Sand Hollow Reservoir in Washington County, Utah, was completed in March 2002 and is operated primarily for managed aquifer recharge by the Washington County Water Conservancy District. Sand Hollow Reservoir has remained nearly full since 2006 because of surface-water diversions of about 288,000 acre-feet (acre-ft) from 2002 through 2018. Groundwater levels in monitoring wells near the reservoir rose through 2006 and have fluctuated since then because of variations in reservoir stage and nearby pumping from production wells. Between 2004 and 2018, about 46,000 acre-ft of groundwater was withdrawn by these wells for municipal supply. In addition, about 45,000 acre-ft of shallow seepage was captured by French drains adjacent to the North and West Dams and used for municipal supply, irrigation, or returned to the reservoir. From 2002 through 2018, about 159,000 acre-ft of water seeped beneath the reservoir to recharge the underlying Navajo Sandstone aquifer, which includes about 18,500 acre-ft of recharge in the 2017–18 period since the last report.
Water quality continued to be monitored at various wells in Sand Hollow during 2017–18 to evaluate the timing and location of reservoir recharge as it moved through the aquifer. Changing geochemical conditions at monitoring well water district (WD) 12 indicated rising groundwater levels and mobilization of vadose-zone salts, which could be a precursor to the arrival of reservoir recharge. Changes to geochemical conditions and environmental tracers at monitoring well WD 22 indicated the arrival of reservoir recharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221089","collaboration":"Prepared in cooperation with the Washington County Water Conservancy District","programNote":"Water Availability and Use Science Program","usgsCitation":"Marston, T.M., 2024, Assessment of managed aquifer recharge at Sand Hollow Reservoir, Washington County, Utah, updated to conditions through 2018: U.S. Geological Survey Open-File Report 2022–1089, 20 p., https://doi.org/10.3133/ofr20221089.","productDescription":"Report: v, 20 p.; 2 Tables","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-124201","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":499185,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115940.htm","linkFileType":{"id":5,"text":"html"}},{"id":424118,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2022/1089/ofr20221089_table1.1.csv","text":"Appendix table 1.1","size":"20 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Field water-quality parameters, dissolved organic carbon, tritium, chlorofluorocarbons, sulfur hexaflouride in groundwater and surface water from Sand Hollow, Utah."},{"id":424116,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1089/images"},{"id":424115,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1089/ofr20221089.xml"},{"id":424114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1089/ofr20221089.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":424113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1089/covrthb.jpg"},{"id":424117,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221089/full"},{"id":424119,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2022/1089/ofr20221089_table1.2.csv","text":"Appendix table 1.2","size":"25 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Major and minor chemical constituents in groundwater and surface water from selected sites in Sand Hollow, Utah."}],"country":"United States","state":"Utah","county":"Washington County","otherGeospatial":"Sand Hollow Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.43516202274216,\n 37.16544148428713\n ],\n [\n -113.43516202274216,\n 37.068527882070626\n ],\n [\n -113.32049222293712,\n 37.068527882070626\n ],\n [\n -113.32049222293712,\n 37.16544148428713\n ],\n [\n -113.43516202274216,\n 37.16544148428713\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
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Macroseismic observations and analysis connect our collective seismological past with the present and the present to the future by facilitating hazard estimates and communicating the effects of ground shaking to a wide variety of audiences across the ages. Invaluable ground shaking and building damage information is gained through standardized, systematic approaches for assigning intensities and, importantly, sharing and archiving those assignments in a reproducible form. The applications for these assignments are far reaching. Traditional macroseismic surveys provide vital constraints on critical aspects of earthquakes and their effects on society, whereas internet-based macroseismic datasets are extremely valuable for real-time earthquake situational awareness, and they contribute to later engineering loss and risk analyses. These important applications of macroseismic observations would be helped by revisiting traditional macroseismic surveys for modern environments, standardizing internet-based collection strategies, and ensuring compatibility between traditional and internet-based approaches of macroseismic data collection.
Even with best practices, we have identified several limitations with modern macroseismic data collection approaches, particularly from the U.S. Geological Survey's perspective. First, whereas crowdsourced, internet-based intensities such as “Did You Feel It?” are robust and definitive for lower intensities, they are poorly defined above intensity VII, where damage observations may require expert knowledge of each building’s structural system.
Second, in the United States, we use the Modified Mercalli Intensity (MMI) Scale, which is consistent with—yet inferior to—the more recently developed European Macroseismic Scale (EMS–98; Grünthal and others, 1998). Similarly, New Zealand uses the New Zealand MMI Scale (Dowrick and others, 2008), which lacks detail on how to assign intensities above MMI VIII. The EMS–98 fundamentally advanced the science of macroseismic intensity assignment by requiring quantitative assessments at each location through consistent application on statistical ranges of well-defined damage grades to building-specific vulnerability classes. Lastly, the United States and New Zealand no longer have professionals dedicated to conducting traditional macroseismic field surveys, so a strategy is needed for allowing postearthquake building inspectors and insurance loss assessors to contribute to intensity assignments.
The goals of our International Macroseismic Scale workshop were thus twofold. First, harmonize the MMI Scale with EMS–98 for the United States and New Zealand—which share several similar building types—by considering those structures and associated damage grades that are not well represented in the current EMS–98 building vulnerability class table. Second, begin to formalize the process of augmenting EMS–98 with new regional building classes and damage grades toward the development of a macroseismic scale that can be used globally, beyond the United States and New Zealand. Such an effort necessarily requires reviewing and expanding the original EMS–98 explanatory documents and consideration of any required revisions. We can build on the shoulders of giants in that a few of the original EMS–98 developers and experts participated in and were integral to our workshop. Their background and guidance were key in moving forward toward an international scale.
We agreed that additional building vulnerability classes, damage grades, and written and pictorial descriptions are necessary and ideally accompanied by a detailed paper trail for other nations to follow. If we can improve the macroseismic assignment process in both nations, we can also aim to refine the process of collecting postearthquake impact data, a boon to many engineering and financial concerns.
The benefits of a truly International Macroseismic Scale are considerable for both the engineering and seismology communities. A modern macroseismic scale requires more deliberate archival damage data collection, motivating more consistent and accessible postevent datasets that would have applications beyond the specific event. Applying field-collected building damage data toward macroseismic assignments would allow for increased coordination between engineering reconnaissance teams and local inspectors in collecting such data for official purposes. In addition, rapid and consistent intensity assignments globally would enable more accurate ShakeMaps—and thus improved earthquake engineering and geotechnical forensics, loss and risk estimates, and correlations between macroseismic intensity and ground motion parameters.
A brief summary of the Powell Center IMS workshop was published by Wald and others (2023) in the magazine Eos. This Open-File Report describes the workshop, its discussions, and its outcomes in detail. In summarizing the workshop, we have added important background material and reflections for proper context.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20231098","usgsCitation":"Wald, D.J., Goded, T., Hortacsu, A., and Loos, S.C., 2024, Developing and implementing an International Macroseismic Scale (IMS) for earthquake engineering, earthquake science, and rapid damage assessment: U.S. Geological Survey Open-File Report 2023–1098, 55 p., https://doi.org/10.3133/ofr20231098.","productDescription":"viii, 55 p.","onlineOnly":"Y","ipdsId":"IP-149203","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":424198,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1098/images"},{"id":424196,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1098/ofr20231098.pdf","text":"Report","size":"7.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1098"},{"id":424195,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1098/coverthb.jpg"},{"id":424207,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231098/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1098"},{"id":424199,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1098/ofr20231098.xml"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
The eastern migratory population of monarch butterflies (Danaus plexippus) started declining as early as the mid-1970s and seemed to stop declining by the early 2000s; the population now (about 2022) persists at a much-reduced abundance. Stochastic variation in abundance, at levels typical of monarch butterflies and other insects, was assessed to determine whether this population is at heightened risk of quasi-extinction, a level of abundance below which recovery of the migratory behavior is uncertain. Using previously published Bayesian state-space modeling methods it was determined roughly equivalent risk of quasi-extinction as was reported in 2016 for the species (28.7 percent [1.9–81.0 credible interval] and 52.0 percent [3.2–97.7 credible interval] at the 10- and 20-year marks, respectively). Though highly uncertain, the risk is non-negligibly positive. Warning signal analysis indicates the current dynamic is dominated by stochastic variation, which seems to be heightening risk with the passage of time. Increasing breeding opportunities through restoration of milkweed in its northern breeding locations seems to be the most promising means of mitigating extinction risk for this species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231097","usgsCitation":"Thogmartin, W.E., 2024, Non-negligible near-term risk of extinction to the eastern migratory population of monarch butterflies—An updated assessment (2006–22): U.S. Geological Survey Open-File Report 2023–1097, 10 p., https://doi.org/10.3133/ofr20231097.","productDescription":"Report: iii, 10 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-152775","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":423797,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WRARO7","text":"USGS data release","linkHelpText":"Eastern migratory monarch butterfly population estimates and associated early warning signals (2006–22)"},{"id":423796,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1097/images/"},{"id":423798,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231097/full"},{"id":423795,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1097/ofr20231097.XML"},{"id":423794,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1097/ofr20231097.pdf","text":"Report","size":"949 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1097"},{"id":423793,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1097/coverthb.jpg"}],"contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
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La Crosse, Wisconsin 54603
The Federal Priority Streamgage (FPS) network of the U.S. Geological Survey (USGS), created in 1999 as the National Streamflow Information Program, receives Congressional appropriations to support the operation of a federally-funded “backbone” network of streamflow gages across the United States that are designated to meet the “Federal needs” or priorities of the country. Anticipating the evolution of Federal stakeholder water-data needs, the USGS launched a re-evaluation of the fundamental priorities for the FPS network in October 2020. In March 2022, the FPS Re-Prioritization Project used an online survey to solicit feedback from 767 stakeholders representing 22 Federal agencies who benefit from the FPS network. Additional feedback from survey respondents was obtained during online listening sessions to validate the USGS’s understanding of current Federal water-data needs. Results of the feedback show that the original five network priorities identified by the U.S. Geological Survey in 1999 are still valid but require modification to better incorporate additional needs, including Federal water operations, streamflow trends and extremes, water rights involving Federal lands, and streamflow data supporting ecosystem health. Federal stakeholder feedback also indicated that the inclusion of precipitation and water-temperature data collection, along with stream imagery, would enhance the value of the FPS network.
