Invasive carp (Hypophthalmichthys nobilis [Bighead Carp], Mylopharyngodon piceus [Black Carp], Ctenopharyngodon idella [Grass Carp], and H. molitrix [Silver Carp]) continue to spread in the United States and deterrents at river navigation locks are one emerging control strategy for slowing the spread. High-head navigation dams on large rivers serve as impediments to the upstream spread of these populations. One possible control technique is using a multimodal deterrent that utilizes a combination of lights, sound, and air bubbles to guide fish away from a location. Laboratory tests and small-scale field deployments of similar multi-stimuli deterrents have demonstrated potential for deterring invasive carp. These earlier studies led to the deployment and initiation of a field study of a multimodal deterrent in 2019 at the downstream lock approach at Barkley Lock and Dam on the Cumberland River near Grand Rivers, Kentucky. We are using two types of telemetry systems to evaluate how the multimodal deterrent affects movement and behavior of Silver Carp, Grass Carp, and four native species: Aplodinotus grunniens (Freshwater Drum), Polyodon spathula (Paddlefish), Ictiobus bubalus (Smallmouth Buffalo), and Acipenser fulvescens (Lake Sturgeon). We are evaluating fish movements in response to the multimodal deterrent by using a study design that cycles between 1 week with the multimodal deterrent on and 1 week with it off. This weekly cycling provides baseline comparisons across variable environmental conditions. When the multimodal deterrent is on, the number of Silver Carp completing upstream passage through Barkley Lock is reduced by about one-half. This study that began in 2019 can provide insights into the effectiveness of a multimodal deterrent for limiting upstream movement of invasive carp or effects on native fishes through strategic navigation locks on large rivers.
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LANDFIRE (LF) completed the LF 2016 Remap effort in 2021, the biggest revision of its product suite since its inception. This document serves to describe the processes that went into this effort and elucidate the methods for creating each LF product. Although the document focuses on the LF 2016 Remap effort, it also details the two updates that have been completed since that effort, LF 2019 Limited (released June 2021) and LF 2020 (underway at the writing of this document).
The LF program is complex, requiring a team of interdisciplinary professionals to manage, produce, and maintain it. LF data production falls under six primary categories: reference, disturbance, vegetation, fuels, fire regime, and topography. Several data production units have the dual goals of producing a valuable stand-alone dataset and serving subsequent LF production needs. This document delves into the technical details of the six primary categories individually while also describing the connections to other LF products. Importantly, this LF technical documentation provides a transparent view of actual LF data layer production processes and can become a general information source for future production, production improvements, user questions, and leadership reference.
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Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The nesting biology and demography of spectacled eiders (Somateria fischeri) along the lower Kashunuk River on the Yukon-Kuskokwim Delta, Alaska, were studied from 1993 to 2002. This previous work demonstrated that the breeding population on the study area was declining, and demographic modeling predicted that the population would continue to decline from 2002 forward. The predicted decline was primarily because of lead shot in tundra wetlands in the area, exposure of nesting females to lead, resulting in low adult female survival. The model predicted that lead pellets already in wetlands would slowly settle beyond the foraging depth of eiders, and that, lead exposure rates would decline. The goal of this project was to test this prediction by revisiting the lower Kashunuk River study area in 2022 to (1) update previous datasets regarding demographic parameters and (2) validate (or refute) existing models relative to lead exposure rates and the effects of lead on population dynamics. In the summer of 2022, a total of 37 nests were found in a sub-area of the historical study area. Comparing to past efforts in this same sub-area, more nests were found than predicted but the proportion of nesting female spectacled eiders exposed to lead in 2022 (24.3 percent) was still similar to levels of exposure observed between 1994 and 2002 (28.5 percent). Thus, data from the 2022 survey suggests that the earlier decline in numbers of nesting spectacled eiders has reversed, but there has been little decrease in lead exposure over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231052","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Flint, P.L., 2023, Status of spectacled eiders (Somateria fischeri) on the Yukon-Kuskokwim Delta, Alaska, 2022—Testing and updating predictive models: U.S. Geological Survey Open-File Report 2023–1052, 5 p., https://doi.org/10.3133/ofr20231052.","productDescription":"vi, 5 p.","onlineOnly":"Y","ipdsId":"IP-151770","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":419316,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1052/ofr20231052.XML"},{"id":419315,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1052/images"},{"id":419314,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231052/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1052"},{"id":419313,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1052/ofr20231052.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1052"},{"id":419312,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1052/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-Kuskokwim Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166.06721221943172,\n 61.59887493914758\n ],\n [\n -166.06721221943172,\n 60.1670676261173\n ],\n [\n -162.86058022136012,\n 60.1670676261173\n ],\n [\n -162.86058022136012,\n 61.59887493914758\n ],\n [\n -166.06721221943172,\n 61.59887493914758\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
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This report outlines quality assurance (QA) processes, including radiometric and geometric calibration guidelines, and guidelines for data acquisition and quality control to be followed by U.S. Geological Survey (USGS) researchers for acquiring and processing uncrewed aircraft systems (UAS) data. These QA processes ensure that UAS data can be used for quantitative analysis and are comparable with other standard geospatial data.
Remote sensing data play a critical role in monitoring Earth’s resources. Traditionally, the USGS and Department of the Interior have used well calibrated metric sensors mounted on satellite or aircraft platforms to collect these data. These sensors and platforms are stable, and data have been processed using standard pipelines. These processes ensured that the data are generally consistent with each other and benefitted a diverse group of users. These data are shared among multiple researchers around the world through the internet and other means, using standard formats and metadata.
In the last few years, UAS platforms have democratized the remote sensing data collection further, bringing an unparalleled level of control of time, sensors, and processes to individual researchers. Together with the development of cheaper and lighter sensors and relaxation of prohibitions against UAS operation in the National Airspace System by the Federal Aviation Authority, researchers can collect remote sensing data using UAS platforms. Researchers often customize the sensors on these UAS systems based on their specific requirements and use ad hoc processing steps to generate data.
A challenge is that these data are often produced by a wide array of sensors and processes that render them potentially inconsistent with each other. Therefore, unlike data collected from metric sensors, UAS-based data are designed to benefit only specific user groups. The data thus generated often lack traceability to known standards, making them difficult to use with other geospatial data.
This report provides radiometric and geometric calibration guidelines, as well as guidelines for data acquisition and quality control, that can be followed by USGS researchers in acquiring and processing UAS data. Instead of calibrating sensors, researchers collecting UAS data can focus on calibrating the data. Various radiometric calibration processes are provided, and the two panel empirical line method is highlighted for radiometric calibration.
For geometric calibration, USGS and Department of the Interior researchers are experienced in following standard calibration procedures provided by standard UAS data processing software. However, researchers may be aided in paying attention to the tie points and the accuracy of the ground control points used for geometric calibration and data production. The accuracy of ground control points are related to the requirements of the project. The ground control points and the quality of tie points directly contribute to the geometric accuracy of the data, regardless of the ground sample distance of the imagery.
