The bedrock geologic map of the Lisbon quadrangle, and parts of the Sugar Hill and East Haverhill quadrangles, Grafton County, New Hampshire, covers an area of approximately 73 square miles (189 square kilometers) in west-central New Hampshire. This map was created as part of a larger effort to produce a new bedrock geologic map of Vermont through the collection of field data at a scale of 1:24,000. A large part of the map area consists of the Bronson Hill anticlinorium, a post-Early Devonian structure that is cored by metamorphosed Cambrian to Devonian sedimentary, volcanic, and plutonic rocks.
The Bronson Hill anticlinorium is the apex of the Middle Ordovician to earliest-Silurian Bronson Hill magmatic arc that contains the Ammonoosuc Volcanics, Partridge Formation, and Oliverian Plutonic Suite, and extends from Maine, through western New Hampshire (down the eastern side of the Connecticut River), through southern New England to Long Island Sound. The deformed and partially eroded arc is locally overlain by a relatively thin Silurian section of metasedimentary rocks (Clough Quartzite and Fitch Formation) that thickens to the east. The Silurian section near Littleton is disconformably overlain by a thicker, Lower Devonian section that includes mostly metasedimentary and minor metavolcanic rocks of the Littleton Formation. The Bronson Hill anticlinorium is bisected by a series of northeast-southwest trending Mesozoic normal faults. Primarily among them is the steeply northwest-dipping Ammonoosuc fault that divides older and younger units (lower and upper sections) of the Ammonoosuc Volcanics. The Ammonoosuc Volcanics are lithologically complex and predominantly include interlayered and interfingered rhyolitic to basaltic volcanic and volcaniclastic rocks, as well as lesser amounts of slate, phyllite, ironstone, chert, sandstone, and pelite. The Albee Formation underlies the Ammonoosuc Volcanics and is predominantly composed of interbedded metamorphosed sandstone, siltstone, and phyllite.
During the Late Ordovician, a series of arc-related plutons intruded the Ammonoosuc Volcanics including the Moody Ledge pluton and the Scrag granite of Billings (1937). Subsequent plutonism related to the Acadian orogeny occurred after volcanism and deposition resulted in the Littleton Formation during the Late Devonian, including the intrusion of the Haverhill pluton and French Pond Granite found in the southern part of the map.
This report consists of a geologic map and an online geographic information systems database that includes contacts of bedrock geologic units, faults, outcrops, and structural geologic information. The geologic map is intended to serve as a foundation for applying geologic information to problems involving land use decisions, groundwater availability and quality, earth resources such as natural aggregate for construction, assessment of natural hazards, and engineering and environmental studies for waste disposal sites and construction projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181016","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Rankin, D.W., 2018, Bedrock geologic map of the Lisbon quadrangle, and parts of the Sugar Hill and East Haverhill quadrangles, Grafton County, New Hampshire: U.S. Geological Survey Open-File Report 2018–1016, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20181016.","productDescription":"1 Sheet: 34.66 x 37.08 inches; Databases; Metadata; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082431","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":399117,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107159.htm"},{"id":353552,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh-metadata.zip","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Lisbon, New Hampshire, Metadata"},{"id":353550,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh.gdb.zip","text":"Database","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Lisbon, New Hampshire, Geodatabase"},{"id":353549,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh-basemap.zip","text":"Base Map","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Lisbon, New Hampshire, Base Map"},{"id":353551,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh-geologicmap.mxd","text":"Geologic Map (ArcGIS 10.5)","linkHelpText":"- Lisbon, New Hampshire, Geologic Map"},{"id":353540,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1016/ofr20181016_lisbon-geologic-map.pdf","text":"Geologic Map","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1016"},{"id":353539,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1016/coverthb2.jpg"}],"scale":"24000","country":"United States","state":"New Hampshire","county":"Grafton County","otherGeospatial":"Lisbon quadrangle, Sugar Hill and East Haverhill quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 44\n ],\n [\n -71.75,\n 44\n ],\n [\n -71.75,\n 44.25\n ],\n [\n -72,\n 44.25\n ],\n [\n -72,\n 44\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate
Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The bedrock geologic map of the Miles Pond and Concord quadrangles covers an area of approximately 107 square miles (276 square kilometers) in east-central Vermont and adjacent New Hampshire, north of and along the Connecticut River. This map was created as part of a larger effort to produce a new bedrock geologic map of Vermont through the collection of field data at a scale of 1:24,000. The majority of the map area consists of the Bronson Hill anticlinorium, a post-Early Devonian structure that is cored by metamorphosed Cambrian to Silurian sedimentary, volcanic, and plutonic rocks. A major feature on the map is the Monroe fault, interpreted to be a west-directed, steeply dipping Late Devonian (Acadian) thrust fault. To the west of the Monroe fault, rocks of the Connecticut Valley-Gaspé trough dominate and consist primarily of metamorphosed Silurian and Devonian sedimentary rocks. To the north, the Victory pluton intrudes the Bronson Hill anticlinorium. The Bronson Hill anticlinorium consists of the metamorphosed Albee Formation, the Ammonoosuc Volcanics, the Comerford Intrusive Complex, the Highlandcroft Granodiorite, and the Joselin Turn tonalite. The Albee Formation is an interlayered, feldspathic metasandstone and pelite that is locally sulfidic. Much of the deformed metasandstone is tectonically pinstriped. In places, one can see compositional layering that was transposed by a steeply southeast-dipping foliation. The Ammonoosuc Volcanics are lithologically complex and predominantly include interlayered and interfingered rhyolitic to basaltic volcanic and volcaniclastic rocks, as well as lesser amounts of siltstone, phyllite, graywacke, and grit. The Comerford Intrusive Complex crops out east of the Monroe fault and consists of metamorphosed gabbro, diorite, tonalite, aplitic tonalite, and crosscutting diabase dikes. Abundant mafic dikes from the Comerford Intrusive Complex intruded the Albee Formation and Ammonoosuc Volcanics east of the Monroe fault. The Highlandcroft Granodiorite and Joslin Turn tonalite plutons intruded during the Middle to Late Ordovician.
West of the Monroe fault, the Connecticut Valley-Gaspé trough consists of the Silurian and Devonian Waits River and Gile Mountain Formations. The Waits River Formation is a carbonaceous muscovite-biotite-quartz (±garnet) phyllite containing abundant beds of micaceous quartz-rich limestone. The Gile Mountain Formation consists of interlayered metasandstone and graphitic (and commonly sulfidic) slate, along with minor calcareous metasandstone and ironstone. Graded bedding is common in the Gile Mountain Formation. Rocks of the Devonian New Hampshire Plutonic Suite intruded as plutons, dikes, and sills. The largest of these is the Victory pluton, which consists of weakly foliated, biotite granite and granodiorite. The Victory pluton also intruded a large part of the Albee Formation to the north.
This report consists of a geologic map and an online geographic information systems database that includes contacts of bedrock geologic units, faults, outcrops, and structural geologic information. The geologic map is intended to serve as a foundation for applying geologic information to problems involving land use decisions, groundwater availability and quality, earth resources such as natural aggregate for construction, assessment of natural hazards, and engineering and environmental studies for waste disposal sites and construction projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181025","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Rankin, D.W., 2018, Bedrock geologic map of the Miles Pond and Concord quadrangles, Essex and Caledonia Counties, Vermont, and Grafton County, New Hampshire: U.S. Geological Survey Open-File Report 2018–1025, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20181025.","productDescription":"1 Sheet: 34.47 x 40.58 inches; Databases; Metadata; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081110","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":353546,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh-geologicmap.mxd","text":"Geologic Map (ArcGIS 10.5)","linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Geologic Map"},{"id":353538,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1025/ofr20181025_concord-miles-pond-geologicmap10.pdf","text":"Geologic Map","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1025"},{"id":399116,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107158.htm"},{"id":353547,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh-metadata.zip","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Metadata"},{"id":353545,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh.gdb.zip","text":"Database","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Geodatabase"},{"id":353544,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh-basemap.zip","text":"Base Map","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Base Map"},{"id":353537,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1025/coverthb3.jpg"}],"scale":"24000","country":"United States","state":"New Hampshire, Vermont","county":"Caledonia County, Essex County, Grafton County","otherGeospatial":"Miles Pond and Concord quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 44.375\n ],\n [\n -71.75,\n 44.375\n ],\n [\n -71.75,\n 44.5\n ],\n [\n -72,\n 44.5\n ],\n [\n -72,\n 44.375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate
Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The collection of high-frequency (in other words, “continuous”) water data has been made easier over the years because of advances in technologies to measure, transmit, store, and query large, temporally dense datasets. Commercially available, in-situ sensors and data-collection platforms—together with new techniques for data analysis—provide an opportunity to monitor water quantity and quality at time scales during which meaningful changes occur. The U.S. Geological Survey (USGS) Continuous Monitoring Workshop was held to build stronger collaboration within the Water Mission Area on the collection, interpretation, and application of continuous monitoring data; share technical approaches for the collection and management of continuous data that improves consistency and efficiency across the USGS; and explore techniques and tools for the interpretation of continuous monitoring data, which increases the value to cooperators and the public. The workshop was organized into three major themes: Collecting Continuous Data, Understanding and Using Continuous Data, and Observing and Delivering Continuous Data in the Future. Presentations each day covered a variety of related topics, with a special session at the end of each day designed to bring discussion and problem solving to the forefront.
