Historically, populations of Lost River suckers (Deltistes luxatus) of the Upper Klamath Basin were so numerous that they were commercially harvested; however, declining numbers throughout the 20th century led to the listing of the species under the United States Endangered Species Act in 1988. Habitat destruction, poor water quality, competition with (and predation by) nonnative species, especially fathead minnows (Pimephales promelas) and yellow perch (Perca flavescens), are hypothesized as primary causes of population decline (U.S. Fish and Wildlife Service, 2013). Age data indicate that almost all adult suckers presently in Upper Klamath Lake spawning populations were hatched in the early 1990s. While entrainment of young fish (especially larvae) may contribute, catch-at-length and age data suggest consistently high mortality during the first year of life may be preventing the recruitment of young adults. The specific causes of juvenile sucker mortality are unknown; however, the absence of juvenile suckers in trap net catches coincides with degraded water quality associated with the decay of cyanobacteria blooms and exposure to toxic microcystin produced by Microcystis cyanobacteria.
Water-quality data collected in Upper Klamath Lake from 2011 to 2016 suggest that microcystin concentrations in Upper Klamath Lake reached potentially lethal levels based on literature findings from studies on a variety of fish species. We conducted a laboratory feeding trial to determine if microcystin toxicity could potentially be a direct cause of juvenile Lost River sucker mortality. We examined the effects of environmentally relevant doses of microcystin on the survival and health of hatchery-reared juvenile Lost River suckers. Results from this laboratory study suggest that Lost River suckers are very tolerant of the microcystin-LR toxin. Histopathological analysis revealed no evidence of tissue changes associated with microcystin-LR exposure. Although no direct effects of microcystin-LR exposure were detected, suckers could potentially be negatively affected through added energy expenditures and stress associated with excretion of microcystin. Furthermore, microcystin may adversely affect other organisms in Upper Klamath Lake that could alter food availability or habitat of the suckers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191079","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and Bureau of Reclamation","usgsCitation":"Martin, B.A., Echols, K.R., Elliott, D.G., Feltz, K., Conway, C.M., and Burdick, S.M., 2019, Effects of microcystin-LR on juvenile Lost River suckers (Deltistes luxatus) during feeding trials, Upper Klamath Lake, Oregon, 2014−16: U.S. Geological Survey Open−File Report 2019–1079, 22 p., https://doi.org/10.3133/ofr20191079.","productDescription":"vi, 22 p.","onlineOnly":"Y","ipdsId":"IP-106575","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":365967,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1079/coverthb.jpg"},{"id":365968,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1079/ofr20191079.pdf","text":"Report","size":"7.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1079"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.08625793457031,\n 42.48222557002593\n ],\n [\n -122.09449768066405,\n 42.47361631282951\n ],\n [\n -122.05879211425781,\n 42.43004544849287\n ],\n [\n -122.04505920410156,\n 42.40976960320691\n ],\n [\n -122.01004028320312,\n 42.38847290951024\n ],\n [\n -121.99836730957031,\n 42.412304442420684\n ],\n [\n -121.97776794433594,\n 42.40013627993722\n ],\n [\n -121.97982788085938,\n 42.367676308265196\n ],\n [\n -121.9482421875,\n 42.39354420646467\n ],\n [\n -121.95922851562501,\n 42.42700448967684\n ],\n [\n -121.91665649414062,\n 42.36006607480819\n ],\n [\n -121.90292358398438,\n 42.357529125471395\n ],\n [\n -121.95098876953125,\n 42.341797753508665\n ],\n [\n -121.94618225097656,\n 42.30676863078423\n ],\n [\n -121.93313598632812,\n 42.2869609344916\n ],\n [\n -121.92420959472655,\n 42.284929023632834\n ],\n [\n -121.92283630371092,\n 42.30422953071753\n ],\n [\n -121.89193725585936,\n 42.31184652369511\n ],\n [\n -121.87889099121092,\n 42.293056273848215\n ],\n [\n -121.85897827148438,\n 42.267655135366624\n ],\n [\n -121.84593200683592,\n 42.254442496693386\n ],\n [\n -121.8438720703125,\n 42.242243757492766\n ],\n [\n -121.83425903320314,\n 42.23461834757937\n ],\n [\n -121.81022644042969,\n 42.23004265933714\n ],\n [\n -121.80335998535158,\n 42.24122708941077\n ],\n [\n -121.8109130859375,\n 42.25850821886463\n ],\n [\n -121.82807922363281,\n 42.28289704723818\n ],\n [\n -121.81846618652345,\n 42.29661161608281\n ],\n [\n -121.80816650390625,\n 42.3143853165376\n ],\n [\n -121.81571960449217,\n 42.33773740551283\n ],\n [\n -121.82533264160156,\n 42.34535034292539\n ],\n [\n -121.80885314941406,\n 42.38137240541685\n ],\n [\n -121.81777954101561,\n 42.40064333382955\n ],\n [\n -121.85966491699217,\n 42.437647200108685\n ],\n [\n -121.86927795410156,\n 42.44980808481614\n ],\n [\n -121.89056396484375,\n 42.44727476182866\n ],\n [\n -121.91253662109376,\n 42.47969355851231\n ],\n [\n -121.92008972167969,\n 42.48019996901214\n ],\n [\n -121.92420959472655,\n 42.49285889946235\n ],\n [\n -121.94000244140624,\n 42.49235259142821\n ],\n [\n -121.94000244140624,\n 42.500959270579585\n ],\n [\n -121.94892883300781,\n 42.49792175437361\n ],\n [\n -122.0086669921875,\n 42.49792175437361\n ],\n [\n -122.03407287597655,\n 42.500959270579585\n ],\n [\n -122.04849243164061,\n 42.49589666159403\n ],\n [\n -122.05879211425781,\n 42.48425110546248\n ],\n [\n -122.06359863281249,\n 42.461460050936715\n ],\n [\n -122.07527160644531,\n 42.46399280017058\n ],\n [\n -122.08625793457031,\n 42.48222557002593\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
For many years, marshes in the coastal areas from Texas to Louisiana have served as critical habitat for Anas fulvigula, the mottled duck. Mottled ducks are a priority species in the Texas/Louisiana Gulf Coast area and have been affected by critical habitat reduction. In recent years, mottled duck habitats have been threatened by natural and anthropogenic changes including urbanization, flooding, saltwater intrusion, and hydrologic alterations. These impacts are affecting the quality of habitat that is essential for the mottled duck nesting, feeding, and livelihood. Cumulative and synergistic effects of contamination and invasive species encroachment have also caused mottled duck habitat to be considered as some of the most critically endangered habitats in the United States. To help understand the environmental conditions that characterize the coastal landscape, U.S. Geological Survey researchers used an unmanned aerial system (UAS) to acquire high-resolution imagery to document current land and water spatial configuration and wetland health at McFaddin National Wildlife Refuge, Texas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191045","usgsCitation":"Jones, W.R., Hartley, S.B., Stagg, C.L., and Osland, M.J., 2019, Using UAS capabilities to help identify hummock-hollow formation and fragmentation in critical marsh habitat (Spartina patens) for mottled ducks in southeast Texas: U.S. Geological Survey Open-File Report 2019–1045, 6 p., https://doi.org/10.3133/ofr20191045.","productDescription":"6 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-105924","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365530,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1045/coverthb.jpg"},{"id":365531,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1045/ofr20191045.pdf","text":"Report","size":"4.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1045"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.66796875,\n 25.760319754713887\n ],\n [\n -93.6474609375,\n 25.760319754713887\n ],\n [\n -93.6474609375,\n 32.24997445586331\n ],\n [\n -99.66796875,\n 32.24997445586331\n ],\n [\n -99.66796875,\n 25.760319754713887\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