The guidelines outlined in this report are intended to ensure that the data are in common units and are quantifiable and comparable with other data. These QA and calibration processes can be critical in ensuring that these datasets are used to the maximum extent possible. Including the calibration parameters (and their uncertainties) as part of metadata can allow for easier data discovery and analytical filters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231033","usgsCitation":"Sampath, A., Shrestha, M., While, M., and Scholl, V.M., 2023, Guidelines for calibration of uncrewed aircraft systems imagery: U.S. Geological Survey Open-File Report 2023–1033, 23 p., https://doi.org/10.3133/ofr20231033.","productDescription":"v, 23 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-146359","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":419305,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231033/full"},{"id":419252,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1033/images/"},{"id":419251,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1033/ofr20231033.XML"},{"id":419250,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1033/ofr20231033.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1033"},{"id":419249,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1033/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
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 1 (January–March) 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 safehold anomaly. On January 26, 2023, the Global Positioning System (GPS) onboard Landsat 8 became invalid because the GPS fault tripped. Later that same day, the GPS was reinitialized, but a Field of View 1 fault trip occurred early the next morning, causing the observatory to go into Earth Point Safe mode, which put the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) into safehold. Once it was safe to reactivate the sensors, the OLI was transitioned to operational status late on January 27 and TIRS was reactivated early on January 28. Additional information about the Landsat 8 safehold anomaly is here: https://www.usgs.gov/landsat-missions/news/landsat-8-recovers-safehold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231050","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T.Z., Shaw, J.L., Denevan, A., Franks, S., Micijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., and Miller, J., 2023, ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2023: U.S. Geological Survey Open-File Report 2023–1050, 39 p., https://doi.org/10.3133/ofr20231050.","productDescription":"Report: vii, 39 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-152817","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":419162,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":419161,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1050/images/"},{"id":419158,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1050/coverthb.jpg"},{"id":419181,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231050/full"},{"id":419160,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1050/ofr20231050.XML"},{"id":419159,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1050/ofr20231050.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1050"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
A telemetry study was conducted during March–October 2022 to evaluate behavior and movement patterns of adult smallmouth bass (Micropterus dolomieu) in the forebay of Bonneville Dam, on the Columbia River in Washington and Oregon. This study was a follow-up to a previous study conducted at the site during August–December 2020. In 2022, a total of 41 smallmouth bass were collected, tagged, and released during March–May in three distinct areas of the dam forebay and monitored until late-October. Movement data from 39 tagged smallmouth bass were used in behavior analyses with an average detection duration (elapsed time from release to last detection) of 121.5 days. Most tagged smallmouth bass had site fidelity while present in the forebay of Bonneville Dam, primarily remaining within their zone of release, or moving into nearby adjacent zones. Although site fidelity was common during the study, we found that some tagged smallmouth bass left the forebay of Bonneville Dam and moved substantial distances upstream or downstream. Thirty-six percent of the tagged smallmouth bass were detected at least 8 kilometers upstream or downstream from the Bonneville Dam at some point during the study period (several of these fish eventually returned to the forebay), and 10 percent of the tagged fish were detected at sites located 24 river kilometers upstream or downstream from the dam. Results from this study build upon previous data collected during 2020 and provide new insights into behavior patterns of smallmouth bass collected and tagged in the Bonneville Dam forebay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231046","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Kock, T.J., and Hansen, G.S., 2023, Behavior and movement of smallmouth bass (Micropterus dolomieu) near Bonneville Dam, Columbia River, Washington and Oregon, March–October 2022: U.S. Geological Survey Open-File Report 2023–1046, 14 p., https://doi.org/10.3133/ofr20231046.","productDescription":"vii, 14 p.","onlineOnly":"Y","ipdsId":"IP-150147","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":419025,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231046/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1046"},{"id":419024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1046/ofr20231046.pdf","text":"Report","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1046"},{"id":419023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1046/coverthb.jpg"},{"id":419027,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1046/ofr20231046.XML"},{"id":419026,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1046/images"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Bonneville Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.98471940891719,\n 45.66526448575243\n ],\n [\n -121.98471940891719,\n 45.62085268028778\n ],\n [\n -121.90466791018856,\n 45.62085268028778\n ],\n [\n -121.90466791018856,\n 45.66526448575243\n ],\n [\n -121.98471940891719,\n 45.66526448575243\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The Poso Creek Oil Field is one of the many fields selected for regional groundwater mapping and monitoring by the California State Water Resources Control Board as part of the Oil and Gas Regional Monitoring Program (RMP; California State Water Resources Control Board, 2015, 2022b; U.S. Geological Survey, 2022a). The U.S. Geological Survey (USGS), in cooperation with the California State Water Resources Control Board, is evaluating several questions about oil and gas development and groundwater resources in California, including (1) the location of groundwater resources; (2) the proximity of oil and gas operations to groundwater and the geologic materials between them; (3) evidence (or no evidence) of fluids from oil and gas sources in groundwater; and (4) the pathways or processes responsible when fluids from oil and gas sources are present in groundwater (U.S. Geological Survey, 2022a). As part of this evaluation, the USGS installed a multiple-well monitoring site within the administrative boundary of the Poso Creek Oil Field about 12 miles north of Bakersfield, California (fig. 1). Data collected at the Poso Creek multiple-well monitoring site (PCCT) provide information about the geology, hydrology, geophysical properties, and water quality of the aquifer system overlying the oil-bearing zone, thus enhancing understanding of relations between adjacent groundwater and the Poso Creek Oil Field in an area where groundwater data are limited, particularly at different depths in the aquifer. This report presents construction information for the PCCT and initial geohydrologic data collected from the site. Similar sites installed on the east side of the Lost Hills Oil Field and North and South Belridge Oil Fields were described by Everett and others (2020a, b).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231047","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Everett, R.R., McMahon, P.B., Stephens, M.J., Gillespie, J.M., Shepherd, M.M., and Fenton, N.C., 2023, Multiple-well monitoring site within the Poso Creek Oil Field, Kern County, California: U.S. Geological Survey Open-File Report 2023-1047, 11 p., https://doi.org/10.3133/ofr20231047.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-143467","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499783,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114968.htm","linkFileType":{"id":5,"text":"html"}},{"id":418877,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/preview/ofr20231047/full"},{"id":418876,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1047/images"},{"id":418875,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1047/ofr20231047.xml"},{"id":418874,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1047/ofr20231047.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":418873,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1047/covrthb.jpg"}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Poso Creek Oil Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.02751948230053,\n 35.55715768005527\n ],\n [\n -119.02751948230053,\n 35.37156425616723\n ],\n [\n -118.8051417495576,\n 35.37156425616723\n ],\n [\n -118.8051417495576,\n 35.55715768005527\n ],\n [\n -119.02751948230053,\n 35.55715768005527\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
This report provides analysis to extend the 2040 forecasts of polar bear (Ursus maritimus) land use for the southern Beaufort and Chukchi Sea populations presented in a recent publication (Rode and others, 2022) through the year 2065. To inform long-term polar bear management considerations, we provide point-estimate forecasts and 95-percent prediction intervals of the proportion of polar bear populations summering onshore for 21 days or more (≥) and their duration onshore every 5 years from 2040 to 2065. Because sea-ice projections based on earth system models show greater divergence with emission scenarios after 2040, we have provided forecasts for three greenhouse gas emission scenarios, SSP1-2.6, SSP2-4.5 and SSP5-8.5, compared to the two emission scenarios used in Rode and others (2022). Our forecasting methods estimated that 61–97 percent of polar bears in the southern Beaufort Sea and 80–100 percent of polar bears in the Chukchi Sea populations may summer onshore for ≥21 days by 2065. Forecasts of mean duration onshore were 105–158 days for polar bears in the southern Beaufort Sea and 111–178 days in the Chukchi Sea populations by 2065. Sea ice conditions projected to occur by 2065 could alter the current patterns of bear behavior from what has been observed over the past 30 years. As a result, these extended projections are associated with a higher degree of uncertainty than estimates through 2040, especially under the SSP5-8.5 scenario.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231048","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Rode, K.D., Douglas, D.C., Atwood, T.C., and Wilson, R.R., Forecasts of polar bear (Ursus maritimus) land use in the southern Beaufort and Chukchi Seas, 2040–65: U.S. Geological Survey Open-File Report 2023–1048, 7 p., https://doi.org/10.3133/ofr20231048.","productDescription":"Report: vi, 7 p.; Data Release","numberOfPages":"7","onlineOnly":"Y","ipdsId":"IP-148069","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":418953,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211048/full"},{"id":418955,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1048/images"},{"id":418954,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1048/ofr20231048.xml"},{"id":418956,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XEOBWV","text":"Polar bear Continuous Time-Correlated Random Walk (CTCRW) location data derived from satellite location data, Chukchi and Beaufort Seas, July-November 1985-2017","description":"Rode, K. D., Douglas, D. C., Atwood, T. C., Durner, G. M., Wilson, R. R., Bromaghin, J. F., Pagano, A. M. and Simac, K. S., 2022, Polar bear Continuous Time-Correlated Random Walk (CTCRW) location data derived from satellite location data, Chukchi and Beaufort Seas, July-November 1985-2017: U.S. Geological Survey data release, https://doi.org/10.5066/P9XEOBWV."},{"id":418951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1048/covrthb.jpg"},{"id":418952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1048/ofr20231048.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The Rocky Flats National Wildlife Refuge (RFNWR) in Colorado is home to increasingly rare, xeric tallgrass prairie. The RFNWR is also located near many combustion and agricultural sources of inorganic reactive nitrogen (Nr), which emit Nr to the atmosphere. Wet atmospheric deposition of Nr was monitored at RFNWR during 2017–19 by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service. Comparison of measured Nr deposition amounts to critical load values indicated local urban air pollution is at a level that could impair the protected RFNWR habitat.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231027","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Wetherbee, G.A., 2023, Atmospheric deposition of inorganic reactive nitrogen at the Rocky Flats National Wildlife Refuge, 2017–19: U.S. Geological Survey Open-File Report 2023–1027, 1 sheet, available at https://doi.org/10.3133/ofr20231027.","productDescription":"1 Sheet: 40.00 × 30.00 inches; Data Release; Project Site","onlineOnly":"Y","ipdsId":"IP-136270","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":418692,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://nadp.slh.wisc.edu/","text":"National Atmospheric Deposition Program"},{"id":418689,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1027/coverthb.jpg"},{"id":418690,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1027/ofr20231027.pdf","text":"Report","size":"1.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1027"},{"id":418691,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OOIQ0E","text":"USGS data release","linkHelpText":"Chemical analyses and precipitation depth data for wet deposition samples collected as part of the National Atmospheric Deposition Program in the Colorado Front Range, 2017-2019"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Flats National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.26103714983329,\n 39.95142757778845\n ],\n [\n -105.26103714983329,\n 39.83241452322963\n ],\n [\n -105.11415803005896,\n 39.83241452322963\n ],\n [\n -105.11415803005896,\n 39.95142757778845\n ],\n [\n -105.26103714983329,\n 39.95142757778845\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Observing Systems Division
Hydrologic Instrumentation Facility
U.S. Geological Survey
Buildings 2101 2204 HIF
Stennis Space Center
Bay St Louis, MS 39529
We completed four protocol surveys for Least Bell’s Vireos (Vireo bellii pusillus; vireo) during the breeding season, supplemented by weekly territory monitoring visits. We identified a total of 133 territorial male vireos; 114 were confirmed as paired, and 3 were confirmed as single males. For the remaining 16 territories, we were unable to confirm breeding status. Two transient vireos were detected in 2022. The vireo population in the Project Area increased by 9 percent from 2021 to 2022. The vireo population at Marine Corps Base Camp Pendleton also increased (4 percent), whereas the population at Marine Corps Air Station remained relatively stable (decreased from 10 pairs to 9) and the Otay River population decreased by 10 percent (2 territories).