The workshop brought together more than 70 USGS scientists and managers from across the Water Mission Area and Water Science Centers. Tools to manage, assure, control quality, and explore large streams of continuous water data are being developed by the USGS and other organizations and will be critical to making full use of these high-frequency data for research and monitoring. Disseminating continuous monitoring data and findings relevant to critical cooperator and societal issues is central to advancing the USGS networks and mission. Several important outcomes emerged from the presentations and breakout sessions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181059","usgsCitation":"Sullivan, D.J., Joiner, J.K., Caslow, K.A., Landers, M.N., Pellerin, B.A., Rasmussen, P.P., and Sheets, R.A., 2018, U.S. Geological Survey continuous monitoring workshop—Workshop summary report: U.S. Geological Survey Open-File Report 2018–1059, 29 p., https://doi.org/10.3133/ofr20181059.","productDescription":"iv, 29 p.","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092143","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":353586,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1059/coverthb.jpg"},{"id":353587,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1059/ofr20181059.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1059"}],"contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
The largest populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) exist in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California. Upper Klamath Lake populations are decreasing because adult mortality, which is relatively low, is not being balanced by recruitment of young adult suckers into known spawning aggregations. Most Upper Klamath Lake juvenile sucker mortality appears to occur within the first year of life. Annual production of juvenile suckers in Clear Lake Reservoir appears to be highly variable and may not occur at all in very dry years. However, juvenile sucker survival is much higher in Clear Lake, with non-trivial numbers of suckers surviving to join spawning aggregations. Long-term monitoring of juvenile sucker populations is needed to (1) determine if there are annual and species-specific differences in production, survival, and growth, (2) to identify the season (summer or winter) in which most mortality occurs, and (3) to help identify potential causes of high juvenile sucker mortality, particularly in Upper Klamath Lake.
We initiated an annual juvenile sucker monitoring program in 2015 to track cohorts in 3 months (June, August, and September) annually in Upper Klamath Lake and Clear Lake Reservoir. We tracked annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, and apparent growth. Using genetic markers, we were able to classify suckers as one of three taxa: shortnose or Klamath largescale suckers, Lost River, or suckers with genetic markers of both species (Intermediate Prob[LRS]). Using catch data, we generated taxa-specific indices of year class strength, August–September apparent survival, and overwinter apparent survival. We also examined prevalence and severity of afflictions such as parasites, wounds, and deformities.
Indices of year class strength in Upper Klamath Lake were similar for shortnose suckers in 2015 and 2016, but about twice as high for Lost River suckers and suckers having intermediate Prob[LRS] in 2016 than in 2015. Indices of apparent August–September survival were lower in 2016 (0.41) than in 2015 (1.07) for shortnose suckers and suckers identified as having intermediate Prob [LRS] (0.14 in 2016 and 1.69 in 2015). Indices of apparent August—September survival were similar in 2016 (0.16) and 2015 (0.07) for Lost River suckers. Indices of apparent survival were lower for age-0 Lost River suckers than age-0 shortnose suckers in both years. Although samples sizes are small, a declining trend in the ratio of Lost River to shortnose suckers from 28/23 (1.22) as age-0 fish in September of 2015 to 1/9 (0.11) as age-1 fish in June of 2016 is consistent with higher over winter apparent mortality for Lost River suckers than shortnose suckers in Upper Klamath Lake.
Shortnose sucker year class strength was greater in years with high Willow Creek inflows and Clear Lake surface elevation during the spawning season, indicating that access to spawning habitat was an important contributing factor. In previous sampling, age-0 sucker catch per unit effort (CPUE) was relatively high in 2011 and 2012, moderately high in 2013, and zero in 2014 and 2015. The 2011 and 2012 year classes continued to be detected, but the 2013 year class went undetected for the first time in 2016. The 2014 year class continued to be undetected in 2016. Three suckers with one annulus each on fin rays were captured in Clear Lake in 2016. Although these fish are potential representatives of the 2015 year class, they were small for their age, indicating they may have hatched in 2016. Age-0 shortnose and Lost River suckers were captured in Clear Lake in 2016, indicating new cohorts of both taxa were produced. Moderate to abundant year classes were produced in 2011, 2012, and 2016 when lake surface elevation greater than 1,378.9 m (4,524 ft) during the February–June spawning season. Also in 2011 and 2016, rapid increases in lake-surface elevation indicated potentially high Willow Creek inflows. A somewhat less abundant year class produced in 2012 than in 2011 and 2016 was associated with lower spawning season inflows. The apparently smaller 2013 year class was formed when Willow Creek inflows were apparently low and lake surface never exceeded 1,379.2 m (4,524.9 ft). In 2014 and 2015, when year-classes were small or not detected, the Clear Lake surface elevations were at or below 1,378.2 m (4,522 ft), and there was very little spring time Willow Creek inflow.
Age-0 shortnose sucker CPUE in Clear Lake was correlated with seasonal decreases in water volumes in 2016 and could not be used to create indices of August–September survival. Age-0 shortnose sucker catch rates in Clear Lake Reservoir were about seven times less in August than in September. Meanwhile, the water volume in Clear Lake Reservoir declined by about 36 percent between these two sampling periods. Higher September catch rates may have resulted from additional age-0 suckers entering the lake from the river, a concentrating effect of declining water volumes, or both.