Results of the FPS Re-Prioritization Project and Open Season that ended in May 2024 revealed that the number of FPS locations meeting the updated eligibility criteria nearly tripled, which illustrates the value of the information provided by the FPS network. The Water Forecasting & Operations and the Water Quality network priorities contributed to the largest number of new eligible FPS sites, demonstrating the importance of the FPS network in supporting informed decisions related to the protection of life, property, the environment, and the economy of the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231032","usgsCitation":"Dillow, J.J.A., McCallum, B.E., and Angeroth, C.E., 2023, Re-prioritization of the U.S. Geological Survey Federal Priority Streamgage Network (ver. 1.1, April 2025): U.S. Geological Survey Open-File Report 2023–1032, 7 p., https://doi.org/10.3133/ofr20231032.","productDescription":"Report: iii, 7 p.; Data Release","numberOfPages":"7","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146165","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":484210,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1032/versionHist.txt","text":"Version History","size":"5 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Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
In response to previous reports of per- and polyfluoroalkyl substances (PFAS) contamination in French Island’s (located in the Mississippi River within the town of Campbell, Wisconsin) primary source of drinking water, 11 locations were sampled by the U.S. Geological Survey (USGS) in October 2021 to assess the potential presence of contaminant mixtures, including PFAS, in tapwater. Three locations were assessed seven times each over the course of three days. These samples were chosen to evaluate the water quality of the deeper Mount Simon bedrock aquifer and the water quality of the shallower sand and gravel (alluvial) aquifer at two locations. The other eight sample locations were spatially distributed within Campbell and were sampled once each. For each of these 11 sites, tapwater samples were analyzed for disinfection byproducts (DBP), pesticides, PFAS, pharmaceuticals, semi-volatile organic compounds (SVOC), volatile organic compounds (VOC), cations, anions, trace elements, alkalinity, microbial indicators, as well as measurements of water temperature, specific conductance, and pH. Of the 506 organic compounds analyzed in each water-quality sample, 74 (14 percent) were detected at least one time in any of the samples collected. Of the 14 percent, detected analytes included 27 pesticides (5 percent), 14 PFAS (3 percent), 6 pharmaceuticals (1 percent), 7 SVOC (1 percent), and 20 VOC (4 percent). No DBP were detected. The total number of organic compounds detected per sample ranged from 0–20 (median of 10), with the sum of concentrations ranging from not detected (nd)–2.53 micrograms per liter (μg/L; median of 0.333 μg/L). Of the inorganic constituents measured, eight were not detected above their reporting limit in any of the samples. The inorganic constituents that were not detected were antimony, arsenic, beryllium, cadmium, cobalt, molybdenum, selenium, and vanadium.
Along with the 11 sites sampled throughout Campbell, Wisconsin, beginning in October 2021, four more wells were sampled on the Upper Midwest Environmental Sciences Center (UMESC) campus for PFAS. Three of these sites withdraw water from the shallow alluvial aquifer (the same source water for tapwater site 002) and one from the Mount Simon aquifer (the same source of water for tapwater site 001). This sampling is ongoing with results from samples through December 2022 summarized in this report. Of the 33 PFAS analyzed in samples from the four UMESC locations, 15 individual PFAS were detected at least one time in any of the samples analyzed with the sum of PFAS concentrations ranging from nd–1.49 μg/L (median of 0.309 μg/L).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231088","collaboration":"Prepared in cooperation with the Town of Campbell, Wisconsin","programNote":"Environmental Health Program","usgsCitation":"Romanok, K.M., Meppelink, S.M., Bradley, P.M., Breitmeyer, S.E., Donahue, L., Gaikowski, M.P., Hines, R.K., and Smalling, K.L., 2023, Occurrence of mixed organic and inorganic chemicals in groundwater and tapwater, town of Campbell, Wisconsin, 2021–22: U.S. Geological Survey Open-File Report 2023–1088, 29 p., https://doi.org/10.3133/ofr20231088.","productDescription":"Report: viii, 29 p.; 2 Data Releases","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-150739","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499196,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115939.htm","linkFileType":{"id":5,"text":"html"}},{"id":423893,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J6XKVS","text":"USGS data release","linkHelpText":"Quarterly sample results for perand polyfluoroalkyl substances (PFAS) for locations in Campbell, Wisconsin, 2021–22"},{"id":423892,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EUBGUF","text":"USGS data release","linkHelpText":"Target-chemical concentrations for assessment of mixed-organic/inorganic chemical and biological exposures in private-well tapwater at Campbell, Wisconsin, 2021"},{"id":423887,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1088/coverthb.jpg"},{"id":423888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1088/ofr20231088.pdf","text":"Report","size":"1.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1088"},{"id":423889,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231088/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1088"},{"id":423890,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1088/ofr20231088.XML"},{"id":423891,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1088/images/"}],"country":"United States","state":"Wisconsin","county":"La Crosse County","city":"Campbell","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.29371444024203,\n 43.904997377408506\n ],\n [\n -91.29371444024203,\n 43.84807720086516\n ],\n [\n -91.23878279961701,\n 43.84807720086516\n ],\n [\n -91.23878279961701,\n 43.904997377408506\n ],\n [\n -91.29371444024203,\n 43.904997377408506\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
3450 Princeton Pike, Suite 110
Lawrenceville, New Jersey 08648
This investigation delineates the geologic framework of an area of 75 square kilometers (km2) located west of the Salton Sea in southern California (fig. 1, on sheet 1). The study area encompasses the south flank of the Santa Rosa Mountains and the eastern part of the Borrego Badlands (sheet 1). In this study area, regionally important stratigraphic and structural elements collectively inform the late Cenozoic geologic evolution of the Anza-Borrego sector of the Salton Trough province. Critical stratigraphic and structural elements in the map area include the following:
Geologic mapping and analysis for this investigation focused on clarifying geologic relations among these four stratigraphic and structural aspects in the map area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231076","usgsCitation":"Pettinga, J.R., Dudash, S.L., and Cossette, P.M., 2023, Preliminary Geologic Map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California: U.S. Geological Survey Open-File Report 2023–1076, scale 1:12,000, https://doi.org/10.3133/ofr20231076.","productDescription":"2 Plates: 70.66 x 31.92 inches and 51.22 x 32.64 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-100617","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":423753,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2023/1076/ofr20231076_sheet1.pdf","text":"Sheet 1","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":423752,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1076/covrthb.jpg"},{"id":499789,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115708.htm","linkFileType":{"id":5,"text":"html"}},{"id":423768,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L8YSQX","text":"USGS Data Release","linkHelpText":"Digital Database for the Preliminary Geologic Map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California"},{"id":423754,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2023/1076/ofr20231076_sheet2.pdf","text":"Sheet 2","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Borrego Badlands, southern Santa Rosa Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.208333,\n 33.316667\n ],\n [\n -116.208333,\n 33.25\n ],\n [\n -116.083333,\n 33.25\n ],\n [\n -116.083333,\n 33.316667\n ],\n [\n -116.208333,\n 33.316667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Imaging sonar was used to assess the influence of a fish guidance net, installed at the entrances to the selective water withdrawal (SWW) intake structure, in the forebay of Round Butte Dam, Oregon, on behavior, abundance, and timing of fish during the spring of 2022. The purposes of the SWW are (1) to direct surface currents in the forebay to attract and collect downriver migrating juvenile salmonid smolts (Chinook salmon [Oncorhynchus tshawytscha], sockeye salmon [O. nerka], and steelhead [O. mykiss]) from Lake Billy Chinook and (2) to enable operators of the SWW to withdraw water from surface and benthic elevations in the reservoir to manage downriver water temperatures. Part of the evaluation to determine how well the structure performs at collecting juvenile salmonids is (1) to regularly assess how fish are approaching the entrance, and (2) determine if operational flows and the installation of a guidance (lead) net near the SWW structure entrance can be optimized to increase the attraction of smolts present in the forebay of Lake Billy Chinook. The goal of this study was to provide data about the effects of the installation of a lead net on the movements and behaviors of juvenile salmonids near the entrance to the SWW to help inform decisions to improve downstream passage solutions.
