In 2021, the U.S. Geological Survey (USGS), in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board, studied floods to produce a library of flood-inundation maps for the Sabinal River near Utopia, Texas. Digital flood-inundation maps were created for a 10-mile reach of the Sabinal River from USGS streamgage 08197936 Sabinal River below Mill Creek near Vanderpool, Tex., at the upstream boundary of the study reach, to USGS streamgage 08197970 Sabinal River at Utopia, Tex. (hereinafter referred to as the “Utopia gage”), at the downstream boundary of the study reach, and for a 7-mile reach of the West Sabinal River. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to selected gage heights (the water-surface elevation at a streamgage, commonly referred to as “stage”) at the Utopia gage. Water-surface elevations were computed for the stream reach by means of a two-dimensional unsteady-state diffusion wave model with the U.S. Army Corps of Engineers Hydrologic Engineering Center River Analysis System program. A synthetic stage-discharge rating curve at the Utopia gage was developed using a regional regression equation to construct the model boundary condition inputs, and the upper bound of the stage-discharge relation was matched to a major flood event in July 2002. The hydraulic model was used to compute water-surface elevations for 35 stages at 0.5-foot (ft) increments referenced to the Utopia gage datum and ranging from 11 ft (near bankfull) to 28 ft (estimated peak stage during the July 2002 flood event). These flood-inundation maps, in conjunction with the real-time stage data from the Utopia gage, are intended to help guide the public in taking individual safety precautions and provide emergency management personnel with a tool to efficiently manage emergency flood operations and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235001","issn":"2328-0328 (online)","collaboration":"Prepared in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board","usgsCitation":"Choi, N., 2023, Flood-inundation maps created using a synthetic rating curve for a 10-mile reach of the Sabinal River and a 7-mile reach of the West Sabinal River near Utopia, Texas, 2021 (ver. 2.0, September 2023): U.S. Geological Survey Scientific Investigations Report 2023–5001, 18 p., https://doi.org/10.3133/sir20235001.","productDescription":"Report: viii, 18 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-136311","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":435168,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CIK9ZF","text":"USGS data release","linkHelpText":"Geospatial and model dataset for flood-Inundation maps in a 10-mile reach of the Sabinal River and a 7-mile reach of the West Sabinal River near Utopia, Texas, 2021"},{"id":421129,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5001/coverthb.jpg"},{"id":500486,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114428.htm","linkFileType":{"id":5,"text":"html"}},{"id":421198,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20233001","text":"Fact Sheet 2023–3001","description":"USGS Fact Sheet 2023–3001","linkHelpText":"- Flood Warning Toolset for the Sabinal River Near Utopia, Texas"},{"id":421197,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2023/5001/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2023-5001 version history"},{"id":421196,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5001/sir20235001.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5001 XML"},{"id":421193,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5001/images"},{"id":421599,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235001/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5001 HTML"},{"id":421194,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5001/sir20235001.pdf","text":"Report","size":"2.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5001"}],"country":"United States","state":"Texas","city":"Utopia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.38878556700459,\n 29.515266260991964\n ],\n [\n -99.38878556700459,\n 29.797981198043047\n ],\n [\n -99.67156342604174,\n 29.797981198043047\n ],\n [\n -99.67156342604174,\n 29.515266260991964\n ],\n [\n -99.38878556700459,\n 29.515266260991964\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: February 2023; Version 2.0: September 2023","contact":"Director, Oklahoma-Texas Water Science Center
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The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 2 (April–June) of 2023. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was a Landsat 8 Thermal Infrared Sensor (TIRS) Scene Select Mechanism (SSM) excursion anomaly. On April 21, 2023, a TIRS SSM excursion error flag was indicated in telemetry during a calibration activity when the SSM encoder was powered on and the mirror was between the nadir position and the deep space position. An initial recovery plan indicated the SSM was moving erratically, so the instrument was put into a safe state for additional troubleshooting. A second recovery plan was developed and successfully executed on April 23, 2023. Additional information about the Landsat 8 TIRS SSM excursion anomaly is available at https://www.usgs.gov/landsat-missions/news/landsat-8-level-1-product-processing-resumes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231075","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T.Z., Shaw, J.L., Denevan, A., Franks, S., Ruslander, K., Micijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., Miller, J., and Ding, L., 2023, ECCOE Landsat quarterly Calibration and Validation report—Quarter 2, 2023: U.S. Geological Survey Open-File Report 2023–1075, 39 p., https://doi.org/10.3133/ofr20231075.","productDescription":"Report: vii, 39 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154779","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":421208,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":421207,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1075/images/"},{"id":421206,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1075/ofr20231075.XML","linkFileType":{"id":8,"text":"xml"}},{"id":421209,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231075/full","linkFileType":{"id":5,"text":"html"}},{"id":421204,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1075/coverthb.jpg"},{"id":421205,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1075/ofr20231075.pdf","text":"Report","size":"126 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1075"}],"contact":"Director, Earth Resources Observation and Science Center
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47914 252nd Street
Sioux Falls, SD 57198
No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Cooperative Science and Monitoring Initiative (CSMI) Lake Huron 2017 final report","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Cooperative Science and Monitoring Initiative (CSMI)","usgsCitation":"Esselman, P., Hondorp, D.W., Roseman, E., Nevers, M., Wills, T., and Riley, S., 2023, Development of an integrated survey design to assess invasive round goby abundance and distribution across gradients in substrate and depth, in Cooperative Science and Monitoring Initiative (CSMI) Lake Huron 2017 final report, p. 245-263.","productDescription":"19 p.","startPage":"245","endPage":"263","ipdsId":"IP-119012","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":425802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":425801,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://greatlakescsmi.org/publications/23718/","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"Lake Huron, Thunder Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.26748319036578,\n 45.023341671651394\n ],\n [\n -83.37733171507917,\n 45.07966771596739\n ],\n [\n -83.44109098841496,\n 45.060880623088025\n ],\n [\n -83.4587983735888,\n 44.981984039965994\n ],\n [\n -83.42692382572686,\n 44.911772535907375\n ],\n [\n -83.26039618877164,\n 44.810053772517335\n ],\n [\n -82.78202358114997,\n 44.55558835438245\n ],\n [\n -82.57118528371684,\n 44.73081073254255\n ],\n [\n -83.26748319036578,\n 45.023341671651394\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hondorp, Darryl W. 0000-0002-5182-1963 dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wills, Todd","contributorId":237770,"corporation":false,"usgs":false,"family":"Wills","given":"Todd","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":807578,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riley, Stephen C.","contributorId":246057,"corporation":false,"usgs":false,"family":"Riley","given":"Stephen C.","affiliations":[{"id":49411,"text":"USGS Great Lakes Science Center (Emeritus)","active":true,"usgs":false}],"preferred":false,"id":807579,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248950,"text":"70248950 - 2023 - A guide to creating an effective big data management framework","interactions":[],"lastModifiedDate":"2023-09-27T16:18:26.710593","indexId":"70248950","displayToPublicDate":"2023-09-26T11:15:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16876,"text":"Journal of Big Data","active":true,"publicationSubtype":{"id":10}},"title":"A guide to creating an effective big data management framework","docAbstract":"Many agencies and organizations, such as the U.S. Geological Survey, handle massive geospatial datasets and their auxiliary data and are thus faced with challenges in storing data and ingesting it, transferring it between internal programs, and egressing it to external entities. As a result, these agencies and organizations may inadvertently devote unnecessary time and money to convey data without existing or outdated standards. This research aims to evaluate the components of data conveyance systems, such as transfer methods, tracking, and automation, to guide their improved performance. Specifically, organizations face the challenges of slow dispatch time and manual intervention when conveying data into, within, and from their systems. Conveyance often requires skilled workers when the system depends on physical media such as hard drives, particularly when terabyte transfers are required. In addition, incomplete or inconsistent metadata may necessitate manual intervention, process changes, or both. A proposed solution is organization-wide guidance for efficient data conveyance. That guidance involves systems analysis to outline a data management framework, which may include understanding the minimum requirements of data manifests, specification of transport mechanisms, and improving automation capabilities.