We used an index of treatment (Treatment Index) to evaluate the effect of on-going vegetation clearing on the Project Area vireo population. The Treatment Index measures the cumulative effect of vegetation treatment within a territory (since 2005) by using the percentage area treated weighted by the number of years since treatment. We determined that the Treatment Index for unoccupied habitat was more than four times that of occupied habitat, indicating that vireos selected habitat that was less treated in which to settle.
We monitored vireo nests at three general site types: (1) within the flood channel where exotic and native vegetation removal has occurred regularly (Channel), (2) three sites near the flood channel where limited exotic and native vegetation removal has occurred (Off-channel), and (3) three sites that have been actively restored by planting native vegetation (Restoration). Nesting activity was monitored in 80 territories, 3 of which were occupied by single males and 1 by a male whose breeding status could not be confirmed. Overall, 38 percent of completed nests were successful and nest success did not differ among the three sites. In 2022, there were no differences with regard to clutch size, hatching, or fledging success among Channel, Off-channel and Restoration sites. Overall breeding success and productivity were slightly higher in 2022 than in 2021, with 72 percent of pairs fledgling at least one young and pairs fledging an average of 2.2±1.7 young.
To investigate if the cumulative years of treatment had an effect on vireo reproductive effort, we looked at the effects of the Treatment Index on reproductive parameters. Results from generalized linear models indicated that treatment did not have an effect on vireo nesting effort or the number of vireo fledglings per pair produced in 2022. Similarly, we did not detect an effect of Treatment Index on daily survival rate (DSR) of nests.
Analysis of vegetation data collected at vireo nests from 2006 to 2022 did not reveal an effect of vegetation cover at the nest on DSR. We did find, however, that Channel nests were placed higher in the host plant than Off-channel nests. In the Channel and Off-channel sites, successful nests were placed closer to the edge of the host plants than unsuccessful nests. Additionally, successful Off-channel nests were placed lower in the vegetation, in shorter host plants, and closer to the edge of the vegetation clump than unsuccessful nests.
Red/arroyo willow (Salix laevigata or Salix lasiolepis) were the species most commonly selected for nesting by vireos in all three site types. Black willow (Salix gooddingii) and mule fat (Baccharis salicifolia) also were commonly used. Vireos used a wider variety of species for nesting in Channel and Off-channel sites (eight and six species, respectively) compared to Restoration sites (two species), although there was limited nesting in Restoration sites in 2022.
There were 43 vireos banded before the 2022 breeding season that were resighted and identified at the Project Area in 2022, all of which were originally banded in the Project Area. Adult birds of known age ranged from 1 to 7 years old. A total of 146 vireos were newly banded in 2022. There were 8 adult vireos banded with a unique color combination, and 138 nestlings were banded with a single dark blue numbered federal band on the left leg. Between 2006 and 2022, survivorship of males (66±11 percent) was consistently higher than that of females (59±12 percent). First-year birds from 2006 to 2022 had an average annual survivorship of 15±6 percent.
First-year dispersal in 2022 averaged 6.7±7.4 kilometers (km), with the longest dispersal (15.3 km) by a male that was recaptured at Fallbrook Creek, Fallbrook Naval Weapons Station (FNWS). From 2007 to 2011, most returning first-year vireos returned to the Project Area, whereas from 2014 to 2016, the majority of returning birds dispersed to areas outside of the Project Area. From 2018 to 2021, the trend shifted, and more first-year vireos returned to the Project area. In 2022, only one first-year vireo returned to the project area and two dispersed to sites outside the Project Area (upstream to the middle San Luis Rey River and to Fallbrook Creek, FNWS). However, the total number of identified first-year vireos was low and the trend in 2022 will likely shift as additional returning first-year vireos are identified in subsequent years.
Most of the returning adult male vireos showed strong between-year site fidelity to their previous territories. Seventy-three percent of males (27/37) occupied a territory in 2022 that they had defended in 2021 (within 100 meters [m]). There were no females (0/4) detected in 2022 that returned to a territory they occupied in 2021; however, 50 percent of females (2/4) detected in 2022 returned to areas adjacent to their previous territories (within 300 m). The average between-year movement for returning adult vireos was 0.3±0.7 km. The amount of treatment at adults’ 2021 territories did not affect the distance adults moved to their 2022 territories.
We completed four protocol surveys for the endangered Southwestern Willow Flycatcher (Empidonax traillii extimus; flycatcher) at the Project Area between May 16 and July 25, 2022. Four transient Willow Flycatchers were detected in the Project Area in 2022. Two transients were detected in Reach 1, one in Reach 3a, and one in Pilgrim Pond. There were not any resident flycatchers documented in the Project Area in 2022.
A total of 46 vegetation transects (528 points) were sampled at the Project Area in 2022. Seventy-one percent (378/528) of points were located in the Channel, and 22 percent (115/528) were in Upper Pond. The remaining 7 percent (35/528) of points were at the Whelan Restoration site. Foliage cover below 2 m was higher at the Channel points compared to Upper Pond and Whelan Restoration, which can be attributed to the dense herbaceous vegetation that grows after mowing. Above 2 m, foliage cover was similar at the Channel and Whelan Restoration sites and was higher than at Upper Pond. Average canopy height was higher in the Channel (5.6±3.4 m) compared to Upper Pond (4.7±2.9 m) and Whelan Restoration (4.6±1.9 m). From 2006 to 2022, total foliage cover declined above 2 m in the Channel, in contrast to Upper Pond and Whelan Restoration, where little directional change in vegetation cover has occurred and where vegetation cover has largely recovered to 2006 levels. Within the Channel, the steepest declines occurred between 2009 and 2013 and between 2014 and 2016. Since 2016, we observed an increase in foliage cover, largely herbaceous, between 0 and 2 m within the Channel. The percent cover remained below levels detected before 2009 for other height classes.
We sampled vegetation at 44 vireo nests and 44 random plots (“territory” plots) within territories in the Channel and Upper Pond after the 2022 breeding season. Vireos in the Channel established territories in areas with significantly more cover from 3 to 6 m but less cover below 2 m relative to the available habitat. Within territories, Channel vireos selected nest sites with significantly more foliage cover from 2 to 3 m. Vireos at Upper Pond established territories in areas with significantly more foliage cover from 5 to 6 m and below 1 m relative to available habitat. However, within territories, Upper Pond vireos selected nest sites with significantly less foliage cover from 5 to 6 m and below 1 m.
Data either are not available or have limited availability owing to restrictions of the funding entity (U.S. Army Corps of Engineers). Please contact Christopher Chabot, Planning Division, Los Angeles District, U.S. Army Corps of Engineers, for more information.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231040","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Houston, A., Allen, L.D., Mendia, S.M., and Kus, B.E., 2023, Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey Flood Risk Management Project Area in San Diego County, California—Breeding activities and habitat use—2022 annual report: U.S. Geological Survey Open-File Report 2023–1040, 74 p., https://doi.org/10.3133/ofr20231040.","productDescription":"viii, 74 p.","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-150400","costCenters":[{"id":651,"text":"Western Ecological Research 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Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Loss and degradation of sagebrush (Artemisia spp.) rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are significant management, conservation, and economic issues in the western U.S. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (hereinafter, “Needs”) for informing the actions proposed under the five topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse (Centrocercus urophasianus), Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.”
Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts.
