The U.S. Geological Survey was asked by the Washington State Department of Transportation to provide technical assistance as a third-party reviewer of their stormwater effectiveness monitoring program during the transition between the completion of the 2014 Washington State Department of Ecology permit requirements and start of the new 2019 Washington State Department of Ecology permit requirements. For the purposes of this evaluation, the U.S. Geological Survey reviewed Washington State Department of Transportation’s 2014 National Pollution Discharge Elimination System permit. This review focuses on sections S7, S8, G9, and appendix 4 of the permit that are specific to monitoring. These sections cover the methods of monitoring, the constituents that were monitored, laboratory requirements, reporting requirements, and data archival. Next, all quality-assurance project plans for the 2014 general permit and annual reports required for the permit were reviewed. The quality-assurance project plans and annual reports were reviewed to ensure that monitoring was executed and reported as required by the 2014 general permit. The monitoring requirements put forth from the permits were fully addressed in quality-assurance project plans and were completed and presented in the annual monitoring reports. Overall, the Washington State Department of Transportation monitoring program does not change much under its new 2019 permit. The Washington State Department of Transportation has followed through with the plan set out in each of its approved quality-assurance project plans and therefore, is in a good position to meet or exceed the new permit requirements in the upcoming 5-year permit cycle.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201079","collaboration":"Prepared in cooperation with the Washington State Department of Transportation","usgsCitation":"Senter, C.A., and Sheibley, R.W., 2020, Evaluation of the Washington State Department of Transportation stormwater monitoring and effectiveness program for 2014–19: U.S. Geological Survey Open-File Report 2020–1079, 11 p., https://doi.org/10.3133/ofr20201079.","productDescription":"iv, 11 p.","onlineOnly":"Y","ipdsId":"IP-117873","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":376565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1079/ofr20201079.pdf","text":"Report","size":"394 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1079"},{"id":376564,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1079/coverthb.jpg"}],"contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The U.S. Geological Survey (USGS) is revising the Chesapeake Bay-based science plan to align it with recent U.S. Department of Interior and USGS science priorities that include, as stated in the plan, providing “an integrated understanding of the factors affecting fish habitat, fish health, and landscape conditions” in Chesapeake Bay and its watershed. A report of partner agencies’ needs and priorities related to aquatic invasive species (AIS) science was identified as an informational gap; a report would help to further development of the science program related to aquatic animal health and habitat. This objective was addressed through review of pertinent documentation and conversations with representatives of State, Federal, and regional agencies with vested interests in AIS management in Chesapeake Bay and the Chesapeake Bay drainage area, and this document was produced to summarize the related findings.
All agencies and organizations (13) reported that AIS are of general concern, with most stakeholder groups reporting AIS-related issues to be of high priority, including invasive fishes and invertebrates, invasive plants, and microbes including aquatic animal pathogens.
Science needs that were recurrently indicated by stakeholders to support management of invasive species include
Potential next steps to address the science needs include
Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
The greater San Francisco Bay estuary, prior to human intervention, encompassed about 2,200 km2 of tidal and salt marshes. Over time, these areas became increasingly diked, developed, and altered from their natural state. In addition, natural forces are always driving a continually shifting equilibrium.
This study area, the Corte Madera marshes, is a tidal marsh or wetland located in southeastern Marin County, and it borders an embayment of central San Francisco Bay along about 2.8 km of shoreline. Most of this shoreline is located within the Corte Madera Marsh Ecological Reserve, managed by the California Department of Fish and Wildlife. Other areas within the marsh include (1) unincorporated Greenbrae (at the boardwalk), (2) diked land (that is, isolated from tidal action) owned by the Golden Gate Bridge Highway and Transportation District, and (3) urbanized areas such as in the Mariner Cove subdivision of Corte Madera. The present tidal marsh area was historically subdivided into the following informally named tracts, listed from north to south: Heerdt marsh, north Muzzi marsh, inner and outer Muzzi marshes, Marta’s marsh, and Triangle marsh.
The purpose of this study is to derive the magnitudes and rates of shoreline change (both erosion and accretion) for the Corte Madera shoreline, with particular emphasis on the time period from 1931 to 2016. The rates of change are then related to different shoreline types (that is, natural or diked) and (or) locations on the shoreline.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201074","usgsCitation":"Carkin, Bradley A., Kayen, Robert E., and Wong, Florence L., 2020, Shoreline retreat of the Corte Madera marshes, 1853 to 2016, Marin County, California: U.S. Geological Survey Open-File Report 2020–1074, 36 p., 6 appendixes, https://doi.org/10.3133/ofr20201074.","productDescription":"vi, 36 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-105624","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":376367,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1074/covrthb.jpg"},{"id":376368,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1074/ofr20201074.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","county":"Marin County","otherGeospatial":"Corte Madera Marshes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.51970291137695,\n 37.92226366023669\n ],\n [\n -122.48828887939453,\n 37.92226366023669\n ],\n [\n -122.48828887939453,\n 37.95069515957716\n ],\n [\n -122.51970291137695,\n 37.95069515957716\n ],\n [\n -122.51970291137695,\n 37.92226366023669\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Managed and wild pollinators are critical components of agricultural and natural systems. Despite the well-known value of insect pollinators to U.S. agriculture, Apis mellifera (Linnaeus, 1758; honey bees) and wild bees currently face numerous stressors that have resulted in declining health. These declines have engendered support for pollinator conservation efforts across all levels of government, private businesses, and nongovernmental organizations. In 2014, the U.S. Department of Agriculture (USDA) and the U.S. Geological Survey initiated an interagency agreement to evaluate honey bee forage across multiple States in the northern Great Plains and upper Midwest. The long-term goal of this study was to provide an empirical evaluation of floral resources used by honey bees, and the relative contribution of multiple land covers and USDA conservation programs to bee health and productivity. Our multi-State analysis of land-use change from 2006 to 2016 revealed loss of grassland and increases in corn and soybean area in North and South Dakota, representing a significant loss of bee-friendly land covers in areas that support the highest density of summer bee yards in the entire United States. Our landscape models demonstrate the importance of the Conservation Reserve Program in providing safe locations for beekeepers to keep honey bees during the summer and highlights how land use in the northern Great Plains has a lasting effect on the health of honey bee colonies during almond pollination the subsequent spring. Our multiseason, multi-State genetic analysis of honey bee-collected pollen revealed Melilotus spp., Asteraceae, Trifolium spp., Fabaceae, Sonchus arvensis, Symphyotrichum cordifolium, and Solidago spp. were the top taxa detected; Melilotus spp. represented 42 percent of all detected taxa. Symphyotrichum cordifolium, Solidago spp., and Grindelia spp. were the top native forbs detected in honey bee-collected pollen. We also conducted plant and bee surveys on private lands enrolled in the Conservation Reserve Program and Environmental Quality Incentives Program. In general, we found significant variability in floral resources and pollinator utilization across USDA programs and practices. On average, greater than 75 percent of honey bee flower observations on private lands enrolled in a USDA conservation program were on non-native forbs, whereas 33 percent of wild bee flower observations were on non-native forbs. Melilotus officinalis and Medicago sativa were the most visited by honey bees, wherease Medicago sativa and Helianthus maximiliani were the most visited by wild bees. Our analysis of nectar dearth periods in June and September for honey bees revealed that although Melilotus officinalis and Medicago sativa were highly visited, less common native forb species such as Ratibida columnifera, Agastache foeniculum, and Gaillardia aristata were preferred species. However, these preferred species were relatively rare on the landscape and are, therefore, unlikely to make up a sizable part of the honey bee diet. In addition to our empirical results, we also showcase how the U.S. Geological Survey Pollinator Library, a decision-support tool for natural resource managers, can be used to design cost-effective seeding mixes for pollinators. Collectively, the results of this research will assist USDA with maximizing the ecological impact and cost-effectiveness of their conservation programs on pollinators in the northern Great Plains.