{"pageNumber":"158","pageRowStart":"3925","pageSize":"25","recordCount":41062,"records":[{"id":70238832,"text":"sir20225084 - 2022 - Precipitation-driven flood-inundation mapping of Muddy Creek at Harrisonville, Missouri","interactions":[],"lastModifiedDate":"2026-04-23T17:23:51.253429","indexId":"sir20225084","displayToPublicDate":"2022-12-14T10:28:07","publicationYear":"2022","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":"2022-5084","displayTitle":"Precipitation-Driven Flood-Inundation Mapping of Muddy Creek at Harrisonville, Missouri","title":"Precipitation-driven flood-inundation mapping of Muddy Creek at Harrisonville, Missouri","docAbstract":"

The U.S. Geological Survey, in cooperation with the city of Harrisonville, Missouri, assessed flooding of Muddy Creek resulting from varying precipitation magnitudes and durations, antecedent runoff conditions, and channel modifications (cleaned culverts and added detention storage). The precipitation scenarios were used to develop a library of flood-inundation maps that included a 3.8-mile reach of Muddy Creek and tributaries within and adjacent to the city.

Hydrologic and hydraulic models of the upper Muddy Creek study basin were used to assess streamflow magnitudes associated with simulated precipitation amounts and the resulting flood-inundation conditions. The U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC–HMS; version 4.4.1) was used to simulate the amount of streamflow produced from a range of precipitation events. The Hydrologic Engineering Center-River Analysis System (HEC–RAS; version 5.0.7) was then used to route streamflows and map resulting areas of flood inundation.

The hydrologic and hydraulic models were calibrated to the September 28, 2019; May 27, 2021; and June 25, 2021, runoff events representing a range of antecedent runoff conditions and hydrologic responses. The calibrated HEC–HMS model was used to simulate streamflows from design rainfall events of 30-minute to 24-hour durations and ranging from a 100- to 0.1-percent annual exceedance probability. Flood-inundation maps were produced for reference stages of 1.0 foot (ft), or near bankfull, to 4.0 ft, or a stage exceeding the 0.1-percent annual exceedance probability interval precipitation, using the HEC–RAS model. The results of each precipitation duration-frequency value were represented by a 0.5-ft increment inundation map based on the generated peak streamflow from that rainfall event and the corresponding stage at the Muddy Creek reference location.

Seven scenarios were developed with the HEC–HMS hydrologic model with resulting streamflows routed in a HEC–RAS hydraulic model, and these scenarios varied by antecedent runoff condition and potential channel modifications. The same precipitation scenarios were used in each of the seven antecedent runoff and channel conditions, and the simulation results were assigned to a flood-inundation map condition based on the generated peak flow and corresponding stage at the Muddy Creek reference location.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225084","collaboration":"Prepared in cooperation with the city of Harrisonville, Missouri","usgsCitation":"Heimann, D.C., and Rydlund, P.H., 2022, Precipitation-driven flood-inundation mapping of Muddy Creek at Harrisonville, Missouri: U.S. Geological Survey Scientific Investigations Report 2022–5084, 18 p., https://doi.org/10.3133/sir20225084.","productDescription":"Report: viii, 18 p.; Data Release; Dataset; Application Site","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-135285","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":503404,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113945.htm","linkFileType":{"id":5,"text":"html"}},{"id":410482,"rank":7,"type":{"id":4,"text":"Application Site"},"url":"https://ci.harrisonville.mo.us/1052/Stormwater-Management","text":"City of Harrisonville web page","linkHelpText":"—Flood-inundation mapping and model of Muddy Creek"},{"id":410391,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":410390,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P969ZOLB","text":"USGS data release","linkHelpText":"Geospatial data and model archives associated with precipitation-driven flood-inundation mapping of Muddy Creek at Harrisonville, Missouri (ver. 2.0, December 2022)"},{"id":410389,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5084/images"},{"id":410388,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5084/sir20225084.XML"},{"id":410386,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5084/sir20225084.pdf","text":"Report","size":"2.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5084"},{"id":410385,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5084/coverthb.jpg"}],"country":"United States","state":"Missouri","county":"Cass County","city":"Harrisonville","otherGeospatial":"Muddy Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.38510524959862,\n 38.66691333285476\n ],\n [\n -94.38510524959862,\n 38.60174153214416\n ],\n [\n -94.30827923799478,\n 38.60174153214416\n ],\n [\n -94.30827923799478,\n 38.66691333285476\n ],\n [\n -94.38510524959862,\n 38.66691333285476\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-12-14","noUsgsAuthors":false,"publicationDate":"2022-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858850,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238919,"text":"70238919 - 2022 - Spatial models can improve the experimental design of field-based transplant gardens by preventing bias due to neighborhood crowding","interactions":[],"lastModifiedDate":"2022-12-16T15:42:54.4896","indexId":"70238919","displayToPublicDate":"2022-12-14T09:40:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Spatial models can improve the experimental design of field-based transplant gardens by preventing bias due to neighborhood crowding","docAbstract":"

Field-based transplant gardens, including common and reciprocal garden experiments, are a powerful tool for studying genetic variation and gene-by-environment interactions. These experiments assume that individuals within the garden represent independent replicates growing in a homogenous environment. Plant neighborhood interactions are pervasive across plant populations and could violate assumptions of transplant garden experiments. We demonstrate how spatially explicit models for plant–plant interactions can provide novel insights on genotypes' performance in field-transplant garden designs. We used individual-based models, based on data from a sagebrush (Artemisia spp.) common garden, to simulate the impact of spatial plant–plant interactions on between-group differences in plant growth. We found that planting densities within the range of those used in many common gardens can bias experimental outcomes. Our results demonstrate that higher planting densities can lead to inflated group differences and may confound genotypes' competitive ability and genetically underpinned variation. Synthesis. We propose that spatially explicit models can help avoid biased results by informing the design and analysis of field-based transplant garden experiments. Alternately, including neighborhood effects in post hoc analyses of transplant garden experiments is likely to provide novel insights into the roles of biotic factors and density dependence in genetic differentiation.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9630","usgsCitation":"Zaiats, A., Requena-Mullor, J.M., Germino, M., Forbey, J.S., Richardson, B.A., and Caughlin, T., 2022, Spatial models can improve the experimental design of field-based transplant gardens by preventing bias due to neighborhood crowding: Ecology and Evolution, v. 12, no. 12, e9630, 9 p., https://doi.org/10.1002/ece3.9630.","productDescription":"e9630, 9 p.","ipdsId":"IP-139927","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":445664,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.9630","text":"Publisher Index Page"},{"id":410630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Zaiats, Andrii 0000-0001-8978-4152","orcid":"https://orcid.org/0000-0001-8978-4152","contributorId":257072,"corporation":false,"usgs":false,"family":"Zaiats","given":"Andrii","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":859166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Requena-Mullor, Juan M.","contributorId":218132,"corporation":false,"usgs":false,"family":"Requena-Mullor","given":"Juan","email":"","middleInitial":"M.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":859167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":859168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forbey, Jennifer S.","contributorId":194442,"corporation":false,"usgs":false,"family":"Forbey","given":"Jennifer","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":859169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richardson, Bryce A.","contributorId":207820,"corporation":false,"usgs":false,"family":"Richardson","given":"Bryce","email":"","middleInitial":"A.","affiliations":[{"id":37640,"text":"U.S.D.A. Forest Service Rocky Mountain Research Station, Provo, UT, 84606 USA","active":true,"usgs":false}],"preferred":false,"id":859170,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caughlin, T. Trevor","contributorId":257076,"corporation":false,"usgs":false,"family":"Caughlin","given":"T. Trevor","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":859171,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238856,"text":"70238856 - 2022 - Acetylenotrophic and diazotrophic Bradyrhizobium sp. strain I71 from TCE-contaminated soils","interactions":[],"lastModifiedDate":"2022-12-14T15:30:15.135816","indexId":"70238856","displayToPublicDate":"2022-12-14T09:10:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Acetylenotrophic and diazotrophic Bradyrhizobium sp. strain I71 from TCE-contaminated soils","title":"Acetylenotrophic and diazotrophic Bradyrhizobium sp. strain I71 from TCE-contaminated soils","docAbstract":"
Abstract
Acetylene (C2H2) is a molecule rarely found in nature, with very few known natural sources, but acetylenotrophic microorganisms can use acetylene as their primary carbon and energy source. As of 2018 there were 15 known strains of aerobic and anaerobic acetylenotrophs; however, we hypothesize there may yet be unrecognized diversity of acetylenotrophs in nature. This study expands the known diversity of acetylenotrophs by isolating the aerobic acetylenotroph, Bradyrhizobium sp. strain I71, from trichloroethylene (TCE)-contaminated soils. Strain I71 is a member of the class Alphaproteobacteria and exhibits acetylenotrophic and diazotrophic activities, the only two enzymatic reactions known to transform acetylene. This unique capability in the isolated strain may increase the genus’ economic impact beyond agriculture as acetylenotrophy is closely linked to bioremediation of chlorinated contaminants. Computational analyses indicate that the Bradyrhizobium sp. strain I71 genome contains 522 unique genes compared to close relatives. Moreover, applying a novel hidden Markov model of known acetylene hydratase (AH) enzymes identified a putative AH enzyme. Protein annotation with I-TASSER software predicted the AH from the microbe Syntrophotalea acetylenica as the closest structural and functional analog. Furthermore, the putative AH was flanked by horizontal gene transfer (HGT) elements, like that of AH in anaerobic acetylenotrophs, suggesting an unknown source of acetylene or acetylenic substrate in the environment that is selecting for the presence of AH.