Two imaging sonar units were deployed during the spring 2022 smolt out-migration period. One unit monitored fish movements near the south entrance and one unit monitored movements near the north entrance of the SWW, with the lead net between the two entrances. Both smolt and bull trout (Salvelinus confluentus)-size fish were regularly observed near the entrances, with greater abundances observed at night, corresponding with greater discharge through the SWW, as opposed to during the day when discharge was reduced. Smolt-size fish groups were primarily observed near the interior halves of each SWW entrance, and greater abundances of fish were observed at the south entrance. Increased counts of bull trout-size fish coincided with the increased abundances of smolt-size fish. Overall, the results indicate that (1) smolt-size fish were more abundant near the entrance of the SWW during periods of increased discharge, (2) bull trout-size fish were present at the SWW, and (3) a greater percentage of smolt-size fish were observed directed toward the entrances of the SWW during periods of increased discharge. The addition of the lead net may assist in orienting fish toward the entrances to the SWW.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231090","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., and Hatton, T.W., 2023, Influence of a guide net on the presence and behavior of fish near the selective water withdrawal structure in Lake Billy Chinook, Oregon, 2022: U.S. Geological Survey Open-File Report 2023–1090, 25 p., https://doi.org/10.3133/ofr20231090.","productDescription":"vii, 25 p.","onlineOnly":"Y","ipdsId":"IP-155570","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":423749,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231090/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1090"},{"id":423751,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1090/ofr20231090.XML"},{"id":423750,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1090/Images"},{"id":423747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1090/ofr20231090.jpg"},{"id":423748,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1090/ofr20231090.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1090"},{"id":500154,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115707.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Billy Chinook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.64591331853623,\n 44.79048612033958\n ],\n [\n -121.64591331853623,\n 44.35814579483878\n ],\n [\n -121.03356092450966,\n 44.35814579483878\n ],\n [\n -121.03356092450966,\n 44.79048612033958\n ],\n [\n -121.64591331853623,\n 44.79048612033958\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
We assessed habitat suitability for salmonids across selected tributaries upstream from three hydroelectric dams on the upper Skagit River in Whatcom County, northern Washington. We used NetMap, a commercial toolset within the ArcMap geographic information system (GIS), to analyze stream attributes based upon a synthetic stream channel network derived from digital elevation models. The GIS-derived stream attributes—including gradient, bankfull width, valley width index, elevation, and stream flow—allowed us to examine the spatial distribution and relative quality of spawning and rearing habitat for salmonids based on existing intrinsic potential (IP) models. As a first step, we created maps of potential anadromous fish distribution by identifying potential migration barriers within the synthetic stream network. Next, we applied a suite of existing IP models for steelhead, coho, and Chinook salmon (Oncorhynchus mykiss, O. kisutch, and O. tshawytscha, respectively) to estimate low, medium, and high IP habitat for each species. Three different IP models were used for each species, based on species preference curves from populations from coastal Oregon, northern California, Alaska, and western Washington. We found that at least 25 tributaries that were greater than third order and contained habitat with the potential for anadromous fish, totaling about 470 river kilometers in 4,453 synthetic stream reaches averaging about 100 meters (m) in length. The IP of each of these reaches was calculated and placed into low, medium, and high IP categories. For Chinook salmon, the only stream with significantly (in other words, greater than 1 kilometer [km]) high IP reaches was the upper Skagit River upstream from Ross Lake reservoir in Canada, upstream from the third dam in the hydroelectric system. There were differences among the three models evaluated, with the model derived for the lower Skagit River showing more high and medium IP habitat than the other two models that were designed for the Columbia River Basin. For coho salmon, all three models showed similar results favoring medium IP over low and high IP habitat. Of the 3 species examined with existing IP models, steelhead had the most habitat rated as high IP with 19 targeted tributaries showing greater than 1 km of high intrinsic potential habitat.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231077","collaboration":"Prepared in cooperation with Seattle City Light","usgsCitation":"Duda, J.J., and Hardiman, J.M., 2023, Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington: U.S. Geological Survey Open-File Report 2023-1077, 44 p. https://doi.org/10.3133/ofr20231077.","productDescription":"Report: viii, 44 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-147497","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":423653,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.XML"},{"id":423733,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MKQ2UK","text":"USGS data release","description":"USGS data release","linkHelpText":"Upper Skagit River intrinsic potential results"},{"id":423650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.pdf"},{"id":423649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.jpg"},{"id":423652,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1077/Images"},{"id":423651,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231077/full"}],"country":"Canada, United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.3,\n 49.3\n ],\n [\n -121.3,\n 48.3\n ],\n [\n -120.3,\n 48.3\n ],\n [\n -120.3,\n 49.3\n ],\n [\n -121.3,\n 49.3\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 contribution of renewable energy to meet worldwide demand continues to grow. In the United States, wind energy is one of the fastest growing renewable energy sectors. Throughout the Great Plains of the United States, wind facilities often are placed in open landscapes of high-elevation grasslands, and those same habitats support sharp-tailed grouse (Tympanuchus phasianellus), a resident gamebird species. To assess the feasibility of using independently derived, long-term datasets gathered in North Dakota and South Dakota to determine whether wind facilities affected lek metrics, the U.S. Geological Survey obtained six datasets and identified 37 study sites, 9 of which contained wind turbines at varying densities. The association between explanatory variables that described geographic, landscape, and climatic attributes with two primary response metrics that described lekking activity within study sites—lek density (leks per square kilometer) and mean number of males per lek—was examined. The explanatory variables included number of turbines, geographic location, elevation, land-cover attributes available from satellite-derived land-cover data, soil moisture, precipitation, and temperature. Sampling units consisted of township-sized blocks, and lek information came from roadside surveys. Low sample sizes of constructed wind facilities available at the time of analysis did not lend itself to advanced statistical techniques, such as employing a rigorous design structure or assessing accuracy on landscape, geographic, or climatic variables. Given the quality of the data, the estimates obtained for lek density and mean number of males per lek should be considered approximations; however, these estimates have value in designing future studies, such as providing estimates for power analyses to determine sufficient sample size. No strong associations were found between the included explanatory variables and response variables (when these variables were measured as described in this report for township-sized blocks). The strongest association was that lek density and mean number of males per lek increased from South Dakota to North Dakota. Owing to the highly unbalanced distribution of turbine and nonturbine study sites across the study area, the analysis with wind turbines was inconclusive. The constraints under which the analysis can be used and the limitations of the independently derived datasets in attempted applications are discussed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231091","usgsCitation":"Shaffer, J.A., Buhl, D.A., and Newton, W.E., 2023, Assessing the use of long-term lek survey data to evaluate the effect of landscape characteristics and wind facilities on sharp-tailed grouse lek dynamics in North Dakota and South Dakota: U.S. Geological Survey Open-File Report 2023–1091, 33 p., https://doi.org/10.3133/ofr20231091.","productDescription":"Report: v, 33 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154704","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":500155,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115688.htm","linkFileType":{"id":5,"text":"html"}},{"id":423438,"rank":3,"type":{"id":31,"text":"Publication 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Dakota\",\"nation\":\"USA \"}}]}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
The authors used decision and modeling analyses to evaluate management alternatives for a decision on whether to permit Cervus canadensis (elk) feeding on two sites on Bridger-Teton National Forest, Dell Creek and Forest Park. Supplemental feeding of elk could increase the transmission of chronic wasting disease (CWD) locally and disease spread regionally, potentially impacting elk populations over time with wider implications for Odocoileus hemionus (mule deer) and Odocoileus virginianus (white-tailed deer) populations and hunting, tourism, and regional revenue. Supplemental feeding is thought to improve overwinter elk survival and reduce the commingling of elk with cattle during months when brucellosis transmission risk is highest. We worked with the U.S. Department of Agriculture Forest Service to identify their fundamental objectives and associated performance metrics related to this feedground decision. We then developed disease and habitat selection models to quantify the effect of four management alternatives on select performance metrics. The four alternatives were to continue to permit feeding, phaseout permits to feed in three years, permit feeding on an emergency basis, or stop permitting feeding. In this report, we present methods and summarized results on disease and habitat selection models and summaries of other performance metrics analyzed by BIO-WEST, Inc. and Cirrus Ecological Solutions as part of an Environmental Impact Statement.
Data from Wyoming Game and Fish Department (WGFD) supported the assumption that supplemental elk feeding allows for larger elk populations in a region. We documented that herd units (HU) without feedgrounds had 23 percent lower densities of elk per area of winter range when compared against HUs with feedgrounds, after accounting for differences in sightability of elk during counts on and off feedgrounds. Thus, throughout our analyses, we assumed feedground closures would reduce elk carrying capacity resulting in an average decline of previously fed elk population segments by 23 percent (5th and 95th percentiles = [11 percent, 35 percent]) by year 20. Most of that decline occurred within the first few years after a feedground ceases to operate. We used a panel of CWD experts to help estimate CWD trans-mission in fed and unfed elk population segments. In aggregate, the expert panel estimated that median values of direct and indirect transmission of CWD are expected to be 1.9 and 4 times higher, respectively, in fed elk populations compared to unfed elk. We used these disease transmission estimates in combination with local elk demographic rates and carrying capacity estimates to project disease and population dynamics.
In year 20, we predicted CWD prevalence would increase to 42 percent (5th and 95th percentiles = [29 percent, 55 percent]), and 13 percent (5th and 95th percentiles = [4 percent, 26 percent]) on average for fed and unfed elk population segments, respectively, given a starting prevalence of 1.6 percent. The prevalence estimates for the unfed elk population segments are in the range of previous observations of CWD in elk in the western United States. The average CWD prevalence from 2016 to 2018 in the unfed elk population of Wind Cave National Park in South Dakota was 18 percent overall but up to 30 percent in some regions (Sargeant and others, 2021). Meanwhile, CWD prevalence in the Iron Mountain and Laramie Peak elk herds in Wyoming from 2016 to 2018 was 14 percent and 7 percent, respectively, despite being present since at least 2002 (Wyoming Game and Fish Department, 2020b).
From 2016 to 2020, elk that were fed at Dell Creek and Forest Park constituted on average 12–20 percent of the total elk on their respective HUs. As a result, the differences between management alternatives are modest when considering the closure of only one feedground on a HU. The no feeding alternative for Forest Park resulted in a CWD prevalence of 17 percent (SD = 7 percent) in the Afton HU compared to 20 percent (SD = 7 percent) with continued feeding by year 20. In the Upper Green River HU, no feeding on Dell Creek resulted in a CWD prevalence of 27 percent (SD = 6 percent) compared to 30 percent (SD = 5 percent) with continued feeding. In terms of disease-associated mortality, we predicted the closure of Forest Park and Dell Creek feedgrounds would reduce the total number of CWD mortalities by 9 percent in the Upper Green River HU and 26 percent in the Afton HU during the 20-year timespan.
Our spatial analyses predicted that management alternative effects vary by HU as a function of private property and other wildlife winter ranges proximity relative to feedground location. The predicted number of elk abortions on private land, as a proxy for brucellosis risk to cattle, may increase by 8–21 percent in the absence of feeding at Dell Creek and Forest Park.