","language":"English","publisher":"Springer","doi":"10.1186/s40537-023-00801-9","usgsCitation":"Arundel, S., McKeehan, K.G., Campbell, B.B., Bulen, A.N., and Thiem, P.T., 2023, A guide to creating an effective big data management framework: Journal of Big Data, v. 10, 146, 22 p., https://doi.org/10.1186/s40537-023-00801-9.","productDescription":"146, 22 p.","ipdsId":"IP-142351","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":442022,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40537-023-00801-9","text":"Publisher Index Page"},{"id":435170,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92KSPMB","text":"USGS data release","linkHelpText":"ADOM: A Data Orchestration Manager"},{"id":421266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2023-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":884325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKeehan, Kevin G 0000-0002-7242-6954","orcid":"https://orcid.org/0000-0002-7242-6954","contributorId":330206,"corporation":false,"usgs":true,"family":"McKeehan","given":"Kevin","email":"","middleInitial":"G","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":884326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, Bryan B 0000-0002-5425-6736","orcid":"https://orcid.org/0000-0002-5425-6736","contributorId":330207,"corporation":false,"usgs":true,"family":"Campbell","given":"Bryan","email":"","middleInitial":"B","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":884327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bulen, Andrew N. 0000-0002-2155-8412","orcid":"https://orcid.org/0000-0002-2155-8412","contributorId":330208,"corporation":false,"usgs":true,"family":"Bulen","given":"Andrew","email":"","middleInitial":"N.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":884328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thiem, Philip T. 0000-0002-3324-2589","orcid":"https://orcid.org/0000-0002-3324-2589","contributorId":287990,"corporation":false,"usgs":true,"family":"Thiem","given":"Philip","email":"","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":884329,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248930,"text":"sir20235102 - 2023 - Long-term water-quality constituent trends in the Little Arkansas River, south-central Kansas, 1995–2021","interactions":[],"lastModifiedDate":"2026-03-16T13:45:27.510092","indexId":"sir20235102","displayToPublicDate":"2023-09-26T10:49:03","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5102","displayTitle":"Long-Term Water-Quality Constituent Trends in the Little Arkansas River, South-Central Kansas, 1995–2021","title":"Long-term water-quality constituent trends in the Little Arkansas River, south-central Kansas, 1995–2021","docAbstract":"The Equus Beds aquifer and Cheney Reservoir are primary sources for the city of Wichita’s current (2023) water supply. The Equus Beds aquifer storage and recovery (ASR) project was developed by the city of Wichita in the early 1990s to meet future water demands using the Little Arkansas River as an artificial aquifer recharge water source during above-base-flow conditions. Little Arkansas River water is removed from the river at an ASR Facility intake structure, treated using National Primary Drinking Water Regulations as a guideline, and is infiltrated into the Equus Beds aquifer through recharge basins or injected into the aquifer through recharge wells for later use. The U.S. Geological Survey, in cooperation with the city of Wichita, completed this study to quantify and characterize Little Arkansas River water-quality data. Data in this report can be used to evaluate changing conditions, provide science-based information for decision making, and help meet regulatory requirements.
Continuous (hourly) physicochemical properties were measured, and discrete water-quality samples were collected from three Little Arkansas River sites located along the easternmost extent of the Equus Beds aquifer during 1995 through 2021 over a range of streamflow conditions. The Little Arkansas River at Highway 50 near Halstead, Kansas, streamgage (U.S. Geological Survey station 07143672; hereafter referred to as the “Highway 50 site”) is located upstream from the other two sites, and the Little Arkansas River near Sedgwick, Kans., streamgage (U.S. Geological Survey station 07144100; hereafter referred to as the “Sedgwick site”) is located downstream from the other two sites; these two sites bracket most of the easternmost part of the Equus Beds aquifer. The Little Arkansas River upstream of ASR Facility near Sedgwick, Kans., streamgage (U.S. Geological Survey station 375350097262800; hereafter referred to as the “Upstream ASR site”) is located between the Highway 50 and Sedgwick sites, about 14.7 river miles (mi) downstream from the Highway 50 site, about 1.7 river mi upstream from the Sedgwick site, and immediately upstream from the ASR Facility intake structure. Surrogate models for water-quality constituents of interest (including bromide, dissolved organic carbon, 2-chloro-4-isopropylamino-6-amino-s-triazine [deethylatrazine], atrazine, and metolachlor) were updated or developed using continuously measured and concomitant discrete data. These surrogate models, along with previously developed regression models, were used to compute concentrations (at the Highway 50, Sedgwick, and Upstream ASR sites) and loads (at the Highway 50 and Sedgwick sites) during the study period. Federal criteria were used to evaluate water quality. Where applicable, water-quality data were compared to Federal national drinking-water regulations. Flow-normalized water-quality constituent trends were evaluated using Weighted Regressions on Time, Discharge, and Season (WRTDS) statistical models and water-quality trends were described using WRTDS bootstrap tests.
Continuously computed primary ion concentrations were generally larger at the Highway 50 site compared to the Sedgwick site. During the study period, the Federal secondary maximum contaminant level (SMCL) for dissolved solids was exceeded 57 percent of the time at the Highway 50 site and 38 percent of the time at the Sedgwick site. Computed bromide concentrations were larger at the Highway 50 site and exceeded the city of Wichita treatment threshold about 70, 21, and 19 percent of the time at the Highway 50, Sedgwick, and Upstream ASR sites, respectively. Chloride concentrations exceeded the Federal SMCL about 16 percent of the time at the Highway 50 site and did not exceed the SMCL at the Sedgwick site. Continuous arsenic concentrations exceeded the Federal Maximum Contaminant Level (MCL) 9 to 15 percent of the time at the Sedgwick and Highway 50 sites, respectively, during the study. Atrazine concentrations exceeded the Federal MCL 10 percent of the time at the Highway 50 and Sedgwick sites and 14 percent of the time at the Upstream ASR site during the study; computed glyphosate concentrations at the Sedgwick site never exceeded the MCL during the study.
Little Arkansas River flow-normalized primary ion concentrations during 1995 through 2021 generally had downward trends and decreases were generally larger at the Highway 50 site compared to the Sedgwick site. Dissolved solids and chloride concentrations decreased at the Highway 50 and Sedgwick sites. Bromide had no trend at the Highway 50 site and a downward trend at the Sedgwick site. Nitrate plus nitrite and total phosphorus concentrations had upward trends at the Highway 50 site but downward trends at the Sedgwick site, whereas total organic carbon had upward trends at both sites. Nitrate plus nitrite, total nitrogen, total phosphorus, and total organic carbon fluxes had upward trends at the Highway 50 and Sedgwick sites. Suspended-sediment concentrations had an upward trend at the Highway 50 site and had no trend at the Sedgwick site. Arsenic concentrations had downward trends at the Highway 50 and Sedgwick sites.
