We determine Modified Mercalli (Seismic) Intensities (MMI) for nine onshore earthquakes of magnitude 4.5 and larger that occurred in central and western Washington between 1989 and 1999, on the basis of effects reported in postal questionnaires, the press, and professional collaborators. The earthquakes studied include four earthquakes of M5 and larger: the M5.0 Deming earthquake of April 13, 1990, the M5.0 Point Robinson earthquake of January 29, 1995, the M5.4 Duvall earthquake of May 3, 1996, and the M5.8 Satsop earthquake of July 3, 1999. The MMI are assigned using data and procedures that evolved at the U.S. Geological Survey (USGS) and its Department of Commerce predecessors and that were used to assign MMI to felt earthquakes occurring in the United States between 1931 and 1986. We refer to the MMI assigned in this report as traditional MMI, because they are based on responses to postal questionnaires and on newspaper reports, and to distinguish them from MMI calculated from data contributed by the public by way of the internet. Maximum traditional MMI documented for the M5 and larger earthquakes are VII for the 1990 Deming earthquake, V for the 1995 Point Robinson earthquake, VI for the 1996 Duvall earthquake, and VII for the 1999 Satsop earthquake; the five other earthquakes were variously assigned maximum intensities of IV, V, or VI. Starting in 1995, the Pacific Northwest Seismic Network (PNSN) published MMI maps for four of the studied earthquakes, based on macroseismic observations submitted by the public by way of the internet. With the availability now of the traditional USGS MMI interpreted for all the sites from which USGS postal questionnaires were returned, the four Washington earthquakes join a rather small group of earthquakes for which both traditional USGS MMI and some type of internet-based MMI have been assigned. The values and distributions of the traditional MMI are broadly similar to the internet-based PNSN intensities; we discuss some differences in detail that reflect differences in data-sampling procedure, differences in the procedure used to assign intensity numbers from macroseismic observations, and differences in how intensities are mapped.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171104","usgsCitation":"Brocher, T.M., Dewey, J.W., and Cassidy, J.F., 2017, Modified Mercalli Intensities for nine earthquakes in central and western Washington between 1989 and 1999: U.S. Geological Survey Open-File Report 2017–1104, 82 p., https://doi.org/10.3133/ofr20171104.","productDescription":"v, 82 p.","numberOfPages":"87","onlineOnly":"Y","ipdsId":"IP-080341","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344861,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1104/ofr2017.1104.pdf","text":"Report","size":"4.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1104"},{"id":344860,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1104/coverthb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.925048828125,\n 44.12702800650004\n ],\n [\n -116.90551757812499,\n 44.12702800650004\n ],\n [\n -116.90551757812499,\n 49.78835749241399\n ],\n [\n -126.925048828125,\n 49.78835749241399\n ],\n [\n -126.925048828125,\n 44.12702800650004\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"USGS Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road
Mail Stop 977
Menlo Park, CA 94025
In 2005, the U.S. Geological Survey began a cooperative study with New York City Department of Environmental Protection to characterize the local groundwater-flow system and identify potential sources of seeps on the southern embankment at the Hillview Reservoir in southern Westchester County, New York. Monthly site inspections at the reservoir indicated an approximately 90-square-foot depression in the land surface directly upslope from a seep that has episodically flowed since 2007. In July 2008, the U.S. Geological Survey surveyed the topography of land surface in this depression area by collecting high-accuracy (resolution less than 1 inch) measurements. A point of origin was established for the topographic survey by using differentially corrected positional data collected by a global navigation satellite system. Eleven points were surveyed along the edge of the depression area and at arbitrary locations within the depression area by using robotic land-surveying techniques. The points were surveyed again in March 2012 to evaluate temporal changes in land-surface altitude. Survey measurements of the depression area indicated that the land-surface altitude at 8 of the 11 points decreased beyond the accepted measurement uncertainty during the 44 months from July 2008 to March 2012. Two additional control points were established at stable locations along Hillview Avenue, which runs parallel to the embankment. These points were measured during the July 2008 survey and measured again during the March 2012 survey to evaluate the relative accuracy of the altitude measurements. The relative horizontal and vertical (altitude) accuracies of the 11 topographic measurements collected in March 2012 were ±0.098 and ±0.060 feet (ft), respectively. Changes in topography at 8 of the 11 points ranged from 0.09 to 0.63 ft and topography remained constant, or within the measurement uncertainty, for 3 of the 11 points.
Two cross sections were constructed through the depression area by using land-surface altitude data that were interpolated from positional data collected during the two topographic surveys. Cross section A–A′ was approximately 8.5 ft long and consisted of three surveyed points that trended north to south across the depression. Land-surface altitude change decreased along the entire north-south trending cross section during the 44 months, and ranged from 0.2 to more than 0.6 ft. In general, greater land-surface altitude change was measured north of the midpoint as compared to south of the midpoint of the cross section. Cross section B–B′ was 18 ft long and consisted of six surveyed points that trended east to west across the depression. Land-surface altitude change generally decreased or remained constant along the east-west trending cross section during the 44 months and ranged from 0.0 to 0.3 ft. Volume change of the depression area was calculated by using a three-dimensional geographic information system utility that subtracts interpolated surfaces. The results indicated a net volume loss of approximately 38 ±5 cubic feet of material from the depression area during the 44 months.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171028","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Noll, M.L., and Chu, Anthony, 2017, Detecting temporal change in land-surface altitude using robotic land-surveying techniques and geographic information system applications at an earthen dam site in southern Westchester County, New York: U.S. Geological Survey Open-File Report 2017–1028, 15 p., https://doi.org/10.3133/ofr20171028.","productDescription":"vi, 15 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077425","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":344641,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1028/ofr20171028.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1028"},{"id":344640,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1028/coverthb.jpg"}],"country":"United States","state":"New York","county":"Westchester County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.88648986816406,\n 40.894180824484465\n ],\n [\n -73.85250091552734,\n 40.894180824484465\n ],\n [\n -73.85250091552734,\n 40.92726192578736\n ],\n [\n -73.88648986816406,\n 40.92726192578736\n ],\n [\n -73.88648986816406,\n 40.894180824484465\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
2045 Route 112, Building 4
Coram, NY 11727
Greater sage-grouse (Centrocercus urophasianus; hereinafter, \"sage-grouse\") are highly dependent on sagebrush (Artemisia spp.) dominated vegetation communities for food and cover from predators. Although this species requires the presence of sagebrush shrubs in the overstory, it also inhabits a broad geographic distribution with significant gradients in precipitation and temperature that drive variation in sagebrush ecosystem structure and concomitant shrub understory conditions. Variability in understory conditions across the species’ range may be responsible for the sometimes contradictory findings in the scientific literature describing sage-grouse habitat use and selection during important life history stages, such as nesting. To help understand the importance of this variability and to help guide management actions, we evaluated the nesting and brood-rearing microhabitat factors that influence selection and survival patterns in the Great Basin using a large dataset of microhabitat characteristics from study areas spanning northern Nevada and a portion of northeastern California from 2009 to 2016. The spatial and temporal coverage of the dataset provided a powerful opportunity to evaluate microhabitat factors important to sage-grouse reproduction, while also considering habitat variation associated with different climatic conditions and areas affected by wildfire. The summary statistics for numerous microhabitat factors, and the strength of their association with sage-grouse habitat selection and survival, are provided in this report to support decisions by land managers, policy-makers, and others with the best-available science in a timely manner.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171087","collaboration":"Prepared in cooperation with the Bureau of Land Management and Nevada Department of Wildlife","usgsCitation":"Coates, P.S., Brussee, B.E., Ricca, M.A., Dudko, J.E., Prochazka, B.G., Espinosa, S.P., Casazza, M.L., and Delehanty, D.J., 2017, Greater sage-grouse (Centrocercus urophasianus) nesting and brood-rearing microhabitat in Nevada and California—Spatial variation in selection and survival patterns: U.S. Geological Survey Open-File Report 2017-1087, 79 p., https://doi.org/10.3133/ofr20171087.","productDescription":"Report: viii, 79 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087866","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":344631,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76M35BC","text":"USGS data release","description":"USGS data release","linkHelpText":"Summary statistics data for greater sage-grouse (Centrocercus urophasianus) nesting and brood-rearing microhabitat in Nevada and California—Spatial variation in selection and survival patterns, 2009–16"},{"id":344629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1087/coverthb.jpg"},{"id":344630,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1087/ofr20171087.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1087"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.9,\n 34\n ],\n [\n -113,\n 34\n ],\n [\n -113,\n 42.25\n ],\n [\n -121.9,\n 42.25\n ],\n [\n -121.9,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Population ecologists have long recognized the importance of ecological scale in understanding processes that guide observed demographic patterns for wildlife species. However, directly incorporating spatial and temporal scale into monitoring strategies that detect whether trajectories are driven by local or regional factors is challenging and rarely implemented. Identifying the appropriate scale is critical to the development of management actions that can attenuate or reverse population declines. We describe a novel example of a monitoring framework for estimating annual rates of population change for greater sage-grouse (Centrocercus urophasianus) within a hierarchical and spatially nested structure. Specifically, we conducted Bayesian analyses on a 17-year dataset (2000–2016) of lek counts in Nevada and northeastern California to estimate annual rates of population change, and compared trends across nested spatial scales. We identified leks and larger scale populations in immediate need of management, based on the occurrence of two criteria: (1) crossing of a destabilizing threshold designed to identify significant rates of population decline at a particular nested scale; and (2) crossing of decoupling thresholds designed to identify rates of population decline at smaller scales that decouple from rates of population change at a larger spatial scale. This approach establishes how declines affected by local disturbances can be separated from those operating at larger scales (for example, broad-scale wildfire and region-wide drought). Given the threshold output from our analysis, this adaptive management framework can be implemented readily and annually to facilitate responsive and effective actions for sage-grouse populations in the Great Basin. The rules of the framework can also be modified to identify populations responding positively to management action or demonstrating strong resilience to disturbance. Similar hierarchical approaches might be beneficial for other species occupying landscapes with heterogeneous disturbance and climatic regimes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171089","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Coates, P.S., Prochazka, B.G., Ricca, M.A., Wann, G.T., Aldridge, C.L., Hanser, S.E., Doherty, K.E., O’Donnell, M.S., Edmunds, D.R., and, Espinosa, S.P., 2017, Hierarchical population monitoring of greater sage-grouse (Centrocercus urophasianus) in Nevada and California—Identifying populations for management at the appropriate spatial scale: U.S. Geological Survey Open-File Report 2017-1089, 49 p., https://doi.org/10.3133/ofr20171089.","productDescription":"viii, 49 p.","onlineOnly":"Y","ipdsId":"IP-087898","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":344634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1089/ofr20171089.pdf","text":"Report","size":"15.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1089"},{"id":344633,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1089/coverthb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.9,\n 34\n ],\n [\n -113,\n 34\n ],\n [\n -113,\n 42.25\n ],\n [\n -121.9,\n 42.25\n ],\n [\n -121.9,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The distribution and abundance of pinyon (Pinus monophylla) and juniper (Juniperus osteosperma, J. occidentalis) trees (hereinafter, \"pinyon-juniper\") in sagebrush (Artemisia spp.) ecosystems of the Great Basin in the Western United States has increased substantially since the late 1800s. Distributional expansion and infill of pinyon-juniper into sagebrush ecosystems threatens the ecological function and economic viability of these ecosystems within the Great Basin, and is now a major contemporary challenge facing land and wildlife managers. Particularly, pinyon-juniper encroachment into intact sagebrush ecosystems has been identified as a primary threat facing populations of greater sage-grouse (Centrocercus urophasianus; hereinafter, \"sage-grouse\"), which is a sagebrush obligate species. Even seemingly innocuous scatterings of isolated pinyon-juniper in an otherwise intact sagebrush landscape can negatively affect survival and reproduction of sage-grouse. Therefore, accurate and high-resolution maps of pinyon-juniper distribution and abundance (indexed by canopy cover) across broad geographic extents would help guide land management decisions that better target areas for pinyon-juniper removal projects (for example, fuel reduction, habitat improvement for sage-grouse, and other sagebrush species) and facilitate science that further quantifies ecological effects of pinyon-juniper encroachment on sage-grouse populations and sagebrush ecosystem processes. Hence, we mapped pinyon-juniper (referred to as conifers for actual mapping) at a 1 × 1-meter (m) high resolution across the entire range of previously mapped sage-grouse habitat in Nevada and northeastern California.