Importance
The isolation of Bradyrhizobium strain I71 expands the distribution of acetylene-consuming microbes to include a group of economically important microorganisms. Members of Bradyrhizobium are well studied for their abilities to improve plant health and increase crop yields by providing bioavailable nitrogen. Additionally, acetylene-consuming microbes have been shown to work in tandem with other microbes to degrade soil contaminants. Based on genome, cultivation, and protein prediction analysis, the ability to consume acetylene is likely not widespread within the genus Bradyrhizobium. These findings suggest that the suite of phenotypic capabilities of strain I71 may be unique and make it a good candidate for further study in several research avenues.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/aem.01219-22","usgsCitation":"Akob, D., Sutton, J.M., Bushman, T., Baesman, S., Klein, E., Shrestha, Y., Andrews, R., Fierst, J.L., Kolton, M., Gushgari-Doyle, S., Oremland, R., and Freeman, J., 2022, Acetylenotrophic and diazotrophic Bradyrhizobium sp. strain I71 from TCE-contaminated soils: Applied and Environmental Microbiology, v. 88, no. 22, e0129-22, 16 p., https://doi.org/10.1128/aem.01219-22.","productDescription":"e0129-22, 16 p.","ipdsId":"IP-127304","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":445667,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9680620","text":"External Repository"},{"id":435595,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DUG9O3","text":"USGS data release","linkHelpText":"Data on the Enrichment and Isolation of the Acetylenotrophic and Diazotrophic Isolate Bradyrhizobium sp. strain I71 (ver 2.0, September 2022)"},{"id":410475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Mountain View","otherGeospatial":"NASA Ames Research Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.06421385493364,\n 37.411100064799356\n ],\n [\n -122.06421385493364,\n 37.407213985987866\n ],\n [\n -122.05159674372769,\n 37.404691335707426\n ],\n [\n -122.04996596064652,\n 37.40632765908168\n ],\n [\n -122.05116759028502,\n 37.40755487815983\n ],\n [\n -122.05322752680851,\n 37.41069101336451\n ],\n [\n -122.05391417231647,\n 37.411372764515065\n ],\n [\n -122.0555449553973,\n 37.41450873988907\n ],\n [\n -122.0540858336932,\n 37.41498594202331\n ],\n [\n -122.05563078608583,\n 37.415872166492235\n ],\n [\n -122.05666075434758,\n 37.41559948315705\n ],\n [\n -122.05743323054405,\n 37.4172355682754\n ],\n [\n -122.05460081782405,\n 37.41825810332479\n ],\n [\n -122.05460081782405,\n 37.41880344964244\n ],\n [\n -122.05803404536312,\n 37.425688105341536\n ],\n [\n -122.05760489192079,\n 37.42650604216438\n ],\n [\n -122.06198225703307,\n 37.433594453639415\n ],\n [\n -122.06747542109562,\n 37.434957532740256\n ],\n [\n -122.0685912200459,\n 37.42848268592772\n ],\n [\n -122.0683337279803,\n 37.4172355682754\n ],\n [\n -122.06696043696476,\n 37.41669021054061\n ],\n [\n -122.06438551631038,\n 37.41450873988907\n ],\n [\n -122.06421385493364,\n 37.411100064799356\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"88","issue":"22","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Semrau, Jeremy D.","contributorId":299916,"corporation":false,"usgs":false,"family":"Semrau","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":49118,"text":"University of Michigan, Ann Arbor","active":true,"usgs":false}],"preferred":false,"id":859015,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Akob, Denise M. 0000-0003-1534-3025","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":204701,"corporation":false,"usgs":true,"family":"Akob","given":"Denise M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":858942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sutton, John M.","contributorId":179294,"corporation":false,"usgs":false,"family":"Sutton","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":858943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bushman, Timothy J.","contributorId":270976,"corporation":false,"usgs":false,"family":"Bushman","given":"Timothy J.","affiliations":[{"id":56236,"text":"Department of Biological Sciences, The University of Alabama","active":true,"usgs":false}],"preferred":false,"id":858944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baesman, Shaun 0000-0003-0741-8269 sbaesman@usgs.gov","orcid":"https://orcid.org/0000-0003-0741-8269","contributorId":3478,"corporation":false,"usgs":true,"family":"Baesman","given":"Shaun","email":"sbaesman@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":858945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klein, Edina 0000-0001-9642-0218","orcid":"https://orcid.org/0000-0001-9642-0218","contributorId":299887,"corporation":false,"usgs":false,"family":"Klein","given":"Edina","email":"","affiliations":[{"id":64968,"text":"Institute for Applied Biology, Department of Applied Biology, Karlsruhe Institute of Technology, Karlsruhe, Germany","active":true,"usgs":false}],"preferred":false,"id":858946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shrestha, Yesha","contributorId":299888,"corporation":false,"usgs":false,"family":"Shrestha","given":"Yesha","affiliations":[{"id":64970,"text":"US FDA","active":true,"usgs":false}],"preferred":false,"id":858947,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Andrews, Robert","contributorId":299889,"corporation":false,"usgs":false,"family":"Andrews","given":"Robert","affiliations":[{"id":64971,"text":"MRIGlobal","active":true,"usgs":false}],"preferred":false,"id":858948,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fierst, Janna L.","contributorId":179295,"corporation":false,"usgs":false,"family":"Fierst","given":"Janna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":858949,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kolton, Max","contributorId":299890,"corporation":false,"usgs":false,"family":"Kolton","given":"Max","email":"","affiliations":[{"id":64972,"text":"School of Biological Sciences, Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":858950,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gushgari-Doyle, Sara","contributorId":225516,"corporation":false,"usgs":false,"family":"Gushgari-Doyle","given":"Sara","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":858951,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Oremland, Ronald 0000-0001-7382-0147","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":299891,"corporation":false,"usgs":false,"family":"Oremland","given":"Ronald","affiliations":[{"id":12608,"text":"USGS, retired","active":true,"usgs":false}],"preferred":false,"id":858952,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Freeman, John 0000-0003-3403-9360","orcid":"https://orcid.org/0000-0003-3403-9360","contributorId":247587,"corporation":false,"usgs":false,"family":"Freeman","given":"John","email":"","affiliations":[{"id":49585,"text":"Intrinsyx Technologies Corporation","active":true,"usgs":false}],"preferred":false,"id":858953,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238829,"text":"ofr20221095 - 2022 - Assessment of significant sand resources in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California","interactions":[],"lastModifiedDate":"2026-03-30T20:46:36.091721","indexId":"ofr20221095","displayToPublicDate":"2022-12-13T09:16:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1095","displayTitle":"Assessment of Significant Sand Resources in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand Littoral Cell Study Areas along the Continental Shelf of California","title":"Assessment of significant sand resources in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California","docAbstract":"

Executive Summary

The Sand Resources Project was established through collaborative agreements between the U.S. Geological Survey (USGS), the Bureau of Ocean Energy Management (BOEM), and the California Ocean Protection Council (OPC) with the purpose of evaluating sand and gravel resources in Federal and California State Waters for potential use in future beach-nourishment projects. Project partners worked in collaboration with California Coastal Sediment Management Workgroup (CSMW) members to define priority study areas for this work based on the potential for finding sand within the broader region and the needs for this sand as shown by beach erosion areas of concern in the adjacent littoral cells. The final study areas were defined to be (1) the San Francisco Littoral Cell, (2) the Oceanside Littoral Cell, and (3) the Silver Strand Littoral Cell.

A two-stage approach was used to assess the study areas. The initial stage was a synthesis of the existing geophysical and sediment-sampling data in each area. This allowed for evaluations of the data availability, data gaps, and general patterns of sediment thickness and grain size. This synthesis was published in a separate USGS open-file report (Warrick and others, 2022). The findings from this assessment were used to refine study area boundaries and develop sampling plans for stage two of the project.

Stage two of the project is the collection, processing, and synthesis of new data, including high-resolution geophysical surveys and sediment cores—this report addresses the second stage. The work focuses on two of the study areas—the San Francisco and the Oceanside Littoral Cells, where several research cruises have been conducted. A more limited, exploratory approach was used for the Silver Strand Littoral Cell, owing to the lack of existing high-resolution bathymetric data for this study area. The data collected provide new information about the three study areas, including sediment thickness, grain-size distributions, and total organic carbon.

Sediment in all three study areas of the Sand Resources Study was suitable for beach nourishment, as reflected by their grain-size distributions and sediment thicknesses. For example, sandy sediment in the San Francisco Littoral Cell study area was on and immediately outside of the ebb-tidal bar of the San Francisco Bay, a landform that has a strong influence on grain-size patterns of the region. The presence of thick sediment deposits in this area was interpreted to be a function of tectonics, which has caused physical features that include a graben north of the Golden Gate whose deposits were thicker and siltier than the remaining area. Sandy sediment on the inner and outer parts of the continental shelf in the Oceanside Littoral Cell may be useful for nourishment, whereas the midshelf between these areas was dominated by silty sediment. Sediment in the Silver Strand Littoral Cell, which was only sampled selectively, had the greatest potential for beach nourishment because of the greater prevalence of beach-comparable grain sizes, especially in the more distal and deeper areas where medium sands were found.

The Sand Resources Project did identify several sandy regions of the continental shelf that are deeper than dredging technologies currently (2022) available in the United States, which are generally limited to 30 meters (m) water depth or less. Although sandy sediment exists in all three study areas at water depths of 30 m or less, additional sediment supplies—most of which are in Federal Waters—are present in deeper settings, especially for the Oceanside and Silver Strand Littoral Cell study areas. Although the Silver Strand Littoral Cell study area was found to be considerably replete in sand resources, these conclusions are based on a limited sampling exercise across that study area. Thus, it may be beneficial to complete a more thorough characterization of the sediment resources in the Silver Strand Littoral Cell study area if it is determined that a need for sandy coastal sediment exists in this region.

As a result of the Sand Resources Project, several areas of sand resources in Federal and California State Waters were found where they were previously unknown. As such, this project may provide important data for future coastal-management decisions in California, and it should provide a model for future investigations of sediment resources in other regions of the State.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221095","collaboration":"Prepared in cooperation with the Bureau of Ocean Energy Management and the State of California Ocean Protection Council","usgsCitation":"Warrick, J.A., Conrad, J.E., Papesh, A., Lorenson, T., and Sliter, R.W., 2022, Assessment of significant sand resources in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California: U.S. Geological Survey Open-File Report 2022–1095, 104 p., https://doi.org/10.3133/ofr20221095.","productDescription":"Report: viii, 104 p.; 3 Data Releases","onlineOnly":"Y","ipdsId":"IP-130530","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501837,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113943.htm","linkFileType":{"id":5,"text":"html"}},{"id":410366,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UELSBU","text":"USGS data release","description":"USGS data release","linkHelpText":"Geophysical and sampling data collected offshore Oceanside, southern California during field activity 2017-686-FA from 2017-10-23 to 2017-10-31"},{"id":410365,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9690BEK","text":"USGS data release","description":"USGS data release","linkHelpText":"Geophysical and core sample data collected offshore Oceanside to San Diego, southern California, during field activity 2018-638-FA from 2018-05-21 to 2018-05-26"},{"id":410364,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LBG9H5","text":"USGS data release","description":"USGS data release","linkHelpText":"Geophysical and core sample data collected offshore San Francisco, California, during field activity 2019-649-FA from 2019-10-11 to 2019-10-18"},{"id":410367,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221094","text":"OFR 2022-1094 —","linkHelpText":"Compilation of existing data for sand resource studies in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California—Strategy for field studies and sand resource assessment"},{"id":410363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1095/ofr20221095.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1095"},{"id":410362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1095/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco, Oceanside, and Silver Strand littoral cell study areas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.32845828309286,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 37.818674364541195\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.13365815618306,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.493660702226535\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.26754558635474,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.52924818029179\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

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

","tableOfContents":"","publishedDate":"2022-12-13","noUsgsAuthors":false,"publicationDate":"2022-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Warrick, Jonathan A. 0000-0002-0205-3814","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":48255,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan A.","affiliations":[],"preferred":false,"id":858830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Papesh, Antoinette 0000-0002-1704-0557","orcid":"https://orcid.org/0000-0002-1704-0557","contributorId":221273,"corporation":false,"usgs":false,"family":"Papesh","given":"Antoinette","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":858832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenson, Tom 0000-0001-7669-2873","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":299853,"corporation":false,"usgs":false,"family":"Lorenson","given":"Tom","email":"","affiliations":[],"preferred":false,"id":858833,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sliter, Ray 0000-0003-0337-3454","orcid":"https://orcid.org/0000-0003-0337-3454","contributorId":221272,"corporation":false,"usgs":true,"family":"Sliter","given":"Ray","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858834,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238789,"text":"fs20223084 - 2022 - Landsat Collection 2 Level-3 Dynamic Surface Water Extent science product","interactions":[],"lastModifiedDate":"2023-06-28T14:34:37.662328","indexId":"fs20223084","displayToPublicDate":"2022-12-13T08:20:53","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3084","displayTitle":"Landsat Collection 2 Level-3 Dynamic Surface Water Extent Science Product","title":"Landsat Collection 2 Level-3 Dynamic Surface Water Extent science product","docAbstract":"

The Landsat Collection 2 Level-3 Dynamic Surface Water Extent science product provides raster data that represent surface water inundation per pixel in Landsat 4–9 imagery. The Collection 2 Dynamic Surface Water Extent science product contains six acquisition-based raster products relating to surface water. Surface water extent is modulated by weather and climate, stream network hydrology, and geological processes such as isostatic rebound. Land use, ecosystem and service management, and overall water management also are affected by changes in surface water extent.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223084","usgsCitation":"U.S. Geological Survey, 2022, Landsat Collection 2 Level-3 Dynamic Surface Water Extent science product (ver. 1.1, June 2023): U.S. Geological Survey Fact Sheet 2022–3084, 2 p., https://doi.org/10.3133/fs20223084.","productDescription":"Report: 2 p.; Dataset","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-139625","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":410308,"rank":1,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":418247,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3084/coverthb2.jpg"},{"id":418249,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2022/3084/versionHist.txt","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":418248,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3084/fs20223084.pdf","text":"Report","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022–3084"}],"edition":"Version 1.0: December 13, 2022; Version 1.1: June 21, 2023","contact":"

Customer Services, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-12-13","revisedDate":"2023-06-21","noUsgsAuthors":false,"publicationDate":"2022-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128240,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":858726,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238770,"text":"sir20225097 - 2022 - Water-quality trends in the Delaware River Basin calculated using multisource data and two methods for trend periods ending in 2018","interactions":[],"lastModifiedDate":"2026-04-27T19:00:25.876555","indexId":"sir20225097","displayToPublicDate":"2022-12-12T12:45:00","publicationYear":"2022","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":"2022-5097","displayTitle":"Water-Quality Trends in the Delaware River Basin Calculated Using Multisource Data and Two Methods for Trend Periods Ending in 2018","title":"Water-quality trends in the Delaware River Basin calculated using multisource data and two methods for trend periods ending in 2018","docAbstract":"