Eight feedgrounds are located on Bridger-Teton National Forest, all of which have permits that have expired or will expire prior to 2028. In addition, WGFD could change their management of feedgrounds given new information; therefore, we also assessed the cumulative effects of continued feeding, phaseout, and no feeding management alternatives across five HUs south of Jackson, Wyoming (Afton HU, Fall Creek HU, Piney HU, Pinedale HU, and Upper Green River HU). These five HUs ranged from about 41 to 85 percent of the elk herd using feedgrounds, which corresponded to a CWD prevalence at year 20 of 23–34 percent if all feedgrounds in those five HUs remained open relative to 12 to 14 percent if all feedgrounds were closed. We predicted feedground closures may result in immediate reductions in population size relative to alternatives that continue feeding (for example, continued feeding and emergency feeding alternatives); however, over longer periods of time, CWD-associated mortality leads to larger population reductions. The no feeding alternative resulted in higher elk population sizes compared to the continued feeding alternative after about 10 years of implementation. Delayed action under a phaseout alternative resulted in increasing the CWD prevalence to 20 percent relative to 12 to 14 percent, on average, without feeding on HUs with a large population of fed elk such as the Upper Green River HU.
Summarizing our cumulative results across all five of the analyzed HUs, we predicted continued feeding will lead to fewer elk by year 20 (mean = 8,300, standard deviation [SD] = 740) compared to no feeding at U.S. Department of Agri-culture Forest Service sites (10,700, SD = 890). The closure of all feedgrounds was projected to result in the largest elk populations at year 20 (12,500, SD = 980). No feeding at all sites also resulted in the largest cumulative harvest of 57,700 (SD = 2,600) compared to 51,100 (SD = 3,800) for continued feeding at all current feedground sites on the five HUs. Continued feeding also resulted in the lowest brucellosis costs to producers ($194,600, SD = $11,500) compared to no feeding on all feedgrounds ($243,000, SD = $13,700). Assuming moderate reductions in hunter interest because of increasing CWD prevalence in elk, we predicted that no feeding resulted in regional revenues generated by hunting activities of $190 million (SD = $10 million) compared to $173 million (SD = $10 million) for continued feeding over the 20-year timeframe.
Recent CWD detections in mule deer and elk in Grand Teton National Park has elevated the importance of the cur-rent decision on whether, and how, to permit elk feeding on Dell Creek and Forest Park and the management of the other feedgrounds. Aggressive male harvest has slowed, but not stopped, the increasing prevalence of CWD in mule deer (Conner and others, 2021). It is unclear whether harvest management can be an effective tool to slow the spread of CWD in elk. There are also no effective treatments or vaccines for CWD, and it is unlikely that any will be developed that can be easily deployed in the near future. Thus, reducing artificial aggregations is one of the few management approaches suggested by the Western Association of Fish and Wildlife Agencies (Almberg and others, 2017).
Future surveillance and monitoring can be designed to resolve uncertainties that can improve future decision-making. If feedgrounds close, research could quantify elk population reductions in the absence of feeding, the redistribution of fed elk to other places, or the consequences of elk movement on private property. If feedgrounds remain open, research could assess how rapidly CWD spreads in artificial aggregations of elk; however, surveillance programs would need to be designed with sufficient power to detect initial changes of CWD prevalence. Delaying action on feedground management was projected to be costly. Results of the phaseout alternative relative to the no feeding alternative suggested a 3-year delay was enough for substantial long-term changes in CWD prevalence. The long-term persistence of infectious CWD prions in the environment suggests that feedground management decisions may have long-lasting consequences.
Our results indicated tradeoffs in the ability of a management agency to achieve all their objectives, and all management alternatives resulted in significant reductions in elk population size. This report contains the foundational elements for formal decision analysis methods, which can be implemented to help decision makers transparently evaluate the consequences of decision alternatives and identify the set of actions that best achieve agency and stakeholder priorities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231015","collaboration":"Prepared in cooperation with U.S. Department of Agriculture, National Park Service, U.S. Fish and Wildlife Service, and Wyoming Game and Fish Department","usgsCitation":"Cook, J.D., Cross, P.C., Tomaszewski, E.M., Cole, E.K., Campbell Grant, E.H., Wilder, J.M., and Runge, M.C., 2023, Evaluating management alternatives for Wyoming Elk feedgrounds in consideration of chronic wasting disease (ver. 2.0, November 2023): U.S. Geological Survey Open-File Report 2023–1015, 50 p., https://doi.org/10.3133/ofr20231015.","productDescription":"Report: ix, 50 p.; Software Release","onlineOnly":"Y","ipdsId":"IP-145385","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499766,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114473.htm","linkFileType":{"id":5,"text":"html"}},{"id":422707,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1015/versionHist.txt","size":"4.0kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2023-1015 history file"},{"id":422706,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1015/ofr20231015.pdf","text":"Report","size":"7.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1015"},{"id":419233,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1015/coverthb2.jpg"},{"id":422704,"rank":2,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9R7XWO1","text":"USGS software release—","linkHelpText":"Simulating chronic wasting disease on Wyoming elk feedgrounds (version 2.0)."}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.03672229293583,\n 43.73180346838649\n ],\n [\n -111.03672229293583,\n 42.40523773968059\n ],\n [\n -109.27478197144448,\n 42.40523773968059\n ],\n [\n -109.27478197144448,\n 43.73180346838649\n ],\n [\n -111.03672229293583,\n 43.73180346838649\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: March 2023: Version 2.0: November 2023","contact":"Director, Northern Rocky Mountain Science Center
U.S. Geological Survey
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This report addresses system characterization of the Pléiades Neo satellite 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.
Pléiades Neo is a constellation of four identical very-high-resolution optical satellites operated by Airbus Defence and Space. The first two satellites, Pléiades Neo-3 and -4, were launched in April and August 2021, respectively. The next two satellites, launched in December 2022, did not reach orbit because of Vega-C launch vehicle failure. Pléiades Neo provides several technical improvements to previous Pléiades-HR satellites, including the addition of coastal aerosol (deep blue) and red edge spectral bands, with improved ground sample distance and swath. The Pléiades Neo satellites were designed and built by Airbus Defence and Space with the high-resolution, multispectral imager for Earth imaging and use the S950 optical satellite bus. The high-resolution sensor on Pléiades Neo collects Earth data in the visible and near-infrared region with six bands and a panchromatic band. The satellites can operate off nadir to achieve a revisit of less than 1 day. More information on Pléiades Neo satellites and sensors is available in the “Land Remote Sensing Satellites Online Compendium” (https://calval.cr.usgs.gov/apps/compendium#) and from the manufacturer (https://www.intelligence-airbusds.com/imagery/constellation/pleiades-Neo/).
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that Pléiades Neo has an interior geometric performance in the range of 0.01 meter (m; 0.008 pixel) to −0.017 m (−0.014 pixel) in band-to-band registration; an exterior geometric performance in the range of −7.015 m (−0.702 pixel) to 3.846 m (0.385 pixel) offset in comparison to Sentinel-2 using ground control points of 2.2 to 7.2 m (95-percent circular error); a radiometric performance in the range of −0.070 (minimum) to −0.053 (maximum) in offset and 1.107 (minimum) to 1.202 (maximum) in slope; and a spatial performance in the range of 1.002 to 1.226 pixels at full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.22 to 0.34 (bands 2–7).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"System Characterization of Earth Observation Sensors","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030P","usgsCitation":"Cantrell, S.J., Sampath, A., Vrabel, J.C., Bresnahan, P., Anderson, C., Kim, M., and Park, S., 2023, System characterization report on the Pléiades Neo Imager (ver. 1.1, April 2024), chap. P of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 52 p., https://doi.org/10.3133/ofr20211030P.","productDescription":"Report: vi, 52 p.; Version History","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-154436","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":422656,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/p/coverthb2.jpg"},{"id":422657,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/p/ofr20211030p.pdf","text":"Report","size":"21.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–P"},{"id":422658,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/p/ofr20211030p.XML"},{"id":428107,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1030/p/versionHist.txt","text":"Version History","size":"1.99 kB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: November 16, 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
From 2014 to 2020, a Monitoring Avian Productivity and Survivorship (MAPS) banding station (station) was operated at the Naval Outlying Landing Field (NOLF), Imperial Beach, in southwestern San Diego County, California. The station was established as part of a long-term monitoring program of Neotropical migratory bird populations on NOLF and helps Naval Base Coronado (NOLF is a component) meet the goals and objectives of the Department of Defense Partners in Flight program and the Birds and Migratory Birds Management Strategies of the Naval Base Coronado Integrated Natural Resources Management Plan. The station was established in 2009 and has been in operation during the spring and summer since 2009 except for 2016 when it was not funded. The station was operated by AMEC Earth and Environmental, Inc., from 2009 to 2011, by the U.S. Geological Survey from 2012 to 2015, the San Diego Natural History Museum in 2017, and the U.S. Geological Survey again from 2018 to 2023. This report synthesizes results from 2014 to 2020. A prior report presents summaries and analyses from 2009 to 2013.
The banding station at NOLF was operated according to the standard MAPS protocol with some exceptions. Ten mist nets used to capture birds were erected in fixed locations that remained consistent between and within years, with few minor relocations. Nets were open for 6 hours per day, once every 10 days (a netting period) for 13 netting periods starting April 1 each year. Occasionally, poor weather conditions (for example, rain, wind, or excessive heat) prevented net operation or forced nets to be closed early (or, rarely, late). Nets were checked periodically throughout the day and birds were removed, processed (leg bands affixed, measurements recorded), and released.
From 2014 to 2020, we had 3,543 captures (including initial captures and recaptures) of a maximum of 3,264 year-unique captures (543±143 year-unique captures [the total number of individual birds captured for the first time each year]). The count of year-unique captures included 2,702 newly banded birds, 258 individuals that were recaptured from previous years, and 304 birds that were released unbanded (218 hummingbirds and 86 other birds that were intentionally released unbanded [game birds, and so forth] or escaped before banding). Individuals of 68 species were captured, 39 of which breed at or in the immediate vicinity of the MAPS banding station. Bird capture rate averaged 43±30 captures per day (corrected to account for variation in effort) for all years (range 7–163 effort-corrected captures per day) and species richness per year averaged 43±4. Bushtit (Psaltriparus minimus) was the most abundant species captured, followed by Orange-crowned Warbler (Leiothlypis celata), Wilson’s Warbler (Cardellina pusilla), House Finch (Haemorhous mexicanus), Song Sparrow (Melospiza melodia), and Common Yellowthroat (Geothlypis trichas). The mean adult sex ratio of all species combined across all years was 54:46 male:female. Adults averaged 73±12 percent of known age captures per year (range 59–94 percent), and juveniles averaged 27±12 percent (range 6–41 percent).
