Establishing and enhancing pollinator habitat to support declining bee populations is a national goal within the United States. Pollinator habitat is often created through incentive-based conservation programs, and the inclusion of cost-effective forbs within the habitat design is a critical component of such programs. U.S. Geological Survey research from 2015 to 2019 identified forb species that (1) were preferred or highly visited by bees, (2) demonstrated high rates of establishment success, and (3) could be purchased at reduced cost. In this report, we enhance this past research by identifying common physical characteristics and functional traits of these cost-effective forbs so that land managers may have easy access to information on cost-effective forbs for new conservation plantings. This report highlights 22 forb species that were preferred and (or) highly visited by honey bees (Apis mellifera Linnaeus) or wild bees. Of the species evaluated for cost-effectiveness, most had less than average seed cost and greater than average apparent establishment rates. Several forb species were not considered cost effective because of bee avoidance, poor establishment, or high seed cost. Most forbs preferred or highly visited by bees were from the Asteraceae family and demonstrated a wide range of flower color. Forb species represented a range of wetland statuses from facultative wetland to upland, indicating that wetland and nonwetland habitat types represent areas where important floral resources for bees exist. Many forb species were in bloom from June to September, but our results showcase forb species that could be used in conservation projects seeking early- (June–July) or late-season (August–September) floral resources for pollinators.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221114","collaboration":"Prepared in cooperation with the Farm Service Agency, Natural Resources Conservation Service, and Honey Bee Health Coalition","usgsCitation":"Simanonok, S.C., and Otto, C.R.V., 2023, Identifying physical characteristics and functional traits of forbs preferred or highly visited by bees in the Prairie Pothole Region: U.S. Geological Survey Open-File Report 2022–1114, 10 p., https://doi.org/10.3133/ofr20221114.","productDescription":"Report: v, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-138617","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":411280,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1114/coverthb.jpg"},{"id":411284,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O61BCB","text":"USGS data release","linkHelpText":"Dataset—Plant and bee transects in the Northern Great Plains, USA, 2015–2019"},{"id":411281,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1114/ofr20221114.pdf","text":"Report","size":"2.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1114"},{"id":411282,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1114/ofr20221114.XML"},{"id":411283,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1114/images"},{"id":411290,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221114/full","text":"Report"}],"country":"United States","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.712890625,\n 43.58039085560784\n ],\n [\n -94.74609375,\n 41.50857729743935\n ],\n [\n -92.548828125,\n 41.77131167976407\n ],\n [\n -92.900390625,\n 43.32517767999296\n ],\n [\n -94.04296874999999,\n 45.460130637921004\n ],\n [\n -95.537109375,\n 48.45835188280866\n ],\n [\n -96.85546875,\n 49.61070993807422\n ],\n [\n -96.767578125,\n 50.401515322782366\n ],\n [\n -97.55859375,\n 51.069016659603896\n ],\n [\n -97.998046875,\n 50.51342652633956\n ],\n [\n -99.140625,\n 51.12421275782688\n ],\n [\n -99.931640625,\n 51.45400691005982\n ],\n [\n -102.216796875,\n 52.696361078274485\n ],\n [\n -104.501953125,\n 54.213861000644926\n ],\n [\n -107.22656249999999,\n 54.41892996865827\n ],\n [\n -111.533203125,\n 55.57834467218206\n ],\n [\n -114.78515624999999,\n 54.97761367069628\n ],\n [\n -115.13671875,\n 52.74959372674114\n ],\n [\n -115.13671875,\n 50.90303283111257\n ],\n [\n -113.90625,\n 49.095452162534826\n ],\n [\n -111.796875,\n 48.22467264956519\n ],\n [\n -110.56640625,\n 48.69096039092549\n ],\n [\n -109.16015624999999,\n 48.45835188280866\n ],\n [\n -107.40234375,\n 48.80686346108517\n ],\n [\n -105.380859375,\n 48.980216985374994\n ],\n [\n -101.77734374999999,\n 47.989921667414194\n ],\n [\n -100.986328125,\n 47.754097979680026\n ],\n [\n -100.37109375,\n 46.800059446787316\n ],\n [\n -100.546875,\n 45.460130637921004\n ],\n [\n -99.66796875,\n 43.96119063892024\n ],\n [\n -98.96484375,\n 43.45291889355465\n ],\n [\n -96.85546875,\n 42.8115217450979\n ],\n [\n -95.712890625,\n 43.58039085560784\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
The U.S. Geological Survey performed subsurface and geophysical site characterization of the irrigated four-plex baseball field in the Langford Valley–Irwin Groundwater Subbasin, as part of a research study in cooperation with the U.S. Environmental Protection Agency, the Agricultural Research Service, and the Fort Irwin National Training Center, California. To help meet future demands, the Fort Irwin National Training Center is evaluating the efficacy of gravity-fed drywells to enhance storm-water recharge into the Langford Valley–Irwin Groundwater Subbasin by bypassing fine-grained, less permeable deposits between land surface and the water table. The amount, rate, and location of recharge beneath an irrigated baseball field in the groundwater basin at the Fort Irwin National Training Center is not well understood, so data were collected using physical and geophysical techniques to characterize subsurface materials, geologic controls, and the vertical movement of water through the unsaturated zone to the water table near the drywell at the Fort Irwin National Training Center. Based on the data collected and interpreted from these techniques, several fine-grained deposits were identified. Although these deposits appear to impede the downward movement of water through the unsaturated zone locally, they are not laterally continuous, and water appears to continue to move downward when it reaches the edges of the deposits. These data will help managers evaluate recharge at the site and determine if the use of gravity-fed drywells enhances recharge from surface runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221118","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","programNote":"U.S. Environmental Protection Agency","usgsCitation":"Densmore, J.N., Dick, M.C., Groover, K.D., Ely, C.P., and Brown, A., 2022, Characterization of subsurface conditions and recharge at the irrigated four-plex baseball field, Fort Irwin National Training Center, California, 2018–20: U.S. Geological Survey Open File Report 2022-1118, 13 p., https://doi.org/10.3133/ofr20221118","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-129107","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499727,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114180.htm","linkFileType":{"id":5,"text":"html"}},{"id":411259,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1118/ofr20221118.XML"},{"id":411257,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1118/images"},{"id":411255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1118/coverthb.jpg"},{"id":411256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1118/ofr20221118.pdf","text":"Report","size":"3.61 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","city":"Fort Irwin","otherGeospatial":"Fort Irwin National Training Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.69261791592291,\n 35.26487666931442\n ],\n [\n -116.69251062756216,\n 35.26470146901906\n ],\n [\n -116.69238188152951,\n 35.26459634865991\n ],\n [\n -116.69212438946424,\n 35.264447427917574\n ],\n [\n -116.69163086300526,\n 35.264359827352905\n ],\n [\n -116.69129826908738,\n 35.26422842632836\n ],\n [\n -116.69092275982544,\n 35.263983143846076\n ],\n [\n -116.68835856800732,\n 35.2661468601287\n ],\n [\n -116.6903755891864,\n 35.26772362102348\n ],\n [\n -116.69260718708664,\n 35.265822744364684\n ],\n [\n -116.69281103497185,\n 35.265752665110384\n ],\n [\n -116.69268228893922,\n 35.26531466839623\n ],\n [\n -116.69261791592291,\n 35.26487666931442\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
https://www.usgs.gov/centers/ca-water/
Contact Pubs Warehouse
https://pubs.er.usgs.gov/contact
Historical observations by the New York City Department of Environmental Protection (NYCDEP) indicate that the Rondout pressure tunnel has been leaking in the vicinity of the hamlet of High Falls, New York. In the 74 days from November 11, 2019, to January 23, 2020, NYCDEP shut down and partially dewatered the pressure tunnel for inspection and repairs. On November 5–7, 2019 (during normal tunnel operations), and on January 21–22, 2020 (when the tunnel was shut down), the U.S. Geological Survey used a network of 31 groundwater wells to collect water-level elevations and determine the potentiometric surface of the bedrock aquifer adjacent to the Rondout pressure tunnel. When the tunnel was fully pressurized during normal operations, water levels indicated a two-mile-long groundwater mound which trended northeastward, approximately along the regional strike of the bedrock units. The mound ranged in elevation from 250 to 300 feet (ft) above the North American Vertical Datum of 1988 and extended from 1,500 ft southwest of a suspected leak at the Rondout pressure tunnel to about 8,500 ft northeast of the possible leak. During the 74-day shutdown, during which the aqueduct was nonoperational, this groundwater mound decreased in magnitude and extent as it reverted to equilibrium conditions. This resulted in a flattening of the potentiometric surface, represented by two remnant groundwater plateaus.
Water-level differences were calculated for wells that may be affected by potential tunnel leakage to determine the influence on the local bedrock aquifer. The five largest water-level differences (77, 61, 49, 42, and 41 ft) occurred in wells that were generally aligned with the northeastward trend of regional bedrock strike; these wells may penetrate the karstic Helderberg Group bedrock unit. Near the suspected tunnel leak, the Helderberg Group overlies the Binnewater Sandstone and the High Falls Shale, both of which produced substantial groundwater inflows during the construction of the Rondout pressure tunnel. Water levels in wells penetrating the Shawangunk Formation just east of Rondout Creek, where the unit is in contact with the High Falls Shale, and in wells penetrating the Esopus Shale, which is adjacent to the Helderberg Group and northwest of the tunnel leak, may be affected by tunnel leakage. It is unclear if water levels in a well 9,000 ft northwest of the suspected tunnel leak are influenced by the tunnel leakage, by another source of artificial recharge, or by both. This well penetrates the Onondaga Limestone in the northwestern part of the study area. An unconsolidated aquifer composed of stratified gravel, sand, silt, and clay overlies the limestone bedrock in this part of study area―additional study is required to determine if this unconsolidated aquifer is affected by tunnel leakage.