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201037","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture","usgsCitation":"Otto, C.R.V., Smart, A., Cornman, R.S., Simanonok, M., and Iwanowicz, D.D., 2020, Forage and habitat for pollinators in the northern Great Plains—Implications for U.S. Department of Agriculture conservation programs: U.S. Geological Survey Open-File Report 2020–1037, 64 p., https://doi.org/10.3133/ofr20201037.","productDescription":"Report: ix, 64 p.; Data Releases","numberOfPages":"78","onlineOnly":"N","ipdsId":"IP-114029","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science 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\"}}]}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Recovery of salmon populations in the upper Cowlitz River Basin depends on trap-and-haul efforts owing to impassable dams. Therefore, successful recovery depends on the collection of out-migrating juvenile salmon at Cowlitz Falls Dam (CFD) for transport below downstream dams, as well as the collection of adults for transport upstream from the dams. Tacoma Power began downstream fish collection efforts at CFD in the mid-1990s and has been working consistently since then to improve collection efficiency to support self-sustaining salmon and steelhead (Onchorhynchus spp.) populations in the upper Cowlitz River Basin. Although much work has focused on estimating fish collection efficiency (FCE), there has been relatively little focus on modeling population dynamics to understand how fish collection efficiency and other factors drive production of both juvenile and adult salmon over their life cycle. As a first step towards understanding the factors affecting population dynamics of Oncorhynchus kisutch (coho salmon) in the upper Cowlitz River Basin, we developed a statistical life cycle model using adult escapement and age structure data, juvenile collection data, and juvenile fish collection efficiency estimates. The goal of the statistical life cycle model is to estimate annual production and survival during two critical life-stage transitions: the freshwater production from escapement of adults upstream from CFD to collection of juveniles at CFD, and the juvenile-to-adult survival from the time of collection at the dam to the return of adults. To structure the life cycle model, we used the Ricker stock-recruitment model to estimate juvenile production from the number of parent spawners. This approach allowed us to account for density dependence at high spawner abundances while estimating annual productivity, defined as the number of juveniles produced per spawner at low spawner abundance. We then expressed productivity as a function two key variables affecting the number of juveniles collected and transported at CFD: (1) annual FCE, and (2) the annual number of days that spill occurred at CFD from September 1 to April 30.
Our key findings were as follows:
Additionally, by including FCE in the model, we estimated that the median pre-collection productivity, defined as the number of juveniles produced per spawner when FCE=1, was 108.4 juveniles per spawner. Because this two-stage life cycle model partitions factors that affect fish production in river compared to the ocean environment and fish life stages, the model estimates should help inform fishery managers about the overall role that fish collection at CFD may have on the recovery and sustainability of coho salmon populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201068","collaboration":"Prepared in cooperation with Tacoma Power","usgsCitation":"Plumb, J.M., and Perry, R.W., 2020, Development of a two-stage life cycle model for Oncorhynchus kisutch (coho salmon) in the upper Cowlitz River Basin, Washington: U.S. Geological Survey Open-File Report 2020–1068, 25 p., https://doi.org/10.3133/ofr20201068.","productDescription":"iv, 25 p.","onlineOnly":"Y","ipdsId":"IP-117483","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":376162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1068/coverthb.jpg"},{"id":376163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1068/ofr20201068.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1068"}],"country":"United States","state":"Washington","otherGeospatial":"Cowlitz River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.97821044921875,\n 46.09228143052647\n ],\n [\n -121.8548583984375,\n 46.09228143052647\n ],\n [\n -121.8548583984375,\n 46.70596917928676\n ],\n [\n -122.97821044921875,\n 46.70596917928676\n ],\n [\n -122.97821044921875,\n 46.09228143052647\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The U.S. Army Corps of Engineers, Jacksonville District, plans to deepen the St. Johns River channel in Jacksonville, Florida, from 40 to 47 feet along 13 miles of the river channel, beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries.
This is the third annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project and contains information pertinent to the data collection during the 2018 water year, from October 2017 to September 2018. Changes to the network on the main stem of the St. Johns River include the addition of (1) three new stations to monitor water temperature and salinity at Racy Point, Shands Bridge, and above Buckman Bridge; (2) stage data collection at both Buckman Bridge and Dames Point Bridge; and (3) three additional parameters, namely stage, velocity, and streamflow direction, to the St. Johns River at Jacksonville and Dames Point Bridge.
Discharge and salinity varied widely during the data collection period, which included residual effects from Hurricane Irma in September 2017 and above-average rainfall for all counties in the project area over the 4-month period from April to July. The annual mean discharge at Durbin Creek was greatest among the tributaries, followed by annual mean discharges at Ortega River, Trout River, Cedar River, Julington Creek, Clapboard Creek, Broward River, Pottsburg Creek, and Dunn Creek. The annual mean discharge for each of the main-stem sites was higher in the 2018 water year than that of the previous 2 years of this study. Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and lowest at Durbin Creek and Ortega River, the sites farthest from the ocean. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which is expected. Relative to annual mean salinity calculated since the 2016 water year, annual mean salinity at all monitoring locations was lower for the 2018 water year, except for Durbin Creek, which was the same.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201061","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2020, Continuous stream discharge, salinity, and associated data collected in the Lower St. Johns River and its tributaries, Florida, 2018: U.S. Geological Survey Open-File Report 2020–1061, 34 p., https://doi.org/10.3133/ofr20201061.","productDescription":"viii, 34 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-107711","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":375991,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1061/coverthb.jpg"},{"id":375992,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1061/ofr20201061.pdf","text":"Report","size":"25.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1061"}],"country":"United States","state":"Florida","otherGeospatial":"Lower St. Johns River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.947021484375,\n 29.504159065872624\n ],\n [\n -81.00769042968749,\n 29.504159065872624\n ],\n [\n -81.00769042968749,\n 30.488917676126846\n ],\n [\n -81.947021484375,\n 30.488917676126846\n ],\n [\n -81.947021484375,\n 29.504159065872624\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Tribal communities may benefit from land management activities that enhance their use of resources on tribal lands. The Bureau of Indian Affairs is implementing a 5-year vegetation management program to provide support for projects that develop and use natural and cultural resources and improve opportunities for agricultural activities to benefit 20 Indian Tribes and Nations in the Eastern Oklahoma Region of the Bureau of Indian Affairs. The bureau is working with individual Tribes to identify project objectives and design treatments, which include prescribed burning, timber removal, thinning, and reduction of hazardous fuels. The total action area for the vegetation management program is estimated to be 236,575 acres, representing approximately 1 percent of the region.
