Sandbars of large sand-bedded rivers of the central United States serve important ecological functions to many species, including the endangered Interior Least Tern (Sternula antillarum, ILT). The ILT is a colonial bird that feeds on fish and nests primarily on riverine sandbars during its annual breeding season of around May through July, depending on region. During this time, ILTs require bare sand of sufficient elevation so as not to be inundated between nest initiation and fledging of hatchlings. Partly because of decreases in available sandbar habitat from river channelization and impoundment, ILTs were listed as endangered in 1985.
Sandbars used by ILTs in central United States rivers are highly dynamic and undergo substantive changes across a wide range of temporal and spatial scales. River hydrology is the primary driver of sandbar morphodynamics in these systems. Better characterization of sandbar area with time, accounting for varying flow regimes, allows for a better understanding of landscape-scale ecology for sandbar-dependent species such as the ILT. This work uses remote-sensing techniques to quantify sandbar area that may be used by ILTs at the land-scape scale and how it has changed with time. The assessment of landscape-scale trends in sandbar area with time requires datasets with high temporal resolution and long record periods covering large geographic areas. Evaluation of remotely sensed datasets requires consideration of river stage fluctuations. To make this assessment, we developed land-cover classification datasets within active channel masks using all available images from the Landsat Thematic Mapper series of satellites meeting cloud-free (40 percent or less) and ice-free criteria. Landsat imagery was selected because of its long record period, spatial coverage, and regular reimaging cycle, making it well suited to monitor ILT sandbar habitat with time. We also attributed each scene with discharge or stage using a new database integrating U.S. Geological Survey and U.S. Army Corps of Engineers river data with Landsat metadata. This report documents development of these riverine classification datasets with a focus on applicability to the ILT. This framework may be used to continue monitoring the ILT sandbar nesting habitat or to evaluate other aquatic and terrestrial species whose life cycles are related to sandbars and channel complexity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1098","collaboration":"Prepared in cooperation with the American Bird Conservancy","usgsCitation":"Bulliner, E.A., Elliott, C.M., Jacobson, R.B., and Lott, C., 2018, Interior Least Tern sandbar nesting habitat measurements from Landsat Thematic Mapper imagery: U.S. Geological Survey Data Series 1098, 32 p., https://doi. org/10.3133/ds1098. ","productDescription":"Report: v, 32 p.; Tables 9–12; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066937","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":360602,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/1098/ds1098_tables9-12.xlsx","text":"Tables 9–12","size":"28.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Tables 9–12"},{"id":360653,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CV4GNG","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Interior least tern sandbar nesting habitat measurements from Landsat TM imagery"},{"id":360600,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1098/coverthb.jpg"},{"id":360601,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1098/ds1098.pdf","text":"Report","size":"1.87 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1098"}],"contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
The Digital Shoreline Analysis System (DSAS) is a freely available software application that works within the Esri Geographic Information System (ArcGIS) software. DSAS computes rate-of-change statistics for a time series of shoreline vector data. DSAS version 5.0 (v5.0) was released in December 2018 and has been tested for compatibility with ArcGIS versions 10.4 and 10.5. It is supported on Windows 7 and Windows 10 operating systems. If you use it, please cite it as follows and make note of the current version:
Himmelstoss, E.A., Farris, A.S., Henderson, R.E., Kratzmann, M.G., Ergul, Ayhan, Zhang, Ouya, Zichichi, J.L., Thieler, E. R., 2018, Digital Shoreline Analysis System (version 5.0): U.S. Geological Survey software release, https://code.usgs.gov/cch/dsas.
This user guide describes the system requirements, installation procedures, and necessary inputs to establish measurement locations with DSAS-generated transects and compute rate-of-change calculations. Although the nomenclature for this software utility is based on use in a coastal environment, the DSAS application could be used to compute rates of change for any boundary-change problem that incorporates a clearly identified feature position at discrete times, such as glacier limits, river banks, or land use/cover boundaries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181179","collaboration":" ","usgsCitation":"Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A.S., 2018, Digital Shoreline Analysis System (DSAS) version 5.0 user guide: U.S. Geological Survey Open-File Report 2018–1179, 110 p., https://doi.org/10.3133/ofr20181179.","productDescription":"Report: xi, 110 p.; Software","ipdsId":"IP-098630","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":360367,"rank":3,"type":{"id":22,"text":"Related Work"},"url":" https://code.usgs.gov/cch/dsas","text":"Digital Shoreline Analysis System (version 5.0) software"},{"id":360366,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1179/ofr20181179.pdf","text":"Report","size":"35.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1179"},{"id":360365,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1179/coverthb.jpg"},{"id":360368,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://woodshole.er.usgs.gov/project-pages/DSAS/","text":"Digital Shoreline Analysis System","linkFileType":{"id":5,"text":"html"}}],"contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
The northwest-trending Chocolate Mountains are situated along the northeastern margin of the southern Salton Trough. The Chocolate Mountain Aerial Gunnery Range occupies most of the 75-km-long part of the Chocolate Mountains that lies between Salt Creek to the north and California State Highway 78 to the south. Mapping studies in the Chocolate Mountains within the gunnery range are few and this study was conducted in cooperation with the U.S. Navy (Naval Facilities Engineering Command Southwest, San Diego, California) and U.S. Marine Corps (Range Management Department, Marine Corps Air Station, Yuma, Arizona).
Crystalline basement rocks in the Chocolate Mountains range in age from early Proterozoic to middle Cenozoic. Early and middle Proterozoic metamorphosed sedimentary and plutonic rocks include sillimanite-biotite-quartz feldspar gneiss, layered biotite-quartz-feldspar gneiss, biotite-quartz-feldspar augen gneiss, and largely undeformed late Proterozoic anorthosite and syenite. These rock types, which crop out as dispersed domains in the Chocolate Mountains, are remnants—along with more extensive domains observed in the Eastern Transverse Ranges to the north and in the San Gabriel Mountains to the northwest—of an originally more continuous assemblage that has been dextrally displaced along strands of the San Andreas Fault System.
