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USGS2000

Geologic assessment of coal in the Colorado Plateau: Arizona, Colorado, New Mexico, and Utah

This CD-ROM set contains a geologic assessment of coal deposits of the Colorado Plateau region and new resource estimates for selected assessment units within the Colorado Plateau. Original resource estimates (in-place resources before production) for the 12 priority assessment units of the Colorado Plateau exceed one half trillion short tons of coal in beds greater than 1 ft thick and under less than 6,000 ft of overburden. The coal is high quality and low sulfur, and a portion of these resources will provide future energy production for the Nation. Disc 1, in Portable Document Format, contains results of the assessment in summary and (or) technical reports for 12 priority coal assessment units in the Colorado Plateau and also contains an ArcView Data Publisher project, which is an interactive geographic information system of digital data collected during the assessment. Disc 2 contains stratigraphic data bases for seven of the priority coal assessment areas within the Colorado Plateau region and an ArcView project identical to the ArcView Data Publisher project on disc 1 except that it retains some of the functionality that is disabled in the ArcView Data Publisher program.

Arizona, Colorado, New Mexico, Utah↗

USGS2015

Flood-inundation maps and wetland restoration suitability index for the Blue River and selected tributaries, Kansas City, Missouri, and vicinity, 2012

Digital flood-inundation maps for a 39.7-mile reach of the Blue River and selected tributaries (Brush Creek, Indian Creek, and Dyke Branch) at Kansas City, Missouri, and vicinity, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Kansas City, Missouri. The flood-inundation maps, accessed through the USGS Flood-Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the spatial extent and depth of flooding corresponding to selected water levels (stages) at 15 reference streamgages and associated stream reaches in the Blue River Basin. Near-real-time stage data from the streamgages may be obtained from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at selected sites. Flood profiles were computed for each of 15 reaches by means of one-dimensional or two-dimensional hydraulic models. The models were calibrated by using the current stage-streamflow relations at 10 USGS streamgages and documented high-water marks from the flood of June 14, 2010. Hydraulic models were then used to compute water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from the National Weather Service Action stage, or near bankfull streamflow, through the stage corresponding to, or exceeding, the estimated 0.2-percent annual exceedance probability flood (500-year recurrence interval flood). The simulated water-surface profiles were then combined with a geographic information system (GIS) terrain model derived from light detection and ranging (lidar) data having a vertical accuracy of less than 0.6 foot and maximum nominal horizontal post spacing of 2.46–3.28 feet to delineate the area flooded at each 1-foot increment of stage. The availability of these flood-inundation maps, along with Internet information regarding current stage from the USGS streamgages and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts. Additional information in this report includes maps of simulated stream velocity for an 8.2-mile, two-dimensional modeled reach of the Blue River and a Wetland Restoration Suitability Index (WRSI) generated for the study area that was based on hydrologic, topographic, and land-use digital feature layers. The calculated WRSI for the selected flood-plain area ranged from 1 (least suitable for possible wetland mitigation efforts) to 10 (most suitable for possible wetland mitigation efforts). A WRSI of 5 to 10 is most closely associated with existing riparian wetlands in the study area. The WRSI allows for the identification of lands along the Blue River and selected tributaries that are most suitable for restoration or creation of wetlands. Alternatively, the index can be used to identify and avoid disturbances to areas with the highest potential to support healthy sustainable riparian wetlands.

Missouri↗

USGS1986

The Breeding Bird Survey: Its first fifteen years, 1965-1979

The Breeding Bird Survey (BBS) is an ongoing cooperative program sponsored jointly by the U.S. Fish and Wildife Service and the Canadian Wildlife Service. Its main purpose is to estimate population trends of the many species of birds that nest in North America north of Mexico and that migrate across international boundaries. This survey provides information, both locally by ecological or political regions and on a continental scale, on (1) short-term population changes that can be correlated with specific weather incidents, (2) recovery periods following catastrophic declines, (3) normal year-to-year variations, (4) long-term population trends, and (5) invasions of exotics. The BBS also permits detailed computer mapping of relative abundance of each species, either year by year to show changes in distribution and relative abundance, or the average over a period of years. It provides base-line data with which more intensive local studies can be compared. For biogeographic studies it provides uniform sampling of bird populations by major physiographic regions across the continent. In conjunction with the Audubon Christmas Bird Count, it permits comparison of summer and winter distribution of species that winter in the United States. Most species of North American birds migrate across international boundaries, especially those shared with Canada, Mexico, and the Soviet Union. As part of our responsibility under treaties with these nations, the U.S. Fish and Wildlife Service has developed the BBS to monitor avian population changes so that any adverse trends can be detected early. This provides the opportunity to determine the reasons for any increase or decrease, to define geographic areas in which changes are greatest, to study correlations between avian population changes and land-use changes, and to make recommendations for controlling undesirable bird population trends. For example, the BBS can be used to detect and estimate the extent of losses resulting from widespread use of pesticides, and to reveal whether major population changes of a given species (e.g., Dickcissel) in certain States are related to a continental decline or are merely a result of population shifts within the breeding range. Effects of urban and suburban expansion are often reflected in the loss of forest interior birds. Population trends for 230 species as well as several avian genera and families are discussed and graphed in this report. For most of these species, regional and well as continental trends are shown. The three major regions discussed are the Eastern, Central, and Western, bounded by the Mississippi River and the eastern base of the Rocky Mountains. Additional graphs for certain States or physiographic regions are included for selected species of special interest. The following paragraphs summarize general trends in the major bird families. The native herons in general are maintaining their populations, whereas the exotic Cattle Egret continues its geographic spread and its steady increase. Waterfowl as a group are stable or increasing. Although most widespread species of hawks are on the increase, the rarer species show evidence of decline. Among the gallinaceous birds, the greatest change was a sharp drop in Northern Bobwhite as a result of the exceptionally cold winters of 1976-77 and 1977-78 in the Ohio Valley and the Middle Atlantic States. Killdeer populations, except for a minor decline during these two winters, showed strong increases except in the West. American Woodcock were poorly sampled by the BBS because they were relatively inactive during daylight. Common Snipe and the other common shorebirds that nest in the United States and southern Canada exhibited stable or increasing populations, especially in the Eastern and Central regions. Herring Gull counts varied dramatically and irregularly from year to year. Laughing Gulls increased along the Atlantic coast and Franklin's Gulls declined in the interior of the continen