A biological assessment was prepared, in cooperation with the bureau and U.S. Fish and Wildlife Service, to evaluate the potential effects of the proposed vegetation management program on 22 federally threatened, endangered, and candidate species that may occur within the Eastern Oklahoma Region. The species evaluated included one plant, two insects, one reptile, five fresh-water mussels, four fishes, five birds, and four bats. Because the proposed treatments will be largely restricted to terrestrial systems, it is expected that there will be no adverse effects on the 15 species associated with aquatic habitats, provided that best management practices are followed. The proposed treatments may affect but are unlikely to adversely affect six of the primarily terrestrial species (the Papaipema eryngii [rattlesnake master borer], Picoides borealis [red-cockaded woodpecker], Myotis grisescens [gray bat], Myotis sodalis [Indiana bat], Myotis septentrionalis [northern long-eared bat], and Corynorhinus townsendii ingens [Ozark big-eared bat]), provided that best management practices are followed, including avoidance of critical habitat features.
The only species likely to be adversely affected by the proposed treatments is Nicrophorus americanus (American burying beetle) as a consequence of short-term disturbances to soils and vegetation. Most adverse effects of the treatments (such as soil compaction and decreased cover in the forest understory) are expected to be short term (habitat will recover or be restored within 5 years of treatments). Less than 1 percent of the action area is expected to result in long-term adverse effects to the American burying beetle as a result of permanent cover changes that persist for more than 5 years. It is expected that the primary treatments will be largely beneficial to the American burying beetle population in the region by reducing the risk of high-severity fires and expansion of invasive woody shrubs, such as Juniperus virginiana (eastern redcedar) within potential beetle habitat and the surrounding landscape. Overall, the proposed management program is expected to provide long-term benefits to American burying beetle habitat across 91 percent of the action area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20201013","collaboration":"Prepared in cooperation with the Bureau of Indian Affairs and U.S. Fish and Wildlife Service","usgsCitation":"Harms, B.R., Bencin, H.L., and Carr, N.B., 2020, Biological assessment of a proposed vegetation management program to benefit Tribes in eastern Oklahoma: U.S. Geological Survey Open-File Report 2020–1013, 49 p., \nhttps://doi.org/10.3133/ofr20201013.","productDescription":"Report: vi, 49 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-111270","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":376079,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95LDGHX","text":"USGS data release","linkHelpText":"Estimated habitat suitability for the American burying beetle using land cover classes in the Southern Plains (ver. 1.1, June 2020)"},{"id":376078,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1013/ofr20201013.pdf","text":"Report","size":"2.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1013"},{"id":376077,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1013/coverthb.jpg"},{"id":384231,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1013/versionHist.txt","text":"version history","size":"9.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2020-1013 version history"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.6142578125,\n 36.99377838872517\n ],\n [\n -96.844482421875,\n 36.98500309285596\n ],\n [\n -96.92138671875,\n 36.61552763134925\n ],\n [\n -97.00927734375,\n 36.421282443649496\n ],\n [\n -96.064453125,\n 36.13787471840729\n ],\n [\n -96.52587890625,\n 35.951329861522666\n ],\n [\n -96.88842773437499,\n 35.7019167328534\n ],\n [\n -97.14111328125,\n 34.939985151560435\n ],\n [\n -97.789306640625,\n 35.27253175660236\n ],\n [\n -98.031005859375,\n 35.28150065789119\n ],\n [\n -98.0859375,\n 34.161818161230386\n ],\n [\n -97.9541015625,\n 33.86129311351553\n ],\n [\n -97.591552734375,\n 34.016241889667015\n ],\n [\n -97.305908203125,\n 33.78827853625996\n ],\n [\n -97.108154296875,\n 33.897777013859475\n ],\n [\n -96.99829101562499,\n 33.73347670599252\n ],\n [\n -96.45996093749999,\n 33.715201644740844\n ],\n [\n -95.712890625,\n 33.87041555094183\n ],\n [\n -95.284423828125,\n 33.86129311351553\n ],\n [\n -95.11962890625,\n 33.93424531117312\n ],\n [\n -94.449462890625,\n 33.61461929233378\n ],\n [\n -94.449462890625,\n 35.38904996691167\n ],\n [\n -94.6142578125,\n 36.99377838872517\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 10 projects funded in fiscal year 2018, outlining their goals, activities, and accomplishments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201062","usgsCitation":"Hsu, L., Andrews, C.M., Bradford, J.B., Buscombe, D.D., Chase, K.J., Daniel, W.M., Jones, J.M., Fuller, P., Mirus, B.B., Neilson, M.E., Vraga, H.W., Walker, J.J., Walworth, D.H., Warrick, J., Weltzin, J., Wieferich, D.J., and Wood, N.J., 2020, Community for Data Integration 2018 funded project report: U.S. Geological Survey Open-File Report 1062, 9 p., https://doi.org/10.3133/ofr20201062.","productDescription":"iv, 9 p.","onlineOnly":"Y","ipdsId":"IP-119025","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":375990,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1062/ofr20201062.pdf","text":"Report","size":"4.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1062"},{"id":375989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1062/coverthb.jpg"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
108 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The second U.S. Department of the Interior (DOI) Economics Training Workshop (hereafter “Workshop”) was held during September 25–27, 2018, in Washington, D.C., to identify, highlight, and better understand needs and opportunities for economic analysis to support DOI’s mission. Building on the first workshop in 2017, the second Workshop, jointly convened by the DOI Office of Policy Analysis and the U.S. Geological Survey (USGS) Science and Decisions Center, provided an opportunity for DOI economists to share expertise and experiences and to build collaboration and communication channels across DOI. In addition, the second Workshop provided training sessions on a variety of relevant economic and modeling topics. More than 40 DOI economists gathered at the Workshop to share their work, discuss shared challenges, and identify approaches to advance the use and contribution of economics at the DOI.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201044","collaboration":"Prepared in cooperation with the U.S. Department of the Interior Office of Policy Analysis","usgsCitation":"Alhassan, M., Pindilli, E.J., Crowley, C.S.L., Shapiro, C.D., and Simon, B.M., 2020, Supporting natural resource-management decisions—The role of economics at the U.S. Department of the Interior (DOI)—2018 DOI Economics Training Workshop: U.S. Geological Survey Open-File Report 2020–1044, 26 p., https://doi.org/10.3133/ofr20201044.","productDescription":"iv, 26 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112653","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":375485,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181054","text":"Open-File Report 2018-1054","linkHelpText":"- Supporting natural resource management—The role of economics at the Department of the Interior—A workshop report"},{"id":375947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1044/ofr20201044.pdf","text":"Report","size":"6.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":375483,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1044/coverthb.jpg"}],"contact":"Director, Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
To understand the behavior of potentially damaging ground motions during earthquakes, seismic-site effects are routinely characterized by using the dispersion of surface waves. Many methods exist to measure dispersion; these methods have various advantages and disadvantages, but they all yield dispersion data that must be inverted for shear-wave velocity. This report presents a graphical tool for efficiently removing spurious data as well as combining data from multiple methods prior to inversion.