The U.S. Geological Survey Western Ecological Research Center, Pheasants Forever, Mandeville Island Duck Club, and the California Department of Fish and Wildlife collaborated in a reconnaissance study to monitor populations of ring-necked pheasant (Phasianus colchicus) using radio-telemetry in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin of northern California. The purpose of this study was to provide agencies and private landowners with a framework of decision-support tools to help manage pheasant populations in California. During winter, spring, and autumn of 2013–17, we radio- or Global Positioning System-marked 227 female pheasant across six study sites. Data collection was focused on investigating nest-site and brood-rearing habitat selection, examining avian predator composition, and estimating population vital rates to improve our understanding of pheasant population dynamics and to identify factors that may contribute to decreases in pheasant populations in California. The cumulative annual adult survival probability across all sites during 2013–17 was 27.6 percent (95-percent confidence interval [CI], 21.9–33.6), and the cumulative nest and brood survival probabilities were 34.5 percent (95-percent CI, 27.0–42.2) and 54.2 percent (95-percent CI, 43.7–63.5), respectively. Evidence from microhabitat surveys completed at nest-sites, brood locations, and random locations suggested that marked female pheasant tended to select increasing vertical cover and residual vegetation cover and tended to avoid areas of increasing bare ground cover regardless of life-history stage. However, females at nest-sites selected increasing grass cover and height, whereas brood-rearing females tended to select increasing forb cover and height. Only perennial grass cover and perennial grass height were shown to have a positive influence on nest survival, which suggests that increasing perennial grass cover in areas occupied by pheasant may increase nest survival. Analysis of environmental factors linked to vital rate information are ongoing and will continue with investigations at increased spatial scales (that is, macro-habitat) to develop integrated population models that can incorporate abundance estimates from crow count data with vital rates from telemetry data. This report includes results from 5 years of data collection and should be interpreted with caution, as these findings are preliminary.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191062","collaboration":"Prepared in cooperation with the California Department of Fish and Wildlife and Pheasants Forever","usgsCitation":"=Dwight, I.A., Coates, P.S., Vogt, J.H., Atkinson, J.L., Fleskes, J.P., Connelly, D.P., Meshriy, M.C., Gardner, S.C., Stoute, S.T., and Pitesky M.E., 2019, Monitoring breeding and survival of ring-necked pheasant (Phasianus colchicus) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, northern California—Five-year summary, 2013–17: U.S. Geological Survey Open-File Report 2019–1062, 90 p., https://doi.org/10.3133/ofr20191062.","productDescription":"90 p.","onlineOnly":"Y","ipdsId":"IP-099248","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":365826,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1062/ofr20191062.pdf","text":"Report","size":"44.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1062"},{"id":365825,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1062/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.9644775390625,\n 37.55328764595765\n ],\n [\n -119.5147705078125,\n 37.55328764595765\n ],\n [\n -119.5147705078125,\n 39.89709437260048\n ],\n [\n -122.9644775390625,\n 39.89709437260048\n ],\n [\n -122.9644775390625,\n 37.55328764595765\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive
Modoc Hall, Room 4004
Sacramento, California 95819
We present new geochronologic, isotopic, and geochemical data for selected igneous rocks in the Lane Mountain area, California. We determined SHRIMP-RG U-Pb zircon ages for the following units: (1) Larrea complex (~253 Ma and ~149–146 Ma); (2) Daisy granodiorite (~151 Ma); (3) Jack Spring quartz monzonite (~85–82 Ma); (4) unnamed porphyritic dikes and stocks (~80–73 Ma); and (5) Lane Mountain volcanics (~22 Ma). These results confirm and refine previous age determinations for the Larrea complex, Jack Spring quartz monzonite, and Lane Mountain volcanics, and provide the first reliable ages for the Daisy granodiorite and the unnamed porphyritic rocks. Sri of the plutonic rocks increases from ~0.704 to ~0.705–0.706 to ~0.708–0.709 for samples dated as ~250, ~150, and ~85–70 Ma, respectively, which indicates progressively greater involvement of Precambrian continental lithosphere in magma generation through time. The Sri and geochemical data suggest that the most significant change in magmatic source occurred between ~150 and 85 Ma.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191070","usgsCitation":"Stone, P., Brown, H.J., Cecil, M.R., Fleck, R.J., Vazquez, J.A., Fitzpatrick, J.A., and Rosario, J., 2019, Geochronologic, isotopic, and geochemical data from igneous rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2019–1070, 34 p., https://doi.org/10.3133/ofr20191070.","productDescription":"34 p.","onlineOnly":"Y","ipdsId":"IP-102033","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":414905,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221115","text":"Open-File Report 2022-1115","description":"Stone, P., Cecil, M.R., Brown, H.J., and Vazquez, J.A., 2023, Geochronologic and geochemical data from metasedimentary and associated rocks in the Lane Mountain area, San Bernardino 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Bernardino\",\"state\":\"CA\"}}]}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Hurricane Maria made landfall south of Yabucoa Harbor, Puerto Rico, as a category 4 hurricane with maximum sustained winds of 155 miles per hour on September 20, 2017. The hurricane devastated much of the U.S. Virgin Islands and Puerto Rico. The U.S. Geological Survey (USGS), in cooperation with Federal Emergency Management Agency, installed a temporary monitoring network of 13 water-level and barometric pressure sensors along the coast of Puerto Rico prior to the storm. In addition to the temporary sensors, the USGS maintains 99 permanent real-time streamgages and 36 real-time precipitation stations in Puerto Rico. The real-time data, updated hourly, during and after the hurricane are displayed in the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#MariaSeptember2017) and in the USGS National Water Information System.
The USGS measured 181 coastal and riverine high-water marks throughout Puerto Rico after the storm. Water elevations are referenced to the Puerto Rico Vertical Datum of 2002 (PRVD02) and local datums in Puerto Rico and to the U.S. Virgin Islands Vertical Datum of 2009 (VIVD09) in the U.S. Virgin Islands. Data from the Hurricane Maria storm-tide network are available in tab-delimited, American Standard Code for Information Interchange (ASCII) format and Network Common Data Form (NetCDF) format by site for each sensor through the USGS Flood Event Viewer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191065","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Byrne, M.J., Sr., 2019, Monitoring storm tide, flooding, and precipitation from Hurricane Maria in Puerto Rico and the U.S. Virgin Islands, September 2017: U.S. Geological Survey Open-File Report 2019–1065,16 p., https://doi.org/10.3133/ofr20191065.","productDescription":"vi, 16 p.","numberOfPages":"26","onlineOnly":"N","ipdsId":"IP-097015","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":365764,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1065/coverthb.jpg"},{"id":365765,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1065/ofr20191065.pdf","text":"Report","size":"4.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Rico\",\"nation\":\"USA \"}}]}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Hydro-Eco Interactions Branch
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, during October 2015 through September 2016 (water year 2016) and October 2016 through September 2017 (water year 2017). Major findings for this period include the following:
Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
This publication consists of three map sheets that display shallow geologic structure, along with sediment distribution and thickness, for an about 225-km-long offshore section of the central California coast between Point Sur and Point Arguello. Each map sheet includes three maps, at scales of either 1:150,000 or 1:200,000, as well as a set of figures that contain representative high-resolution seismic-reflection profiles. The maps and seismic-reflection surveys cover most of the continental shelf in this region. In addition, the maps show the locations of the shelf break and the 3-nautical-mile limit of California’s State Waters.