We used digital orthophoto quad tiles from National Agriculture Imagery Program (2010, 2013) as base imagery, and then classified conifers using automated feature extraction methodology with the program Feature Analyst™. This method relies on machine learning algorithms that extract features from imagery based on their spectral and spatial signatures. We classified conifers in 6,230 tiles and then tested for errors of omission and commission using confusion matrices. Accuracy ranged from 79.1 to 96.8, with an overall accuracy of 84.3 percent across all mapped areas. An estimated accuracy coefficient (kappa) indicated substantial to nearly perfect agreement, which varied across mapped areas. For this mapping process across the entire mapping extent, four sets of products are available at https://doi.org/10.5066/F7348HVC, including (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at a 1 × 1 m resolution; (3) a 30 × 30 m resolution raster representing percentages of conifer canopy cover within each cell from 0 to 100; and (4) 1 × 1 m resolution canopy cover classification rasters derived from a 50-m-radius moving window analysis. The latter two products can be reclassified in a geographic information system (GIS) into user-specified bins to meet different objectives, which include approximations for phases of encroachment. These products complement, and in some cases improve upon, existing conifer maps in the Western United States, and will help facilitate sage-grouse habitat management and sagebrush ecosystem restoration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171093","collaboration":"Prepared in cooperation with the Bureau of Land Management and Nevada Department of Wildlife","usgsCitation":"Coates, P.S., Gustafson, K.B., Roth, C.L., Chenaille, M.P., Ricca, M.A., Mauch, Kimberly, Sanchez-Chopitea, Erika, Kroger, T.J., Perry, W.M., and Casazza, M.L., 2017, Using object-based image analysis to conduct high-resolution conifer extraction at regional spatial scales: U.S. Geological Survey Open-File Report 2017-1093, 40 p., https://doi.org/10.3133/ofr20171093.","productDescription":"Report: vi, 40 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088288","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":344637,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7348HVC","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data for object-based high-resolution classification of conifers within greater sage-grouse habitat across Nevada and a portion of northeastern California"},{"id":344635,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1093/coverthb.jpg"},{"id":344636,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1093/ofr20171093.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1093"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.9,\n 34\n ],\n [\n -113,\n 34\n ],\n [\n -113,\n 42.25\n ],\n [\n -121.9,\n 42.25\n ],\n [\n -121.9,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
We built a population viability analysis (PVA) model to predict future population status of the lesser prairie-chicken (Tympanuchus pallidicinctus, LEPC) in four ecoregions across the species’ range. The model results will be used in the U.S. Fish and Wildlife Service's (FWS) Species Status Assessment (SSA) for the LEPC. Our stochastic projection model combined demographic rate estimates from previously published literature with demographic rate estimates that integrate the influence of climate conditions. This LEPC PVA projects declining populations with estimated population growth rates well below 1 in each ecoregion regardless of habitat or climate change. These results are consistent with estimates of LEPC population growth rates derived from other demographic process models. Although the absolute magnitude of the decline is unlikely to be as low as modeling tools indicate, several different lines of evidence suggest LEPC populations are declining.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171071","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Cummings, J.W., Converse, S.J., Moore, C.T., Smith, D.R., Nichols, C.T., Allan, N.L., and O'Meilia, C.M., 2017, A projection of lesser prairie chicken (Tympanuchus pallidicinctus) populations range-wide: U.S. Geological Survey Open-File Report 2017-1071, 60 p., https://doi.org/10.3133/ofr20171071.","productDescription":"vi, 60 p.","onlineOnly":"Y","ipdsId":"IP-087040","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":343047,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1071/coverthb.jpg"},{"id":343048,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1071/ofr20171071.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1071"}],"country":"United States","state":"Colorado, Kansas, New Mexico, Oklahoma, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.99609375,\n 32.045332838858506\n ],\n [\n -98.3056640625,\n 32.045332838858506\n ],\n [\n -98.3056640625,\n 39.436192999314095\n ],\n [\n -105.99609375,\n 39.436192999314095\n ],\n [\n -105.99609375,\n 32.045332838858506\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Leader, Washington Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
Fishery Sciences Building, Box 355020
University of Washington
Seattle, Washington, 98195
The U.S. Army Corps of Engineers (USACE) operates the Willamette Valley Project (Project) in northwestern Oregon, which includes a series of dams, reservoirs, revetments, and fish hatcheries. Project dams were constructed during the 1950s and 1960s on rivers that supported populations of spring Chinook salmon (Oncorhynchus tshawytscha), winter steelhead (O. mykiss), and other anadromous fish species in the Willamette River Basin. These dams, and the reservoirs they created, negatively affected anadromous fish populations. Efforts are currently underway to improve passage conditions within the Project and enhance populations of anadromous fish species. Research on downstream fish passage within the Project has occurred since 1960 and these efforts are documented in numerous reports and publications. These studies are important resources to managers in the Project, so the USACE requested a synthesis of existing literature that could serve as a resource for future decision-making processes. In 2016, the U.S. Geological Survey conducted an extensive literature review on downstream fish passage studies within the Project. We identified 116 documents that described studies conducted during 1960–2016. Each of these documents were obtained, reviewed, and organized by their content to describe the state-of-knowledge within four subbasins in the Project, which include the North Santiam, South Santiam, McKenzie, and Middle Fork Willamette Rivers. In this document, we summarize key findings from various studies on downstream fish passage in the Willamette Project. Readers are advised to review specific reports of interest to insure that study methods, results, and additional considerations are fully understood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171101","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hansen, A.C., Kock, T.J., and Hansen, G.S., 2017, Synthesis of downstream fish passage information at projects owned by the U.S. Army Corps of Engineers in the Willamette River Basin, Oregon: U.S. Geological Survey Open File Report 2017-1101, 118 p., https://doi.org/10.3133/ofr20171101.","productDescription":"viii, 118 p.","onlineOnly":"Y","ipdsId":"IP-084048","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":344627,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1101/coverthb.jpg"},{"id":344628,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1101/ofr20171101.pdf","text":"Report","size":"14.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1101"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.431396484375,\n 44.11125397357155\n ],\n [\n -121.4208984375,\n 44.11125397357155\n ],\n [\n -121.4208984375,\n 45.537136680398596\n ],\n [\n -123.431396484375,\n 45.537136680398596\n ],\n [\n -123.431396484375,\n 44.11125397357155\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Barrier islands are dynamic environments due to their position at the land-sea interface. Storms, waves, tides, currents, and relative sea-level rise are powerful forces that shape barrier island geomorphology and habitats (for example, beach, dune, marsh, and forest). Hurricane Katrina in 2005 and the Deep Water Horizon oil spill in 2010 are two major events that have affected habitats and natural resources on Dauphin Island, Alabama. The latter event prompted a collaborative effort between the U.S. Geological Survey, the U.S. Army Corps of Engineers, and the State of Alabama funded by the National Fish and Wildlife Foundation to investigate viable, sustainable restoration options that protect and restore the natural resources of Dauphin Island, Alabama.