Differences in August standard length, apparent growth rates, and the prevalence of abnormalities were consistent with healthier age-0 suckers in Clear Lake Reservoir than in Upper Klamath Lake. Age-0 suckers were larger in August in Clear Lake Reservoir than in Upper Klamath Lake, which may be due to an earlier hatch date, faster growth, or both in Clear Lake Reservoir. Sample sizes were only large enough to compare growth rates of age-0 shortnose suckers from Upper Klamath Lake in 2015 to Clear Lake Reservoir in 2016. Age-0 shortnose suckers grew more between August and September in Clear Lake Reservoir in 2016 than in Upper Klamath Lake in 2015. Petechial hemorrhages of the skin on age-0 suckers were more prevalent in Upper Klamath Lake than in Clear Lake Reservoir in 2016. Deformed opercula, black-spot forming parasites, and infections presumed to be Columnaris sp. were observed on less than 12 percent of suckers from Upper Klamath Lake but were not observed on suckers from Clear Lake Reservoir in 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181066","usgsCitation":"Burdick, S.M., Ostberg, C.O., and Hoy, M.S., 2018, Juvenile Lost River and shortnose sucker year class strength, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2016 Monitoring Report: U.S. Geological Survey Open-File Report 2018–1066, 43 p., https://doi.org/10.3133/ofr20181066.","productDescription":"vi, 43 p.","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-094193","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":353625,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1066/coverthb.jpg"},{"id":353626,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1066/ofr20181066.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1066"}],"country":"United States","state":"California, Oregon","county":"Klamath County, Modoc County","otherGeospatial":"Clear Lake Reservoir, 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 -122.11509704589845,\n 42.222924262739824\n ],\n [\n -121.75186157226561,\n 42.222924262739824\n ],\n [\n -121.75186157226561,\n 42.61829672418602\n ],\n [\n -122.11509704589845,\n 42.61829672418602\n ],\n [\n -122.11509704589845,\n 42.222924262739824\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.23687744140624,\n 41.781552998900345\n ],\n [\n -121.04736328125,\n 41.781552998900345\n ],\n [\n -121.04736328125,\n 41.94365947797709\n ],\n [\n -121.23687744140624,\n 41.94365947797709\n ],\n [\n -121.23687744140624,\n 41.781552998900345\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The year 2017 was a year of review and renewal for the Department of the Interior (DOI) Climate Science Centers (CSCs) and the U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center (NCCWSC). The Southeast, Northwest, Alaska, Southwest, and North Central CSCs’ 5-year summary review reports were released in 2017 and contain the findings of the external review teams led by the Cornell University Human Dimensions Research Unit in conjunction with the American Fisheries Society. The reports for the Pacific Islands, South Central, and Northeast CSCs are planned for release in 2018. The reviews provide an opportunity to evaluate aspects of the cooperative agreement, such as the effectiveness of the CSC in meeting project goals and assessment of the level of scientific contribution and achievement. These reviews serve as a way for the CSCs and NCCWSC to look for ways to recognize and enhance our network’s strengths and identify areas for improvement. The reviews were followed by the CSC recompetition, which led to new hosting agreements at the Northwest, Alaska, and Southeast CSCs. Learn more about the excellent science and activities conducted by the network centers in the 2017 annual report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181049","usgsCitation":"Varela Minder, Elda, 2018, U.S. Department of the Interior Climate Science Centers and U.S. Geological Survey National Climate Change and Wildlife Science Center—Annual report for 2017: U.S. Geological Survey Open-File Report 2018–1049, 14 p., https://doi.org/10.3133/ofr20181049.","productDescription":"14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-093217","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":353570,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1049/ofr20181049.pdf","text":"Report","size":"3.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1049"},{"id":353569,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1049/coverthb.jpg"}],"contact":"Director, National Climate Change and Wildlife Science Center (NCCWSC)
U.S. Geological Survey
Mail Stop 516
12201 Sunrise Valley Drive
Reston, VA 20192
The first U.S. Department of the Interior Economics Workshop was held April 5–7, 2017 in Washington, D.C., to identify, highlight, and better understand needs and opportunities for economic analysis to support the Department of the Interior’s mission. The Economics Workshop, jointly convened by the Department of the Interior Office of Policy Analysis and the U.S. Geological Survey Science and Decisions Center, provided an opportunity for Department of the Interior’s economists to share expertise and experiences and to build collaboration and communication channels across the Department of the Interior.
Natural and cultural resource managers face complex questions and often have to balance competing stakeholder interests. Per the mission statement, the Department of the Interior “protects and manages the Nation’s natural resources and cultural heritage; provides scientific and other information about those resources; and honors its trust responsibilities or special commitments to American Indians, Alaska Natives, and affiliated island communities.” Economic analysis is relevant to issues integral to nearly all the land and water management decisions made by the Department of the Interior. More than 80 Department of the Interior economists gathered at the Economics Workshop to share their work, discuss common challenges, and identify approaches to advance the use and contribution of economics at the Department of the Interior.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181054","collaboration":"Prepared in cooperation with the Office of Policy Analysis, U.S. Department of the Interior","usgsCitation":"Pindilli, E.J., Crowley, C.S.L., Cline, S.A., Good, A.J., Shapiro, C.D., and Simon, B.M., 2018, Supporting natural resource management—The role of economics at the Department of the Interior—A workshop report: U.S. Geological Survey Open-File Report 2018–1054, 32 p., https://doi.org/10.3133/ofr20181054.","productDescription":"iv, 32 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-093562","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":353564,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1054/coverthb.jpg"},{"id":353565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1054/ofr20181054.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1054"}],"contact":"Director, Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
We have conducted a gravity survey of the Coso geothermal field to continue the time-lapse gravity study of the area initiated in 1991. In this report, we outline a method of processing the gravity data that minimizes the random errors and instrument bias introduced into the data by the Scintrex CG-5 relative gravimeters that were used. After processing, the standard deviation of the data was estimated to be ±13 microGals. These data reveal that the negative gravity anomaly over the Coso geothermal field, centered on gravity station CER1, is continuing to increase in magnitude over time. Preliminary modeling indicates that water-table drawdown at the location of CER1 is between 65 and 326 meters over the last two decades. We note, however, that several assumptions on which the model results depend, such as constant elevation and free-water level over the study period, still require verification.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181053","collaboration":"Prepared in cooperation with the U.S. Department of the Navy Geothermal Program Office","usgsCitation":"Phelps, G., Cronkite-Ratcliff, C., and Blake, K., 2018, A time-lapse gravity survey of the Coso geothermal field, China Lake Naval Air Weapons Station, California: U.S. Geological Survey Open-File Report 2018–1053, 25 p., https://doi.org/10.3133/ofr20181053.","productDescription":"Report: v, 25 p.; Table","numberOfPages":"31","onlineOnly":"Y","ipdsId":"IP-082096","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":353589,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1053/coverthb.jpg"},{"id":353590,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1053/ofr20181053.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1053"},{"id":353607,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2018/1053/ofr20181053_table1.xlsx","text":"Table 1","size":"22 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2018-1053"}],"country":"United States","state":"California","otherGeospatial":"Coso Geothermal Field, China Lake Naval Air Weapons Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118,\n 35.88682489453265\n ],\n [\n -117.625,\n 35.88682489453265\n ],\n [\n -117.625,\n 36.25\n ],\n [\n -118,\n 36.25\n ],\n [\n -118,\n 35.88682489453265\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Over the period 2014–2016, the number of nonnative brown trout (Salmo trutta) captured during routine monitoring in the Lees Ferry reach of the Colorado River, downstream of Glen Canyon Dam, began increasing. Management agencies and stakeholders have questioned whether the increase in brown trout in the Lees Ferry reach represents a threat to the endangered humpback chub (Gila cypha), to the rainbow trout (Oncorhynchus mykiss) sport fishery, or to other resources of concern. In this report, we evaluate the evidence for the expansion of brown trout in the Lees Ferry reach, consider a range of causal hypotheses for this expansion, examine the likely efficacy of several potential management interventions to reduce brown trout, and analyze the effects of those interventions on other resources of concern.
The brown trout population at Lees Ferry historically consisted of a small number of large fish supported by low levels of immigration from downstream reaches. This population is now showing signs of sustained successful reproduction and is on the cusp of recruiting locally hatched fish into the spawning class, based on analysis with a new integrated population model. The proximate causes of this change in status are a large pulse of immigration in the fall of 2014 and higher reproductive rates in 2015–2017. The ultimate causes of this change are not clear. The pulse of immigrants from downstream reaches in fall 2014 may have been induced by three sequential high-flow releases from the dam in November of 2012–2014, but may also have been the result of a unique set of circumstances unrelated to dam operations. The increase in reproduction may have been the result of any number of changes, including an Allee effect, warmer water temperatures, a decrease in competition from rainbow trout, or fall high-flow releases. Correlations over space and time among predictor variables do not allow us to make a clear inference about the cause of the changes. Under a null causal model, and without any changes to management, we predict there is a 36-percent chance the brown trout population at Lees Ferry will not show sustained growth, and will remain around a mean size of 5,800 adults, near its current size; in contrast, we predict there is a 64-percent chance that the population has a positive intrinsic growth rate and will increase 3–10 fold over the next 20 years. A humpback chub population model linked to the brown trout model suggests an increase of brown trout of this magnitude could lead to declines in the minimum adult humpback chub population over the same time period. Forecasts of rainbow trout abundance, however, suggest that increased abundance of brown trout in the Lees Ferry reach does not pose a threat to the rainbow trout fishery there.
There are interventions that may be effective in moderating the growth of the brown trout population in the Lees Ferry reach of the Colorado River. Across causal hypotheses, we predict that removal strategies (for example, a concerted electrofishing effort or an incentivized take program targeted at large brown trout) could reduce brown trout abundance by approximately 50 percent relative to status quo management. Reductions in the frequency or a change in the seasonal timing of high-flow releases from Glen Canyon Dam could be even more effective, but only under the causal hypotheses that involve effects of such releases on immigration or reproduction. Brown trout management flows— dam releases designed to strand young fish at a vulnerable stage—may be able to reduce brown trout abundance to some degree, but are not forecast to be the most effective strategy under any causal hypothesis.