Resource Publication↗

USGS1991

Importance of hydrologic data for interpreting wetland maps and assessing wetland loss and mitigation

The US Geological Survey collects and disseminates, in written and digital formats, groundwater and surface-water information related to the tidal and nontidal wetlands of the United States. This information includes quantity, quality, and availability of groundwater and surface water; groundwater and surface-water interactions (recharge-discharge); groundwater flow; and the basic surface-water characteristics of streams, rivers, lakes, and wetlands. Water resources information in digital format can be used in geographic information systems (GISs) for many purposes related to wetlands. US Geological Survey wetland-related activities include collection of information important for assessing and mitigating coastal wetland loss and modification, hydrologic data collection and interpretation, GIS activities, identification of national trends in water quality and quantity, and process-oriented wetland research. -Author

Biological Report - US Fish & Wildlife Service↗

USGS2014

Geographic information system (GIS)-based maps of Appalachian basin oil and gas fields

One of the more recent maps of Appalachian basin oil and gas fields (and the adjoining Black Warrior basin) is the U.S. Geological Survey (USGS) compilation by Mast and others (1998) (see Trippi and others, this volume, chap. I.1). This map is part of a larger oil and gas field map for the conterminous United States that was derived by Mast and others (1998) from the Well History Control System (WHCS) database of Petroleum Information, Inc. (now IHS Energy Group). Rather than constructing the map from the approximately 500,000 proprietary wells in the Appalachian and Black Warrior part of the WHCS database, Mast and others (1998) subdivided the region into a grid of 1-mi 2 (square mile) cells and allocated an appropriate type of hydrocarbon production (oil production, gas production, oil and gas production, or explored but no production) to each cell. Each 1-mi 2 cell contains from 0 to 5 or more exploratory and (or) development wells. For example, if the wells in the 1-mi 2 cell consisted of three oil wells, one gas well, and one dry well, then the cell would be characterized on the map as an area of oil and gas production. The map by Mast and others (1998) accurately shows the distribution and types of hydrocarbon accumulation in the Appalachian and Black Warrior basins, but it does not show the names of individual fields. To determine the locality and name of individual oil and gas fields, one must refer to State oil and gas maps (for example, Harper and others, 1982), which are generally published at scales of 1:250,000 or 1:500,000 (see References Cited), and (or) published journal articles. Other recent USGS Appalachian basin oil and gas field maps show the distribution of oil and gas production with a cell size as small as 0.25 mi 2 , such as the maps converted by Trippi and others (this volume, chap. I.1) from proprietary well-location maps used in the USGS 2002 assessment of oil and gas resources of the Appalachian basin (Milici and others, 2003). Another set of Appalachian basin oil and gas cell maps (based on a cell size of 0.25 mi 2 ) was created for the USGS 1995 National Assessment of United States Oil and Gas Resources (Gautier and others, 1995; Beeman and others, 1996). Between 1991 and 1994, R.T. Ryder (with R.E. Mattick, J.B. Roen, and J.R. San Filipo, USGS, Reston, Va.) compiled oil and gas fields on stable-base mylar greenline base maps (scale 1:500,000) for selected plays in the Appalachian basin. These map compilations included field names and field numbers where assigned by State agencies. The purpose of the maps was to provide supporting data for the USGS 1995 National Assessment of United States Oil and Gas Resources (Gautier and others, 1995). In particular, the greenline oil and gas field maps were linked, where possible, with production data from State records and (or) published literature in order to determine ultimate sizes for conventional fields and estimated ultimate recovery (EUR) values for wells in continuous accumulations (for definitions of the conventional and continuous terminology, see USGS National Oil and Gas Assessment Team, 1995; Schmoker, 1997; Schenk and Pollastro, 2002). This approach was used in the 1995 national oil and gas assessment because ultimate field size and EUR data were unavailable in the Appalachian region from Petroleum Information, Inc., and other commercial sources. In 2006 and 2007, the greenline Appalachian basin field maps were digitized under the supervision of Scott Kinney and converted to geographic information system (GIS) files for chapter I.1 (this volume). By converting these oil and gas field maps to a digital format and maintaining the field names where noted, they are now available for a variety of oil and gas and possibly carbon-dioxide sequestration projects. Having historical names assigned to known digitized conventional fields provides a convenient classification scheme into which cumulative production and ultimate field-size databases can be organized. Moreover, as exploratory and development drilling expands across the basin, many previously named fields that were originally treated as conventional fields have evolved into large, commonly unnamed continuous-type accumulations. These new digital maps will facilitate a comparison between EUR values from recently drilled, unnamed parts of continuous accumulations and EUR values from named fields discovered early during the exploration cycle of continuous accumulations.