In order to understand the feasibility and sustainability of various restoration scenarios, it is important to understand current conditions on Dauphin Island. To further this understanding, a detailed 19-class habitat map for Dauphin Island was produced from 1-foot aerial infrared photography collected on December 4, 2015, and lidar data collected in January 2015. We also conducted a ground survey of habitat types, vegetation community structure, and elevations in November and December 2015. These products provide baseline data regarding the ecological and general geomorphological attributes of the area, which can be compared with observations from other dates for tracking changes over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171083","collaboration":"Prepared in collaboration with the U.S. Army Corps of Engineers","usgsCitation":"Enwright, N.M., Borchert, S.M., Day, R.H., Feher, L.C., Osland, M.J., Wang, Lei, and Wang, Hongqing, 2017, Barrier island habitat map and vegetation survey—Dauphin Island, Alabama, 2015: U.S. Geological Survey Open-File Report 2017–1083, 17 p., https://doi.org/10.3133/ofr20171083.","productDescription":"Report: vi, 17 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087262","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":344579,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7513WPC","text":"USGS - Data Release","description":"USGS Data Release","linkHelpText":"Barrier island habitat map and vegetation survey, Dauphin Island, AL, 2015"},{"id":344578,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1083/ofr20171083.pdf","size":"2.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1083"},{"id":344577,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1083/coverthb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.37127685546875,\n 30.20626765511821\n ],\n [\n -88.05541992187499,\n 30.20626765511821\n ],\n [\n -88.05541992187499,\n 30.288717426233095\n ],\n [\n -88.37127685546875,\n 30.288717426233095\n ],\n [\n -88.37127685546875,\n 30.20626765511821\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
The U.S. Army Garrison Fort Carson (AGFC) and the Piñon Canyon Maneuver Site (PCMS) are facilities operated by the U.S. Department of the Army in southern Colorado. The U.S. Geological Survey, in cooperation with the U.S. Department of the Army, established a hydrologic and water-quality data-collection network at the AGFC in June 1978 and at the PCMS in October 1982. The data-collection networks are designed to assess the quantity and quality of water resources and monitor the effects of military training activities on streamflow and water quality. Two preexisting U.S. Geological Survey streamgages at the PCMS were incorporated into the data-collection network at the time it was established, providing periods of record that begin as early as 1966. This report presents and summarizes precipitation, streamflow, suspended-sediment, and water-quality data from 34 U.S. Geological Survey sites on or near the AGFC and the PCMS for the period of record at each site. (Streamflow data are presented as discharge in cubic feet per second.)
At AGFC, daily sum precipitation ranged from 0 to 11.85 inches, daily mean discharge ranged from 0 to 836 cubic feet per second, and daily mean suspended-sediment discharge ranged from 0 to 39,900 tons per day. With the exception of total (unfiltered) mercury and filtered sulfate at two sites and filtered manganese at three sites, 95th percentile trace element concentrations and median total (unfiltered) metal concentrations were less than regulatory numeric standards for all samples. However, individual water-quality results occasionally exceeded respective regulatory numeric standards.
At the PCMS, daily sum precipitation ranged from 0 to 4.59 inches, daily mean discharge ranged from 0 to 4,190 cubic feet per second, and daily mean suspended-sediment discharge ranged from 0 to 21,100 tons per day. Water-quality results, 95th percentile trace element concentrations, and median total (unfiltered) metal concentrations were less than regulatory numeric standards for most properties and constituents except for filtered chloride at one site, filtered sulfate at six sites, filtered phosphorus at one site, filtered manganese at three sites, and total (unfiltered) iron at three sites. Individual water-quality values also occasionally exceeded respective regulatory numeric standards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171072","collaboration":"Prepared in cooperation with the U.S. Department of the Army","usgsCitation":"Arnold, L.R., 2017, Precipitation, streamflow, suspended-sediment, and water-quality data for the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, 1966–2015: U.S. Geological Survey Open-File Report 2017–1072, 130 p., https://doi.org/10.3133/ofr20171072.","productDescription":"v, 129 p.","onlineOnly":"Y","ipdsId":"IP-086258","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":344560,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1072/ofr20171072.pdf","text":"Report","size":"4.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1072"},{"id":344559,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1072/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Piñon Canyon Maneuver Site, U.S. Army Garrison Fort Carson","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.05,\n 38.77\n ],\n [\n -104.59,\n 38.77\n ],\n [\n -104.59,\n 38.4\n ],\n [\n -105.05,\n 38.4\n ],\n [\n -105.05,\n 38.77\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
Great Lakes fishery managers have the opportunity and have expressed interest in reestablishing a native forage base in the Great Lakes consisting of various forms and species within the genus Coregonus. This report summarizes the proceedings of a workshop focused on a subset of the genus, and the term “coregonines” is used to refer to several species of deepwater ciscoes (also known as “chubs”) and the one more pelagic-oriented cisco species (Coregonus artedi, also known as “lake herring”). As the principal conservation agency for the United States Government, the Department of Interior has unique and significant authorities and capacities to support a coregonine reestablishment program in the Great Lakes. To identify and discuss key uncertainties associated with such a program and develop a coordinated approach, the U.S. Geological Survey (USGS) and the U.S. Fish and Wildlife Service (FWS), the principal Department of the Interior bureaus to address Great Lakes fishery issues, held the first of a series of workshops on coregonine science in Ann Arbor, Michigan, on October 11–13, 2016. Workshop objectives were to identify (1) perceived key uncertainties associated with coregonine restoration in the Great Lakes and (2) DOI capacities for addressing these key uncertainties.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171081","usgsCitation":"Bronte, C.R., Bunnell, D.B., David, S.R., Gordon, Roger, Gorsky, Dimitry, Millard, M.J., Read, Jennifer, Stein, R.A., and Vaccaro, Lynn, 2017, Report from the Workshop on Coregonine Restoration Science: U.S. Geological Survey Open-File Report 2017–1081, 23 p., https://doi.org/10.3133/ofr20171081.","productDescription":"vi, 23 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087856","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":344507,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1081/ofr20171081.pdf","text":"Report","size":"902 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1081"},{"id":344506,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1081/coverthb.jpg"}],"publicComments":"Convened by the Coregonid Steering Committee, with membership from U.S. Fish and Wildlife Service and U.S. Geological Survey, on October 11–13, 2016","contact":"Director, Great Lakes Science Center
U.S. Geological Survey
1451 Green Rd.
Ann Arbor, MI 48105
Continuous records of discharge and turbidity at a U.S. Geological Survey (USGS) streamgage in the lower Stillaguamish River were paired with discrete measurements of suspended-sediment concentration (SSC) in order to estimate suspended-sediment loads over the water years 2014 and 2015. First, relations between turbidity and SSC were developed and used to translate the continuous turbidity record into a continuous estimate of SSC. Those concentrations were then used to predict suspended-sediment loads based on the current discharge record, reported at daily intervals. Alternative methods were used to in-fill a small number of days with either missing periods of turbidity or discharge records. Uncertainties in our predictions at daily and annual time scales were estimated based on the parameter uncertainties in our turbidity-SSC regressions. Daily loads ranged from as high as 121,000 tons during a large autumn storm to as low as –56 tons, when tidal return flow moved more sediment upstream than river discharge did downstream. Annual suspended-sediment loads for both water years were close to 1.4 ± 0.2 million tons.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171066","usgsCitation":"Anderson, S.W., Curran, C.A., and Grossman, E.E., 2017, Suspended-sediment loads in the lower Stillaguamish River, Snohomish County, Washington, 2014–15: U.S. Geological Survey Open-File Report 2017–1066, 10 p., https://doi.org/10.3133/ofr20171066.","productDescription":"Report: iv, 10 p.; Table","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085882","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":344567,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1066/coverthb.jpg"},{"id":344568,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1066/ofr2017.1066.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1066"},{"id":344569,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2017/1066/ofr20171066_table03.xlsx","text":"Table 3","size":"46 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2017-1066"}],"country":"United States","state":"Washington","county":"Snohomish County","otherGeospatial":"Lower Stillaguamish River","contact":"Director,
Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
This report describes the U.S. Geological Survey’s (USGS) ongoing commitment to its mission of understanding the nature and distribution of global mineral commodity supply chains by updating and publishing the georeferenced locations of mineral commodity production and processing facilities, mineral exploration and development sites, and mineral commodity exporting ports in Latin America and the Caribbean. The report includes an overview of data sources and an explanation of the geospatial PDF map format.