We predict that the alternative management interventions would have effects on other resource goals as well, and the pattern of these effects differs across causal hypotheses. The removal strategies would incur direct costs (on the order of $7 million over 20 years) and the mechanical removal strategy is unethical from the perspective of several tribes. The strategies that involve reducing the frequency of high-flow releases from Glen Canyon Dam would decrease the ability to transport and store sediment in the ecosystem, potentially undermining goals associated with sandbar building, recreation, and riparian vegetation, but would increase hydropower revenue. Trout management flows would reduce hydropower revenue. From the standpoint of humpback chub, the alternative strategies largely follow the effect on brown trout; when brown trout abundance is reduced, predation pressure decreases, and humpback chub viability is predicted to increase, but the variation in predicted chub viability is not large across strategies or causal hypotheses.
To design a response to brown trout, management agencies will need to navigate both the tradeoffs among resources goals and the uncertainty in the causes of the brown trout expansion. Continued monitoring, possibly coupled with new research or experimental management actions that better inform demographic and ecological dynamics, can help to reduce the causal uncertainty.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181069","collaboration":"Prepared in cooperation with the National Park Service, U.S. Fish and Wildlife Service, Arizona Game and Fish Department, and the Western Area Power Administration","usgsCitation":"Runge, M.C., Yackulic, C.B., Bair, L.S., Kennedy, T.A., Valdez, R.A., Ellsworth, C., Kershner J.L., Rogers, R.S., Trammell, M.A., and Young, K.L., 2018, Brown trout in the Lees Ferry reach of the Colorado River—Evaluation of causal hypotheses and potential interventions: U.S. Geological Survey Open-File Report 2018–1069, 83 p.,\nhttps://doi.org/10.3133/ofr20181069.","productDescription":"ix, 83 p.","numberOfPages":"94","onlineOnly":"Y","ipdsId":"IP-095595","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":353922,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FN15HC","linkHelpText":"Population dynamics of humpback chub, rainbow trout and brown trout in the Colorado River in its Grand Canyon Reach: modelling code and input data"},{"id":353488,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1069/ofr20181069.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1069"},{"id":353487,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1069/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.59500122070312,\n 36.834843899148495\n ],\n [\n -111.47209167480469,\n 36.834843899148495\n ],\n [\n -111.47209167480469,\n 36.946599271636295\n ],\n [\n -111.59500122070312,\n 36.946599271636295\n ],\n [\n -111.59500122070312,\n 36.834843899148495\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road, Ste 4039
Laurel, MD 20708-4039
Beginning in 2014, the U.S. Geological Survey, in collaboration with Bloom Biological, Inc., began telemetry research on golden eagles (Aquila chrysaetos) captured in the San Diego, Orange, and western Riverside Counties of southern California. This work was supported by the San Diego Association of Governments, California Department of Fish and Wildlife, the U.S. Fish and Wildlife Service, the Bureau of Land Management, and the U.S. Geological Survey. Since 2014, we have tracked more than 40 eagles, although this report focuses only on San Diego County eagles.
An important objective of this research is to develop habitat selection models for golden eagles. Here we provide predictions of population-level habitat selection for golden eagles in San Diego County based on environmental covariates related to land use and terrain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181067","collaboration":"Prepared in cooperation with San Diego Association of Governments, U.S. Fish and Wildlife Service, Bureau of Land Management, California Department of Fish and Wildlife","usgsCitation":"Tracey, J.A., Madden, M.C., Bloom, P.H., Katzner, T.E., and Fisher, R.N., 2018, Golden eagle (Aquila chrysaetos) habitat selection as a function of land use and terrain, San Diego County, California: U.S. Geological Survey Open-File Report 2018–1067, 13 p., https://doi.org/10.3133/ofr20181067.","productDescription":"Report: iv, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-096732","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":353465,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OZVGEG","text":"USGS data release","description":"USGS Data 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Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive
Sacramento, California 95819
Seagrasses are highly productive ecosystems. A before-after-control-impact (BACI) design was used to examine effects of dredging on seagrasses and the animals that inhabit them. The control site North Biscayne Bay and the affected site Port of Miami had seagrass densities decrease during both the before, Fish and Invertebrate Assessment Network 2006-2011, and after, Faunal Monitoring in Response to Harbor Dredging 2014-2016, studies. Turbidity levels increased at North Biscayne Bay and Port of Miami basins during the Faunal Monitoring in Response to Harbor Dredging study, especially in 2016. Animal populations decreased significantly in North Biscayne Bay and Port of Miami in the Faunal Monitoring in Response to Harbor Dredging study compared to the Fish and Invertebrate Assessment Network study. Predictive modeling shows that numbers of animal populations will likely continue to decrease if the negative trends in seagrass densities continue unabated. There could be effects on several fisheries vital to the south Florida economy. Additional research could determine if animal populations and seagrass densities have rebounded or continued to decrease.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181052","usgsCitation":"Daniels, A., Stevenson, R., Smith, E., and Robblee, M., 2018, Faunal and vegetation monitoring in response to harbor dredging in the Port of Miami: U.S. Geological Survey Open-File Report 2018–1052, 38 p., https://doi.org/10.3133/ofr20181052.","productDescription":"Report: viii, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-084431","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":353291,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1052/ofr20181052.pdf","text":"Report","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1052"},{"id":353292,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JH3KD9","text":"USGS data release","description":"USGS Data Release ","linkHelpText":"Faunal and vegetation monitoring in response to harbor dredging in Port of Miami"},{"id":353290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1052/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"North Biscayne Bay, Port of Miami","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.20774841308594,\n 25.723209559418265\n ],\n [\n -80.11505126953125,\n 25.723209559418265\n ],\n [\n -80.11505126953125,\n 25.9117325831107\n ],\n [\n -80.20774841308594,\n 25.9117325831107\n ],\n [\n -80.20774841308594,\n 25.723209559418265\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71 Street
Gainesville, FL 32653
Program Coordinator, National Water Quality Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
A geologic map of the greater Portland, Oregon, metropolitan area is planned that will document the region’s complex geology (currently in review: “Geologic map of the greater Portland metropolitan area and surrounding region, Oregon and Washington,” by Wells, R.E., Haugerud, R.A., Niem, A., Niem, W., Ma, L., Evarts, R., Madin, I., and others). The map, which is planned to be published as a U.S. Geological Survey Scientific Investigations Map, will consist of 51 7.5′ quadrangles covering more than 2,500 square miles, and it will represent more than 100 person-years of geologic mapping and studies. The region was mapped at the relatively detailed scale of 1:24,000 to improve understanding of its geology and its earthquake hazards. More than 100 geologic map units will record the 50-million-year history of volcanism, sedimentation, folding, and faulting above the Cascadia Subduction Zone. The geology contributes to the varied terroir of four American Viticultural Areas (AVAs) in the northwestern Willamette Valley: the Yamhill-Carlton, Dundee Hills, Chehalem Mountains, and Ribbon Ridge AVAs. Terroir is defined as the environmental conditions, especially climate and soils, that influence the quality and character of a region’s crops—in this case, grapes for wine.