This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed four Needs identified under the Climate and Weather topic in the Plan. The topic outlined research Needs broadly focused on understanding the potential effects of climate change on vegetative resilience to inform restoration of sagebrush rangelands. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (hereinafter, “Next Steps”) were either addressed well, partially addressed or remain outstanding (that is, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 92 science products that at least partially addressed a Need identified in the Climate and Weather topic. The Needs that were well and partially addressed included:
The Need addressed poorly was the identification of native plant species, genotypes and ecotypes, and seed mixes that may be resilient to a changing climate. The information provided in this assessment will assist updating the Plan, and can inform updates of other relevant science planning documents as needed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231035","usgsCitation":"Anthony, C.R., Holloran, M.J., Ricca, M.A., Hanser, S.E., Phillips, S.L., Steblein, P., and Wiechman, L.A., 2023, Integrated rangeland fire management strategy actionable science plan completion assessment— Climate and weather topic, 2015–20: U.S. Geological Survey Open-File Report 2023–1035, 21 p., https://doi.org/10.3133/ofr20231035.","productDescription":"vi, 21 p.","onlineOnly":"Y","ipdsId":"IP-146246","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":418269,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1035/ofr20231035.pdf","text":"Report","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1035"},{"id":418268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1035/coverthb.jpg"},{"id":418270,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231035/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1035"},{"id":418484,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231003","text":"OFR 2023-1003 —","description":"OFR 2023-1003","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Invasives topic, 2015–20"},{"id":418485,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231004","text":"OFR 2023-1004 —","description":"OFR 2023-1004","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Restoration topic, 2015–20"},{"id":418486,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231009","text":"OFR 2023-1009 —","description":"OFR 2023-1009","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Fire topic, 2015–20"},{"id":499777,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114937.htm","linkFileType":{"id":5,"text":"html"}},{"id":418487,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231010","text":"OFR 2023-1010 —","description":"OFR 2023-1010","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Sagebrush and sage-grouse topic, 2015–20"},{"id":418272,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1035/ofr20231035.XML"},{"id":418271,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1035/images"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.36129089491212,\n 48.70726157141266\n ],\n [\n -123.36129089491212,\n 35.200401221823014\n ],\n [\n -101.0466463055924,\n 35.200401221823014\n ],\n [\n -101.0466463055924,\n 48.70726157141266\n ],\n [\n -123.36129089491212,\n 48.70726157141266\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
Increasing density of pinyon (Pinus spp.) and juniper (Juniperus spp.) woodlands (hereinafter “pinyon-juniper”), as well as expansion of these woodlands into adjacent shrublands and grasslands, has altered ecosystem function and wildlife habitat across large areas of the interior western United States. Although there are many natural and human-caused drivers of woodland infilling and expansion, restoration of sagebrush (Artemisia spp.) habitat through removal of pinyon-juniper is considered an urgent management objective in many locations, particularly in support of sagebrush-dependent wildlife species of conservation concern. In December 2020, the Bureau of Land Management (BLM) established the Pinyon-Juniper Management Categorical Exclusion (PJCX) to expedite the regulatory process for pinyon-juniper removal projects on public lands, largely intended to benefit mule deer (Odocoileus hemionus) and greater sage-grouse (Centrocercus urophasianus) habitats. During final preparation of this report, the BLM discontinued use of the PJCX (as of November, 2022), but the pinyon-juniper tree removal techniques assessed in this report are commonly used and understanding their effects remains relevant to land use planning.
To address areas of uncertainty relative to potential ecological effects of the PJCX, we conducted a review of the peer-reviewed science literature to better understand the likely responses of vegetation, environmental (for example, soils), and wildlife variables to specific tree removal techniques permitted by the PJCX. In brief, the PJCX permitted removal of trees by either manual cutting, mechanical cutting, or mastication; allowed certain methods to redistribute or remove resulting tree biomass after treatment; and prohibited broadcast burning, roadbuilding, removal of old-growth, and seeding of non-native species. Specifically, we conducted our review to address the following questions:
To answer these questions, we considered studies related to pinyon-juniper ecosystems, focusing on research that occurred over a large portion of the interior western United States that is the primary focus of the PJCX. We also focused on papers published from 2014 onward, to avoid excessive overlap with other recent reviews on pinyon-juniper management effects. Using strict criteria, including only considering research that tested responses for statistical significance, we identified 48 papers that primarily examined treatment effects on vegetation and other environmental variables (1,709 responses), and 11 papers that addressed effects on wildlife (132 responses). Responses to the PJCX-permitted treatments were summarized as either positive (that is, a significant increase), negative (that is, a significant decrease), or non-significant (that is, no significant difference). Responses were assigned to categories (for example, Native Annual Grass/Forb Abundance) and hierarchical treatment levels.
We found that there were large proportions of non-significant responses among all categories combined, with roughly half or more of all responses non-significant (48 percent for wildlife, 60 percent for vegetation-environmental), comparable to other recent systematic reviews of pinyon-juniper treatment effects. However, we also found that when there were significant responses, some important trends potentially emerged. Important undesirable outcomes included far more positive than negative responses of exotic grass and forb abundance among nearly all treatment types. Cutting treatments were also more likely to decrease biocrust cover and microbial activity. Potentially beneficial outcomes included mostly positive responses among sagebrush obligate species, including more positive than negative responses for mule deer and sage-grouse. Some treatment types (for example, mastication) also resulted in more positive than negative responses for native grasses and forbs (although, non-significant responses were the majority). We also highlighted many limitations of this review, including how responses often come from few studies, and how some response-treatment category combinations lack adequate response data. Moreover, the existing research is often insufficient to address many key questions about treatment effects, largely owing to short time-scales and limited spatial extents of observations, which do not match the size of treatments being implemented by land managers, nor capture long-term, post-treatment ecological dynamics. We also identify a lack of research that addresses key interactions that could undermine restoration objectives, including potential effects of climate change and grazing on post-treatment environments. Thus, we emphasize the importance of integrating these factors into future pinyon-juniper treatment research, and we stress the need for use of monitoring programs and research studies that partake in data collection and analysis over long durations and broad spatial scales.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231041","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Shinneman, D.J., McIlroy, S.K., Poessel, S.A., Downing, R.L., Johnson, T.N., Young, A.C., and Katzner, T.E., 2023, Ecological effects of pinyon-juniper removal in the Western United States—A synthesis of scientific research, January 2014–March 2021: U.S. Geological Survey Open-File Report 2023–1041, 56 p., https://doi.org/10.3133/ofr20231041.","productDescription":"viii, 56 p.","onlineOnly":"Y","ipdsId":"IP-147314","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":417951,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1041/images"},{"id":417950,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231041/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1041"},{"id":417949,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1041/ofr20231041.pdf","text":"Report","size":"96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1041"},{"id":417948,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1041/coverthb.jpg"},{"id":417952,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1041/ofr20231041.XML"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -127.07350481470358,\n 50.40448106244946\n ],\n [\n -127.07350481470358,\n 30.159124183877992\n ],\n [\n -101.68400762449346,\n 30.159124183877992\n ],\n [\n -101.68400762449346,\n 50.40448106244946\n ],\n [\n -127.07350481470358,\n 50.40448106244946\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
Sablefish (Anoplopoma fimbria) is a commercially valuable groundfish species in Alaska, with the population assessed annually by the National Oceanic and Atmospheric Administration Alaska Fisheries Science Center. Sablefish recruit into the commercially fished population at 2 years old and are poorly sampled by most surveys before that age. However, information on the abundance, distribution, and size of pre-recruitment age fish is valuable as an ecosystem indicator for older fish. Size and an index of growth rate of age-0 sablefish were quantified using samples from seabird diets at Middleton Island, Alaska, an island in the northern Gulf of Alaska. Age-0 sablefish information may serve as an indicator for potential recruitment into older age populations. This report (1) provides information on the data collection for age-0 sablefish from seabird diets at Middleton Island, Alaska from 1978 to 2022, (2) describes a method for quantifying age-0 sablefish size and growth rate, and (3) describes the size and growth rate of sablefish sampled over time. An annual release of age-0 sablefish size and growth data by U.S. Geological Survey based on continued collections on Middleton Island, Alaska, may be used to assess ecosystem status and as a recruitment indicator for sablefish.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231049","collaboration":"Prepared in cooperation with National Oceanic and Atmospheric Administration Alaska Fisheries Science Center","usgsCitation":"Arimitsu, M.L., and Hatch, S.A., 2023, Age-0 sablefish size and growth indices from seabird diets at Middleton Island, Gulf of Alaska: U.S. Geological Survey Open-File Report 2023–1049, 4 p., https://doi.org/10.3133/ofr20231049.","productDescription":"Report: v, 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-151412","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":418265,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94KVH9X","text":"USGS data release","description":"USGS data release","linkHelpText":"Age-0 Sablefish size and growth indices from seabird diets at Middleton Island, Alaska"},{"id":418263,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1049/ofr20231049.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1049"},{"id":418262,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1049/coverthb.jpg"},{"id":418267,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1049/ofr20231049.XML"},{"id":418266,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1049/images"},{"id":418264,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231049/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1049"}],"country":"United States","state":"Alaska","otherGeospatial":"Middleton Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -147.10005001165774,\n 59.77785521975687\n ],\n [\n -147.10005001165774,\n 58.9779941146154\n ],\n [\n -145.39789946473627,\n 58.9779941146154\n ],\n [\n -145.39789946473627,\n 59.77785521975687\n ],\n [\n -147.10005001165774,\n 59.77785521975687\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