The geodatabase and geospatial data layers described in this report create a new geographic information product in the form of a geospatial portable document format (PDF) map. The geodatabase contains additional data layers from USGS, foreign governmental, and open-source sources as follows: (1) coal occurrence areas, (2) electric power generating facilities, (3) electric power transmission lines, (4) hydrocarbon resource cumulative production data, (5) liquefied natural gas terminals, (6) oil and gas concession leasing areas, (7) oil and gas field center points, (8) oil and gas pipelines, (9) USGS petroleum provinces, (10) railroads, (11) recoverable proven plus probable hydrocarbon resources, (12) major cities, (13) major rivers, and (14) undiscovered porphyry copper tracts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171079","collaboration":"Prepared in cooperation with the Inter-American Development Bank","usgsCitation":"Baker, M.S., Buteyn, S.D., Freeman, P.A., Trippi, M.H., and Trimmer, L.M., III, 2017, Compilation of geospatial data for the mineral industries and related infrastructure of Latin America and the Caribbean: U.S. Geological Survey Open-File Report 2017–1079, 87 p., 1 geodatabase and 1 geospatial PDF map, https://doi.org/10.3133/ofr20171079. ","productDescription":"Report: xi, 87 p; 3 Data Releases; Geodatabase and Metadata; Map: 8.5 x 11.0 inches","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078672","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":438258,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BZ6460","text":"USGS data release","linkHelpText":"Mineral commodity exporting ports of Latin America and the Caribbean"},{"id":344263,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/58093603e4b0f497e78f3f31","text":"USGS data release","description":"USGS data release","linkHelpText":"Mineral commodity exporting ports of Latin America and the Caribbean"},{"id":344257,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1079/coverthb.jpg"},{"id":344258,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1079/ofr20171079.pdf","text":"Report","size":"4.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1079"},{"id":344259,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1079/ofr20171079_lac-indust-infra.pdf","text":"Geospatial Map","size":"29 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Compilation of Geospatial Data for the Mineral Industries and Related Infrastructure of Latin America and the Caribbean"},{"id":344260,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2017/1079/ofr20171079_lac-indust-infra.zip","text":"Geodatabase and metadata","size":"28.7 MB","linkFileType":{"id":6,"text":"zip"}},{"id":344261,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MG7MM6","text":"USGS data release","description":"USGS data release","linkHelpText":"Mineral facilities of Latin America and the Caribbean"},{"id":344262,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GQ6VWG","text":"USGS data release","description":"USGS data release","linkHelpText":"Mineral exploration sites of Latin America and the Caribbean"}],"otherGeospatial":"Caribbean, Latin America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.828125,\n -57.51582286553883\n ],\n [\n -29.179687499999996,\n -57.51582286553883\n ],\n [\n -29.179687499999996,\n 34.30714385628804\n ],\n [\n -118.828125,\n 34.30714385628804\n ],\n [\n -118.828125,\n -57.51582286553883\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Multiyear remote sensing mapping of the normalized difference vegetation index (NDVI) was carried out as an indicator of live biomass composition of the Phragmites australis (hereafter Phragmites) marsh in the lower Mississippi River Delta (hereafter delta) from 2014 to 2017. Maps of NDVI change showed that the Phragmites condition was fairly stable between May 2014 and July 2015. From July 2015 to April 2016 NDVI change indicated Phragmites suffered a widespread decline in the live biomass proportion. Between April and September 2016, most marsh remained unchanged from the earlier period or showed improvement; although there were pockets of continued decline scattered throughout the lower delta. From September 2016 to May 2017 a pronounced and widely exhibited decline in the condition of Phragmites marsh again occurred throughout the lower delta. This final NDVI change mapping supported field observations of Phragmites decline during the same period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171098","usgsCitation":"Ramsey, E.W., III, and Rangoonwala, Amina, 2017, Mapping the change of Phragmites australis live biomass in the lower Mississippi River Delta marshes: U.S. Geological Survey Open-File Report 2017–1098, https://doi.org/10.3133/ofr20171098.","productDescription":"HTML Document","onlineOnly":"Y","ipdsId":"IP-088917","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":344420,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1098/","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2017-1098 HTML"},{"id":344433,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1098/images/coverthb.png"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Mississippi River delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.5,\n 29.5\n ],\n [\n -89,\n 29.5\n ],\n [\n -89,\n 28.9\n ],\n [\n -89.5,\n 28.9\n ],\n [\n -89.5,\n 29.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
A sound understanding of sources contributing to instream sediment flux in a watershed is important when developing total maximum daily load (TMDL) management strategies designed to reduce suspended sediment in streams. Sediment fingerprinting and sediment budget approaches are two techniques that, when used jointly, can qualify and quantify the major sources of sediment in a given watershed. The sediment fingerprinting approach uses trace element concentrations from samples in known potential source areas to determine a clear signature of each potential source. A mixing model is then used to determine the relative source contribution to the target suspended sediment samples.
The computational steps required to apportion sediment for each target sample are quite involved and time intensive, a problem the Sediment Source Assessment Tool (Sed_SAT) addresses. Sed_SAT is a user-friendly statistical model that guides the user through the necessary steps in order to quantify the relative contributions of sediment sources in a given watershed. The model is written using the statistical software R (R Core Team, 2016b) and utilizes Microsoft Access® as a user interface but requires no prior knowledge of R or Microsoft Access® to successfully run the model successfully. Sed_SAT identifies outliers, corrects for differences in size and organic content in the source samples relative to the target samples, evaluates the conservative behavior of tracers used in fingerprinting by applying a “Bracket Test,” identifies tracers with the highest discriminatory power, and provides robust error analysis through a Monte Carlo simulation following the mixing model. Quantifying sediment source contributions using the sediment fingerprinting approach provides local, State, and Federal land management agencies with important information needed to implement effective strategies to reduce sediment. Sed_SAT is designed to assist these agencies in applying the sediment fingerprinting approach to quantify sediment sources in the sediment TMDL framework.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171062","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Gorman Sanisaca, L.E., Gellis, A.C., and Lorenz, D.L., 2017, Determining the sources of fine-grained sediment using the Sediment Source Assessment Tool (Sed_SAT): U.S. Geological Survey Open File Report 2017–1062, 104 p., https://doi.org/10.3133/ofr20171062.","productDescription":"Report: viii, 104 p.; Application Site","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079059","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":438259,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76Q1VBX","text":"USGS data release","linkHelpText":"Sediment Source Assessment Tool (Sed_SAT)"},{"id":344315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1062/coverthb2.jpg"},{"id":344316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1062/ofr20171062.pdf","text":"Report","size":"18.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1062"},{"id":344317,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://doi.org/10.5066/F76Q1VBX","text":"Sed_Sat Software","linkHelpText":"- Determining the Sources of Fine-Grained Sediment Using the Sediment Source Assessment Tool (Sed_SAT)"}],"contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
The Central Utah Water Conservancy District (CUWCD) is proposing to deliver supplemental flow to Hobble Creek from Strawberry Reservoir through the Mapleton-Springville Lateral pipeline. A substantial portion of the supplemental water is intended to benefit June Sucker recovery and other fish and wildlife along Hobble Creek. The objective of this study was to determine gains or losses of water in a section of Hobble Creek between the Island Dam and the Swenson Dam (the primary study reach) during different seasons and flow conditions.
Paired measurements of flow in Hobble Creek were made during June to November 2016, at sites bracketing the primary study reach from site HC3 to HC6. These measurements showed increased streamflow in this reach that ranged from 6.1 cubic feet per second (ft3/s) to 9.3 ft3/s. During August and November, two sets of measurements were made at several locations along the study reach to document baseline conditions, and then an additional amount of water (a pulse of about 9–10 ft3/s) from Strawberry Reservoir through the Mapleton-Springville Lateral pipeline, was added to the reach. During the August 23 measurements, the average change at the upstream site (HC3) relative to the pulse was 9.3 ft3/s, and the average change at the downstream site (HC6) was about 8.4 ft3/s, leaving about 0.9 ft3/s of the additional water unaccounted for at site HC6. However, there was no significant difference between the net streamflow volume at sites HC3 and HC6 associated with the pulse that would indicate water was being lost. During the November 7–9 streamflow measurements, the average change in discharge at site HC3 relative to an increase in flow from the Mapleton-Springville Lateral pipeline (the pulse) was 9.6 ft3/s, and the average change at site HC6 was about 9.8 ft3/s. On the basis of these measurements it appears that the entire amount of the pulse added to the stream at site HC3 was accounted for at site HC6. Additionally, there was no significant difference between the net streamflow volume at sites HC3 and HC8 associated with the pulse that would indicate water was being lost.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171084","collaboration":"Prepared in cooperation with the Central Utah Water Conservancy District","usgsCitation":"Gerner, S.J., 2017, Streamflow investigations on a reach of Hobble Creek near Springville, Utah: U.S. Geological Survey Open-File Report 2017–1084, 9 p., https://doi.org/10.3133/ofr20171084.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-083190","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":344300,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1084/ofr.20171084.