About one-quarter to one-half of the Little Arkansas River loads, including nutrients and sediment, were transported during 1 percent of the time during the study. Because streamflows are highly sensitive to climatic variation and an increase of extreme precipitation events in the Great Plains is expected, similar disproportionately large pollutant loading events may increase into the future. Continuous measurement of physicochemical properties in near-real time allowed characterization of Little Arkansas River surface water during conditions and time scales that would not have been possible otherwise and served as a complement to discrete water-quality sampling. Continuation of this water-quality monitoring will provide data to characterize changing conditions in the Little Arkansas River and possibly identify new and changing trends. Information in this report allows the city of Wichita to make informed municipal water-supply decisions using past and present water-quality conditions and trends in the watershed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235102","collaboration":"Prepared in cooperation with the city of Wichita, Kansas","usgsCitation":"Stone, M.L., and Klager, B.J., 2023, Long-term water-quality constituent trends in the Little Arkansas River, south-central Kansas, 1995–2021: U.S. Geological Survey Scientific Investigations Report 2023–5102, 103 p., https://doi.org/10.3133/sir20235102.","productDescription":"Report: ix, 103 p.; 1 Figure; 9 Tables; 5 Appendixes; Dataset","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-146544","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":421187,"rank":26,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix10.zip","text":"Appendix 10","size":"46 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season Graphical Output at station 07144100"},{"id":421186,"rank":25,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix9.zip","text":"Appendix 9","size":"35 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season Graphical Output at station 07143672"},{"id":421177,"rank":24,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix6.zip","text":"Appendix 6","size":"2.6 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Surrogate Regression Model Archive Summaries for the Little Arkansas River upstream of ASR Facility near Sedgwick, Kansas"},{"id":421176,"rank":23,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix5.zip","text":"Appendix 5","size":"2.7 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Surrogate Regression Model Archive Summaries for the Little Arkansas River near Sedgwick, Kansas"},{"id":421175,"rank":22,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix4.zip","text":"Appendix 4","size":"1.1 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Surrogate Regression Model Archive Summaries for the Little Arkansas River at Highway 50 near Halstead, Kansas"},{"id":421185,"rank":19,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table8.3.csv","text":"Table 8.3","size":"9 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated mean, flow-normalized, and generalized mean fluxes for sediment, indicator bacteria, and trace elements at the Little Arkansas River at Highway 50 near Halstead, Kansas, and Little Arkansas River near Sedgwick, Kans., 1995–2021"},{"id":421184,"rank":18,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table8.2.csv","text":"Table 8.2","size":"10 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated mean, flow-normalized, and generalized mean fluxes for nutrients and carbon species at the Little Arkansas River at Highway 50 near Halstead, Kansas, and Little Arkansas River near Sedgwick, Kans., 1995–2021"},{"id":421183,"rank":17,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table8.1.csv","text":"Table 8.1","size":"12 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated mean, flow-normalized, and generalized mean fluxes for primary ions at the Little Arkansas River at Highway 50 near Halstead, Kansas, and Little Arkansas River near Sedgwick, Kans., 1995–2021"},{"id":421181,"rank":15,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table7.3.csv","text":"Table 7.3","size":"8 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated mean, flow-normalized, and generalized mean concentrations or densities for sediment, indicator bacteria, and trace elements at the Little Arkansas River at Highway 50 near Halstead, Kansas, and Little Arkansas River near Sedgwick, Kans., 1995–2021"},{"id":421180,"rank":14,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table7.2.csv","text":"Table 7.2","size":"10 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated mean, flow-normalized, and generalized mean concentrations for nutrients and carbon species at the Little Arkansas River at Highway 50 near Halstead, Kansas, and Little Arkansas River near Sedgwick, Kans., 1995–2021"},{"id":421179,"rank":13,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table7.1.csv","text":"Table 7.1","size":"12 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated mean, flow-normalized, and generalized mean concentrations for primary ions at the Little Arkansas River at Highway 50 near Halstead, Kansas, and Little Arkansas River near Sedgwick, Kans., 1995–2021"},{"id":421178,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_tables7.1-7.3.xlsx","text":"Tables 7.1–7.3","size":"108 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":421174,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table3.1.csv","text":"Table 3.1","size":"6.3 KB","linkFileType":{"id":7,"text":"csv"}},{"id":421173,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table3.1.xlsx","text":"Table 3.1","size":"27 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Relative percentage differences for discrete replicate pairs and detection percentages for blank discrete water-quality samples for the Little Arkansas River sites near Sedgwick, Kansas, 1995–2021"},{"id":421171,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table2.1.csv","text":"Table 2.1","size":"2.2 KB","linkFileType":{"id":7,"text":"csv"}},{"id":421172,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table2.1.xlsx","text":"Table 2.1","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Summary statistics for continuously (hourly) measured turbidity data measured with different sensors at the Little Arkansas River at Highway 50 near Halstead, Kansas; Little Arkansas River near Sedgwick, Kans.; and Little Arkansas River upstream of ASR Facility near Sedgwick, Kans., 2004–19"},{"id":421170,"rank":7,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_fig1.1.PDF","text":"Figure 1.1","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Relations between turbidity sensors, 2004–19. 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U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
PyLith, a community, open-source code for modelling quasi-static and dynamic crustal deformation with an emphasis on earthquake faulting, has recently been updated with a flexible multiphysics implementation. We demonstrate the versatility of the multiphysics implementation by extending the code to model fully coupled continuum poromechanics. We verify the newly incorporated physics using standard benchmarks for a porous medium saturated with a slightly compressible fluid. The benchmarks include the 1-D consolidation problem as outlined by Terzaghi, Mandel’s problem for the 2-D case, and Cryer’s problem for the 3-D case. All three benchmarks have been added to the PyLith continuous integration test suite. We compare the closed form analytical solution for each benchmark against solutions generated by our updated code, and lastly, demonstrate that the poroelastic material formulation may be used alongside the existing fault implementation in PyLith.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggad370","usgsCitation":"Walker, R.L., Knepley, M.G., Aagaard, B.T., and Williams, C.A., 2023, Multiphysics modelling in PyLith: Poroelasticity: Geophysical Journal International, v. 235, no. 3, p. 2442-2475, https://doi.org/10.1093/gji/ggad370.","productDescription":"34 p.","startPage":"2442","endPage":"2475","ipdsId":"IP-146478","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":424189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"235","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Robert L.","contributorId":333017,"corporation":false,"usgs":false,"family":"Walker","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":891663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knepley, Matthew G.","contributorId":333018,"corporation":false,"usgs":false,"family":"Knepley","given":"Matthew","email":"","middleInitial":"G.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":891664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":891665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Charles A.","contributorId":333019,"corporation":false,"usgs":false,"family":"Williams","given":"Charles","email":"","middleInitial":"A.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":891666,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248951,"text":"70248951 - 2023 - Informing ASR treatment practices in a Florida aquifer through a human health risk approach","interactions":[],"lastModifiedDate":"2023-09-27T12:02:41.775734","indexId":"70248951","displayToPublicDate":"2023-09-26T07:00:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16877,"text":"International Journal of Enviornmental Research and Public Health","active":true,"publicationSubtype":{"id":10}},"title":"Informing ASR treatment practices in a Florida aquifer through a human health risk approach","docAbstract":"Big sagebrush (Artemisia tridentata) ecosystems across the western United States have experienced many changes in ecosystem dynamics and vegetation composition over the last century due to livestock grazing, non-native species, and changing climate and fire regimes. We conducted the first systematic investigation of historical vegetation composition and vegetation change in a sagebrush landscape in the southwestern United States, asking whether sagebrush or grass dominated the landscape historically?
The Rio Grande del Norte National Monument (RGDN), northern New Mexico, USA.
We combined General Land Office (GLO) surveys from 1881 with modern vegetation maps, field vegetation surveys, and sagebrush ages from growth ring analysis to test for changes in vegetation in the RGDN over the last 140 years.
We found that big sagebrush presence across the study area increased significantly, from being present on 16% of section lines in 1881 to 79% in 2019, and only three section lines lost sagebrush presence during that period. Concurrently, the number of section lines with low grass index more than doubled since 1881, while moderate and high grass index declined. Grass declined equally in areas where sagebrush increased and areas with no change in sagebrush, suggesting that changes in both vegetation types were catalyzed by external factors, likely including overgrazing. The growth ring analysis of 93 sagebrush revealed a maximum age of 87 years and establishment in every decade since the 1930s, consistent with the GLO results.
The significant vegetation changes in the RGDN over the last century, including an increase of sagebrush, provide important context about the shifting mosaic of grasslands and shrublands relevant to current and future management and ecosystem dynamics.