This report addresses system characterization of the BlackSky Global satellites and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
The BlackSky Global satellites are three-band multispectral imagers (red, green, and blue multispectral bands plus a panchromatic band) with a 0.8- to 0.9-meter (m) pixel ground sample distance for the assessed satellites. BlackSky Global satellites 9 and 12–17 were launched in March and December 2021, respectively, into a Sun-synchronous orbit of 430–450 kilometers with an inclination of 42–53 degrees and a swath width of 6 kilometers at nadir. Each Global satellite has an expected lifetime of about 3 years. More information on the BlackSky Global satellites is available in the “Land Remote Sensing Satellites Online Compendium” (https://calval.cr.usgs.gov/apps/compendium) and from BlackSky at Real-Time Space-Based Intelligence (blacksky.com)
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior) and spatial performances. Results of these analyses indicate that the assessed BlackSky Global satellites have an interior geometric performance in the range of −0.011 m (−0.012 pixel) to 0.007 m (0.008 pixel) in easting and −0.018 m (−0.020 pixel) to 0.012 m (0.013 pixel) in northing in band-to-band registration; an exterior geometric performance using ground control points of 8.0-m circular error (95-percent certainty) for orthorectified products and 10.7- to 17.4-m circular error (95-percent certainty) for nonorthorectified products, depending on the geolocation metadata used; and a spatial performance in the range of 1.70 to 2.43 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.032 to 0.084.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030O","usgsCitation":"Vrabel, J.C., Anderson, C., Bresnahan, P.C., Christopherson, J.B., Clauson, J., Kim, M., Ryan, R.E., and Sampath, A., 2023, System characterization report on the BlackSky Global multispectral sensor (ver. 1.1, April 2024), chap. O of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 23 p., https://doi.org/10.3133/ofr20211030O.","productDescription":"Report: v, 23 p., Version History","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-150816","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":428109,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1030/o/versionHist.txt","text":"Version History","size":"1.33 kB","linkFileType":{"id":2,"text":"txt"}},{"id":417822,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/o/ofr20211030o.XML"},{"id":417821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/o/ofr20211030o.pdf","text":"Report","size":"3.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–O"},{"id":417820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/o/coverthb2.jpg"}],"edition":"Version 1.0: June 6, 2023; Version 1.1: April 29, 2024","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The U.S. Geological Survey, in cooperation with the Suffolk County Water Authority, evaluated the groundwater-flow characteristics and aquifer properties of the North Magee Street well field north of the village of Southampton, New York. Characteristics and properties included groundwater-flow direction, potential groundwater-contributing areas to the well field production wells, and aquifer transmissivity and storage. The groundwater flow and aquifer properties were also evaluated to allow Suffolk County Water Authority to better assess the potential source of dissolved halocarbons (refrigerants, such as chlorofluorocarbons).
The well field production wells are screened in the upper glacial aquifer and an observation well is screened in the Magothy aquifer. Based on depth and available logs, groundwater from wells screened in the upper glacial aquifer was classified as under water-table (unconfined) conditions, and groundwater from wells screened in the Magothy aquifer was classified as being under semiconfined conditions.
Groundwater flows radially to the well field during production and in a northwesterly direction under the effect of the regional flow regime. A previously published particle tracking analysis identified the following recharge contributing areas nearby the well field: (1) contributing areas to surface-water bodies of the Peconic Estuary, (2) contributing areas to surface-water bodies of the South Shore Estuary Reserve, (3) a contributing area to the Atlantic Ocean, and (4) a contributing area to another Suffolk County Water Authority well field. Five other pumping well contributing areas were identified within the study area, including those of various wells pumped for golf-course irrigation.
Analysis of drawdown and recovery data collected during the multiple-well aquifer test, through the application of a Neuman analytical model, provided estimates of upper glacial aquifer characteristics and properties. Inclusion of lateral aquifer boundaries was not necessary for the analysis to result in satisfactory matches with the observed water-level responses. Aquifer transmissivity was estimated to be 170,000 feet squared per day. Storativity was estimated to be 0.02 (dimensionless), and specific yield was estimated to be 0.08 (dimensionless), consistent with the inferred degree of confinement and well field characteristics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231028","collaboration":"Prepared in cooperation with the Suffolk County Water Authority","usgsCitation":"Misut, P.E., 2023, Analysis of aquifer framework and properties, North Magee Street well field, Southampton, New York: U.S. Geological Survey Open-File Report 2023–1028, 14 p., https://doi.org/10.3133/ofr20231028.","productDescription":"Report: iv, 14 p.; Dataset","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-124210","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":499775,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114761.htm","linkFileType":{"id":5,"text":"html"}},{"id":417746,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the nation"},{"id":417745,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1028/images/"},{"id":417744,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1028/ofr20231028.XML"},{"id":417743,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231028/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1028"},{"id":417742,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1028/ofr20231028.pdf","text":"Report","size":"2.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1028"},{"id":417741,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1028/coverthb.jpg"}],"country":"United States","state":"New York","city":"Southampton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.43897301957882,\n 40.91839299249426\n ],\n [\n -72.43897301957882,\n 40.87699855750361\n ],\n [\n -72.37328061868494,\n 40.87699855750361\n ],\n [\n -72.37328061868494,\n 40.91839299249426\n ],\n [\n -72.43897301957882,\n 40.91839299249426\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Groundwater wells and surface-water storm sewers contaminated with volatile organic compounds (VOCs) and per- and polyfluoroalkyl substances (PFASs) at the former Naval Air Warfare Center (NAWC) site in West Trenton, New Jersey were sampled in 2018 as part of the Navy’s long-term monitoring program. Trichloroethene (TCE), cis-1,2-dichloroethene (cisDCE), and vinyl chloride concentrations were plotted in map view and selected cross sections to elucidate the vertical and horizontal extent and distribution of contamination, along with a tabular comparison between 2018 and previous analytical results. The 2018 data showed that the areas of VOC contamination (>1 microgram per liter) decreased slightly on the north and east sides of the NAWC site from previous sampling dates; these decreases are attributed to the influence of the pump-and-treat system, natural attenuation processes, and various engineered bioaugmentation experiments that have occurred onsite. Off-site groundwater samples indicate the VOC contaminated groundwater is likely hydraulically constrained by the pump-and-treat system and appears to not be moving offsite to the south and west of NAWC. Only one offsite well, 50BR, located along the eastern margin of the site, was found to have detectable TCE and cisDCE concentrations, indicating that VOC contamination continues to migrate a short distance offsite to the east. Detectable VOC contamination was found in wells as deep as 200 and 221 feet on both the east and west sides of the NAWC site. Comparisons of present-day data to data from past sampling efforts indicate that TCE concentrations in most wells have decreased slowly over time.
Results from surface-water samples indicate that VOCs enter surface water predominantly through the West Ditch drainage system. Concentrations and fluxes of VOCs are higher when groundwater levels are higher, indicating contaminated groundwater discharges into the surface water system. Higher VOC concentrations at the Interceptor site relative to other sites in the West Ditch indicate the contamination in the West Ditch system is likely caused by contaminated groundwater discharging to the West Ditch storm sewer near manhole MH-140 when water table levels are high.
The pump-and-treat extraction wells at the former NAWC site were sampled for per- and polyfluoroalkyl substances (PFAS) in 2018. The suite of reported PFAS include perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid, and perfluorobutane sulfonate. Concentrations were plotted in map view to determine the areal extent of the PFAS contamination at the site. Extraction well 48BR sampled on the eastern half of the site was found to have PFOS and PFOA concentrations greater than the New Jersey Department of Environmental Protection Drinking Water maximum contaminant levels (MCLs), which is consistent with the distribution of highest PFAS concentrations in surface water in the OF-4 storm sewer system that drains that area, as well as previously collected PFAS concentrations in monitoring wells. On the western half of the site, the extraction well 08BR sample exceeded MCLs for PFOA and PFOS and the extraction well 22BR sample exceeded the MCL for PFOA, but samples from all other extraction wells were below the MCLs or other criteria for all PFAS analyzed. Concentrations of PFOA exceeded concentrations of PFOS on the west side of NAWC in both groundwater and surface water, which contrasts with the conditions on the east side of NAWC where PFOS concentrations exceeded PFOA concentrations. However, this observation was based on a limited number of samples on the west side of NAWC from 2018 and previous years, so more PFAS sampling is needed on the west side to assess this further.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231022","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Fiore, A.R., Imbrigiotta, T.E., and Wilson, T.P., 2023, Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018: U.S. Geological Survey Open-File Report 2023–1022, 81 p., https://doi.org/10.3133/ofr20231022.","productDescription":"Report: ix, 81 p.; Data Release","numberOfPages":"81","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114249","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":417658,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCAQ5N","text":"USGS data release","linkHelpText":"Concentrations of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water, former Naval Air Warfare Center, West Trenton, New Jersey"},{"id":417657,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1022/images/"},{"id":417656,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1022/ofr20231022.XML"},{"id":417655,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231022/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1022"},{"id":417654,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1022/ofr20231022.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1022"},{"id":417653,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1022/coverthb.jpg"},{"id":499772,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114760.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"former Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.816667,\n 40.275\n ],\n [\n -74.816667,\n 40.2667\n ],\n [\n -74.808333,\n 40.2667\n ],\n [\n -74.808333,\n 40.275\n ],\n [\n -74.816667,\n 40.275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ, 08648
The Trinity River is managed in two sections: (1) the upper 64-kilometer (km) “restoration reach” downstream from Lewiston Dam and (2) the 120-km lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously constructed and calibrated for the restoration reach. In this report, we extended and parameterized S3 for the 120-km section of the lower Trinity River to the confluence with the Klamath River and then to the Pacific Ocean in northern California.