Robert Francis Breault, Center Director
New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
Cross-correlation waveforms of seismic noise in the Seattle basin, Washington, were analyzed to determine the group velocities of surface waves and constrain the shear-wave velocity (VS) for depths less than about 2 kilometers (km). Twenty broadband seismometers were deployed for about 3 weeks in three dense arrays separated by about 5 km, with minimum intra-array station spacing of about 0.5 km. Cross correlations of only 9 days of noise recordings produced Green’s functions at periods of 2 to 6 seconds (s) for sites about 5 km apart. Usable noise correlations for shorter periods of 0.5 to 1.0 s were found for sites within the arrays separated by 1 to 2 km. We bandpass filtered the inter- and intra-array cross-correlation waveforms to determine Love-wave group velocities at periods of 0.5 to 6 s for paths within the Seattle basin and at 3 to 5 s for paths crossing the southern edge of the basin. We developed a non-linear inversion program to determine VS profiles that fit the observed group velocities for paths in the basin. We found that these group velocities are well fit by a variety of VS profiles, each with a distinct jump in VS at depths ranging from 0.9 to 1.3 km. This jump in VS is inferred to represent the top of bedrock. The observed group velocities are not matched by models with the top of bedrock at 0.7-km depth or shallower. The group velocities are also fit by a model with no large jumps in VS in depths less than 2.4 km. The VS profile for the middle of the basin from Stephenson and others (2017), with a depth to bedrock of 0.9 km, also adequately fits the group velocity observations, if a velocity gradient is added from 0.05- to 0.1-km depth. The results indicate that short (3-week) deployments of seismometers to record seismic noise may provide useful constraints on the VS of sedimentary basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221108","collaboration":"Prepared in cooperation with the University of Washington","usgsCitation":"Frankel, A., and Bodin, P., 2022, Using seismic noise correlation to determine the shallow velocity structure of the Seattle basin, Washington: U.S. Geological Survey Open-File Report 2022–1108, 13 p., https://doi.org/10.3133/ofr20221108.","productDescription":"vi, 12 p.","onlineOnly":"Y","ipdsId":"IP-140830","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":501842,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114001.htm","linkFileType":{"id":5,"text":"html"}},{"id":410660,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1108/ofr20221108.XML"},{"id":410656,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1108/coverthb.jpg"},{"id":410657,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1108/ofr20221108.pdf","text":"Report","description":"OFR 2022-1108"},{"id":410658,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221108/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1108"},{"id":410659,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1108/images"}],"country":"United States","state":"Washington","city":"Seattle","otherGeospatial":"Seattle Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.45036951581977,\n 47.693059199440825\n ],\n [\n -122.45036951581977,\n 47.51906296781365\n ],\n [\n -122.22524539503297,\n 47.51906296781365\n ],\n [\n -122.22524539503297,\n 47.693059199440825\n ],\n [\n -122.45036951581977,\n 47.693059199440825\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, California 94025
The U.S. Geological Survey’s Grand Canyon Monitoring and Research Center, in coordination with the Glen Canyon Dam Adaptive Management Program, has monitored the geomorphic condition of select archaeological sites along the Colorado River in Grand Canyon using high-resolution terrestrial light detection and ranging (lidar) topographic surveys. Many of these sites are vulnerable to degradation by natural erosional processes. Regulation of the Colorado River by some operations of Glen Canyon Dam has been shown to affect archaeological resources by directly or indirectly causing degradation of site condition. Conversely, some specific operations of Glen Canyon Dam, such as controlled flood releases (termed high flow experiments), can potentially be used to slow or stop erosion at some degraded archaeological sites. Results of monitoring conducted with terrestrial lidar surveys from 2006 to 2010 have been synthesized in previous reports and publications. Here, we present and summarize results of monitoring conducted at 30 archaeological sites within 23 monitoring locations from 2010 to 2020. This report presents a sample of a much larger population of Colorado River archaeological sites in Grand Canyon that are being qualitatively monitored by the National Park Service (NPS). To ensure relevance to the NPS monitoring program, the quantitative high-resolution topographic monitoring presented in this report focused on sites binned by geomorphic context, using two previously published geomorphic classification frameworks to identify important changes in geomorphic condition within archaeological sites that can be related to operations of Glen Canyon Dam. We found that 22 archaeological sites changed within one or both of the previously determined geomorphic classifications, and changes at 21 of those 22 sites were interpreted as a transition to a more degraded geomorphic condition. The monitoring records contained within this report represent the foundation for future monitoring of these and other archaeological sites with high-resolution topographic surveys and change detection. These monitoring results provide benchmarks for managers of cultural resources along the Colorado River in Grand Canyon to assess significant changes to cultural resource integrity, aid in future risk management at these locations, and illustrate methods relevant for assessing geomorphic condition changes within other river valleys.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221097","usgsCitation":"Caster, J., Sankey, J.B., Fairley, H., and Kasprak, A., 2022, Terrestrial lidar monitoring of the effects of Glen Canyon Dam operations on the geomorphic condition of archaeological sites in Grand Canyon National Park, 2010–2020: U.S. Geological Survey Open-File Report 2022–1097, 100 p., https://doi.org/10.3133/ofr20221097.","productDescription":"xii, 100 p.","onlineOnly":"Y","ipdsId":"IP-112281","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501838,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114000.htm","linkFileType":{"id":5,"text":"html"}},{"id":410864,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1097/ofr20221097.pdf","text":"Report","size":"60.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1097"},{"id":410863,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1097/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.94729427966845,\n 36.935208423901784\n ],\n [\n -113.47307709825252,\n 36.935208423901784\n ],\n [\n -113.47307709825252,\n 35.500002816586004\n ],\n [\n -110.94729427966845,\n 35.500002816586004\n ],\n [\n -110.94729427966845,\n 36.935208423901784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
The U.S. Geological Survey (USGS) completed an assessment in 2007 of the undiscovered, technically recoverable, continuous gas potential of Cretaceous–Tertiary coal beds of the onshore areas and State waters of the northern Gulf of Mexico Coastal Plain. The assessment was based on geologic elements including hydrocarbon source rocks, availability of suitable reservoir rocks, and hydrocarbon accumulations in three coalbed gas total petroleum systems (TPSs) identified in the region: (1) the Olmos Coalbed Gas TPS (Upper Cretaceous), (2) the Wilcox Coalbed Gas TPS (Paleocene–Eocene), and (3) the Cretaceous-Tertiary Coalbed Gas TPS. Four continuous assessment units (AUs) were defined within these three TPSs: (1) the Cretaceous Olmos Coalbed Gas AU, (2) the Rio Escondido Basin Olmos Coalbed Gas AU, (3) the Wilcox Coalbed Gas AU, and (4) the Cretaceous-Tertiary Coalbed Gas AU, which was not quantitatively assessed and which includes all other Cretaceous and Tertiary coal beds that are not included in the other AUs.
This USGS assessment estimated a mean of 4.06 trillion cubic feet of undiscovered, technically recoverable, continuous coalbed gas resources in the four AUs that were assessed. Nearly all of the undiscovered continuous gas resources that were estimated (95 percent, or 3.86 trillion cubic feet of gas [TCFG]) were in the Wilcox Coalbed Gas AU. The continuous gas resources resided in coalbed reservoirs. Gas sourced from these coal beds may also occur as conventional accumulations in adjacent or interlayered sandstones that were not included in this assessment of continuous resources. The assessment was conducted via the established USGS methodology for continuous petroleum accumulations and reflects estimates of undiscovered resources based on vertical (nonhorizontal) drilling technology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171167","usgsCitation":"Warwick, P.D., 2022, Geologic assessment of undiscovered gas resources in Cretaceous–Tertiary coal beds of the U.S. Gulf of Mexico Coastal Plain: U.S. Geological Survey Open-File Report 2017–1167, 52 p., https://doi.org/10.3133/ofr20171167.","productDescription":"Report: vi, 52 p.; 3 Appendixes","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-017257","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":501520,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113996.htm","linkFileType":{"id":5,"text":"html"}},{"id":410558,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.er.usgs.gov/publication/ofr20171111","text":"Open-File Report 2017–1111","linkHelpText":"- Geologic assessment of undiscovered conventional oil and gas resources in the Lower Paleogene Midway and Wilcox Groups, and the Carrizo Sand of the Claiborne Group, of the Northern Gulf coast region"},{"id":410555,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167_appendix1.pdf","text":"Appendix 1","size":"165 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Input Data Form for the Cretaceous Olmos Coalbed Gas Assessment Unit (50470281)"},{"id":410985,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20171167/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2017-1167"},{"id":410553,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167.pdf","text":"Report","size":"15.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1167"},{"id":410552,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1167/coverthb.jpg"},{"id":409355,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167.XML"},{"id":409356,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2017/1167/images/"},{"id":410556,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167_appendix2.pdf","text":"Appendix 2","size":"161 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Input Data Form for the Rio Escondido Basin Olmos Coalbed Gas Assessment Unit (53000281)"},{"id":410557,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167_appendix3.pdf","text":"Appendix 3","size":"168 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Input Data Form for the Wilcox Coalbed Gas Assessment Unit (50470381)"}],"country":"United States","otherGeospatial":"U.S. Gulf of Mexico Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.32775336731807,\n 26.212616580411137\n ],\n [\n -81.93279691237665,\n 26.212616580411137\n ],\n [\n -81.3178237043738,\n 38.82626189520937\n ],\n [\n -99.67916662903421,\n 38.491360932976605\n ],\n [\n -102.44654606504763,\n 38.43753817164347\n ],\n [\n -102.40261940733356,\n 36.63809827557699\n ],\n [\n -102.4904727227622,\n 31.785348237738653\n ],\n [\n -99.32775336731807,\n 26.212616580411137\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Program Coordinator, Energy Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Telephone: 703–648–6470
AskEnergyProgram@usgs.gov
The U.S. Geological Survey monitors a suite of intertidal black abalone sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential effect of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, usually annually or biennially. Monitoring resumed in 2001 and has been completed annually since then. Since 2018, the work has been carried out by the U.S. Geological Survey Western Ecological Research Center. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992 and during the next few years, it reduced the population there by more than 99 percent. The species was subsequently listed as endangered under the Endangered Species Act in 2009.