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1084"},{"id":344298,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1084/coverthb.jpg"}],"country":"United States","state":"Utah","city":"Springville","otherGeospatial":"Hobble Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.65834426879881,\n 40.1338721947653\n ],\n [\n -111.55157089233398,\n 40.1338721947653\n ],\n [\n -111.55157089233398,\n 40.181627516058576\n ],\n [\n -111.65834426879881,\n 40.181627516058576\n ],\n [\n -111.65834426879881,\n 40.1338721947653\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Five passive membrane samplers were deployed for 28 continuous days at select sites along and near the west Maui coastline to assess organic compounds and contaminant inputs to diverse, shallow coral reef ecosystems. Daily and weekly fluctuations in such inputs were captured on the membranes using integrative sampling. The distribution of organic compounds observed at these five coastal sites showed considerable variation; with high concentrations of terrestrially sourced organic compounds such as C29 sterols and high molecular weight n-alkanes at the strongly groundwater-influenced Kahekili vent site. In comparison, the coastal sites were presumably influenced more by seasonal surface and stream water runoff and therefore had marine-sourced organic compounds and fewer pharmaceuticals and personal care products. The direct correlation to upstream land-use practices was not obvious and may require additional wet-season sampling. Pharmaceuticals and personal care products as well as flame retardants were detected at all sites, and the Kahekili vent site had the highest number of detections. Planned future work must also determine the organic compound and contaminant concentrations adsorbed onto water column particulate matter, because it may also be an important vector for contaminant transport to coral reef ecosystems. The impact of contaminants per individual (such as fecundity and metabolism) as well as per community (such as species abundance and diversity) is necessary for an accurate assessment of environmental stress. Results presented herein provide current contaminant inputs to select nearshore environments along the west Maui coastline captured during the dry season, and they can be useful to aid potential future evaluations and (or) comparisons.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171097","collaboration":"Prepared in cooperation with U.S. Environmental Protection Agency and the State of Hawaii Department of Health","usgsCitation":"Campbell, P.L., Prouty, N.G., Storlazzi, C.D., and D’Antonio, N.L., 2017, The use of passive membrane samplers to assess organic contaminant inputs at five coastal sites in west Maui, Hawaii: U.S. Geological Survey Open-File Report 2017-1097, 19 p., https://doi.org/10.3133/ofr20171097.","productDescription":"vi, 19 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-076397","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":344370,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1097/coverthb.jpg"},{"id":344371,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1097/ofr.20171097.pdf","text":"Report","size":"500 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1097"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.72718048095703,\n 20.80394129420893\n ],\n [\n -156.5994644165039,\n 20.80394129420893\n ],\n [\n -156.5994644165039,\n 20.966248568790633\n ],\n [\n -156.72718048095703,\n 20.966248568790633\n ],\n [\n -156.72718048095703,\n 20.80394129420893\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
This report presents selected photographic images taken by the author during U.S. Geological Survey (USGS) research into paleoclimatology and geochemistry in Devils Hole cavern during 1984 to 1993 in cooperation with the National Park Service. The unaltered suite of photographs was prepared by the USGS dive team as an aid to assist nondiving scientists with a visual perspective of the environment where earth-science samples were collected and subsequently analyzed for chemical and isotopic composition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171058","usgsCitation":"Hoffman, R.J., 2017, Devils Hole, Nevada—A photographic story of a restricted subaqueous environment: U.S. Geological Survey Open-File Report 2017–1058, 34 p., https://doi.org/10.3133/ofr20171058.","productDescription":"iv, 34 p. ","startPage":"1","endPage":"34","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-085250","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":343076,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1058/ofr20171058.pdf","text":"Report","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1058"},{"id":343075,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1058/coverthb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Devil's Hole ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.30109786987303,\n 36.41838163154906\n ],\n [\n -116.28710746765137,\n 36.41838163154906\n ],\n [\n -116.28710746765137,\n 36.43177971506432\n ],\n [\n -116.30109786987303,\n 36.43177971506432\n ],\n [\n -116.30109786987303,\n 36.41838163154906\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, National Research Program, Eastern Branch
U.S. Geological Survey
12201 Sunrise Valley Drive
432 National Center
Reston, VA 20192
In October 2012, the U.S. Geological Survey (USGS) began measuring the concentration of the pesticide fipronil and three of its degradates (desulfinylfipronil, fipronil sulfide, and fipronil sulfone) by a new laboratory method using direct aqueous-injection liquid chromatography tandem mass spectrometry (DAI LC–MS/MS). This method replaced the previous method—in use since 2002—that used gas chromatography/mass spectrometry (GC/MS). The performance of the two methods is not comparable for fipronil and the three degradates. Concentrations of these four chemical compounds determined by the DAI LC–MS/MS method are substantially lower than the GC/MS method. A method was developed to correct for the difference in concentrations obtained by the two laboratory methods based on a methods comparison field study done in 2012. Environmental and field matrix spike samples to be analyzed by both methods from 48 stream sites from across the United States were sampled approximately three times each for this study. These data were used to develop a relation between the two laboratory methods for each compound using regression analysis. The relations were used to calibrate data obtained by the older method to the new method in order to remove any biases attributable to differences in the methods. The coefficients of the equations obtained from the regressions were used to calibrate over 16,600 observations of fipronil, as well as the three degradates determined by the GC/MS method retrieved from the USGS National Water Information System. The calibrated values were then compared to over 7,800 observations of fipronil and to the three degradates determined by the DAI LC–MS/MS method also retrieved from the National Water Information System. The original and calibrated values from the GC/MS method, along with measures of uncertainty in the calibrated values and the original values from the DAI LC–MS/MS method, are provided in an accompanying data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171056","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Crawford, C.G., and Martin, J.D., 2017, A method for addressing differences in concentrations of fipronil and three degradates obtained by two different laboratory methods: U.S. Geological Survey Open-File Report 2017–1056, 26 p., https://doi.org/10.3133/ofr20171056.","productDescription":"Report: vi, 26 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-085104","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":343953,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QC01QR","text":"USGS data release","description":"USGS data release","linkHelpText":"A Method for Addressing Differences in Concentrations of Fipronil and Three Degradates Obtained by Two Different Laboratory Methods"},{"id":342897,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1056/ofr20171056.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1056"},{"id":342896,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1056/coverthb.jpg"}],"contact":"National Water-Quality Assessment Project
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (LRS; Deltistes luxatus) and shortnose suckers (SNS; Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2015 were incorporated into capture-recapture analyses of population dynamics. Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Separate analyses were done for each species and also for each subpopulation of LRS. Shortnose suckers and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake. Characteristics of the spawning migrations in 2015, such as the effects of temperature on the timing of the migrations, were similar to past years.
Capture-recapture analyses for the LRS subpopulation that spawns at the shoreline areas included encounter histories for 13,617 individuals, and analyses for the subpopulation that spawns in the rivers included 39,321 encounter histories. With a few exceptions, the survival of males and females in both subpopulations was high (greater than or equal to 0.86) between 1999 and 2013. Survival was notably lower for males from the rivers in 2000, 2006, and 2012. Survival probabilities were lower for males from the shoreline areas in 2002. Between 2001 and 2014, the abundance of males in the lakeshore spawning subpopulation decreased by at least 59 percent and the abundance of females decreased by at least 53 percent. By combining information from capture-recapture models and size composition data, we concluded that the abundance of both sexes in the river spawning subpopulation of LRS likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation between 2002 and 2014. Capture-recapture analyses for SNS included encounter histories for 20,981 individuals. Most annual survival estimates between 2005 and 2009 were high (greater than 0.88), but both sexes of SNS experienced lower and more variable survival in 2001–04 and 2010–13. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 77 percent and the abundance of females decreased by 74 percent between 2001 and 2014. Decreases in abundance for both sexes likely are greater than these estimates indicate. Despite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. The status of the endangered sucker populations in Upper Klamath Lake remains worrisome, especially for SNS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171059","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B.S., and Harris, A.C., 2017, Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2015: U.S. Geological Survey Open-File Report 2017–1059, 38 p., https://doi.org/10.3133/ofr20171059.","productDescription":"iv, 38 p.","onlineOnly":"Y","ipdsId":"IP-081967","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":344162,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1059/ofr20171059.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1059"},{"id":344161,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1059/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.17,\n 42.2\n ],\n [\n -121.75,\n 42.2\n ],\n [\n -121.75,\n 42.62\n ],\n [\n -122.17,\n 42.62\n ],\n [\n -122.17,\n 42.2\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Long-term rates of shoreline change for the Gulf of Mexico and Southeast Atlantic regions of the United States have been updated as part of the U.S. Geological Survey’s National Assessment of Shoreline Change project. Additional shoreline position data were used to compute rates where the previous rate-of-change assessment only included four shoreline positions at a given location. The long-term shoreline change rates also incorporate the proxy-datum bias correction to account for the unidirectional onshore bias of the proxy-based high water line shorelines relative to the datum-based mean high water shorelines. The calculation of uncertainty associated with the long-term average rates has also been updated to match refined methods used in other study regions of the National Assessment project. The average rates reported here have a reduced amount of uncertainty relative to those presented in the previous assessments for these two regions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171015","usgsCitation":"Himmelstoss, E.A., Kratzmann, M.G., and Thieler, E.R., 2017, National assessment of shoreline change—Summary statistics for updated vector shorelines and associated shoreline change data for the Gulf of Mexico and Southeast Atlantic coasts: U.S. Geological Survey Open-File Report 2017–1015, 8 p., https://doi.org/10.3133/ofr20171015.","productDescription":"Report: vi, 8 p.; 2 Data Releases","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-080390","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":343570,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1015/coverthb.jpg"},{"id":343571,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1015/ofr20171015.pdf","text":"Report","size":"567 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1015"},{"id":343572,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74X55X7","text":"USGS