The seismic-reflection data, which are the primary dataset used to develop the maps, were collected to support the California Seafloor Mapping Program and U.S. Geological Survey Offshore Geologic Hazards projects. In addition to the three map sheets, this publication includes geographic information system data files of interpreted faults, folds, sediment thicknesses, and depths-to-base of sediment. The faults and folds shown on the maps have been locally simplified as appropriate for the map scales.
The right-lateral San Gregorio–Hosgri Fault (SGHF) is the most significant structure in the map area. On a regional scale, the SGHF is part of a 400-km-long, right-lateral fault system that extends northwestward from Point Arguello to the area offshore of San Francisco, where it merges with the San Andreas Fault. From north to south in this part of central California, the SGHF lies offshore between the south flank of Point Sur and the north flank of Point Piedras Blancas, then comes onshore at Point Piedras Blancas, before heading offshore again between the south flank of Point Piedras Blancas and Point Arguello. Cumulative fault offset along the SGHF is as much as 150 to 160 km, decreasing to the south by transferring slip on to northwest-striking faults that converge with the SGHF both onland and offshore from the east. In the map area, the offshore-converging faults include the Los Osos Fault, the Shoreline–Point Buchon Fault, the Casmalia Fault, and the Lions Head Fault.
Quaternary sediments and bedrock underlie the shelf. On the seismic-reflection profiles, we divide Quaternary shelf sediments into two units. Characterizing the younger, upper unit is a focus of this publication. This unit is inferred to have been deposited on the shelf in the last about 21,000 years during the sea-level rise that followed the last major lowstand and the Last Glacial Maximum (LGM). This upper unit overlies a transgressive surface of erosion, a commonly angular, wave-cut unconformity, and is generally characterized by low-amplitude, continuous to moderately continuous, diffuse, subparallel, generally flat reflections. Maps in this publication show both the thickness of this upper sediment unit and the depth to the base of the sediment unit. Within the map region, 11 different “domains” of post-LGM shelf sediment are delineated on the basis of sediment thickness and coastal geomorphology. Maximum sediment thickness is in the southern part of the region, offshore of the mouths of the Santa Ynez and Santa Maria Rivers. Minimum sediment thickness is found offshore of prominent rocky points, including Point Buchon and Piedras Blancas. Mean sediment thickness for the entire shelf in the map area between Point Sur and Point Arguello is 12.2 m, and total sediment volume is 24.7 million cubic meters.
Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Water, bed sediment, and biota were sampled in selected streams from Butte to near Missoula, Montana, as part of a monitoring program in the Clark Fork Basin of western Montana. The sampling program was led by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to characterize aquatic resources in the Clark Fork Basin and emphasize trace elements associated with historic mining and smelting activities. Sampling sites were on the Clark Fork and selected tributaries. Water samples were collected periodically at 20 sites from October 2016 through September 2017. Bed-sediment and biota samples were collected once at 13 sites during August 2017.
This report presents the analytical results and quality-assurance data for water-quality, bed-sediment, and biota samples collected at sites from October 2016 through September 2017. Water-quality data include concentrations of selected major ions, dissolved organic carbon, turbidity, nitrogen (nitrate plus nitrite), trace elements, and suspended sediment. Seasonal daily values of turbidity were determined at four sites. Bed-sediment data include trace-element concentrations in the fine-grained (less than 0.063 millimeter) fraction. Biological data include trace-element concentrations in whole-body tissue of aquatic benthic insects. Statistical summaries of water-quality, bed-sediment, and biological data for sites in the Clark Fork Basin are provided for the period of record.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191060","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Cleasby, T.E., Hornberger, M.I., Heinert, T.L., and Turner, M.A., 2019, Water-quality, bed-sediment, and biological data (October 2016 through September 2017) and statistical summaries of data for streams in the Clark Fork Basin, Montana: U.S. Geological Survey Open-File Report 2019–1060, 110 p., https://doi.org/10.3133/ofr20191060.","productDescription":"Report: v, 110 p.; Data Release","numberOfPages":"120","onlineOnly":"Y","ipdsId":"IP-102556","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":365345,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YX9400","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Water-quality, bed-sediment, and biological data (October 2016 through September 2017) and statistical summaries of data for streams in the Clark Fork Basin, Montana"},{"id":365352,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1060/ofr20191060_v6.pdf","text":"Report","size":"2.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1060"},{"id":365343,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1060/coverthb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.169921875,\n 46.6795944656402\n ],\n [\n -114.19189453125,\n 46.37725420510028\n ],\n [\n -113.22509765625,\n 46.263442671779885\n ],\n [\n -113.170166015625,\n 45.66780526567164\n ],\n [\n -112.269287109375,\n 45.62172169252446\n ],\n [\n -112.137451171875,\n 46.38483322349276\n ],\n [\n -112.576904296875,\n 47.21956811231547\n ],\n [\n -114.27978515625,\n 47.264320080254805\n ],\n [\n -114.169921875,\n 46.6795944656402\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
The Pahranagat roundtail chub (Gila robusta jordani; hereinafter “chub”) was federally listed as endangered in 1970 (U.S. Fish and Wildlife Service, 1970). In the decades following the listing, the chub has declined to extremely low numbers (Tuttle and others, 1990; Guadalupe, 2014). Loss of available habitat appears to be one of the main reasons for the decline of this species. Historically, the chub are assumed to have had approximately 30 kilometers (km) of habitat available to them, whereas currently they appear to primarily occupy 3.5 km of the Pahranagat River, up to 2.5 km of the Pahranagat Ditch, and a small portion of the Pahranagat Drain. Each year in mid-March, a gate at the top of the fish passage structure is closed to divert water down the Pahranagat Ditch, almost completely eliminating any flow into the Pahranagat Drain. The gate is usually removed in mid-October, allowing for flow to reoccur in the Pahranagat Drain. Due to the intermittent nature of the Pahranagat Drain, it is considered a sink for the species, and yearly salvage operations are conducted to remove chub from the Pahranagat Drain. The lower portion of the Pahranagat Ditch is also thought to be a sink for the species, due to high flows and limited structure potentially pushing the chub out of the system. Movements of passive-integrated-transponder (PIT) tagged chub indicate that adults and larger juveniles are not likely to be swept downstream to the point of exiting the system; however, the smaller juveniles and larvae are likely to be entrained in the Pahranagat Drain and possibly the lower portion of the Pahranagat Ditch. Only 2 of 64 PIT-tagged chub (3 percent) were observed to exit the system through the Pahranagat Ditch as they were last recorded on the Lower Ditch antenna. No PIT-tagged chub was observed exiting the system through the Pahranagat Drain.
Although capture location was a good predictor of where PIT tagged fish were primarily detected, fish were observed to meander throughout the available habitat. Chub captured and released in the Pahranagat River were detected more often in the upper portion of the Pahranagat River, whereas chub captured and released in the Pahranagat Ditch were more often detected in and near the Pahranagat Ditch. This suggests some degree of site fidelity. However, the two chub that were captured in the Pahranagat Drain and relocated into the middle portion of the Pahranagat River near the Between Bridges antenna were not able to get back to the closed off Pahranagat Drain (closed to fish passage from mid-March through mid-October), but were primarily detected in and near the Pahranagat Ditch. Movements from one end of the system to the other end of the system (3.5 km) could occur within a day and there were no observed seasonal location preferences for the chubs. However, there was more activity in the uppermost sites during fall and winter, presumedly associated with spawning. Furthermore, chub were found to be more active during the daylight hours in fall and winter verses spring and summer. During summer, chubs were the least active, especially during daylight hours.