The subject of this report is the 2021 survey of the sites and how the measured population status compares to the long-term data (collected over several decades) at San Nicolas Island. During the last two decades, the total monitored black abalone population at the island has grown approximately ten-fold after the disease related decline, from about 200 to more than 2,000 abalone. Since it was first consistently measured in 2005, the mean distance between adjacent black abalone has decreased substantially from approximately 50 centimeters to less than 15 centimeters, indicating that abalone are close enough together at several of the sites to reproduce successfully. The 2021 counts were the first since 2016 to indicate a possible decline in the monitored population at San Nicolas Island. Although still more than ten times the population counted in 2001, counts on the transects dropped by 13.6 percent from the survey count in 2020. The most significant decline was the loss of 341 abalone, from the previous count of 547, on a transect that since 2002 had the highest count of all 44 transects. Between 2020 and 2021, there were increases and decreases at the sites and the transects at each site. Although the 2021 count was lower than the 2020 count, it was the second highest since 1997. Based on the number of small abalone counted, recruitment rates were similar to most years since 2008 and higher than the rates observed before the population declines resulting from withering syndrome.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221107","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2022, Black Abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2021, annual report: U.S. Geological Survey Open-File Report 2022–1107, 34 p., https://doi.org/10.3133/ofr20221107.","productDescription":"vii, 34 p.","onlineOnly":"Y","ipdsId":"IP-144353","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":410409,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1107/ofr20221107.XML"},{"id":410407,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221107/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1107"},{"id":410408,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1107/images"},{"id":410406,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1107/ofr20221107.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1107"},{"id":410405,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1107/coverthb.jpg"}],"country":"United States","state":"California","county":"Ventura County","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.59425743862556,\n 33.2937160305206\n ],\n [\n -119.59425743862556,\n 33.20294676390226\n ],\n [\n -119.4170269925379,\n 33.20294676390226\n ],\n [\n -119.4170269925379,\n 33.2937160305206\n ],\n [\n -119.59425743862556,\n 33.2937160305206\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This study evaluated carbon dioxide (CO2) injected into water as a possible behavioral stimulant to enhance capture and removal of invasive red swamp crayfish (RSC, Procambarus clarkii [Girard, 1852]) from a retention pond in southeastern Michigan. Objectives of this study were (1) to determine if target CO2 concentrations were attainable within the infested pond and (2) to determine if CO2 treatment was effective to push RSC either towards shorelines or onto dry land, where they could be collected and removed. Carbon dioxide was applied directly into one treatment pond (about [~]2,500 cubic meters) in Novi, Michigan. Two nearby ponds in Livonia, Mich., were used as untreated control ponds. Crayfish removal efficiency was evaluated in all ponds using baited traps and shoreline surveys. Results showed that the CO2 treatment pond reached its target concentration of greater than (>) 200 milligrams per liter (mg/L) of CO2, a benchmark determined from previous laboratory studies, approximately 11 hours after injection started, and maintained concentrations between 200 and 351 mg/L of CO2 for about 2.5 days. During treatment, some emergent crayfish were observed near influent culverts around the pond, which possibly brought about a behavioral response. However, the number of individuals and crayfish observations were minimal and infrequent. Crayfish continued to be removed throughout CO2 treatment with baited traps and perimeter surveys, but differences in catch rates between the treatment and control ponds were not apparent and confounded by a temporal decline in catch rates across all ponds. Overall, this study demonstrated that open-water treatment applications with CO2 are possible, but its effectiveness to enhance RSC removal was unclear because of the limited crayfish observations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221105","collaboration":"Prepared in cooperation with Michigan Department of Natural Resources, Michigan State University, and Auburn University","programNote":"Biological Threats and Invasive Species Research Program","usgsCitation":"Smerud, J., Rivera, J., Johnson, T., Tix, J., Fredricks, K., Barbour, M., Herbst, S., Thomas, S., Nathan, L., Roth, B., Smith, K., Allert, A., Stoeckel, J., and Cupp, A., 2022, Field application of carbon dioxide as a behavioral control method for invasive red swamp crayfish (Procambarus clarkii) in southeastern Michigan water retention ponds: U.S. Geological Survey Open-File Report 2022–1105, 12 p., https://doi.org/10.3133/ofr20221105.","productDescription":"Report: vii, 12 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-138063","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":501841,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113941.htm","linkFileType":{"id":5,"text":"html"}},{"id":410370,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221105/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":410273,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99OUHMV","text":"USGS data release","linkHelpText":"Water quality and atmospheric carbon dioxide data for field application of carbon dioxide during summer 2018 as a behavioral control method for invasive red swamp crayfish (Procambarus clarkii) in southeastern Michigan water retention ponds"},{"id":410272,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1105/images"},{"id":410271,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1105/ofr20221105.XML"},{"id":410270,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1105/ofr20221105.pdf","text":"Report","size":"1.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1105"},{"id":410269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1105/coverthb.jpg"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.44162797914937,\n 42.44723847720684\n ],\n [\n -83.44162797914937,\n 42.42580674596837\n ],\n [\n -83.3843952063379,\n 42.42580674596837\n ],\n [\n -83.3843952063379,\n 42.44723847720684\n ],\n [\n -83.44162797914937,\n 42.44723847720684\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
The Sand Resources Project was established through collaborative agreements between the U.S. Geological Survey (USGS), the Bureau of Ocean Energy Management (BOEM), and the California Ocean Protection Council (OPC) with the purpose of evaluating sand and gravel resources in Federal and California State Waters for potential use in future beach-nourishment projects. Project partners worked in collaboration with California Coastal Sediment Management Workgroup (CSMW) members to define priority study areas for this work based on the potential for finding sand within the broader region and the needs for this sand as shown by beach erosion areas of concern in the adjacent littoral cells. The final study areas were defined to be (1) the San Francisco Littoral Cell, (2) the Oceanside Littoral Cell, and (3) the Silver Strand Littoral Cell.
A two-stage approach was used to assess the study areas. The initial stage was a synthesis of the existing geophysical and sediment-sampling data in each area. This allowed for evaluations of the data availability, data gaps, and general patterns of sediment thickness and grain size. This synthesis was published in a separate USGS open-file report (Warrick and others, 2022). The findings from this assessment were used to refine study area boundaries and develop sampling plans for stage two of the project.
Stage two of the project is the collection, processing, and synthesis of new data, including high-resolution geophysical surveys and sediment cores—this report addresses the second stage. The work focuses on two of the study areas—the San Francisco and the Oceanside Littoral Cells, where several research cruises have been conducted. A more limited, exploratory approach was used for the Silver Strand Littoral Cell, owing to the lack of existing high-resolution bathymetric data for this study area. The data collected provide new information about the three study areas, including sediment thickness, grain-size distributions, and total organic carbon.
Sediment in all three study areas of the Sand Resources Study was suitable for beach nourishment, as reflected by their grain-size distributions and sediment thicknesses. For example, sandy sediment in the San Francisco Littoral Cell study area was on and immediately outside of the ebb-tidal bar of the San Francisco Bay, a landform that has a strong influence on grain-size patterns of the region. The presence of thick sediment deposits in this area was interpreted to be a function of tectonics, which has caused physical features that include a graben north of the Golden Gate whose deposits were thicker and siltier than the remaining area. Sandy sediment on the inner and outer parts of the continental shelf in the Oceanside Littoral Cell may be useful for nourishment, whereas the midshelf between these areas was dominated by silty sediment. Sediment in the Silver Strand Littoral Cell, which was only sampled selectively, had the greatest potential for beach nourishment because of the greater prevalence of beach-comparable grain sizes, especially in the more distal and deeper areas where medium sands were found.
The Sand Resources Project did identify several sandy regions of the continental shelf that are deeper than dredging technologies currently (2022) available in the United States, which are generally limited to 30 meters (m) water depth or less. Although sandy sediment exists in all three study areas at water depths of 30 m or less, additional sediment supplies—most of which are in Federal Waters—are present in deeper settings, especially for the Oceanside and Silver Strand Littoral Cell study areas. Although the Silver Strand Littoral Cell study area was found to be considerably replete in sand resources, these conclusions are based on a limited sampling exercise across that study area. Thus, it may be beneficial to complete a more thorough characterization of the sediment resources in the Silver Strand Littoral Cell study area if it is determined that a need for sandy coastal sediment exists in this region.
As a result of the Sand Resources Project, several areas of sand resources in Federal and California State Waters were found where they were previously unknown. As such, this project may provide important data for future coastal-management decisions in California, and it should provide a model for future investigations of sediment resources in other regions of the State.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221095","collaboration":"Prepared in cooperation with the Bureau of Ocean Energy Management and the State of California Ocean Protection Council","usgsCitation":"Warrick, J.A., Conrad, J.E., Papesh, A., Lorenson, T., and Sliter, R.W., 2022, Assessment of significant sand resources in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California: U.S. Geological Survey Open-File Report 2022–1095, 104 p., https://doi.org/10.3133/ofr20221095.","productDescription":"Report: viii, 104 p.; 3 Data Releases","onlineOnly":"Y","ipdsId":"IP-130530","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501837,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113943.htm","linkFileType":{"id":5,"text":"html"}},{"id":410366,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UELSBU","text":"USGS data release","description":"USGS data release","linkHelpText":"Geophysical and sampling data collected offshore Oceanside, southern California during field activity 2017-686-FA from 2017-10-23 to 2017-10-31"},{"id":410365,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9690BEK","text":"USGS data release","description":"USGS data release","linkHelpText":"Geophysical and core sample data collected offshore Oceanside to San Diego, southern California, during field activity 2018-638-FA from 2018-05-21 to 2018-05-26"},{"id":410364,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LBG9H5","text":"USGS data release","description":"USGS data release","linkHelpText":"Geophysical and core sample data collected offshore San Francisco, California, during field activity 2019-649-FA from 2019-10-11 to 2019-10-18"},{"id":410367,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221094","text":"OFR 2022-1094 —","linkHelpText":"Compilation of existing data for sand resource studies in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California—Strategy for field studies and sand resource assessment"},{"id":410363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1095/ofr20221095.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1095"},{"id":410362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1095/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco, Oceanside, and Silver Strand littoral cell study areas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.32845828309286,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 37.818674364541195\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.13365815618306,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.493660702226535\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.26754558635474,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.52924818029179\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St
Santa Cruz, CA 95060
The Sand Resources Project was established through collaborative agreements between the U.S. Geological Survey (USGS), the Bureau of Ocean Energy Management (BOEM), and the California Ocean Protection Council (OPC) with the purpose of evaluating sand and gravel resources in Federal and California State Waters for potential use in future beach-nourishment projects. Project partners worked in collaboration with California Coastal Sediment Management Workgroup (CSMW) members to define priority study areas for this work based on the potential for finding sand within the broader region and the needs for this sand as shown by beach erosion areas of concern in the adjacent littoral cells. The final study areas were defined to be (1) the San Francisco Littoral Cell, (2) the Oceanside Littoral Cell, and (3) the Silver Strand Littoral Cell.
A two-stage approach was used to assess the study areas. This report addresses the initial stage, which is a synthesis of the existing geophysical and sediment-sampling data in each area. This allowed for evaluations of the data availability, data gaps, and general patterns of sediment thickness and grain size. This report provides a description of the methods and results of this synthesis. The findings from this work were used to refine study area boundaries and develop sampling plans for stage two of the project.
Stage two of the project, the results of which will be published separately, will be the collection, processing, and synthesis of new data, including high-resolution geophysical surveys and sediment cores within the three study areas. The data collected will provide new information about the three study areas including sediment thickness, grain-size distributions, and total organic carbon. The description and results of stage two of the work is included in another USGS report (Warrick and others, 2022).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221094","collaboration":"Prepared in cooperation with the Bureau of Ocean Energy Management and the State of California Ocean Protection Council","usgsCitation":"Warrick, J.A., Conrad, J.E., Papesh, A., Lorenson, T., and Sliter, R.W., 2022, Compilation of existing data for sand resource studies in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California—Strategy for field studies and sand resource assessment: U.S. Geological Survey Open-File Report 2022–1094, 21 p., https://doi.org/10.3133/ofr20221094.","productDescription":"vii, 21 p.","onlineOnly":"Y","ipdsId":"IP-142746","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":410369,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1094/ofr20221094.pdf","text":"Report","size":"6.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1094"},{"id":410368,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1094/coverthb.jpg"},{"id":501836,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113942.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"San Francisco, Oceanside, and Silver Strand littoral cell study areas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.32845828309286,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 37.818674364541195\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.13365815618306,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.493660702226535\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.26754558635474,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.52924818029179\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St
Santa Cruz, CA 95060
A cascading set of hazards to coastal environments is intimately tied to sediment transport and includes the flooding and erosion of shorelines and habitats that support communities, industry, infrastructure, and ecosystem functions (for example, habitats critical to fisheries). This report summarizes modeling and measurement data used to evaluate the sediment budget of the Nisqually River Delta, the vulnerability of the largest estuary restoration project in Puget Sound at the Billy Frank Jr. Nisqually National Wildlife Refuge, and the role of coastal hydrodynamics and potential restoration alternatives for recovering sediment delivery to its marshes. The 2009 Brown’s Farm Restoration achieved many goals toward recovering salmon habitat, but the understanding of the delta and restoration area sediment budgets remain poorly quantified. Specifically, quantitative estimates of the amount of sediment delivered to the delta and restored marsh areas, which had subsided in response to historical diking and draining for grazing, were identified as important information needs. Forecasts of potential outcomes of proposed adaptive distributary channel restoration actions were also prioritized to inform potential solutions. These estimates can be used to evaluate whether sufficient sediment is available for marsh recovery downstream from Alder Lake, which traps about 90 percent the Nisqually River sediment load that could reach the delta. Additionally, quantitative sediment information was identified to help prioritize opportunities to recover and maintain the area marshes and guide ecosystem restoration investments across the delta to reduce the vulnerability of the system to drowning under projected sea level rise.