data release","description":"USGS data release","linkHelpText":"Updated vector shorelines and associated shoreline change data for the Southeast Atlantic coast"},{"id":343592,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5XNK","text":"USGS data release","description":"USGS data release","linkHelpText":"Updated vector shorelines and associated shoreline change data for the Gulf of Mexico coast"}],"country":"United States","state":"Alabama, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Texas","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-87.984916,35.005881],[-84.394903,34.98803],[-83.978286,35.44782],[-82.995803,35.773128],[-82.637165,36.065805],[-82.531292,35.972188],[-82.349957,36.117109],[-82.054142,36.126821],[-81.600934,36.587019],[-75.867044,36.550754],[-75.533012,35.787377],[-75.960069,36.495025],[-75.791637,36.082267],[-76.132005,36.287773],[-76.191715,36.107197],[-76.447812,36.192514],[-76.298733,36.1012],[-76.575936,36.006167],[-76.721445,36.147838],[-76.675462,36.266882],[-76.722996,36.066585],[-76.608052,35.936668],[-76.093697,35.993001],[-76.046813,35.717935],[-75.86042,35.978262],[-75.713502,35.693993],[-76.165392,35.328659],[-76.499251,35.381492],[-76.586349,35.508957],[-76.476706,35.511707],[-76.634468,35.510332],[-76.580187,35.387113],[-77.023912,35.514802],[-76.472273,35.294936],[-76.801426,34.964369],[-76.958465,35.047647],[-76.762931,34.920374],[-76.463468,35.076411],[-76.332044,34.970917],[-76.524712,34.681964],[-76.673619,34.71491],[-76.523303,34.652271],[-76.093349,35.048705],[-76.524199,34.615416],[-76.990262,34.669623],[-77.556943,34.417218],[-77.956881,33.87779],[-78.383964,33.901946],[-78.772737,33.768511],[-79.359961,33.006672],[-79.55756,33.021269],[-79.968468,32.639732],[-80.413487,32.470672],[-80.466342,32.31917],[-80.905378,32.051943],[-80.841913,32.002643],[-81.065255,31.877095],[-81.254218,31.55594],[-81.17831,31.52241],[-81.276862,31.254734],[-81.490586,30.984952],[-81.408484,30.977718],[-81.308978,29.96944],[-80.995423,29.206052],[-80.567361,28.562353],[-80.566432,28.09563],[-80.031362,26.796339],[-80.152896,25.702855],[-80.229107,25.732509],[-80.409103,25.25346],[-80.652253,25.146705],[-81.079859,25.118797],[-81.362272,25.824401],[-81.727086,25.907207],[-81.868983,26.378648],[-82.094748,26.48393],[-82.076349,26.958263],[-82.147068,26.789803],[-82.301736,26.841588],[-82.714521,27.500415],[-82.393383,27.837519],[-82.716522,27.958398],[-82.566819,27.858002],[-82.721622,27.663908],[-82.851126,27.8863],[-82.674787,28.441956],[-82.702618,28.932955],[-82.827073,29.158425],[-83.018212,29.151417],[-83.679219,29.918513],[-84.000716,30.096209],[-85.343619,29.672004],[-85.405052,29.938487],[-86.2987,30.363049],[-88.014572,30.222366],[-87.766626,30.262353],[-88.008396,30.684956],[-88.191542,30.317002],[-89.315067,30.375408],[-89.461275,30.174745],[-89.854533,30.007821],[-89.711158,29.879287],[-89.418465,30.049747],[-89.231178,29.925484],[-89.42421,29.697638],[-89.598068,29.74757],[-89.487915,29.630405],[-89.681092,29.534487],[-89.02185,29.218162],[-89.09126,29.066931],[-89.383814,28.947434],[-89.447472,29.178576],[-89.782149,29.311132],[-89.832898,29.463536],[-90.01251,29.462775],[-90.097678,29.26199],[-90.019772,29.231903],[-90.174273,29.105301],[-90.343293,29.057062],[-90.311523,29.256374],[-90.495299,29.287277],[-90.811473,29.03658],[-91.278792,29.247776],[-91.258226,29.446954],[-91.854677,29.807436],[-92.134347,29.669516],[-91.719102,29.565568],[-91.848665,29.484144],[-93.267456,29.778113],[-94.056506,29.671163],[-94.731047,29.369141],[-94.532348,29.5178],[-94.767246,29.525523],[-94.692434,29.70361],[-94.816085,29.75671],[-95.015636,29.639457],[-94.894234,29.338],[-95.16525,29.113566],[-94.73132,29.338066],[-94.803695,29.279237],[-96.341617,28.417334],[-95.983106,28.641942],[-96.221784,28.580364],[-96.287942,28.683164],[-96.473694,28.57324],[-96.664534,28.696904],[-96.481836,28.407844],[-96.790235,28.383926],[-96.898123,28.152881],[-97.21535,28.076575],[-97.040618,28.028708],[-97.183455,27.833231],[-97.354614,27.849572],[-97.296598,27.613947],[-97.399398,27.344735],[-97.640111,27.270943],[-97.485149,27.250841],[-97.552325,26.867633],[-97.145567,25.971132],[-97.445113,25.850026],[-97.711145,26.033043],[-98.20496,26.066419],[-99.110855,26.426278],[-99.452316,27.062669],[-99.556812,27.614336],[-99.841708,27.766464],[-100.280518,28.267969],[-100.785521,29.228137],[-101.441059,29.753451],[-102.341033,29.869305],[-102.698347,29.695591],[-103.107811,29.013812],[-103.427754,29.042334],[-104.46652,29.609296],[-104.924796,30.604832],[-106.158218,31.438885],[-106.623933,31.925335],[-103.088698,32.000453],[-103.041924,36.500439],[-100.003762,36.499699],[-100.000381,34.560509],[-99.630905,34.376007],[-99.381011,34.456936],[-99.192104,34.216694],[-98.504182,34.072371],[-98.138979,34.141805],[-97.905467,33.863531],[-97.688023,33.986607],[-97.372941,33.819454],[-97.226522,33.914642],[-97.126102,33.716941],[-96.922114,33.959579],[-96.36959,33.716809],[-95.230491,33.960764],[-94.413155,33.569368],[-94.100107,33.572568],[-94.043036,33.079485],[-93.814553,33.019372],[-91.166073,33.004106],[-91.057621,33.445341],[-91.210275,33.433796],[-91.086758,33.95827],[-90.874541,34.072041],[-90.93268,34.214824],[-90.580677,34.410554],[-90.483969,34.877176],[-90.34038,34.860357],[-90.293083,34.974574],[-87.984916,35.005881]]],[[[-81.582923,24.658732],[-81.451267,24.747464],[-81.298028,24.656774],[-81.765993,24.552103],[-81.582923,24.658732]]],[[[-84.777208,29.707398],[-84.696726,29.76993],[-85.036219,29.588919],[-84.777208,29.707398]]],[[[-82.255777,26.703437],[-82.038403,26.456907],[-82.186441,26.489221],[-82.255777,26.703437]]],[[[-80.250581,25.34193],[-80.611693,24.93842],[-80.192336,25.473331],[-80.250581,25.34193]]],[[[-88.865067,29.752714],[-88.940346,29.657234],[-88.86972,30.043798],[-88.865067,29.752714]]],[[[-75.753765,35.199612],[-75.523952,35.318198],[-75.533512,35.773577],[-75.52592,35.233839],[-75.982812,35.081513],[-75.753765,35.199612]]],[[[-97.240849,26.411504],[-97.383531,26.875521],[-97.366771,27.333276],[-96.946988,28.026522],[-96.403206,28.371475],[-96.929053,27.99044],[-97.276091,27.472145],[-97.370731,26.909706],[-97.161471,26.088705],[-97.240849,26.411504]]]]},\"properties\":{\"name\":\"Alabama\",\"nation\":\"USA \"}}]}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
Globally, rivers and streams are highly altered by impoundments, diversions, and stream channelization associated with agricultural and water delivery needs. Climate change imposes additional challenges by further reducing discharge, introducing variability in seasonal precipitation patterns, and increasing temperatures. Collectively, these changes in a river or stream’s annual hydrology affects surface and groundwater dynamics, fluvial processes, and the linked aquatic and riparian responses, particularly in arid regions. Recognizing the inherent ecosystem services that riparian and aquatic habitats provide, society increasingly supports restoring the functionality of riparian and aquatic ecosystems.
Given the wide range in types and scales of riparian impacts, approaches to riparian restoration can range from tactical, short-term, and site-specific efforts to strategic projects and long-term collaborations best pursued at the watershed scale. In the spirit of sharing information, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center convened a workshop June 23-25, 2015, in Flagstaff, Ariz. for practitioners in restoration science to share general principles, successful restoration practices, and discuss the challenges that face those practicing riparian restoration in the southwestern United States. Presenters from the Colorado River and the Rio Grande basins, offered their perspectives and experiences in restoration at the local, reach and watershed scale. Outcomes of the workshop include this Proceedings volume, which is composed of extended abstracts of most of the presentations given at the workshop, and recommendations or information needs identified by participants. The organization of the Proceedings follows a general progression from local scale restoration to river and watershed scale approaches, and finishes with restoration assessments and monitoring.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171091","usgsCitation":"Ralston, B.E., and Sarr, D.A., 2017, Case studies of riparian and watershed restoration in the southwestern United States—Principles, challenges, and successes: U.S. Geological Survey Open-File Report 2017-1091, 116 p., https://doi.org/10.3133/ofr20171091.","productDescription":"ix, 116 p.","onlineOnly":"Y","ipdsId":"IP-087333","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":343991,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1091/ofr20171091.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1091"},{"id":343990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1091/coverthb.jpg"}],"country":"United States","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Rock core and sediment from U.S. Geological Survey test corehole G–2984 completed in 2011 in Broward County, Florida, provide an opportunity to improve the understanding of the lithostratigraphic, sequence stratigraphic, and hydrogeologic framework of the intermediate confining unit and Floridan aquifer system in southeastern Florida. A multidisciplinary approach including characterization of sequence stratigraphy, lithofacies, ichnology, foraminiferal paleontology, depositional environments, porosity, and permeability was used to describe the geologic samples from this test corehole. This information has produced a detailed characterization of the lithofacies and sequence stratigraphy of the upper part of the middle Eocene Avon Park Formation and Oligocene to middle Miocene Arcadia Formation. This enhancement of the knowledge of the sequence stratigraphic framework is especially important, because subaerial karst unconformities at the upper boundary of depositional cycles at various hierarchical scales are commonly associated with secondary porosity and enhanced permeability in the Floridan aquifer system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171074","collaboration":"Prepared in cooperation with Broward County, Florida","usgsCitation":"Cunningham, K.J., and Robinson, Edward, 2017, Lithofacies and sequence stratigraphic description of the upper part of the Avon Park Formation and the Arcadia Formation in U.S. Geological Survey G–2984 test corehole, Broward County, Florida: U.S. Geological Survey Open File-Report 2017–1074, 139 p., https://doi.org/10.3133/ofr20171074.","productDescription":"v, 139 p.","onlineOnly":"Y","ipdsId":"IP-083814","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":343757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1074/coverthb2.jpg"},{"id":343758,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1074/ofr20171074.pdf","text":"Report","size":"23.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1074"}],"country":"United States","state":"Florida","county":"Broward County","otherGeospatial":"Test corehole G-2984","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.15,\n 26.35\n ],\n [\n -80.1,\n 26.35\n ],\n [\n -80.1,\n 26.3\n ],\n [\n -80.15,\n 26.3\n ],\n [\n -80.15,\n 26.35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The Liberty Island Conservation Bank (LICB) is a tidal freshwater marsh restored for the purpose of mitigating adverse effects on sensitive fish populations elsewhere in the region. The LICB was completed in 2012 and is in the northern Cache Slough region of the Sacramento–San Joaquin Delta. The wetland vegetation at the LICB is stunted and yellow-green in color (chlorotic) compared to nearby wetlands. A study was done to investigate three potential causes of the stunted and chlorotic vegetation: (1) improper grading of the marsh plain, (2) pesticide contamination from agricultural and urban inputs upstream from the site, (3) nitrogen-deficient soil, or some combination of these. Water samples were collected from channels at five sites, and soil samples were collected from four wetlands, including the LICB, during the summer of 2015. Real-time kinematic global positioning system (RTK-GPS) elevation surveys were completed at the LICB and north Little Holland Tract, a closely situated natural marsh that has similar hydrodynamics as the LICB, but contains healthy marsh vegetation.