Many organizations in the Delaware River Basin (DRB) monitor surface-water quality for regulatory, scientific, and decision-making purposes. In support of these purposes, over 260,000 water-quality records provided by 8 different organizations were compiled, screened, and used to generate water-quality trends in the DRB. These trends, for periods of record that end in 2018, were generated for 124 sites and up to 16 constituents using 2 trend methods: the Seasonal Kendall Test and the Weighted Regressions on Time, Discharge, and Season model. Seasonal Kendall Tests were performed on all water-quality records to detect monotonic trends in concentration over the period of record and for as many as four additional trend periods (1978–2018, 1998–2018, 2003–18, and 2008–18). The Weighted Regressions on Time, Discharge, and Season model was applied to water-quality records that passed more stringent screening criteria and was used to detect monontonic and nonmonotonic trends, account for variations in streamflow, and estimate annual concentrations. These two trend methods produced different trend directions less than 1 percent of the time, illustrating general agreement between the methods despite the different approaches and data input requirements. Overall, the changes in concentration for salinity constituents (specific conductance and total dissolved solids), chloride, and sodium were increases; those increases were some of the largest changes observed in the basin, and they occurred at faster rates over time. Total dissolved solids concentration trends at 4 of the 60 sites increased from below to above the level of concern threshold (a secondary drinking water threshold) over the period of record, indicating potentially meaningful degradation in water quality. Nutrient constituent (ammonia, nitrate, orthophosphate, total nitrogen, and total phosphorus) concentrations tended to decrease over the period of record, although fewer sites had significant trends and the changes in concentration were smaller compared to the salinity constituents. Total nitrogen and total phosphorus were the only nutrient constituents to have decreasing concentration trends that crossed from above to below the level of concern threshold, U.S. Environmental Protection Agency (EPA) ecoregional nutrient criteria, (EPA, undated c). This finding indicates water-quality improvement at sites with these trends (nine sites with total nitrogen trends and one site with a total phosphorus trend), although many sites were still in exceedance of the level of concern. Trends for total suspended solids and some major ions (calcium, magnesium, potassium) were largely nonsignificant or variable between sites, with no prevalent patterns across the DRB; however, sulfate concentrations decreased at most sites. Cumulative land-surface change within each watershed had a strong positive relation with changes in water-quality concentrations for the salinity constituents and most major ions, but not for the other constituents, indicating that land-surface changes are related to the sources and transport of these constituents. Investigating long-term trends (a decade or longer) in water quality can help the DRB water management community quantify the success of management practices and identify potential threats to water availability.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225097","programNote":"Water Availability and Use Science Program, National Water Quality Program","usgsCitation":"Shoda, M.E., and Murphy, J.C., 2022, Water-quality trends in the Delaware River Basin calculated using multisource data and two methods for trend periods ending in 2018: U.S. Geological Survey Scientific Investigations Report 2022–5097, 60 p., https://doi.org/10.3133/sir20225097.","productDescription":"Report v, 60 p.; 2 Data Releases","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122487","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":503561,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113940.htm","linkFileType":{"id":5,"text":"html"}},{"id":433058,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20233014","text":"USGS Fact Sheet 2023-3014","linkFileType":{"id":5,"text":"html"}},{"id":410213,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5097/images/"},{"id":410212,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5097/sir20225097.XML"},{"id":410211,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PX8LZO","text":"USGS data release","linkHelpText":"Multisource surface-water-quality data and U.S. Geological Survey streamgage match for the Delaware River Basin"},{"id":410209,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225097/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5097"},{"id":410208,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5097/sir20225097.pdf","text":"Report","size":"16.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5097"},{"id":410207,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5097/coverthb.jpg"},{"id":410210,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KMWNJ5","text":"USGS data release","linkHelpText":"Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, water years 1978–2018"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.68904449140135,\n 38.5435194562952\n ],\n [\n -75.2278145853991,\n 38.47477347574127\n ],\n [\n -75.03014462568353,\n 38.95461543352394\n ],\n [\n -74.87640132368297,\n 39.566811726970116\n ],\n [\n -74.28339144453736,\n 40.70854805354401\n ],\n [\n -74.1735748002507,\n 41.56866114554592\n ],\n [\n -73.77823488082065,\n 42.41747384003048\n ],\n [\n -74.21750145796516,\n 42.64406475670245\n ],\n [\n -74.96425463911187,\n 42.44989429480822\n ],\n [\n -75.44744787397136,\n 42.043433704426945\n ],\n [\n -75.88671445111639,\n 41.486448364247764\n ],\n [\n -76.19420105511806,\n 40.79174109891525\n ],\n [\n -76.23812771283252,\n 40.37473571760768\n ],\n [\n -76.01849442425974,\n 39.702128532888\n ],\n [\n -75.75493447797302,\n 39.14224249538836\n ],\n [\n -75.68904449140135,\n 38.5435194562952\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Program Coordinator
Water Availability and Use Science Program
National Water Quality Program
U.S. Geological Survey

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2022-12-12","noUsgsAuthors":false,"publicationDate":"2022-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":4281,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858541,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238771,"text":"sir20225115 - 2022 - The Seamless Integrated Geologic Mapping (SIGMa) extension to the Geologic Map Schema (GeMS)","interactions":[],"lastModifiedDate":"2022-12-16T21:44:48.335264","indexId":"sir20225115","displayToPublicDate":"2022-12-12T11:55:00","publicationYear":"2022","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":"2022-5115","displayTitle":"The Seamless Integrated Geologic Mapping (SIGMa) Extension to the Geologic Map Schema (GeMS)","title":"The Seamless Integrated Geologic Mapping (SIGMa) extension to the Geologic Map Schema (GeMS)","docAbstract":"

Geologic maps are the fundamental building blocks of surface and subsurface three-dimensional geologic framework models of the Earth’s crust. However, as the production and availability of geologic map databases continues to increase, inconsistent data models and the lack of synthesized, national geologic map data at scales appropriate for informed decision making negatively affect the functional integration of geologic map data with other national datasets. The Geologic Map Schema (GeMS) is the publication and archive database standard for geologic map data funded by the U.S. Geological Survey National Cooperative Geologic Mapping Program, and standardizes the organization and content of a single map database. However, synthesizing multiple databases into a seamless geologic map database creates a different set of challenges and database needs than GeMS was designed to accommodate. The Seamless Integrated Geologic Mapping (SIGMa) extension is designed to expand the capabilities of GeMS by enabling integration of map-based geoscience data. In particular, the SIGMa extension enables capturing a diverse and ever-changing set of map units, produced by many contributors operating independently, and by incremental and noncontiguous assembly and publication. Feature-level metadata fields allow data sources and digital compilation methods to be attributed separately and a relational structure is designed to support the link between data sources and features attributed with multiple data sources. Instead of paragraph-style map-unit descriptions that can be highly inconsistent, SIGMa parses fundamental map-unit attributes, including material, genetic process, and age, into thematically specific fields. The SIGMa extension uses a hierarchical map-unit organization to facilitate a dynamic and evolving, formation-level stratigraphic framework. The hierarchy is developed around geologic provinces that represent temporally restricted geologic events, processes, and settings. Geologic provinces can include magmatic events, depositional settings associated with tectonic processes or stable continental margins, and processes that are actively shaping the modern landscape. A geologic province hierarchy places map units into a geologic context at subregional to continental scales and provides the flexibility to support incremental assembly of the stratigraphy.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225115","usgsCitation":"Turner, K.J., Workman, J.B., Colgan, J.P., Gilmer, A.K., Berry, M.E., Johnstone, S.A., Warrell, K.F., Dechesne, M., VanSistine, D.P., Thompson, R.A., Hudson, A.M., Zellman, K.L., Sweetkind, D., and Ruleman, C.A., 2022, The Seamless Integrated Geologic Mapping (SIGMa) extension to the Geologic Map Schema (GeMS): U.S. Geological Survey Scientific Investigations Report 2022–5115, 33 p., https://doi.org/10.3133/sir20225115.","productDescription":"vii, 33 p.","onlineOnly":"Y","ipdsId":"IP-125234","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":410653,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225115/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5115"},{"id":410248,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5115/sir20225115.xml"},{"id":410247,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5115/images"},{"id":410246,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5115/sir20225115.pdf","text":"Report","size":"3.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5115"},{"id":410245,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5115/coverthb.jpg"}],"contact":"

Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046

","tableOfContents":"","publishedDate":"2022-12-12","noUsgsAuthors":false,"publicationDate":"2022-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":858544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Workman, Jeremiah B. 0000-0001-7816-6420 jworkman@usgs.gov","orcid":"https://orcid.org/0000-0001-7816-6420","contributorId":714,"corporation":false,"usgs":true,"family":"Workman","given":"Jeremiah","email":"jworkman@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":858545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":858546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":858547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berry, Margaret E. 0000-0002-4113-8212 meberry@usgs.gov","orcid":"https://orcid.org/0000-0002-4113-8212","contributorId":1544,"corporation":false,"usgs":true,"family":"Berry","given":"Margaret","email":"meberry@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":858548,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":858549,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warrell, Kathleen F. 0000-0002-5631-969X","orcid":"https://orcid.org/0000-0002-5631-969X","contributorId":299759,"corporation":false,"usgs":false,"family":"Warrell","given":"Kathleen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":858550,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dechesne, Marieke 0000-0002-4468-7495 mdechesne@usgs.gov","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":5036,"corporation":false,"usgs":true,"family":"Dechesne","given":"Marieke","email":"mdechesne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":858551,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"VanSistine, D. Paco 0000-0003-1166-2547 dvansistine@usgs.gov","orcid":"https://orcid.org/0000-0003-1166-2547","contributorId":4994,"corporation":false,"usgs":true,"family":"VanSistine","given":"D. Paco","email":"dvansistine@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":858552,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Thompson, Ren A. 0000-0002-3044-3043 rathomps@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":1265,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren","email":"rathomps@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":858553,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":858554,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zellman, Kristine L. 0000-0002-7088-429X kzellman@usgs.gov","orcid":"https://orcid.org/0000-0002-7088-429X","contributorId":4849,"corporation":false,"usgs":true,"family":"Zellman","given":"Kristine","email":"kzellman@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":858555,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sweetkind, Donald S. 0000-0003-0892-4796 dsweetkind@usgs.gov","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":139913,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald","email":"dsweetkind@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":858556,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":858557,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70238762,"text":"sir20225119 - 2022 - Flood-inundation maps for Schoharie Creek in North Blenheim, New York","interactions":[],"lastModifiedDate":"2026-04-27T19:16:36.230774","indexId":"sir20225119","displayToPublicDate":"2022-12-12T09:55:00","publicationYear":"2022","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":"2022-5119","displayTitle":"Flood-Inundation Maps for Schoharie Creek in North Blenheim, New York","title":"Flood-inundation maps for Schoharie Creek in North Blenheim, New York","docAbstract":"

Digital flood-inundation maps for a 2.4-mile reach of the Schoharie Creek in North Blenheim, New York, were created by the U.S. Geological Survey (USGS) in cooperation with the New York Power Authority. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://fim.wim.usgs.gov/fim/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Schoharie Creek near North Blenheim, N.Y. (station number 01350212). Near-real-time stage at this streamgage may be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/. Flood profiles were computed for the stream reach by means of a two-dimensional implicit finite-volume hydraulic model. The model was calibrated by using the active (as of April 2021) stage-discharge ratings at the USGS streamgages on the Schoharie Creek near North Blenheim (station number 01350212) and at North Blenheim (station number 01350180) and documented high-water marks in the study reach from the floods of August 28, 2011; January 19, 1996; and April 4, 1987.