A coupled, numerical hydrodynamic-sediment transport model and measurements of the sediment load just upstream from the delta were used to evaluate the (1) availability of sediment for marsh recovery, (2) sediment transport dynamics across the estuary, and (3) potential outcomes of distributary reconnection alternatives under existing and projected conditions of streamflow and sea level. Modeling and measurements indicated that the volume of fluvial sediment load reaching and accumulating in the restoration area ranges from 7 to 32 percent and identified that restoration alternatives could recover about an additional 10–12 percent under current and projected sea-level rise by the year 2100. At these rates of sediment delivery, 85–200+ years may be necessary to fill for marsh vegetation development and maintenance. The model also reveals the sensitivity of sediment transport and accumulation to sediment properties, hydrodynamics, and wave conditions. The low sediment accumulation results in large part because of the role of waves in directing sediment transport offshore and challenges of restoring geomorphic processes suited to maintaining habitat structure where opportunity exists or least conflicts with land use. The findings therefore have implications for siting, phasing, and implementing strategies to route and retain sediment. This study shows that opportunities to recover sediment higher in the tidal prism, where a greater hydraulic gradient and gravity could promote progradation and greater sediment retention, may be more effective than alternatives lower in the tidal prism implemented to date and assessed in this study. Furthermore, the modeling indicates that distributary channel restoration also may provide additional benefits to society by reducing flood stage, and therefore, flood hazards surrounding the delta.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221088","collaboration":"Prepared in cooperation with Nisqually Indian Tribe, U.S. Fish and Wildlife Service, Billy Frank Jr. Nisqually National Wildlife Refuge, and Washington Department of Fish and Wildlife Estuary and Salmon Restoration Program","usgsCitation":"Grossman, E.E., Crosby, S.C., Stevens, A.W., Nowacki, D.J., vanAredonk, N.R., and Curran, C.A., 2022, Assessment of vulnerabilities and opportunities to restore marsh sediment supply at Nisqually River Delta, west-central Washington: U.S. Geological Survey Open-File Report 2022–1088, 50 p., https://doi.org/10.3133/ofr20221088.","productDescription":"Report: ix, 50 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-121432","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":410185,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GF0SG7","text":"USGS data release","description":"USGS data release","linkHelpText":"Stage, water velocity and water quality data collected in the Lower Nisqually River, McAllister Creek and tidal channels of the Nisqually River Delta, Thurston County, Washington, February 11, 2016 to September 18, 2017 (ver. 1.1, December, 2019)"},{"id":410186,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95N6CIT","text":"USGS data release","description":"USGS data release","linkHelpText":"Topobathymetric Model of Puget Sound, Washington, 1887 to 2017"},{"id":410184,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1088/ofr20221088.pdf","text":"Report","size":"32.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1088"},{"id":410183,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1088/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.12450821055306,\n 47.12862354087443\n ],\n [\n -123.12450821055306,\n 45.666890715537136\n ],\n [\n -121.49348505325844,\n 45.666890715537136\n ],\n [\n -121.49348505325844,\n 47.12862354087443\n ],\n [\n -123.12450821055306,\n 47.12862354087443\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
The U.S. Geological Survey (USGS) completed a verification study of selected commercially available phosphorus analyzers for their applicability to scientific surface-water applications. In this study, the analyzers were the Hach EZ7800 TOPHO, Hach Phosphax sc, Sea-Bird Scientific HydroCycle-PO4, and the YSI Inc. Alyza IQ PO4. Verification tests included laboratory trials comparing analyzer results to known standards with several known concentrations of dissolved organic matter and waste production estimates. Field trials were completed at the Vermilion River near Danville, Illinois (U.S. Geological Survey station 03339000), where analyzer-measured concentrations were compared against discrete samples across a wide range of environmental conditions from November 2020 to August 2021. Data coverage was closely tracked for analyzer malfunctions and operator errors that caused missing data. Laboratory and field trials indicated that each analyzer is a viable option for scientific surface-water studies depending on environmental conditions. Because of the complexity of the analyzers, a substantial time investiture was required to get maximum data coverage including considerable site infrastructure investments and well-trained technicians. Data coverage was closely related to each analyzer’s ability to handle elevated turbidity levels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221100","collaboration":"Prepared in cooperation with the Next Generation Water Observing System","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"Peake, C.S., 2022, Verification of multiple phosphorus analyzers for use in surface-water applications: U.S. Geological Survey Open-File Report 2022–1100, 23 p., https://doi.org/10.3133/ofr20221100.","productDescription":"Report: viii, 23 p.; Dataset","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-139337","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":410009,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221100/full","text":"Report"},{"id":409997,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.XML"},{"id":409995,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1100/coverthb.jpg"},{"id":501839,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113882.htm","linkFileType":{"id":5,"text":"html"}},{"id":409998,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1100/images"},{"id":409996,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.pdf","text":"Report","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1100"},{"id":409999,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","state":"Illinois, Indiana","otherGeospatial":"Vermilion River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.41449158849616,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 39.979211528524246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
This study used the complete set of continuous water-quality (WQ) data and discrete measurements of total ammonia collected by the U.S. Geological Survey from 2005 to 2019 at the four core sites in Upper Klamath Lake, Oregon, to examine relations between variables and extreme conditions that may be harmful for endemic Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris). Several graphical and tabular approaches were used to compare variables, sites, and years to better understand the factors contributing to and timing of extreme WQ in the lake. Extreme WQ thresholds were defined as the 1st or 99th percentiles of the daily average dataset of water temperature, pH, and dissolved oxygen (DO) concentration, and the weekly estimated un-ionized ammonia (NH3) from 2005 to 2019. Extreme WQ days were defined as those when at least 12 hours of measurements exceeded the extreme WQ threshold. The core site at Mid-Trench, which was also the deepest measurement site with a full-pool depth of 15 meters and at which water-quality sondes were deployed at the top and bottom of the water column, had the most extreme conditions of high water temperature, low DO, and high NH3. The upper sonde at Mid-Trench represented 40 percent of all days of extremely high water temperature (days with at least 12 hours exceeding 24.38 degrees Celsius) in the lake and 71 percent of all weekly estimates of extremely high NH3 (greater than 264 micrograms per liter) in the lake. The lower sonde at Mid-Trench represented 85 percent of all days of extremely low DO (days with at least 12 hours of DO concentrations less than 1.76 milligrams per liter) in the lake. In each of the study years, poor water quality at Mid-Trench, as represented by several metrics, lasted for multiple days. The shallowest site at the Williamson River outlet represented 54 percent of all days of extremely high pH (days with at least 12 hours of pH measurements exceeding 10.04) in the lake. The seasonality of extreme WQ during the summer sampling period (limited to June through September) was evaluated and most days of extremely high water temperature (83 percent) and extremely high pH (54 percent) occurred in July, whereas most days of extremely low DO (57 percent) and extremely high NH3 (57 percent) occurred in August. The years with the most days of extreme WQ accumulated for all variables (high water temperature, low DO, high pH, and high NH3) were 2012–15 and 2017, which all occurred in the latter half of the study period. The years with the fewest accumulated days of extreme WQ were 2010 and 2011.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221080","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Wherry, S.A., 2022, Summary of extreme water-quality conditions in Upper Klamath Lake, Oregon, 2005–19: U.S. Geological Survey Open-File Report 2022–1080, 29 p., https://doi.org/10.3133/ofr20221080.","productDescription":"vii, 29 p.","onlineOnly":"Y","ipdsId":"IP-128098","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501831,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113883.htm","linkFileType":{"id":5,"text":"html"}},{"id":410005,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.XML"},{"id":410002,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1080"},{"id":410001,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1080/coverthb.jpg"},{"id":410004,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1080/images"},{"id":410003,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221080/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1080"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11865576927013,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.623699726465674\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
The Conservation Reserve Enhancement Program is a program administered by the U.S. Department of Agriculture’s Farm Service Agency. The Secretary of Agriculture is required to submit an annual report to Congress on Conservation Reserve Enhancement Program agreements that, among other things, reports on the progress made towards fulfilling commitments outlined in the agreements. The U.S. Geological Survey developed an online reporting form designed to ensure that consistent information is submitted to the Farm Service Agency from Conservation Reserve Enhancement Program State partners. Combined with the automated importation of text from partner-provided forms to word-processing documents, individual State reports and annual reports to Congress can now be produced efficiently and in a standardized format. Use of a standardized reporting format will also assist the Farm Service Agency in collecting information needed to support ecosystem service quantifications that go beyond the quantifications required from partners to document progress towards meeting the specific purposes and objectives identified in each agreement. Addition of these overarching conservation effect quantifications builds upon past ecosystem services modeling efforts based on the Integrated Valuation of Ecosystem Services and Tradeoffs suite of open-source software models; these offer a spatially explicit means to quantify additional ecosystem services across diverse partners in a consistent manner. Data sources are currently available to provide much of the information needed to run these models and complete simulations that would facilitate the quantification and reporting of the societal values of conservation actions taken under the Conservation Reserve Enhancement Program. It is the aim of this report to provide the information needed to move towards widescale monitoring of the Nation’s ecosystem services in a natural accounting framework, similar to the framework used to value financial and human capital.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221104","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture’s Farm Production and Conservation Business Center and Farm Service Agency","usgsCitation":"Mushet, D.M., and McKenna, O.P., 2022, Development of an online reporting format to facilitate the inclusion of ecosystem services into Conservation Reserve Enhancement Program reports: U.S. Geological Survey Open-File Report 2022–1104, 19 p., https://doi.org/10.3133/ofr20221104.","productDescription":"Report: vi, 19 p.; 5 Appendixes","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-141507","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":409698,"rank":10,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221104/full","text":"Report"},{"id":409675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1104/coverthb.jpg"},{"id":409676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104.pdf","text":"Report","size":"725 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1104"},{"id":409677,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104.XML"},{"id":409678,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix1.pdf","text":"Appendix 1","description":"OFR 2022–1104, Appendix 1","linkHelpText":"—Farm Service Agency Notice Implementing Use of Online Reporting Form"},{"id":409679,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix2.pdf","text":"Appendix 2","description":"OFR 2022–1104, Appendix 2","linkHelpText":"—A Guide for Completing Conservation Reserve Enhancement Program Annual Reports Using the New Online Reporting Form"},{"id":409681,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix4.pdf","text":"Appendix 4","description":"OFR 2022–1104, Appendix 4","linkHelpText":"—Microsoft Word Mail Merge State Report Template"},{"id":409682,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix5.pdf","text":"Appendix 5","description":"OFR 2022–1104, Appendix 5","linkHelpText":"—Draft Text Produced for 2020 Report to Congress"},{"id":409683,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix6.pdf","text":"Appendix 6","description":"OFR 2022–1104, Appendix 6","linkHelpText":"—Draft Text Produced for 2021 Report to Congress"},{"id":409687,"rank":9,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1104/images"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