The Dispersion Plot Editor (DPE) program presented here (version 1.5) is coded in Python 3, which is open source and platform independent. DPE accepts input dispersion data as one or more delimited text files. The program plots the data in useful forms, including both scattered points and an interpolated heat map. The user selects points to delete by drawing arbitrary shapes with the mouse cursor. After the spurious data are removed, the user may represent the acceptable data with a dispersion curve. The acceptable data and the representative dispersion curve are output as separate comma-delimited text files. Images of the plotted data and the representative dispersion curve may also be saved.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201065","usgsCitation":"McPhillips, D., Yong, A.K., Martin, A., and Stephenson, W.J., 2020, Graphical Dispersion Plot Editor (DPE) for seismic-site characterization by using multiple surface-wave methods: U.S. Geological Survey Open-File Report 2020–1065, 8 p., https://doi.org/10.3133/ofr20201065.","productDescription":"Report: iii, 8 p.; Appendix","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-113656","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":375790,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1065/coverthb.jpg"},{"id":375791,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1065/ofr20201065.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":375792,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1065/ofr20201065_appendix.zip","size":"110 KB","linkFileType":{"id":6,"text":"zip"}}],"contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Road
Moffett Field, CA 94035
Authorization of lease sales for oil development in the 1002 Area of the Arctic National Wildlife Refuge has highlighted gaps in information about biological communities in the area. The U.S. Fish and Wildlife Service, which is planning a study to evaluate spatial variation in the nest survival of tundra-breeding shorebirds to identify hotspots with high nest survival, sought advice from the U.S. Geological Survey on how to predict which sampling designs might be successful in achieving the study goals. I used previously obtained data on nest survival from Alaska’s North Slope to develop a simulation study that explored the statistical consequences of various sampling designs in the context of expected ranges of values of biological parameters. Of all sampling parameters, the number of nests per plot had the strongest influence on the ability to detect hotspots, followed by number of years of monitoring and the age at which nests were found. The benefit of sampling 98 plots instead of 68 was relatively small. Ages of nests cannot be predicted a priori, so I developed a field reference chart to identify when further nest-searching would be useful for a given plot. This simulation study used the best available information, but values of biological parameters will become better defined following subsequent data collection in the 1002 Area. Data from upcoming field seasons could be used to refine this analysis and improve estimation of the expected results of the field study, thus maximizing the likelihood that data from the 1002 Area nest survival study will meet the monitoring goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201066","collaboration":"U.S. Geological Survey Wildlife Program","usgsCitation":"Weiser, E., 2020, Sample-size considerations for a study of shorebird nest survival in the 1002 Area, Arctic National Wildlife Refuge, Alaska: U.S. Geological Survey Open-File Report 2020–1066, 18 p., https://doi.org/10.3133/ofr20201066","productDescription":"iv, 18 p.","onlineOnly":"Y","ipdsId":"IP-116976","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":375788,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1066/coverthb.jpg"},{"id":375789,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1066/ofr20201066.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1066"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.6318359375,\n 68.56038368664157\n ],\n [\n -141.1083984375,\n 68.56038368664157\n ],\n [\n -141.1083984375,\n 71.81512993041657\n ],\n [\n -157.6318359375,\n 71.81512993041657\n ],\n [\n -157.6318359375,\n 68.56038368664157\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Water, bed sediment, and invertebrate tissue were sampled in streams from Butte to near Missoula, Montana, as part of a monitoring program in the Clark Fork Basin. The sampling program was completed by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to characterize aquatic resources in the Clark Fork Basin and monitor trace elements associated with historical mining and smelting activities. Sampling sites were on the river and tributaries of the Clark Fork. Water samples were collected periodically at 20 sites from October 2017 through September 2018. Bed-sediment and tissue samples were collected once at 13 sites during August 2018.
Water-quality data included concentrations of major ions, dissolved organic carbon, nitrogen (nitrate plus nitrite), trace elements, and suspended sediment. Daily values of turbidity were determined at four sites. Bed-sediment data included trace-element concentrations in the fine-grained (less than 0.063 millimeter) fraction. Biological data included trace-element concentrations in whole-body tissue of aquatic benthic invertebrates. Statistical summaries of water-quality, bed-sediment, and invertebrate tissue trace element data for sites in the Clark Fork Basin were provided for the period of record: March 1985–September 2018.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201067","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Clark, G.D., Hornberger, M.I., Cleasby, T.E., Heinert, T.L., and Turner, M.A., 2020, Water-quality, bed-sediment, and invertebrate tissue trace-element concentrations for tributaries in the Clark Fork Basin, Montana, October 2017–September 2018: U.S. Geological Survey Open-File Report 2020–1067, 16 p., https://doi.org/10.3133/ofr20201067.","productDescription":"Report: vi, 16 p.; Data Release; Dataset","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-115189","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":375701,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98IRLJF","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-quality, bed-sediment, and invertebrate tissue trace element concentrations for tributaries in the Clark Fork Basin, Montana, October 2017–September 2018"},{"id":375700,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1067/ofr20201067.pdf","text":"Report","size":"1.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1067"},{"id":375699,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1067/coverthb.jpg"},{"id":375702,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System","description":"NWIS","linkHelpText":"— USGS Water Data for the Nation"}],"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 -114.345703125,\n 45.24395342262324\n ],\n [\n -111.181640625,\n 45.24395342262324\n ],\n [\n -111.181640625,\n 47.264320080254805\n ],\n [\n -114.345703125,\n 47.264320080254805\n ],\n [\n -114.345703125,\n 45.24395342262324\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Boseman Avenue
Helena, MT 59601
Access to bathymetry and geomorphology data for rivers and reservoirs is a critical need in multiple agencies and academia. These data are needed to make water-resource-management decisions regarding river restoration, resource protection, infrastructure design and sustainability, and flood-risk reduction, and during natural disasters. Sharing of data increases decision-making capacity by incorporating information from entire watersheds, provides knowledge from similar settings being managed or studied by other entities, and helps meet the goals of the Federal Open Water Data Initiative. Addressing these needs across broad spatial and temporal scales would be made more efficient if these data were available in consistent formats with standardized metadata and were either stored in a centralized database or integrated with existing geospatial datasets. Because of renewed interest and technological advances, representatives from multiple Federal agencies and academic institutions have created a new working group to scope the development of a Geomorphology Data Exchange Portal to increase access to needed data. The working group has developed a vision for the Portal and outlined possible approaches to achieve the vision. Short-term approaches may include leveraging existing data-access portals and data-processing tools and integrating geomorphology data with existing national geospatial datasets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201056","collaboration":"USGS Water Observing Systems ProgramOffice of Associate Director, Water
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir (hereinafter Clear Lake), California, are experiencing long-term decreases in abundance. Upper Klamath Lake populations are decreasing not only because of adult mortality, which is relatively low, but also because they are not being balanced by recruitment of young adult suckers into known adult spawning aggregations.
Long-term monitoring of juvenile sucker populations is conducted to (1) determine if there are annual and species-specific differences in production, survival, and growth; (2) better understand when juvenile sucker mortality is greatest, and (3) help identify potential causes of high juvenile sucker mortality, particularly in Upper Klamath Lake. The U.S. Geological Survey monitoring program, which began in 2015, tracks cohorts through summer months and among years in Upper Klamath and Clear Lakes. Data on juvenile suckers captured in trap nets are used to provide information on annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, apparent growth, species composition, and health.
Juvenile sucker year-class strength and apparent survival were low in 2018 in Upper Klamath Lake. Most juvenile sucker mortality occurs within the first year of life. The Upper Klamath Lake year-class strength indices for Lost River and shortnose suckers in 2018 were the lowest they had been since the start of monitoring in 2015. The annual catch rates of shortnose sucker remained consistently low, whereas Lost River sucker catch rates varied. The capture of only four age-1 and older suckers from Upper Klamath Lake during the 2018 sampling season indicated low annual survival of the 2017 cohort.