Appalachian basin↗

USGS2018

First comprehensive list of non-native species established in three major regions of the United States

Invasive species are a subset of non-native (or alien) species, and knowing what species are non-native to a region is a first step to managing invasive species. People have been compiling non-native and invasive species lists ever since these species started causing harm, yet national non-native species lists are neither universal, nor common. Non-native species lists serve diverse purposes: watch lists for preventing invasions, inventory and monitoring lists for research and modeling, regulatory lists for species control, and nonregulatory lists for raising awareness. This diversity of purpose and the lists’ variation in geographic scope make compiling comprehensive lists of established (or naturalized) species for large regions difficult. However, listing what species are non-native in an area helps measure Essential Biodiversity Variables for invasive species monitoring and mount an effective response to established non-native species. In total, 1,166 authoritative sources were reviewed to compile the first comprehensive non-native species list for three large regions of the United States: Alaska, Hawaii, and the conterminous United States (lower 48 States). The list contains 11,344 unique names: 598 taxa for Alaska, 5,848 taxa for Hawaii, and 6,675 taxa for the conterminous United States. The list is available to the public from U.S. Geological Survey ScienceBase ( https://doi.org/10.5066/P9E5K160 ), and the intent, though not a guarantee, is to update the list as non-native species become established in, or are eliminated from, the United States. The list has been used to annotate non-native species occurrence records in the U.S. Geological Survey all-taxa mapping application, Biodiversity Information Serving Our Nation (BISON, https://bison.usgs.gov ).

Open-File Report↗

USGS2013

Diet of the eastern mudminnow (Umbra pygmaea DeKay) from two geographically distinct populations within the North American native range

Umbra pygmaea (Eastern Mudminnow) is a freshwater species common in Atlantic slope coastal lowlands from southern New York to northern Florida and is typical of slow-moving, mud-bottomed, and highly vegetated streams, swamps, and small ponds. We examined its seasonal food habits at the Great Swamp National Wildlife Refuge (NWR), NJ and at the Croatan National Forest, NC. A total of 147 Eastern Mudminnow from 35–112 mm TL and 190 Eastern Mudminnow from 22–89 mm TL were examined from these sites, respectively. At both locations, we found it to be a bottom-feeding generalist that consumes cladocerans, ostracods, chironomid larvae, coleopteran larvae, and other insects and crustaceans. Ostracods were most common in the diet at the Great Swamp NWR and occurred in 62% ± 2.5% of the stomachs with food. At Croatan National Forest, chironomid larvae were most common and occurred in 66.7% ± 15.8% of the stomachs. There were no statistically significant differences in diet composition between the sites during the winter, summer, and fall. However, when compared on an annual basis, Jaccard’s Index (θ J = 0.636, P = 0.05) suggested that the diet at the two study sites was significantly different. While we identified the same major food groups at both locations, the utilization of these food groups varied seasonally. Detritus was a major stomach content at both locations throughout the year. We also documented cannibalism during the summer season at both locations. The seasonal diet of the Eastern Mudminnow was similar to that of Umbra limi (Central Mudminnow) and Umbra krameri (European Mudminnow). Our findings here are the first quantitative examinations of seasonal differences in the diet of the Eastern Mudminnow within its native North American range.

Northeastern Naturalist↗

USGS2006

Proceedings of the U.S. Geological Survey Sixth Biennial Geographic Information Science Workshop, Denver, Colorado, April 24-28, 2006