Nineteen sensitive species were detected at NOLF (12 captured and 7 observed only). During 2014–20, we captured one State and federally endangered species, Least Bell’s Vireo (Vireo bellii pusillus); one federally threatened species, California Gnatcatcher (Polioptila californica); one State endangered species, Willow Flycatcher (Empidonax traillii); and two State species of concern, Yellow-breasted Chat (Icteria virens) and Yellow Warbler (Setophaga petechia). One additional State species of concern, Northern Harrier (Circus hudsonius), was observed at the MAPS banding station but not captured. Peregrine Falcon (Falco peregrinus) and White-tailed Kite (Elanus leucurus), California State fully protected species, also were observed at the MAPS banding station. Seven federal bird species of conservation concern—Calliope Hummingbird (Selasphorus calliope), Rufous Hummingbird (Selasphorus rufus), Allen’s Hummingbird (Selasphorus sasin), Nuttall’s Woodpecker (Dryobates nuttallii), Wrentit (Chamaea fasciata), California Thrasher (Toxostoma redivivum), and Lawrence’s Goldfinch (Spinus lawrencei)—also were captured, and four additional federal bird species of conservation concern—Willet (Tringa semipalmata), Western Gull (Larus occidentalis), California Gull (Larus californicus), and Bullock’s Oriole (Icterus bullockii)—were observed but not captured.
Local population trends varied among species and years. From 2012 to 2019, year-round residents Bushtit, Song Sparrow, and Common Yellowthroat significantly decreased, whereas the migrant Least Bell’s Vireo increased. The total number of captures for all species except Least Bell’s Vireo was lowest in 2017, corresponding to the habitat damage caused by Kuroshio shot hole borer beetle (Euwallacea kuroshio) in the Tijuana River Valley.
Annual productivity and annual adult survival were calculated for seven breeding species based on criteria used by the Institute for Bird Populations (Least Bell’s Vireo, Bushtit, Wrentit, House Wren [Troglodytes aedon], Song Sparrow, Orange-crowned Warbler, and Common Yellowthroat). Productivity was highest for most species in 2010 and 2019, years with high precipitation, and lowest in 2014 and 2018, years with low precipitation. Song Sparrow demonstrated the highest productivity among species and Least Bell’s Vireo had the lowest productivity. Annual adult survival was generally high from 2011 to 2012 and from 2018 to 2019. Bushtit had higher annual survival with lower late winter precipitation. Either temperature or precipitation was associated with productivity for all species except Wrentit, and with survival for all species except Least Bell’s Vireo and Common Yellowthroat. For most species, productivity was positively associated with precipitation, and both productivity and survival were negatively associated with temperature. Other studies have found that higher temperatures led to increased predation by snakes and birds and also increased vector-borne disease transmission, such as West Nile virus. Predicted regional increases in temperature over the next 30 years will likely affect the demographics of these species.
The Song Sparrow population increased with higher breeding productivity during the previous year, and the Bushtit population increased with higher annual survival and higher productivity during the previous year. Aside from a possible positive association between survivorship and Common Yellowthroat population growth, productivity and survival rates did not appear to influence population change for other focal species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231055","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Lynn, S., Mendia, S., and Kus, B.E., 2023, Monitoring Avian Productivity and Survivorship (MAPS) 6-year summary, Naval Outlying Landing Field, Imperial Beach, southwestern San Diego County, California, 2014–20: U.S. Geological Survey Open-File Report 2023–1055, 68 p., https://doi.org/10.3133/ofr20231055.","productDescription":"viii, 68 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-150872","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":422046,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1055/images"},{"id":422047,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231055/full"},{"id":422044,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1055/ofr20231055.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":422043,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1055/covrthb.jpg"},{"id":422045,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1055/ofr20231055.xml"}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.13399491171916,\n 32.5777941285686\n ],\n [\n -117.13399491171916,\n 32.54958248003706\n ],\n [\n -117.08507141928763,\n 32.54958248003706\n ],\n [\n -117.08507141928763,\n 32.5777941285686\n ],\n [\n -117.13399491171916,\n 32.5777941285686\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The Rainy-Lake of the Woods Basin covers 70,000 square kilometers in mid-central North America and is contained within the Provinces of Ontario and Manitoba in Canada and the State of Minnesota in the United States. This basin contains natural wilderness areas, national parks, and thousands of lakes that bring outdoor enthusiasts from around the world for hunting, fishing, backpacking, boating, and other forms of recreation. However, trade, commerce, visitors, and wildlife can inadvertently transport hitchhiking exotic invasive species that affect the functioning of natural systems by displacing native organisms, introducing diseases, and modifying predator/prey relations. In cooperation with the International Joint Commission, the U.S. Geological Survey evaluated the aquatic invasive species that pose a possible threat to North America. The outcome of this project is a set of lists of invasive species that have traits amenable or proximity to the Rainy-Lake of the Woods Basin. These lists can be referenced to further evaluate known and potential nonindigenous invasive species. The lists were derived by evaluating more than 1,500 species from several online sources including Non-Indigenous Aquatic Species, Great Lakes Aquatic Nonindigenous Species Information System, Biodiversity Information Serving Our Nation, and other State, Provincial, and Federal lists in the United States and Canada. The purpose of these lists is to be a coarse filter to determine which species pose the greatest risk to the Rainy-Lake of the Woods Basin. Using this filter, seven categories of risk assessment priorities were developed: Very High-Approaching, Very High-Present, High-Approaching, High-Present, Moderate, Low, and Native. These categories can be used by the International Rainy-Lake of the Woods Multi-Agency Arrangement Aquatic Invasive Species Subcommittee to prioritize which species will be evaluated further focusing on five risk factors: arrival risk, vulnerability assessment, ecological impact, socioeconomic impact, and beneficial impact. Based on proximity, ease of transport or introduction, and known impact to Rainy-Lake of the Woods or other impacted ecosystems, this project identified the following 10 species that could be prioritized first for risk evaluations: Bythotrephes longimanus (spiny waterflea), Faxonius rusticus (rusty crayfish), Neogobius melanostomus (round goby), Dreissena polymorpha (zebra mussel), Bithynia tentaculata (mud Bithynia or faucet snail), Potamopyrgus antipodarum (New Zealand mud snail), Butomus umbellatus (flowering rush), Nitellopsis obtusa (starry stonewort), Myriophyllum spicatum (Eurasian watermilfoil), and Phragmites australis australis (common reed).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221070","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Bell, A.H., Katona, L.R., and Vellequette, N.M., 2023, Development and application of a risk assessment tool for aquatic invasive species in the international Rainy-Lake of the Woods Basin, United States and Canada: U.S. Geological Survey Open-File Report 2022–1070, 26 p., https://doi.org/10.3133/ofr20221070.","productDescription":"Report: vi, 26 p.; 3 Datasets","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127028","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499719,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115587.htm","linkFileType":{"id":5,"text":"html"}},{"id":422425,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221070/full"},{"id":422424,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://bison.usgs.gov/","text":"USGS database","linkHelpText":"—Biodiversity Information Serving Our Nation (BISON)"},{"id":422421,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1070/images/"},{"id":422418,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1070/coverthb.jpg"},{"id":422420,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1070/ofr20221070.XML"},{"id":422419,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1070/ofr20221070.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1070"},{"id":422422,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://www.glerl.noaa.gov/glansis/riskAssessment.html","text":"NOAA database","linkHelpText":"—Great Lake Aquatic Nonindigenous Species Information System (GLANSIS) Risk Assessment Clearinghouse"},{"id":422423,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://nas.er.usgs.gov/","text":"USGS database","linkHelpText":"—NAS—Nonindigenous Aquatic Species"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.7568318410593,\n 50.39164460188181\n ],\n [\n -95.7568318410593,\n 47.02962883799128\n ],\n [\n -90.08788652855912,\n 47.02962883799128\n ],\n [\n -90.08788652855912,\n 50.39164460188181\n ],\n [\n -95.7568318410593,\n 50.39164460188181\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
The U.S. Geological Survey (USGS) Risk Research and Applications Community of Practice (Risk CoP) is a bureau-wide forum to share resources and discuss issues relevant to “conducting and applying scientific research in hazards—the dangerous processes or phenomena that may cause damage—to enhance the reduction of risk—the potential for societally relevant losses caused by hazards” (Ludwig and others, 2018). In 2021, this group held a workshop entitled “Considering Equitable Engagement in Research Design” as a part of its annual meeting. This report is a result of the workshop findings and includes additional input from the Risk CoP, other communities of practice, and subject matter experts across the USGS. The resources described in this report are intended to help guide USGS scientists aiming to include equity into their risk research but can apply to all USGS scientists, regardless of their research focus. This report shares key considerations for equitable engagement as identified by workshop participants, a discussion of the spectrum of engagement in equity-related research, and a toolkit that can help USGS scientists consider how to integrate equity into their work. Although this report is not comprehensive, it does seek to fill a gap that exists at the USGS; at the time of writing, there is no guidance on how to integrate equity into research design. The authors of this report believe that this document can serve as a foundation for future equity-related work at the USGS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231072","usgsCitation":"Brooks, E., Pennaz, A., and Jurjonas, M., 2023, U.S. Geological Survey risk research community of practice 2021 workshop report—Workshop on considering equitable engagement in research design: U.S. Geological Survey Open-File Report 2023–1072, 25 p., https://doi.org/10.3133/ofr20231072.","productDescription":"iv, 25 p.","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-145163","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":422253,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1072/ofr20231072.XML"},{"id":422252,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1072/images/"},{"id":422251,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231072/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1072 HTML"},{"id":422250,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1072/ofr20231072.pdf","text":"Report","size":"1.10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1072 PDF"},{"id":422249,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1072/coverthb.jpg"}],"contact":"Director, Natural Hazards Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr.