Annual production indices of juvenile suckers in Clear Lake are highly variable and potentially affected by seasonal connections to spawning habitat in Willow Creek. A total of seven age-0 shortnose or Klamath largescale suckers (Catostomus snyderi) were captured from Clear Lake in 2018, which was a relatively wet year, indicating that a small cohort was formed or that there was a delay in the recruitment of age-0 suckers. The 2018 sampling continued to detect recruitment of juveniles from the 2015 cohort to the lake. Given the dysconnectivity between Willow Creek and Clear Lake during the 2015 spawning season, the continued recruitment of young fish of this cohort to the lake may be attributed to reproduction by resident suckers in Willow Creek. Suckers younger than age-3 in Clear Lake could be identified as either shortnose or Klamath largescale suckers. A stream resident life history, if it were occurring, is consistent with these fish being Klamath largescale suckers. Survival of all distinguishable taxa of juvenile suckers is much higher in Clear Lake than in Upper Klamath Lake, with non-trivial numbers of suckers surviving to join spawning aggregations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201064","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Bart, R.J., Burdick, S.M., Hoy, M.S., and Ostberg, C.O., 2020, Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 monitoring report: U.S. Geological Survey Open-File Report 2020–1064, 33 p., https://doi.org/10.3133/ofr20201064.","productDescription":"vi, 33 p.","onlineOnly":"Y","ipdsId":"IP-116680","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":375530,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1064/ofr20201064.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1064"},{"id":375529,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1064/coverthb.jpg"}],"country":"United States","state":"California, Oregon","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 -121.25747680664064,\n 41.789744876718984\n ],\n [\n -121.04324340820312,\n 41.789744876718984\n ],\n [\n -121.04324340820312,\n 41.94519164538106\n ],\n [\n -121.25747680664064,\n 41.94519164538106\n ],\n [\n -121.25747680664064,\n 41.789744876718984\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1075439453125,\n 42.224449701009725\n ],\n [\n -121.76834106445311,\n 42.224449701009725\n ],\n [\n -121.76834106445311,\n 42.593532625649935\n ],\n [\n -122.1075439453125,\n 42.593532625649935\n ],\n [\n -122.1075439453125,\n 42.224449701009725\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Groundwater-level conditions, generalized groundwater potentiometric surfaces, and generalized flow directions at the decommissioned Naval Air Warfare Center in West Trenton, New Jersey, were evaluated for calendar year 2018. Groundwater levels measured continuously in five on-site wells and one nearby off-site well were plotted as hydrographs for January 1, 2018, through December 31, 2018. Groundwater levels measured in 110 wells on June 18, 2018, were contoured as generalized potentiometric surfaces on maps and sections. Generalized groundwater-flow directions inferred from the June 2018 data are shown in the maps and sections.
Groundwater levels in six monitoring wells fluctuated in response to seasonal changes, precipitation, and pumping from “pump-and-treat” (P&T) wells. Record high precipitation totals in November, combined with a shutdown of three P&T wells in November, resulted in annual high water levels in late November for five of the six wells monitored. Annual high groundwater levels that occur during the fall are uncharacteristic of the typical timing of annual high water levels, which usually occur in the spring following low evapotranspiration during the winter months, compared to annual low water levels, which usually occur in fall because of high evapotranspiration during the summer months. The annual high water levels occurred following a 3-day precipitation event totaling 3.50 inches from November 24-26, which also caused the largest 1-day water-level increase for five of the six wells in 2018.
The groundwater-level contour maps and sections include generalized flow directions. Given the heterogeneity of the site’s fractured rock aquifers, contours and associated groundwater-flow directions shown on the maps and sections should be considered as broad conceptualizations. A nearly vertical fault striking southwest to northeast separates the northwestern part of the site underlain by the Lockatong Formation from the southeastern part, which is underlain by the Stockton Formation. In the Lockatong Formation, general groundwater-flow directions were toward P&T wells. The P&T wells limited the flow of groundwater in the Lockatong Formation from the site into the adjacent areas and contained most groundwater contamination within the site. A groundwater divide bisected the site; groundwater in the western part generally flowed to P&T wells 8BR, 15BR, 20BR, 29BR, 56BR, 91BR, and BRP-2, and groundwater in the eastern part generally flowed to P&T well 48BR. A groundwater divide also was present in the Stockton Formation. Groundwater west of the divide in the Stockton Formation generally flowed toward P&T well 22BR, and groundwater east of the divide generally flowed south and southeast, away from the site. Saprolite and fill from land surface to depths of 25 feet below land surface exhibit similar properties to those of porous media, and water levels in surficial wells were contoured using a porous media aquifer approach. Water levels in these surficial wells indicate that groundwater in the saprolite and fill flowed predominantly toward Gold Run and, to a lesser extent, the West Ditch spring that drains to Gold Run. In addition, some shallow groundwater was captured by the cone of depression in the fractured bedrock and was attributed to P&T well 48BR.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201016","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Fiore, A.R., and Lacombe, P.J., 2020, Groundwater levels and generalized potentiometric surfaces, former Naval Air Warfare Center, West Trenton, New Jersey, 2018: U.S. Geological Survey Open-File Report 2020–1016, 28 p., https://doi.org/10.3133/ofr20201016.","productDescription":"Report: v, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-104199","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":375290,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1016/ofr20201016.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1016"},{"id":375285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1016/coverthb.jpg"},{"id":375288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98N1GWV","text":"USGS data release","linkHelpText":"Reported groundwater levels and groundwater pump-and-treat withdrawals, former Naval Air Warfare Center, West Trenton, New Jersey, 2018"}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"Former Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81613278388977,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.26694411855267\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Native steelhead (anadromous form of rainbow trout [Oncorhynchus mykiss]) and bridgelip sucker (Catostomus columbianus) were historically used by the Kah-miltpah (Rock Creek) Band for sustenance, trade, and traditional practices in Rock Creek, a tributary to the Columbia River in southeastern Washington State. Rock Creek flows south to the Columbia River at river kilometer (rkm) 368 and is an intermittent stream of great significance to the Yakama Nation and to the Kah-miltpah Band in particular. Concern over declines in the abundance of these fish in Rock Creek prompted a research and monitoring program to better understand habitat conditions, population status, and limiting factors. In addition to steelhead and bridgelip sucker, coho salmon (Oncorhynchus kisutch) and resident rainbow trout are also present and monitored. Rainbow trout and steelhead will be collectively referred to as O. mykiss. Streamflow is a limiting habitat factor in this system, but steelhead and coho salmon still successfully return to spawn, rear, outmigrate, and survive over summer in many of the isolated pools that provide important refuge for juvenile rearing.
We completed a habitat survey during autumn 2018 to assess the perennial pools during low-flow conditions. In Rock Creek, the overall percentage of habitat recorded as dry was 41, non-pool wet was 42, and pool was 17. The number of pools (n=93) recorded was less than during previous years’ survey efforts (2015–17). The percentage of non-pool wet habitat was generally higher in 2018 than in previous years. This is a likely result of habitat reaches, which in the past, were considered pools but have become shallower and smaller and are now categorized as non-pool wet habitat. However, the fewer habitat reaches categorized as pools in 2018 now have an average length, area, and depth that are generally greater than in past years. In Walaluuks Creek, the percentage of habitat recorded as dry was 53, non-pool wet was 40, and pool was 7. The percentage of pool habitat was the lowest of all years surveyed since 2015.