The hydraulic model was used to compute 13 water-surface profiles for flood stages at 1-foot intervals referenced to the datum at the streamgage on the Schoharie Creek near North Blenheim, N.Y. (01350212). These profiles range from 14 feet, or near bankfull, to 26 feet, which is the highest whole-foot increment on the stage-discharge rating for the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.52-foot vertical accuracy and 3.3-foot [1-meter] horizontal resolution) to delineate the area flooded at each stage. Flood inundation maps, along with near-real-time stage data from USGS streamgages, can provide emergency management personnel and residents with information critical for flood-response activities, such as evacuations and road closures, as well as for postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225119","collaboration":"Prepared in cooperation with the New York Power Authority","usgsCitation":"Nystrom, E.A., 2022, Flood-inundation maps for Schoharie Creek in North Blenheim, New York: U.S. Geological Survey Scientific Investigations Report 2022–5119, 14 p., https://doi.org/10.3133/sir20225119.","productDescription":"Report: vi, 14 p.; Data Release","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122520","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":503571,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113939.htm","linkFileType":{"id":5,"text":"html"}},{"id":410179,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225119/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5119"},{"id":410180,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92YVB9V","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Geospatial dataset for flood inundation maps of Schoharie Creek in North Blenheim, New York"},{"id":410177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5119/coverthb.jpg"},{"id":410182,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5119/images/"},{"id":410181,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5119/sir20225119.XML"},{"id":410178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5119/sir20225119.pdf","text":"Report","size":"49.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5119"}],"country":"United States","state":"New York","city":"North Blenheim","otherGeospatial":"Schoharie Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.43435753120507,\n 42.481471549691946\n ],\n [\n -74.46929205403138,\n 42.481471549691946\n ],\n [\n -74.46929205403138,\n 42.457988603472074\n ],\n [\n -74.43435753120507,\n 42.457988603472074\n ],\n [\n -74.43435753120507,\n 42.481471549691946\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-12-12","noUsgsAuthors":false,"publicationDate":"2022-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Nystrom, Elizabeth A. 0000-0002-0886-3439 nystrom@usgs.gov","orcid":"https://orcid.org/0000-0002-0886-3439","contributorId":1072,"corporation":false,"usgs":true,"family":"Nystrom","given":"Elizabeth","email":"nystrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858499,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238780,"text":"70238780 - 2022 - A channel sampling strategy for measurement of mineral modal and chemical composition of drill cores: Application to lower oceanic crustal rocks from IODP Expedition 345 to the Hess Deep rift","interactions":[],"lastModifiedDate":"2022-12-12T15:00:33.468536","indexId":"70238780","displayToPublicDate":"2022-12-12T08:43:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3356,"text":"Scientific Drilling","active":true,"publicationSubtype":{"id":10}},"title":"A channel sampling strategy for measurement of mineral modal and chemical composition of drill cores: Application to lower oceanic crustal rocks from IODP Expedition 345 to the Hess Deep rift","docAbstract":"

We report a new sampling strategy for collecting representative samples of drill core. By splitting the core with a diamond saw into working and archive halves, the saw cuttings constitute a “channel” sample, the best subsample from which to obtain an average mineralogical and geochemical composition of a core. We apply this procedure to sampling core of the lower oceanic crust in the Hess Deep obtained during Expedition 345 of the Integrated Ocean Drilling Program (now International Ocean Discovery Program).

Our results show that particles produced by sawing range from sand to clay sizes. Sand- and silt-sized cuttings can be sampled with a spatula, whereas clay-sized particles remained in suspension after 12 h and could be collected only by settling, aided by centrifuge. X-ray diffraction (XRD) analysis and Rietveld refinement show that phyllosilicates were fractionated into the clay-sized fraction. Thus, collection of both the sedimented fraction and the clay-sized suspended fraction (commonly > 15 wt % of the total) is necessary to capture the whole sample. The strong positive correlation between the recovered sample mass (in grams) and length of core cut demonstrates that this sampling protocol was uniform and systematic, with almost 1.4 g sediment produced per centimeter of core cut. We show that major-element concentrations of our channel samples compare favorably with the compositions of billet-sized samples analyzed aboard the JOIDES Resolution, but the results show that individual billet analyses are rarely representative of the whole core recovered. A final test of the validity of our methods comes from the strong positive correlation between the loss on ignition (LOI) values of our channel samples and the H2O contents calculated from the modal mineralogy obtained by X-ray diffraction and Rietveld refinement. This sampling procedure shows that grain-sized fractionation modifies both mineralogical and chemical compositions; nevertheless, this channel sampling method is a reliable method of obtaining representative samples of bulk cores. With the ever-increasing precision offered by modern analytical instrumentation, this sampling protocol allows the accuracy of the analytical results to keep pace.

","language":"English","publisher":"Copernicus Publications","doi":"10.5194/sd-31-71-2022","usgsCitation":"Wintsch, R.P., Meyer, R., Bish, D., Deasy, R.T., Nozaka, T., and Johnson, C., 2022, A channel sampling strategy for measurement of mineral modal and chemical composition of drill cores: Application to lower oceanic crustal rocks from IODP Expedition 345 to the Hess Deep rift: Scientific Drilling, v. 31, p. 71-84, https://doi.org/10.5194/sd-31-71-2022.","productDescription":"14 p.","startPage":"71","endPage":"84","ipdsId":"IP-133634","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":445680,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/sd-31-71-2022","text":"Publisher Index Page"},{"id":410280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Hess Deep Rift, Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.57372796106893,\n 3.330136493398328\n ],\n [\n -111.57372796106893,\n -1.0981582918846584\n ],\n [\n -101.19437373696735,\n -1.0981582918846584\n ],\n [\n -101.19437373696735,\n 3.330136493398328\n ],\n [\n -111.57372796106893,\n 3.330136493398328\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Wintsch, Robert P.","contributorId":192913,"corporation":false,"usgs":false,"family":"Wintsch","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":858574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Romain","contributorId":148991,"corporation":false,"usgs":false,"family":"Meyer","given":"Romain","email":"","affiliations":[{"id":17609,"text":"Deutsche GeoForchungsZentrum Potsdam","active":true,"usgs":false}],"preferred":false,"id":858575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bish, David","contributorId":291943,"corporation":false,"usgs":false,"family":"Bish","given":"David","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":858576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deasy, Ryan T. 0000-0002-7530-803X","orcid":"https://orcid.org/0000-0002-7530-803X","contributorId":299762,"corporation":false,"usgs":true,"family":"Deasy","given":"Ryan","middleInitial":"T.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":858577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nozaka, Toshio","contributorId":299763,"corporation":false,"usgs":false,"family":"Nozaka","given":"Toshio","email":"","affiliations":[{"id":64944,"text":"Okayama University","active":true,"usgs":false}],"preferred":false,"id":858578,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Carley","contributorId":299764,"corporation":false,"usgs":false,"family":"Johnson","given":"Carley","email":"","affiliations":[{"id":64945,"text":"Marathon","active":true,"usgs":false}],"preferred":false,"id":858579,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70239015,"text":"70239015 - 2022 - Evaluating the sensitivity of multi-dimensional model predictions of salmon habitat to the source of remotely sensed river bathymetry","interactions":[],"lastModifiedDate":"2022-12-21T12:40:22.808277","indexId":"70239015","displayToPublicDate":"2022-12-12T06:37:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the sensitivity of multi-dimensional model predictions of salmon habitat to the source of remotely sensed river bathymetry","docAbstract":"

Multi-dimensional numerical models are fundamental tools for investigating biophysical processes in aquatic ecosystems. Remote sensing techniques increase the feasibility of applying such models at riverscape scales, but tests of model performance on large rivers have been limited. We evaluated the potential to develop two-dimensional (2D) and three-dimensional (3D) hydrodynamic models for a 1.6-km reach of a large gravel-bed river using three sources of remotely sensed river bathymetry. We estimated depth from hyperspectral image data acquired from conventional and uncrewed aircraft and multispectral satellite imagery. Our results indicated that modeled water depth errors were similar between 2D and 3D models, with depth residuals that were comparable to the uncertainty associated with the bathymetry used as input. We found good agreement between measured and modeled depth-averaged velocities generated by 2D and 3D models, while 3D models provided superior predictions of near-bed velocities. We found that optimal model performance occurred for lower flow resistance values than previously reported in the literature, possibly as a consequence of the high-resolution bathymetry used as model input. Model predictions of winter-run Chinook salmon (Oncorhynchus tshawytscha) spawning and rearing habitat were not sensitive to the source of bathymetric information, but bioenergetic predictions related to adult holding costs were influenced by the input bathymetry. Our results suggest that hyperspectral imagery acquired from piloted and/or uncrewed aircraft can be used to map the bathymetry of clear-flowing, relatively shallow large rivers with sufficient accuracy to support multi-dimensional flow model development; models developed from multispectral satellite imagery had more limited predictive capability.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR033097","usgsCitation":"Harrison, L.R., Legleiter, C.J., Sridharana, V.K., Dudley, P., and Daniels, M.E., 2022, Evaluating the sensitivity of multi-dimensional model predictions of salmon habitat to the source of remotely sensed river bathymetry: Water Resources Research, v. 58, no. 12, e2022WR033097, 20 p., https://doi.org/10.1029/2022WR033097.","productDescription":"e2022WR033097, 20 p.","ipdsId":"IP-139279","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":435597,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P946FW28","text":"USGS data release","linkHelpText":"Digital elevation models (DEMs) and field measurements of flow velocity used to develop and test a multidimensional hydrodynamic model for a reach of the upper Sacramento River in northern California"},{"id":410851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.41676004309863,\n 40.60116333311635\n ],\n [\n -122.41676004309863,\n 39.600784314785784\n ],\n [\n -121.81513604555622,\n 39.600784314785784\n ],\n [\n -121.81513604555622,\n 40.60116333311635\n ],\n [\n -122.41676004309863,\n 40.60116333311635\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Lee R.","contributorId":174322,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":859742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":859743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sridharana, Vamsi K 0000-0003-1457-6900","orcid":"https://orcid.org/0000-0003-1457-6900","contributorId":300259,"corporation":false,"usgs":false,"family":"Sridharana","given":"Vamsi","email":"","middleInitial":"K","affiliations":[{"id":18933,"text":"NOAA Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":859744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dudley, Peter 0000-0002-3210-634X","orcid":"https://orcid.org/0000-0002-3210-634X","contributorId":300260,"corporation":false,"usgs":false,"family":"Dudley","given":"Peter","email":"","affiliations":[{"id":18933,"text":"NOAA Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":859745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Daniels, Miles E.","contributorId":279656,"corporation":false,"usgs":false,"family":"Daniels","given":"Miles","email":"","middleInitial":"E.","affiliations":[{"id":57331,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 McAllister Way, Santa Cruz, CA 95060, USA","active":true,"usgs":false}],"preferred":false,"id":859746,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262265,"text":"70262265 - 2022 - Diet composition and overlap for adult walleye, lake whitefish, and yellow perch in Green Bay, Lake Michigan","interactions":[],"lastModifiedDate":"2025-01-23T14:22:53.648546","indexId":"70262265","displayToPublicDate":"2022-12-12T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Diet composition and overlap for adult walleye, lake whitefish, and yellow perch in Green Bay, Lake Michigan","docAbstract":"