Reston, VA 20192
Integrating recent scientific knowledge into management decisions supports effective natural resource management and can lead to better resource outcomes. However, finding and accessing scientific knowledge can be time consuming and costly. To assist in this process, the U.S. Geological Survey (USGS) created a series of annotated bibliographies on topics of management concern for western lands. Previously published reports introduced a methodology for preparing annotated bibliographies to facilitate integration of recent, peer-reviewed science into resource management decisions. Therefore, relevant text from those efforts is reproduced here and built on to incorporate new information. The greater sage-grouse (Centrocercus urophasianus; hereafter “GRSG”) has been a focus of scientific investigation and management action for the past two decades. The 2015 U.S. Fish and Wildlife Service listing determination of “not warranted” under the Endangered Species Act was in part a result of a large-scale collaborative effort to develop strategies to conserve GRSG populations and their habitat and to reduce threats to both. New scientific information augments existing knowledge and can help inform updates or modifications to existing plans for managing GRSG and sagebrush ecosystems. However, the sheer number of scientific publications can be a challenge for managers tasked with evaluating and determining the need for potential updates to existing planning documents. To assist in this process, the USGS has reviewed and summarized the scientific literature published since January 1, 2015. Our most recent GRSG literature summary was published in 2020 (Carter and others, 2020) and included products published through October 2, 2019. Here, we consider products published between October 2, 2019, and July 21, 2022. We compiled and summarized peer-reviewed journal articles, data products, and formal technical reports (such as U.S. Department of Agriculture Forest Service General Technical Reports and USGS Open-File Reports) on greater sage-grouse. We first systematically searched three reference databases and three government databases using the search phrase “greater sage-grouse.” We refined the initial list of products by removing (1) duplicates, (2) publications not published as research, data products, or scientific review articles in peer-reviewed journals or as formal technical reports, and (3) products for which greater sage-grouse was not a research focus or the study did not present new data or findings about greater sage-grouse. We summarized each product using a consistent structure (background, objectives, methods, location, findings, and implications) and identified management topics addressed by each product; for example, species and population characteristics. We also identified projects that provided new geospatial data. The review process for this annotated bibliography included two initial internal colleague reviews of each summary, requesting input on each summary from an author of the original publication, and formal peer review. Our initial searches resulted in 221 total products, of which 147 met our criteria for inclusion. Across products summarized in the annotated bibliography, broad-scale habitat characteristics, behavior or demographics, site-scale habitat characteristics, habitat selection, and population estimates or targets were the most commonly addressed management topics. The online version of this bibliography, which will be available on the Science for Resource Managers tool (https://apps.usgs.gov/science-for-resource-managers), will be searchable by topic, location, and year, and will include links to each original publication. The studies compiled and summarized here may inform planning and management actions that seek to maintain and restore sagebrush landscapes and GRSG populations across the GRSG range.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231082","usgsCitation":"Teige, E.C., Maxwell, L.M., Jordan, S.E., Rutherford, T.K., Dietrich, E.I., Samuel, E.M., Stoneburner, A.L., Kleist, N.J., Meineke, J.K., Selby, L.B., Foster, A.C., and Carter, S.K., 2023, Annotated bibliography of scientific research on greater sage-grouse published from October 2019 to July 2022 (ver. 1.1, November 2023): U.S. Geological Survey Open-File Report 2023–1082, 122 p., https://doi.org/10.3133/ofr20231082.","productDescription":"ix, 122 p.","onlineOnly":"Y","ipdsId":"IP-152382","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":422491,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1082/versionHist.txt","size":"12.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2023-1082 version history"},{"id":422190,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1082/ofr20231082.pdf","text":"Report","size":"5.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1082"},{"id":422189,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1082/coverthb2.jpg"},{"id":422620,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231082/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1082"},{"id":422537,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1082/images"},{"id":422538,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1082/ofr20231082.xml"}],"edition":"Version 1.0: October 27, 2023; Version 1.1: November 13, 2023","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The Elk Hills 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 (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 groundwater resources near areas of oil and gas development in California, including (1) the location of groundwater resources near oil fields; (2) the proximity of oil and gas operations to groundwater, and the geologic materials between them; (3) evidence (or lack of 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 near the administrative boundary of the Elk Hills Oil Field in the southern San Joaquin Valley about 6 miles northeast of Taft, California (California Department of Water Resources, 2020; fig. 1). Data collected at the Elk Hills multiple-well monitoring site (ELKH) provide information about the geology, hydrology, geophysical properties, and water quality of the aquifer system, thus enhancing the understanding of relations between adjacent groundwater and the Elk Hills Oil Field in an area where groundwater data are limited, particularly at different depths in the aquifer. This report presents construction information for the ELKH and initial geohydrologic data collected from the site. Similar sites installed on the east side of the Lost Hills Oil Field, on the east side of the North and South Belridge Oil Fields, and within the Poso Creek Oil Field were described by Everett and others (2020a, b, 2023).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231073","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Everett, R.R., Gillespie J.M., Shepherd, M.M., Morita, A.Y., Bobbitt, M., Kohel, C.A., and Warden, J.G., 2023, Multiple-well monitoring site adjacent to the Elk Hills Oil Field, Kern County, California: U.S. Geological Survey Open-File Report 2023–1073, 11 p., https://doi.org/10.3133/ofr20231073.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-148290","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499485,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115583.htm","linkFileType":{"id":5,"text":"html"}},{"id":422144,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231073/full"},{"id":422143,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1073/images"},{"id":422141,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1073/ofr20231073.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":422140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1073/covrthb.jpg"},{"id":422142,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1073/ofr20231073.xml"}],"country":"United States","state":"California","county":"Kern County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.35,\n 35.2\n ],\n [\n -119.35,\n 35.1\n ],\n [\n -119.1,\n 35.1\n ],\n [\n -119.1,\n 35.2\n ],\n [\n -119.35,\n 35.2\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 publication is a preliminary map and geodatabase of the coseismic surface rupture and other coseismic features generated from the August 9, 2020, Mw 5.1 earthquake near Sparta, North Carolina. Geologic mapping facilitated by analysis of post-earthquake quality level 0 to 1 lidar, document the coseismic surface rupture, named the Little River fault, and other coseismic features. The Little River fault is traced for approximately 4 kilometers and cuts the regional Paleozoic fabric (mean foliation, 063°/57°), and the dominant strike of joint sets are 0°–10°, 130°–150°, and 320°–340°. Individual fault strands occur in an en echelon pattern within an approximately 10-meter-wide zone. Trenches across the Little River fault document a thrust fault oriented 110°/45° with at least 10 centimeters (cm) of displacement. The Little River fault is marked by a flexure or scarp with a height of 5–30 cm and a local maximum height of 50 cm. Southwest-side-up displacement is consistent along the fault and indicates thrust kinematics. The strike of the Little River fault changes from 110° to 130° near Duncan Farm where it crosses Chestnut Grove Church Road (NC Rt. 1426). Although the surface expression of the fault terminates and (or) is imperceptible at both ends, deformation is still clear in residual surface maps showing the change between pre- and post-earthquake lidar elevations. Other coseismic features documented are rockfalls, ground cracks, fissures, lateral spreading on a sandbar, and mass-wasting scarps; several possible faults that were identified from lidar analyses strike E-W and oblique to the Little River fault.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231074","usgsCitation":"Merschat, A.J., and Carter, M.W., 2023, Preliminary map of the surface rupture from the August 9, 2020, Mw 5.1 earthquake near Sparta, North Carolina—The Little River fault and other possible coseismic features: U.S. Geological Survey Open-File Report 2023–1074, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20231074.","productDescription":"Sheet: 47.89 x 19.47 inches; Data Release","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-144102","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":421654,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S5PGIH","text":"USGS data release","linkHelpText":"Database for the preliminary map of the surface rupture from the August 9, 2020, Mw 5.1 earthquake near Sparta, North Carolina—The Little River fault and other possible coseismic features"},{"id":421652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1074/coverthb.jpg"},{"id":421653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1074/ofr20231074.pdf","text":"Report","size":"106 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1074"},{"id":499788,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115507.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"North Carolina","city":"Sparta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.18690346012897,\n 36.54364449287644\n ],\n [\n -81.18690346012897,\n 36.472458202284926\n ],\n [\n -81.09177792830289,\n 36.472458202284926\n ],\n [\n -81.09177792830289,\n 36.54364449287644\n ],\n [\n -81.18690346012897,\n 36.54364449287644\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Rattlesnake Knoll is a small, 30-meter-high mound of igneous breccia in the center of Spring Valley, east-central Nevada. In the past, researchers have disagreed as to whether the unusual-looking outcrop is intrusive or volcanic. The breccia possesses a normal magnetic polarity, but this is not apparent in aeromagnetic survey data. These data instead show that the knoll lies within a small aeromagnetic low that partially overlaps the extent of a small gravity high. The small gravity anomaly associated with the knoll, combined with an initial, limited ground magnetic survey taken at the knoll, indicates that the knoll rocks extend northward in the subsurface. A second, more extensive ground magnetic traverse was also done north of the knoll. Taking into consideration these new survey data and preexisting data, a two and one-half dimensional modeling program based on Webring (1985) was used to produce a geophysical model that accounts for gravity and magnetic properties, satisfies available geologic information, and conforms to current estimates of basin thickness. This model and the field observations support the interpretation that the knoll consists of gently west-dipping beds of Tertiary volcanic flow breccia, mudflow breccia, and conglomerate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231002","usgsCitation":"Mankinen, E.A., Rowley, P.D., and McKee, E.H., 2023, The enigmatic Rattlesnake Knoll, Spring Valley, east-central Nevada—A geophysical perspective: U.S. Geological Survey Open-File Report 2023–1002, 13 p., https://doi.org/10.3133/ofr20231002.","productDescription":"Report: vi, 13 p.; Data Release","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-133281","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":435149,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WL97XY","text":"USGS data release","linkHelpText":"Ground magnetic data, Spring Valley, White Pine County, Nevada"},{"id":421859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1002/covrthb_.jpg"},{"id":421860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1002/ofr20231002.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":499729,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115506.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nevada","otherGeospatial":"Spring Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.36,\n 39.06\n ],\n [\n -114.36,\n 39.00\n ],\n [\n -114.24,\n 39.00\n ],\n [\n -114.24,\n 39.06\n ],\n [\n -114.36,\n 39.06\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Anadromous fish returning to the lower American River are restricted to 36 kilometers of free-flowing river between Nimbus Dam and American River’s confluence with the Sacramento River, California. Salmon in the American River provide an important freshwater recreational fishery. However, annual salmon production in the American River in recent years has been low relative to the mid-1990s (Surface Water Resources, Inc., 2001). To investigate the low production of fall-run Chinook salmon (Oncorhynchus tshawytscha), the Bureau of Reclamation requested that the U.S. Geological Survey apply the Stream Salmonid Simulator (S3) model to the population of fall-run Chinook salmon on the American River.