In this report, we consider evolutionary and ecological connectivity for westslope cutthroat trout (Oncorhynchus clarkii lewisi) and mountain whitefish (Prosopium williamsoni) within the Pend Oreille River in northeastern Washington State, northern Idaho, and adjacent portions of southeastern British Columbia, Canada. Specifically, we focused on the rationale for active translocation of individuals of these species upstream from Boundary Dam both in the context of natural patterns of pre-dam evolutionary connectivity as well as preserving contemporary ecological and evolutionary characteristics of local extant populations. Boundary Dam impounds the Pend Oreille River (called the Pend d’Oreille River in Canada) with the resulting reservoir inundating two historical barriers to upstream movement of fish (Metaline Falls and Z Canyon). Historically, it was thought these barriers impeded the upstream movement of westslope cutthroat trout and mountain whitefish, as well as Pacific salmon (Oncorhynchus spp.), steelhead trout (O. mykiss), and other resident species such as bull trout (Salvelinus confluentus). To address connectivity, we consider historical and contemporary processes and features. This review includes an assessment of postglacial processes within the Pend Oreille River and systems upstream that include Priest Lake, Lake Pend Oreille, the Clark Fork River, features of Boundary Reservoir and its tributaries, and areas downstream in the Pend Oreille River such as the Salmo River. Based on this information, we then give a more detailed review of existing genetic and ecological data to summarize what is known about connectivity for westslope cutthroat trout and mountain whitefish. Our assessment of the collective evidence leads us to conclude that moving fish upstream over Boundary Dam is not warranted if the management objective is to maintain natural patterns of evolutionary and ecological connectivity or to conserve unique ecological and evolutionary characteristics of extant local populations of these species in the system. These findings parallel that of a previous analysis of bull trout. Although we were able to arrive at well-supported conclusions in relation to Boundary Dam, we suggest that more work on connectivity further upstream in the Pend Oreille River would help to better understand the role of historical processes and dams further up in the system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221084","collaboration":"Prepared in cooperation with the University of British Columbia, Biodiversity Research Centre and Beaty Biodiversity Museum, and Idaho State University, Department of Biological Sciences, Fish Ecology Laboratory","usgsCitation":"Dunham, J.B., Taylor, E.B., and Keeley, E.R., 2022, Evolutionary and ecological connectivity in westslope cutthroat\ntrout (Oncorhynchus clarkii lewisi) and mountain whitefish (Prosopium williamsoni) in relation to the potential\ninfluences of Boundary Dam, Washington, Idaho, and parts of British Columbia: U.S. Geological Survey Open-File\nReport 2022–1084, 22 p., https://doi.org/10.3133/ofr20221084.","productDescription":"vii, 22 p.","onlineOnly":"Y","ipdsId":"IP-137003","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":409558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1084/coverthb.jpg"},{"id":409559,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1084/ofr20221084.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1084"},{"id":409561,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1084/images"},{"id":409562,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1084/ofr20221084.XML"}],"country":"Canada, United States","state":"British Columbia, Idaho, Washington","otherGeospatial":"Boundary Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.81638376433206,\n 49.098372085467105\n ],\n [\n -117.81638376433206,\n 47.528691502768\n ],\n [\n -113.48236882623914,\n 47.528691502768\n ],\n [\n -113.48236882623914,\n 49.098372085467105\n ],\n [\n -117.81638376433206,\n 49.098372085467105\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
Flat Creek, a tributary to the Snake River in northwestern Wyoming, is an important source of irrigation water, fish and wildlife habitat, and local recreation. Since 1996, a section of Flat Creek within the town of Jackson has failed to meet Wyoming Department of Environmental Quality’s surface-water-quality standards for total suspended solids and turbidity required by its State water-use classification. Wyoming Department of Environmental Quality water-quality standards prohibit increases of greater than 10 nephelometric turbidity units (NTU) because of human activities in streambodies of Wyoming. Sediment loading from urban stormwater runoff is hypothesized in previous publications to be the primary cause of impairment, but the relative fine sediment contributions from various sources have not been quantified.
In cooperation with the Teton Conservation District, the U.S. Geological Survey began a pilot study in the Flat Creek drainage basin to investigate the use of continuous turbidity measurements to predict suspended-sediment concentrations, loads, and sources through the town of Jackson, Wyoming. The predictions were based on turbidity measurements collected every 15 minutes during parts of water years 2019 and 2020. Analysis of differences in the more than 15,000 turbidity measurements coincident between upstream and downstream streamgages indicated that differences of 10 formazin nephelometric units (FNU) or greater composed about 1 percent of the total accepted measurements during the 2019 and 2020 measurement periods. The median difference in measured turbidity between coincident records at the upstream and downstream streamgages in 2019 was 0.20 FNU and the median difference in 2020 was 0.0 FNU.
Calculations of mean total sediment loads in Flat Creek during 2019 and 2020 indicate substantially more suspended-sediment was in Flat Creek below the town of Jackson than above town. Mean total calculated suspended-sediment loads at the upstream streamgage were 26 percent in 2019 and 21 percent in 2020 of the mean total suspended-sediment loads at the downstream streamgage. For measurements occurring at the same time (coincident), mean calculated suspended-sediment loads entering the town of Jackson from Flat Creek were 39 percent in 2019 and 35 percent in 2020 of those loads exiting town in Flat Creek. Incorporating statistical model uncertainty, mean differences between predicted suspended-sediment loads could potentially be zero. The annual period of operations of the South Park Supply Ditch, which diverts water into Flat Creek from the Gros Ventre River, constituted between 91 and 90 percent of the total calculated suspended-sediment load at the upstream streamgage, and between 88 and 87 percent of the loads at the downstream streamgage for coincident periods of record in 2019 and 2020, respectively. However, in the absence of simultaneous continuous monitoring and resulting measurements at the outlet of the South Park Supply Ditch, no robust method was available to quantify suspended-sediment loads from the ditch.
A moving average filter was used to identify and isolate short-duration (minutes to hours) spikes in turbidity at the downstream streamgage that were likely caused by overland flow and urban runoff. Suspended-sediment loads during urban runoff constituted about 8 and 10 percent of the total calculated suspended-sediment loads at the downstream streamgage (Flat Creek below Cache Creek, near Jackson, Wyoming; U.S. Geological Survey streamgage 13018350), and 6 and 4 percent of the loads calculated for the record coincident with the upstream streamgage in 2019 and 2020, respectively. Estimated suspended-sediment loads at the upstream streamgage during urban runoff events for the coincident period of record constitute 32 and 40 percent of the total estimated suspended-sediment loads at the downstream streamgage in 2019 and 2020, respectively, indicating sediment loads from urban runoff may contribute less than 10 percent, even as little as 5 percent, of the total sediment load exiting the town of Jackson on Flat Creek. Estimation of the proportion of suspended-sediment loads at the upstream site that originate from the South Park Supply Ditch or Cache Creek can only be done with assumptions but have the potential to be equivalent to or greater than calculated suspended-sediment loads associated with urban runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221103","collaboration":"Prepared in cooperation with the Teton Conservation District","programNote":"Water Mission Area","usgsCitation":"Alexander, J.S., Girard, C., Campbell, J., Ellison, C., Gosselin, E., and Smith, E., 2022, Using continuous measurements of turbidity to predict suspended-sediment concentrations, loads, and sources in Flat Creek through the town of Jackson, Wyoming, 2019−20 — A pilot study: U.S. Geological Survey Open-File Report 2022–1103, 29 p., https://doi.org/10.3133/ofr20221103.","productDescription":"Report: viii, 29 p.; Dataset","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-136294","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":409367,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":409366,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1103/images"},{"id":409364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1103/ofr20221103.pdf","text":"Report","size":"2.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1103"},{"id":409365,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1103/ofr20221103.XML"},{"id":409363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1103/coverthb.jpg"},{"id":501840,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113833.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","city":"Jackson","otherGeospatial":"Flat Creek drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.72880406891166,\n 43.5011735765672\n ],\n [\n -110.8241704639435,\n 43.5011735765672\n ],\n [\n -110.8241704639435,\n 43.42146497765464\n ],\n [\n -110.72880406891166,\n 43.42146497765464\n ],\n [\n -110.72880406891166,\n 43.5011735765672\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Current time-invariant groundwater vulnerability assessments may not capture intermittent contamination events in landscape areas that experience rapid infiltration following precipitation or snowmelt. Occurrences of rapid infiltration and intermittent degradation of groundwater quality are frequently reported in fractured-rock aquifers. This investigation identifies landscape areas underlain by fractured rock within the conterminous United States (CONUS) that may be susceptible to rapid infiltration and where groundwater is a principal source of water supply to the population. Our analysis shows that approximately 27 percent of the CONUS, corresponding to a population of approximately 150 million people, is both underlain by fractured rock and denoted as an area of significant groundwater use.
The results of this survey identified shallow fractured-rock aquifers underlying glacial sediments in the upper Midwest and northeastern United States as areas that may be subject to rapid infiltration events. Additionally, aquifers associated with the early Mesozoic basins located in the northeastern and mid-Atlantic United States and bands of carbonate aquifers in the southeastern United States show high susceptibility to rapid infiltration. Index values used in this investigation indicate isolated areas in the western half of the United States also show high susceptibility to rapid infiltration. The isolated areas in Oklahoma, Texas, Arkansas, and southwestern Missouri correspond to karst regions of carbonate aquifers. The isolated areas showing high susceptibility to rapid infiltration and contamination from agricultural sources are locations where more detailed investigations of transient contamination events are warranted.
This survey also addresses the potential for contaminant longevity in fractured-rock aquifers stemming from intermittent contamination events. Contaminants that can dissolve into the groundwater following infiltration may be introduced into fractures, and the dissolved constituents can diffuse from fractures into the porosity of the adjacent rock matrix. These constituents can then diffuse back into permeable fractures and adversely affect groundwater quality at downgradient locations over an extended time frame. Rock types with larger matrix porosities have the capacity to retain and then release larger quantities of dissolved constituents, resulting in longer residence times for dissolved groundwater contaminants. The magnitude of the dissolved contaminant concentration infiltrating to the water table will also dictate whether the contaminant concentration in the groundwater exceeds limits for human consumption over the duration of a contamination event.