Interspecific interactions among walleye Sander vitreus, lake whitefish Coregonus clupeaformis, and yellow perch Perca flavescens in Green Bay could influence the population status of each species, but potential trophic interactions are poorly understood. Our objectives were to determine if diet assemblages for each species and diet overlap among species varied spatially and temporally within Green Bay. Adult walleye (≥ 381 mm total length (TL); N = 981), lake whitefish (≥ 432 mm TL; N = 1507), and yellow perch (≥ 150 mm TL; N = 1174) were collected during May-October of 2018 and 2019 from multiple locations in southern and northern Green Bay. Diet assemblages of all three species varied between zones but walleye diets were more temporally variable (among months within zones and between years) than diets of lake whitefish or yellow perch. Lake whitefish represented a seasonally important prey item for walleye in southern Green Bay, composing 10% and 41% of walleye diets by weight in May and June, respectively. Yellow perch generally composed < 15% of walleye diets by weight but were consumed at a broader spatiotemporal scale than lake whitefish. Diet overlap between walleye and both lake whitefish and yellow perch was generally weak or moderate, whereas diet overlap between whitefish and perch was generally strong. Our assessment of adult trophic interactions suggests that changes in the population status of one species could influence fisheries for all three, and we identify additional research questions to address potential population-level effects of these trophic interactions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2022.09.005","usgsCitation":"Koeniga, L., Dembkowski, D., Hansen, S., Tsehaye, I., Tammie J. Paoli, Zorn, T., and Isermann, D.A., 2022, Diet composition and overlap for adult walleye, lake whitefish, and yellow perch in Green Bay, Lake Michigan: Journal of Great Lakes Research, v. 48, no. 6, p. 1681-1695, https://doi.org/10.1016/j.jglr.2022.09.005.","productDescription":"15 p.","startPage":"1681","endPage":"1695","ipdsId":"IP-140407","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480917,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Green Bay, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.25433685919877,\n 45.59617874752695\n ],\n [\n -87.9984005897609,\n 44.918805118493594\n ],\n [\n -87.98617785518738,\n 44.57675244172867\n ],\n [\n -87.3651194846989,\n 44.78875465437872\n ],\n [\n -86.56980682225971,\n 45.71326930572798\n ],\n [\n -87.03874882070055,\n 45.85231391585981\n ],\n [\n -87.25433685919877,\n 45.59617874752695\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Koeniga, Lucas D.","contributorId":348678,"corporation":false,"usgs":false,"family":"Koeniga","given":"Lucas D.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":923697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dembkowski, Daniel J.","contributorId":348681,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":923698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Scott P.","contributorId":348684,"corporation":false,"usgs":false,"family":"Hansen","given":"Scott P.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tsehaye, Iyob","contributorId":348687,"corporation":false,"usgs":false,"family":"Tsehaye","given":"Iyob","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923700,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tammie J. Paoli","contributorId":348689,"corporation":false,"usgs":false,"family":"Tammie J. Paoli","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923701,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zorn, Troy G.","contributorId":348692,"corporation":false,"usgs":false,"family":"Zorn","given":"Troy G.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923702,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923703,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70238927,"text":"70238927 - 2022 - Decades of global sturgeon conservation efforts are threatened by an expanding captive culture industry","interactions":[],"lastModifiedDate":"2023-02-14T14:48:20.225927","indexId":"70238927","displayToPublicDate":"2022-12-08T09:50:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Decades of global sturgeon conservation efforts are threatened by an expanding captive culture industry","docAbstract":"

After centuries of overexploitation and habitat loss, many of the world's sturgeon (Acipenseridae) populations are at the brink of extinction. Although significant resources are invested into the conservation and restoration of imperiled sturgeons, the burgeoning commercial culture industry poses an imminent threat to the persistence of many populations. In the past decade, the number and distribution of captive sturgeon facilities has grown exponentially and now encompasses diverse interest groups ranging from hobby aquarists to industrial-scale commercial facilities. Expansion of sturgeon captive culture has largely fallen outside the purview of existing regulatory frameworks, raising concerns that continued growth of this industry has real potential to jeopardize conservation of global sturgeon populations. Here, we highlight some of the most significant threats commercial culture poses to wild populations, with particular emphasis on how releases can accelerate wild population declines through mechanisms such as hybridization, introgression, competition, and disease transmission. We also note that in some circumstances, commercial captive culture has continued to motivate harvest of wild populations, potentially accelerating species' declines. Given the prevalence and trajectory of sturgeon captive culture programs, we comment on modifications to regulatory frameworks that could improve the ability of captive culture to support wild sturgeon conservation.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/fsh.10865","usgsCitation":"White, S.L., Fox, D.A., Beridze, T., Bolden, S.K., Johnson, R.L., Savoy, T.F., Scheele, F., Schreier, A., and Kazyak, D., 2022, Decades of global sturgeon conservation efforts are threatened by an expanding captive culture industry: Fisheries Magazine, v. 48, no. 2, p. 54-61, https://doi.org/10.1002/fsh.10865.","productDescription":"8 p.","startPage":"54","endPage":"61","ipdsId":"IP-139797","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":467139,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/63487","text":"External Repository"},{"id":410632,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fox, Dewayne A.","contributorId":117052,"corporation":false,"usgs":false,"family":"Fox","given":"Dewayne","email":"","middleInitial":"A.","affiliations":[{"id":12970,"text":"Department of Agriculture and Natural Resources, Delaware State University","active":true,"usgs":false}],"preferred":false,"id":859203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beridze, Tamar","contributorId":299977,"corporation":false,"usgs":false,"family":"Beridze","given":"Tamar","email":"","affiliations":[{"id":63351,"text":"Ilia State University","active":true,"usgs":false}],"preferred":false,"id":859204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bolden, Stephania K","contributorId":299978,"corporation":false,"usgs":false,"family":"Bolden","given":"Stephania","email":"","middleInitial":"K","affiliations":[{"id":64993,"text":"NMFS (retired)","active":true,"usgs":false}],"preferred":false,"id":859205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Robin L. 0000-0003-4314-3792 rjohnson1@usgs.gov","orcid":"https://orcid.org/0000-0003-4314-3792","contributorId":224717,"corporation":false,"usgs":true,"family":"Johnson","given":"Robin","email":"rjohnson1@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859206,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Savoy, Thomas F","contributorId":299979,"corporation":false,"usgs":false,"family":"Savoy","given":"Thomas","email":"","middleInitial":"F","affiliations":[{"id":62986,"text":"Connecticut Department of Energy and Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":859207,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Scheele, Fleur","contributorId":299983,"corporation":false,"usgs":false,"family":"Scheele","given":"Fleur","email":"","affiliations":[],"preferred":false,"id":859219,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schreier, Andrea D","contributorId":299980,"corporation":false,"usgs":false,"family":"Schreier","given":"Andrea D","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":859208,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859209,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70238763,"text":"ofr20221088 - 2022 - Assessment of vulnerabilities and opportunities to restore marsh sediment supply at Nisqually River Delta, west-central Washington","interactions":[],"lastModifiedDate":"2022-12-09T20:48:54.83197","indexId":"ofr20221088","displayToPublicDate":"2022-12-08T08:00:44","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1088","displayTitle":"Assessment of Vulnerabilities and Opportunities to Restore Marsh Sediment Supply at Nisqually River Delta, West-Central Washington","title":"Assessment of vulnerabilities and opportunities to restore marsh sediment supply at Nisqually River Delta, west-central Washington","docAbstract":"

A cascading set of hazards to coastal environments is intimately tied to sediment transport and includes the flooding and erosion of shorelines and habitats that support communities, industry, infrastructure, and ecosystem functions (for example, habitats critical to fisheries). This report summarizes modeling and measurement data used to evaluate the sediment budget of the Nisqually River Delta, the vulnerability of the largest estuary restoration project in Puget Sound at the Billy Frank Jr. Nisqually National Wildlife Refuge, and the role of coastal hydrodynamics and potential restoration alternatives for recovering sediment delivery to its marshes. The 2009 Brown’s Farm Restoration achieved many goals toward recovering salmon habitat, but the understanding of the delta and restoration area sediment budgets remain poorly quantified. Specifically, quantitative estimates of the amount of sediment delivered to the delta and restored marsh areas, which had subsided in response to historical diking and draining for grazing, were identified as important information needs. Forecasts of potential outcomes of proposed adaptive distributary channel restoration actions were also prioritized to inform potential solutions. These estimates can be used to evaluate whether sufficient sediment is available for marsh recovery downstream from Alder Lake, which traps about 90 percent the Nisqually River sediment load that could reach the delta. Additionally, quantitative sediment information was identified to help prioritize opportunities to recover and maintain the area marshes and guide ecosystem restoration investments across the delta to reduce the vulnerability of the system to drowning under projected sea level rise.  

A coupled, numerical hydrodynamic-sediment transport model and measurements of the sediment load just upstream from the delta were used to evaluate the (1) availability of sediment for marsh recovery, (2) sediment transport dynamics across the estuary, and (3) potential outcomes of distributary reconnection alternatives under existing and projected conditions of streamflow and sea level. Modeling and measurements indicated that the volume of fluvial sediment load reaching and accumulating in the restoration area ranges from 7 to 32 percent and identified that restoration alternatives could recover about an additional 10–12 percent under current and projected sea-level rise by the year 2100. At these rates of sediment delivery, 85–200+ years may be necessary to fill for marsh vegetation development and maintenance. The model also reveals the sensitivity of sediment transport and accumulation to sediment properties, hydrodynamics, and wave conditions. The low sediment accumulation results in large part because of the role of waves in directing sediment transport offshore and challenges of restoring geomorphic processes suited to maintaining habitat structure where opportunity exists or least conflicts with land use. The findings therefore have implications for siting, phasing, and implementing strategies to route and retain sediment. This study shows that opportunities to recover sediment higher in the tidal prism, where a greater hydraulic gradient and gravity could promote progradation and greater sediment retention, may be more effective than alternatives lower in the tidal prism implemented to date and assessed in this study. Furthermore, the modeling indicates that distributary channel restoration also may provide additional benefits to society by reducing flood stage, and therefore, flood hazards surrounding the delta.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221088","collaboration":"Prepared in cooperation with Nisqually Indian Tribe, U.S. Fish and Wildlife Service, Billy Frank Jr. Nisqually National Wildlife Refuge, and Washington Department of Fish and Wildlife Estuary and Salmon Restoration Program","usgsCitation":"Grossman, E.E., Crosby, S.C., Stevens, A.W., Nowacki, D.J., vanAredonk, N.R., and Curran, C.A., 2022, Assessment of vulnerabilities and opportunities to restore marsh sediment supply at Nisqually River Delta, west-central Washington: U.S. Geological Survey Open-File Report 2022–1088, 50 p., https://doi.org/10.3133/ofr20221088.","productDescription":"Report: ix, 50 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-121432","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":410185,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GF0SG7","text":"USGS data release","description":"USGS data release","linkHelpText":"Stage, water velocity and water quality data collected in the Lower Nisqually River, McAllister Creek and tidal channels of the Nisqually River Delta, Thurston County, Washington, February 11, 2016 to September 18, 2017 (ver. 1.1, December, 2019)"},{"id":410186,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95N6CIT","text":"USGS data release","description":"USGS data release","linkHelpText":"Topobathymetric Model of Puget Sound, Washington, 1887 to 2017"},{"id":410184,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1088/ofr20221088.pdf","text":"Report","size":"32.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1088"},{"id":410183,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1088/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.12450821055306,\n 47.12862354087443\n ],\n [\n -123.12450821055306,\n 45.666890715537136\n ],\n [\n -121.49348505325844,\n 45.666890715537136\n ],\n [\n -121.49348505325844,\n 47.12862354087443\n ],\n [\n -123.12450821055306,\n 47.12862354087443\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

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

","tableOfContents":"","publishedDate":"2022-12-08","noUsgsAuthors":false,"publicationDate":"2022-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":858500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crosby, Sean C. 0000-0002-1499-6836","orcid":"https://orcid.org/0000-0002-1499-6836","contributorId":219466,"corporation":false,"usgs":false,"family":"Crosby","given":"Sean","email":"","middleInitial":"C.","affiliations":[{"id":40000,"text":"Contractor, USGS","active":true,"usgs":false}],"preferred":false,"id":858501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stevens, Andrew W. 0000-0003-2334-129X astevens@usgs.gov","orcid":"https://orcid.org/0000-0003-2334-129X","contributorId":139313,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nowacki, Daniel J. 0000-0002-7015-3710 dnowacki@usgs.gov","orcid":"https://orcid.org/0000-0002-7015-3710","contributorId":174586,"corporation":false,"usgs":true,"family":"Nowacki","given":"Daniel","email":"dnowacki@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":858503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"vanArendonk, Nathan R. 0000-0003-3911-995X","orcid":"https://orcid.org/0000-0003-3911-995X","contributorId":219469,"corporation":false,"usgs":false,"family":"vanArendonk","given":"Nathan","email":"","middleInitial":"R.","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":858504,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858505,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238777,"text":"70238777 - 2022 - Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain","interactions":[],"lastModifiedDate":"2022-12-12T13:54:40.518768","indexId":"70238777","displayToPublicDate":"2022-12-08T07:41:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3554,"text":"The Cryosphere","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain","docAbstract":"

Dynamic natural processes govern snow distribution in mountainous environments throughout the world. Interactions between these different processes create spatially variable patterns of snow depth across a landscape. Variations in accumulation and redistribution occur at a variety of spatial scales, which are well established for moderate mountain terrain. However, spatial patterns of snow depth variability in steep, complex mountain terrain have not been fully explored due to insufficient spatial resolutions of snow depth measurement. Recent advances in uncrewed aerial systems (UASs) and structure from motion (SfM) photogrammetry provide an opportunity to map spatially continuous snow depths at high resolutions in these environments. Using UASs and SfM photogrammetry, we produced 11 snow depth maps at a steep couloir site in the Bridger Range of Montana, USA, during the 2019–2020 winter. We quantified the spatial scales of snow depth variability in this complex mountain terrain at a variety of resolutions over 2 orders of magnitude (0.02 to 20 m) and time steps (4 to 58 d) using variogram analysis in a high-performance computing environment. We found that spatial resolutions greater than 0.5 m do not capture the complete patterns of snow depth spatial variability within complex mountain terrain and that snow depths are autocorrelated within horizontal distances of 15 m at our study site. The results of this research have the potential to reduce uncertainty currently associated with snowpack and snow water resource analysis by documenting and quantifying snow depth variability and snowpack evolution on relatively inaccessible slopes in complex terrain at high spatial and temporal resolutions.