The American River was chosen among seven candidate Sacramento Basin rivers for S3 application. The American River was selected because of its management and public interest, recently low anadromous fish production, and rich time series of key demographic data needed for S3 application. Data that were not available, however, were empirical estimates on juvenile salmon habitat suitability in the American River. Therefore, a large component of applying S3 to the American River was devoted to the estimation of juvenile salmon habitat suitability and capacity. This entailed snorkeling the lower American River for 3 weeks in March 2021 during the early out-migration period for juvenile Chinook salmon. These efforts were fruitful and showed that the typically small fish (<55 millimeters) in the American River preferred much shallower depths than predicted by habitat suitability criteria derived from the literature for this population. Having empirical estimates on juvenile salmon in the American River provided a solid foundation from which to simulate the population using the S3 model.
The S3 model is a spatially explicit population model that runs on a daily time step to simulate redd superimposition, egg maturation, fry emergence and the subsequent growth, survival, and emigration of juvenile Chinook salmon from the river. The key features of this model relevant to this report include (1) a temperature-dependent bioenergetics model driving daily growth rates; (2) density-dependent dynamics that are influenced by the effect of flow on suitable habitat area; and (3) within-year habitat, river flow, and water temperature effects specific to spawning, egg incubation, and fry, parr, and smolt life stages. We used estimates of spawning escapement and geo-referenced redd locations to quantify the spatial and temporal distribution of female spawners for brood years 2014–19. These estimates of female spawners initiate the simulation of each year’s juvenile salmon emergence and emigration over a spatial domain extending from Nimbus Dam to the river’s confluence with the Sacramento River.
Using weekly estimates of juvenile salmon abundance and size (fork length) that passed the Watt Avenue fish trap (river kilometer 14.7), we calibrated the S3 model by estimating three key demographic parameters for each year, y: (1) Sy, the average daily survival probability, (2) M0y, the intercept for density-dependence in movement, representing the average daily probability of remaining in a habitat at zero abundance, and (3) Cy, the average daily proportion of maximum consumption. These parameters were obtained by minimizing the Mallow’s distance (Lupu and others, 2017) between distributions of weekly abundances and sizes of fish at the traps and weekly simulated abundances and sizes (by S3). Investigation of model fit showed excellent agreement between simulated annual abundances and the abundance of fish passing the fish trap. However, when we compared weekly abundances at the fish trap, S3 under-predicted peaks and over-predicted troughs in the time series of weekly abundances at the fish trap. Thus, some unknown within-year effects have yet to be identified and incorporated in the S3 model. Identifying these important effects and incorporating them in the S3 model would help explain the lack of fit between estimated and simulated weekly abundances.
We estimated parameters for 6 years that included a wide range of female spawner abundances (3,057–10,753) and water year types (Critical–Wet). We contrast our estimated parameters to the corresponding number of female spawners and the water year type for the Sacramento Valley. By happenstance, years having higher annual spawner abundances concurred with Critical to Dry water year types. Estimates of survival trended lower with higher spawner abundances and Critical to Dry conditions. In contrast, the extremely wet water year of 2017 had the lowest M0y, suggesting less density-dependence in fish movement, and the lowest Cy, suggesting lower average consumption in this year. When this high-flow year was excluded, a trend towards higher probabilities of fish remaining in a habitat at low abundance and lower proportions of maximum consumption was apparent from Critical to Wet conditions, but only 5 years of data were included. Except for 2017, daily proportions of maximum consumption were relatively high (Cy > 0.83), suggesting that fish were feeding at reasonably high proportions relative to the expected maximum consumption as defined by the “Wisconsin” bioenergetics model (Stewart and Ibarra, 1991).
Survival estimates from fry emergence to outmigration at the Sacramento River confluence were generally low when integrated over time. The highest daily survival probability was Sy = 0.93 in 2019, or 50 percent total mortality after 10 days. In contrast, our lowest daily survival probability was Sy = 0.74 in 2015, or 95 percent total mortality after 10 days. Consequently, even our highest estimated daily survival probability might be considered low. This is especially true given that Sy was estimated over a relatively short distance (<14.7 kilometers) from emergence to the Watt Avenue fish trap. Several factors, including our assumed and relatively high daily egg survival rate of 0.9975, could influence juvenile survival estimates. For example, an egg survival rate of 0.9975 results in 3-percent total mortality after 10 days. Egg mortality estimates used in S3 calibration were approximated from egg survivorship studies in the Yakima River, Washington (Johnson and others, 2012), and remains one of the greater uncertainties in S3 when estimating survival across life stages. By including bona fide estimates of egg survival in S3 simulations, the validity of the S3’s current daily egg survival rate could be assessed specifically for the American River. Tagging studies also could provide S3 with direct estimates of juvenile survival and movement; survival during egg incubation then could be estimated indirectly via model fitting.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231060","collaboration":"Prepared in cooperation with U.S. Bureau of Reclamation","usgsCitation":"Plumb, J.M., Perry, R.W., Hatton, T.W., Smith, C.D., and Hannon, J.M., 2023, Application of the Stream Salmonid Simulator (S3) model to assess fall Chinook salmon (Oncorhynchus tshawytscha) production in the American River, California: U.S. Geological Survey Open-File Report 2023–1060, 35 p., https://doi.org/10.3133/ofr20231060.","productDescription":"ix, 35 p.","onlineOnly":"Y","ipdsId":"IP-141661","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":421858,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1060/ofr20231060.XML"},{"id":421857,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1060/images"},{"id":421856,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231060/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1060"},{"id":421855,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1060/ofr20231060.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1060"},{"id":421854,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1060/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"American River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5064051133351,\n 38.727216763718815\n ],\n [\n -121.5064051133351,\n 38.523370433079805\n ],\n [\n -121.11639046489739,\n 38.523370433079805\n ],\n [\n -121.11639046489739,\n 38.727216763718815\n ],\n [\n -121.5064051133351,\n 38.727216763718815\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
Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 926A
Reston, VA 20192
The San Francisco Bay supports thousands of breeding waterbirds annually and hosts large populations of American avocets (Recurvirostra americana), black-necked stilts (Himantopus mexicanus), and Forster’s terns (Sterna forsteri). These three species have relied largely on former commercial salt ponds in South San Francisco Bay, which provide wetland foraging habitat and island nesting habitat. The South Bay Salt Pond Restoration Project is in the process of restoring 50–90 percent of 15,100 acres of these former salt ponds to tidal marsh and tidal mudflats. Although this restoration is expected to have numerous benefits, including providing habitat for tidal wetland-dependent species, improving water quality, buffering against storm surge, and protecting inland areas from sea level rise, the reduction in former salt pond habitat and nesting islands may negatively affect breeding waterbirds. To address the reduction in former salt pond habitat available to waterbirds, the South Bay Salt Pond Restoration Project also includes enhancements to remaining pond habitat, such as the construction of new islands for nesting. Moreover, the South Bay Salt Pond Restoration Project follows an adaptive management plan in which waterbird response to the changing landscape is monitored over time to ensure that existing breeding waterbird populations are maintained. In this report, we provide results of waterbird nest monitoring in South San Francisco Bay during the 2022 breeding season and present these results in the context of annual nest monitoring in South San Francisco Bay since 2005. Overall, nest abundance in 2022 remained at or near 18-year lows for American avocets (176 nests) and black-necked stilts (97 nests), but Forster’s tern nest abundance (1,727 nests) was at an 18-year high, reversing historically low abundance observed during 2015–2017. In 2022, there were only 6 American avocet, 4 black-necked stilt, and 4 Forster’s tern major colony nesting sites, which is down from annual averages of 12.4, 6.6, and 6.6 observed during 2005–2009. Nest success (30 percent for American avocets, 29 percent for black-necked stilt, and 53 percent for Forster’s terns) was below the 2005–2007 baseline values established for the South Bay Salt Pond Restoration Project. Average egg-hatching success (98 percent, 100 percent, and 90 percent), and clutch sizes (3.68, 3.70, and 2.63 eggs) of American avocets, black-necked stilts, and Forster’s terns, respectively, were similar to values observed during 2005–2010. All three species displayed notable shifts in nest initiation dates in 2022, with American avocets and Forster’s terns nesting 10–11 days earlier and black-necked stilts nesting 10 days later than during 2005–2010. Finally, the enhanced, managed ponds with newly constructed islands (Ponds A16 and SF2) supported 86 percent of all the Forster’s tern nests recorded in South San Francisco Bay in 2022, which is the first time these managed ponds have hosted such a substantial number of tern nests.