The results showed no significant differences in carbon or nitrogen content in the surface soils or in pesticides in water among the sites. The elevation survey indicated that the mean elevation of the LICB was about 26 centimeters higher than that of the north Little Holland Tract marsh. Because marsh plain elevation largely determines the hydroperiod of a marsh, these results indicated that the LICB has a hydroperiod that differs from that of neighboring north Little Holland Tract marsh. This difference in hydroperiod contributed to the lower stature and decreased vigor of wetland vegetation at the LICB. Although the LICB cannot be regraded without great expense, it could be possible to reduce the sharp angle of the marsh edge to facilitate deeper and more frequent tidal flooding along the marsh periphery. Establishing optimal elevations for restored wetlands is necessary for obtaining the full suite of ecosystem services provided by tidal wetlands. A better system of tidal benchmarks throughout the delta is needed to help restoration practitioners correctly grade the elevation of newly restored wetlands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171077","usgsCitation":"Orlando, J.L., and Drexler, J.Z., 2017, Factors affecting marsh vegetation at the Liberty Island Conservation Bank in the Cache Slough region of the Sacramento–San Joaquin Delta, California, 2017: U.S. Geological Survey Open-File Report 2017–1077, 25 p., https://doi.org/10.3133/ofr20171077.","productDescription":"v, 25 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-075770","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343340,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1077/ofr20171077.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1077"},{"id":343339,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1077/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Liberty Island Conservation Bank, Sacramento–San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.80370330810547,\n 38.15939647721454\n ],\n [\n -121.5427780151367,\n 38.15939647721454\n ],\n [\n -121.5427780151367,\n 38.4167\n ],\n [\n -121.80370330810547,\n 38.4167\n ],\n [\n -121.80370330810547,\n 38.15939647721454\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The U.S. Geological Survey (USGS) has a long history of advancing the traditional Earth science disciplines and identifying opportunities to integrate USGS science across disciplines to address complex societal problems. The USGS science strategy for 2007–2017 laid out key challenges in disciplinary and interdisciplinary arenas, culminating in a call for increased focus on a number of crosscutting science directions. Ten years on, to further the goal of integrated science and at the request of the Executive Leadership Team (ELT), a workshop with three dozen invited scientists spanning different disciplines and career stages in the Bureau convened on February 7–10, 2017, at the USGS John Wesley Powell Center for Analysis and Synthesis in Fort Collins, Colorado.
The workshop focused on identifying “grand challenges” for integrated USGS science. Individual participants identified nearly 70 potential grand challenges before the workshop and through workshop discussions. After discussion, four overarching grand challenges emerged:
Participants also identified a “comprehensive science challenge” that highlights the development of integrative science, data, models, and tools—all interacting in a modular framework—that can be used to address these and other future grand challenges:
EarthMAP is our long-term vision for an integrated scientific framework that spans traditional scientific boundaries and disciplines, and integrates the full portfolio of USGS science: research, monitoring, assessment, analysis, and information delivery.
The Department of Interior, and the Nation in general, have a vast array of information needs. The USGS meets these needs by having a broadly trained and agile scientific workforce. Encouraging and supporting cross-discipline engagement would position the USGS to tackle complex and multifaceted scientific and societal challenges in the 21st Century.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171076","usgsCitation":"Jenni, K.E., Goldhaber, M.B., Betancourt, J.L., Baron, J.S., Bristol, R.S., Cantrill, Mary, Exter, P.E., Focazio, M.J., Haines, J.W., Hay, L.E., Hsu, Leslie, Labson, V.F., Lafferty, K.D., Ludwig, K.A., Milly, P.C., Morelli, T.L., Morman, S.A., Nassar, N.T., Newman, T.R., Ostroff, A.C., Read, J.S., Reed, S.C., Shapiro, C.D., Smith, R.A., Sanford, W.E., Sohl, T.L., Stets, E.G., Terando, A.J., Tillitt, D.E., Tischler, M.A., Toccalino, P.L., Wald, D.J., Waldrop, M.P., Wein, Anne, Weltzin, J.F., and Zimmerman, C.E., 2017, Grand challenges for integrated USGS science—A workshop report: U.S. Geological Survey Open-File Report 2017–1076, 94 p., https://doi.org/10.3133/ofr20171076.","productDescription":"94 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-085873","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":343080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1076/ofr20171076.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1076"},{"id":343079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1076/coverthbtest.jpg"}],"contact":"John Wesley Powell Center
U.S. Geological Survey
2150 Centre Avenue
Building C
Fort Collins, CO 80526-8118
https://powellcenter.usgs.gov/
Seventy-two gravity cores were collected by the U.S. Geological Survey in 1990, 1991, and 2000 from San Pablo Bay and Carquinez Strait, California. The gravity cores collected within San Pablo Bay contain bioturbated laminated silts and sandy clays, whole and broken bivalve shells (mostly mussels), fossil tube structures, and fine-grained plant or wood fragments. Gravity cores from the channel wall of Carquinez Strait east of San Pablo Bay consist of sand and clay layers, whole and broken bivalve shells (less than in San Pablo Bay), trace fossil tubes, and minute fragments of plant material.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171078","usgsCitation":"Woodrow, D.L., Chin, J.L., Wong, F.L., Fregoso, Theresa, Jaffe, B.E., 2017, Description of gravity cores from San Pablo Bay and Carquinez Strait, San Francisco Bay, California: U.S. Geological Survey Open-File Report 2017–1078, 14 p., https://doi.org/10.3133/ofr20171078.","productDescription":"Report: iv, 15 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-084096","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438291,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XG9PB0","text":"USGS data release","linkHelpText":"Gravity cores from San Pablo Bay and Carquinez Strait, San Francisco Bay, California"},{"id":343001,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5849b74fe4b071492e42db02","text":"USGS data release","description":"USGS data release","linkHelpText":"Gravity cores from San Pablo Bay and Carquinez Strait, San Francisco Bay, California"},{"id":342990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1078/coverthb.jpg"},{"id":342991,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1078/ofr20171078.pdf","text":"Report","size":"915 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1078"}],"country":"United States","state":"California","city":"San Francisco ","otherGeospatial":"Carquinez Strait, San Francisco Bay, San Pablo Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.45704650878905,\n 37.98019812825676\n ],\n [\n -122.46356964111327,\n 37.982092409208875\n ],\n [\n -122.46803283691405,\n 37.98425724185128\n ],\n [\n -122.47352600097658,\n 37.98236301678186\n ],\n [\n -122.47421264648439,\n 37.979115660044805\n ],\n [\n -122.47798919677733,\n 37.97397371800425\n ],\n [\n -122.48416900634766,\n 37.972079227501396\n ],\n [\n -122.48519897460936,\n 37.970725990064786\n ],\n [\n -122.49446868896483,\n 37.96883141574578\n ],\n [\n -122.48863220214842,\n 37.95719224376526\n ],\n [\n -122.4869155883789,\n 37.94717566570979\n ],\n [\n -122.47695922851562,\n 37.94230224202578\n ],\n [\n -122.44949340820312,\n 37.9363453963773\n ],\n [\n -122.41069793701172,\n 37.9330960043492\n ],\n [\n -122.41378784179688,\n 37.937428495133396\n ],\n [\n -122.41172790527345,\n 37.94121921509192\n ],\n [\n -122.41584777832031,\n 37.94528048379506\n ],\n [\n -122.42374420166016,\n 37.94582196933006\n ],\n [\n -122.4196243286133,\n 37.95340234782487\n ],\n [\n -122.42546081542967,\n 37.95827503526034\n ],\n [\n -122.43061065673827,\n 37.96774877989782\n ],\n [\n -122.4209976196289,\n 37.965854128749434\n ],\n [\n -122.4100112915039,\n 37.96152331396614\n ],\n [\n -122.40966796874999,\n 37.95692154339725\n ],\n [\n -122.40554809570311,\n 37.95502661288625\n ],\n [\n -122.39936828613281,\n 37.95394377350263\n ],\n [\n -122.39765167236327,\n 37.95394377350263\n ],\n [\n -122.39627838134766,\n 37.95502661288625\n ],\n [\n -122.39902496337889,\n 37.95719224376526\n ],\n [\n -122.39627838134766,\n 37.9585457306399\n ],\n [\n -122.3938751220703,\n 37.9593578107923\n ],\n [\n -122.39542007446289,\n 37.96389175994797\n ],\n [\n -122.39765167236327,\n 37.96829009981737\n ],\n [\n -122.39318847656249,\n 37.96991403562913\n ],\n [\n -122.39112854003905,\n 37.96910207221332\n ],\n [\n -122.38846778869627,\n 37.969440391394585\n ],\n [\n -122.38838195800781,\n 37.97153793552019\n ],\n [\n -122.38520622253417,\n 37.97167325888967\n ],\n [\n -122.38572120666504,\n 37.973838398875515\n ],\n [\n -122.3832321166992,\n 37.97593581733786\n ],\n [\n -122.37876892089842,\n 37.97586815961326\n ],\n [\n -122.37387657165527,\n 37.9743120147347\n ],\n [\n -122.36409187316895,\n 37.983107182462135\n ],\n [\n -122.35937118530273,\n 37.98973668903741\n ],\n [\n -122.36040115356447,\n 37.9942011212103\n ],\n [\n -122.36246109008789,\n 37.99650087417057\n ],\n [\n -122.36580848693848,\n 37.99751544814143\n ],\n [\n -122.36666679382324,\n 38.00292627228207\n ],\n [\n -122.3682117462158,\n 38.00799855732857\n ],\n [\n -122.36640930175781,\n 38.012935244447135\n ],\n [\n -122.36400604248047,\n 38.011582760492196\n ],\n [\n -122.36083030700682,\n 38.008539580355944\n ],\n [\n -122.35542297363281,\n 38.00833669718854\n ],\n [\n -122.35095977783202,\n 38.00833669718854\n ],\n [\n -122.34649658203124,\n 38.00536101289634\n ],\n [\n -122.33860015869139,\n 38.00292627228207\n ],\n [\n -122.33276367187499,\n 38.00103252924477\n ],\n [\n -122.3276138305664,\n 38.00292627228207\n ],\n [\n -122.31834411621095,\n 38.00860720795364\n ],\n [\n -122.31628417968749,\n 38.012664749652494\n ],\n [\n -122.3063278198242,\n 38.0107712581413\n ],\n [\n -122.29980468749999,\n 38.01104175992311\n ],\n [\n -122.29705810546874,\n 38.014017213643996\n ],\n [\n -122.2943115234375,\n 38.01564013749379\n ],\n [\n -122.29122161865233,\n 38.01969728990135\n ],\n [\n -122.29259490966795,\n 38.02213147353745\n ],\n [\n -122.28641510009766,\n 38.021861012681974\n ],\n [\n -122.28160858154297,\n 38.02240193339466\n ],\n [\n -122.27405548095702,\n 38.032137823399275\n ],\n [\n -122.27474212646483,\n 38.037546092117\n ],\n [\n -122.2726821899414,\n 38.040250076719225\n ],\n [\n -122.26341247558594,\n 38.03889809689809\n ],\n [\n -122.26341247558594,\n 38.04755033643351\n ],\n [\n -122.26306915283205,\n 38.052687119903034\n ],\n [\n -122.25929260253906,\n 38.052146422828116\n ],\n [\n -122.25311279296874,\n 38.052416771864834\n ],\n [\n -122.24933624267578,\n 38.05701255271462\n ],\n [\n -122.24109649658203,\n 38.05863452411495\n ],\n [\n -122.23491668701172,\n 38.05782354290831\n ],\n [\n -122.22873687744139,\n 38.05782354290831\n ],\n [\n -122.22187042236328,\n 38.05782354290831\n ],\n [\n -122.21260070800781,\n 38.05701255271462\n ],\n [\n -122.20161437988281,\n 38.05430918716337\n ],\n [\n -122.18856811523436,\n 38.05295746694274\n ],\n [\n -122.18479156494142,\n 38.04944287754316\n ],\n [\n -122.17964172363281,\n 38.04430586642022\n ],\n [\n -122.17517852783203,\n 38.03970928778597\n ],\n [\n -122.17346191406249,\n 38.03348992801713\n ],\n [\n -122.16796875,\n 38.028622234587964\n ],\n [\n -122.15045928955077,\n 38.021590550828236\n ],\n [\n -122.14324951171874,\n 38.02294285011436\n ],\n [\n -122.14050292968749,\n 38.02618826657808\n ],\n [\n -122.135009765625,\n 38.02835179769117\n ],\n [\n -122.12814331054686,\n 38.029703972192\n ],\n [\n -122.12230682373048,\n 38.03105612173487\n ],\n [\n -122.11132049560547,\n 38.03646447032118\n ],\n [\n -122.10582733154295,\n 38.04079086165885\n ],\n [\n -122.0972442626953,\n 38.04160203158016\n ],\n [\n -122.09415435791016,\n 38.04349472645177\n ],\n [\n -122.09003448486327,\n 38.04782070244462\n ],\n [\n -122.07698822021484,\n 38.04944287754316\n ],\n [\n -122.07286834716795,\n 38.04944287754316\n ],\n [\n -122.09896087646484,\n 38.08052761936274\n ],\n [\n -122.10891723632812,\n 38.07350092012434\n ],\n [\n -122.11200714111328,\n 38.0694467480777\n ],\n [\n -122.1247100830078,\n 38.05457952821193\n ],\n [\n -122.12951660156249,\n 38.04457624441283\n ],\n [\n -122.13363647460938,\n 38.043765107439675\n ],\n [\n -122.1463394165039,\n 38.04268357749736\n ],\n [\n -122.1566390991211,\n 38.042953961480585\n ],\n [\n -122.16625213623045,\n 38.04403548742916\n ],\n [\n -122.16384887695312,\n 38.04619849140099\n ],\n [\n -122.1617889404297,\n 38.048091067457236\n ],\n [\n -122.16247558593751,\n 38.049713236564884\n ],\n [\n -122.16522216796875,\n 38.052416771864834\n ],\n [\n -122.17449188232422,\n 38.0575532138423\n ],\n [\n -122.18032836914062,\n 38.06106741381201\n ],\n [\n -122.18410491943358,\n 38.063770529720564\n ],\n [\n -122.1844482421875,\n 38.066743841880246\n ],\n [\n -122.18650817871094,\n 38.068906174827404\n ],\n [\n -122.19303131103516,\n 38.068906174827404\n ],\n [\n -122.19303131103516,\n 38.0656626514393\n ],\n [\n -122.19303131103516,\n 38.06241898424877\n ],\n [\n -122.19303131103516,\n 38.060256459566865\n ],\n [\n -122.1964645385742,\n 38.059715818410524\n ],\n [\n -122.200927734375,\n 38.06160804498248\n ],\n [\n -122.20230102539062,\n 38.06322991452768\n ],\n [\n -122.20436096191405,\n 38.0656626514393\n ],\n [\n -122.20642089843749,\n 38.067554724225275\n ],\n [\n -122.21260070800781,\n 38.065932950547484\n ],\n [\n -122.22221374511717,\n 38.065932950547484\n ],\n [\n -122.2283935546875,\n 38.06620324865703\n ],\n [\n -122.2335433959961,\n 38.0694467480777\n ],\n [\n -122.23628997802734,\n 38.070798163726785\n ],\n [\n -122.2390365600586,\n 38.0729603768343\n ],\n [\n -122.24796295166017,\n 38.07674409597339\n ],\n [\n -122.24933624267578,\n 38.07458199472\n ],\n [\n -122.25173950195311,\n 38.07241982954952\n ],\n [\n -122.25448608398436,\n 38.0729603768343\n ],\n [\n -122.25723266601562,\n 38.0705278825943\n ],\n [\n -122.25894927978514,\n 38.06863588670429\n ],\n [\n -122.26821899414061,\n 38.06701413699389\n ],\n [\n -122.27542877197264,\n 38.06539235133249\n ],\n [\n -122.27714538574219,\n 38.0729603768343\n ],\n [\n -122.28195190429686,\n 38.082419307649296\n ],\n [\n -122.29019165039062,\n 38.09214721719905\n ],\n [\n -122.3052978515625,\n 38.10592620640843\n ],\n [\n -122.33585357666014,\n 38.12132317831781\n ],\n [\n -122.36366271972655,\n 38.13428653167246\n ],\n [\n -122.38906860351562,\n 38.14265747385727\n ],\n [\n -122.39559173583984,\n 38.14319750166766\n ],\n [\n -122.40280151367188,\n 38.15075747130226\n ],\n [\n -122.40589141845703,\n 38.153727245014004\n ],\n [\n -122.40589141845703,\n 38.14616758317493\n ],\n [\n -122.40554809570311,\n 38.14076734504349\n ],\n [\n -122.41207122802734,\n 38.13482662143656\n ],\n [\n -122.41928100585938,\n 38.13077585078312\n ],\n [\n -122.43713378906249,\n 38.120512892298976\n ],\n [\n -122.43988037109374,\n 38.117001548978614\n ],\n [\n -122.44468688964844,\n 38.11484063839791\n ],\n [\n -122.44743347167969,\n 38.11619121500379\n ],\n [\n -122.45121002197266,\n 38.1164613273278\n ],\n [\n -122.45361328124999,\n 38.119162395618986\n ],\n [\n -122.45704650878905,\n 38.11943249695316\n ],\n [\n -122.48519897460936,\n 38.11349003681576\n ],\n [\n -122.49137878417969,\n 38.110518625420134\n ],\n [\n -122.48897552490234,\n 38.10457543999035\n ],\n [\n -122.48794555664061,\n 38.09809141355002\n ],\n [\n -122.4869155883789,\n 38.095389566050656\n ],\n [\n -122.48588562011717,\n 38.0916068117397\n ],\n [\n -122.48313903808594,\n 38.08160859009049\n ],\n [\n -122.48416900634766,\n 38.0705278825943\n ],\n [\n -122.4869155883789,\n 38.06295960543331\n ],\n [\n -122.49172210693358,\n 38.05430918716337\n ],\n [\n -122.4930953979492,\n 38.048631794487044\n ],\n [\n -122.49378204345702,\n 38.04322434446539\n ],\n [\n -122.49893188476561,\n 38.02727004012099\n ],\n [\n -122.4965286254883,\n 38.02050869343089\n ],\n [\n -122.49927520751953,\n 38.016451585943095\n ],\n [\n -122.49481201171875,\n 38.01455819225335\n ],\n [\n -122.4872589111328,\n 38.012664749652494\n ],\n [\n -122.48348236083984,\n 38.01050075536135\n ],\n [\n -122.47936248779295,\n 38.008066185425335\n ],\n [\n -122.47592926025389,\n 38.00698412839117\n ],\n [\n -122.47249603271484,\n 38.00563153464076\n ],\n [\n -122.4707794189453,\n 38.004819966413194\n ],\n [\n -122.46871948242186,\n 38.00454944167447\n ],\n [\n -122.46391296386719,\n 38.00292627228207\n ],\n [\n -122.45532989501953,\n 37.99751544814143\n ],\n [\n -122.45258331298828,\n 37.99480988636414\n ],\n [\n -122.44674682617188,\n 37.98858671553364\n ],\n [\n -122.44606018066406,\n 37.98425724185128\n ],\n [\n -122.45704650878905,\n 37.98019812825676\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060