","language":"English","publisher":"Copernicus Journals","doi":"10.5194/tc-16-4907-2022","usgsCitation":"Miller, Z., Peitzsch, E.H., Sproles, E.A., Birkeland, K.W., and Palomaki, R.T., 2022, Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain: The Cryosphere, v. 16, no. 12, p. 4907-4930, https://doi.org/10.5194/tc-16-4907-2022.","productDescription":"24 p.","startPage":"4907","endPage":"4930","ipdsId":"IP-139965","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":445693,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-16-4907-2022","text":"Publisher Index Page"},{"id":435598,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YCIA1R","text":"USGS data release","linkHelpText":"2020 winter timeseries of UAS derived digital surface models (DSMs) from the Hourglass study site, Bridger Mountains, Montana, USA"},{"id":410274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Bridger Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.94,\n 45.84\n ],\n [\n -110.94,\n 45.830\n ],\n [\n -110.93,\n 45.83\n ],\n [\n -110.93,\n 45.84\n ],\n [\n -110.94,\n 45.84\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Zachary 0000-0002-6876-6710","orcid":"https://orcid.org/0000-0002-6876-6710","contributorId":214464,"corporation":false,"usgs":true,"family":"Miller","given":"Zachary","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":858561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peitzsch, Erich H. 0000-0001-7624-0455","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":202576,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":858562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sproles, Eric A. 0000-0003-1245-1653","orcid":"https://orcid.org/0000-0003-1245-1653","contributorId":299760,"corporation":false,"usgs":false,"family":"Sproles","given":"Eric","email":"","middleInitial":"A.","affiliations":[{"id":64943,"text":"Montana State University Earth Sciences Department","active":true,"usgs":false}],"preferred":false,"id":858563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birkeland, Karl W.","contributorId":209943,"corporation":false,"usgs":false,"family":"Birkeland","given":"Karl","email":"","middleInitial":"W.","affiliations":[{"id":38033,"text":"U.S.D.A. Forest Service National Avalanche Center, Bozeman, Montana, USA","active":true,"usgs":false}],"preferred":false,"id":858564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Palomaki, Ross T. 0000-0002-3304-9914","orcid":"https://orcid.org/0000-0002-3304-9914","contributorId":299761,"corporation":false,"usgs":false,"family":"Palomaki","given":"Ross","email":"","middleInitial":"T.","affiliations":[{"id":64943,"text":"Montana State University Earth Sciences Department","active":true,"usgs":false}],"preferred":false,"id":858565,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243187,"text":"70243187 - 2022 - Quantifying permanent uplift due to lithosphere-hotspot interaction","interactions":[],"lastModifiedDate":"2023-05-03T11:51:00.692258","indexId":"70243187","displayToPublicDate":"2022-12-08T06:48:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying permanent uplift due to lithosphere-hotspot interaction","docAbstract":"

Vertical motions that accompany the passage of the lithosphere over a mantle hotspot can shed light on the nature of the hotspot and its effect on the lithosphere. However, quantifying the temporal vertical and spatial extent, is challenging due to the paucity of evidence in the geological record. Here, we utilize dense seismic and well data covering the intersection of the Great Meteor Hotspot (GMH) track with the U.S. Atlantic continental margin to constrain the surface expression of the hotspot passage under the lithosphere. The continuous sedimentary record of the eastern North American margin during its passage over the hotspot allows determination of the timing, magnitude, width and rate of denudation. We find that a ∼300 km wide region was denuded by up to 850 m between ∼97 and 86 Ma, ∼10 m.y. after the passage of the GMH. Stratigraphic relationships suggest a decaying rock uplift rate with time and no subsequent sagging. The broad, long-lasting, and delayed uplift was modeled as a surface manifestation of either sub-lithospheric mantle depletion, permanently eroded base of the continental lithosphere, or intrusions of depleted magma. We consider sub-lithospheric depletion to be the most likely cause, based on seismic imaging results.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022TC007448","usgsCitation":"Lang, G., and ten Brink, U.S., 2022, Quantifying permanent uplift due to lithosphere-hotspot interaction: Tectonics, v. 41, no. 12, e2022TC007448, 16 p., https://doi.org/10.1029/2022TC007448.","productDescription":"e2022TC007448, 16 p.","ipdsId":"IP-138344","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445696,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022tc007448","text":"Publisher Index Page"},{"id":416651,"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 \"coordinates\": [\n [\n [\n -77.6418461037233,\n 46.41102221638212\n ],\n [\n -77.6418461037233,\n 39.63263170609457\n ],\n [\n -64.1048906255545,\n 39.63263170609457\n ],\n [\n -64.1048906255545,\n 46.41102221638212\n ],\n [\n -77.6418461037233,\n 46.41102221638212\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Lang, Guy","contributorId":304702,"corporation":false,"usgs":false,"family":"Lang","given":"Guy","email":"","affiliations":[{"id":66147,"text":"Dept. of Marine Geosciences, University of Haifa","active":true,"usgs":false}],"preferred":false,"id":871409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"ten Brink, Uri S. 0000-0001-6858-3001","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":201741,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri","email":"","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":871410,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238840,"text":"70238840 - 2022 - Working toward a National Coordinated Soil Moisture Monitoring Network: Vision, progress, and future directions","interactions":[],"lastModifiedDate":"2022-12-14T12:38:35.379339","indexId":"70238840","displayToPublicDate":"2022-12-08T06:36:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"Working toward a National Coordinated Soil Moisture Monitoring Network: Vision, progress, and future directions","docAbstract":"

Soil moisture is a critical land surface variable, impacting the water, energy, and carbon cycles. While in situ soil moisture monitoring networks are still developing, there is no cohesive strategy or framework to coordinate, integrate, or disseminate these diverse data sources in a synergistic way that can improve our ability to understand climate variability at the national, state, and local levels. Thus, a national strategy is needed to guide network deployment, sustainable network operation, data integration and dissemination, and user-focused product development. The National Coordinated Soil Moisture Monitoring Network (NCSMMN) is a federally led, multi-institution effort that aims to address these needs by capitalizing on existing wide-ranging soil moisture monitoring activities, increasing the utility of observational data, and supporting their strategic application to the full range of decision-making needs. The goals of the NCSMMN are to 1) establish a national “network of networks” that effectively demonstrates data integration and operational coordination of diverse in situ networks; 2) build a community of practice around soil moisture measurement, interpretation, and application—a “network of people” that links data providers, researchers, and the public; and 3) support research and development (R&D) on techniques to merge in situ soil moisture data with remotely sensed and modeled hydrologic data to create user-friendly soil moisture maps and associated tools. The overarching mission of the NCSMMN is to provide coordinated high-quality, nationwide soil moisture information for the public good by supporting applications like drought and flood monitoring, water resource management, agricultural and forestry planning, and fire danger ratings.

","language":"English","publisher":"American Meteorology Society","doi":"10.1175/BAMS-D-21-0178.1","usgsCitation":"Baker, C.B., Cosh, M.H., Bolten, J., Brusberg, M., Caldwell, T., Connolly, S., Dobreva, I., Edwards, N., Goble, P.E., Ochsner, T.E., Quiring, S.M., Robotham, M., Skumanich, M., Svoboda, M., White, W.A., and Woloszyn, M., 2022, Working toward a National Coordinated Soil Moisture Monitoring Network: Vision, progress, and future directions: Bulletin of the American Meteorological Society, v. 103, no. 12, p. E2719-E2732, https://doi.org/10.1175/BAMS-D-21-0178.1.","productDescription":"14 p,","startPage":"E2719","endPage":"E2732","ipdsId":"IP-138457","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":445699,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1175/bams-d-21-0178.1","text":"External Repository"},{"id":410457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baker, C. Bruce","contributorId":299861,"corporation":false,"usgs":false,"family":"Baker","given":"C.","email":"","middleInitial":"Bruce","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":858871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cosh, Michael H.","contributorId":146998,"corporation":false,"usgs":false,"family":"Cosh","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":858872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bolten, John","contributorId":299863,"corporation":false,"usgs":false,"family":"Bolten","given":"John","email":"","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":858873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brusberg, Mark","contributorId":299864,"corporation":false,"usgs":false,"family":"Brusberg","given":"Mark","email":"","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":858874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caldwell, Todd 0000-0003-4068-0648","orcid":"https://orcid.org/0000-0003-4068-0648","contributorId":217924,"corporation":false,"usgs":true,"family":"Caldwell","given":"Todd","email":"","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Connolly, Stephanie","contributorId":299866,"corporation":false,"usgs":false,"family":"Connolly","given":"Stephanie","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":858876,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dobreva, Iliyana","contributorId":299868,"corporation":false,"usgs":false,"family":"Dobreva","given":"Iliyana","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":858877,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Edwards, Nathan","contributorId":260132,"corporation":false,"usgs":false,"family":"Edwards","given":"Nathan","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":858878,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Goble, Peter E.","contributorId":299870,"corporation":false,"usgs":false,"family":"Goble","given":"Peter","email":"","middleInitial":"E.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":858879,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ochsner, Tyson E.","contributorId":299872,"corporation":false,"usgs":false,"family":"Ochsner","given":"Tyson","email":"","middleInitial":"E.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":858880,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Quiring, Steven M.","contributorId":299874,"corporation":false,"usgs":false,"family":"Quiring","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":858881,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Robotham, Michael","contributorId":299876,"corporation":false,"usgs":false,"family":"Robotham","given":"Michael","email":"","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":858882,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Skumanich, Marina","contributorId":260137,"corporation":false,"usgs":false,"family":"Skumanich","given":"Marina","email":"","affiliations":[{"id":52519,"text":"NOAA National Integrated Drought Information System","active":true,"usgs":false}],"preferred":false,"id":858883,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Svoboda, Mark","contributorId":192357,"corporation":false,"usgs":false,"family":"Svoboda","given":"Mark","email":"","affiliations":[],"preferred":false,"id":858884,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"White, W. Alex","contributorId":299878,"corporation":false,"usgs":false,"family":"White","given":"W.","email":"","middleInitial":"Alex","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":858885,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Woloszyn, Molly","contributorId":260136,"corporation":false,"usgs":false,"family":"Woloszyn","given":"Molly","email":"","affiliations":[{"id":52519,"text":"NOAA National Integrated Drought Information System","active":true,"usgs":false}],"preferred":false,"id":858886,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70238769,"text":"70238769 - 2022 - Physical controls on the hydrology of perennially ice-covered lakes, Taylor Valley, Antarctica (1996-2013)","interactions":[],"lastModifiedDate":"2022-12-15T16:05:28.641938","indexId":"70238769","displayToPublicDate":"2022-12-07T06:43:08","publicationYear":"2022","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":"Physical controls on the hydrology of perennially ice-covered lakes, Taylor Valley, Antarctica (1996-2013)","docAbstract":"

