisha","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":921051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howerton, Emily 0000-0002-0639-3728","orcid":"https://orcid.org/0000-0002-0639-3728","contributorId":258035,"corporation":false,"usgs":false,"family":"Howerton","given":"Emily","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":921052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Probert, William J.M.","contributorId":268234,"corporation":false,"usgs":false,"family":"Probert","given":"William J.M.","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":921053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":921054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Viboud, Cecile 0000-0003-3243-4711","orcid":"https://orcid.org/0000-0003-3243-4711","contributorId":258034,"corporation":false,"usgs":false,"family":"Viboud","given":"Cecile","email":"","affiliations":[{"id":52216,"text":"National Institutes of Health Fogarty International Center","active":true,"usgs":false}],"preferred":false,"id":921055,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shea, Katriona 0000-0002-7607-8248","orcid":"https://orcid.org/0000-0002-7607-8248","contributorId":193646,"corporation":false,"usgs":false,"family":"Shea","given":"Katriona","email":"","affiliations":[],"preferred":false,"id":921056,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256544,"text":"70256544 - 2024 - Impounded sediment and dam removal: Erosion rates and proximal downstream fate","interactions":[],"lastModifiedDate":"2024-08-01T14:36:55.324873","indexId":"70256544","displayToPublicDate":"2024-05-06T09:28:16","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18171,"text":"Earth Systems Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Impounded sediment and dam removal: Erosion rates and proximal downstream fate","docAbstract":"Sediment management is an important aspect of dam removal projects, often driving costs and influencing community acceptance. For dams storing uncontaminated sediments, downstream release is often the cheapest and most practical approach and can be ecologically beneficial to downstream areas deprived of sediment for years. To employ this option, project proponents must estimate the sediment quantity to be released and, if substantial, estimate how long it will take to erode, where it will go and how long it will stay there. We investigated these issues when the Bloede Dam was removed from the Patapsco River in Maryland, USA, in 2018. The dam was about 10 m high, and its impoundment was nearly filled with an estimated 186 600 m3 of sediment composed of 70% sand and 30% mud. After removal, using elevation surveys generated by traditional methods as well as structure-from-motion (SfM) photogrammetry at high temporal resolution, we documented rapid erosion of stored sediments in the first 6 months (~60%) followed by greatly reduced erosion rates for the next two and a half years. A stable channel developed in the impoundment during the rapid erosion phase. These results were predicted by a two-phased erosion response model developed from observations at sand-filled impoundments, thus expanding its applicability to include impoundments with a sand-over-mud stratigraphy. A similar two-phase erosion response has been reported for sediment releases at other dam removals in the United States, France and Japan across a range of dam and watershed scales, indicating what practitioners and communities should expect in similar settings. Downstream, repeat surveys combined with discharge and sediment gaging showed rapid transport of eroded sediments through a 5-km reach, especially during the first year when discharges were above normal, and little overbank storage.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.5850","usgsCitation":"Collins, M.J., Baker, M.E., Cashman, M.J., Miller, A., and Van Ryswick, S., 2024, Impounded sediment and dam removal: Erosion rates and proximal downstream fate: Earth Systems Processes and Landforms, v. 49, p. 2690-2703, https://doi.org/10.1002/esp.5850.","productDescription":"14 p.","startPage":"2690","endPage":"2703","ipdsId":"IP-155014","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":439656,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5850","text":"Publisher Index Page"},{"id":432028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Patapsco River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.83408755981594,\n 39.30706218141856\n ],\n [\n -76.82795890419602,\n 39.32160674641318\n ],\n [\n -76.87308992002937,\n 39.34486766362994\n ],\n [\n -76.88530997597846,\n 39.33378339261742\n ],\n [\n -76.83504342654426,\n 39.302889650775796\n ],\n [\n -76.83408755981594,\n 39.30706218141856\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","noUsgsAuthors":false,"publicationDate":"2024-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Matthias J. 0000-0003-4238-2038","orcid":"https://orcid.org/0000-0003-4238-2038","contributorId":196365,"corporation":false,"usgs":false,"family":"Collins","given":"Matthias","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":907903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Matthew E.","contributorId":149189,"corporation":false,"usgs":false,"family":"Baker","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":17665,"text":"Department of Geography and Environmental Systems, University of Maryland, Baltimore County, Baltimore, Maryland, US","active":true,"usgs":false}],"preferred":false,"id":907904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":907905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Andrew","contributorId":200717,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew","affiliations":[],"preferred":false,"id":907906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Ryswick, Stephen","contributorId":341076,"corporation":false,"usgs":false,"family":"Van Ryswick","given":"Stephen","email":"","affiliations":[{"id":25435,"text":"Maryland Geological Survey","active":true,"usgs":false}],"preferred":false,"id":907907,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273290,"text":"70273290 - 2024 - Modeling nearshore total phosphorus in Lake Michigan using linked hydrodynamic and water quality models","interactions":[],"lastModifiedDate":"2026-01-05T15:24:15.668823","indexId":"70273290","displayToPublicDate":"2024-05-06T09:12:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling nearshore total phosphorus in Lake Michigan using linked hydrodynamic and water quality models","docAbstract":"Hurricane Maria induced about 70 000 landslides throughout Puerto Rico, USA, including thousands each in three municipalities situated in Puerto Rico's rugged Cordillera Central range. By combining a nonlinear soil-depth model, presumed wettest-case pore pressures, and quasi-three-dimensional (3D) slope-stability analysis, we developed a landslide susceptibility map that has very good performance and continuous susceptibility zones having smooth, buffered boundaries. Our landslide susceptibility map enables assessment of potential ground-failure locations and their use as landslide sources in a companion assessment of inundation and debris-flow runout. The quasi-3D factor of safety, F3, showed strong inverse correlation to landslide density (high density at low F3). Area under the curve (AUC) of true positive rate (TPR) versus false positive rate (FPR) indicated success of F3 in identifying head-scarp points (AUC = 0.84) and source-area polygons (0.85 ≤ AUC ≤ 0.88). The susceptibility zones enclose specific percentages of observed landslides. Thus, zone boundaries use successive F3 levels for increasing TPR of landslide head-scarp points, with zones bounded by F3 at TPR = 0.75, very high; F3 at TPR = 0.90, high; and the remainder moderate to low. The very high susceptibility zone, with 118 landslides km−2, covered 23 % of the three municipalities. The high zone (51 landslides km−2) covered another 10 %.