","language":"English","publisher":"Wiley","doi":"10.1111/jvs.13202","usgsCitation":"Fox, K., Margolis, E.Q., Lopez, M.K., Kasten, E., and Stevens, J., 2023, Vegetation change over 140 years in a sagebrush landscape of the Rio Grande del Norte National Monument, New Mexico, USA: Journal of Vegetation Science, v. 34, no. 5, e13202, 17 p., https://doi.org/10.1111/jvs.13202.","productDescription":"e13202, 17 p.","ipdsId":"IP-151212","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":423620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Rio Grande del Norte National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.5540076425751,\n 37.026637990156544\n ],\n [\n -106.5540076425751,\n 36.224664603824266\n ],\n [\n -105.13109401921486,\n 36.224664603824266\n ],\n [\n -105.13109401921486,\n 37.026637990156544\n ],\n [\n -106.5540076425751,\n 37.026637990156544\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"34","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Fox, Kara","contributorId":261706,"corporation":false,"usgs":false,"family":"Fox","given":"Kara","email":"","affiliations":[],"preferred":false,"id":890344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":890345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez, Manuel K.","contributorId":298167,"corporation":false,"usgs":false,"family":"Lopez","given":"Manuel","email":"","middleInitial":"K.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":890346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kasten, Ella","contributorId":332521,"corporation":false,"usgs":false,"family":"Kasten","given":"Ella","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":890347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stevens, J.T.","contributorId":332522,"corporation":false,"usgs":false,"family":"Stevens","given":"J.T.","email":"","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":890348,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249458,"text":"70249458 - 2023 - Survey optimization for invasive Burmese pythons informed by camera traps","interactions":[],"lastModifiedDate":"2023-11-07T16:16:54.037489","indexId":"70249458","displayToPublicDate":"2023-09-25T14:56:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17053,"text":"Wildlife Letters","active":true,"publicationSubtype":{"id":10}},"title":"Survey optimization for invasive Burmese pythons informed by camera traps","docAbstract":"The Burmese python (Python bivittatus) is an invasive predator responsible for broad mammal declines in South Florida, United States. Despite their large size, pythons remain cryptic and require multifaceted approaches for detection. We evaluated a novel technique by deploying camera traps at known locations of radiotagged pythons in the Florida Keys. We estimated daily detection probabilities of snakes and plotted diel activity patterns. Our results suggest camera traps can effectively survey pythons but seasonality and camera trigger mechanisms affect utility. Pythons were most detectable with time-lapse camera traps and more detectable in winter. The diel activity pattern of pythons peaked midday through early afternoon, indicating an optimal survey time for other search methods. Artificial intelligence can alleviate photo volume, so we recommend a combination of motion detection and time-lapse with shorter time (1 min) intervals for python-specific surveys and where camera traps are deployed to monitor mammals to improve passive python detection.
Management agencies are tasked with difficult decisions for conservation and management of natural resources. These decisions are difficult because of ecological and social uncertainties, the potential for multiple decision makers from multiple jurisdictions, and the need to account for the diverse values of stakeholders. Decision analysis provides a framework for accounting for these difficulties when making conservation and management decisions. We discuss the benefits of the application of decision analysis for these types of issues and provide insights from three case studies from the Laurentian Great Lakes. These case studies describe applications of decision analysis for decisions within an agency (management of double-crested cormorant), among agencies (response to invasive grass carp), and among agencies and stakeholders (sustainable fisheries harvest management). These case studies provide insight into the ways that decision analysis can be useful for conservation and management of natural resources, but we also highlight future needs for decision making for these resources. In particular, applications of decision analysis for conservation and management would benefit from enhanced integration of both ecological and social science, inclusion of a broader base of stakeholders and rightsholders, and better educational opportunities surrounding decision analysis for undergraduates and graduate students of natural resources management programs. Specific lessons from our experiences include the importance of establishing trust and transparency early through the formation of a working group, collaboratively defining objectives and evaluating uncertainties, risks, and tradeoffs, and implementing participatory modeling processes with an independent facilitator with appropriate quantitative skills.
","language":"English","publisher":"Informs","doi":"10.1287/deca.2023.0015","usgsCitation":"Robinson, K.F., Dufour, M.R., Fischer, J., Herbst, S.J., Jones, M., Nathan, L.R., and Newcomb, T.J., 2023, Lessons learned in applying decision analysis to natural resource management for high stakes issues surrounded by uncertainty: Decision Analysis, v. 20, no. 4, p. 326-342, https://doi.org/10.1287/deca.2023.0015.","productDescription":"17 p.","startPage":"326","endPage":"342","ipdsId":"IP-149566","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442032,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://osf.io/3bgt9","text":"External Repository"},{"id":432151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Kelly Filer 0000-0001-8109-9492","orcid":"https://orcid.org/0000-0001-8109-9492","contributorId":340631,"corporation":false,"usgs":true,"family":"Robinson","given":"Kelly","email":"","middleInitial":"Filer","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":907415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischer, Jason L.","contributorId":241112,"corporation":false,"usgs":false,"family":"Fischer","given":"Jason L.","affiliations":[],"preferred":false,"id":907416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herbst, Seth J.","contributorId":11102,"corporation":false,"usgs":true,"family":"Herbst","given":"Seth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":907417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Michael L.","contributorId":126763,"corporation":false,"usgs":false,"family":"Jones","given":"Michael L.","affiliations":[{"id":6600,"text":"Qauntitative Fisheries Center, Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907418,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nathan, Lucas R.","contributorId":340047,"corporation":false,"usgs":false,"family":"Nathan","given":"Lucas","email":"","middleInitial":"R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907419,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Newcomb, Tammy J.","contributorId":13908,"corporation":false,"usgs":true,"family":"Newcomb","given":"Tammy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":907420,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70249912,"text":"70249912 - 2023 - Lessons learned from community and citizen science monitoring projects on the Elwha River Restoration Project","interactions":[],"lastModifiedDate":"2023-11-06T14:51:55.403508","indexId":"70249912","displayToPublicDate":"2023-09-25T08:45:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Lessons learned from community and citizen science monitoring projects on the Elwha River Restoration Project","docAbstract":"Community and citizen science (CCS) projects – initiatives that involve public participation in scientific research – can both sustain and expand long-term monitoring of large dam removal projects. In this article, we discuss our perspectives on CCS associated with the Elwha River dam removals. We summarize how the public has been or could be involved in monitoring and distill lessons learned for other large dam removal projects. Much of the Elwha monitoring involved technical field work requiring training and incurring potential liability risks, guiding projects towards smaller-scale public involvement. Partnering with organizations that have capacity for volunteer management expanded CCS opportunities and provided logistical support to project managers committed to public engagement. We found that many projects engaged with students and/or with paid or unpaid interns; compensating participants in various ways can help to create reciprocal relationships that support long-term monitoring. In the future, other large dam removals could consider planning ahead for community involvement in dam removal monitoring to accommodate the technical and potentially hazardous nature of the work – broadening who may be able to participate. In addition, involving community members in setting research agendas could be an important first step in engaging them in long-term monitoring, in turn facilitating multi-generational research at the timescale of landscape-level changes. Finally, explicit relationship-building with Indigenous communities can enhance the benefits of community engagement in dam removal science for all involved.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1216080","usgsCitation":"Eitzel, M., Meyer, R., Morley, S.A., Miller, I.M., Shafroth, P., Behymer, C., Jadallah, C., Parks, D., Kagley, A., Shaffer, A., and Ballard, H.L., 2023, Lessons learned from community and citizen science monitoring projects on the Elwha River Restoration Project: Frontiers in Ecology and Evolution, v. 11, 1216080, 8 p., https://doi.org/10.3389/fevo.2023.1216080.","productDescription":"1216080, 8 p.","ipdsId":"IP-153133","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":442034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1216080","text":"Publisher Index Page"},{"id":422400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.8042115532547,\n 48.18296274689851\n ],\n [\n -123.8042115532547,\n 47.722552996994835\n ],\n [\n -123.34685932477454,\n 47.722552996994835\n ],\n [\n -123.34685932477454,\n 48.18296274689851\n ],\n [\n -123.8042115532547,\n 48.18296274689851\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Eitzel, M. V.","contributorId":331429,"corporation":false,"usgs":false,"family":"Eitzel","given":"M. V.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":887677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Ryan","contributorId":303790,"corporation":false,"usgs":false,"family":"Meyer","given":"Ryan","email":"","affiliations":[{"id":65906,"text":"Center for Community and Citizen Science, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":887678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morley, Sarah A.","contributorId":148956,"corporation":false,"usgs":false,"family":"Morley","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":17601,"text":"NOAA Fisheries, Northwest Fisheries Science Center, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":887679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":887680,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Behymer, Chelsea","contributorId":303789,"corporation":false,"usgs":false,"family":"Behymer","given":"Chelsea","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":887682,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jadallah, Christopher","contributorId":303792,"corporation":false,"usgs":false,"family":"Jadallah","given":"Christopher","email":"","affiliations":[{"id":65906,"text":"Center for Community and Citizen Science, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":887683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Parks, David","contributorId":331431,"corporation":false,"usgs":false,"family":"Parks","given":"David","email":"","affiliations":[{"id":79206,"text":"Washington Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":887684,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kagley, Anna","contributorId":303791,"corporation":false,"usgs":false,"family":"Kagley","given":"Anna","email":"","affiliations":[{"id":65907,"text":"Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":887685,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shaffer, Anne","contributorId":168504,"corporation":false,"usgs":false,"family":"Shaffer","given":"Anne","email":"","affiliations":[],"preferred":false,"id":887686,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ballard, Heidi L.","contributorId":149651,"corporation":false,"usgs":false,"family":"Ballard","given":"Heidi","email":"","middleInitial":"L.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":887687,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70249979,"text":"70249979 - 2023 - Synergistic behavioral antagonists of a sex pheromone reduce reproduction of invasive sea lamprey","interactions":[],"lastModifiedDate":"2023-11-12T14:16:34.646692","indexId":"70249979","displayToPublicDate":"2023-09-25T08:07:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16668,"text":"iScience","active":true,"publicationSubtype":{"id":10}},"title":"Synergistic behavioral antagonists of a sex pheromone reduce reproduction of invasive sea lamprey","docAbstract":"Sex pheromones impart maximal attraction when their components are present at optimal ratios that confer balanced olfactory inputs in potential mates. Altering ratios or adding pheromone analogs to optimal mixtures may disrupt balanced olfactory antagonism and result in reduced attraction, however, tests in natural populations are lacking. We tested this hypothesis in sea lamprey (Petromyzon marinus), a fish whose male sex pheromone attracts females when two critical components, 3-keto petromyzonol sulfate (3kPZS) and petromyzonol sulfate (PZS), are present at certain ratios. Here, we report a pheromone analog, petromyzonol tetrasulfate (3sPZS), reduced female attraction to 3kPZS but not to PZS. 3sPZS mixed with additional PZS synergistically disrupted female attraction to the male pheromone and reduced spawning by 97% in a high-density population. Our results provide evidence of balanced olfactory antagonism in a vertebrate and establish a tactic to disrupt spawning of sea lamprey, a destructive invader of the Laurentian Great Lakes.