The McMurdo Dry Valleys, Antarctica, are a polar desert populated with numerous closed-watershed, perennially ice-covered lakes primarily fed by glacial melt. Lake levels have varied by as much as 8 m since 1972 and are currently rising after a decade of decreasing. Precipitation falls as snow, so lake hydrology is dominated by energy available to melt glacier ice and to sublimate lake ice. To understand the energy and hydrologic controls on lake level changes and to explain the variability between neighboring lakes, only a few kilometers apart, we model the hydrology for the three largest lakes in Taylor Valley. We apply a physically based hydrological model that includes a surface energy balance model to estimate glacial melt and lake sublimation to constrain mass fluxes to and from the lakes. Results show that lake levels are very sensitive to small changes in glacier albedo, air temperature, and wind speed. We were able to balance the hydrologic budget in two watersheds using meltwater inflow and sublimation loss from the ice-covered lake alone. A third watershed, closest to the coast, required additional inflow beyond model uncertainties. We hypothesize a shallow groundwater system within the active layer, fed by dispersed snow patches, contributes 23% of the inflow to this watershed. The lakes are out of equilibrium with the current climate. If the climate of our study period (1996-2013) persists into the future, the lakes will reach equilibrium starting in 2300, with levels 2-17 m higher, depending on the lake, relative to the 2020 level.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JF006833","usgsCitation":"Cross, J., Fountain, A., Hoffman, M., and Obryk, M., 2022, Physical controls on the hydrology of perennially ice-covered lakes, Taylor Valley, Antarctica (1996-2013): JGR Earth Surface, v. 127, no. 12, e2022JF006833, 20 p., https://doi.org/10.1029/2022JF006833.","productDescription":"e2022JF006833, 20 p.","ipdsId":"IP-143444","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445703,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1903551","text":"External Repository"},{"id":410194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Taylor Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 164,\n -77\n ],\n [\n 160,\n -77\n ],\n [\n 160,\n -78\n ],\n [\n 164,\n -78\n ],\n [\n 164,\n -77\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Cross, Julian 0000-0001-7209-119X","orcid":"https://orcid.org/0000-0001-7209-119X","contributorId":299754,"corporation":false,"usgs":false,"family":"Cross","given":"Julian","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":858532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fountain, Andrew","contributorId":299755,"corporation":false,"usgs":false,"family":"Fountain","given":"Andrew","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":858533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoffman, Matthew 0000-0001-5076-0540","orcid":"https://orcid.org/0000-0001-5076-0540","contributorId":299756,"corporation":false,"usgs":false,"family":"Hoffman","given":"Matthew","email":"","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":858534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Obryk, Maciej K. 0000-0002-8182-8656","orcid":"https://orcid.org/0000-0002-8182-8656","contributorId":203477,"corporation":false,"usgs":true,"family":"Obryk","given":"Maciej","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":858535,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269048,"text":"70269048 - 2022 - The Pondosa fault zone: A distributed dextral-normal-oblique fault system in northeastern California, USA","interactions":[],"lastModifiedDate":"2025-07-15T16:49:27.549522","indexId":"70269048","displayToPublicDate":"2022-12-07T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"The Pondosa fault zone: A distributed dextral-normal-oblique fault system in northeastern California, USA","docAbstract":"

The tectonic domains of Basin and Range extension, Cascadia subduction zone contraction, and Walker Lane dextral transtension converge in the Mushroom Rock region of northeastern California, USA. We combined analysis of high-resolution topographic data, bedrock mapping, 40Ar/39Ar geochronology, low-temperature thermochronology, and existing geologic and fault mapping to characterize an extensive dextral-normal-oblique fault system called the Pondosa fault zone. This fault zone extends north-northwest from the Pit River east of Soldier Mountain, California, into moderately high-relief volcanic topography as far north as the Bartle (California) townsite with normal and dextral offset apparent in geomorphology and fault exposures. New and existing 40Ar/39Ar and radiocarbon dating of offset lava flows provides ages of 12.4 ka to 9.6 Ma for late Cenozoic stratigraphic units. Scarp morphology and geomorphic expression indicate that the fault system was active in the late Pleistocene. The Pondosa fault zone may represent a dextral-oblique accommodation zone between north-south–oriented Basin and Range extensional fault systems and/or part of the Sierra Nevada–Oregon Coast block microplate boundary.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02450.1","usgsCitation":"Jobe, J.A., Briggs, R.W., Gold, R.D., DeLong, S.B., Hille, M., Delano, J., Johnstone, S., Pickering, A., Phillips, R., and Calvert, A.T., 2022, The Pondosa fault zone: A distributed dextral-normal-oblique fault system in northeastern California, USA: Geosphere, v. 19, no. 1, p. 179-205, https://doi.org/10.1130/GES02450.1.","productDescription":"27 p.","startPage":"179","endPage":"205","ipdsId":"IP-137700","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":492497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02450.1","text":"Publisher Index Page"},{"id":492284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"eastern California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.27831636230019,\n 41.12301709043055\n ],\n [\n -122.27831636230019,\n 39.963081252129996\n ],\n [\n -120.53795346715106,\n 39.963081252129996\n ],\n [\n -120.53795346715106,\n 41.12301709043055\n ],\n [\n -122.27831636230019,\n 41.12301709043055\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson Jobe, Jessica A. 0000-0001-5574-4523","orcid":"https://orcid.org/0000-0001-5574-4523","contributorId":295377,"corporation":false,"usgs":true,"family":"Thompson Jobe","given":"Jessica","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science 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0000-0002-0945-2172 sdelong@usgs.gov","orcid":"https://orcid.org/0000-0002-0945-2172","contributorId":5240,"corporation":false,"usgs":true,"family":"DeLong","given":"Stephen","email":"sdelong@usgs.gov","middleInitial":"B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":943091,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hille, Madeline 0000-0001-7240-8214","orcid":"https://orcid.org/0000-0001-7240-8214","contributorId":315582,"corporation":false,"usgs":false,"family":"Hille","given":"Madeline","email":"","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":943092,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delano, Jaime 0000-0003-2601-2600","orcid":"https://orcid.org/0000-0003-2601-2600","contributorId":225594,"corporation":false,"usgs":false,"family":"Delano","given":"Jaime","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":943093,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":943094,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pickering, Alexandra 0000-0002-1281-6117","orcid":"https://orcid.org/0000-0002-1281-6117","contributorId":329929,"corporation":false,"usgs":false,"family":"Pickering","given":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":943095,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Phillips, Rachel","contributorId":341951,"corporation":false,"usgs":false,"family":"Phillips","given":"Rachel","affiliations":[{"id":81813,"text":"Department of Geological Sciences, The University of Texas El Paso, El Paso, TX","active":true,"usgs":false}],"preferred":false,"id":943096,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":943097,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70238730,"text":"70238730 - 2022 - Climate-modulated range expansion of reef-building coral communities off southeast Florida during the late Holocene","interactions":[],"lastModifiedDate":"2022-12-07T12:50:48.189461","indexId":"70238730","displayToPublicDate":"2022-12-06T06:46:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Climate-modulated range expansion of reef-building coral communities off southeast Florida during the late Holocene","docAbstract":"

The Holocene reefs off southeast Florida provide unique insights into the biogeographical and ecological response of western Atlantic coral reefs to past climate change that can be used to evaluate future climate impacts. However, previous studies have focused on millennial-scale change during the stable mid-Holocene, making it difficult to make inferences about the impact of shorter-term variability that is relevant to modern climate warming. Using uranium-series dating of newly discovered subfossil coral rubble deposits, we establish a new high-resolution record of coral community development off southeast Florida during a period of variable climate in the late Holocene. Our results indicate that coral communities dominated by reef-building Acropora palmata and Orbicella spp. persisted in the nearshore environments off southeast Florida ~75 km north of their primary historical ranges between ~3500 and 1800 years before present. This timing coincides with regional warming at the northern extent of the Atlantic Warm Pool, suggesting a likely link between regional oceanographic climate and the expansion of cold-sensitive reef-building coral communities to the high-latitude reefs off southeast Florida. These findings not only extend the record of coral-reef development in southeast Florida into the late Holocene, but they also have important implications for future range expansions of reef-building coral communities in response to modern climate change.

","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2022.995256","usgsCitation":"Modys, A.B., Olenik, A.E., Mortlock, R.A., Toth, L., and Precht, W.F., 2022, Climate-modulated range expansion of reef-building coral communities off southeast Florida during the late Holocene: Frontiers in Marine Science, v. 9, 995256, 10 p., https://doi.org/10.3389/fmars.2022.995256.","productDescription":"995256, 10 p.","ipdsId":"IP-143123","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445708,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2022.995256","text":"Publisher Index Page"},{"id":410153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.44712094032758,\n 26.986269004281183\n ],\n [\n -80.44712094032758,\n 24.922752022261463\n ],\n [\n -79.72233108803808,\n 24.922752022261463\n ],\n [\n -79.72233108803808,\n 26.986269004281183\n ],\n [\n -80.44712094032758,\n 26.986269004281183\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2022-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Modys, Alex B.","contributorId":299717,"corporation":false,"usgs":false,"family":"Modys","given":"Alex","email":"","middleInitial":"B.","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":858436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olenik, Anton E.","contributorId":260617,"corporation":false,"usgs":false,"family":"Olenik","given":"Anton","email":"","middleInitial":"E.","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":858437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mortlock, Richard A.","contributorId":299718,"corporation":false,"usgs":false,"family":"Mortlock","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":858438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Precht, William F. 0000-0002-6546-985X","orcid":"https://orcid.org/0000-0002-6546-985X","contributorId":260614,"corporation":false,"usgs":false,"family":"Precht","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":52621,"text":"Dial Cordy & Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":858440,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237589,"text":"70237589 - 2022 - Defining the Hoek-Brown constant mi for volcanic lithologies","interactions":[],"lastModifiedDate":"2023-01-10T16:30:36.565423","indexId":"70237589","displayToPublicDate":"2022-12-05T11:49:27","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"displayTitle":"Defining the Hoek-Brown constant mi for volcanic lithologies","title":"Defining the Hoek-Brown constant mi for volcanic lithologies","docAbstract":"The empirical Hoek-Brown failure criterion is a well-known and commonly used failure criterion for both intact rocks and rock masses, especially in geological engineering. The intact criterion is calculated using experimental triaxial compression test results on intact samples while the rock mass criterion modifies the intact strength using quantified measures of the rock mass quality. The Hoek-Brown failure criterion includes a fitting constant for intact rocks, mi, which controls the steepness and curvature of the failure envelope, and is derived from curve-fitting the failure criterion to triaxial test data. However, because of the existence of tabulated mi values for various rock types, calculated using 1000’s of triaxial experiments, mi values are often extracted from the tables in the literature rather than the more time- and resource-intensive triaxial experiments. Using 100’s of triaxial experiments on variously altered volcanic rocks from volcanoes around the world, we demonstrate that mi varies dramatically based on a complex combination of alteration, lithology and texture, for example ranging from 2-38 for andesites. In contrast, tabulated estimates are typically given as small ranges, for example 25±5 for andesite. This means the failure criteria for volcanic rocks based on tabulated estimates could significantly over or under predict the intact strength, and thereby the rock mass strength, causing errors for stability and deformation assessments for a variety of volcanological and geological engineering purposes, from dome deformation or flank stability to excavation in volcanic rocks. In this research we not only highlight the high variability of mi for volcanic rocks, but by building on published relationships between porosity and strength, we demonstrate that it too is sensitive to porosity. We propose a number of preliminary methods to constrain mi values, including one using porosity.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Rock mechanics and engineering geology in volcanic fields","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"5th International Workshop on Rock Mechanics and Engineering Geology in Volcanic Fields","conferenceDate":"September 9-10, 2021","conferenceLocation":"Fukuoka, Japan","language":"English","publisher":"CRC Press","usgsCitation":"Villeneuve, M., Heap, M.J., and Schaefer, L.N., 2022, Defining the Hoek-Brown constant mi for volcanic lithologies, in Rock mechanics and engineering geology in volcanic fields, Fukuoka, Japan, September 9-10, 2021, p. 261-268.","productDescription":"8 p.","startPage":"261","endPage":"268","ipdsId":"IP-135372","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409800,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/books/edit/10.1201/9781003293590/rock-mechanics-engineering-geology-volcanic-fields-takehiro-ohta-takatoshi-ito-masahiko-osada","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Villeneuve, Marlène C.","contributorId":260116,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Marlène C.","affiliations":[{"id":52510,"text":"Chair of Subsurface Engineering, Montanuniversität Leoben, Leoben, Austria","active":true,"usgs":false}],"preferred":false,"id":854543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heap, Michael J. 0000-0002-4748-735X","orcid":"https://orcid.org/0000-0002-4748-735X","contributorId":297882,"corporation":false,"usgs":false,"family":"Heap","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":64429,"text":"Université de Strasbourg","active":true,"usgs":false}],"preferred":false,"id":854544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":854545,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263091,"text":"70263091 - 2022 - Drivers of habitat quality for a reintroduced elk herd","interactions":[],"lastModifiedDate":"2025-01-29T15:09:39.072874","indexId":"70263091","displayToPublicDate":"2022-12-05T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of habitat quality for a reintroduced elk herd","docAbstract":"

Understanding spatiotemporal variation in habitat quality is essential for guiding wildlife reintroduction and restoration programs. The habitat productivity hypothesis posits that home range size is inversely related to habitat quality. Thus, home range size may be used as a proxy for habitat quality and can identify important land cover features for a recovering species. We sought to quantify variation in home range size across the biological cycle (seasons) for a reintroduced elk (Cervus canadensis) population in southwestern Virginia, USA and quantify habitat quality by linking home range sizes to the land cover types they contain using linear mixed-effects models. We found mean home range size was largest during late gestation for female elk. Additionally, throughout the year, smaller home ranges were associated with larger proportions of non-forested habitats whereas forested habitats were generally the opposite. However, both presumed poor- and high-quality habitats influenced female elk space use. Our approach revealed spatial variation in habitat quality for a recovering elk herd, demonstrated the importance of non-forested habitats to elk, can guide decisions regarding the location of future elk reintroduction programs, and serve as a model for evaluating habitat quality associated with wildlife reintroductions.