S3 is a deterministic life-stage structured-population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive (1) survival and growth within each habitat unit and (2) movement of fish among habitat units.
The physical template of the Trinity River was formed by classifying the river into 910 meso-habitat units that were designated into runs, riffles, or pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival.
We estimated key movement and survival parameters by calibrating the model to 12 years (2007–18) of weekly juvenile abundance estimates from two rotary screw traps: (1) the Pear Tree trap near the downstream end of the restoration reach and (2) the Willow Creek trap site is about 40.2 km upriver from the Trinity River’s confluence with the Klamath River. The calibration consisted of replicating historical conditions as closely as possible (for example: flow, temperature, spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location. We also evaluated four alternative model structures that included either no density-dependence, density-independent movement and survival, density-dependent survival, or density-dependent movement. Akaike information criterion model selection was used to evaluate the strength of evidence for alternative model structures to simulate the observed abundance estimates.
Model selection supported the conclusion that the fully density-dependent model and density-dependent survival model was better supported by the data than the no density-dependence or density-dependent movement model. Because density-dependent movement was favored in past evaluations, we focus on the results from the fully density-dependent model. Parameter estimates from this model indicated that fry were less likely than parr to move downstream and that fry moved slower. Fry had a lower daily survival probability than parr. In contrast, hatchery fish had the highest probability of movement and the lowest daily survival probability.
Fitting the model to both traps individually enabled us to independently compare the fit and performance of S3 at simulating fish abundance, timing, and growth of juvenile salmon in the upper restoration reach and lower Trinity River. We obtained a better fit to the data at the Willow Creek trap site than we obtained at the Pear Tree trap site, regardless of whether we fit the model to the abundances at the Pear Tree trap or Willow Creek trap. This better fit was surprising given that the S3 input data for the upper restoration reach required fewer assumptions than fitting to the Willow Creek trap site that is farther down river. Fitting S3 to weekly abundances at the Willow Creek trap site required making assumptions about (1) extrapolating capacity-flow relationships to unmeasured habitat units; (2) spatially allocating spawners within the lower Trinity River; and (3) approximating the abundance, timing, and size of juveniles entering from tributaries. The model provided better fit to the data at the Willow Creek trap site. In the weekly abundance estimates, in relation to the S3 simulated abundances, several migration years’ (2011, 2015–17) weekly abundance estimates appeared truncated and were near or at peak annual abundances in January, suggesting that a large fraction of juveniles was migrating as early as December at the Pear Tree trap site. Some early life dynamics may not be currently incorporated into S3. For example, the estimation of abundance at the Pear Tree trap may be biased because of size selectivity. Knowing about selectivity at the Pear Tree trap could greatly improve S3’s ability to predict weekly and peak abundances each year.
Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The Pacific Gas and Electric Company (PG&E) Hinkley compressor station, in the Mojave Desert, 80 miles northeast of Los Angeles, California, is used to compress natural gas as it is transported through a pipeline from Texas to California. Between 1952 and 1964, cooling water was treated with a compound containing hexavalent chromium, Cr(VI), to prevent corrosion of machinery within the compressor station. Cooling wastewater containing Cr(VI) was discharged to unlined ponds and released into groundwater. Since 1964, cooling-water management practices have been used that do not contribute chromium to groundwater.
","language":"English, Spanish","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231043","collaboration":"Prepared in cooperation with Lahontan Regional Water Quality Control Board","usgsCitation":"Izbicki, J.A., Groover, K.D., Seymour, W.A., Miller, D.M., Warden, J.G., and Miller, L.G., 2023, Natural and anthropogenic hexavalent chromium, Cr(VI), in groundwater near a mapped plume, Hinkley, California (ver. 1.1, June 2023): U.S. Geological Survey Open-File Report 2023-1043, 6 p., https://doi.org/10.3133/ofr20231043.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-124184","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":499781,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114741.htm","linkFileType":{"id":5,"text":"html"}},{"id":417444,"rank":2,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1885","text":"Professional Paper 1885","linkHelpText":"- Natural and Anthropogenic (Human-Made) Hexavalent Chromium, Cr(VI), in Groundwater near a Mapped Plume, Hinkley, California"},{"id":418433,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1043/ofr20231043.xml"},{"id":418435,"rank":6,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1043/covrthb.jpg"},{"id":417273,"rank":1,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1043/images"},{"id":418431,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1043/versionHist.txt"},{"id":418432,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1043/ofr20231043.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":432299,"rank":7,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1043/ofr20231043_spanish.pdf","text":"Report (Spanish)","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2023-1043 in Spanish"}],"country":"United States","state":"California","city":"Hinkley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.45302333136905,\n 35.19277332893611\n ],\n [\n -117.45302333136905,\n 34.55310182669082\n ],\n [\n -116.77216386614738,\n 34.55310182669082\n ],\n [\n -116.77216386614738,\n 35.19277332893611\n ],\n [\n -117.45302333136905,\n 35.19277332893611\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: May 2023; Version 1.1: June 2023","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
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 4 (October–December) of 2022. 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 the lowering of the Landsat 7 orbit. On April 6, 2022, the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor was placed into standby mode, and a series of spacecraft burns was completed through the month of April to lower the satellite’s orbit by 8 kilometers. Imaging resumed at a lower orbit of 697 kilometers on May 5, 2022, extending the science mission. Additional information about the Landsat 7 orbit lowering is here: https://www.usgs.gov/centers/eros/news/landsat-7-lowered-standard-landsat-orbit#:~:text=The%20satellite's%20primary%20science%20mission%20has%20ended&text=On%20April%206%2C%202022%2C%20the,satellite's%20orbit%20by%208%20kilometers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231044","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T.Z., Shaw, J.L., Denevan, A., Franks, S., Micijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., and Miller, J., 2023, ECCOE Landsat quarterly Calibration and Validation report—Quarter 4, 2022: U.S. Geological Survey Open-File Report 2023–1044, 39 p., https://doi.org/10.3133/ofr20231044.","productDescription":"Report: vii, 39 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-149560","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":417400,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231044/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":417365,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":417362,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1044/ofr20231044.pdf","text":"Report","size":"4.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1044"},{"id":417361,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1044/coverthb.jpg"},{"id":417363,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1044/ofr20231044.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":417364,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1044/images"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The northern spotted owl (Strix occidentalis caurina; hereinafter NSO) was listed as “threatened” under the Endangered Species Act in 1990 and population declines have continued since that listing. Given the species’ protected status, any proposed activities on Federal lands that might impact NSO require consultation with U.S. Fish and Wildlife Service and part of that consultation often includes surveys to determine presence and occupancy status of the species in the proposed activity area. The objective of this report is to present study-area specific estimates of the probability of detection for NSO pairs from twelve 2-week seasonal survey periods using data from a recent range-wide meta-analysis. These estimates were a by-product of pair occupancy modeling but might provide insight into potential changes in the effect of the invasive barred owl on NSO detection rates. We used two-species multi-season occupancy models to estimate the probability of detection for NSOs on each of 11 study areas for each 2-week survey period and relative to the range-wide effect of barred owl presence or absence. Detection probabilities within the season generally increased from the earliest surveys in March through mid-season, decreasing again in the late season on five study areas. For three other study areas, detection rates were highest during the earliest survey periods in late March or early April. Estimates of cumulative seasonal detection of NSO (across a maximum of six within-season surveys) were less than 0.90 when barred owls (BO) were present on all but one study area, regardless of when surveys were conducted within a season. However, despite low detection rates, the probability that a territory was occupied when an NSO pair was not detected over six within-season surveys was also very low. When BO are not present on a territory, a six-survey protocol had a high probability of detecting an NSO pair at least once during the season on all study areas, except for the very lowest per-survey estimates. Conducting most surveys earlier in the season, when the probability of detecting pairs is highest (through May on most areas) could improve seasonal detection rates. However, alternative methods of population monitoring—such as the use of passive acoustic recorders—may be needed to continue monitoring NSO for research and management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231012","collaboration":"Prepared in cooperation with Oregon State University","usgsCitation":"Dugger, K.M., Franklin, A.B., Lesmeister, D.B., Davis, R.J., Wiens, J.D., White, G.C., Nichols, J.D., Hines, J.E., Yackulic, C.B., Schwarz, C.J., Ackers, S.H., Andrews, L.S., Bailey, L.L., Bown, R., Burgher, J., Burnham, K.P., Carlson, P.C., Chestnut, T., Conner, M.M., Dilione, K.E., Forsman, E.D., Gremel, S.A., Hamm, K.A., Herter, D.R., Higley, J.M., Horn, R.B., Jenkins, J.M., Kendall, W.L., Lamphear, D.W., McCafferty, C., McDonald, T.L., Reid, J.A., Rockweit, J.T., Simon, D.C., Sovern, S.G., Swingle, J.K., and Wise, H., 2023, Estimating northern spotted owl (Strix occidentalis caurina) pair detection probabilities based on call-back surveys associated with long-term mark-recapture studies, 1993–2018: U.S. Geological Survey Open-File Report 2023–1012, 25 p., https://doi.org/10.3133/ofr20231012.","productDescription":"vii, 25 p.","onlineOnly":"Y","ipdsId":"IP-133003","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":417167,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231012/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1012"},{"id":417166,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1012/ofr20231012.