Director,
Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
University of Arizona
ENRB Bldg, 520 N. Park Ave, Rm 355
Tucson, AZ 85719-5035
A SPARROW (SPAtially Related Regressions On Watershed attributes) model that was previously developed for western Oregon and northwestern California was updated using advancements in the SPARROW software and refinements to the input data. As was the case for the original model calibration, the updated models used the NHD Plus Version 2 as a hydrologic framework and relied on the same estimates of long-term mean suspended-sediment loads and watershed attributes. The updated calibration results indicated that two different SPARROW models were possible—one model from which sediment sources were represented by local lithology and one from which sediment sources were represented by generalized land-cover classes; precipitation, catchment slope, wildfire disturbance, and sediment loss in impoundments were significantly correlated with suspended-sediment loads in both models. The updated models also included a method to compensate for the bias introduced by using total suspended solids to represent suspended sediment in the calibration dataset—a feature that was not available during the original model calibration. The effect of this feature was an overall increase in estimated suspended-sediment loads. Although the lithology- and the land-cover based models used different landscape properties to describe sediment sources, each could be useful in specific applications. The lithology-based model provides more accurate estimates of suspended-sediment load, but the land-cover based model allows water-quality managers to estimate how much in-stream suspended-sediment load originates in areas with extensive development compared to the load that originates in areas with relatively little human impact.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185156","usgsCitation":"Wise, D.R., 2018, Updates to the suspended sediment SPARROW model developed for western Oregon and northeastern California: U.S. Geological Survey Scientific Investigations Report 2018–5156, 23 p., https://doi.org/10.3133/sir20185156.","productDescription":"Report: v, 23 p.; Appendix; Data Release","onlineOnly":"Y","ipdsId":"IP-093497","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":360706,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XVX2SM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Predictions from the updated SPARROW suspended sediment models developed for western Oregon and northwestern California"},{"id":360705,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5156/sir20185156_appendix01.xlsx","text":"Appendix 1","size":"34 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5156 Appendix 1"},{"id":360704,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5156/sir20185156.pdf","text":"Report","size":"16.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5156"},{"id":360703,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5156/coverthb.jpg"}],"country":"United States","state":"California, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.62890625,\n 40\n ],\n [\n -120.5,\n 40\n ],\n [\n -120.5,\n 46.3\n ],\n [\n -124.62890625,\n 46.3\n ],\n [\n -124.62890625,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Improved predictions of earthquake ground motions are critical to advancing seismic hazard analyses and earthquake response. The high seismicity rate from 2009 to 2016 in Oklahoma and Kansas provides an extensive data set for examining the ground motions from these events. We evaluate the ability of three suites of ground‐motion prediction equations (GMPEs)—appropriate for modeling tectonic earthquakes in active crustal and stable continental regions—to reproduce the observed ground motions. Mixed‐effects regressions are used to separate the ground‐motion residuals into bias, between‐event, and within‐event terms. Although the residuals depict differing accuracies in the ability of the three GMPE suites to predict the ground motions, some consistent trends emerge in the period, magnitude, and distance dependence. The trends suggest that aspects of the ground motions from these induced earthquakes are not well modeled by current tectonic GMPEs. Most important, we find evidence for relatively poor overall fit to the ground motions, by all of the GMPE suites, at periods less than about 0.2 s and above 3 s, greater‐than‐predicted magnitude scaling for small to moderate‐magnitude events (
The Upper Mississippi River Restoration (UMRR) Program Long Term Resource Monitoring (LTRM) element has been monitoring fish, water quality, and vegetation in six study pools in the Upper Mississippi River system for approximately 30 years. Geographic locations were recorded for all sampling points. All of this information has been made publicly available by way of data download and visualization tools (https://www.umesc.usgs.gov/ltrm-home.html), but it has not been available to decision makers, scientists, resource managers, and the public by way of an internet-based mapping and query application. Presenting the information in this way is vital to providing decision makers with the information and understanding needed to maintain the Upper Mississippi River system as a viable multiple-use river ecosystem, the primary mission of the UMRR LTRM.
Spatial data query tools have been developed that allow the query, display, mapping, and data extraction of the UMRR LTRM element component data by means of an easy-to-use graphical user interface. A separate spatial data query tool application was developed for each study pool within the Upper Mississippi River system and is accessible as individual links at the bottom of the website located at https://www.umesc.usgs.gov/ltrmp/spatial_data_query_tool.html. In addition to the UMRR LTRM element component data, the spatial data query tool also contains land cover and bathymetric (water depth) data collected by the UMRR LTRM element.
Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
Hydrograph analysis tools using a master recession curve (MRC) can produce many types of hydrologically important watershed-response quantifications, including aquifer recharge and stormflow characterization. An MRC is the relation between the value of a measured response R and its rate of change with time, dR/dt, occurring on the falling limb when there is no infiltration or other water input. We have developed MRC and episodic hydrograph-evaluation methods for multiple purposes, utilizing both water table and streamflow data. The determination of a parameterized MRC through a structured procedure provides a basis for quantification of hydrologic variables and characteristics that can be validly compared among different events, sites, and periods of time. Application of the MRC to needed hydrologic quantifications is done with our revised episodic master recession (EMR) method. Expert-guided iterative procedures are used to quantify parameters needed in applying the MRC and EMR methods to a given site. Hydrologic judgments such as the significance threshold for response magnitude, and the time window within which the precipitation is assumed to be the cause of an observed response, inherently involve some elements of subjectivity. Our structured iterative approach, however, affords much flexibility in formulating expert judgments and serves to confine them to statements and procedures that can be quantified and documented. Parallel application to streamflow and water table hydrographs can produce new hydrologic insights and understanding, not least in the role of unsaturated zone processes in controlling exchanges among components of the water cycle.
","language":"English","publisher":"ACSESS","doi":"10.2136/vzj2018.03.0050","usgsCitation":"Nimmo, J.R., and Perkins, K., 2018, Episodic master recession evaluation of groundwater and streamflow hydrographs for water-resource estimation: Vadose Zone Journal, v. 17, no. 1, p. 1-25, https://doi.org/10.2136/vzj2018.03.0050.","productDescription":"25 p.","startPage":"1","endPage":"25","ipdsId":"IP-096220","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":468177,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2018.03.0050","text":"Publisher Index Page"},{"id":360784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":755294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perkins, Kimberlie 0000-0001-8349-447X kperkins@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-447X","contributorId":138544,"corporation":false,"usgs":true,"family":"Perkins","given":"Kimberlie","email":"kperkins@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":755295,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201458,"text":"ofr20181192 - 2018 - Analysis of groundwater response to tidal fluctuations, Site 10 Naval Magazine Indian Island, Port Hadlock, Washington","interactions":[],"lastModifiedDate":"2018-12-21T10:28:59","indexId":"ofr20181192","displayToPublicDate":"2018-12-20T11:02:22","publicationYear":"2018","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":"2018-1192","displayTitle":"Analysis of Groundwater Response to Tidal Fluctuations, Site 10 Naval Magazine Indian Island, Port Hadlock, Washington","title":"Analysis of groundwater response to tidal fluctuations, Site 10 Naval Magazine Indian Island, Port Hadlock, Washington","docAbstract":"Site 10 at Naval Magazine Indian Island is an approximately 3.7-acre inactive landfill. The site was used as the primary landfill for the island from about 1945 until the mid-1970s, receiving paints, batteries, trash, and materials. In a memorandum to Washington State Department of Ecology, Naval Facilities Engineering Command Northwest (NAVFAC NW) stipulated that a new tidal study would be conducted to recalculate tidal influence lag-time in each groundwater monitoring well at Site 10.
Groundwater levels and specific conductance in five monitoring wells, along with marine water-levels (tidal levels) in Port Townsend Bay, were monitored every 15 minutes during a 2-week period to better understand nearshore groundwater-seawater interactions at Site 10. Time series data were collected from April 17 to May 3, 2018, a period that included neap and spring tides.
Vertical profiles of specific conductance were measured once in the screened interval of each well prior to instrument deployment to determine if a freshwater/saltwater interface was present in the well prior to instrument deployment. Profiles where measured during an ebbing tide at approximately the top, middle, and bottom of the saturated thickness within the screened interval of each well. The landward-most well, MW10-8 and coastline wells MW10-10, MW10-11 and MW10-12R, had a uniform specific conductance in the range of fresh or brackish water. Landfill monitoring well MW10-6 showed the highest uniform specific conductance profile also in the range of brackish water.
Lag times between minimum spring-tide levels and minimum groundwater levels in wells ranged from about 0 to 4 hours. Results of lag times showed a logical increase in lag time as the distance increases from the shoreline to each monitoring well.
The specific-conductance time-series data showed minimal change in the screened interval of each well. Fluctuation of specific conductance in each well was unique but no sharp groundwater saltwater interface was observed. Increases in specific conductivity concurrent with spring low tides were measured in coastline wells, suggesting shoreward transport of high specific conductivity landfill leachate rather than seawater intrusion.