","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-022-25058-9","usgsCitation":"Quinlan, B., Rosenberger, J., Kalb, D., Abernathy, H., Thorne, E., Ford, W., and Cherry, M., 2022, Drivers of habitat quality for a reintroduced elk herd: Scientific Reports, v. 12, 20960, 12 p., https://doi.org/10.1038/s41598-022-25058-9.","productDescription":"20960, 12 p.","ipdsId":"IP-142591","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-25058-9","text":"Publisher Index Page"},{"id":481447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"southwestern Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.81797132520401,\n 37.10392995435147\n ],\n [\n -83.4791350332288,\n 36.59438261785931\n ],\n [\n -80.45872432537026,\n 36.57458088905058\n ],\n [\n -80.9768195014316,\n 37.315441708410084\n ],\n [\n -81.71516471822216,\n 37.318178569421775\n ],\n [\n -81.94847969969248,\n 37.58994839228791\n ],\n [\n -82.81797132520401,\n 37.10392995435147\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Quinlan, Braiden A.","contributorId":350149,"corporation":false,"usgs":false,"family":"Quinlan","given":"Braiden A.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":925498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Jacalyn P.","contributorId":350150,"corporation":false,"usgs":false,"family":"Rosenberger","given":"Jacalyn P.","affiliations":[{"id":56188,"text":"Virginia Department of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":925499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kalb, David M.","contributorId":350151,"corporation":false,"usgs":false,"family":"Kalb","given":"David M.","affiliations":[{"id":39552,"text":"Rhode Island Department of Environmental Management","active":true,"usgs":false}],"preferred":false,"id":925500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abernathy, Heather N.","contributorId":350220,"corporation":false,"usgs":false,"family":"Abernathy","given":"Heather N.","affiliations":[{"id":13724,"text":"Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":925501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorne, Emily D.","contributorId":350153,"corporation":false,"usgs":false,"family":"Thorne","given":"Emily D.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":925502,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":925503,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cherry, Michael J.","contributorId":350156,"corporation":false,"usgs":false,"family":"Cherry","given":"Michael J.","affiliations":[{"id":13724,"text":"Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":925504,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70238881,"text":"70238881 - 2022 - Optimizing Landsat Next shortwave infrared bands for crop residue characterization","interactions":[],"lastModifiedDate":"2022-12-15T13:48:36.566374","indexId":"70238881","displayToPublicDate":"2022-12-03T07:44:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing Landsat Next shortwave infrared bands for crop residue characterization","docAbstract":"

This study focused on optimizing the placement of shortwave infrared (SWIR) bands for pixel-level estimation of fractional crop residue cover (fR) for the upcoming Landsat Next mission. We applied an iterative wavelength shift approach to a database of crop residue field spectra collected in Beltsville, Maryland, USA (n = 916) and computed generalized two- and three-band spectral indices for all wavelength combinations between 2000 and 2350 nm, then used these indices to model field-measured fR. A subset of the full dataset with a Normalized Difference Vegetation Index (NDVI) < 0.3 threshold (n = 643) was generated to evaluate green vegetation impacts on fR estimation. For the two-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized normalized difference using 2226 nm and 2263 nm bands produced the top fR estimation performance (R2 = 0.8222; RMSE = 0.1296). These findings were similar to the established two-band Shortwave Infrared Normalized Difference Residue Index (SINDRI) (R2 = 0.8145; RMSE = 0.1324). Performance of the two-band generalized normalized difference and SINDRI decreased for the full-NDVI dataset (R2 = 0.5865 and 0.4144, respectively). For the three-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized ratio-based index with a 2031–2085–2216 nm band combination, closely matching established Cellulose Absorption Index (CAI) bands, was top performing (R2 = 0.8397; RMSE = 0.1231). Three-band indices with CAI-type wavelengths maintained top fR estimation performance for the full-NDVI dataset with a 2036–2111–2217 nm band combination (R2 = 0.7581; RMSE = 0.1548). The 2036–2111–2217 nm band combination was also top performing in fR estimation (R2 = 0.8690; RMSE = 0.0970) for an additional analysis assessing combined green vegetation cover and surface moisture effects. Our results indicate that a three-band configuration with band centers and wavelength tolerances of 2036 nm (±5 nm), 2097 nm (±14 nm), and 2214 (±11 nm) would optimize Landsat Next SWIR bands for fR estimation.

","language":"English","publisher":"MDPI","doi":"10.3390/rs14236128","usgsCitation":"Lamb, B.T., Dennison, P., Hively, W.D., Kokaly, R.F., Serbin, G., Wu, Z., Dabney, P.W., Masek, J.G., Campbell, M., and Daughtry, C.S., 2022, Optimizing Landsat Next shortwave infrared bands for crop residue characterization: Remote Sensing, v. 14, no. 23, 6128, 29 p., https://doi.org/10.3390/rs14236128.","productDescription":"6128, 29 p.","ipdsId":"IP-144753","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":445721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14236128","text":"Publisher Index Page"},{"id":410537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"23","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamb, Brian T. 0000-0001-7957-5488","orcid":"https://orcid.org/0000-0001-7957-5488","contributorId":291893,"corporation":false,"usgs":true,"family":"Lamb","given":"Brian","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennison, Phillip 0000-0002-0241-1917","orcid":"https://orcid.org/0000-0002-0241-1917","contributorId":266031,"corporation":false,"usgs":false,"family":"Dennison","given":"Phillip","email":"","affiliations":[{"id":54865,"text":"Dept. Geography, Utah State University","active":true,"usgs":false}],"preferred":false,"id":859053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":859054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":859055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Serbin, Guy 0000-0001-9345-1772","orcid":"https://orcid.org/0000-0001-9345-1772","contributorId":266030,"corporation":false,"usgs":false,"family":"Serbin","given":"Guy","email":"","affiliations":[{"id":54864,"text":"EOAnalytics","active":true,"usgs":false}],"preferred":false,"id":859056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":859057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dabney, Philip W.","contributorId":214572,"corporation":false,"usgs":false,"family":"Dabney","given":"Philip","email":"","middleInitial":"W.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Masek, Jeffery G.","contributorId":294418,"corporation":false,"usgs":false,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859059,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Campbell, Michael","contributorId":299937,"corporation":false,"usgs":false,"family":"Campbell","given":"Michael","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":859060,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Daughtry, Craig S. T.","contributorId":211093,"corporation":false,"usgs":false,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S. T.","affiliations":[{"id":38179,"text":"USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":859061,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70271307,"text":"70271307 - 2022 - Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits","interactions":[],"lastModifiedDate":"2025-09-08T14:03:52.052483","indexId":"70271307","displayToPublicDate":"2022-12-03T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2746,"text":"Mineralium Deposita","active":true,"publicationSubtype":{"id":10}},"title":"Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits","docAbstract":"

The North Australian Zinc Belt is the largest zinc-lead province in the world, containing three of the ten largest known individual deposits (HYC, Hilton-George Fisher, and Mount Isa). The Northern Cordillera in North America is the second largest zinc-lead province, containing a further two of the world’s top ten deposits (Red Dog and Howards Pass). Despite this world-class endowment, exploration in both mineral provinces during the past 2 decades has not been particularly successful, yielding only two significant discoveries (Teena, Australia, and Boundary, Canada). One of the most important aspects of exploration is to choose mineral provinces and districts within geological belts that have the greatest potential for discovery. Here, we present results from these two zinc belts that highlight previously unused datasets for area selection and targeting. Lead isotope mapping using analyses of mineralized material has identified gradients in μ (238U/204Pb) that coincide closely with many major deposits. Locations of these deposits also coincide with a gradient in the depth of the lithosphere-asthenosphere boundary determined from calibrated surface wave tomography models converted to temperature. Furthermore, gradients in upward-continued gravity anomalies and a step in Moho depth correspond to a pre-existing major crustal boundary in both zinc belts. A spatial association of deposits with a linear mid- to lower-crustal resistivity anomaly from magnetotelluric data is also observed in the North Australian Zinc Belt. The change from thicker to thinner lithosphere is interpreted to localize prospective basins for zinc-lead mineralization and to control the gradient in lead isotope and geophysical data. These data, when combined with data indicative of paleoenvironment and changes in plate motion at the time of mineralization, provide new exploration criteria that can be used to identify prospective mineralized basins and define the most favorable parts of these basins.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s00126-022-01153-9","usgsCitation":"Huston, D.L., Champion, D.C., Czarnota, K., Duan, J., Hutchens, M., Paradis, S., Hoggard, M., Ware, B., Gibson, G.M., Doublier, M.P., Kelley, K.D., McCafferty, A.E., Hayward, N., Richards, F., Tessalina, S., and Carr, G., 2022, Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits: Mineralium Deposita, v. 58, p. 707-729, https://doi.org/10.1007/s00126-022-01153-9.","productDescription":"23 p.","startPage":"707","endPage":"729","ipdsId":"IP-135613","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495149,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495180,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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Fred","contributorId":360921,"corporation":false,"usgs":false,"family":"Richards","given":"Fred","affiliations":[],"preferred":false,"id":947923,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tessalina, Svetlana","contributorId":360922,"corporation":false,"usgs":false,"family":"Tessalina","given":"Svetlana","affiliations":[],"preferred":false,"id":947924,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Carr, Graham","contributorId":360923,"corporation":false,"usgs":false,"family":"Carr","given":"Graham","affiliations":[],"preferred":false,"id":947925,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70238684,"text":"70238684 - 2022 - Can we avert an Amazon tipping point? The economic and environmental costs","interactions":[],"lastModifiedDate":"2022-12-05T12:37:03.967845","indexId":"70238684","displayToPublicDate":"2022-12-02T06:32:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Can we avert an Amazon tipping point? The economic and environmental costs","docAbstract":"

The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.

","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/aca3b8","usgsCitation":"Banerjee, O., Cicowiez, M., Macedo, M., Malek, Z., Verburg, P.H., Goodwin, S., Vargas, R., Rattis, L., Bagstad, K.J., Brando, P.M., Coe, M.T., Neill, C., Damiani Marti, O., and Avila Murillo, J., 2022, Can we avert an Amazon tipping point? 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Mitigating risk to migratory birds from energy development requires information on the distribution and abundance of seabirds in offshore waters. Seabirds are highly mobile, with species-specific seasonal migrations that result in variable patterns of distribution in space and time. In remote offshore marine areas, obtaining useful and current information on resources is difficult to achieve and maintain, both fiscally and logistically, necessitating collaborative effort (Danielson et al. 2022). We used seabird at-sea survey data (2007-2021) and new modeling techniques to develop spatio-temporal models of seasonal abundance and distribution of species in waters of the Pacific Arctic. For six species groups selected as model test cases, we identified fine-scale distributions for each year, using data collected during summer to early fall (June through September). Our approach uses the best available data and can be updated as new data are generated, providing up-to-date information for regions with existing or potential future oil and gas development.

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