On this new poster (“New geologic mapping of the northwestern Willamette Valley, Oregon, and its American Viticultural Areas (AVAs)—A foundation for understanding their terroir”), we present the geologic map at a reduced scale (about 1:175,000) to show the general distribution of geologic map units, and we highlight, discuss, and illustrate six major geologic events that helped shape the region and form its terrior. We also discuss the geologic elements that contribute to the character of each of the four AVAs in the northwestern Willamette Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181044","usgsCitation":"Wells, R.E., Haugerud, R., Niem, A., Niem, W., Ma, L., Madin, I., and Evarts, R., 2018, New geologic mapping of the northwestern Willamette Valley, Oregon, and its American Viticultural Areas (AVAs)—A foundation for understanding their terroir: U.S. Geological Survey Open-File Report 2018–1044, https://doi.org/10.3133/ofr20181044.","productDescription":"74.00 x 36.03 inches","ipdsId":"IP-077948","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":353258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1044/coverthb.jpg"},{"id":353259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1044/ofr20181044.pdf","text":"Sheet","size":"58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1044"}],"country":"United States","state":"Oregon","otherGeospatial":"Northwestern Willamette Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.375,\n 46\n ],\n [\n -122.25,\n 46\n ],\n [\n -122.25,\n 45.25\n ],\n [\n -123.375,\n 45.25\n ],\n [\n -123.375,\n 46\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Sample descriptions and analytical data for more than 200 K/Ar and 40Ar/39Ar analyses from rocks of the Alaska-Aleutian Range batholith of south-central Alaska are reported here. Samples were collected over a period of 20 years by Bruce R. Reed and Marvin A. Lanphere (both U.S. Geological Survey) as part of their studies of the batholith.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181033","usgsCitation":"Koeneman, L.L., and Wilson, F.H., comps., 2018, Legacy K/Ar and 40Ar/39Ar geochronologic data from the Alaska-\nAleutian Range batholith of south-central Alaska: U.S. Geological Survey Open-File Report 2018–1033, 8 p.,\n1 plate, https://doi.org/10.3133/ofr20181033.","productDescription":"Plate: 16.96 x 27.64 inches; Pamphlet: iii, 8 p.; 2 Tables; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-086126","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":352666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1033/coverthb.jpg"},{"id":352667,"rank":2,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2018/1033/ofr20181033.pdf","text":"Report","size":"50.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1033"},{"id":352670,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2018/1033/ofr20181033_table02.csv","text":"Table 2","size":"7 KB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2018-1033 Table 2"},{"id":352669,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2018/1033/ofr20181033_table01.csv","text":"Table 1","size":"83 KB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2018-1033 Table 1"},{"id":352671,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1033/ofr20181033_metadata.zipx","text":"Metadata","size":"19 KB zipx","description":"OFR 2018-1033 Metadata"},{"id":352668,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1033/ofr20181033_pamphlet.pdf","text":"Pamphlet","size":"404 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1033 Pamphlet"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.25,\n 59.75\n ],\n [\n -151.875,\n 59.75\n ],\n [\n -151.875,\n 62\n ],\n [\n -155.25,\n 62\n ],\n [\n -155.25,\n 59.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center staff
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Alaska Mineral Resources
Alaska Science Center
Fisheries and water managers often use population models to aid in understanding the effect of alternative water management or restoration actions on anadromous fish populations. We developed the Stream Salmonid Simulator (S3) to help resource managers evaluate the effect of management alternatives on juvenile salmonid populations. S3 is a deterministic stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and usable habitat area or carrying capacity. The physical characteristics of each habitat unit and the number of fish occupying each unit, in turn, drive survival and growth within each habitat unit and movement of fish among habitat units.
The purpose of this report is to outline the underlying general structure of the S3 model that is common among different applications of the model. We have developed applications of the S3 model for juvenile fall Chinook salmon (Oncorhynchus tshawytscha) in the lower Klamath River. Thus, this report is a companion to current application of the S3 model to the Trinity River (in review). The general S3 model structure provides a biological and physical framework for the salmonid freshwater life cycle. This framework captures important demographics of juvenile salmonids aimed at translating management alternatives into simulated population responses. Although the S3 model is built on this common framework, the model has been constructed to allow much flexibility in application of the model to specific river systems. The ability for practitioners to include system-specific information for the physical stream structure, survival, growth, and movement processes ensures that simulations provide results that are relevant to the questions asked about the population under study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181056","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Perry, R.W., Plumb, J.M., Jones, E.C., Som, N.A., Hetrick, N.J., and Hardy, T.B., 2018, Model structure of the stream salmonid simulator (S3)—A dynamic model for simulating growth, movement, and survival of juvenile salmonids: U.S. Geological Survey Open-File Report 2018-1056, 32 p., https://doi.org/10.3133/ofr20181056.","productDescription":"iv, 32 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-092781","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":353225,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1056/coverthb.jpg"},{"id":353226,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1056/ofr20181056.pdf","text":"Report","size":"971 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1056"}],"contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Kings Bay, Florida, is one of the most important natural winter habitat locations for the federally threatened Trichechus manatus latirostris (Florida manatee). Crystal River National Wildlife Refuge was established in 1983 specifically to provide protection for manatees and their critical habitat. To aid managers at the refuge and other agencies with this task, spatial analyses of local habitat use locations and travel corridors of manatees in Kings Bay during manatee season (November 15–March 31) are presented based on Global Positioning System telemetry of 41 manatees over a 12-year timespan (2006−18). Local habitat use areas and travel corridors differed spatially when Gulf of Mexico water temperatures were cold (less than or equal to 17 degrees Celsius) versus when they were warm (greater than 17 degrees Celsius). During times of cold water, manatees were found in higher concentrations in the main springs and canals throughout the eastern side of the bay, whereas when waters were warm, they were found more generally throughout the bay and into Crystal River, except for the central open part of the bay and the southwest corner.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181051","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Bureau of Ocean Energy Management","usgsCitation":"Slone, D.H., Butler, S.M., and Reid, J.P., 2018, Movements and habitat use locations of manatees within Kings Bay Florida during the Crystal River National Wildlife Refuge winter season (November 15–March 31): U.S. Geological Survey Open-File Report 2018–1051, 11 p., https://doi.org/10.3133/ofr20181051.","productDescription":"iv, 11 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-096292","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":353049,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171146","text":"Open-File Report 2017-1146","linkHelpText":"Timing of warm water refuge use in Crystal River National Wildlife Refuge by manatees—Results and insights from Global Positioning System telemetry data"},{"id":353037,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1051/coverthb2.jpg"},{"id":353038,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1051/ofr20181051.pdf","text":"Report","size":"3.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1051"}],"country":"United States","state":"Florida","otherGeospatial":"Kings Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.62,\n 28.9\n ],\n [\n -82.58,\n 28.9\n ],\n [\n -82.58,\n 28.875\n ],\n [\n -82.62,\n 28.875\n ],\n [\n -82.62,\n 28.9\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71 Street
Gainesville, FL 32653
The U.S. Geological Survey (USGS) conducted a program of bedrock geologic mapping in much of the central and western Upper Peninsula of Michigan from the 1940s until the late 1990s. Geologic studies in this region are hampered by a scarcity of bedrock exposures because of a nearly continuous blanket of unconsolidated sediments resulting from glaciation of the region during the Pleistocene ice ages. The USGS mapping, done largely at a scale of 1:24,000, routinely recorded the location and extent of exposed bedrock to provide both an indication of where direct observations were made and a guide for future investigations to expedite location of observable rock exposures. The locations of outcrops were generally shown as colored or patterned overlays on printed geologic maps. Although those maps have been scanned and are available as Portable Document Format (PDF) files, no further digital portrayal of the outcrops had been done. We have conducted a prototype study of digitizing and improving locational accuracy of the outcrop locations in parts of Dickinson County, Michigan, to form a data layer that can be used with other data layers in geographic information system applications.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181042","usgsCitation":"Cannon, W.F., Schulte, Ruth, and Bickerstaff, Damon, 2018, Digital representation of exposures of Precambrian bedrock in parts of Dickinson and Iron Counties, Michigan, and Florence and Marinette Counties, Wisconsin: \nU.S. Geological Survey Open-File Report 2018–1042, 3 p., https://doi.org/10.3133/ofr20181042.","productDescription":"Report: 3 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091916","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":352778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1042/coverthb.jpg"},{"id":352779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1042/ofr20181042.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1042"},{"id":352780,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7SJ1JH0","text":"USGS data release","description":"USGS data release"}],"country":"United States","state":"Michigan, Wisconsin","county":"Dickinson County, Florence County, Iron County, Marinette County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.1333,\n 45.75\n ],\n [\n -87.7,\n 45.75\n ],\n [\n -87.7,\n 46.1\n ],\n [\n -88.1333,\n 46.1\n ],\n [\n -88.1333,\n 45.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Mineral and Environmental Resources
12201 Sunrise Valley Drive
Mail Stop 954
Reston, VA 20192
The Nation’s eastern coast is fringed by beaches, dunes, barrier islands, wetlands, and bluffs. These natural coastal barriers provide critical benefits and services, and can mitigate the impact of storms, erosion, and sea-level rise on our coastal communities. Waves and storm surge resulting from Hurricane Sandy, which made landfall along the New Jersey coast on October 29, 2012, impacted the U.S. coastline from North Carolina to Massachusetts, including Assateague Island, Maryland and Virginia, and the Delmarva coastal system. The storm impacts included changes in topography, coastal morphology, geology, hydrology, environmental quality, and ecosystems.