Numerous studies have evaluated the application of Remote Sensing (RS) techniques for mapping actual evapotranspiration (ETa) using Vegetation-Index-based (VI-based) and surface energy balance methods (SEB). SEB models computationally require a large effort for application. VI-based methods are fast and easy to apply and could therefore potentially be applied at high resolution; however, the accuracy of VI-based methods in comparison to SEB-based models remains unclear. We tested the ETa computed with the modified 2-band Enhanced Vegetation Index (METEVI2) implemented in the Google Earth Engine – for mapping croplands’ water use dynamics in the Lower Colorado River Basin. We compared METEVI2 with the well-established RS-based products of OpenET (Ensemble, eeMETRIC, SSEBop, SIMS, PT_JPL, DisALEXI and geeSEBAL). METEVI2 was then evaluated with measured ETa from four wheat fields (2017–2018). Results indicated that the monthly ETa variations for METEVI2 and OpenET models were comparable, though of varying magnitudes. On average, METEVI2 had the lowest difference rate from the average observed ETa with 17 mm underestimation, while SIMS had the highest difference rate (82 mm). Findings show that METEVI2 is a cost-effective ETa mapping tool in drylands to track crop water use. Future studies should test METEVI2’s applicability to croplands in more humid regions.
Lunar red spots are small spectrally red features that have been proposed to be the result of non-mare volcanism. Studies have shown that a number of red spots are silicic, and are spectrally distinct from both highlands and mare compositions. In this work, we use data from LRO Diviner, Mini-RF, and Arecibo to investigate the material properties of 10 red spots. We create albedo maps using Diviner daytime solar reflectance data to use as an input to our improved thermophysical model, and calculate the rock abundance (RA) and H-parameter values that best fit Diviner nighttime thermal infrared radiance measurements. The H-parameter can be considered analogous to the thermal inertia of the regolith, with a high H-parameter corresponding to low thermal inertia. We find that the red spots generally have low RA, and do not have a uniform H-parameter but contain localized regions of high H-parameter. We additionally find that the red spots have a low circular polarization ratio (CPR) in many of the same locations that show a low RA and high H-parameter. Low RA, high H-parameter, and low CPR indicate a relative lack of rocks larger than ∼10 cm, which is consistent with previous findings of a mantling of fine-grained pyroclastic material for at least three red spots. Areas with high H-parameter but that do not show clear signs of pyroclastics in other data sets may be evidence of previously undiscovered pyroclastics, or could be due to the unique physical properties (e.g., porosity, rock strength/breakdown resistance) of the rocks that make up the red spots.
","language":"English","publisher":"American Astronomical Society","doi":"10.3847/PSJ/acf134","usgsCitation":"Byron, B., Elder, C., Glotch, T., Hayne, P., Pigue, L.M., and Cahill, J.T., 2023, Evidence for fine-grained material at lunar red spots: Insights from thermal infrared and radar data sets: Planetary Science Journal, v. 4, no. 9, 182, 24 p., https://doi.org/10.3847/PSJ/acf134.","productDescription":"182, 24 p.","ipdsId":"IP-152412","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":442043,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/acf134","text":"Publisher Index Page"},{"id":422001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Moon","volume":"4","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Byron, Benjamin","contributorId":331016,"corporation":false,"usgs":false,"family":"Byron","given":"Benjamin","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":886491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elder, Catherine","contributorId":331017,"corporation":false,"usgs":false,"family":"Elder","given":"Catherine","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":886492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glotch, Timothy","contributorId":331018,"corporation":false,"usgs":false,"family":"Glotch","given":"Timothy","affiliations":[{"id":25401,"text":"Stony Brook University, Stony Brook, NY","active":true,"usgs":false}],"preferred":false,"id":886493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayne, Paul O.","contributorId":331019,"corporation":false,"usgs":false,"family":"Hayne","given":"Paul","middleInitial":"O.","affiliations":[{"id":79091,"text":"Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":886494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pigue, Lori M. 0000-0002-6675-6877","orcid":"https://orcid.org/0000-0002-6675-6877","contributorId":330994,"corporation":false,"usgs":true,"family":"Pigue","given":"Lori","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":886495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cahill, Joshua T. S.","contributorId":331020,"corporation":false,"usgs":false,"family":"Cahill","given":"Joshua","email":"","middleInitial":"T. S.","affiliations":[{"id":7166,"text":"Johns Hopkins University Applied Physics Laboratory","active":true,"usgs":false}],"preferred":false,"id":886496,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70249313,"text":"70249313 - 2023 - Eruption of stagnant lava from an inactive perched lava lake","interactions":[],"lastModifiedDate":"2023-10-04T11:40:20.695469","indexId":"70249313","displayToPublicDate":"2023-09-23T06:37:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Eruption of stagnant lava from an inactive perched lava lake","docAbstract":"Lava flow hazards are usually thought to end when the erupting vent becomes inactive, but this is not always the case. At Kīlauea in August 2014, a spiny ʻaʻā flow erupted from the levee of a crusted perched lava lake that had been inactive for a month, and the surface of the lava lake subsided as the flow advanced downslope over the following few days. Topography constructed from oblique aerial photographs using structure-from-motion (SfM) software shows that the volume of the flow (∼68,000 m3) closely matches the volume of subsidence of the crusted lava lake (∼64,000 m3). The similarity of these volumes, along with the textural characteristics of the lava, shows that the lava that fed the flow had been stored beneath the surface of the perched lava lake, and that the flow was not generated by reactivation of the vent. This extends the duration of the local lava flow hazard presented by perched lava lakes and similar flow field structures that store lava, such as rootless shields. The flow probably occurred because the density of the lava beneath the crusted surface of the perched lava lake increased through loss of gas bubbles until it was able to penetrate the less-dense levee, which was composed of relatively vesicular overflows. The flow is thus equivalent to the lava seeps described previously at Kīlauea and elsewhere. We present a simple physical model for the pressure change at the base of a densifying body of lava, which we apply to this case study, and which could be applied to similar scenarios elsewhere.