Based on all the data collected during this investigation, the optimal time for sampling monitoring wells at Site 10 would be during a 0–4-hour period following the predicted low-low tide.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181192","collaboration":"Prepared in cooperation with the Department of the Navy, Naval Facilities Engineering Command, Northwest","usgsCitation":"Opatz, C.C., and Dinicola, R.S., 2018, Analysis of groundwater response to tidal fluctuations, Site 10 Naval Magazine Indian Island, Port Hadlock, Washington: U.S. Geological Survey Open-File Report 2018-1192, 21 p., https://doi.org/10.3133/ofr20181192.","productDescription":"iv, 21 p.","onlineOnly":"Y","ipdsId":"IP-099654","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":360629,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1192/ofr20181192.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1192"},{"id":360628,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1192/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Naval Magazine Indian Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73732662200928,\n 48.08149085582177\n ],\n [\n -122.72406578063963,\n 48.08149085582177\n ],\n [\n -122.72406578063963,\n 48.0877406628633\n ],\n [\n -122.73732662200928,\n 48.0877406628633\n ],\n [\n -122.73732662200928,\n 48.08149085582177\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Understanding the relationship between environmental factors and vital rates is an important step in predicting a species’ response to environmental change. Species associated with sea ice are of particular concern because sea ice is projected to decrease rapidly in polar environments with continued levels of greenhouse gas emissions. The relationship between sea ice and the vital rates of the Spectacled Eider, a threatened species that breeds in Alaska and Russia and winters in the Bering Sea, appears to be complex. While severe ice can impede foraging for benthic prey, ice also suppresses wave action and provides a platform on which eiders roost, thereby reducing thermoregulation costs. We analyzed a 23‐year mark‐recapture dataset for Spectacled Eiders nesting on Kigigak Island in western Alaska, and tested survival models containing different ice and weather‐related covariates. We found that much of the variation in eider survival could be explained by the number of days per year with >95% sea ice concentration at the Bering Sea core wintering area. Furthermore, the data supported a quadratic relationship with sea ice rather than a linear one, indicating that intermediate sea ice concentrations were optimal for survival. We then used matrix population models to project population trajectories using General Circulation Model (GCM) outputs of daily sea ice cover. GCMs projected reduced sea ice at the wintering area by year 2100 under a moderated emissions scenario (RCP 4.5) and nearly ice‐free conditions under an unabated emissions scenario (RCP 8.5). Under RCP 4.5, stochastic models projected an increase in population size until 2069 coincident with moderate ice conditions, followed by a decline in population size as ice conditions shifted from intermediate to mostly ice‐free. Under RCP 8.5, eider abundance increased until 2040 and then decreased to near extirpation toward the end of the century as the Bering Sea became ice‐free. Considerable uncertainty around parameter estimates for survival in years with minimal sea ice contributed to variation in stochastic projections of future population size, and this uncertainty could be reduced with additional survival data from low‐ice winters.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4637","usgsCitation":"Christie, K.S., Hollmen, T.E., Flint, P.L., and Douglas, D., 2018, Non‐linear effect of sea ice: Spectacled Eider survival declines at both extremes of the ice spectrum: Ecology and Evolution, v. 8, no. 23, p. 11808-11818, https://doi.org/10.1002/ece3.4637.","productDescription":"11 p.","startPage":"11808","endPage":"11818","ipdsId":"IP-093761","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468178,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4637","text":"Publisher Index Page"},{"id":360610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":" Kigigak Island","volume":"8","issue":"23","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","scienceBaseUri":"5c1cb85de4b0708288c83817","contributors":{"authors":[{"text":"Christie, Katherine S.","contributorId":177114,"corporation":false,"usgs":false,"family":"Christie","given":"Katherine","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":754733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hollmen, Tuula E.","contributorId":211728,"corporation":false,"usgs":false,"family":"Hollmen","given":"Tuula","email":"","middleInitial":"E.","affiliations":[{"id":16211,"text":"Alaska SeaLife Center","active":true,"usgs":false}],"preferred":false,"id":754734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754731,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":150115,"corporation":false,"usgs":true,"family":"Douglas","given":"David C.","email":"ddouglas@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":754732,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201359,"text":"sir20185167 - 2018 - Flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York","interactions":[],"lastModifiedDate":"2018-12-20T16:27:27","indexId":"sir20185167","displayToPublicDate":"2018-12-20T06:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5167","displayTitle":"Flood-Inundation Maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York","title":"Flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York","docAbstract":"Digital flood-inundation maps for a 2.9-square-mile area of Ithaca, New York, were created in 2015–18 by the U.S. Geological Survey in cooperation with the City of Ithaca, New York, and the New York State Department of State. The flood-inundation maps depict estimates of the maximum areal extent and depth of flooding corresponding to selected flood frequencies for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek and selected water-surface elevations of Cayuga Lake.
Flood profiles for the stream reaches were computed by combining a one-dimensional step-backwater model for the stream channels and a two-dimensional model for the overbank areas. The resulting hydraulic model was calibrated by using water-surface profiles from five observed storm events. The model was then used to compute 15 water-surface profiles for 5 flood frequencies (50-, 10-, 2-, 1-, and 0.2-percent annual exceedance probabilities, or 2-, 10-, 50-, 100-, and 500-year recurrence intervals) and 3 lake levels (representing average conditions, a 2-year-high condition, and a 100-year-high condition). The simulated water-surface profiles were then combined with a digital elevation model (derived from light detection and ranging data having 0.31‑foot vertical accuracy and 3.3-foot horizontal resolution) to delineate the maximum area flooded at each water level.
Flood-inundation maps and geographic information system flood-extent polygons and depth grids are available in the data release associated with this report. These maps can provide emergency management personnel and residents with information that is critical for flood-management planning, flood-response activities, and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185167","collaboration":"Prepared in cooperation with the City of Ithaca, New York, and the New York State Department of State","usgsCitation":"Nystrom, E.A., Lilienthal, A.G., III, and Coon, W.F., 2018, Flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York: U.S. Geological Survey Scientific Investigations Report 2018–5167, 27 p., https://doi.org/10.3133/sir20185167. \n\n","productDescription":"Report: viii, 27 p.; Data release","ipdsId":"IP-097931","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":437643,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V8ED23","text":"USGS data release","linkHelpText":"Geospatial dataset of flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York"},{"id":360375,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V8ED23 ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial dataset of flood-inundation maps for Cayuga Inlet, Sixmile Creek, Cascadilla Creek, and Fall Creek at Ithaca, New York, 2018"},{"id":360373,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5167/coverthb.jpg"},{"id":360374,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5167/sir20185167.pdf","text":"Report","size":"6.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5167"}],"country":"United States","state":"New York","city":"Ithaca","otherGeospatial":"Cascadilla Creek, Cayuga Inlet, Fall Creek, Sixmile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.53213500976562,\n 42.413825296776835\n ],\n [\n -76.48578643798827,\n 42.413825296776835\n ],\n [\n -76.48578643798827,\n 42.46994435756588\n ],\n [\n -76.53213500976562,\n 42.46994435756588\n ],\n [\n -76.53213500976562,\n 42.413825296776835\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180
Knowing how many manatees live in Florida is critical for conservation and management of this threatened species. Martin et al. (2015) flew aerial surveys in 2011–2012 and estimated abundance in those years using advanced techniques that incorporated multiple data sources. We flew additional aerial surveys in 2015–2016 to count manatees and again applied advanced statistical techniques to estimate their abundance. We also made several methodological advances over the earlier work, including accounting for how sea state (water surface conditions) and synchronous surfacing behavior affect the availability of manatees to be detected and incorporating all parts of Florida in the area of inference. We estimate that the number of manatees in Florida in 2015–2016 was 8,810 (95% Bayesian credible interval 7,520–10,280), of which 4,810 (3,820–6,010) were on the west coast of Florida and 4,000 (3,240–4,910) were on the east coast. These estimates and associated uncertainty, in addition to being of immediate value to wildlife managers, are essential new data for incorporation into integrated population models and population viability analyses.