Most of the fish tagged were estimated to be adults based on size; 84 percent of fish tagged in this study were greater than 100 millimeters (mm) total length (TL). One chub monitored during this study (139 mm TL when tagged) was observed for a total of 714 days following capture, indicating that chub can survive at least 3 years. Furthermore, two fish greater than 200 mm TL when tagged were detected for another 7 months after tagging, which supports life history descriptions in the Recovery Plan that states Pahranagat roundtail chub can reach 250 mm TL (U.S. Fish and Wildlife Service, 1998). In addition to natural mortality events, fish may die from extreme temperatures or other environmental stressors. None of the fish tagged in 2014 or 2015 were detected past August 31, 2016, which suggests that there may have been some external influence causing mortality of the few remaining fish from May 1, 2016, to August 31, 2016. Although habitat for chub has been limited for decades to a very small section of the Pahranagat River and the Pahranagat Ditch (U.S. Fish and Wildlife Service, 1998), this study suggests that recent declining numbers of chub are most likely due to mortality events and not due to the fish emigrating from the system through the Pahranagat Ditch or the Pahranagat Drain.
Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
No abstract available.
","language":"English","publisher":"Wyoming State Geological Survey Publications","usgsCitation":"Zellman, M.S., DuRoss, C., and Thackray, G.R., 2019, The Teton fault: Open-File Report 2019-1, Sheet: 30 x 42 inches.","productDescription":"Sheet: 30 x 42 inches","ipdsId":"IP-106316","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370488,"type":{"id":15,"text":"Index Page"},"url":"https://sales.wsgs.wyo.gov/the-teton-fault-2019/"},{"id":371085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"projection":"75000","country":"United States","state":"Wyoming","county":"Teton County","otherGeospatial":"Teton Fault","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.0551,44.6669],[-110.6668,44.6667],[-110.6666,44.5836],[-110.3748,44.5834],[-110.3762,44.5794],[-110.3717,44.5741],[-110.3713,44.5718],[-110.373,44.569],[-110.3783,44.5681],[-110.3834,44.5653],[-110.3825,44.5636],[-110.3788,44.5628],[-110.3716,44.5602],[-110.3647,44.5565],[-110.362,44.5539],[-110.3528,44.5522],[-110.3381,44.5487],[-110.3324,44.5484],[-110.3314,44.5497],[-110.3298,44.5543],[-110.314,44.5556],[-110.3059,44.5532],[-110.2953,44.5473],[-110.2902,44.5423],[-110.2899,44.5397],[-110.295,44.5376],[-110.298,44.5285],[-110.293,44.5279],[-110.2862,44.5268],[-110.2782,44.5205],[-110.2761,44.5153],[-110.279,44.5103],[-110.2769,44.4989],[-110.2814,44.4946],[-110.2839,44.4892],[-110.2813,44.4756],[-110.288,44.4737],[-110.2908,44.4712],[-110.2892,44.4676],[-110.2903,44.4609],[-110.289,44.4512],[-110.2965,44.4333],[-110.2966,44.4319],[-110.295,44.4288],[-110.2921,44.4275],[-110.2888,44.4248],[-110.2867,44.4192],[-110.2784,44.4142],[-110.2737,44.4128],[-110.2708,44.4129],[-110.2632,44.4105],[-110.2593,44.4094],[-110.255,44.4053],[-110.2543,44.4008],[-110.253,44.3953],[-110.2541,44.3904],[-110.2501,44.3891],[-110.2433,44.3876],[-110.2409,44.385],[-110.2386,44.3842],[-110.2345,44.3818],[-110.2314,44.3779],[-110.2281,44.3742],[-110.229,44.3712],[-110.2277,44.3686],[-110.2269,44.3645],[-110.2261,44.3613],[-110.2274,44.3588],[-110.2254,44.3515],[-110.2242,44.3498],[-110.2231,44.3469],[-110.2239,44.3438],[-110.2254,44.3423],[-110.2248,44.3408],[-110.2242,44.3377],[-110.2219,44.3348],[-110.2168,44.3316],[-110.2044,44.3288],[-110.2012,44.3274],[-110.2007,44.3246],[-110.2059,44.3189],[-110.2011,44.3129],[-110.2054,44.3105],[-110.202,44.3058],[-110.1969,44.3061],[-110.1905,44.3013],[-110.1865,44.3013],[-110.1853,44.3049],[-110.1864,44.3084],[-110.1847,44.3095],[-110.1812,44.3084],[-110.1809,44.3059],[-110.1791,44.3043],[-110.1762,44.3045],[-110.1723,44.302],[-110.174,44.2991],[-110.1669,44.2981],[-110.1591,44.2962],[-110.1515,44.2926],[-110.1496,44.2904],[-110.1438,44.2824],[-110.144,44.2783],[-110.1398,44.276],[-110.1405,44.2743],[-110.1478,44.2722],[-110.1484,44.271],[-110.1456,44.2649],[-110.1402,44.2634],[-110.1419,44.2566],[-110.1348,44.2466],[-110.1349,44.238],[-110.1314,44.2271],[-110.1275,44.2227],[-110.1271,44.2198],[-110.1245,44.218],[-110.124,44.2165],[-110.1141,44.2168],[-110.1093,44.21],[-110.1201,44.208],[-110.1234,44.2055],[-110.1199,44.1998],[-110.1119,44.2006],[-110.1077,44.1941],[-110.11,44.1924],[-110.1195,44.1952],[-110.12,44.1953],[-110.1232,44.1939],[-110.1149,44.1836],[-110.1069,44.1871],[-110.1037,44.1857],[-110.1088,44.1785],[-110.1138,44.1795],[-110.1221,44.1749],[-110.1153,44.168],[-110.1274,44.159],[-110.1245,44.1546],[-110.1246,44.1444],[-110.1171,44.1333],[-110.0527,44.133],[-110.0553,44.0061],[-110.0545,43.4666],[-110.0547,43.452],[-110.0538,43.3797],[-110.1117,43.3797],[-110.1584,43.3798],[-110.3456,43.3807],[-110.3456,43.3252],[-110.3457,43.2938],[-110.5824,43.2939],[-110.5774,43.2353],[-110.813,43.2357],[-110.8178,43.2945],[-110.8964,43.2937],[-110.9285,43.293],[-110.9276,43.3148],[-110.9716,43.3148],[-111.0436,43.3136],[-111.0439,43.4998],[-111.0449,43.5005],[-111.045,43.5061],[-111.0449,43.5503],[-111.045,43.5553],[-111.0453,43.5695],[-111.0454,43.6501],[-111.0455,43.7275],[-111.0461,43.8821],[-111.0466,43.9855],[-111.0466,43.9885],[-111.047,44.0327],[-111.0477,44.1102],[-111.0479,44.1351],[-111.0481,44.2269],[-111.0482,44.2418],[-111.0487,44.4772],[-111.0551,44.6669]]]},\"properties\":{\"name\":\"Teton\",\"state\":\"WY\"}}]}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zellman, M. S.","contributorId":221613,"corporation":false,"usgs":false,"family":"Zellman","given":"M.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":779144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":779145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thackray, Glenn R.","contributorId":221430,"corporation":false,"usgs":false,"family":"Thackray","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":40375,"text":"Department of Geosciences, Idaho State University","active":true,"usgs":false}],"preferred":false,"id":779146,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203473,"text":"ofr20191056 - 2019 - Optimization of salt marsh management at the Chincoteague National Wildlife Refuge, Virginia, through use of structured decision making","interactions":[],"lastModifiedDate":"2024-03-04T18:44:10.106398","indexId":"ofr20191056","displayToPublicDate":"2019-06-28T13:45:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1056","displayTitle":"Optimization of Salt Marsh Management at the Chincoteague National Wildlife Refuge, Virginia, Through Use of Structured Decision Making","title":"Optimization of salt marsh management at the Chincoteague National Wildlife Refuge, Virginia, through use of structured decision making","docAbstract":"Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing salt marsh management decisions at the Chincoteague National Wildlife Refuge in Virginia. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 12 salt marsh management units within the refuge and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per salt marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $2.5 million, but that further expenditures may yield diminishing return on investment. For multiple salt marsh management units, a scenario incorporating managing grazing practices within the marsh was selected to maximize benefits while constraining total costs for the refuge at less than $2.5 million. Thin-layer deposition was predicted to increase the total management benefit substantially, but at considerable total costs ($2.5 million to $83 million). The prototype presented here provides a framework for decision making at the Chincoteague National Wildlife Refuge that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191056","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., and Holcomb, K.S., 2019, Optimization of salt marsh management at the Chincoteague National Wildlife Refuge, Virginia, through use of structured decision making: U.S. Geological Survey Open-File Report 2019–1056, 29 p., https://doi.org/10.3133/ofr20191056.","productDescription":"vi, 29 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101219","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":364633,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1056/coverthb.jpg"},{"id":364634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1056/ofr20191056.pdf","text":"Report","size":"2.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1056"}],"country":"United States","state":"Virginia","otherGeospatial":"Chincoteague Island, Chincoteague National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.38440704345703,\n 37.91278405007035\n ],\n [\n -75.3830337524414,\n 37.916169765380076\n ],\n [\n -75.37445068359375,\n 37.917117737741826\n ],\n [\n -75.37273406982422,\n 37.916576040745376\n ],\n [\n -75.36895751953125,\n 37.91468006984207\n ],\n [\n -75.36449432373047,\n 37.91562806140234\n ],\n [\n -75.35608291625977,\n 37.91562806140234\n ],\n [\n -75.35076141357422,\n 37.91684688974227\n ],\n [\n -75.34818649291992,\n 37.920367835943516\n ],\n [\n -75.34629821777344,\n 37.924565666890146\n ],\n [\n -75.34406661987303,\n 37.9276800317787\n ],\n [\n -75.34046173095703,\n 37.936074619194514\n ],\n [\n -75.33823013305664,\n 37.93945926228315\n ],\n [\n -75.34475326538086,\n 37.94094845586459\n ],\n [\n -75.34612655639648,\n 37.947040297194114\n ],\n [\n -75.34114837646484,\n 37.953673061162604\n ],\n [\n -75.33102035522461,\n 37.958681077955525\n ],\n [\n -75.32638549804688,\n 37.958004338883114\n ],\n [\n -75.32655715942383,\n 37.96720745598712\n ],\n [\n -75.31213760375975,\n 37.98141588591056\n ],\n [\n -75.31848907470703,\n 37.983310135428795\n ],\n [\n -75.3219223022461,\n 37.98019812825676\n ],\n [\n -75.32432556152342,\n 37.98182180063798\n ],\n [\n -75.32827377319335,\n 37.982904228934125\n ],\n [\n -75.33102035522461,\n 37.98141588591056\n ],\n [\n -75.33187866210936,\n 37.97153793552019\n ],\n [\n -75.33308029174805,\n 37.968966744104264\n ],\n [\n -75.33565521240234,\n 37.96829009981737\n ],\n [\n -75.34097671508789,\n 37.9630120603577\n ],\n [\n -75.34664154052734,\n 37.959493156611366\n ],\n [\n -75.35642623901367,\n 37.953266990781884\n ],\n [\n -75.36518096923828,\n 37.94568659832042\n ],\n [\n -75.36792755126953,\n 37.942166864531906\n ],\n [\n -75.36672592163085,\n 37.94798787156644\n ],\n [\n -75.3691291809082,\n 37.94988298364895\n ],\n [\n -75.37359237670898,\n 37.94825860485678\n ],\n [\n -75.37445068359375,\n 37.944874367025136\n ],\n [\n -75.37273406982422,\n 37.94162535206254\n ],\n [\n -75.37256240844727,\n 37.93851157792925\n ],\n [\n -75.377197265625,\n 37.935262281661146\n ],\n [\n -75.38389205932617,\n 37.932554425046405\n ],\n [\n -75.39127349853516,\n 37.92402402474885\n ],\n [\n -75.39505004882812,\n 37.916305190751174\n ],\n [\n -75.40895462036133,\n 37.90492859043573\n ],\n [\n -75.40672302246094,\n 37.89937508713545\n ],\n [\n -75.40157318115234,\n 37.898020510564386\n ],\n [\n -75.39573669433594,\n 37.89896871678171\n ],\n [\n -75.39281845092773,\n 37.899781455245545\n ],\n [\n -75.38818359375,\n 37.89910417381559\n ],\n [\n -75.38320541381836,\n 37.90072963877702\n ],\n [\n -75.38114547729492,\n 37.90398046100267\n ],\n [\n -75.3823471069336,\n 37.90858554667319\n ],\n [\n -75.38440704345703,\n 37.91115885137137\n ],\n [\n -75.38440704345703,\n 37.91278405007035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
Populations of Northern Spotted Owls (Strix occidentalis caurina; herineafter referred to as Spotted Owl) have declined throughout the subspecies’ geographic range. Evidence indicates that competition with invading Barred Owls (S. varia) has contributed significantly to those declines. A pilot study in California showed that removal of Barred Owls coupled with conservation of suitable habitat conditions can slow or even reverse population declines of Spotted Owls. It is unknown, however, whether similar results can be obtained in areas with different forest conditions, greater densities of Barred Owls, and fewer remaining Spotted Owls. We initiated a before-after-control-impact (BACI) experiment at three study areas in Oregon and Washington to determine if removal of Barred Owls can improve population trends of Spotted Owls. This report describes research accomplishments and initial results from the first 3.5 years of the study (March 2015–August 2018).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191074","usgsCitation":"Wiens, J.D., Dugger, K.M., Lesmeister, D.B., Dilione, K.E., and Simon, D.C., 2019, Effects of Barred Owl (Strix varia) removal on population demography of Northern Spotted Owls (Strix occidentalis caurina) in Washington and Oregon, 2015–18: U.S. Geological Survey Open-File Report 2019-1074, 17 p., https://doi.org/10.3133/ofr20191074.","productDescription":"vi, 17 p.","onlineOnly":"Y","ipdsId":"IP-108218","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":365174,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1074/coverthb.jpg"},{"id":365175,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1074/ofr20191074.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1074"}],"country":"United States","state":"Oregon, Washington","city":"Cle Elum","otherGeospatial":"Oregon Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.9093017578125,\n 43.79885402720353\n ],\n [\n -122.3382568359375,\n 43.79885402720353\n ],\n [\n -122.3382568359375,\n 45.41773242370463\n ],\n [\n -123.9093017578125,\n 45.41773242370463\n ],\n [\n -123.9093017578125,\n 43.79885402720353\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.991943359375,\n 42.532844281713125\n ],\n [\n -120.86608886718749,\n 42.532844281713125\n ],\n [\n -120.86608886718749,\n 43.55252937447483\n ],\n [\n -122.991943359375,\n 43.55252937447483\n ],\n [\n -122.991943359375,\n 42.532844281713125\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.37695312499999,\n 46.619261036171515\n ],\n [\n -120.14648437499999,\n 46.619261036171515\n ],\n [\n -120.14648437499999,\n 47.73932336136857\n ],\n [\n -121.37695312499999,\n 47.73932336136857\n ],\n [\n -121.37695312499999,\n 46.619261036171515\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
We present a petrologic and mineral physics database as part of the U.S. Geological Survey National Crustal Model (NCM). Each of 209 geologic units, 134 of which are currently part of the geologic framework within the NCM, was assigned a mineralogical composition according to generalized classifications with some refinement for specific geologic formations. This report is concerned with the petrology and mineral physics of each geologic unit within the NCM, which control the physical behavior of the solid mineral matrix within the rock.