The U.S. Geological Survey's (USGS) Sixth Biennial Geographic Information Science Workshop April 24 - 28, 2006, at the Denver Federal Center in Denver, Colorado, provides a unique opportunity for multi-disciplinary Geographic Information Systems (GIS) and associated scientific professionals to share, learn, present, and discuss a wide variety of geospatial-related topics. Information is exchanged through a series of plenary sessions, hands-on technical workshops, user and commercial vendor demonstrations, lecture and poster sessions, and specialty meetings. Workshop attendance is limited to Department of Interior (DOI) and USGS employees and contractors; however, plenary, hands-on, and lecture sessions have presenters from other Federal agencies, numerous commercial vendors, universities, and several consortia. Over 175 participants are expected to attend the Workshop. Several prominent speakers are featured at this Workshop. Monday evening Star Guest Speaker and National Aeronautics and Space Administration (NASA) Astronaut Captain Dominic Gorie will talk about his experiences as a veteran of three space flights and over 32 days in space, including the NASA Space Shuttle Radar Topography Mission that mapped more than 47 million miles of the Earth's land surface. Selected as an astronaut candidate by NASA in December 1994, Captain Gorie is currently Chief of the Astronaut Shuttle Branch. Monday evening also features a town hall meeting with Geographic Information Office (GIO) leaders Karen Siderelis, Kevin Gallagher, Bob Pierce, Steve Guptill, Mark DeMulder, John Mahoney, and Mark Negri, who will discuss changes and activities within the GIO in an open discussion format. Tuesday plenary sessions feature keynote speaker Dr. P. Patrick Leahy, Acting USGS Director. Dr. Leahy holds undergraduate and graduate degrees in geology (1968) and geophysics (1970) from Boston College. In 1979, he received his doctorate in geology from Rensselaer Polytechnic Institute, where he specialized in regional ground-water studies and hydraulics. Dr. Leahy has been with the USGS since 1974, and has held various technical and managerial positions, including Associate Director for Geology and Chief of the National Water-Quality Assessment (NAWQA) Program. Dr. Leahy will be discussing a broad range of topics including Bureau accomplishments, initiatives, and budgets. The purpose of this proceedings volume is to serve as an activity reference for Workshop attendees as well as an archive of technical abstracts submitted, presented, and discussed at the Workshop. Author, co-author, and presenter names, affiliations, and contact information are listed with presentation titles along with submitted abstracts. Some hands-on sessions are offered twice. In these instances, abstracts submitted for publication are presented in the proceedings on both days they are offered. All acronyms used in these proceedings are explained in the text of each abstract. The term 'ArcGIS' refers to an integrated collection of GIS software products produced by Environmental Systems Research Institute, Inc. (ESRI).

Scientific Investigations Report↗

USGS2013

Desert fires fueled by native annual forbs: effects of fire on communities of plants and birds in the lower Sonoran Desert of Arizona

In 2005, fire ignited by humans swept from Yuma Proving Grounds into Kofa National Wildlife Refuge, Arizona, burning ca. 9,255 ha of Wilderness Area. Fuels were predominantly the native forb Plantago ovata . Large fires at low elevations were rare in the 19th and 20th centuries, and fires fueled by native vegetation are undocumented in the southwestern deserts. We estimated the area damaged by fire using Moderate Resolution Imaging Spectroradiometer and Normalized Difference Vegetation Index, which are more accurate and reduce subjectivity of aerial surveys of perimeters of fires. Assemblages of upland and xeroriparian plants lost 91 and 81% of live cover, respectively, in fires. The trees Olneya tesota and Cercidium had high amounts of top-kill. King Valley was an important xeroriparian corridor for birds. Species richness of birds decreased significantly following the fire. Numbers of breeding birds were lower in burned areas of King Valley 3 years post-fire, compared to numbers in nearby but unburned Alamo Wash. Although birds function within a large geographic scale, the extent of this burn still influenced the relative abundance of local species of breeding birds. This suggests that breeding birds respond to conditions of localized burns and slow recovery of vegetation contributes to continued lower numbers of birds in the burned sites in King Valley.

Arizona↗

USGS2023

Reproductive response of the Samoan swallowtail butterfly to variability in host plant and habitat characteristics

The Samoan swallowtail butterfly ( Papilio godeffroyi ) has become restricted to Tutuila Island, American Samoa. Factors driving its extirpation on other islands may be partly due to the availability and suitability of habitat, given the singular association we observed of P. godeffroyi with its host plant, Micromelum minutum. We expected that as a host plant specialist, P. godeffroyi might respond to variation in the physical traits and habitat context of M. minutum , which could help identify conservation opportunities throughout its present and former range. Because the ecology of P. godeffroyi is largely unknown, we conducted systematic surveys during 15 months in 2013 and 2014 on Tutuila to investigate its reproductive response to the physical and phenological variability of individual host trees and to the structural and geographical variability of the stands in which they occurred. We searched foliage for eggs, larvae, and pupae and monitored seasonal trends in herbivory and production of leaves, flowers, and fruits on 117 host trees in 8 rainforest stands, mostly within the National Park of American Samoa (NPSA), starting in March 2013 and ending in August 2014. We observed high variability in butterfly reproductive output between individual trees and stands, due largely to a strong negative relationship between leaf biomass (at both tree and stand levels) and oviposition density (number of eggs per foliar biomass) and frequency (number of eggs per survey). Distribution patterns of larvae and pupae were less distinct but generally followed trends in oviposition. Our findings indicate that the butterfly is reproducing widely across Tutuila and is likely to respond positively to management to increase the availability of small host trees in low-density stands. Thus, the species is a good candidate for conservation management focusing on habitat.