","language":"English","publisher":"Florida Fish and Wildlife Conservation Commission, Fish and Wildfish Research Institute","usgsCitation":"Hostetler, J.A., Edwards, H.H., Martin, J., and Schueller, P., 2018, Updated statewide abundance estimates for the Florida manatee: Technical Report 23, 23 p.","productDescription":"23 p.","ipdsId":"IP-102216","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":360625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":360588,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://f50006a.eos-intl.net/F50006A/OPAC/Details/Record.aspx?BibCode=1864664"}],"country":"United 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julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":754580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schueller, Paul","contributorId":181829,"corporation":false,"usgs":false,"family":"Schueller","given":"Paul","email":"","affiliations":[],"preferred":false,"id":754583,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201600,"text":"ofr20181194 - 2018 - Changes in aquatic prey resources in response to estuary restoration in Willapa Bay, southwestern Washington","interactions":[],"lastModifiedDate":"2018-12-20T16:18:00","indexId":"ofr20181194","displayToPublicDate":"2018-12-19T14:42:44","publicationYear":"2018","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":"2018-1194","displayTitle":"Changes in Aquatic Prey Resources in Response to Estuary Restoration in Willapa Bay, Southwestern Washington","title":"Changes in aquatic prey resources in response to estuary restoration in Willapa Bay, southwestern Washington","docAbstract":"The ongoing restoration of more than 200 hectares of estuarine habitat at Willapa National Wildlife Refuge, southwestern Washington, is expected to benefit a variety of species, including salmonids that use estuarine and tidal marshes as rearing and feeding areas as well as migratory waterbirds. During March–June 2014 and 2015, U.S. Geological Survey Western Ecological Research Center (WERC) initiated a study to assess aquatic prey resources, in coordination with a separate but parallel fish study done by the Columbia River Estuary Study Taskforce. WERC collected data on environmental variables and invertebrate community structure, and the taskforce provided salmonid diet data at restored (Lewis Stream and Porter Point) and reference (Greenhead Slough and Ellsworth Creek) sites. We analyzed these data to determine the functional capacity of the estuary for supporting invertebrate prey resources for fish following restoration.
The results of our analyses were as follows:
Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The Colorado Department of Transportation maintains roadways crossing over large streams and rivers where sediment transport and channel alignment changes can affect the structural stability of bridges. Structural stability during and immediately after peak streamflow can be assessed by measuring streambed scour; however, placing personnel or boats in the water during high-streamflow events using traditional methods can be difficult, hazardous, and time consuming. To address this need, the U.S. Geological Survey, in cooperation with Colorado Department of Transportation, installed instrumentation at two bridges in western Colorado to measure streambed elevations in real-time during snowmelt-runoff periods (May through June) in 2016 and 2017. The bridges include U.S. Highway 50 eastbound over the Gunnison River at milepost 70.0 (bridge I–04–K) and Colorado Highway 141 over the Gunnison River at milepost 153.7 (bridge I–03–A).
Bridge I–04–K was outfitted with two echosounders, each mounted on the north side of pier 3. Data collected during the 2016 snowmelt runoff did not indicate scour had occurred. Data collected during 2017 snowmelt runoff indicated minor scour and fill occurred under the downstream echosounder.
Bridge I–03–A was outfitted with two echosounders, each mounted on opposite sides of pier 4, at the transition of the upstream nose to the straight section of the pier wall. Data recorded during 2016 did not indicate any scour under the echosounders. Debris accumulation around the nose of the pier and under the echosounders resulted in inconsistent streambed elevation data. Data recorded during 2017 did not indicate any scour under the echosounders. Probing of the pier wall and streambed interface and underwater photographs obtained in 2016 revealed undermining along the length of the pier wall. The undermining extended side-to-side to a depth of about 2 feet. Underwater photographs were obtained again in 2017; no changes from the previous year were observed.
Cross-section surveys were completed at each bridge to measure and document changes in channel geometry during the study. Surveys were performed in spring 2016 before snowmelt runoff, spring 2017 before snowmelt runoff, and fall 2017. Streambed elevations from cross-section surveys at both bridges were evaluated using two-tailed, paired t-tests and Wilcoxon rank sum tests to identify significant changes between the surveys. Both tests indicated significant changes in mean streambed elevations for the cross-sections and around the monitored piers at bridges I–04–K and I–03–A during the 2-year study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185123","collaboration":"Prepared in cooperation with the Colorado Department of Transportation","usgsCitation":"Henneberg, M.F., 2018, Real-time streambed scour monitoring at two bridges over the Gunnison River in western Colorado, 2016–17: U.S. Geological Survey Scientific Investigation Report 2018–5123, 15 p., https://doi.org/10.3133/sir20185123.","productDescription":"Report: v, 15 p.; Data release","onlineOnly":"Y","ipdsId":"IP-093925","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":437646,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92EY47R","text":"USGS data release","linkHelpText":"Cross-Section Geometry at Two Bridges over the Gunnison River in Western Colorado, 2016-17"},{"id":360449,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5123/sir20185123.pdf","text":"Report","size":"5.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5123"},{"id":360530,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/P92EY47R","text":"USGS data release","linkHelpText":"Cross-Section Geometry at Two Bridges over the Gunnison River in Western Colorado, 2016–17"},{"id":360448,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5123/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Gunnison River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.8333,\n 39.6667\n ],\n [\n -107.8333,\n 39.6667\n ],\n [\n -107.8333,\n 39.1667\n ],\n [\n -108.8333,\n 39.1667\n ],\n [\n -108.8333,\n 39.6667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
The Navajo (N) aquifer is an extensive aquifer and the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Availability of water is an important issue in the Black Mesa area because of continued water requirements for industrial and municipal use by a growing population and because of the arid climate. Precipitation in the area typically ranges from less than 6 to more than 16 inches per year depending on location.
The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents results of data collected as part of the monitoring program in the Black Mesa area from November 2015 to December 2016. The monitoring program includes measurements of (1) groundwater withdrawals (pumping), (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater chemistry.
In calendar year 2016, total groundwater withdrawals were 3,540 acre-ft, industrial withdrawals were 1,090 acre-ft, and municipal withdrawals were 2,450 acre-ft. Total withdrawals during 2016 were about 52 percent less than total withdrawals in 2005 because of Peabody Western Coal Company’s discontinued use of water to transport coal in a coal slurry pipeline.
From 2015 to 2016, annually measured water levels available for comparison in wells completed in the unconfined areas of the N aquifer within the Black Mesa area declined in 9 of 16 wells, and the median change was –0.1 feet. Water levels also declined in 8 of 16 wells measured in the confined area of the aquifer. The median change for the confined area of the aquifer was 0.0 feet. From the prestress period (prior to 1965) to 2016, the median water-level change for all 32 wells in both the confined and unconfined areas was –10.2 feet; the median water-level changes were –1.6 feet for the 16 wells measured in the unconfined areas and –36.1 feet for the 16 wells measured in the confined area.
Spring flow was measured at four springs in 2016. Flow fluctuated during the period of record for Burro Spring and Pasture Canyon Spring, but a decreasing trend was statistically significant (p<0.05) at Moenkopi School Spring and Unnamed Spring near Dennehotso. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s and discharge at Pasture Canyon Spring has fluctuated for the period of record.
Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976 to 2016), Dinnebito Wash near Sand Springs 09401110 (1993 to 2016), Polacca Wash near Second Mesa 09400568 (1994 to 2016), and Pasture Canyon Springs 09401265 (2004 to 2016). Median winter flows (November through February) of each water year were used as an index of the amount of groundwater discharge at the above-named sites. For the period of record, the median winter flows have generally remained constant at Dinnebito Wash and Polacca Wash, whereas a decreasing trend was indicated at Moenkopi Wash and Pasture Canyon Springs.