Fish sampling occurred during autumn after habitat surveys were completed from October 1 to November 9. Fish species distribution, relative abundance, length-frequency distribution, and pool fish density were determined using backpack electrofishing in stratified, systematically selected pools. During fish sampling, 855 O. mykiss were handled and 662 were tagged with a passive integrated transponder (PIT) tag, and 718 coho salmon were handled and 567 were PIT tagged. A total of 536 bridgelip suckers and largescale suckers (Catostomus macrocheilus [n=6]) were handled and 294 were PIT tagged. In Rock Creek, pool abundance estimates were calculated for six pools for both O. mykiss age classes (age 0 and age 1 or older [age 1+]) and one additional pool for age 1+. For pools where age-0 O. mykiss were present, the average pool population abundance was 0.144 (n=6; range: 0.052–0.208) fish per square meter. For age-1+ O. mykiss, the average pool population abundance was 0.045 (n=7; range: 0.002–0.179) fish per square meter. For age-0 O. mykiss in Walaluuks Creek, the average pool abundance was 0.207 fish per square meter (n=7; range: 0.038–0.416), and for age-1+ fish, the average pool abundance was 0.382 fish per square meter (n=6; range: 0.009–0.761). In Rock Creek, coho salmon were more abundant than O. mykiss in pools except for three pools upstream from rkm 20. The average pool abundance for coho salmon was 0.256 fish per square meter (n=8; range: 0.019–0.756) in Rock Creek pools. In Walaluuks Creek, coho salmon were captured in four pools and were not captured in the upstream pools sampled. The average pool abundance for coho salmon in the four lower pools was 0.488 fish per square meter (n=4; range: 0.417–0.548). Bridgelip suckers were captured in all pools in Rock Creek except the pool sampled at rkm 21.8. The average pool abundance for bridgelip suckers was 0.552 fish per square meter (n=7; range: 0.015–1.554) in Rock Creek. Bridgelip suckers were captured in three downstream pools in Walaluuks Creek, and the average abundance was 0.044 fish per square meter (n=3; range: 0.024–0.085).
Overwinter and reach survival probabilities were estimated for O. mykiss and coho salmon using a Cormack-Jolly-Seber modeling approach. The best fit survival model for the O. mykiss and coho salmon was a reach only model. The upstream reach includes overwinter survival probability because fish are tagged and released in autumn and primarily migrate the following spring. During 2018, coho salmon (0.568, standard error [SE]=0.027) had a significantly higher probability of overwinter survival than O. mykiss (0.276, SE=0.019). The reach survival probability was higher for O. mykiss than coho salmon in the downstream migratory reaches. Survival was not modeled for bridgelip suckers. For bridgelip suckers, 147 were detected of 294, that were PIT tagged and released in the Rock Creek subbasin (50.0 percent).
Information provided in this report increases our understanding of the status and trends of these populations. It further documents how intermittent streams can support salmonid populations. It also provides insight into potential management and restoration actions that could be beneficial and timing and allocation of resources. Ongoing monitoring work of this population will inform progress towards Rock Creek species recovery goals and contribution to recovery goals for the steelhead Middle Columbia River Distinct Population Segment.
Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Cape May and Supawna Meadows National Wildlife Refuges in New Jersey. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 13 marsh management units within the refuges and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $785,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $785,000 included applying sediment to the marsh surface (thin layer deposition) in seven marsh management units, controlling the invasive reed Phragmites australis in four marsh management units, remediating hydrologic alterations in two marsh management units, and planting native vegetation in one marsh management unit. The management benefits were derived from expected improvements in the capacity for marsh elevation to keep pace with sea-level rise, increases in numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds, and increased cover of native vegetation. The prototype presented here provides a framework for decision making at the Cape May and Supawna Meadows National Wildlife Refuges that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201055","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Braudis, B., and Hanlon, H., 2020, Optimization of tidal marsh management at the Cape May and Supawna Meadows National Wildlife Refuges, New Jersey, through use of structured decision making: U.S. Geological Survey Open-File Report 2020–1055, 41 p., https://doi.org/10.3133/ofr20201055.","productDescription":"vii, 41 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101980","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":375304,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1055/ofr20201055.pdf","text":"Report","size":"3.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1055"},{"id":375303,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1055/coverthb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Cape May, Supawna Meadows National Wildlife Refuges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.377197265625,\n 39.690280594818034\n ],\n [\n -75.1025390625,\n 39.95185892663005\n ],\n [\n -75.41015624999999,\n 39.9602803542957\n ],\n [\n -75.618896484375,\n 39.58029027440865\n ],\n [\n -75.3662109375,\n 39.2407625100131\n ],\n [\n -75.0146484375,\n 38.788345355085625\n ],\n [\n -74.42138671875,\n 39.07037913108751\n ],\n [\n -74.410400390625,\n 39.605688178320804\n ],\n [\n -74.77294921875,\n 39.36827914916014\n ],\n [\n -75.16845703124999,\n 39.40224434029275\n ],\n [\n -75.377197265625,\n 39.690280594818034\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708–4039
This report provides an overview of model-based climate science in a risk management context. In addition, it summarizes how the U.S. Geological Survey (USGS) will continue to follow best scientific practices and when and how the results of this research will be delivered to the U.S. Department of the Interior (DOI) and other stakeholders to inform policymaking. Climate change is a risk management challenge for society because of the uncertain consequences for natural and human systems across decades to centuries. Climate-related science activities within the USGS emphasize research on adaptation to climate change. This research helps inform adaptive management processes and planning activities within other DOI bureaus and by DOI stakeholders.
Global climate models are sophisticated numerical representations of the Earth’s climate system. Research groups from around the world regularly participate in a coordinated effort to produce a suite of climate models. This global effort provides a test bed to assess model performance and analyze projections of future change under various prescribed climate scenarios. These climate scenarios describe a plausible future outcome associated with a specific set of societal actions. Because scenarios are developed in a risk-based framework with a high degree of uncertainty about future societal developments, they are usually not assigned a formal likelihood of occurrence. Examining a range of projected climate outcomes based on multiple scenarios is a recommended best practice because it allows decision makers to better consider both short- and long-term risks and opportunities.