Past efforts to explain variation of invertebrate assemblages in freshwater wetlands have been less productive than anticipated. To explore why efforts are disappointing, we assembled large invertebrate data sets from North Dakota prairie potholes, California rock pools, and Georgia Carolina bay wetlands that addressed spatial (among wetlands) and temporal (among seasons and years) variation. We anticipated that these large data-set sizes would enable robust conclusions to be drawn, and each place had unique environmental conditions that might contribute to greater explanatory power. We used statistical techniques that partitioned variation in invertebrate assemblages into spatial and/or temporal components, and that also yielded a measure of the amount of unexplained variation; Permutational Multivariate Analysis of Variation and Principal Coordinates Analysis assessed whole assemblage variation, and Analysis of Variance or Analysis of Covariance assessed variation in taxon richness, total abundances, and abundances of wide-spread individual taxa. Across all locations, variation explained by spatial and temporal factors, and unexplained variation were of comparable magnitudes (i.e., similar R2 values of ~ 50%). Review of other published studies indicate that this pattern is widespread. The 50% or more unexplained variation is typically ignored by researchers, who instead focus on explained fractions. We argue that, besides addressing explained spatial and temporal variation in invertebrate assemblages (e.g., control by hydrology, resources, predation), efforts to understand what contributes to currently unexplained variation, that is unrelated to local spatial or temporal controls (e.g., broad climatic and biogeographic patterns, organism physiology and behavior), will lead to a fuller comprehension of how invertebrates in freshwater wetlands are controlled.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-023-01734-y","usgsCitation":"Reindl, S., McLean, K., Kneitel, J.M., Bell, D., and Batzer, D., 2023, Doing the same thing over and over again and getting the same result: Assessing variance in wetland invertebrate assemblages: Wetlands, v. 43, 84, 10 p., https://doi.org/10.1007/s13157-023-01734-y.","productDescription":"84, 10 p.","ipdsId":"IP-142858","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":465148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","noUsgsAuthors":false,"publicationDate":"2023-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Reindl, Sophie","contributorId":347248,"corporation":false,"usgs":false,"family":"Reindl","given":"Sophie","email":"","affiliations":[],"preferred":false,"id":921012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLean, Kyle 0000-0003-3803-0136 kmclean@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-0136","contributorId":168533,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle","email":"kmclean@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":921013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kneitel, Jamie M.","contributorId":347179,"corporation":false,"usgs":false,"family":"Kneitel","given":"Jamie","email":"","middleInitial":"M.","affiliations":[{"id":83096,"text":"Department of Biological Sciences, California State University, 6000 J St, Sacramento, CA 95819, USA","active":true,"usgs":false}],"preferred":false,"id":921014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bell, Douglas A.","contributorId":347182,"corporation":false,"usgs":false,"family":"Bell","given":"Douglas A.","affiliations":[{"id":83098,"text":"East Bay Regional Park District, 2950 Peralta Oaks Court, Oakland, CA 94605, USA","active":true,"usgs":false}],"preferred":false,"id":921015,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Batzer, Darold P.","contributorId":347183,"corporation":false,"usgs":false,"family":"Batzer","given":"Darold P.","affiliations":[{"id":83097,"text":"Department of Entomology, 120 Cedar St, University of Georgia, Athens, GA 30605, USA","active":true,"usgs":false}],"preferred":false,"id":921016,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248889,"text":"70248889 - 2023 - The 50-year Landsat collection 2 archive","interactions":[],"lastModifiedDate":"2023-09-25T12:08:39.553001","indexId":"70248889","displayToPublicDate":"2023-09-22T07:06:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9346,"text":"Science of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The 50-year Landsat collection 2 archive","docAbstract":"The Landsat global consolidated data archive now exceeds 50 years. In recognition of the need for consistently processed data across the Landsat satellite series, the U.S. Geological Survey (USGS) initiated collection-based processing of the entire archive that was processed as Collection 1 in 2016. In preparation for the data from the now successfully launched Landsat 9, the USGS reprocessed the Landsat archive as Collection 2 in 2020. This paper describes the rationale for, and the contents and advancements provided by Collection 2, and highlights the differences between the Collection 1 and Collection 2 products. Notably, the Collection 2 products have improved geolocation and, for the first time, the USGS provides a global inventory of Level 2 surface reflectance and surface temperature products. Also for the first time, the USGS used a commercial cloud computing architecture to efficiently process the archive and enable direct cloud access of the Landsat products. The paper concludes with discussion of likely improvements expected in Collection 3 in preparation for the Landsat Next mission that is planned for launch in the early 2030s.
Amphibians are among the most sensitive taxa to climate change, and species inhabiting arid and semiarid landscapes at the extremes of their range are especially vulnerable to drought. The Jack Creek, Oregon, USA, population of Oregon spotted frogs (Rana pretiosa) faces unique challenges because it occupies the highest elevation site in the species' extant range and one that has been transformed by loss of American beavers (Castor canadensis), which historically maintained open water. We evaluated the effects of drought mitigation (addition of excavated ponds) on relationships between local and regional water availability, inactive legacy beaver dams, and Oregon spotted frog population dynamics in the Jack Creek system. We conducted egg mass surveys and capture-mark-recapture sampling at a treatment reach with excavated ponds and 3 reference reaches over 13 years; surveys spanned a period before and after pond excavation at the treatment and 1 primary comparison reference reach. We analyzed data using a combination of robust design capture-mark-recapture estimators and generalized linear mixed models to characterize population dynamics. Adult Oregon spotted frog survival was approximately 19.5% higher at the treatment reach than the primary reference reach during the study period. Annual survival was most strongly associated with late summer vegetation greenness, a proxy for water availability, and males had higher survival than females. Among the 4 study reaches, the treatment reach consistently had higher late summer vegetation greenness, and the hydrology functioned more independently of regional precipitation patterns relative to the reference reaches; however, these dynamics were not linked to pond excavation. Breeding was concentrated in 2 legacy beaver ponds that were deepened by excavation during the study compared to an unexcavated beaver pond, 2 excavated ponds without legacy beaver dams, and 9 reference ponds. These results point to the benefit of enhancing existing beaver structures and indicate that management actions aimed at maintaining surface water for breeding in spring and saturated soils and ponded water for adults in late summer would benefit this unique population of Oregon spotted frogs in the face of drought.