In 2016, water samples collected from three wells and four springs in the Black Mesa area were analyzed for selected chemical constituents, and the results were compared with previous analyses from the same wells and springs. Concentrations of dissolved solids, chloride, and sulfate have varied at all three wells for the period of record, but neither increasing nor decreasing trends over time were found. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 25 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied significantly (p>0.05) since the early 1980s, and there is no increasing or decreasing trend in those data. Concentrations of dissolved solids, chloride, and sulfate at Burro Spring and Unnamed Spring near Dennehotso have varied for the period of record, but there is no statistical trend in the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181193","collaboration":"Prepared in cooperation with the Navajo Nation and the Arizona Department of Water Resources","usgsCitation":"Mason, J.P., and Macy, J.P., 2018, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2015–2016: U.S. Geological Survey Open-File Report 2018–1193, 60 p., https://doi.org/10.3133/ofr20181193.","productDescription":"vii, 60 p.","onlineOnly":"Y","ipdsId":"IP-097246","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":384544,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211124","text":"Open-File Report 2021-1124","linkHelpText":"- Groundwater, Surface-Water, and Water-Chemistry Data, Black Mesa Area, Northeastern Arizona—2016–2018"},{"id":360531,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1193/coverthb.jpg"},{"id":360532,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1193/ofr20181193.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1193"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.5,\n 35.5\n ],\n [\n -109.5,\n 35.5\n ],\n [\n -109.5,\n 37\n ],\n [\n -111.5,\n 37\n ],\n [\n -111.5,\n 35.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
It is asserted that reduction or elimination of hatchery stocking will increase natural‐origin salmon Oncorhynchus spp. and steelhead O. mykiss production. We conducted an analysis of steelhead population census data (1958–2017) to determine whether elimination of summer steelhead stocking in the upper Clackamas River in 1998 increased the productivity of natural‐origin winter steelhead. A Bayesian state–space stock–recruitment model was fitted to the adult steelhead data set, and productivity was estimated as a function of hatchery‐origin spawner abundance as well as other environmental factors. When used as a predictive variable in our model, the abundance of hatchery summer steelhead spawners (1972–2001) did not have a negative effect on winter steelhead recruitment. However, spill at North Fork Dam (the gateway to the upper Clackamas River basin) and the Pacific Decadal Oscillation (an index of ocean conditions) were both negatively associated with winter steelhead recruitment. Moreover, winter steelhead abundance in the upper Clackamas River basin failed to rebound to abundances observed in years prior to the hatchery program, and fluctuations in winter steelhead abundance were correlated with those of other regional winter steelhead stocks. Our assessment underscores the need for studies that (1) directly quantify the effects of hatchery fish on the production of natural‐origin salmon and steelhead, (2) empirically test published theories about mechanisms of hatchery fish impacts on natural‐origin populations, and (3) document population responses to major changes in hatchery programs.
","language":"English","publisher":"American Fisheries Society ","doi":"10.1002/tafs.10140","usgsCitation":"Courter, I.I., Wyatt, G.J., Perry, R., Plumb, J., Carpenter, F.M., Ackerman, N.K., Lessard, R.B., and Galbreath, P., 2018, A natural‐origin steelhead population's response to exclusion of hatchery fish: Transactions of the American Fisheries Society, v. 148, no. 2, p. 339-351, https://doi.org/10.1002/tafs.10140.","productDescription":"13 p.","startPage":"339","endPage":"351","ipdsId":"IP-098370","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468181,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10140","text":"Publisher Index Page"},{"id":363055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":" Clackamas River ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73376464843749,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.0657615477031\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Courter, Ian I","contributorId":214903,"corporation":false,"usgs":false,"family":"Courter","given":"Ian","email":"","middleInitial":"I","affiliations":[{"id":39134,"text":"Mount Hood Environmental, P.O. Box 744, Boring, Oregon 97009","active":true,"usgs":false}],"preferred":false,"id":761132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wyatt, Garth J","contributorId":214904,"corporation":false,"usgs":false,"family":"Wyatt","given":"Garth","email":"","middleInitial":"J","affiliations":[{"id":39135,"text":"Portland General Electric, 33831 Faraday Rd., Estacada, Oregon 97023","active":true,"usgs":false}],"preferred":false,"id":761133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":214905,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":761134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plumb, John 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":214906,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":761135,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carpenter, Forrest M","contributorId":214907,"corporation":false,"usgs":false,"family":"Carpenter","given":"Forrest","email":"","middleInitial":"M","affiliations":[{"id":39134,"text":"Mount Hood Environmental, P.O. 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Mining activities since the late 19th century, specifically placer mining and associated dredging from 1940 to 1953, have left the fluvial system in a highly altered and unnatural state. To improve aquatic and terrestrial habitat in the Yankee Fork, the Bureau of Reclamation and other stakeholders collaborated on the Dredge Tailings Restoration Project and Yankee Fork Rehabilitation Project. In conjunction with these rehabilitation efforts, the U.S. Geological Survey monitored suspended-sediment transport and discharge between 2012 and 2015 at three sites in the lower reaches of the Yankee Fork. Pseudo-hydrographs were developed for the Bonanza and Confluence sites using data from the streamgage site as a surrogate. Results showed a good fit between measured and calculated discharge with R2 values of 0.96 for the Bonanza site and 0.98 for the Confluence site. Both regressions have high hypothesis test statistics (t>23) and low probability values (p<0.0001), indicating a strong linear correlation. Suspended-sediment samples collected mostly during snowmelt runoff showed a positive correlation with stream discharge. Hysteresis in the sample results indicates a supply-limited suspended-sediment transport regime. Percent sand by weight of suspended-sediment samples identified a possible discharge threshold for sand suspension at about 400 cubic feet per second (ft3/s) at the Bonanza site and about 1,000 ft3/s at the Confluence and Gage sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181189","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Johnsen, J.W., 2018, Sediment transport monitoring of the Yankee Fork of the Salmon River near Stanley, Idaho, 2012–15: U.S. Geological Survey Open-File Report 2018-1189, 17 p., https://doi.org/10.3133/ofr20181189.","productDescription":"iv, 17 p.","onlineOnly":"Y","ipdsId":"IP-090600","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":360434,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1189/coverthb.jpg"},{"id":360435,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1189/ofr20181189.pdf","text":"Report","size":"12.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1189"}],"country":"United States","state":"Idaho","city":"Stanley","otherGeospatial":"Salmon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.4892,\n 43.5222\n ],\n [\n -114.2392,\n 43.5222\n ],\n [\n -114.2392,\n 44.7725\n ],\n [\n -115.4892,\n 44.7725\n ],\n [\n -115.4892,\n 43.5222\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
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Researchers from the U.S. Geological Survey (USGS) conducted a long-term coastal morphologic-change study at Fire Island, New York, prior to and after Hurricane Sandy impacted the area in October 2012. The Fire Island Coastal Change project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related effects, post-storm beach response, and recovery. In April 2016, scientists from the USGS St. Petersburg Coastal and Marine Science Center conducted sediment sampling and geophysical surveys on Fire Island to characterize and quantify spatial variability in the subaerial geology with the goal of subsequently integrating onshore geology with other surf zone and nearshore datasets.