In general, sedimentary- and carbonate-rock aquifers have larger matrix porosities in comparison to igneous- and metamorphic-rock aquifers, and thus, they are more susceptible to longer contaminant residence times. Aquifers composed of sedimentary or carbonate rock constitute approximately 51 percent of the CONUS, and 19 percent of the CONUS is associated with sedimentary- or carbonate-rock aquifers that are of significance for groundwater use. Depending on the contaminants of concern and the concentration of the contaminants introduced into the groundwater from infiltrating water, it would be beneficial for investigations of susceptibility to rapid infiltration to also consider the potential for contaminant longevity.
This investigation identifies areas of rapid infiltration into fractured rock using index values applied to the attributes (1) depth to the water table, (2) depth to bedrock, and (3) percentage of sand in soil, where larger index values indicate a greater susceptibility to rapid infiltration. These attributes are selected as the most likely factors that affect rapid infiltration to the water table. The combination of depth to water table and depth to bedrock highlight those aquifer settings that are characterized as shallow fractured-rock aquifers, where the water table may reside either in the bedrock or in overlying unconsolidated geologic materials. In addition, we consider the percentage of agricultural use as a land-use attribute when formulating an index of susceptibility to rapid infiltration and contamination. Agricultural areas are well recognized as nonpoint sources of contaminants that can affect groundwater quality because of seasonal amendments applied to the land surface. Rural agricultural areas are also characterized by septic tanks and leach fields for onsite treatment of wastewater, which may also be a source of contamination that may be introduced into the groundwater following precipitation or snowmelt events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221093","programNote":"National Water Quality Program","usgsCitation":"Shapiro, A.M., and Falcone, J.A., 2022, Mapping areas of groundwater susceptible to transient contamination events from rapid infiltration into shallow fractured-rock aquifers in agricultural regions of the conterminous United States: U.S. Geological Survey Open-File Report 2022–1093, 25 p., https://doi.org/10.3133/ofr20221093.","productDescription":"v, 25 p.","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132538","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":501835,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113829.htm","linkFileType":{"id":5,"text":"html"}},{"id":409297,"rank":1,"type":{"id":31,"text":"Publication 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U.S. Geological Survey
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Imaging sonar was used to assess the behavior, abundance, and timing of fish at the entrances to the Selective Water Withdrawal (SWW) intake structure located in the forebay of Round Butte Dam, Oregon during the spring of 2021. 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, needs (A) to regularly assess how fish are approaching the entrance, and (B) to determine if operational flows could be optimized to increase the attraction of smolts present in the forebay of Lake Billy Chinook. The primary goals of this study were (1) to assess the abundance and behaviors of smolt-size fish observed near the SWW and (2) to provide data of the effect of two-night generation operation timing conditions on movements and behaviors of fish near the entrance to the SWW structure. The purpose of this assessment is to improve downstream passage solutions.
Two imaging sonar units were deployed during the spring 2021 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. Both smolt and bull trout (Salvelinus confluentus)-size fish were regularly observed near the entrances with greater abundances observed during night, corresponding with greater discharge through the SWW than during the day when discharge was reduced. Differences in fish abundance were observed between the night generation operation timing conditions, with increased fish counts observed when elevated discharge was extended to 6:00 a.m., rather than when discharges have been traditionally reduced in the early morning at 4:00 a.m. Fish of all size groups were primarily observed near the center of the SWW, 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 (A) smolt-size fish were more abundant near the entrance of the SWW during periods of increased discharge, (B) bull trout-size fish were present at the SWW, and (C) fish were more numerous at the SWW when night generation operation timing was extended later into the morning hours rather than the traditional operation timing flow reduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221098","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., and Hatton, T.W., 2022, Evaluation of fish behavior at the entrances to a Selective Water Withdrawal structure in Lake Billy Chinook, Oregon, 2021: U.S. Geological Survey Open-File Report 2022–1098, 28 p., https://doi.org/10.3133/ofr20221098.","productDescription":"viii, 28 p.","onlineOnly":"Y","ipdsId":"IP-139510","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409425,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1098/images"},{"id":409424,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221098/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1098"},{"id":409423,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1098/ofr20221098.pdf","text":"Report","size":"36.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1098"},{"id":409422,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1098/coverthb.jpg"},{"id":409426,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1098/ofr20221098.XML"}],"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 -121.5557866634069,\n 44.75388913871075\n ],\n [\n -121.5557866634069,\n 44.38885839267408\n ],\n [\n -121.07886358532556,\n 44.38885839267408\n ],\n [\n -121.07886358532556,\n 44.75388913871075\n ],\n [\n -121.5557866634069,\n 44.75388913871075\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
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We surveyed for Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) at 33 locations along multiple drainages in San Diego County, including portions of Agua Hedionda Creek, Cottonwood Creek, Escondido Creek, Los Penasquitos Creek, Otay River, San Diego River, San Dieguito River, San Luis Rey River, Sweetwater River, and Tijuana River. Resident flycatchers were only found on two drainages in San Diego County, at San Dieguito and San Luis Rey Rivers, with 99 percent occurring on the San Luis Rey River. Resident flycatchers were detected at 18 percent of survey locations (Bonsall, Cleveland National Forest, Rey River Ranch, San Dieguito, and Vista Irrigation District [VID], and VID Lake Henshaw). Resident flycatchers were documented for the first time at Lake Henshaw, the only new location surveyed that supported flycatchers. We detected a minimum of 80 resident flycatchers from 2015 to 2019, most of these were upstream and downstream from Lake Henshaw. Transient flycatchers were found at 42 percent of survey locations; 38 transient individuals were detected at Agua Hedionda Creek, Otay River, San Diego River, San Dieguito River, and the San Luis Rey River.
Over the course of this study, 11 locations historically occupied by resident flycatchers were resurveyed; only 5 were found to have resident flycatchers: (1) Bonsall, (2) Cleveland National Forest, (3) Rey River Ranch, (4) San Dieguito, and (5) Vista Irrigation District. The number of resident flycatchers declined from previous high counts at all five locations. Collectively, the number of resident flycatcher territories within the historically occupied area of the upper San Luis Rey River downstream from Lake Henshaw (Cleveland National Forest, Rey River Ranch, and Vista Irrigation District) declined 71 percent between 1999 (48) and 2019 (14); 42 percent of the decline occurred between 1999 and 2016, with an additional decline (50 percent) occurring between 2016 and 2019. In 2016, the distribution of flycatcher territories at the historically occupied area of the upper San Luis Rey River changed relative to the distribution in 1999: the proportion of territories at Cleveland National Forest and Rey River Ranch decreased to 36 percent each, while Vista Irrigation District increased to 29 percent, creating a more equal distribution of territories across the historically occupied area. By 2019, the distribution changed relative to 2016, with most of the territories spread equally between Cleveland National Forest and Rey River Ranch (43 percent each), while the proportion of territories at Vista Irrigation District declined to 14 percent.
During countywide surveys, we documented the dispersal of two natal banded flycatchers; both were females that were originally banded as nestlings at Marine Corps Base Camp Pendleton and were seen for the first time as breeding adults. One of the females dispersed to San Dieguito, a distance of 41 kilometers, and a second female dispersed to Cleveland National Forest, a distance of 55 kilometers. We also documented the within-season movement of a uniquely banded male that was seen at the beginning of the 2017 breeding season at Bonsall and was later documented at San Dieguito, a movement distance of 31 kilometers.
We completed nest monitoring activities along the upper San Luis Rey River near Lake Henshaw in Santa Ysabel, California from 2016 to 2019. Monitoring occurred at three locations: (1) Cleveland National Forest, (2) Rey River Ranch, and (3) Vista Irrigation District, collectively the upper San Luis Rey River monitoring area. The number of flycatcher territories monitored each year ranged from 14 to 27. We observed polygynous pairings (one male paired with multiple females) in all years, with the lowest rate of polygyny (number of polygynous pairs/total number of pairs) observed in 2016 (10 percent) and the highest in 2017 (70 percent). The proportion of paired males that were polygynous ranged from 5 to 54 percent between 2016 and 2019.
We monitored the nesting activity of 14–27 pairs annually during the course of the study. Most of the first nesting attempts were initiated during late May and early June. We monitored 18–41 Southwestern Willow Flycatcher nests per year from 2016 to 2019. Apparent nest success ranged from 11 to 37 percent and differed significantly by year, with higher success in 2016 and 2017 compared to 2018 and 2019. Predation was the presumed to be the primary source of nest failure, with 63–84 percent of failures annually attributed to predation. Although none of the failures were attributed to Brown-headed cowbird (Molothrus ater) parasitism, 4–27 percent of nests were parasitized annually from 2016 to 2019, with increased parasitism rates observed in 2018 and 2019 compared to 2016 and 2017. We “rescued” 11 parasitized nests between 2016 and 2019 by removing cowbird eggs; if those nests had been allowed to fail, apparent nest success would have been up to 45 percent lower annually.
Flycatcher egg clutch size ranged from 2.8±0.8 to 3.1±0.8 annually and did not vary significantly between years. The number of fledglings per pair ranged from 0.5±1.0 to 1.6±1.5 annually from 2016 to 2019. There was a significant difference in the number of young fledged per pair between years, with pairs in 2016 producing more than three times the number of fledglings compared to 2019. The percent of pairs fledging at least one young ranged from 18 to 62 percent annually but did not vary significantly by year.
Analysis of flycatcher daily nest survival rates suggested that both early and late winter precipitation influenced nest survival, with increases in early winter precipitation positively influencing nest survival and later winter precipitation negatively influencing nest survival. The second-best supported model included year, with the lowest daily nest survival occurring in 2018 and 2019.
A total of 119 flycatchers were newly banded over the course of this study; 36 adult flycatchers were banded with a unique color combination, and 83 nestlings (57 of which survived to fledging) were banded with a single band on the left or right leg. In addition, two adults that were banded before 2015 were observed in the monitoring area. Between 2015 and 2019, we accumulated 94 resights of 49 individual color-banded adult flycatchers that ranged in age from 1 to 8 years old.
Banding allowed us to examine differences in annual survivorship among flycatchers of different ages and sexes. We estimated annual survivorship of adult males to be 69±7 percent, which is higher than estimates of female survivorship (45±10 percent). Annual survivorship of first-year flycatchers ranged from 24 to 41 percent, which is roughly half the estimates calculated for adult flycatchers (52–75 percent). We found no evidence that precipitation in the previous breeding year had an effect on flycatcher survival.
We were also able to observe dispersal and movement among adults and first-year flycatchers. Average first-year dispersal distance was 3.1±2.6 kilometers, with the longest dispersal (8.5 kilometers) by a natal female dispersing from the monitoring area to Lake Henshaw. Of the first-year flycatchers, 65 percent returned to the monitoring area to establish an adult breeding territory, while the remaining 35 percent dispersed to Lake Henshaw.
Territory fidelity among adult flycatchers was high with 69±13 percent of returning adults occupying the same territory (or within 100 meters) from the previous year. There was no significant difference in territory fidelity between males and females, or across years. Nesting success in the previous year appeared to be a strong driver of territory fidelity, with adults more likely to return to the same territory following years when they successfully fledged young. The average between-year movement for returning adult flycatchers was 0.5±0.8 km. We documented the movement of two adult males from the monitoring area to Lake Henshaw. Between-year movement distances did not differ by sex or year.