","language":"English","publisher":"U.S. Geological Center","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231067","collaboration":"Prepared in cooperation with California State Coastal Conservancy, California Wildlife Foundation, California Department of Fish and Wildlife, U.S. Fish and Wildlife Service, and South Bay Salt Pond Restoration Project","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Ackerman, J.T., Hartman, C.A., and Herzog, M., 2023, Monitoring nesting waterbirds for the South Bay Salt Pond Restoration Project—2022 breeding season: U.S. Geological Survey Open-File Report 2023–1067, 25 p., https://doi.org/10.3133/ofr20231067.","productDescription":"vi, 25 p.","numberOfPages":"25","onlineOnly":"Y","ipdsId":"IP-151077","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":421402,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231067/full"},{"id":421401,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1067/images"},{"id":421400,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1067/ofr20231067.xml"},{"id":421398,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1067/covrthb.jpg"},{"id":421399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1067/ofr20231067.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"South Bay Salt Pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11258522212694,\n 37.585319000832044\n ],\n [\n -122.11258522212694,\n 37.361346093418206\n ],\n [\n -121.87569252193163,\n 37.361346093418206\n ],\n [\n -121.87569252193163,\n 37.585319000832044\n ],\n [\n -122.11258522212694,\n 37.585319000832044\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Integrating recent scientific knowledge into management decisions supports effective natural resource management and can lead to better resource outcomes. However, finding and accessing scientific knowledge can be time consuming and costly. To assist in this process, the U.S. Geological Survey is creating a series of annotated bibliographies on topics of management concern for western lands. Previously published reports introduced a methodology for preparing annotated bibliographies to facilitate the integration of recent, peer-reviewed science into resource management decisions. Therefore, relevant text from those efforts is reproduced here to frame the presentation. Centrocercus minimus (Gunnison sage-grouse; hereafter GUSG) has been a focus of scientific investigation since the early 2000s. The U.S. Fish and Wildlife Service listed GUSG as threatened under the Endangered Species Act in 2014 because of declining populations and increasing habitat loss. The U.S. Fish and Wildlife Service, Bureau of Land Management, and Colorado Parks and Wildlife have sought to increase the conservation of this species by adapting management and recovery plans to reduce threats and increase population resiliency. GUSG are studied less than the closely related Centrocercus urophasianus (greater sage-grouse); however, research efforts have recently increased to understand the life history, genetics, and habitat suitability of this sagebrush-obligate species. We compiled and summarized peer-reviewed journal articles, data products, and formal technical reports (such as U.S. Department of Agriculture Forest Service General Technical Reports and U.S. Geological Survey Open-File Reports) on GUSG, published between January 2005 and September 2022. We first systematically searched three reference databases and three government databases using the following search phrases: “Gunnison sage-grouse” or “lesser sage-grouse” or “Gunnison grouse” or “Gunnison sage grouse” or “lesser sage grouse” or “Centrocercus minimus.” We refined the initial list of products by removing (1) duplicates, (2) publications that were not published as research, data products, or scientific review articles in peer-reviewed journals or as formal technical reports, and (3) products that did not have GUSG as a research focus or products that did not present new data or findings about GUSG. We summarized each product using a consistent structure (background, objectives, methods, location, findings, and implications) and identified the management topics (for example, population estimates or targets, habitat, and management efforts) addressed by each product. We also noted which publications included new geospatial data. The review process for this annotated bibliography included two initial internal colleague reviews of each summary, requesting input on each summary from an author of the original publication, and a formal peer review. Our initial searches resulted in 80 total products, of which 63 met our criteria for inclusion of which 53 were products that had not been summarized before. Across products summarized in the annotated bibliography, broad-scale habitat characteristics; population estimates or targets; behavior or demographics; and genetics were the most commonly addressed management topics. The bibliographies are available on the Science for Resource Managers tool (https://apps.usgs.gov/science-for-resource-managers) and are searchable by topic, location, and year, and the search tool includes links to each original publication. The studies compiled and summarized in this annotated bibliography may inform planning and management actions that seek to maintain and restore sagebrush landscapes and GUSG populations across the GUSG range.
","publisher":"U S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231079","usgsCitation":"Maxwell, L.M., Teige, E.C., Jordan, S.E., Rutherford, T.K., Samuel, E.M., Selby, L.B., Foster, A.C., Kleist, N.J., and Carter, S.K., 2023, Annotated bibliography of scientific research on Gunnison sage-grouse published from January 2005 to September 2022: U.S. Geological Survey Open-File Report 2023–1079, 52 p., https://doi.org/10.3133/ofr20231079.","productDescription":"vii, 52 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":421428,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231079/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1079"},{"id":421397,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1079/ofr20231079.xml"},{"id":421355,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1079/ofr20231079.pdf","text":"Report","size":"2.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1079"},{"id":421396,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1079/images"},{"id":421354,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1079/coverthb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.12083328575649,\n 39.47396881795231\n ],\n [\n -109.12083328575649,\n 36.98898041947241\n ],\n [\n -104.41868484825648,\n 36.98898041947241\n ],\n [\n -104.41868484825648,\n 39.47396881795231\n ],\n [\n -109.12083328575649,\n 39.47396881795231\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
As of 2016, the U.S. Geological Survey (USGS) Fundamental Science Practices require data management plans (DMPs) for all USGS and USGS-funded research. The USGS Science Data Management Branch of the Science Analytics and Synthesis Program has been working to help the USGS (Bureau) meet this requirement. However, USGS researchers still encounter common data management-related challenges that may be reduced or eliminated by better planning. In 2021, USGS staff were given a series of surveys aimed to better understand current data management planning practices, perceptions, and needs. The survey results indicated that adoption and integration of data management planning and DMPs into USGS research project workflows are broad, if inconsistent, across USGS Science Centers and programs. The USGS Science Data Management Branch can help improve clarity and guidance on the purpose, intended audience, content, workflows, and evaluation processes for DMPs. It would also be beneficial to provide additional supporting cyberinfrastructure to support DMP activities. Survey responses indicated it would be beneficial for the Science Data Management Branch to develop a strategy, other than through DMPs, for teaching and encouraging good data management practices. Although these surveys were an opportunity for USGS staff to provide feedback on their experiences, the surveys may also have revealed the desire for more frequent evaluations, cross-disciplinary communication, and training on research data management and DMP development and integration, in the context of USGS policy, Fundamental Science Practices requirements, and overall Bureau expectations. Data management-related roles such as data manager or steward, information technologist, and repository manager may need to be formally recognized as skilled professional career positions within the Bureau. At a minimum, the best practice for USGS would be to create and maintain DMPs as living documents, integrated with existing systems that are broadly accessible to all stakeholders, and include quantitatively measurable benefits tied directly to a clearly defined purpose.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231069","programNote":"Science Synthesis, Analysis, and Research Program","usgsCitation":"Langseth, M.L., Sellers, E.A., Donovan, G.C., and Liford, A.N., 2023, Assessing the value and usage of data management planning and data management plans within the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2023–1069, 44 p., https://doi.org/10.3133/ofr20231069.","productDescription":"Report: vi, 44 p.; 6 Appendixes; Data Release","onlineOnly":"Y","ipdsId":"IP-139788","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":421261,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91WKCA3","text":"USGS data release","description":"Data release associated with OFR 2023-1069","linkHelpText":"U.S. Geological Survey 2021 Data Management Planning Survey Results and Analyses"},{"id":422160,"rank":12,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231069/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1069"},{"id":421342,"rank":11,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069.xml"},{"id":421254,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix3.pdf","text":"Appendix 3","size":"180 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2023-1069 Appendix 3","linkHelpText":"- Data Management Planning Questionnaire for Center Directors"},{"id":421255,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix4.pdf","text":"Appendix 4","size":"168kB","description":"OFR 2023-1069 Appendix 4","linkHelpText":"- Data Management Planning Questionnaire for Program Coordinators and Bureau Approving Officials Appendix"},{"id":421257,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix6.pdf","text":"Appendix 6","size":"88 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 6","linkHelpText":"- Interview Questions for Data Managers"},{"id":421219,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix1.pdf","text":"Appendix 1","size":"184 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 1","linkHelpText":"- Data Management Planning Questionnaire for Researchers"},{"id":421253,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix2.pdf","text":"Appendix 2","size":"184 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 2","linkHelpText":"- Data Management Planning Questionnaire for Data Managers and Information Technologists"},{"id":421341,"rank":10,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1069/images"},{"id":421256,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix5.pdf","text":"Appendix 5","size":"108 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 5","linkHelpText":"- Interview Questions for Researchers"},{"id":421217,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1069/coverthb.jpg"},{"id":421218,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069.pdf","text":"Report","size":"1.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069"}],"contact":"Director, Science Analytics and Synthesis Program
U.S. Geological Survey
P.O. Box 25046, Mail Stop 302
Denver, CO 80225
The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 2 (April–June) of 2023. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was a Landsat 8 Thermal Infrared Sensor (TIRS) Scene Select Mechanism (SSM) excursion anomaly. On April 21, 2023, a TIRS SSM excursion error flag was indicated in telemetry during a calibration activity when the SSM encoder was powered on and the mirror was between the nadir position and the deep space position. An initial recovery plan indicated the SSM was moving erratically, so the instrument was put into a safe state for additional troubleshooting. A second recovery plan was developed and successfully executed on April 23, 2023. Additional information about the Landsat 8 TIRS SSM excursion anomaly is available at https://www.usgs.gov/landsat-missions/news/landsat-8-level-1-product-processing-resumes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231075","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T.Z., Shaw, J.L., Denevan, A., Franks, S., Ruslander, K., Micijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., Miller, J., and Ding, L., 2023, ECCOE Landsat quarterly Calibration and Validation report—Quarter 2, 2023: U.S. Geological Survey Open-File Report 2023–1075, 39 p., https://doi.org/10.3133/ofr20231075.","productDescription":"Report: vii, 39 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154779","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":421208,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":421207,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1075/images/"},{"id":421206,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1075/ofr20231075.XML","linkFileType":{"id":8,"text":"xml"}},{"id":421209,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231075/full","linkFileType":{"id":5,"text":"html"}},{"id":421204,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1075/coverthb.jpg"},{"id":421205,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1075/ofr20231075.pdf","text":"Report","size":"126 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1075"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198