In the immediate aftermath of the storm, light detection and ranging (lidar) surveys from North Carolina to New York documented storm impacts to coastal barriers, providing a baseline to assess vulnerability of the reconfigured coast. The focus of much of the existing coastal change assessment is along the ocean-facing coastline; however, much of the coastline affected by Hurricane Sandy includes the estuarine-facing coastlines of barrier-island systems. Specifically, the wetland and back-barrier shorelines experienced substantial change as a result of wave action and storm surge that occurred during Hurricane Sandy (see also USGS photograph, http://coastal.er.usgs.gov/hurricanes/sandy/photo-comparisons/virginia.php). Assessing physical shoreline and wetland change (land loss as well as land gains) can help to determine the resiliency of wetland systems that protect adjacent habitat, shorelines, and communities.
To address storm impacts to wetlands, a vulnerability assessment should describe both long-term (for example, several decades) and short-term (for example, Sandy’s landfall) extent and character of the interior wetlands and the back-barrier-shoreline changes. The objective of this report is to describe several new wetland vulnerability assessments based on the detailed physical changes estimated from observations. The scope includes understanding changes caused by both short- and long-term processes using both remotely sensed and in situ observations to characterize changes to the wetland in terms of accretion/expansion and erosion/contraction. Accretion may be due to net vertical and (or) horizontal deposition, including estuarine-shoreline change due to overwash. Wetland erosion may be due to elevated waves and water levels in the estuary itself. We included additional information based on wave runup and storm-surge elevations based on models and elevation data. We then developed a predictive assessment for wetland vulnerability that describes the likelihood of changes of the estuarine shoreline and the landward extent of sand overwash driven by processes occurring on the ocean-facing shoreline. This assessment is intended to be linked to the beach and dune vulnerability assessments that have been developed previously.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171157","usgsCitation":"Plant, N.G., Smith, K.E.L., Passeri, D.L., Smith, C.G., and Bernier, J.C., 2018, Barrier-island and estuarine-wetland physical-change assessment after Hurricane Sandy: U.S. Geological Survey Open-File Report 2017–1157, 36 p., https://doi.org/10.3133/ofr20171157.","productDescription":"viii, 36 p.","numberOfPages":"45","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073468","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353051,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1157/coverthb.jpg"},{"id":353052,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1157/ofr20171157.pdf","text":"Report","size":"7.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1157"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
A multi-year evaluation was conducted during 2010–16 to evaluate passage survival of juvenile steelhead (Oncorhynchus mykiss), Chinook salmon (O. tshawytscha), and coho salmon (O. kisutch) in Lake Scanewa, and at Cowlitz Falls Dam in the upper Cowlitz River Basin, Washington. Reservoir passage survival was evaluated in 2010, 2011, and 2016, and included the tagging and release of 1,127 juvenile salmonids. Tagged fish were released directly into the Cowlitz and Cispus Rivers, 22.3 and 8.9 km, respectively, upstream of the reservoir, and were monitored as they moved downstream into, and through the reservoir. A single release-recapture survival model was used to analyze detection records and estimate reservoir passage survival, which was defined as successful passage from reservoir entry to arrival at Cowlitz Falls Dam. Tagged fish generally moved quickly downstream of the release sites and, on average, arrived in the dam forebay within 2 d of release. Median travel time from release to first detection at the dam ranged from 0.23 to 0.96 d for juvenile steelhead, from 0.15 to 1.11 d for juvenile coho salmon, and from 0.18 to 1.89 d for juvenile Chinook salmon. Minimum reservoir passage survival probabilities were 0.960 for steelhead, 0.855 for coho salmon and 0.900 for Chinook salmon.
Dam passage survival was evaluated at the pilot-study level during 2013–16 and included the tagging and release of 2,512 juvenile salmonids. Juvenile Chinook salmon were evaluated during 2013–14, and juvenile steelhead and coho salmon were evaluated during 2015–16. A paired-release study design was used that included release sites located upstream and downstream of Cowlitz Falls Dam. The downstream release site was positioned at the downstream margin of the dam’s tailrace, which allowed dam passage survival to be measured in a manner that included mortality that occurred in the passage route and in the dam tailrace. More than one-half of the tagged Chinook salmon (52 percent) released upstream of Cowlitz Falls Dam moved downstream and passed the project; the remaining fish either remained upstream of the dam (37 percent) or were collected (11 percent). In 2015 and 2016, collection efficiencies at Cowlitz Falls Dam were abnormally high for juvenile steelhead and coho salmon, which resulted in few fish passing the dam. Seven percent of the tagged steelhead (40 fish) and 4 percent of the tagged coho salmon (18 fish) released upstream of the dam eventually passed the project, but these low numbers of fish precluded the estimation of meaningful survival estimates. Dam passage survival probability estimates for juvenile Chinook salmon were 0.828 in 2013 and 0.861 in 2014, lower than previously reported for turbine-specific passage Cowlitz Falls Dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181050","collaboration":"Prepared in cooperation with the Lewis County Public Utility District, Washington","usgsCitation":"Liedtke, T.L., Kock, T.J., and Hurst, W., 2018, Passage survival of juvenile steelhead, coho salmon, and Chinook salmon in Lake Scanewa and at Cowlitz Falls Dam, Cowlitz River, Washington, 2010–16: U.S. Geological Survey Open-File Report 2018-1050, 44 p., https://doi.org/10.3133/ofr20181050.","productDescription":"viii, 44 p.","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-094272","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":353112,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1050/ofr20181050.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1050"},{"id":353111,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1050/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Cowlitz Falls Dam, Cowlitz River, Lake Scanewa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1844482421875,\n 46.42129253514276\n ],\n [\n -121.94549560546875,\n 46.42129253514276\n ],\n [\n -121.94549560546875,\n 46.53477563383562\n ],\n [\n -122.1844482421875,\n 46.53477563383562\n ],\n [\n -122.1844482421875,\n 46.42129253514276\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The South Bay Salt Pond Restoration Project (Project) is one of the largest restoration efforts in the United States. It is located in South San Francisco Bay of California. It is unique not only for its size—more than 15,000 acres—but also for its location adjacent to one of the nation’s largest urban areas, home to more than 4 million people (Alameda, Santa Clara, and San Mateo Counties). The Project is intended to restore and enhance wetlands in South San Francisco Bay while providing for flood management, wildlife-oriented public access, and recreation. Restoration goals of the project are to provide a mosaic of saltmarsh habitat to benefit marsh species and managed ponds to benefit waterbirds, throughout 3 complexes and 54 former salt ponds.
Although much is known about the project area, significant uncertainties remain with a project of this geographic and temporal scale of an estimated 50 years to complete the restoration. For example, in order to convert anywhere from 50 to 90 percent of the existing managed ponds to saltmarsh habitat, conservation managers first enhance the habitat of managed ponds in order to increase use by waterbirds, and provide migratory, wintering, and nesting habitat for more than 90 species of waterbirds. Project managers have concluded that the best way to address these uncertainties is to carefully implement the project in phases and learn from the outcome of each phase. The Adaptive Management Plan (AMP) identifies specific restoration targets for multiple aspects of the Project and defines triggers that would necessitate some type of management action if a particular aspect is trending negatively. U.S. Geological Survey (USGS) biologist Laura Valoppi served as the project Lead Scientist and oversaw implementation of the AMP in coordination with other members of the Project Management Team (PMT), comprised of representatives from the California State Coastal Conservancy, California Department of Fish and Wildlife, the Santa Clara Valley Water District, the U.S. Army Corps of Engineers, and the U.S. Fish and Wildlife Service.
To implement the AMP, the PMT have selected and funded applied studies and monitoring projects to address key uncertainties. This information is used by the PMT to make decisions about current management of the project area and future restoration actions in order to meet project.