This mineral physics database builds on the work of Abers and Hacker to include 13 minerals specific to continental rock types. We explored the effect of this database on zero-porosity anharmonic P- and S-wave rock velocities and density relative to a well-used empirical study of relations between wavespeeds and density by Brocher. We found that empirical relations between P-wave velocity and S-wave velocity or density do well on average but can differ from mineral physics calculations by up to 15 percent in S-wave velocity and almost 40 percent in density. This is consistent with Brocher’s study where he obtained similar results for in situ measurements and laboratory rock specimens.
Additionally, the substantial presence of quartz in many rocks plays a major role in crustal seismic velocities and density due to quartz’s α–β phase transition, which can interfere with these empirical relationships. With increasing depth, quartz P-wave velocity can suddenly jump by 15 percent accompanied by little change in S-wave velocity and a modest decrease in density. Empirical relations based on observed P-wave velocity where P-wave velocity is positively correlated with S-wave velocity and density would then significantly overestimate both S-wave velocity and density.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191035","usgsCitation":"Sowers, T., and Boyd, O.S., 2019, Petrologic and mineral physics database for use with the U.S. Geological Survey National Crustal Model: U.S. Geological Survey Open-File Report 2019–1035, 17 p.,https://doi.org/10.3133/ofr20191035.","productDescription":"17 p.","onlineOnly":"Y","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437403,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FK25WM","text":"USGS data release","linkHelpText":"MinVel"},{"id":364257,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HN170G","text":"USGS data release","linkHelpText":"Petrologic and Mineral Physics Database for use with the USGS National Crustal Model - Data Release"},{"id":365082,"rank":4,"type":{"id":4,"text":"Application Site"},"url":"https://github.com/usgs/MinVel","text":"MinVel ","linkHelpText":"software that supports this report is available in the GitHub repository."},{"id":364255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1035/coverthb.jpg"},{"id":364256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1035/ofr20191035.pdf","text":"Report","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1035"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS-966
Denver, CO 80225-0046
Since 2014, the U.S. Geological Survey has been working in cooperation with the Bureau of Land Management, Mono County, Ormat Technologies, Inc., and the Mammoth Community Water District to design and implement a groundwater-monitoring program for the proposed Casa Diablo IV Geothermal Power Project in Long Valley Caldera, California, to characterize baseline groundwater-level, water-temperature, and water-chemistry conditions at dedicated monitoring wells and municipal supply wells. The publicly available data and the analyses provided here represent quality-assured and peer-reviewed information to help with the management of the thermal and non-thermal water resources beneath and in the vicinity of the town of Mammoth Lakes, California.
The methods of data collection for continuous water levels and quarterly water-temperature profiles for two 600-foot-deep monitoring wells during 2016 through 2017 are discussed. Also discussed are the methods of water-sample collection and characterizations of the water chemistry in numerous wells in the multilayered aquifer system beneath Mammoth Lakes. Additionally, the methodology used to develop digital (mathematical) filters to remove or reduce the effects of barometric pressure and solid Earth tides on the continuous water-level records is discussed.
Digitally filtered water levels for a 2017 flow test of a deep geothermal production well are described, and various aquifer responses observed during the flow test are discussed. These are further considered in a companion evaluation of potential physical and chemical influences on the water-level data collected during the flow test.
The digitally filtered water-level data indicated that some hydraulic communication exists between the deep geothermal aquifer and shallow groundwater aquifer at the location of the flow test, northeast of Mammoth Lakes. Groundwater-chemistry data from three wells indicated that shallow groundwater naturally mixes with a small component of geothermal water along the northern periphery of the shallow aquifer system at Mammoth Lakes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191063","usgsCitation":"Howle, J.F., Evans, W.C., Galloway, D.L., Hsieh, P.A., Hurwitz, S., Smith, G.A., and Nawikas, J., 2019, Hydraulic, geochemical, and thermal monitoring of an aquifer system in the vicinity of Mammoth Lakes, Mono County, California, 2015–17: U.S. Geological Survey Open-File Report 2019–1063, 90 p., https://doi.org/10.3133/ofr20191063.","productDescription":"Report: xii, 90 p.; Data Release","numberOfPages":"90","onlineOnly":"Y","ipdsId":"IP-098793","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437404,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ON8U5U","text":"USGS data release","linkHelpText":"Atmospheric-loading frequency response functions and groundwater-levels filtered for the effects of atmospheric loading and solid Earth tides for three monitoring wells near Mammoth Lakes, California, 2015 - 2017"},{"id":365075,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5bdc7dcee4b0b3fc5cf01d9d","linkHelpText":"Atmospheric-loading frequency response functions and groundwater-levels filtered for the effects of atmospheric loading and solid Earth tides for three monitoring wells near Mammoth Lakes, California, 2015–2017"},{"id":364987,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1063/coverthb.jpg"},{"id":364988,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1063/ofr20191063.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1063"}],"country":"United States","state":"California","county":"Mono 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California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Coral reefs are widely recognized as critical to Hawaiʻi’s economy, food resources, and protection from damaging storm waves. Yet overfishing, land-based pollution, and climate change are threatening the health and sustainability of those reefs, and accordingly, both the Federal and State governments have called for protection and effective management. In 2000, the U.S. Coral Reef Task Force stated that 20 percent of coral reefs should be protected by 2010. In 2016, the Governor of Hawaiʻi committed to effective management of 30 percent of Hawaiian coastal habitats by 2030 to protect coral reefs. At present, the amount of coral protected in the main Hawaiian Islands is less than 1 percent.
Most of the large, highly diverse coral reef tracts in the main Hawaiian Islands surround the four islands of Maui, Molokaʻi, Lānaʻi, and Kahoʻolawe, collectively known as Maui Nui. This report provides fundamental information on the location, extent, coral cover, threats, and connectivity of these major coral reef tracts in Maui Nui essential for identifying areas for management and protection.
By combining high-resolution bathymetric data with available maps, publications, and satellite and underwater images, nine major coral reef tracts are identified in the coastal waters of Maui Nui. Three very large reef tracts lie along the south side of Molokaʻi, two on the east side of Lānaʻi, and four off Maui. The factors that make these Maui Nui coral reef tracts a major and important resource for Hawaiʻi include their vast size and high coral cover (nearly 16,000 acres of reef, most of which has more than 50 percent live coral cover); diversity of shape, size, and location; and separation between reefs while retaining connectivity via currents. The decline in the health of these coral reefs over the past several decades has been slow but persistent. Punctuation of the decline by large-scale disturbance events, such as the thermal bleaching that occurred in 2015, is accelerating the loss of viable reef areas by an order of magnitude.