Resident flycatchers in the upper San Luis Rey River monitoring area used five habitat types from 2016 to 2019: (1) willow-oak, (2) willow-ash, (3) oak-sycamore, (4) mixed willow riparian, and (5) willow-sycamore, with willow-oak the most commonly used habitat type. The most commonly recorded dominant species at flycatcher territories included coast live oak (Quercus agrifolia), red or arroyo willow (Salix laevigata or Salix lasiolepis), California sycamore (Platanus racemosa), and velvet ash (Fraxinus velutina).
In 2018, we anecdotally began to observe dead and dying oaks in the monitoring area, which we believe to be the result of goldspotted oak borer (Agrilus auroguttatus) infestation. At the conclusion of this study, we investigated the overall change in normalized difference vegetation index (NDVI) in flycatcher territories within the monitoring area. The greatest negative change in NDVI occurred in territories closest to Lake Henshaw, and many of the affected territories were no longer occupied in the later years of the study.
Flycatchers used 13 plant species for nesting at the monitoring area from 2016 to 2019; 70 percent of all nests were placed in coast live oak. None of the nest characteristics including host height, nest height, distance to the edge of the host, or distance to the edge of the vegetation clump where the nest was placed differed between years. In 2016, successful nests were placed higher than unsuccessful nests; no other within-year differences were observed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221082","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., Kus, B.E., and Mendia, S.M., 2022, Distribution and demography of Southwestern Willow Flycatchers in San Diego County, 2015–19: U.S. Geological Survey Open-File Report 2022–1082, 43 p., https://doi.org/10.3133/ofr20221082.","productDescription":"Report: ix, 43 p.; Data Release","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-139367","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":409362,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1082/images"},{"id":409388,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221082/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1082"},{"id":409359,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1082/ofr20221082.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1082"},{"id":409361,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1082/ofr20221082.xml"},{"id":409360,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96VC5Y4","text":"USGS data release","linkHelpText":"Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys and nest monitoring in San Diego County, California"},{"id":409358,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1082/covrthb.jpg"}],"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 -117.57666896119845,\n 33.481188795657516\n ],\n [\n -117.57666896119845,\n 32.493491667261026\n ],\n [\n -116.14905258547724,\n 32.493491667261026\n ],\n [\n -116.14905258547724,\n 33.481188795657516\n ],\n [\n -117.57666896119845,\n 33.481188795657516\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
Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir (hereinafter, Clear Lake), California, are experiencing long-term decreases in abundance. Upper Klamath Lake populations are decreasing not only because of adult mortality, which is relatively low, but also because they are not being balanced by recruitment of young adult suckers into known adult spawning aggregations.
Long-term monitoring of juvenile sucker populations is conducted to (1) determine if there are annual and species-specific differences in production, survival, and growth, (2) better understand when juvenile sucker mortality is greatest, and (3) help identify potential causes of high juvenile sucker mortality particularly in Upper Klamath Lake. The U.S. Geological Survey (USGS) monitoring program, begun in 2015, tracks cohorts through summer months and among years in Upper Klamath and Clear Lakes. Data on juvenile suckers captured in trap nets are used to provide information on annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, apparent growth, species composition, and health.
Upper Klamath Lake indices of year-class strength suggest that the 2020 age-0 cohort is one of the lowest since standardized monitoring began. Despite apparently low over-winter survival, the relatively large 2019 cohort persisted in our 2020 samples and continues to contribute to the populations. Although the 2019 cohort age-0 suckers were composed mainly of Lost River suckers, the age-1 suckers from the 2019 cohort were mainly shortnose suckers. Lost River suckers comprised the largest proportion of the 2020 year-class and were only captured in July and August. Shortnose suckers were mainly captured in August and September and comprised a smaller proportion of the 2020 year-class.
Age distribution of suckers captured in Clear Lake indicates greater juvenile survival than in Upper Klamath Lake. Most juvenile suckers captured were age-3 and age-4 suckers classified as the combination of Klamath largescale suckers (Catostomus snyderi) and shortnose suckers from the Lost River Basin, from the 2016 and 2017 cohorts. A lack of age-0 suckers captured in Clear Lake during years with the low inflow or lake levels initially lead us to believe that low water prevented spawning and year class formation. However, recent data indicate that some cohorts that were not captured as age-0 suckers were detected in later years at age-1 or age-2. This finding indicates that juvenile suckers in Clear Lake may spend one or more years in the tributaries or that sampling efficacy for age-0 suckers varies among years because of water depth.
The first 5 years of this monitoring program indicated different patterns in recruitment and survival of juvenile suckers between Upper Klamath and Clear Lakes. Since the monitoring program began in 2015, age-0 sucker catch rates, interpreted as indices of year-class strength, were greatest in Upper Klamath Lake in 2016 and 2019. In those years Lost River suckers made up the majority of age-0 sucker catches; however, in 2017 and 2020 the age-1 sucker catches from these cohorts were mainly composed of shortnose suckers or suckers with genetic markers of both Klamath largescale and shortnose suckers, indicating a low overwinter survival for Lost River suckers even when the age-0 catches were high. Age-0 suckers do not fully recruit to our sampling gear in Upper Klamath Lake until August, experience high mortality by September, and are almost undetectable by the following July or August in most years. In Clear Lake, suckers frequently are not captured until age-1 or age-2 and annual survival appears much greater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221099","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Martin, B.A., Kelsey, C.M., Burdick, S.M., and Bart, R.J., 2022, Growth, survival, and cohort formation of juvenile Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2020 monitoring report: U.S. Geological Survey Open-File Report 2022–1099, 27 p., https://doi.org/10.3133/ofr20221099.","productDescription":"vi, 27 p.","onlineOnly":"Y","ipdsId":"IP-141866","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409276,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221099/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1099"},{"id":409274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1099/coverthb.jpg"},{"id":409278,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1099/ofr20221099.XML"},{"id":409277,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1099/images"},{"id":409275,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1099/ofr20221099.pdf","text":"Report","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1099"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath Lake, Clear Lake Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.23841270893135,\n 42.66770378348696\n ],\n [\n -122.23841270893135,\n 41.77275507129002\n ],\n [\n -121.00794395893129,\n 41.77275507129002\n ],\n [\n -121.00794395893129,\n 42.66770378348696\n ],\n [\n -122.23841270893135,\n 42.66770378348696\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
Across the Pacific Northwest, there are many examples of artificial structures created to allow passage of upstream-migrating salmon over natural barriers. We studied upstream passage across three structures installed in 1989 to allow passage of salmon over Lake Creek Falls, a series of three natural waterfalls at the outlet of Triangle Lake on Lake Creek, in the central Oregon Coast Range (lat 123.57508°; long 44.15735°). To track upstream passage by adult coho salmon (Oncorhynchus kisutch), 87 fish were tagged using gastrically implanted radio tags. Tracking was accomplished with a series of stationary receivers installed to detect crossings at each of three structures—over Lake Creek Falls using two upstream Denil-type ladders and a bypass downstream constructed to mimic a natural side channel. Tracking spanned the upstream migration and spawn timing for adult coho salmon in the basin and extended from October 2019 to February 2020. A total of 15 coho salmon (17 percent) were tagged in October, 30 coho salmon (35 percent) were tagged in November, and 42 coho salmon (48 percent) were tagged in December. Later-than-normal precipitation and associated low discharge delayed upstream migrations. Accordingly, most fish arrived late in the season (late November and December) and in sudden flushes with the erratic rain events. Fish that were tagged earlier were more likely to cross all three ladders, with more than 93 percent of fish tagged in October compared to 46.7 and 19.0 percent of November and December fish passing, respectively. The decline in passage rate could be attributed to the overlapping influences of stream discharge and advanced stage of maturation (lower energy reserves) of fish later in the season. Near the end of the study, both fish that crossed and fish obstructed by barriers were observed in tributaries known to be used for spawning by coho salmon. Without a much longer-term study involving many more fish than the current study, more intensive tracking, and coverage of different flow years, firm conclusions are difficult to draw regarding the overall influences of the passage structures on the likelihood of upstream passage by adult coho salmon. However, substantial numbers of fish are capable of crossing during certain conditions. The population-level consequences of the barriers on spawning distribution and the production of coho salmon in the watershed are not clear. Additional empirical study or population modeling could be used to address this question in more detail.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221083","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Fischer, R.B., Dunham, J., Scheidt, N., Hansen, A.C., and Heaston, E.D., 2022, Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019: U.S. Geological Survey Open-File Report 2022–1083, 19 p., https://doi.org/10.3133/ofr20221083.","productDescription":"vii, 19 p.","onlineOnly":"Y","ipdsId":"IP-130393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1083/coverthb.jpg"},{"id":409181,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.XML"},{"id":409180,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1083/images"},{"id":409179,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221083/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1083"},{"id":409178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1083"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Creek Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.61844237310005,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.17170307975459\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
The seagrasses eelgrass (Zostera marina) and widgeongrass (Ruppia maritima) are prominent features of coastal lagoons along the Pacific coast of Baja California, Mexico, supporting a rich diversity of marine life. Yet little is known about their spatial distribution in this region. This is a concern because of declining trends in the abundance and distribution of seagrass in parts of northern Baja California and southern California. We used 7-band satellite imagery, 4-band digital multispectral videography, and 3-band color aerial photography to map the distribution of eelgrass and widgeongrass in six embayments along the central Pacific coast of Baja California. The total spatial extent of seagrass was estimated to be 42,697 hectares, of which about 70 percent was eelgrass. This seagrass was primarily lower in the intertidal than widgeongrass in all embayments. Eelgrass and widgeongrass composed the greatest proportion (47 percent) of the spatial extent in the two largest embayments, Lagunas Ojo de Liebre and San Ignacio, and these two embayments accounted for 85 percent of all seagrass in the study area. The native cordgrass (Spartina foliosa) and pickleweed (Salicornia spp.) were the predominate vegetation cover type of marshes in the three northern and three southern embayments, respectively. The three southern embayments contained mangrove (Rhizophora spp.) and the three northern embayments did not, thus marking the northern edge of mangroves along the Pacific coast of North America. This study establishes an embayment-wide baseline for continuing investigations and monitoring future changes in the spatial abundance of seagrasses in central Baja California.