This report, along with the accompanying USGS data release, serves as an archive of sediment data from 14 vibracores collected on April 10 and 11, 2016 (USGS Field Activity Number 2016–322–FA), along 6 transects that extend from the upper to lower subaerial shoreface at Fire Island. Sedimentologic and stratigraphic metrics (for example, sediment texture or unit thicknesses) derived from these data can be used to assess spatial and temporal trends and may aid in understanding beach evolution. Data products include sample location tables, descriptive core logs, core photographs, results of sediment grain-size analyses, and geographic information system data files with accompanying formal Federal Geographic Data Committee metadata.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1100","usgsCitation":"Buster, N.A., Bernier, J.C., Brenner, O.T., Kelso, K.W., Tuten, T.M., and Miselis, J.L., 2018, Sediment data from vibracores collected in 2016 from Fire Island, New York: U.S. Geological Survey Data Series 1100, https://doi.org/10.3133/ds1100.","productDescription":"HTML Document; Data Release","ipdsId":"IP-099448","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437649,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91P1T88","text":"USGS data release","linkHelpText":"Sediment Data From Vibracores and Sand Augers Collected in 2021 and 2022 From Fire Island, New York"},{"id":359473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1100/coverthb.jpg"},{"id":359475,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FN15GX","text":"USGS data release","description":"USGS data release"},{"id":359474,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1100/","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1100"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.32069396972655,\n 40.60926110386811\n ],\n [\n -72.74871826171875,\n 40.60926110386811\n ],\n [\n -72.74871826171875,\n 40.77534183237267\n ],\n [\n -73.32069396972655,\n 40.77534183237267\n ],\n [\n -73.32069396972655,\n 40.60926110386811\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
This report is a user guide for the Massachusetts Sustainable-Yield Estimator (MA SYE) computer program (version 2.0). The MA SYE was developed by the U.S. Geological Survey in cooperation with the Massachusetts Department of Environmental Protection to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics to assess sustainable water use at ungaged sites in Massachusetts. The MA SYE provides estimates of unaltered streamflow (which is assumed to occur in the absence of any water withdrawals or wastewater discharges and with minimal human development), net streamflow alterations caused by water use, water-use-adjusted streamflow, streamflow yields (estimated unaltered streamflow minus user-defined flow targets), and estimates of the accuracy and uncertainty of estimated unaltered streamflow. The MA SYE uses basin characteristics and water-use volumes (water withdrawals and wastewater-return flows) obtained from the U.S. Geological Survey online StreamStats application to estimate the unaltered and water-use-adjusted streamflows. The MA SYE is a database application with a graphical user interface developed by using Visual Basic for Applications with the 32-bit version of Microsoft Access. The graphical user interface is designed include full documentation for users: an introductory instruction form and onscreen help within each interactive form, including explanation buttons, context-sensitive help buttons, and tool-tip and status-bar messages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181169","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Granato, G.E., and Levin, S.B., 2018, User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program: U.S. Geological Survey Open-File Report 2018–1169, 7 p., https://doi.org/10.3133/ofr20181169.\n\n","productDescription":"Report: vi, 7 p.; Software release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098957","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":358596,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95VX5AX","text":"USGS software release","description":"USGS software release","linkHelpText":"Massachusetts Sustainable-Yield Estimator (MASYE) application software (version 2.0) 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The Massachusetts Sustainable-Yield Estimator is a decision support tool that provides estimates of daily unaltered streamflow, water-use-adjusted streamflow, and water availability for ungaged, user-defined basins in Massachusetts. Daily streamflow at the ungaged site is estimated for unaltered (no water use) and water-use scenarios. The procedure for estimating streamflow was developed previously and has been implemented with minor changes and updated water-use data in version 2.0 of the Massachusetts Sustainable-Yield Estimator. Unaltered streamflow at selected exceedance probabilities is estimated by previously published regression equations. Streamflow is interpolated between the regressed quantiles to produce a continuous flow duration curve. A daily streamflow time series is produced for the ungaged site by relating the estimated flow duration curve at the ungaged site to a flow duration curve at a gaged reference site and then transferring the dates from the reference site to the ungaged site.
Minor refinements were made to the previously published methods to estimate unaltered and water-use-adjusted streamflow, including a procedure to enforce the monotonic structure of the regression-based unaltered flow quantiles, improvements to the interpolation method used for computing the estimated flow duration curve, and updates to the methods used to compute time-lagged stream alterations from groundwater pumping or discharges. Additionally, a procedure was developed to estimate prediction intervals for daily and monthly unregulated streamflow time series at an ungaged site.
The Massachusetts Sustainable-Yield Estimator computes water-use-adjusted streamflow using water-use data provided by the Massachusetts Department of Environmental Protection. Available water-use data included monthly withdrawal and wastewater discharge volumes from 2010 to 2014 for surface-water and groundwater sources. Water-use-adjusted streamflow represents the potential effect of current water use on natural streamflow in the basin over the range of historical hydrologic conditions. Georeferenced water withdrawal and discharge volumes were incorporated into the Massachusetts StreamStats web application for use in version 2.0 of the Massachusetts Sustainable-Yield Estimator. To compute water-use-adjusted streamflow, mean daily withdrawals and discharges within a user-defined basin are subtracted and added to the unaltered time series, respectively. Surface-water volumes are applied directly to the equation. Time-lagged streamflow alterations from groundwater withdrawal or wastewater discharge sources are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models in Massachusetts.
The Massachusetts Sustainable-Yield Estimator was updated to version 2.0 to improve software stability and usability. The version 2.0 software application was developed in Microsoft Access with a graphical user interface. All geoprocessing steps, including basin delineation and compilation of basin characteristics and water use within the basin, were completed in the Massachusetts StreamStats web application and exported for use by the Massachusetts Sustainable-Yield Estimator version 2.0.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185146","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Levin, S.B., and Granato, G.E., 2018, Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0: U.S. Geological Survey Scientific Investigations Report 2018–5146, 16 p., https://doi.org/10.3133/sir20185146.","productDescription":"Report: vi, 16 p.; Software release","ipdsId":"IP-087736","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5146/coverthb.jpg"},{"id":360271,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95VX5AX ","text":"USGS software release","description":"USGS software 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Occupancy models provide a reliable method of estimating species distributions while accounting for imperfect detectability. The cost of accounting for false absences is that detection and nondetection surveys typically require repeated visits to a site or multiple-observer techniques. More efficient methods of collecting data to estimate detection probabilities would allow additional sites to be surveyed for the same amount of effort, which would support more precise estimation of covariate effects to improve inference about underlying ecological processes. Time-to-detection surveys allow the estimation of detection probability based on a single site visit by one observer, and therefore might be an efficient technique for herpetological occupancy studies. We evaluated the use of time-to-detection surveys to estimate the occupancy of pond-breeding amphibians at Point Reyes National Seashore, California, USA, including variables that affected detection rates and the probability of occurrence. We found that detection times were short enough, and occupancy was high enough, to estimate reliably the probability of occurrence of three pond-breeding amphibians at Point Reyes National Seashore, and that survey and site conditions had species-specific effects on detection rates. In particular, pond characteristics affected detection times of all commonly detected species. Probability of occurrence of Sierran Treefrogs (Hyliola sierra) and Rough-Skinned Newts (Taricha granulosa) was negatively related to the detection of fish and pond area. Time-to-detection surveys can provide an efficient method for estimating detection probabilities and accounting for false absences in occupancy studies of reptiles and amphibians.
","language":"English","publisher":"The Society for the Study of Amphibians and Reptiles","doi":"10.1670/18-049","usgsCitation":"Halstead, B., Kleeman, P.M., and Rose, J.P., 2018, Time-to-detection occupancy modeling: An efficient method for analyzing the occurrence of amphibians and reptiles: Journal of Herpetology, v. 52, no. 4, p. 415-424, https://doi.org/10.1670/18-049.","productDescription":"10 p.; Data Release","startPage":"415","endPage":"424","ipdsId":"IP-098079","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437651,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9LA1O","text":"USGS data release","linkHelpText":"Time to detection data for Point Reyes pond-breeding amphibians, 2017"},{"id":360358,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Point Reyes National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.03451538085939,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 37.92578434712101\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c18c423e4b006c4f856acce","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754354,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201266,"text":"ofr20181190 - 2018 - Development of new information to inform fish passage decisions at the Yale and Merwin hydro projects on the Lewis River, Washington—Final report, 2018","interactions":[],"lastModifiedDate":"2018-12-14T16:38:47","indexId":"ofr20181190","displayToPublicDate":"2018-12-14T14:50:00","publicationYear":"2018","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":"2018-1190","title":"Development of new information to inform fish passage decisions at the Yale and Merwin hydro projects on the Lewis River, Washington—Final report, 2018","docAbstract":"The reintroduction of extirpated salmonids to historically occupied areas is becoming increasingly common as a conservation and recovery strategy. Often, reintroductions are implemented after the factors that originally led to species extirpation have been reduced, eliminated, or mitigated. For anadromous Oncorhynchus spp. (Pacific salmon) and O. mykiss (steelhead), addressing barriers to migration, which have been a primary factor in the decline and extirpation of many populations, has been an integral component of recovery efforts. Mitigation has included barrier removal, developing fish passage opportunities, and (or) actively trapping and hauling juvenile and adult anadromous salmonids around barriers.
With any reintroduction, there are a number of concerns regarding the ecological impact of the reintroduction efforts. Three of the main tenets to consider when assessing reintroductions are (1) the potential benefits if reintroduction is successful, (2) the biological risk through interactions of reintroduced strains with existing populations, and (3) the factors potentially limiting a successful reintroduction. This report focuses on information and data to address the second and third factors as they apply to the upper Lewis River in Washington.