The economic, cultural, and recreational value of these coral reef tracts highlights the importance of their long-term survival to the local communities and all of Hawaiʻi. There is scientific consensus that increasing pressures from climate change, overfishing, and land-based pollution will virtually assure the continued, and perhaps accelerating, decline of Hawaiʻi’s coral reefs unless action is taken. Information presented in this report, coupled with the results of numerous scientific studies, provides scientific underpinning to help establish a network of large-scale, connected Marine Protected Areas to meet the Federal and State governments’ call for effective management and protection of coral reefs in Maui Nui.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191019","usgsCitation":"Field, M.E., Storlazzi, C.D., Gibbs, A.E., D’Antonio, N.L., and Cochran, S.A, 2019, The major coral reefs of Maui Nui, Hawai‘i—Distribution, physical characteristics, oceanographic controls, and environmental threats: U.S. Geological Survey Open-File Report 2019–1019, 71 p., https://doi.org/10.3133/ofr20191019.","productDescription":"Report: vi, 71 p.","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-096402","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":365042,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1019/ofr20191019.pdf","text":"Report","size":"31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1019"},{"id":365041,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1019/coverthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui Nui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.5439453125,\n 20.33432561683554\n ],\n [\n -155.6982421875,\n 20.33432561683554\n ],\n [\n -155.6982421875,\n 21.49396356306447\n ],\n [\n -157.5439453125,\n 21.49396356306447\n ],\n [\n -157.5439453125,\n 20.33432561683554\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
La Honda, California, is a small town in unincorporated San Mateo County, located on the west edge of the San Francisco Peninsula in the Santa Cruz Mountains, between San Francisco and San Jose. The Scenic Drive area of La Honda has experienced several past episodes of landslide motion, which were documented in 1998, 2005, and 2006. This report documents the movement of the upper Scenic Drive landslide that occurred between January 10 and June 28, 2017. Our mapping provides a snapshot of the 2017 upper Scenic Drive landslide, as imaged from high-resolution terrestrial laser scanner (TLS) survey data (also referred to as terrestrial lidar) that we collected January 27–28, 2017; we mapped the landforms associated with the 2017 upper Scenic Drive landslide motion using a bare-earth TLS shaded-relief base map, in addition to field observations. Our mapping is supplemented by photographs of the mapped landforms, which were taken between January 11 and 31, 2017; these photographs illustrate the development of selected landslide features. The purpose of this report is to make available the maps constructed from three-dimensional TLS data and the photographs that show the landslide morphology of the 2017 upper Scenic Drive landslide. The scope of this report is limited to the motion of the upper Scenic Drive landslide that occurred between January 10 and June 28, 2017.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191024","usgsCitation":"Pickering, A.J., Prentice, C.S., and DeLong, S.B., 2019, Landscape change associated with the upper Scenic Drive landslide, La Honda, California, January 10–June 28, 2017: U.S. Geological Survey Open-File Report 2019–1024, 17 p., 1 sheet, scale 1:400, https://doi.org/10.3133/ofr20191024.","productDescription":"Pamphlet: iv, 17 p.; one 32\" x 20\" Sheet; Metadata; Database","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-096298","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":364982,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1024/coverthb.jpg"},{"id":364983,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2019/1024/ofr20191024_mapsheet.pdf","text":"Mapsheet","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1024 Sheet"},{"id":364984,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1024/ofr20191024_pamphlet.pdf","text":"Pamphlet","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1024 Pamphlet"},{"id":364985,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2019/1024/ofr20191024_metadata.txt","text":"Metadata","size":"20 KB","linkFileType":{"id":2,"text":"txt"},"description":"Open-File Report 2019-1024 Metadata"},{"id":364986,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2019/1024/ofr20191024_gdb.zip","size":"80 KB","linkFileType":{"id":6,"text":"zip"},"description":"Open-File Report 2019-1024 Database"}],"country":"United States","state":"California","city":"La Honda","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.27036476135254,\n 37.31737642114842\n ],\n [\n -122.26358413696288,\n 37.31737642114842\n ],\n [\n -122.26358413696288,\n 37.32302474535866\n ],\n [\n -122.27036476135254,\n 37.32302474535866\n ],\n [\n -122.27036476135254,\n 37.31737642114842\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, California 94025
This report describes a software tool that calculates costs associated with the reconstruction of supply chain interdependent critical infrastructure in the advent of a catastrophic failure by either outside forces (extreme events) or internal forces (fatigue). This tool fills a gap between search and recover strategies of the Federal Emergency Management Agency (or FEMA) and construction techniques under full recovery. In addition to overall construction costs, the tool calculates reconstruction needs in terms of personnel and their required support. From these estimates, total costs (or the cost of each element to be restored) can be calculated. Estimates are based upon historic reconstruction data, although decision managers do have the choice of entering their own input data to tailor the results to a local area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191061","usgsCitation":"Ojha, A., Kanwar, B., Long, S.K., Shoberg, T.G., and Corns, S., 2019, Supply chain infrastructure restoration calculator software tool—Developer guide and user manual: U.S. Geological Survey Open-File Report 2019–1061, 17 p., https://doi.org/10.3133/ofr20191061.","productDescription":"iv, 17 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-101221","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":364946,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1061/coverthb.jpg"},{"id":364947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1061/ofr20191061.pdf","text":"Report","size":"2.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1061"}],"contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Hurricane Michael made landfall near Mexico Beach and Tyndall Air Force Base in the Florida Panhandle, with maximum sustained winds over 160 miles per hour, on October 10, 2018. The maximum recorded storm tide was 15.55 feet above the North American Vertical Datum of 1988 (NAVD 88). The elevation of the maximum high-water mark, found in Port St. Joe, Florida, exceeded 20 feet above NAVD 88. The storm tide and winds destroyed much of the tourist town of Mexico Beach and caused extensive damage to the surrounding communities, including Tyndall Air Force Base, Panama City Beach, Port St. Joe, and Cape San Blas, Fla.