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1012"},{"id":417169,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1012/ofr20231012.XML"},{"id":417168,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1012/images"},{"id":417165,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1012/coverthb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.82419135781177,\n 37.90972622681076\n ],\n [\n -122.3277779102568,\n 38.08861577320431\n ],\n [\n -120.925210233316,\n 42.44504507790097\n ],\n [\n -120.0290356856878,\n 48.995370896990295\n ],\n [\n -123.35793848445479,\n 48.94274756685837\n ],\n [\n -123.44660126094462,\n 48.247927989659445\n ],\n [\n -125.06690973675748,\n 48.590141468479914\n ],\n [\n -124.10299464056828,\n 46.115944811333236\n ],\n [\n -124.32184346408252,\n 43.795550298890845\n ],\n [\n -124.71979791193871,\n 42.67568668540227\n ],\n [\n -124.10920825253021,\n 41.43162232110191\n ],\n [\n -124.53261803772267,\n 40.21134172936314\n ],\n [\n -123.80095675617886,\n 38.77121416707598\n ],\n [\n -122.82419135781177,\n 37.90972622681076\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street
Suite 400
Corvallis, OR 97330
Emydoidea blandingii (Holbrook, 1838; Blanding’s turtles) are a species of medium-sized, long-lived, semiaquatic, freshwater turtles with a wide distribution across the northern and eastern United States and southern Canada. They have an annual activity cycle consisting of late autumn and winter overwintering and spring emergence, spring movement and foraging, spring and summer nesting, and summer and autumn foraging and nonnesting movement. In response to changes in average and extreme temperatures, Blanding’s turtles are likely to experience increased physiological stress and reduced reproductive success. Variability in precipitation may affect the availability of freshwater habitats for overwintering, shelter, and feeding; however, projected changes in precipitation vary widely. This analysis presents anticipated climate conditions and effects on the species; the complex life history and expansive geographic range of this species require additional analysis at local scales.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211104D","usgsCitation":"Lyons, M.P., Nikiel, C.A., LeDee, O.E., and Boyles, R., 2023, Potential effects of climate change on Emydoidea blandingii (Blanding’s turtle): U.S. Geological Survey Open-File Report 2021–1104–D, 46 p., https://doi.org/10.3133/ofr20211104D.","productDescription":"viii, 46 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-149510","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":417246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1104/d/coverthb.jpg"},{"id":417247,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1104/d/ofr20211104d.pdf","text":"Report","size":"27.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1104–D"},{"id":417248,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1104/d/ofr20211104d.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":417249,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1104/d/images"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101,\n 48.1\n ],\n [\n -101,\n 39\n ],\n [\n -71,\n 39\n ],\n [\n -71,\n 48.1\n ],\n [\n -101,\n 48.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Midwest Climate Adaptation Science Center
U.S. Geological Survey
1954 Buford Avenue
St. Paul, MN 55108
The National Park Service (NPS), in collaboration with the U.S. Geological Survey (USGS), recognizes the need to quantify the sediment budget of the barrier islands within the Gulf Islands National Seashore (GINS) to understand the coastal processes affecting island resiliency. To achieve this goal, identifying and quantifying the physical parameters that drive long-term change is necessary to model the processes that are both generative and terminal in island evolution and capture island response to long-term human alteration and climatic patterns. For example, measuring change across periods of storminess is more effective at assessing island resiliency than measuring change resulting from a single storm impact. Understanding changes to the physical environment over time is key to successfully predicting island responses to future storm impacts, human alteration, and sea-level rise and is necessary for effective decision making and management response. Yet, the diversity of factors affecting natural and cultural resources necessitates a strategic approach to data collection priorities that can inform sediment budget quantification and integrated resource management.
This study sought to advance sediment budget modeling efforts by conducting a “Needs Assessment Workshop” at the GINS. The purpose of the workshop was to identify and prioritize the specific research and data needs regarding the sediment budget at the GINS that can enhance the NPS efforts to conserve the islands’ natural resources, cultural resources, and the facilities and infrastructure that support both conservation and visitor use of those resources. This effort explored two research questions: (1) “what research and data needs exist for the sediment budget at Gulf Islands National Seashore” (research question 1) and (2) “how can research to address these needs capitalize on regional partnerships to advance natural and cultural resource conservation at Gulf Islands National Seashore” (research question 2)? The workshop was conducted virtually in a two-part, two-day series.
The workshop series was organized by researchers from North Carolina State University in collaboration with NPS and USGS staff and was facilitated by National Oceanographic and Atmospheric Administration staff. The workshop series (two paired, sequential, partial-day workshops) addressed two target audiences: (1) NPS and USGS staff (April workshop) and (2) regional Federal, State, county, and nongovernmental organization staff, including NPS and USGS staff (May workshop). A total of four workshop sessions were held, comprising two sessions with each target audience.
The workshop series intended to identify sediment management research and data needs that could enhance natural and cultural resource stewardship at the GINS. One objective was to share information about regional sediment transport and management, available sediment management plans, and predictive modeling capabilities, including geomorphologic and hydrodynamic predictive models. This information was shared through a series of presentations by park managers and NPS and USGS researchers that identified park issues and available capabilities and data. The second objective was to elicit research and data needs, with a primary goal of assessing the importance and urgency of the identified needs. This assessment was partly determined by requesting that the workshop participants identify and prioritize research themes through polls, comments, and discussion.
The polls explicitly asked participants to qualitatively evaluate the importance (not at all, slightly, somewhat, very, or extremely) and urgency (not at all, slightly, somewhat, very, or extremely) of the thematically grouped research and data needs. These evaluations were plotted and shared during the workshop to visualize how the relative importance (x-axis) and relative urgency (y-axis) of each “need,” relative to other needs, to identify the most necessary (importance) and time-sensitive (urgent) items, thereby allowing an enhanced, holistic understanding of the sediment budget at GINS. Results of the poll are published as a USGS data release.
The assessment results revealed that the most important and urgent research and data needs included mapping (for example, elevation, habitat, and cultural resources), a regional sediment budget and management plan, and the dynamic modeling of sediment processes. During the workshop, these issues were visualized using scatter plots to demonstrate the relative importance and urgency of each theme, provide descriptive statistics, and elicit discussion. This format of iterative presentation, discussion, and prioritization allowed the project team to effectively accomplish their objective of identifying important and urgent research needs for natural and cultural resource stewardship at the GINS. Through the workshop, it was determined that expanded communication with the broader research community was needed to coordinate research activities and streamline potential funding opportunities and that research and policy should be integrated through a structured decision-making process.
At the conclusion of the workshop, an administered poll showed that the presentations effectively identified data and research needs and that the goals of the workshop were achieved. The results suggest that this type of needs-assessment workshop can effectively identify existing research capabilities and data, determine and prioritize research and data needs, and address how these efforts can use regional partnerships to aid natural and cultural resource conservation and management at National Parks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221087","programNote":"Coastal/Marine Hazards and Resources Program","usgsCitation":"Seekamp, E., Flocks, J., Hotchkiss, C., York, L., and Irick, K., 2023, Gulf Islands National Seashore regional sediment budget research and data needs—Workshop series summary: U.S. Geological Survey Open-File Report 2022–1087, 46 p., https://doi.org/10.3133/ofr20221087.","productDescription":"Report: vii, 46 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127837","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416372,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1087/coverthb.jpg"},{"id":416373,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1087/ofr20221087.pdf","text":"Report","size":"2.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1087"},{"id":416375,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1087/ofr20221087.XML"},{"id":416376,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1087/images/"},{"id":416377,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JG3J7B","text":"USGS data release","linkHelpText":"Gulf Islands National Seashore 2020 workshop-attendee survey results"},{"id":499720,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114708.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida, Mississippi","otherGeospatial":"Gulf Islands National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.47993451563534,\n 30.4372165405142\n ],\n [\n -89.47993451563534,\n 30.14326231135827\n ],\n [\n -86.39410371358161,\n 30.14326231135827\n ],\n [\n -86.39410371358161,\n 30.4372165405142\n ],\n [\n -89.47993451563534,\n 30.4372165405142\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South St.