This document summarizes the major scientific findings from studies conducted from 2009 to 2016, as part of the science program that was conducted in conjunction with Phase 1 restoration and management actions. Additionally, this report summarizes the management response to the study results under the guidance of the AMP framework and provides a list of suggested studies to be conducted in “Phase 2–A scorecard summarizing the Project’s progress toward meeting the AMP goals for a range of Project objectives.” The scoring to date indicates that the Project is meeting or exceeding expectations for sediment accretion and western snowy plover (Charadrius alexandrinus nivosus) recovery. There is uncertainty with respect to objectives for California gulls (Larus californicus), California least tern (Sternula antillarum), steelhead trout (Oncorhynchus mykiss), and regulatory water quality objectives. Water quality and algal blooms, specifically of the managed ponds, is indicated as trending negative. However, the vast majority of objectives are trending positive, including increased abundance for a number of bird guilds, increasing marsh habitat, maintenance of mudflats, visitor experience, estuarine fish numbers, and special-status marsh species numbers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181039","collaboration":"Prepared for South Bay Salt Pond Restoration Project","usgsCitation":"Valoppi, L., 2018, Phase 1 studies summary of major findings of the South Bay Salt Pond Restoration Project, South San Francisco Bay, California: U.S. Geological Survey Open-File Report 2018–1039, 58 p., plus appendixes, https://doi.org/10.3133/ofr20181039.","productDescription":"Report: vi, 58 p.; 3 Appendixes","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081943","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":353042,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1039/ofr20181039.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1039"},{"id":353041,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1039/coverthb.jpg"},{"id":353043,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1039/ofr20181039_appendix01.pdf","text":"Appendix 1","size":"401 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1039 Appendix 1"},{"id":353044,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1039/ofr20181039_appendix02.pdf","text":"Appendix 2","size":"265 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1039 Appendix 2"},{"id":353045,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1039/ofr20181039_appendix03.pdf","text":"Appendix 3","size":"216 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1039 Appendix 3"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.33688354492188,\n 37.36797435878155\n ],\n [\n -121.86309814453124,\n 37.36797435878155\n ],\n [\n -121.86309814453124,\n 37.654470456416256\n ],\n [\n -122.33688354492188,\n 37.654470456416256\n ],\n [\n -122.33688354492188,\n 37.36797435878155\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 aim of the South Bay Salt Pond Restoration Project (hereinafter “Project”) is to restore 50–90 percent of former salt evaporation ponds to tidal marsh in San Francisco Bay (SFB). However, hundreds of thousands of waterbirds use these ponds over winter and during fall and spring migration. To ensure that existing waterbird populations are supported while tidal marsh is restored in the Project area, managers plan to enhance the habitat suitability of ponds by adding islands and berms to change pond topography, manipulating water salinity and depth, and selecting appropriate ponds to maintain for birds. To help inform these actions, we used 13 years of monthly (October–April) bird abundance data from Project ponds to (1) assess trends in waterbird abundance since the inception of the Project, and (2) evaluate which pond habitat characteristics were associated with highest abundances of different avian guilds and species. For comparison, we also evaluated waterbird abundance trends in active salt production ponds using 10 years of monthly survey data.
We assessed bird guild and species abundance trends through time, and created separate trend curves for Project and salt production ponds using data from every pond that was counted in a year. We divided abundance data into three seasons—fall (October–November), winter (December–February), and spring (March–April). We used the resulting curves to assess which periods had the highest bird abundance and to identify increasing or decreasing trends for each guild and species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181040","usgsCitation":"De La Cruz, S.E.W., Smith, L.M., Moskal, S.M., Strong, C., Krause, J., Wang, Y., and Takekawa, J.Y., 2018, Trends and habitat associations of waterbirds using the South Bay Salt Pond Restoration Project, San Francisco Bay, California: U.S. Geological Survey Open-File Report 2018–1040, 136 p., https://doi.org/10.3133/ofr20181040.","productDescription":"viii, 136 p.","numberOfPages":"148","onlineOnly":"Y","ipdsId":"IP-080192","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":353069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1040/coverthb.jpg"},{"id":353070,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1040/ofr20181040.pdf","text":"Report","size":"6.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1040"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.20642089843749,\n 37.406164630829345\n ],\n [\n -121.90704345703124,\n 37.406164630829345\n ],\n [\n -121.90704345703124,\n 37.645771969647\n ],\n [\n -122.20642089843749,\n 37.645771969647\n ],\n [\n -122.20642089843749,\n 37.406164630829345\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
Factors affecting water-quality trends in urban streams are not well understood, despite current regulatory requirements and considerable ongoing investments in gray and green infrastructure. To address this gap, long-term water-quality trends and factors affecting these trends were examined in the Gwynns Falls, Maryland, watershed during 1998–2016 in cooperation with Blue Water Baltimore. Data on water-quality constituents and potential factors of influence were obtained from multiple sources and compiled for analysis, with a focus on data collected as part of the National Science Foundation funded Long-Term Ecological Research project, the Baltimore Ecosystem Study.
Variability in climate (specifically, precipitation) and land cover can overwhelm actions taken to improve water quality and can present challenges for meeting regulatory goals. Analysis of land cover during 2001–11 in the Gwynns Falls watershed indicated minimal change during the study time frame; therefore, land-cover change is likely not a factor affecting trends in water quality. However, a modest increase in annual precipitation and a significant increase in winter precipitation were apparent in the region. A higher proportion of runoff producing storms was observed in the winter and a lower proportion in the summer, indicating that climate change may affect water quality in the watershed. The increase in precipitation was not reflected in annual or seasonal trends of streamflow in the watershed. Nonetheless, these precipitation changes may exacerbate the inflow and infiltration of water to gray infrastructure and reduce the effectiveness of green infrastructure. For streamflow and most water-quality constituents examined, no discernable trends were noted over the timeframe examined. Despite the increases in precipitation, no trends were observed for annual or seasonal discharge at the various sites within the study area. In some locations, nitrate, phosphate, and total nitrogen show downward trends, and total phosphorus and chloride show upward trends.
Sanitary sewer overflows (gray infrastructure) and best management practices (green infrastructure) were identified as factors affecting water-quality change. The duration of sanitary sewer overflows was positively correlated with annual loads of nutrients and bacteria, and the drainage area of best management practices was negatively correlated with annual loads of phosphate and sulfate. Results of the study indicate that continued investments in gray and green infrastructure are necessary for urban water-quality improvement. Although this outcome is not unexpected, long-term datasets such as the one used in this study, allow the effects of gray and green infrastructures to be quantified.
Results of this study have implications for the Gwynns Falls watershed and its residents and Baltimore City and County managers. Moreover, outcomes are relevant to other watersheds in the metropolitan region that do not have the same long-term dataset. Further, this study has established a framework for ongoing statistical analysis of primary factors affecting urban water-quality trends as regulatory programs mature.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181038","collaboration":"Prepared in cooperation with Blue Water Baltimore","usgsCitation":"Majcher, E.H., Woytowitz, E.L., Reisinger, A.J., and Groffman, P.M., 2018, Factors affecting long-term trends in surface-water quality in the Gwynns Falls watershed, Baltimore City and County, Maryland, 1998–2016: U.S. Geological Survey Open-File Report 2018–1038, 27 p., https://doi.org/10.3133/ofr20181038.","productDescription":"Report: viii, 27 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-094705","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":352999,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1038/coverthb2.jpg"},{"id":353000,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1038/ofr20181038.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1038"},{"id":353001,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76T0KTJ","text":"USGS data release","description":"USGS data release","linkHelpText":"Nutrient, bacteria, ammonia, total Kjeldahl nitrogen, & total suspended solids annual loads; green & gray infrastructure; land cover change; & climate data in the Gwynns Falls subwatersheds, Baltimore, Maryland, 1998-2016 "}],"country":"United States","state":"Maryland","county":"Baltimore County","city":"Baltimore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.8833,\n 39.5\n ],\n [\n -76.5,\n 39.5\n ],\n [\n -76.5,\n 39.1667\n ],\n [\n -76.8833,\n 39.1667\n ],\n [\n -76.8833,\n 39.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
A substantial part of the U.S. Pacific Northwest is underlain by Cenozoic volcanic and continental sedimentary rocks and, where widespread, these strata form important aquifers. The legacy geologic mapping presented with this report contains new thematic categorization added to state digital compilations published by the U.S. Geological Survey for Oregon, California, Idaho, Nevada, Utah, and Washington (Ludington and others, 2005). Our additional coding is designed to allow rapid characterization, mainly for hydrogeologic purposes, of similar rocks and deposits within a boundary expanded slightly beyond that of the Pacific Northwest Volcanic Aquifer System study area. To be useful for hydrogeologic analysis and to be more statistically manageable, statewide compilations from Ludington and others (2005) were mosaicked into a regional map and then reinterpreted into four main categories on the basis of (1) age, (2) composition, (3) hydrogeologic grouping, and (4) lithologic pattern. The coding scheme emphasizes Cenozoic volcanic or volcanic-related rocks and deposits, and of primary interest are the codings for composition and age.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181030","usgsCitation":"Sherrod, D.R., and Keith, M.K., 2018, GIS database and discussion for the distribution, composition, and age of Cenozoic volcanic rocks of the Pacific Northwest Volcanic Aquifer System study area: U.S. Geological Survey Open-File Report 2018–1030, 16 p., https://doi.org/10.3133/ofr20181030. ","productDescription":"Pamphlet: iv, 16 p.; Spatial data; Metadata; Readme","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085785","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":353011,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2018/1030/ofr20181030_readme.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2018-1030 Read Me"},{"id":353014,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1030/ofr20181030_NVASA_AgeComp_gis.zip","size":"14.1 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1030 GIS"},{"id":353008,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1030/coverthb.jpg"},{"id":353009,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1030/ofr20181030_pamphlet.pdf","text":"Pamphlet","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1030 Pamphlet"},{"id":353013,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1030/ofr20181030_NVASA_AgeComp_metadata.zip","size":"14 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1030 Metadata"}],"country":"United States","otherGeospatial":"Pacific Northwest Volcanic Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 39\n ],\n [\n -113,\n 39\n ],\n [\n -113,\n 47\n ],\n [\n -123,\n 47\n ],\n [\n -123,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
Cascades Volcano Observatory - Portland
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, WA, 98683
Water, bed sediment, and biota were sampled in selected streams from Butte to near Missoula, Montana, as part of a monitoring program in the upper Clark Fork Basin of western Montana. The sampling program was led by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to characterize aquatic resources in the Clark Fork Basin, with emphasis on trace elements associated with historic mining and smelting activities. Sampling sites were on the Clark Fork and selected tributaries. Water samples were collected periodically at 20 sites from October 2015 through September 2016. Bed-sediment and biota samples were collected once at 13 sites during August 2016.