The U.S. Geological Survey (USGS), in cooperation with Federal Emergency Management Agency and Florida Division of Emergency Management, deployed a temporary monitoring network of water-level and barometric pressure sensors at 34 sites along the northwest coast of Florida to record the timing, areal extent, and magnitude of hurricane storm tide generated by Hurricane Michael. A total of 522 high-water marks were recovered and surveyed from 331 sites from Seaside, Fla. to Cedar Key, Fla. The USGS, in cooperation with Federal Emergency Management Agency and Florida Division of Emergency Management, displays real-time water-level data from long-term USGS streamflow stations, rapid deployment gages and National Oceanic and Atmospheric Administration tide-gage stations, updated hourly (or, in some cases, more frequently), through satellite telemetry, on the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#Michael2018).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191059","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency and Florida Division of Emergency Management","usgsCitation":"Byrne, M.J., Sr., 2019, Monitoring storm tide from Hurricane Michael along the northwest coast of Florida, October 2018: U.S. Geological Survey Open-File Report 2019–1059, 10 p., https://doi.org/10.3133/ofr20191059.","productDescription":"vi, 10 p.","numberOfPages":"20","onlineOnly":"N","ipdsId":"IP-104232","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":364728,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1059/coverthb.jpg"},{"id":364729,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1059/ofr20191059.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1059"},{"id":399411,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_108709.htm"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.98974609375,\n 29.11377539511439\n ],\n [\n -82.96875,\n 29.11377539511439\n ],\n [\n -82.96875,\n 30.789036751261136\n ],\n [\n -86.98974609375,\n 30.789036751261136\n ],\n [\n -86.98974609375,\n 29.11377539511439\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
A trap-and-haul program is operated to move anadromous Pacific salmon (Oncorhynchus spp.) around dams and reservoirs in the Cowlitz River basin, Washington. The primary release site for adult fish is in Lake Scanewa, a small reservoir created by Cowlitz Falls Dam, the uppermost dam in the basin. Releases in the reservoir are terminated when reservoir water temperature is 16 degrees Celsius (°C) or greater to reduce the risk of exposing adult salmon and steelhead (O. mykiss) to thermal conditions known to be stressful for these species. When the water temperature limit is reached, fish are released into the Cowlitz and Cispus Rivers upstream of the reservoir. Concerns have been raised about fish presence in the reservoir during warm conditions, so an empirical evaluation of water temperatures selected by spring Chinook salmon (O. tshawytscha) in Lake Scanewa was requested by resource managers. We conducted the evaluation during June–October 2012. Water temperature in the reservoir was measured using a series of thermographs combined with daily measurements at the Cowlitz Falls Fish Facility. Temperature-use data were collected from 50 adult hatchery-origin spring Chinook salmon tagged with temperature-sensing radio transmitters and released into the reservoir. This approach yielded a total of 930,056 individual temperature-use records in the reservoir during the study. Tagged fish occupied water temperatures less than 16 °C during most of the study period. Water temperatures ranged from 5 to 18.5 °C during the study, peaking in mid-August. Overall, about 25 percent of the detections of tagged fish were in water temperatures in the 16–20 °C range. In August, tagged fish detections in the 18–20 °C range comprised 13 percent of the total detections, and the remainder of the detections were in water less than or equal to 17 °C. Results from the study indicate that adult hatchery-origin spring Chinook salmon were able to locate and use water temperatures in the reservoir less than levels associated with stress. However, we also observed that thermal conditions in the reservoir were cool relative to most other years during 2008–16. Additional research may be warranted to better understand thermal exposure of adult spring Chinook salmon during warmer years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191055","collaboration":"Prepared in cooperation with Public Utility District Number 1 of Lewis County, Washington","usgsCitation":"Kock, T.J., Ekstrom, B.K., and Liedtke, T.L., 2018, Distribution of adult Chinook salmon (Oncorhynchus tshawytscha) in relation to water temperatures, Lake Scanewa, Cowlitz River, Washington, 2012: U.S. Geological Survey Open-File Report 2019-1055, 14 p., https://doi.org/10.3133/ofr20191055.","productDescription":"iv, 14 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-106983","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":364309,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1055/coverthb2.jpg"},{"id":364310,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1055/ofr20191055.pdf","text":"Report","size":"1.7 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\"}}]}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
2018 marked the 10-year anniversary of the establishment of the U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center! With the passage of the fiscal year 2018 budget on March 23, 2018, our program name was changed from the National Climate Change and Wildlife Science Center to the National Climate Adaptation Science Center (NCASC). The eight regional Department of the Interior (DOI) Climate Science Centers were renamed Climate Adaptation Science Centers (CASCs). The name changes more clearly align the national and regional centers and emphasize their focus on meeting natural resource adaptation needs. Although the program has a new name, our mission has not changed. We are still hard at work delivering science to help fish, wildlife, water, land, and people adapt to a changing climate.
During the past 10 years, the NCASC and the eight regional CASCs funded over 425 science projects and built a network of research partners, resource management stakeholders, interdisciplinary staff, fellows, and early career researchers. In celebration of our work and accomplishments over the last 10 years, the NCASC began a monthly web post series on “10 Things You May Not Know” about topics our science has focused on, including drought, glaciers, and wildfire.
Additionally, CASCs that had completed their initial hosting agreement with the USGS underwent a formal review and recompetition process. New hosting agreements were awarded to the Southwest and North Central CASCs in 2018. Read the 2018 annual report to learn more about the CASCs' great science, partnerships, capacity building, and more from 2018.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191041","usgsCitation":"Varela Minder, E., 2019, Climate Adaptation Science Centers—Annual report for 2018: U.S. Geological Survey Open-File Report 2019–1041, 14 p., https://doi.org/10.3133/ofr20191041.","productDescription":"14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103920","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":364065,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1041/ofr20191041.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1041"},{"id":364064,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1041/coverthb2.jpg"}],"contact":"Director, National Climate Adaptation Science Center
U.S. Geological Survey
Mail Stop 516
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, collected groundwater samples from 5 production wells and 5 domestic wells in the Delaware River Basin, 8 production wells and 7 domestic wells in the Genesee River Basin, and 1 municipal well, 7 production wells, and 13 domestic wells in the St. Lawrence River Basin in New York. All samples were collected from May through November 2015 in an effort to characterize groundwater quality in these basins. The samples were collected and processed by using standard U.S. Geological Survey procedures and were analyzed for 148 physiochemical properties and constituents, including dissolved gases, major ions, nutrients, trace elements, pesticides, volatile organic compounds, radionuclides, and indicator bacteria.
The Delaware River Basin study area covers 2,360 square miles (mi2) in southeastern New York. Of the 10 wells sampled in the Delaware River Basin, 3 are completed in sand and gravel, and 7 are completed in bedrock. Groundwater in the Delaware River Basin was generally of good quality, although properties and concentrations of some constituents—pH, iron, manganese, aluminum, radon-222, and total coliform bacteria—sometimes equaled or exceeded primary, secondary, or proposed drinking-water standards. The constituent most frequently detected in concentrations exceeding drinking-water standards (10 of 10 samples) was radon-222.
The Genesee River Basin study area includes the entire 2,439 mi2 of the basin in western New York. Of the 15 wells sampled in the Genesee River Basin, 6 are completed in sand and gravel, and 9 are completed in bedrock. Groundwater in the Genesee River Basin was generally of good quality, although properties and concentrations of some constituents—chloride, sodium, dissolved solids, iron, manganese, aluminum, arsenic, radon-222, methane, total coliform bacteria, fecal coliform bacteria, and Escherichia coli bacteria—sometimes equaled or exceeded primary, secondary, or proposed drinking-water standards. The constituent most frequently detected in concentrations exceeding drinking-water standards (12 of 15 samples) was radon-222.
The St. Lawrence River Basin study area includes the entire 5,650 mi2 of the basin in northeastern New York. Of the 21 wells sampled in the St. Lawrence River Basin, 7 are completed in sand and gravel, and 14 are completed in bedrock. Groundwater in the St. Lawrence River Basin was generally of good quality, although properties and concentrations of some constituents—pH, chloride, sodium, dissolved solids, iron, manganese, sulfate, nitrate, radon-222, total coliform bacteria, fecal coliform bacteria, and Escherichia coli bacteria—sometimes equaled or exceeded primary, secondary, or proposed drinking-water standards. The constituent most frequently detected in concentrations exceeding drinking-water standards (14 of 21 samples) was radon-222.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191005","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation ","usgsCitation":"Scott, T.-M., Nystrom, E.A., and Reddy, J.E., 2019, Groundwater quality in the Delaware, Genesee, and St. Lawrence River Basins, New York, 2015: U.S. Geological Survey Open-File Report 2019–1005, 42 p., 2 app., https://doi.org/10.3133/ofr20191005. ","productDescription":"Report: viii, 42 p.; 2 Appendixes ","numberOfPages":"54","ipdsId":"IP-086322","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":363728,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1005/ofr20191005_appendix1.xlsx","text":"Appendix 1","size":"85 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- tables 1.1 through 1.9 "},{"id":363729,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1005/ofr20191005_appendix2.xlsx","text":"Appendix 2","size":"86 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- tables 2.1 through 2.8 "},{"id":363730,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1005/ofr20191005.pdf","text":"Report","size":"14.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1005"},{"id":363755,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1005/ofr20191005_appendixes.zip","text":"Appendixes 1 and 2","size":"34 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- all tables in CSV format"},{"id":363727,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1005/coverthb.jpg"}],"country":"United States","state":"New 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York\",\"nation\":\"USA \"}}]}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180