As part of a joint Saudi Geological Survey (SGS) and United States Geological Survey project, we analyzed P-wave receiver functions from seismic stations covering most of the Kingdom of Saudi Arabia to map the thickness of the crust across the Arabia Plate. We present an update of crustal thickness estimates and fill in gaps for the western Arabian Shield and the rifted margin at the Red Sea (the coastal plain), as well as the eastern Arabian Platform. We applied a conventional H-k stacking algorithm and included careful attention to stacking weights, two forms of sedimentary corrections for stations located on the Arabian Platform, and additional processing for noisy stations. We obtained useful results at 154 stations from 898 teleseismic events over a 2-year period from 1995–1997 (for non-SGS stations) and a 6-year period from 2008–2014 (for SGS stations). Average crustal thickness (that is, depth to the Mohorovičić discontinuity [Moho] below the surface) beneath the Red Sea coastal plain (the rift margin) is 29 kilometers (km), beneath the volcanic fields (known in Arabic as harra [plural] or harrat [singular]) is 35 km, beneath the Arabian Shield (excluding harrats) is 37 km, and beneath the Arabian Platform is 38 km. Crustal thinning appears not to extend east of the rift escarpment, suggesting uniform extension that is no broader at depth than at the surface. In contrast to some previous interpretations that the Arabian Platform crust is thicker than that of the Arabian Shield, we find no statistically significant difference between their whole crustal thicknesses. However, the average sub-sedimentary crustal thickness (that is, the crystalline crust) for stations on the Arabian Platform is 34 km, 3 km thinner than the crust of the Arabian Shield. Individual station P-wave (pressure) velocity and S-wave (shear) velocity ratios (VP/VS) are highly variable for the Arabia Plate, ranging from 1.60 to 1.97 and averaging 1.75, with a standard deviation of 0.07. There are no statistically significant differences between VP/VS ratios of the different geologic regions of Saudi Arabia. Similar VP/ VS ratios, coupled with similar crustal thicknesses for harrats and the Arabian Shield, indicate that Cenozoic magmatism has contributed negligibly to crustal growth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231042","usgsCitation":"Blanchette, A.R., Klemperer, S.L., and Mooney, W.D., 2023, Crustal thickness and the VP/VS ratio within the Arabia Plate from P-wave receiver functions at 154 broadband seismic stations: U.S. Geological Survey Open-File Report 2023–1042, 325 p., https://doi.org/10.3133/ofr20231042.","productDescription":"xi, 325 p.","onlineOnly":"Y","ipdsId":"IP-136065","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":421029,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1042/coverthb.jpg"},{"id":421030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1042/ofr20231042.pdf","text":"Report","size":"84.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1042"}],"country":"Saudi Arabia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[42.77933,16.34789],[42.64957,16.77464],[42.34799,17.07581],[42.27089,17.47472],[41.75438,17.83305],[41.22139,18.6716],[40.93934,19.48649],[40.24765,20.17463],[39.80168,20.33886],[39.1394,21.2919],[39.0237,21.98688],[39.06633,22.57966],[38.49277,23.68845],[38.02386,24.07869],[37.48363,24.28549],[37.15482,24.85848],[37.20949,25.08454],[36.93163,25.60296],[36.6396,25.82623],[36.24914,26.57014],[35.64018,27.37652],[35.13019,28.06335],[34.63234,28.05855],[34.78778,28.60743],[34.83222,28.95748],[34.95604,29.35655],[36.06894,29.19749],[36.50121,29.50525],[36.74053,29.86528],[37.50358,30.00378],[37.66812,30.33867],[37.99885,30.5085],[37.00217,31.50841],[39.00489,32.01022],[39.19547,32.16101],[40.39999,31.88999],[41.88998,31.19001],[44.7095,29.17889],[46.56871,29.09903],[47.45982,29.00252],[47.70885,28.52606],[48.41609,28.552],[48.80759,27.68963],[49.29955,27.46122],[49.47091,27.11],[50.15242,26.68966],[50.21294,26.27703],[50.1133,25.94397],[50.23986,25.60805],[50.52739,25.32781],[50.66056,24.9999],[50.81011,24.75474],[51.11242,24.55633],[51.38961,24.62739],[51.57952,24.2455],[51.61771,24.01422],[52.00073,23.00115],[55.0068,22.49695],[55.20834,22.70833],[55.66666,22],[54.99998,19.99999],[52.00001,19],[49.11667,18.61667],[48.18334,18.16667],[47.46669,17.11668],[47,16.95],[46.74999,17.28334],[46.36666,17.23332],[45.4,17.33334],[45.21665,17.43333],[44.06261,17.41036],[43.79152,17.31998],[43.38079,17.57999],[43.1158,17.08844],[43.21838,16.66689],[42.77933,16.34789]]]},\"properties\":{\"name\":\"Saudi Arabia\"}}]}","contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035
Introduction: Declining hunter populations across North America present wildlife management agencies with the prospect of declining revenues for wildlife conservation and management and the need for new tools to evaluate management strategies and predict future status of game species and hunters.
Methods: Here we present a modeling framework and potential decision support tool for managers to link future hunter population dynamics to regulatory restrictiveness, prey abundance, and harvest success. Our hunter model is parameterized based on the authors’ judgment and can be used for demonstration purposes. We simulated three scenarios of restricted harvest, moderate harvest and liberal harvest.
Results: Our simulations show that even though liberal harvest predicts higher cumulative license sales revenue, it corresponds with a slight decline in buck abundance over 10 years. In contrast, highly restrictive harvest corresponds with deer population growth, but a near collapse of hunter populations. Our model demonstrates that managers might face tradeoffs between managing for deer population abundance and hunting revenue and clarifies how these factors might affect decision making.
Discussion: The utility of our tool would be dependent on accessing data on hunter retention and recruitment, however, the strength of our paper is in highlighting a new way of thinking about and potentially addressing these potential tradeoffs. Further, these simulations demonstrate that these tools could be used to evaluate management strategies but also highlight uncertainties, establish research priorities, and potentially design an adaptive management framework.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcosc.2023.1265806","usgsCitation":"McGowan, C., Price Tack, J., Silvano, A., and Grand, J.B., 2023, Models for linking hunter retention and recruitment to regulations and game populations: Frontiers in Conservation Science, v. 4, 126506, 9 p., https://doi.org/10.3389/fcosc.2023.1265806.","productDescription":"126506, 9 p.","ipdsId":"IP-140942","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442050,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2023.1265806","text":"Publisher Index Page"},{"id":432487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"4","noUsgsAuthors":false,"publicationDate":"2023-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":907711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price Tack, Jennifer L.","contributorId":340942,"corporation":false,"usgs":false,"family":"Price Tack","given":"Jennifer L.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":907712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvano, Amy","contributorId":340943,"corporation":false,"usgs":false,"family":"Silvano","given":"Amy","affiliations":[{"id":35940,"text":"Alabama Division of Wildlife and Freshwater Fisheries","active":true,"usgs":false}],"preferred":false,"id":907713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907714,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248851,"text":"70248851 - 2023 - Salinity trends in a groundwater system supplemented by 50 years of imported Colorado River water","interactions":[],"lastModifiedDate":"2023-10-23T16:09:01.925637","indexId":"70248851","displayToPublicDate":"2023-09-21T09:12:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16870,"text":"Environmental Science & Technology Water","active":true,"publicationSubtype":{"id":10}},"title":"Salinity trends in a groundwater system supplemented by 50 years of imported Colorado River water","docAbstract":"The Indio subbasin of the Coachella Valley is a desert area of southern California where a growing population depends primarily on groundwater for drinking and agricultural uses. The aquifer system has been supplemented with Colorado River water through managed recharge and widespread irrigation since the mid-20th century. We use a combination of geochemical modeling and trend analysis to identify changes in total dissolved solids through time, elucidate the sources of dissolved solids, and quantify the extent of contributions from those sources throughout the Indio subbasin. We conclude that recharged Colorado River water is the primary source and driver of increasing salinity, particularly in areas immediately downgradient from the recharge locations and in the eastern part of the subbasin away from the recharge ponds due to irrigation using imported water. Other contributions of dissolved solids to groundwater resources include geothermal waters, wastewater effluent, and agricultural return flow, although their effects are more localized. This study presents a broadly applicable framework for identifying sources of dissolved solids in groundwater wells and salinity trends at a regional scale in a large data set.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acsestwater.3c00239","usgsCitation":"Harkness, J.S., McCarthy, P.M., Jurgens, B., and Levy, Z., 2023, Salinity trends in a groundwater system supplemented by 50 years of imported Colorado River water: Environmental Science & Technology Water, v. 3, no. 10, p. 3253-3264, https://doi.org/10.1021/acsestwater.3c00239.","productDescription":"12 p.","startPage":"3253","endPage":"3264","ipdsId":"IP-148329","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":442051,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acsestwater.3c00239","text":"Publisher Index Page"},{"id":435173,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KUBQKM","text":"USGS data release","linkHelpText":"Inverse Model Data for: Salinity trends in a groundwater system supplemented by 50 years of imported Colorado River water"},{"id":421073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coachella Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.13573439891272,\n 33.44388210065128\n ],\n [\n -115.83959902010358,\n 33.47539980820645\n ],\n [\n -116.10770512437531,\n 33.77373918192059\n ],\n [\n -116.49280298323828,\n 33.977110302145775\n ],\n [\n -116.5817654632921,\n 33.996309353196736\n ],\n [\n -116.645135997029,\n 33.92049840312886\n ],\n [\n -116.51108294489313,\n 33.79298404948595\n ],\n [\n -116.29781672558602,\n 33.66122225831866\n ],\n [\n -116.21372890197347,\n 33.55363612855925\n ],\n [\n -116.13573439891272,\n 33.44388210065128\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Harkness, Jennifer S. 0000-0001-9050-2570 jharkness@usgs.gov","orcid":"https://orcid.org/0000-0001-9050-2570","contributorId":224299,"corporation":false,"usgs":true,"family":"Harkness","given":"Jennifer","email":"jharkness@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Patrick Michael 0000-0002-5492-1409","orcid":"https://orcid.org/0000-0002-5492-1409","contributorId":330033,"corporation":false,"usgs":true,"family":"McCarthy","given":"Patrick","email":"","middleInitial":"Michael","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Levy, Zeno F. 0000-0003-4580-2309","orcid":"https://orcid.org/0000-0003-4580-2309","contributorId":222340,"corporation":false,"usgs":true,"family":"Levy","given":"Zeno","middleInitial":"F.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883887,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248843,"text":"70248843 - 2023 - Relating absolute abundance of an estuarine fish to habitat area in an urbanizing environment","interactions":[],"lastModifiedDate":"2023-09-22T12:22:47.101959","indexId":"70248843","displayToPublicDate":"2023-09-21T07:20:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16867,"text":"Marine Ecologly Progressive Series","active":true,"publicationSubtype":{"id":10}},"title":"Relating absolute abundance of an estuarine fish to habitat area in an urbanizing environment","docAbstract":"Organisms that rely on salt marsh habitat are an important trophic link, helping to maintain estuarine ecosystem productivity. We used GIS to quantify intertidal (assumed salt marsh) area from aerial photographs taken in 1939 and from software-supplied satellite imagery taken in 2021 for tidal creeks in North Carolina (USA) that have experienced minor (<20%), moderate (20-60%), or substantial (>60%) losses of intertidal habitat over the 8 decades. The current (2022) absolute abundance of adult Fundulus heteroclitus, a trophically important resident fish in US Atlantic estuaries, was estimated over each season in each creek by fitting a Lincoln-Petersen model to tag-recapture data. Current abundances of F. heteroclitus were lowest in creeks with the lowest intertidal area. The median and 2.5/97.5 credible intervals of the posterior probability distribution for the slope of a regression model relating current fish abundance to current intertidal area were positive, demonstrating that intertidal area was a meaningful covariate of abundance. Loss of intertidal area in the creeks between 1939 and 2021 ranged from 8 to 93%. The correlation between current intertidal area and historical loss of this habitat was negative and significant (Pearson r = -0.91, p = 0.012). Parameters from the regression relating current abundance to intertidal area were used to estimate historic F. heteroclitus abundances in each creek using GIS-derived estimates of historic intertidal area. Historic abundances were predicted to have been on average (across study creeks) 7.5 times greater in 1939 than in 2022. Reduced abundances, and thus reduced trophic relay by F. heteroclitus to higher-order consumers, can be expected in estuaries that have lost salt marsh due to inter-decadal development.