The upper Lewis River historically contained wild populations of O. tshawytscha (Chinook salmon), O. kisutch (coho salmon), and steelhead. These populations were extirpated after completion of hydropower facilities on Lake Merwin in 1932, Yale Lake in 1953, and Swift Reservoir in 1958, which prevented fish from migrating to and from ocean environments. However, recent licenses issued by the Federal Energy Regulatory Commission require the installation and operation of an upstream fish passage facility at Lake Merwin and a downstream fish passage facility at Swift Reservoir. The licenses were developed in consultation with the National Marine Fisheries Service and the U.S. Fish and Wildlife Service. The overarching goal of this fish reintroduction project is to establish viable, self-sustaining, naturally reproducing, harvestable populations of spring Chinook salmon, winter steelhead, and coho salmon at levels higher than minimum viable populations.
This report uses a combination of field data and existing information to address six key objectives related to the reintroduction in order to inform decisions about passage at the Yale Lake and Lake Merwin hydropower projects. The objectives are (1) a review of information relevant to anadromous fish reintroduction and full fish passage; (2) a habitat assessment of tributaries to Swift Reservoir, Yale Lake, and Lake Merwin; (3) a field study to assess adult potential for spawning success; (4) an assessment of juvenile production and outmigration success; (5) a Lake Merwin predator impact study; and (6) a set of studies assessing interactions between anadromous and resident fish.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181190","collaboration":"Prepared in cooperation with PacifiCorp","usgsCitation":"Al-Chokhachy, R., Clark, C.L., Sorel, M.H., and Beauchamp, D.A., 2018, Development of new information to inform fish passage decisions at the Yale and Merwin hydro projects on the Lewis River, Washington—Final report, 2018: U.S. Geological Survey Open-File Report 2018–1190, 206 p., https://doi.org/10.3133/ofr20181190.","productDescription":"xv, 206 p.","onlineOnly":"Y","ipdsId":"IP-078496","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":360226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1190/coverthb.jpg"},{"id":360227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1190/ofr20181190.pdf","text":"Report","size":"12.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1190"}],"country":"United States","state":"Washington","otherGeospatial":"Lewis River","contact":"Director, Northern Rocky Mountain Science Center
U.S. Geological Survey
2327 University Way, Suite 2
Bozeman, MT 59715
We present an exploratory study examining the use of airborne remote-sensing observations to detect ecological responses to elevated CO2emissions from active volcanic systems. To evaluate these ecosystem responses, existing spectroscopic, thermal, and lidar data acquired over forest ecosystems on Mammoth Mountain volcano, California, were exploited, along with in situ measurements of persistent volcanic soil CO2fluxes. The elevated CO2 response was used to statistically model ecosystem structure, composition, and function, evaluated via data products including biomass, plant foliar traits and vegetation indices, and evapotranspiration (ET). Using regression ensemble models, we found that soil CO2 flux was a significant predictor for ecological variables, including canopy greenness (normalized vegetation difference index, NDVI), canopy nitrogen, ET, and biomass. With increasing CO2, we found a decrease in ET and an increase in canopy nitrogen, both consistent with theory, suggesting more water- and nutrient-use-efficient canopies. However, we also observed a decrease in NDVI with increasing CO2 (a mean NDVI of 0.27 at 200 g m−2 d−1 CO2 reduced to a mean NDVI of 0.10 at 800 g m−2 d−1 CO2). This is inconsistent with theory though consistent with increased efficiency of fewer leaves. We found a decrease in above-ground biomass with increasing CO2, also inconsistent with theory, but we did also find a decrease in biomass variance, pointing to a long-term homogenization of structure with elevated CO2. Additionally, the relationships between ecological variables changed with elevated CO2, suggesting a shift in coupling/decoupling among ecosystem structure, composition, and function synergies. For example, ET and biomass were significantly correlated for areas without elevated CO2 flux but decoupled with elevated CO2 flux. This study demonstrates that (a) volcanic systems show great potential as a means to study the properties of ecosystems and their responses to elevated CO2 emissions and (b) these ecosystem responses are measurable using a suite of airborne remotely sensed data.
","language":"English","publisher":"European Biogeosciences Union","doi":"10.5194/bg-15-7403-2018","usgsCitation":"Cawse-Nicholson, K., Fisher, J.B., Famiglietti, C.A., Braverman, A., Schwandner, F.M., Lewicki, J.L., Townsend, P.A., Schimel, D.S., Pavlick, R., Bormann, K., Ferraz, A., Kang, E.L., Ma, P., Bogue, R.R., Youmans, T., and Pieri, D.C., 2018, Ecosystem responses to elevated CO2 using airborne remote sensing at Mammoth Mountain, California: Biogeosciences, v. 15, p. 7403-7418, https://doi.org/10.5194/bg-15-7403-2018.","productDescription":"16 p.","startPage":"7403","endPage":"7418","ipdsId":"IP-094903","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468185,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-15-7403-2018","text":"Publisher Index Page"},{"id":360330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","volume":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-14","publicationStatus":"PW","scienceBaseUri":"5c14cfb4e4b006c4f8545d1c","contributors":{"authors":[{"text":"Cawse-Nicholson, Kerry","contributorId":211502,"corporation":false,"usgs":false,"family":"Cawse-Nicholson","given":"Kerry","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Joshua B.","contributorId":211503,"corporation":false,"usgs":false,"family":"Fisher","given":"Joshua","email":"","middleInitial":"B.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Famiglietti, Caroline A.","contributorId":211504,"corporation":false,"usgs":false,"family":"Famiglietti","given":"Caroline","email":"","middleInitial":"A.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braverman, Amy","contributorId":211505,"corporation":false,"usgs":false,"family":"Braverman","given":"Amy","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwandner, Florian M.","contributorId":211506,"corporation":false,"usgs":false,"family":"Schwandner","given":"Florian","email":"","middleInitial":"M.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":754297,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Townsend, Philip A.","contributorId":211507,"corporation":false,"usgs":false,"family":"Townsend","given":"Philip","email":"","middleInitial":"A.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":754303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schimel, David S.","contributorId":211508,"corporation":false,"usgs":false,"family":"Schimel","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754304,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pavlick, Ryan","contributorId":211509,"corporation":false,"usgs":false,"family":"Pavlick","given":"Ryan","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754305,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bormann, Kathryn J.","contributorId":211510,"corporation":false,"usgs":false,"family":"Bormann","given":"Kathryn J.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754306,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ferraz, Antonio","contributorId":211511,"corporation":false,"usgs":false,"family":"Ferraz","given":"Antonio","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754307,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kang, Emily L.","contributorId":211512,"corporation":false,"usgs":false,"family":"Kang","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":38260,"text":"University of Cincinnnati","active":true,"usgs":false}],"preferred":false,"id":754308,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ma, Pulong","contributorId":211513,"corporation":false,"usgs":false,"family":"Ma","given":"Pulong","email":"","affiliations":[{"id":38260,"text":"University of Cincinnnati","active":true,"usgs":false}],"preferred":false,"id":754309,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bogue, Robert R.","contributorId":211528,"corporation":false,"usgs":false,"family":"Bogue","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754334,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Youmans, Thomas","contributorId":211529,"corporation":false,"usgs":false,"family":"Youmans","given":"Thomas","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754335,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pieri, David C.","contributorId":211514,"corporation":false,"usgs":false,"family":"Pieri","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754310,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70198779,"text":"ofr20181109 - 2018 - Southern Great Plains Rapid Ecoregional Assessment—Volume II. Species and assemblages","interactions":[],"lastModifiedDate":"2018-12-14T11:38:36","indexId":"ofr20181109","displayToPublicDate":"2018-12-13T17:15:00","publicationYear":"2018","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":"2018-1109","title":"Southern Great Plains Rapid Ecoregional Assessment—Volume II. Species and assemblages","docAbstract":"The Southern Great Plains Rapid Ecoregional Assessment was conducted in partnership with the Bureau of Land Management (BLM) and the Great Plains Landscape Conservation Cooperative. The overall goal of the Rapid Ecoregional Assessments (REAs) is to compile and synthesize regional datasets to facilitate evaluation of the cumulative effects of change agents on priority ecological communities and species. In particular, the REAs identify and map the distribution of communities and wildlife habitats at broad spatial extents and provide assessments of ecological conditions. The REAs also identify where and to what degree ecological resources are currently at risk from change agents, such as development, fire, invasive species, and climate change. The REAs can help managers identify and prioritize potential areas for conservation or restoration, assess cumulative effects as required by the National Environmental Policy Act, and inform landscape-level planning and management decisions for multiple uses of public lands.