This report presents the analytical results and quality-assurance data for water-quality, bed-sediment, and biota samples collected at sites from October 2015 through September 2016. Water-quality data include concentrations of selected major ions, trace elements, and suspended sediment. Samples for analysis of turbidity were collected at 13 sites, whereas samples for analysis of dissolved organic carbon were collected at 10 sites. In addition, samples for analysis of nitrogen (nitrate plus nitrite) were collected at two sites. Daily values of mean suspended-sediment concentration and suspended-sediment discharge were determined for three sites. Seasonal daily values of turbidity were determined for five sites. Bed-sediment data include trace-element concentrations in the fine-grained (less than 0.063 millimeter) fraction. Biological data include trace-element concentrations in whole-body tissue of aquatic benthic insects. Statistical summaries of water-quality, bed-sediment, and biological data for sites in the upper Clark Fork Basin are provided for the period of record.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171136","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Dodge, K.A., Hornberger, M.I., and Turner, M.A., 2018, Water-quality, bed-sediment, and biological data (October 2015 through September 2016) and statistical summaries of data for streams in the Clark Fork Basin, Montana: U.S. Geological Survey Open-File Report 2017–1136, 118 p., https://doi.org/10.3133/ofr20171136.","productDescription":"Report: vi, 118 p.; Data Release","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-089429","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":352885,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79C6WDM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-Quality, Bed-Sediment, and Biological Data (October 2015 through September 2016) and Statistical Summaries of Data for Streams in the Clark Fork Basin, Montana"},{"id":352884,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pubs/of/2017/1136/ofr20171136.pdf","text":"Report","size":"3.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2017–1136"},{"id":352883,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pubs/of/2017/1136/coverthb2.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114,\n 45.85\n ],\n [\n -112.41485595703125,\n 45.85\n ],\n [\n -112.41485595703125,\n 47\n ],\n [\n -114,\n 47\n ],\n [\n -114,\n 45.85\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Habitat models using lidar-derived variables that quantify fine-scale variation in vegetation structure can improve the accuracy of occupancy estimates for canopy-dwelling species over models that use variables derived from other remote sensing techniques. However, the ability of models developed at such a fine spatial scale to maintain accuracy at regional or larger spatial scales has not been tested. We tested the transferability of a lidar-based habitat model for the threatened Marbled Murrelet (Brachyramphus marmoratus) between two management districts within a larger regional conservation zone in coastal western Oregon. We compared the performance of the transferred model against models developed with data from the application location. The transferred model had good discrimination (AUC = 0.73) at the application location, and model performance was further improved by fitting the original model with coefficients from the application location dataset (AUC = 0.79). However, the model selection procedure indicated that neither of these transferred models were considered competitive with a model trained on local data. The new model trained on data from the application location resulted in the selection of a slightly different set of lidar metrics from the original model, but both transferred and locally trained models consistently indicated positive relationships between the probability of occupancy and lidar measures of canopy structural complexity. We conclude that while the locally trained model had superior performance for local application, the transferred model could reasonably be applied to the entire conservation zone.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181035","usgsCitation":"Hagar, J.C., Perez, R.A., Haggerty, P., and Hollenbeck, J.P., 2018, Modeling habitat for Marbled Murrelets on the Siuslaw National Forest, Oregon, using lidar data: U.S. Geological Survey Open-File Report 2018–1035, 21 p., https://doi.org/10.3133/ofr20181035.","productDescription":"iv, 21 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-088393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":352857,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1035/ofr20181035.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1035"},{"id":352856,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1035/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Siuslaw National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.68383789062499,\n 41.9921602333763\n ],\n [\n -123.28857421875,\n 41.9921602333763\n ],\n [\n -123.28857421875,\n 45.62172169252446\n ],\n [\n -124.68383789062499,\n 45.62172169252446\n ],\n [\n -124.68383789062499,\n 41.9921602333763\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Few studies exist on the long-term geomorphic effects of floods. However, the U.S. Geological Survey (USGS) was able to begin such a study after a 50-year recurrence interval flood in 1978 because 20 channel cross sections along a 100-kilometer reach of river were established in 1975 and 1977 as part of a study for a proposed dam on Powder River in southeastern Montana. These cross-section measurements (data for each channel cross section are available at the USGS ScienceBase website) have been repeated about 30 times during four decades (1975–2016) and provide a unique dataset for understanding long-term changes in channel morphology caused by an extreme flood and a spectrum of annual floods.
Changes in channel morphology of a 100-kilometer reach of Powder River are documented in a series of narratives for each channel cross section that include a time series of photographs as a record of these changes. The primary change during the first decade (1975–85) was the rapid vertical growth of a new inset flood plain within the flood-widened channel. Changes during the second decade (1985–95) were characterized by slower growth of the flood plain, and the effects of ice-jam floods typical of a northward-flowing river. Changes during the third decade (1995–2005) showed little vertical growth of the inset flood plain, which had reached a height that limited overbank deposition. And changes during the final decade (2005–16) covered in this report showed that, because the new inset flood plain had reached a limiting height, the effects of the large annual flood of 2008 (largest flood since 1978) were relatively small compared to smaller floods in previous decades. Throughout these four decades, the riparian vegetation, which interacts with the river, has undergone a gradual but substantial change that may have lasting effects on the channel morphology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181012","usgsCitation":"Moody, J.A., and Meade, R.H., 2018, Decadal changes in channel morphology of a freely meandering river—Powder River, Montana, 1975–2016: U.S. Geological Survey Open-File Report 2018–1012, 143 p., https://doi.org/10.3133/ofr20181012.","productDescription":"Report: viii, 143 p.; Data Release","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090628","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":352547,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TQ5ZRN","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Channel Cross-section Data for Powder River between Moorhead and Broadus, Montana from 1975 to 2016"},{"id":352545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1012/coverthb2.jpg"},{"id":352546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1012/ofr20181012.pdf","text":"Report","size":"35.6 MB"}],"country":"United States","state":"Montana","otherGeospatial":"Powder River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.25,\n 45\n ],\n [\n -106,\n 45\n ],\n [\n -106,\n 45.5\n ],\n [\n -105.25,\n 45.5\n ],\n [\n -105.25,\n 45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"