Tutuila Island↗

USGS2016

Range expansion by Passer montanus in North America

Passer montanus became established in a small area of central North America following its introduction in 1870. P. montanus underwent minimal range expansion in the first 100 years following introduction. However, the North American population of P. montanus is now growing in size and expanding in geographic distribution, having expanded approximately 125 km to the north by 1970. We quantify the distance of spread by P. montanus from its introduction site in the greater St. Louis, Missouri-Illinois, USA area, using distributional (presence) data from the National Audubon Society Christmas Bird Count surveys for the period of 1951 to 2014. Linear regressions of the average annual range center of P. montanus confirmed significant shifts to the north at a rate of 3.3 km/year ( P < 0.001) km/year. Linear regressions of the linear and angular distance of range center indicates significant northern movement (change in angle of mean range center; P < 0.001) since 1951. Our results quantify the extent of a northward range expansion, and suggesting a probable spread of this species northward.

Biological Invasions↗

USGS1992

Map showing bottom topography of the Pacific Continental Margin, Cape Mendocino to Point Conception

All contours, geographic outlines, and political boundaries shown on this map of the bottom topography, or bathymetry, of the Pacific continental margin between 34? and 41? N. latitudes were plotted from digital data bases in the library of the U.S. Geological Survey (USGS)-National Oceanic and Atmospheric Administration (NOAA) Joint Office for Mapping and Research (JOMAR). These digital data were obtained and compiled from many sources; consequently, data quality varies within particular data bases as well as from one data base to another. Bathymetric contours were digitized from a map compiled by Chase and others (1981) and from the unpublished large scale versions of that map (T.E. Chase, unpub. maps, 1981). Data for the area seaward of the continental slope (~2000 m depth) were obtained primarily from the U.S. Coast and Geodetic Survey (C&GS) 1955 Pacific Exploratory Survey, a systematic and detailed (~8 -nmi trackline spacing) survey between Mexico and Canada. The USGS provided data from cruises S3-78-NC, S15-79-NC, L2-77-NC, Ll0-76-NC, and Bartlett 72. Data were also obtained from Scripps Institution of Oceanography cruises Merazine, Blue Flash, Kayak B, Scan I, and Seven Tow (Chase and Menard, 1971; Chase and others, 1975; Wilde and others, 1976; Wilde and others, 1978). The 200-m contour was derived from the National Ocean Survey charts 1306N-20 (1975), 1307N-l1B (1974a), 1307N-18B (1974b), and C&GS chart 1308N-12 (1969). Sea-floor depths were corrected for sound velocity in sea water using Matthew's (1939) tables. Onshore topographic contours were generated by computer from a modified version of 3-arc-second elevation data provided by the Defense Mapping Agency. The United States digital shoreline was obtained from the NOAA, NOS, Nautical Charting Division, National Atlas files. The coastline of Canada was digitized from Canadian Hydrographic Service bathymetric maps. The primary source of names of the sea floor features was the "Gazetteer of Undersea Features" (Defense Mapping Agency, 1990). Acknowledgments Christopher Hines assisted in the construction and verification of the digital data bases. Reviews and suggestions by Edward C. Escowitz and Florence Wong and advice provided by Will Stettner regarding the cartographic design substantially improved the quality of this map. References Cited Chase, T.E., and Menard, H.W., 1971, Bathymetric atlas of the northeastern Pacific Ocean: U.S. Naval Oceanographic Office Publication 1303, scale 1:2,000,000 at 33° latitude, 48 p. Chase, T.E., Wilde, Pat, and Normark, W.R., 1975, Oceanographic data of the Monterey Deep Sea Fan: San Diego, University of California, Institute of Marine Resources Publication TR 58, scale 1:898,524 at 35° latitude. Chase, T.E., Wilde, Pat, Normark, W.R., Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Coast and Geodetic Survey, 1969, Point St. George to Point Delgada: Coast and Geodetic Survey Bathymetric Map 1308N-12, scale 1:250,000. Defense Mapping Agency, 1990, Gazetteer of undersea features (4th ed.): Washington, D.C., Defense Mapping Agency. Matthews, D.J., 1939, Tables of the velocity of sound in pure water and sea water (2d ed.): London, Admiralty, Hydrographic Department, H.D. 282, 52 p. National Ocean Survey, 1974a, Vicinity Pt. Sur to Pt. Reyes: National Ocean Survey Bathymetric Map 1307N-11B, scale 1:250,000. National Ocean Survey, 1974b, Pt. Reyes to Tolo Bank: National Ocean Survey Bathymetric Map 1307N-18B, scale 1:250,000. National Ocean Survey, 1975, Cape San Martin to Point Conception: National Ocean Survey Bathymetric Map 1306N-20, scale 1:250,000. Wilde, Pat, Normark, W.R., and Chase, T.E., 1976, Oceanographic data off central California 37° to 40° North including the Delgada Deep Sea Fan: Berkeley, University of California, Lawrence Berkeley Laboratory Publication 92, scale 1 :864,581 at 38° latitude. Wilde, Pat, Chase, T.E., Holmes, M.L., Normark, W.R., Thomas, J.A., McCulloch, D.S., and Kulm, L.D., 1978, Oceanographic data off northern California-southern Oregon 40° to 43° North including the Gorda Deep Sea Fan: Berkeley, University of California, Lawrence Berkeley Laboratory Publication 251, scale 1:815,482 at 42° latitude.