","language":"English","publisher":"MDPI","doi":"10.3354/meps14387","usgsCitation":"Rudershausen, P.J., Lombardo, S.M., Stilson, G.R., and O'Donnell, M.J., 2023, Relating absolute abundance of an estuarine fish to habitat area in an urbanizing environment: Marine Ecologly Progressive Series, v. 719, https://doi.org/10.3354/meps14387.","productDescription":"16 p.","startPage":"92","ipdsId":"IP-146609","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":421066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"719","edition":"77","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rudershausen, Paul J.","contributorId":330010,"corporation":false,"usgs":false,"family":"Rudershausen","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":78765,"text":"Department of Applied Ecology, North Carolina State University, Center for Marine Sciences and Technology","active":true,"usgs":false}],"preferred":false,"id":883852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lombardo, Steven M.","contributorId":330011,"corporation":false,"usgs":false,"family":"Lombardo","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":78766,"text":"Bonefish and Tarpon Trust","active":true,"usgs":false}],"preferred":false,"id":883853,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stilson, George R.","contributorId":330012,"corporation":false,"usgs":false,"family":"Stilson","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":78767,"text":"North Carolina Department of the Environment and Natural Resources, Division of Marine Fisheries","active":true,"usgs":false}],"preferred":false,"id":883854,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O'Donnell, Matthew J. 0000-0002-9089-2377","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":295467,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Matthew","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":883855,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249469,"text":"70249469 - 2023 - Fecal metabarcoding of the endangered Pacific pocket mouse (Perognathus longimembris pacificus) reveals a diverse and forb rich diet that reflects local habitat availability","interactions":[],"lastModifiedDate":"2023-10-10T12:11:11.454532","indexId":"70249469","displayToPublicDate":"2023-09-21T07:09:04","publicationYear":"2023","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":"Fecal metabarcoding of the endangered Pacific pocket mouse (Perognathus longimembris pacificus) reveals a diverse and forb rich diet that reflects local habitat availability","docAbstract":"Information on diet breadth and preference can assist in understanding links between food resources and population growth and inform habitat restoration for rare herbivores. We assessed the diet of the endangered Pacific pocket mouse using metabarcoding of fecal samples and compared it to plant community composition in long-term study plots in two populations on Marine Corps Base Camp Pendleton, San Diego County, CA. Fecal samples (n = 221) were collected between spring 2016 and fall 2017 during monthly live-trap surveys. Concurrently, percent cover and plant phenology were measured in plots centered on trap locations. Fecal samples were sequenced with paired-end reads of the internal transcribed spacer 2 region of the nuclear ribosomal gene, and the resulting amplicons were matched to a regionally specific database. Seventy-three plant taxa were detected, which were mostly forbs and perennial herbs (70–90%). Diet composition differed between populations, years, seasons, and plots. Overall, diet and local habitat composition in plots were significantly correlated. However, we detected some differences in above-ground seed availability and proportion in fecal samples that indicate diet preferences for some forbs, perennial herbs, and native bunch grasses over perennial shrubs and non-native grasses. This is the first study of PPM to pair plant phenology surveys with diet metabarcoding to estimate resource selection, and results suggest that managing habitat for diverse native forb communities and reducing non-native grass cover may be beneficial for this critically endangered species.
No abstract available.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10641-023-01436-8","usgsCitation":"Brant, C., 2023, A memoir very much worth the read: Reviewing: My Life in Fish: One Scientist’s Journey, by Gary D. Grossman (illustrated by Ryan Tavarez), published by Today’s Ecological Solutions (2022): Environmental Biology of Fishes, v. 106, p. 1915-1916, https://doi.org/10.1007/s10641-023-01436-8.","productDescription":"2 p.","startPage":"1915","endPage":"1916","ipdsId":"IP-153441","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":423238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","noUsgsAuthors":false,"publicationDate":"2023-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Brant, Cory 0000-0002-0919-1566","orcid":"https://orcid.org/0000-0002-0919-1566","contributorId":223422,"corporation":false,"usgs":true,"family":"Brant","given":"Cory","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":889511,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70249300,"text":"70249300 - 2023 - Future marsh evolution due to tidal changes induced by human adaptation to sea level rise","interactions":[],"lastModifiedDate":"2023-10-04T12:07:02.06102","indexId":"70249300","displayToPublicDate":"2023-09-21T07:00:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Future marsh evolution due to tidal changes induced by human adaptation to sea level rise","docAbstract":"With sea level rise threatening coastal development, decision-makers are beginning to act by modifying shorelines. Previous research has shown that hardening or softening shorelines may change the tidal range under future sea level rise. Tidal range can also be changed by natural factors. Coastal marshes, which humans increasingly depend on for shoreline protection, are ecologically sensitive to tidal range. Therefore, it is critical to examine how changes in tidal range could influence marsh processes. A marsh accretion model was used to investigate the ecological response of a San Francisco Bay, California, USA marsh to multiple tidal range scenarios and sea level rise from 2010 to 2100. The scenarios include a baseline scenario with no shoreline modifications in the estuary, a shoreline hardening scenario that amplifies the tidal range, and 14 tidal range scenarios as a sensitivity analysis that span tidal amplification and reduction of the baseline scenario. The modeling results expose key tradeoffs to consider when planning for sea level rise. Compared to the baseline, the hardening scenario shows minor differences. However, further tidal amplification prolongs marsh survival but decreases Sarcocornia pacifica cover, an important species for certain threatened wildlife and an effective attenuator of wave energy. Conversely, tidal reduction precipitates marsh drowning but shows gains in Sarcocornia pacifica cover. These mixed impacts of tidal amplification and reduction shown by the model indicate potential tradeoffs in relation to marsh survival, habitat characteristics, and shoreline protection. This study suggests the need for a cross-sectoral, regional approach to sea level rise adaptation.