As part of its routine science practices, the USGS regularly reviews the state of knowledge of climate science, develops and maintains best practices in using global climate models to project climate change impacts, and provides data and interpretations of potential impacts to the DOI and other stakeholders. Management and policy decisions within the DOI will reflect different tolerances for risk, which has implications for what type of information should be considered and how that information should be used. It is suggested that a followup document be produced that would describe in more detail how these management decisions with differing risk tolerances can be made effectively and consistently in light of an uncertain future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201058","usgsCitation":"Terando, A., Reidmiller, D., Hostetler, S.W., Littell, J.S., Beard, T.D., Jr., Weiskopf, S.R., Belnap, J., and Plumlee, G.S., 2020, Using information from global climate models to inform policymaking—The role of the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2020–1058, 25 p., https://doi.org/10.3133/ofr20201058.","productDescription":"v, 25 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118715","costCenters":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"links":[{"id":375144,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1058/coverthb.jpg"},{"id":375198,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1058/ofr20201058.pdf","text":"Report","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1058"}],"contact":"National Climate Adaptation Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Mail Stop 516
Reston, VA 20192
https://www.usgs.gov/land-resources/
climate-adaptation-science-centers
The novel β-coronavirus, SARS-CoV-2, may pose a threat to North American bat populations if bats are exposed to the virus through interaction with humans, if the virus can subsequently infect bats and be transmitted among them, and if the virus causes morbidity or mortality in bats. Further, if SARS-CoV-2 became established in bat populations, it could possibly serve as a source for new infection in humans, domesticated animals, or other wild animals. Wildlife management agencies in the United States are concerned about these potential risks and have begun to issue guidance regarding work that brings humans into contact with bats, but decision making is difficult because of the high degree of uncertainty about many of the relevant processes that could lead to virus transmission and establishment. The risk assessment described in this report was undertaken to provide management agencies with an understanding of the likelihood that the various steps in the causal pathways would lead to SARS-CoV-2 infection of North American bats from people. This assessment focused on the active season for bats in the temperate zone of North America (April 15 through November 15), and used Myotis lucifugus (little brown bats) as a surrogate species. At the time of this work (April 2020), no empirical data about the effects of SARS-CoV-2 on North American bats were available, so a formal process of expert judgment was used to elicit estimates of the underlying parameters. Twelve experts in bat ecology, epidemiology, virology, and wildlife disease from the United States, United Kingdom, and Australia participated in the elicitation. A Monte Carlo simulation model was used to integrate the parameter estimates elicited from the experts and to predict the likelihood of exposure and infection in bats through a series of transmission pathways, with particular attention to capturing uncertainty in the predictions.
Given the current state of knowledge as expressed by the expert panel, the results of this assessment indicate that there is a non-negligible risk of transmission of SARS-CoV-2 from humans to bats. For example, if a research scientist were shedding SARS-CoV-2 virus while handling bats under the field protocols used in North America prior to the COVID-19 pandemic, the risk model indicates that 50 percent (uncertainty, 15–84 percent) of those bats could be exposed to virus, and 17 percent (uncertainty, 3–51 percent) could become infected. Use of personal protective equipment, especially a respirator, is expected to reduce the exposure risk. The expert panel estimated that exposure risk from research scientists could be reduced 94–96 percent (uncertainty, 86–99 percent) through proper use of appropriate N95 respirators (a type of mechanical filter worn over the nose and mouth), dedicated clothing (such as Tyvek coveralls), and gloves. Should any North American bats become infected with SARS-CoV-2, the expert panel estimated that there is an approximately 33-percent chance the virus could spread within a bat population.
This study, conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, identified several critical uncertainties that could affect the estimate of risks associated with SARS-CoV-2 entering bat populations—notably, the underlying probability that a human would be shedding virus while working with bats, the likelihood of the virus replicating in bat tissue, and the likelihood of transmission of the virus within bat populations. Ongoing empirical work during May–October 2020 may shed light on these issues. Follow-up work is needed to better understand the probability of transmission of SARS-CoV-2 to bats from the general public; the manner in which the probabilities of exposure, infection, and transmission would differ during hibernation compared to the breeding season; and the likelihood of important effects, like morbidity and mortality in bats, the possibility of zoonosis from a North American bat reservoir, and effects of and on other wildlife.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201060","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Runge, M.C., Grant, E.H.C., Coleman, J.T.H., Reichard, J.D., Gibbs, S.E.J., Cryan, P.M., Olival, K.J., Walsh, D.P., Blehert, D.S., Hopkins, M.C., and Sleeman, J.M., 2020, Assessing the risks posed by SARS-CoV-2 in and via North American bats—Decision framing and rapid risk assessment: U.S. Geological Survey Open-File Report 2020–1060, 43 p., https://doi.org/10.3133/ofr20201060.","productDescription":"vi, 43 p.","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118911","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":375248,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1060/ofr20201060.pdf","text":"Report","size":"4.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1060"},{"id":375199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1060/coverthb.jpg"}],"country":"Canada, Mexico, United States","otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.1640625,\n 13.581920900545844\n ],\n [\n -84.72656249999999,\n 19.973348786110602\n ],\n [\n -75.9375,\n 27.371767300523047\n ],\n [\n -55.8984375,\n 45.336701909968134\n ],\n [\n -48.8671875,\n 45.336701909968134\n ],\n [\n -65.0390625,\n 61.77312286453146\n ],\n [\n -58.71093750000001,\n 67.47492238478702\n ],\n [\n -84.375,\n 74.1160468394894\n ],\n [\n -125.5078125,\n 75.32002523220804\n ],\n [\n -135.703125,\n 70.95969716686398\n ],\n [\n -156.4453125,\n 71.52490903732816\n ],\n [\n -167.34375,\n 68.9110048456202\n ],\n [\n -168.046875,\n 61.60639637138628\n ],\n [\n -166.2890625,\n 53.12040528310657\n ],\n [\n -146.95312499999997,\n 57.326521225217064\n ],\n [\n -138.515625,\n 56.559482483762245\n ],\n [\n -131.484375,\n 48.922499263758255\n ],\n [\n -127.96875,\n 40.17887331434696\n ],\n [\n -116.01562499999999,\n 24.84656534821976\n ],\n [\n -98.7890625,\n 13.239945499286312\n ],\n [\n -93.1640625,\n 13.581920900545844\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
The Kansas River provides drinking water for multiple cities in northeastern Kansas and is used for recreational purposes. Thus, improving the scientific knowledge of streamflow velocities and traveltimes will greatly aid in water-treatment plans and response to critical events and threats to water supplies. Dye-tracer studies are usually done to enhance knowledge of transport characteristics, which include streamflow velocities, traveltimes, and dispersion rates, within a river system. To achieve this in the Kansas River, rhodamine water-tracing dye is planned to be injected into the Kansas River during three different flow ranges at three locations: Manhattan, Topeka, and Eudora. The primary purpose of doing a dye-tracer study in the Kansas River is to calibrate a time-of-travel model used for estimating streamflow velocities and traveltimes, which can be used by the public as well as drinking water suppliers to protect water resources and public-water supplies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201039","collaboration":"Prepared in cooperation with the Kansas Water Office, Kansas Department of Health and Environment, The Nature Conservancy, City of Topeka, Johnson County WaterOne, City of Manhattan, and City of Olathe","usgsCitation":"Davis, C.A., Lukasz, B.S., and May, M.R., 2020, Dye-tracing plan for verifying the Kansas River time-of-travel model: U.S. Geological Survey Open-File Report 2020–1039, 10 p., https://doi.org/10.3133/ofr20201039.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-107718","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":375197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1039/ofr20201039.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1039"},{"id":375196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1039/coverthb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.1630859375,\n 38.53097889440024\n ],\n [\n -94.4384765625,\n 38.53097889440024\n ],\n [\n -94.4384765625,\n 39.926588421909436\n ],\n [\n -97.1630859375,\n 39.926588421909436\n ],\n [\n -97.1630859375,\n 38.53097889440024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
The U.S. Atomic Energy Commission established the National Uranium Resources Evaluation (NURE) program in 1973 to identify uranium resources throughout the United States. Part of this program focused on the collection of stream-sediment samples and subsequent geochemical analyses of these samples for uranium, in addition to 47 other elements. As part of the original program, 18,424 stream-sediment samples were collected from Wyoming and analyzed. All original samples are stored at the U.S. Geological Survey’s (USGS) National Geochemical Sample Archive (NGSA). The Wyoming State Geological Survey (WSGS) recently selected 159 of the original Wyoming NURE stream samples to be reanalyzed using modern and standardized analytical equipment. The raw results of the reanalysis are provided with this report.