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221004","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., Morton, A., Markon, C.J., and Hogrefe, K.R., 2022, Spatial extent of seagrasses (Zostera marina and Ruppia maritima) along the central Pacific coast of Baja California, Mexico, 1999–2000: U.S. Geological Survey Open-File Report 2022–1004, 13 p., https://doi.org/10.3133/ofr20221004.","productDescription":"Report: vi, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-128315","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":409029,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H4LBP3","text":"USGS data release","description":"USGS data release.","linkHelpText":"Point sampling data for eelgrass (Zostera marina) and widgeongrass (Ruppia maritima) abundance in embayments of the north Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409030,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEK4JI","text":"USGS data release","description":"USGS data release.","linkHelpText":"Mapping data of eelgrass (Zostera marina) distribution, Alaska and Baja California, Mexico"},{"id":409032,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1004/ofr20221004.XML"},{"id":409031,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1004/images"},{"id":409026,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1004/coverthb.jpg"},{"id":409041,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221078","text":"OFR 2022-1078 —","description":"OFR 2022-1078","linkHelpText":"Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409028,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221004/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1004"},{"id":409027,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1004/ofr20221004.pdf","text":"Report","size":"6.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1004"}],"country":"Mexico","otherGeospatial":"Baja California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.34490212994275,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 28.246325178662076\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Trends in the abundance and distribution of eelgrass (Zostera marina), the primary winter forage of black brant (Branta bernicla nigricans), was evaluated at three major wintering sites for black brant along the northern Pacific coast of Baja California, Mexico. This region of northwestern Mexico contains significant beds of eelgrass that were showing signs of decline, which may negatively affect the Pacific flyway population of black brant. Embayment-wide surveys of eelgrass were conducted at Bahia San Quintin (BSQ), Laguna Ojo de Liebre (LOL), and Laguna San Ignacio (LSI) between 1998 and 2012 to estimate baselines and trends in the distribution and abundance of this seagrass in Mexico. Eelgrass was the most abundant and frequently encountered seagrass in each site across survey years. Density and aboveground biomass of eelgrass was greater in BSQ than in LOL and LSI while abundance of widgeongrass (Ruppia maritima), a secondary source of food for brant, was greatest in LSI across survey years. Widgeongrass occurred higher in the intertidal zone than did eelgrass in all embayments, and both seagrasses generally shifted to lower water depths along a southward latitudinal gradient. A negative temporal trend in abundance of seagrasses was detected in BSQ that appeared linked to impacts of climate warming and an increase in macroalgae populations. Decreases in abundance of seagrasses were also detected in LOL and LSI, although long-term trends were less certain in LOL. Overall, declines in abundance of eelgrass in Baja California may be influencing the ongoing shift in the winter distribution of brant to areas north of the Mexican border.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221078","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., 2022, Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012: U.S. Geological Survey Open-File Report 2022–1078, 15 p., https://doi.org/10.3133/ofr20221078.","productDescription":"Report: vi, 15 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-135227","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":409019,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEK4JI","text":"USGS data release","description":"USGS data release.","linkHelpText":"Mapping data of eelgrass (Zostera marina) distribution, Alaska and Baja California, Mexico"},{"id":409018,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H4LBP3","text":"USGS data release","description":"USGS data release.","linkHelpText":"Point sampling data for eelgrass (Zostera marina) and widgeongrass (Ruppia maritima) abundance in embayments of the north Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409021,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1078/ofr20221078.XML"},{"id":409020,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1078/images"},{"id":409042,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221004","text":"OFR 2022-1004 —","description":"OFR 2022-1004","linkHelpText":"Spatial extent of seagrasses (Zostera marina and Ruppia maritima) along the central Pacific coast of Baja California, Mexico, 1999–2000"},{"id":409015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1078/coverthb2.jpg"},{"id":409017,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221078/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1078"},{"id":409016,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1078/ofr20221078.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1078"}],"country":"Mexico","otherGeospatial":"Baja California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.34490212994275,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 28.246325178662076\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
In 2015, U.S. Geological Survey scientists in collaboration with scientists from other institutions began a study of the Queen Charlotte fault—the first systematic study of the fault in more than three decades. The primary goal of the study was to gain a better understanding of the earthquake, tsunami, and underwater-landslide hazards throughout southeastern Alaska, as well as gather data to develop geologic models that can be applied to similar plate boundaries around the globe, such as the San Andreas fault system in southern California, the Alpine fault in New Zealand, and the North Anatolian fault in Turkey. A bathymetric terrain model was compiled from six different multibeam surveys of the previously unmapped Queen Charlotte fault offshore of southeastern Alaska and Haida Gwaii archipelago.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221085","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"Andrews, B.D., Brothers, D.S., Dartnell, P., Barrie, J.V., Haeussler, P.J., Green, K.M., Greene, H.G., Miller, N.C., Kluesner, J.W., and ten Brink, U.S., 2022, Systematic mapping of the ocean-continent transform plate boundary of the Queen Charlotte fault system, southeastern Alaska and western British Columbia—A preliminary bathymetric terrain model: U.S. Geological Survey Open-File Report 2022–1085, 2 sheets, 7-p. pamphlet, https://doi.org/10.3133/ofr20221085.","productDescription":"Pamphlet: iii, 7 p.; 2 Sheets: 60.50 × 42.50 inches and 60.00 × 42.00 inches; Data Release","numberOfPages":"7","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-128196","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501832,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113792.htm","linkFileType":{"id":5,"text":"html"}},{"id":408793,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085_sheet2.pdf","text":"Sheet 2","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Contents of sheet replicated in the HTML version of the report linked to above"},{"id":408792,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085_sheet1.pdf","text":"Sheet 1","size":"72.3 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Contents of sheet replicated in the HTML version of the report linked to above"},{"id":408791,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1085/images/"},{"id":408787,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1085/coverthb.jpg"},{"id":408788,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085_pamphlet.pdf","text":"Pamphlet","size":"5.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1085"},{"id":408790,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085.XML"},{"id":408789,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221085/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1085"},{"id":408794,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YGDHIQ","text":"USGS data release","linkHelpText":"A bathymetric terrain model of multibeam sonar data collected between 2005 and 2018 along the Queen Charlotte fault system in the eastern Gulf of Alaska from Cross Sound, Alaska, to Queen Charlotte Sound, Canada"}],"country":"Canada, United States","state":"Alaska, British Columbia","otherGeospatial":"Queen Charlotte Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -140.92029001527425,\n 58\n ],\n [\n -140.92029001527425,\n 46.46240819189495\n ],\n [\n -124.69923324285543,\n 46.46240819189495\n ],\n [\n -124.69923324285543,\n 58\n ],\n [\n -140.92029001527425,\n 58\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
The Mount Blue Sky (formerly Mount Evans) 7.5’ quadrangle lies in Park and Clear Creek counties, Colorado, about 60 km west of Denver. The highest elevation in the quadrangle is 14,265 ft (4,348 m) at the top of Mount Blue Sky. The lowest is at about 9,200 ft (2,804 m) on Guanella Pass Road at the southern edge of the quadrangle. Bedrock directly underlies most of the map area, with surficial deposits primarily in the valleys. The geology of the quadrangle was previously mapped at 1:100,000 scale as part of a regional compilation by Kellogg and others (2008). The oldest rocks in the Mount Blue Sky 7.5-minute quadrangle are Paleoproterozoic metasedimentary rocks, and mafic to felsic metaigneous rocks (all units starting with ‘X’ on Plate 1). These rocks were metamorphosed under upper amphibolite facies conditions and intruded by Mesoproterozoic felsic igneous rocks of the ~1442 Ma Mount Blue Sky (YgR, Yt, Ygdm, Ymgm and ~1424 Ma Silver Plume (Yg) batholiths (Spurr and others, 1908; Tweto, 1897; Aleinikoff and others, 1993; du Bray and others, 2018) and, in the southern part of the quadrangle, by rocks that may also be part of the Mount Blue Sky batholith, but may alternatively interpreted as part of the ~1115 Ma to ~1066 Ma Pikes Peak batholith (Unruh and others, 1995; Guitreau and others, 2016). Four generations of folds affected the area. The oldest, F1 folds are isoclinal of various orientations, but primarily northerly-plunging in the southern part of the quadrangle (Mahatma, 2019; Mahatma and others, 2022). In the northern part of the quadrangle (Powell, 2020), open to close F2 chevron folds exist with various orientations. F3 folds in the northern part of the quadrangle are open to close with upright axial planes and plunges to the north and south, and in the southern part of the quadrangle they are open centimeter- to meter- scale northerly-plunging folds, possibly overprinted by another generation of northerly-plunging folds based on orientations of axial planes (F2 and F3 of Mahatma and others, 2022). F4 folds throughout the quadrangle are open to gentle with upright axial planes and shallow plunges to the east and west. The Mount Blue Sky batholith displays a pervasive moderately NW-dipping biotite-hornblende foliation (Fig. 1) in addition to a flow foliation near the margins, indicating NW-directed shortening after ~1442 Ma (Powell, 2020). The relationship between this foliation and the folds is not clear. Various joint sets are present in the area. The most pervasive joint set strikes 355°-020° and is subvertical. It is best developed in the western to southwestern part of the map area, and may be related to late Cenozoic extension associated with the Rio Grande Rift. Joint orientations are generally consistent with the trends of topographical lineaments. Surficial deposits include two series of glacial till deposits (Qtb and Qtp), and outwash (Qgp) deposits. They correlate with the Bull Lake (170-120 ka) and Pinedale (30-12 ka) glacial periods (Dahms, 2004) based on original depositional morphology, geomorphic and topographic position, deposit weathering and pedogenic properties. Possible older glacial deposits (Qti) have been observed along topographically higher surfaces.
","language":"English","publisher":"Colorado Geological Survey","usgsCitation":"Powell, L., Mahatma, A.A., Kuiper, Y., and Ruleman, C.A., 2022, Geologic map of the Mount Blue Sky (formerly Mount Evans) quadrangle, Clear Creek and Park Counties, Colorado: Open-File Report OF-22-11, 2 Plates: 33.00 x 31.50 inches and 41.00 x 31.00 inches: Data Files.","productDescription":"2 Plates: 33.00 x 31.50 inches and 41.00 x 31.00 inches: Data Files","ipdsId":"IP-139573","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":413293,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":413292,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://coloradogeologicalsurvey.org/publications/geologic-map-mount-evans-quadrangle-clear-creek-park-colorado/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Mount Evans quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.75,\n 39.625\n ],\n [\n -105.75,\n 39.5\n ],\n [\n -105.625,\n 39.5\n ],\n [\n -105.625,\n 39.625\n ],\n [\n -105.75,\n 39.625\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Powell, Logan 0000-0002-0528-3092 ljpowell@usgs.gov","orcid":"https://orcid.org/0000-0002-0528-3092","contributorId":299647,"corporation":false,"usgs":false,"family":"Powell","given":"Logan","email":"ljpowell@usgs.gov","affiliations":[{"id":64912,"text":"Colorado School of Mines MS Graduate","active":true,"usgs":false}],"preferred":false,"id":858245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahatma, Asha A.","contributorId":299648,"corporation":false,"usgs":false,"family":"Mahatma","given":"Asha","email":"","middleInitial":"A.","affiliations":[{"id":64913,"text":"Colorado School of Mines PhD Graduate","active":true,"usgs":false}],"preferred":false,"id":858246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuiper, Yvette 0000-0002-8506-8180","orcid":"https://orcid.org/0000-0002-8506-8180","contributorId":299649,"corporation":false,"usgs":false,"family":"Kuiper","given":"Yvette","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":858247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":858248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}