IMAP↗

USGS2018

Revised technical implementation plan for the ShakeAlert system—An earthquake early warning system for the West Coast of the United States

The U.S. Geological Survey (USGS), along with partner organizations, has developed an earthquake early warning (EEW) system called ShakeAlert for the highest risk areas of the United States: namely, California, Oregon, and Washington. The purpose of the system is to reduce the impact of earthquakes and save lives and property by providing alerts to institutional users and the public. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Alerts can then be sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System. However, these networks were not originally designed for EEW; old equipment needs to be updated and new stations must be added to construct EEW-capable networks. The ShakeAlert data-processing infrastructure includes redundant servers that are geographically distributed at monitoring centers in Seattle, Washington, as well as Menlo Park, Berkeley, and Pasadena in California. Three data-processing layers collect raw ground-motion data from field stations (data layer), analyze these data to estimate the area and intensity of the resulting shaking (production layer), and publish alert products as appropriate for end users (alert layer). The alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission, infrastructure, or expertise to perform public notifications and is therefore recruiting technology enablers from the private sector. Additionally, ShakeAlert will coordinate with both public and private partners to accomplish consistent and ongoing public communication, education, and outreach. The estimated cost of completing the ShakeAlert infrastructure and sensor networks is \$39.4 million and has an estimated annual operation and maintenance cost of \$28.6 million per year. Building a highly reliable data telemetry infrastructure would cost another \$20.5 million and operating this telemetry system would add \$49.8 million per year; however, these costs could be reduced if project partners provide bandwidth on existing systems.

Open-File Report↗

USGS2019

Regional protocol framework for the inventory and monitoring of breeding Atlantic Coast Piping Plovers

This regional protocol provides a framework for quantifying the number of breeding pairs and productivity of Atlantic Coast piping plover (Charadrius melodus) populations during the breeding season. A primary purpose of this protocol is to standardize piping plover monitoring during the breeding season. The survey techniques described herein involve repeated visual counts of adults, nests, eggs, and chicks within a defined survey site (i.e., beach) as well as visual identification of potential threats to survival and productivity. Resulting data can be compiled and analyzed across multiple geographic units (i.e., sites, states, and recovery units) to assess progress toward recovery goals, inform local management decisions, assess management effectiveness, and improve monitoring efforts. This protocol framework was developed as part of the United States Fish and Wildlife Service (USFWS) National Wildlife Refuge System (NWRS) Inventory and Monitoring (I&M) Initiative in coordination with Ecological Services (ES) and state coordinators within the Southeast and Northeast Regions (4 and 5, respectively). Although this protocol framework is to be used primarily by NWRS to inform recovery goals, assist with local management decision-making, and meet State reporting requirements, the approach strives to assist monitoring efforts of nonNWRS partners, such as other federal agencies (e.g. National Park Service), State wildlife agencies, non-governmental organizations, and private landowners. This protocol framework and associated data management system (PIPLweb) aims to interface with existing data management and analysis tools (i.e., PIPLODES, NestStory, and PiperEx) to ensure that data collection is efficient and comparable across scales, and supports management decisions across partners. The content and structure of the protocol framework follows standards set forth in the USFWS’s How to Develop Survey Protocols: A Handbook (Version 1.0; 2013). The eight elements addressed include: introduction, sampling design, field methods, data management and analysis, reporting, personnel requirements and training, operational requirements, and references. A series of standard operating procedures (SOPs) provides greater detail on recommended methods and technical aspects of this protocol. Data entry, archival, and multi-scale analysis are handled through a secure web application (Plover Inventory and Productivity Library; PIPLweb) developed by the United States Geological Survey (USGS). When management activities and survey objectives are similar across management units, partners (Refuges, other federal agencies, State, NGOs, private) are encouraged to use this protocol framework to develop stepped-down site-specific survey protocols that include guidance for conducting on-the-ground monitoring and management plans.

Regional Protocol Framework↗

USGS1984

Habitat Suitability Index Models: Pink shrimp

Shrimp support the most valuable seafood industry in the United States (Roedel 1973; National Marine Fisheries Service 1983). The three most important commercial species are the white shrimp (Penaeus setiferus L.), brown shrimp (P. aztecus Ives), and pink shrimp (P. duorarum Burkenroad). Adult pink shdmp are caught "in commercial quantities throughout most of the geographic ranqe of the species (L indner 1957), and juveni les support a sizable bait shrimp industry along the Florida coast and throughout the Gulf of Mexico (Saloman 1965).