Management questions form the basis for the REA framework and were developed in conjunction with the BLM and other stakeholders. Conservation elements are communities and species that are of regional management concern. Core management questions relate to the key ecological attributes and change agents associated with each conservation element. Integrated management questions synthesize the results of the primary core management questions into overall landscape-level ranks for each conservation element.
The ecological communities evaluated as conservation elements are shortgrass, mixed-grass, and sand prairies; all grasslands; riparian and nonplaya wetlands; playa wetlands and saline lakes; and prairie streams and rivers. Species and species assemblages evaluated are the freshwater mussel assemblage, Arkansas River shiner (Notropis girardi), ferruginous hawk (Buteo regalis), lesser prairie chicken (Tympanuchus pallidicinctus), snowy plover (Charadrius nivosus), mountain plover (Charadrius montanus), long-billed curlew (Numenius americanus), interior least tern (Sternula antillarum athalassos), burrowing owl (Athene cunicularia), black-tailed prairie dog (Cynomys ludovicianus), bat assemblage, swift fox (Vulpes velox), and mule deer (Odocoileus hemionus).
The Southern Great Plains REA is summarized in a series of three reports and associated datasets. The pre-assessment report (available online at https://doi.org/10.3133/ofr20151003) summarizes the process used by the REA stakeholders to select management questions, conservation elements, and change agents. It also provides background information for each conservation element. Volume I of the Southern Great Plains REA report addresses the ecological communities (available online at https://doi.org/10.3133/ofr20171100). Volume II (this volume) addresses the species and species assemblages. All source and derived datasets used to produce the maps and graphs for REAs are available online at the BLM Landscape Approach Data Portal (https://landscape.blm.gov/geoportal/catalog/REAs/REAs.page).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181109","collaboration":"Prepared in cooperation with the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative","usgsCitation":"Reese, G.C., Carr, N.B., and Burris, L.E., 2018, Southern Great Plains Rapid Ecoregional Assessment—Volume II. Species and assemblages (ver. 1.1, December 2018): U.S. Geological Survey Open-File Report 2018–1109, 134 p., https://doi.org/10.3133/ofr20181109.","productDescription":"xiii, 134 p.","onlineOnly":"Y","ipdsId":"IP-094978","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":360274,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2018/1109/versionHist.txt","text":"Version History","size":"4.00 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"},{"id":359623,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171100 ","text":"Open-File Report 2017-1100—","linkHelpText":"Southern Great Plains Rapid Ecoregional assessment—Volume I. Ecological communities"},{"id":359620,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1109/coverthb2.jpg"},{"id":359621,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1109/ofr20181109.pdf","text":"Report","size":"9.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1109"},{"id":359622,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20151003","text":"Open-File Report 2015–1003—","linkHelpText":"Southern Great Plains Rapid Ecoregional Assessment—Pre-Assessment Report"}],"country":"United States","state":"Colorado, Kansas, Nebraska, New Mexico, Oklahoma, Texas, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.14990234375,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 30.939924331023445\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: December 2018; Version 1.0: November 2018","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
The U.S. Geological Survey has created a hydrogeologic framework for Quaternary sediments in glaciated areas of the conterminous United States that categorizes, maps, and characterizes the glacial sediments at and beneath the land surface. The hydrogeologic framework divides the glaciated United States into 17 distinct hydrogeologic terranes using a geologic approach based on previous mapping, and was characterized using the Glacial Environments and Surficial Sediments geodatabase compiled from the Quaternary Atlas of the United States map series, the Surficial Materials Map of the United States, and several Integrated Geologic Map Databases for the United States; a groundwater use database compiled from public-supply, water-well data; and a lithologic database compiled from State-managed well records and geologic logs. This framework is to be used to assess the occurrence and characteristics of confined and unconfined glacial aquifers, their distribution and extent, and their potential intrinsic susceptibility and vulnerability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1090","usgsCitation":"Haj, A.E., Soller, D.R., Reddy, J.E., Kauffman, L.J., Yager, R.M., and Buchwald, C.A., 2018, Hydrogeologic framework for characterization and occurrence of confined and unconfined aquifers in quaternary sediments in the glaciated conterminous United States—A digital map compilation and database: U.S. Geological Survey Data Series 1090, 31 p., https://doi.org/10.3133/ds1090.\n\n","productDescription":"Report: vi, 31 p.; Interactive Maps; Data Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081250","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":359730,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20185091","text":"Scientific Investigations Report 2018-5091","linkHelpText":"- Characterization and occurrence of confined and unconfined aquifers in Quaternary sediments in the glaciated conterminous United States"},{"id":359725,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1090/coverthb.jpg"},{"id":359729,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HH6J8X","text":"USGS data release","description":"USGS data release","linkHelpText":"Digital products from a hydrogeologic framework for Quaternary sediments within the glaciated conterminous United States "},{"id":359726,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1090/ds1090.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1090"},{"id":359727,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1090/ds1090_index.html","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Index page for oversized, interactive Leaflet maps"},{"id":359728,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6PQG","text":"USGS data release","description":"USGS data release","linkHelpText":"Databases used to develop a hydrogeologic framework for Quaternary sediments in the glaciated conterminous United States"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.969069883,\n 35.090811167\n ],\n [\n -65.343237884,\n 35.090811167\n ],\n [\n -65.343237884,\n 50.932504994\n ],\n [\n -124.969069883,\n 50.932504994\n ],\n [\n -124.969069883,\n 35.090811167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street
Iowa City, IA 52240
This report is a user guide for the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) computer program (version 1.0). The CT SSWUE was developed by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics to assess sustainable water use at ungaged sites in Connecticut. The CT SSWUE provides estimates of unaltered streamflow (which is assumed to occur in the absence of any water withdrawals or wastewater discharges and with minimal human development), net streamflow alterations caused by water use, water-use-adjusted streamflow, streamflow yields (estimated unaltered streamflow minus user-defined flow targets), and estimates of the accuracy and uncertainty of estimated unaltered streamflow. The CT SSWUE uses basin characteristics and water-use volumes (water withdrawals and wastewater-return flows) obtained from the U.S. Geological Survey online StreamStats application to estimate the unaltered and water-use-adjusted streamflows. The CT SSWUE is a database application with a graphical user interface developed by using Visual Basic for Applications with the 32-bit version of Microsoft Access. The graphical user interface is designed to include full documentation for users: an introductory instruction form and onscreen help within each interactive form, including explanation buttons, context-sensitive help buttons, and tool-tip and status-bar messages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181163","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Granato, G.E., and Levin, S.B., 2018, User guide for the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE—version 1.0) computer program: U.S. Geological Survey Open-File Report 2018–1163, 7 p., https://doi.org/10.3133/ofr20181163.","productDescription":"vi, 7 p.","ipdsId":"IP-098955","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360048,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V6ARUS","text":"USGS data release","description":"USGS data release","linkHelpText":"Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) Application Software "},{"id":360046,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1163/ofr20181163.pdf","text":"Report","size":"360 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1163"},{"id":360045,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1163/coverthb.jpg"},{"id":360047,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20185135","text":"Scientific Investigations Report 2018–5135","linkHelpText":"- The Connecticut Streamflow and Sustainable Water Use Estimator: A Decision-Support Tool To Estimate Water Availability at Ungaged Stream Locations in Connecticut"}],"contact":"Director, New England Water Science Center
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