Petersburg, FL 33701
Over the past two decades, the U.S. Geological Survey (USGS) and other agencies have pioneered the use of active acoustic sensors to monitor suspended-sediment concentrations and particle sizes in rivers and streams at the subdaily time scale. The LISST-ABS submersible acoustic backscatter sediment sensor (or “ABS sensor”) was developed by Sequoia Scientific, Inc., as an alternative to turbidity sensors for monitoring suspended-sediment concentrations in surface waters. The ABS sensor is different than traditional active acoustic instruments because it is small, lower in cost, lightweight, and requires less power; and the sampling volume is within the first 15 centimeters of the transducer face. Initial testing by the USGS indicated the ABS sensor had utility as a novel, cost-effective, off-the-shelf tool for monitoring suspended-sediment concentration in surface waters, and its use within the agency has increased in since its introduction around 2016. However, initial testing did not account for the potential of transducer calibration drift over longer deployments.
As part of its mission to unify and standardize research and development activities of Federal agencies involved in fluvial sediment studies, the Federal Interagency Sedimentation Project partnered with the USGS Wyoming-Montana and New Mexico Water Science Centers to examine the potential for use of standard, low-tech laboratory equipment to perform calibration checks on ABS sensors on long-term deployments. The experiments were intended to provide USGS scientists and the public with interim guidance to assist in operating and maintaining the ABS sensor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231039","collaboration":"Prepared in cooperation with the Federal Interagency Sedimentation Project","usgsCitation":"Alexander, J.S., O’Connell, J.P., and Brown, J.E., 2023, Interim guidance for calibration checks on a submersible acoustic backscatter sediment sensor (ver. 1.1, November 2023): U.S. Geological Survey Open-File Report 2023–1039, 23 p., https://doi.org/10.3133/ofr20231039.","productDescription":"Report: v, 23 p.; Data Release; 2 Datasets","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-147547","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":422961,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1039/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2023-1039 Version History"},{"id":416561,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://waterdata.usgs.gov/nwis/inventory/?site_no=09363500&agency_cd=USGS&","text":"USGS National Water Information System database","linkHelpText":"—USGS 09363500 Animas River near Cedar Hill, NM, in USGS water data for the Nation"},{"id":416559,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M41G3W","text":"USGS data release","linkHelpText":"Data from lab experiments to support interim guidance for performing calibration checks on the Sequoia Scientific LISST-ABS acoustic backscatter sensor"},{"id":416557,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1039/ofr20231039.XML","size":"149 kB","description":"OFR 2023-1039 XML"},{"id":416555,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1039/coverthb2.jpg"},{"id":422960,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1039/ofr20231039.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1039"},{"id":416558,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1039/images"},{"id":416560,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"edition":"Version 1.0: May 1, 2023; Version 1.1: November 27, 2023","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
We present new X-ray fluorescence compositions of 27 core samples from Phase 3, Hole G of the San Andreas Fault Observatory at Depth, nearly doubling the published dataset for the core. The new analyses consist of major and trace element compositions and the first published data for rare earth elements from Hole G. Whole-rock compositions were obtained to further the analysis of active geochemical processes within the creeping section of the San Andreas Fault in central California. In this report, we plot the new data along with previously published analyses to illustrate some of the compositional features of the Hole G core and to relate them to the core mineralogy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231019","usgsCitation":"Moore, D.E., and Bradbury, K.K., 2023, Chemical characterization of San Andreas Fault Observatory at Depth (SAFOD) Phase 3 core: U.S. Geological Survey Open-File Report 2023–1019, 15 p., https://doi.org/10.3133/ofr20231019.","productDescription":"iv, 15 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-142575","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":416448,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1019/ofr20231019.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":499770,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114706.htm","linkFileType":{"id":5,"text":"html"}},{"id":416447,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1019/covrthb.jpg"}],"contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Road
Moffett Field, CA 94035
Trace-metal concentrations in sediment and in the clam Limecola petalum (World Register of Marine Species, 2020; formerly reported as Macoma balthica and M. petalum), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer (km) south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, California. This report includes the data collected by the U.S. Geological Survey (USGS) for January 2020–December 2020 (Cain and others, 2022). These data append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2020 data within the context of the longer, multidecadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving- Water Monitoring Program, initiated in 1994.
Silver and copper contamination substantially decreased at the site in the 1980s following the implementation by PARWQCP of advanced wastewater-treatment and source-control measures. Since the 1990s, concentrations of these elements in surface sediments have continued to decrease, although more slowly. For example, from 1994 to 2020, the minimum annual mean silver concentration—0.20 milligram per kilogram (mg/kg)—was observed in multiple years. In 2020, silver concentrations ranged from 0.18 to 0.28 mg/kg. These concentrations are 2 to 3 times higher than the regional background concentration. Presently (2020), sediment-copper concentrations appear to be near the regional background level. Over the same period (1994–2020), sedimentary iron and zinc exhibited modest decreases. Sedimentary aluminum, chromium, mercury, nickel, and selenium have not exhibited any trend. Since 1994, silver and copper concentrations in L. petalum have varied seasonally, apparently in response to a combination of site-specific metal exposures and cyclic growth and reproduction, as reported previously. Seasonal patterns for other elements, including chromium, mercury, nickel, selenium, and zinc, generally were similar in timing and magnitude as those for silver and copper. Downward trends in the silver and zinc concentrations in L. petalum during 1994–2020 were evident and appeared to be related to the general physiological condition of the clam, indicated by a condition index.
Biological effects of elevated silver and copper contamination at the Palo Alto site have been interpreted from data collected during and after the recession of these contaminants. Concentrations of both elements in the soft tissues of L. petalum decreased with sedimentary copper and silver. This pattern was associated with changes in the reproductive activity of L. petalum, as well as the structure of the benthic invertebrate community. Reproductive activity of L. petalum increased as metal concentrations in L. petalum decreased (Hornberger and others, 2000), and presently is stable with almost all animals initiating reproduction in the fall and spawning the following spring. Analyses of the benthic community structure indicate that the infaunal invertebrate community has shifted from one dominated by several opportunistic species when silver and copper exposures were highest to one in which the species abundance is more evenly distributed, a pattern that indicates a more stable community that is subjected to fewer stressors. Importantly, this long-term change is unrelated to other metals and other measured environmental factors, including salinity and sediment composition. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decrease in dominance coincident with the decrease in metals. Both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2020. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly from 2011 to 2012 and returned to pre-2011 numbers in 2020.
The reproductive mode of most species that were present in 2020 was indicative of species that were capable of movement either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2020 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, those that have pelagic larvae that must survive landing on the sediment, and those that brood their young. The long-term recovery observed after the 1970s can be ascribed to the decrease in sediment pollutants.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231017","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Croteau, M.-N., Thompson, J.K., Parchaso, F., Stewart, R., Zierdt Smith, E.L., Shrader, K.H., Kieu, L.H., and Luoma, S.N., 2023, Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2020: U.S. Geological Survey Open-File Report 2023–1017, 51 p., https://doi.org/10.3133/ofr20231017.","productDescription":"Report: ix, 51 p.; Data Release","numberOfPages":"51","onlineOnly":"Y","ipdsId":"IP-133169","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":416134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1017/covrthb.jpg"},{"id":416135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1017/ofr20231017.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":416139,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181107","text":"Open-File Report 2018-1107","linkHelpText":"- Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017"},{"id":416136,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IBQ23S","text":"Data for monitoring trace metal and benthic community near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California (ver 2.0, November 2022)","description":"Cain, D.J., Croteau, M., Parchaso, F., Stewart, R., Zierdt Smith, E.L., Thompson, J.K., Kieu, L., Turner, M., and Baesman, S.M., 2022, Data for monitoring trace metal and benthic community near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California (ver 2.0, November 2022): U.S. Geological Survey data release, https://doi.org/10.5066/P9IBQ23S."},{"id":416140,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016"},{"id":499767,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114697.htm","linkFileType":{"id":5,"text":"html"}},{"id":416137,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416138,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416141,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.26067527634044,\n 37.52598582053362\n ],\n [\n -122.26067527634044,\n 37.38564942805466\n ],\n [\n -121.8210169399245,\n 37.38564942805466\n ],\n [\n -121.8210169399245,\n 37.52598582053362\n ],\n [\n -122.26067527634044,\n 37.52598582053362\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035