FWS/OBS↗

USGS2005

Public acceptance of management actions and judgments of responsibility for the wolves of the southern Greater Yellowstone Area: Report to Grand Teton National Park

Introduction Wolves of Grand Teton National Park and the Greater Yellowstone Area Gray wolves (Canis lupus) appeared in Grand Teton National Park (GRTE) in October of 1998, two years after being reintroduced to Yellowstone National Park (YNP). Since that time, five packs have been within the GRTE borders - Gros Ventre Pack, Nez Perce Pack, Yellowstone Delta Pack, Teton Pack, and Green River Pack (Table 1). Wolves in the Greater Yellowstone Area are increasing and spreading out geographically (USFWS and others, 2004). This dispersion was demonstrated recently by the death of a 2-year-old female wolf from the Swan Lake pack on I-70 in Colorado (June 7, 2004; http://mountain-prairie.USFWS.gov/pressrel /04-43.htm). The organization of wolf packs in the GYA is dynamic and highly structured. In 2003, for example, a wolf from the Teton Pack joined with the Green River Pack, and several young wolves left the Teton Pack and moved south (USFWS and others, 2004). Pack size (averaging five to ten members) is dependent on hunting efficiency, which depends on prey size, type, and density. Each pack defends home ranges of several hundred square miles. The social structure of the pack is based on a breeding pair (an alpha male and female). Other wolves in the pack can be categorized as betas (males and/or females second in rank to the alphas), subordinates, pups, and occasional omegas (outcasts). Because generally only the alpha pair breeds, subordinate wolves of reproductive age must disperse from their packs and form new associations in order to breed. (http://www.nps.gov/grte/wolf/biolo.htm). The reintroduced wolves are classified by the U.S. Fish and Wildlife Service (USFWS) as "nonessential experimental" under section 10(j) of the Endangered Species Act. The recovery criteria for the GYA wolves were met in 2002 for removing the wolves from the Endangered Species List (30 or more breeding pairs). Currently, the USFWS manages wolf populations in the GYA until delisting occurs. After delisting, state Fish and Wildlife Services in Montana, Idaho, and Wyoming will be responsible for managing wolves. Each state must submit a wolf management plan to the USFWS which then must be approved before management shifts occur. As of this writing, the process of delisting the wolves in the state of Wyoming is ongoing. However, the reclassification of wolves nationwide was completed on April 1, 2003. Wolves outside of YNP changed in status from endangered to threatened. The wolves classified in the experimental nonessential population did not change in status (USFWS and others, 2004). This classification of experimental nonessential population allows for flexibility in management decisions concerning the wolves (Smith and others, 2004). For example, control actions in the GYA included trapping and radio-collaring four wolves; intensive monitoring; increasing riders on grazing allotments; harassing wolves with rubber bullets, cracker shells, and lights; moving livestock to different pastures; and issuing four shoot on-sight permits. When non-lethal control methods were not effective, wolves were killed in an attempt to prevent further livestock depredations (USFWS and others, 2004; Table 1). At the same time that wolf numbers are rising, human population statistics in the GRTE area are also rising. The population of Teton County, Wyoming in 1990 was just over 11,000 people; today that number has increased to approximately 19,000 (U.S. Census Bureau, 2005). park visitation for GRTE has been substantial over the last several years with an average visitation of 2.5 million visitors (NPS, 2004a). Furthermore, land ownership surrounding GRTE and the establishment of grazing rights within park boundaries are problem areas for wolf-human interactions due to livestock depredation. With increasing numbers of visitors, residents, and livestock it is reasonable to assume that conflicts are going to increase also. In 1950, GRTE was expanded to in

Open-File Report↗

USGS2014

Evaluation of the expected moments algorithm and a multiple low-outlier test for flood frequency analysis at streamgaging stations in Arizona

Flooding is among the costliest natural disasters in terms of loss of life and property in Arizona, which is why the accurate estimation of flood frequency and magnitude is crucial for proper structural design and accurate floodplain mapping. Current guidelines for flood frequency analysis in the United States are described in Bulletin 17B (B17B), yet since B17B’s publication in 1982 (Interagency Advisory Committee on Water Data, 1982), several improvements have been proposed as updates for future guidelines. Two proposed updates are the Expected Moments Algorithm (EMA) to accommodate historical and censored data, and a generalized multiple Grubbs-Beck (MGB) low-outlier test. The current guidelines use a standard Grubbs-Beck (GB) method to identify low outliers, changing the determination of the moment estimators because B17B uses a conditional probability adjustment to handle low outliers while EMA censors the low outliers. B17B and EMA estimates are identical if no historical information or censored or low outliers are present in the peak-flow data. EMA with MGB (EMA-MGB) test was compared to the standard B17B (B17B-GB) method for flood frequency analysis at 328 streamgaging stations in Arizona. The methods were compared using the relative percent difference (RPD) between annual exceedance probabilities (AEPs), goodness-of-fit assessments, random resampling procedures, and Monte Carlo simulations. The AEPs were calculated and compared using both station skew and weighted skew. Streamgaging stations were classified by U.S. Geological Survey (USGS) National Water Information System (NWIS) qualification codes, used to denote historical and censored peak-flow data, to better understand the effect that nonstandard flood information has on the flood frequency analysis for each method. Streamgaging stations were also grouped according to geographic flood regions and analyzed separately to better understand regional differences caused by physiography and climate. The B17B-GB and EMA-MGB RPD-boxplot results showed that the median RPDs across all streamgaging stations for the 10-, 1-, and 0.2-percent AEPs, computed using station skew, were approximately zero. As the AEP flow estimates decreased (that is, from 10 to 0.2 percent AEP) the variability in the RPDs increased, indicating that the AEP flow estimate was greater for EMA-MGB when compared to B17B-GB. There was only one RPD greater than 100 percent for the 10- and 1-percent AEP estimates, whereas 19 RPDs exceeded 100 percent for the 0.2-percent AEP. At streamgaging stations with low-outlier data, historical peak-flow data, or both, RPDs ranged from −84 to 262 percent for the 0.2-percent AEP flow estimate. When streamgaging stations were separated by the presence of historical peak-flow data (that is, no low outliers or censored peaks) or by low outlier peak-flow data (no historical data), the results showed that RPD variability was greatest for the 0.2-AEP flow estimates, indicating that the treatment of historical and (or) low-outlier data was different between methods and that method differences were most influential when estimating the less probable AEP flows (1, 0.5, and 0.2 percent). When regional skew information was weighted with the station skew, B17B-GB estimates were generally higher than the EMA-MGB estimates for any given AEP. This was related to the different regional skews and mean square error used in the weighting procedure for each flood frequency analysis. The B17B-GB weighted skew analysis used a more positive regional skew determined in USGS Water Supply Paper 2433 (Thomas and others, 1997), while the EMA-MGB analysis used a more negative regional skew with a lower mean square error determined from a Bayesian generalized least squares analysis. Regional groupings of streamgaging stations reflected differences in physiographic and climatic characteristics. Potentially influential low flows (PILFs) were more prevalent in arid regions of the State, and generally AEP flows were larger with EMA-MGB than with B17B-GB for gaging stations with PILFs. In most cases EMA-MGB curves would fit the largest floods more accurately than B17B-GB. In areas of the State with more baseflow, such as along the Mogollon Rim and the White Mountains, streamgaging stations generally had fewer PILFs and more positive skews, causing estimated AEP flows to be larger with B17B-GB than with EMA-MGB. The effect of including regional skew was similar for all regions, and the observed pattern was increasingly greater B17B-GB flows (more negative RPDs) with each decreasing AEP quantile. A variation on a goodness-of-fit test statistic was used to describe each method’s ability to fit the largest floods. The mean absolute percent difference between the measured peak flows and the log-Pearson Type 3 (LP3)-estimated flows, for each method, was averaged over the 90th, 75th, and 50th percentiles of peak-flow data at each site. In most percentile subsets, EMA-MGB on average had smaller differences (1 to 3 percent) between the observed and fitted value, suggesting that the EMA-MGB-LP3 distribution is fitting the observed peak-flow data more precisely than B17B-GB. The smallest EMA-MGB percent differences occurred for the greatest 10 percent (90th percentile) of the peak-flow data. When stations were analyzed by USGS NWIS peak flow qualification code groups, the stations with historical peak flows and no low outliers had average percent differences as high as 11 percent greater for B17B-GB, indicating that EMA-MGB utilized the historical information to fit the largest observed floods more accurately. A resampling procedure was used in which 1,000 random subsamples were drawn, each comprising one-half of the observed data. An LP3 distribution was fit to each subsample using B17B-GB and EMA-MGB methods, and the predicted 1-percent AEP flows were compared to those generated from distributions fit to the entire dataset. With station skew, the two methods were similar in the median percent difference, but with weighted skew EMA-MGB estimates were generally better. At two gages where B17B-GB appeared to perform better, a large number of peak flows were deemed to be PILFs by the MGB test, although they did not appear to depart significantly from the trend of the data (step or dogleg appearance). At two gages where EMA-MGB performed better, the MGB identified several PILFs that were affecting the fitted distribution of the B17B-GB method. Monte Carlo simulations were run for the LP3 distribution using different skews and with different assumptions about the expected number of historical peaks. The primary benefit of running Monte Carlo simulations is that the underlying distribution statistics are known, meaning that the true 1-percent AEP is known. The results showed that EMA-MGB performed as well or better in situations where the LP3 distribution had a zero or positive skew and historical information. When the skew for the LP3 distribution was negative, EMA-MGB performed significantly better than B17B-GB and EMA-MGB estimates were less biased by more closely estimating the true 1-percent AEP for 1, 2, and 10 historical flood scenarios.

Arizona↗

USGS1993

National Geodata Policy Forum: present and emerging U.S. policies governing the development, evolution, and use of the National Spatial Data Infrastructure: summary report

The first National Geo-Data Policy Forum was held on May 10-12, 1993, in Tyson's Corner, Virginia. The objective of the National Geo-Data Policy Forum was to examine policies related to the evolution and use of the National Spatial Data Infrastructure (NSDI). A second goal was to identify issues concerning spatial data technology and its use by all citizens. Policy makers from the public and private sectors offered ideas on the myriad issues and questions related to the NSDI and learned of concerns that their organizations must address. The links that connect the NSDI to the Clinton Administration's National Information Infrastructure were identified and discussed. The forum offered participants an opportunity to define the NSDI's role in carrying out technology policy.

General Information Product↗