","language":"English","publisher":"Wyoming State Geological Survey","collaboration":"Wyoming State Geological Survey","usgsCitation":"Lucke, D.W., Smith, S.M., Azain, J., and Ingraham, A.D., 2020, Data release of reprocessed select National Uranium Resources Evaluation program samples in Wyoming: Open-File Report 2020-7, 9 p.","productDescription":"9 p.","ipdsId":"IP-118527","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":386992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375997,"type":{"id":15,"text":"Index Page"},"url":"https://sales.wsgs.wyo.gov/data-release-of-reprocessed-select-national-uranium-resources-evaluation-program-samples-in-wyoming-2020/"}],"country":"United 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0000-0002-8256-7494","orcid":"https://orcid.org/0000-0002-8256-7494","contributorId":201966,"corporation":false,"usgs":true,"family":"Azain","given":"Jaime S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingraham, Andrew David 0000-0001-7347-6171","orcid":"https://orcid.org/0000-0001-7347-6171","contributorId":225588,"corporation":false,"usgs":true,"family":"Ingraham","given":"Andrew","email":"","middleInitial":"David","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":791763,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210279,"text":"ofr20191134 - 2020 - Regional hydrostratigraphic framework of Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, in the context of perfluoroalkyl substances contamination of groundwater and surface water","interactions":[],"lastModifiedDate":"2020-05-29T15:12:09.612507","indexId":"ofr20191134","displayToPublicDate":"2020-05-29T09:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1134","displayTitle":"Regional Hydrostratigraphic Framework of Joint Base McGuire-Dix-Lakehurst and Vicinity, New Jersey, in the Context of Perfluoroalkyl Substances Contamination of Groundwater and Surface Water","title":"Regional hydrostratigraphic framework of Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, in the context of perfluoroalkyl substances contamination of groundwater and surface water","docAbstract":"A study was conducted by the U.S. Geological Survey, in cooperation with the U.S. Air Force, to describe the regional hydrostratigraphy of shallow aquifers and confining units underlying Joint Base McGuire-Dix-Lakehurst (JBMDL) and vicinity, New Jersey, in the context of contamination of groundwater and surface water by per- and polyfluoroalkyl substances (PFAS) potentially originating from JBMDL sources. The aquifers studied are two that crop out within JBMDL boundaries—the Kirkwood-Cohansey aquifer system and the Vincentown aquifer—and another aquifer near JBMDL that does not crop out at land surface—the Piney Point aquifer. The unconfined portion of the Vincentown aquifer and portions of the Kirkwood-Cohansey aquifer system that overlie the unconfined portion of the Vincentown aquifer are consolidated into, and described as, a single, separate unconfined aquifer system. Regionally extensive clay subunits that potentially create semiconfined hydrologic conditions within the mostly unconfined Kirkwood-Cohansey aquifer system also are identified. Two confining units were studied—the Manasquan-Shark River confining unit underlying the Kirkwood-Cohansey aquifer system, which includes the basal confining sediment in the Kirkwood Formation, and the Navesink-Hornerstown confining unit underlying the Vincentown aquifer. The hydrostratigraphic units are defined using available borehole geophysical logs, lithologic logs, and (or) drillers’ logs from 131 wells and are presented in a series of 8 aquifer structure maps and 12 cross sections. The framework positions JBMDL into a regional hydrostratigraphic structure for which higher-resolution delineation of the shallow aquifers can be constructed to determine potential pathways of PFAS contamination in groundwater to off-site drinking water wells in areas adjacent to JBMDL.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191134","collaboration":"Prepared in cooperation with the U.S. Air Force","usgsCitation":"Fiore, A.R., 2020, Regional hydrostratigraphic framework of Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, in the context of perfluoroalkyl substances contamination of groundwater and surface water: U.S. Geological Survey Open-File Report 2019–1134, 42 p., https://doi.org/10.3133/ofr20191134.","productDescription":"Report: viii, 42 p.; 12 Plates: 30 x 24 inches; 2 Tables","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-107327","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":375120,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate06.pdf","text":"Plate 6","size":"1.87 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the top of the confined portion of the Vincentown aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375125,"rank":13,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate11.pdf","text":"Plate 11","size":"533 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sections F-F’ through I-I’, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1134/coverthb.jpg"},{"id":375114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134.pdf","text":"Report","size":"9.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1134"},{"id":375115,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate01.pdf","text":"Plate 1","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of well locations and outcrop areas of hydrostratigraphic units, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375116,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate02.pdf","text":"Plate 2","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the bottom of the Kirkwood-Cohansey aquifer system, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375117,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate03.pdf","text":"Plate 3","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the top of semiconfining subunits within the Kirkwood-Cohansey aquifer system, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375122,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate08.pdf","text":"Plate 8","size":"1.88 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the bottom of the unconfined portion of the Vincentown aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375123,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate09.pdf","text":"Plate 9","size":"2.04 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the bottom of the Navesink-Hornerstown confining unit, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375124,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate10.pdf","text":"Plate 10","size":"588 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sections A-A’ through E-E’, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375127,"rank":15,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_table03.xlsx","text":"Table 3","size":"23.2 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Wells used to develop a hydrostratigraphic framework, and interpreted aquifer structure points, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey (Preferred method to view file)"},{"id":375128,"rank":16,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_table03.csv","text":"Table 3","size":"10.2 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Wells used to develop a hydrostratigraphic framework, and interpreted aquifer structure points, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375118,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate04.pdf","text":"Plate 4","size":"1.48 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the thickness of semiconfining subunits within the Kirkwood-Cohansey aquifer system, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375119,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate05.pdf","text":"Plate 5","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the top of the Piney Point aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375121,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate07.pdf","text":"Plate 7","size":"755 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the thickness of the confined portion of the Vincentown aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375126,"rank":14,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate12.pdf","text":"Plate 12","size":"409 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sections J-J’ through L-L’, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"}],"country":"United States","state":"New Jersey","otherGeospatial":"Joint Base McGuire-Dix-Lakehurst","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.74822998046875,\n 39.886557705928475\n ],\n [\n -74.25796508789062,\n 39.886557705928475\n ],\n [\n -74.25796508789062,\n 40.11799004890473\n ],\n [\n -74.74822998046875,\n 40.11799004890473\n ],\n [\n -74.74822998046875,\n 39.886557705928475\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Bathymetric and topographic surveys performed annually along the coastlines of northern Oregon and southwestern Washington documented changes in beach and nearshore morphology between 2014 and 2019. Volume change analysis revealed measurable localized erosion and deposition throughout the study area, but significant net erosion at the regional scale (several kilometers [km]) was limited to Benson Beach, Wash., a 3-km-long stretch of coastline immediately north of the Columbia River inlet. Despite the placement of approximately 6.3 million cubic meters (Mm3) of sand dredged from the Columbia River navigational channel at nearshore placement sites located nearby, Benson Beach eroded 2.1±0.8 Mm3 over the 5-year (yr) monitoring time period (420,000 cubic meters/year [m3/yr]). A hydrodynamic and sediment transport model was applied to simulate sediment transport fluxes, and a new visualization technique was developed to evaluate the linkages between nearshore dredge placement sites and adjacent coastlines near the mouth of the Columbia River. The model results indicate the dominance of wave processes on sediment-transport patterns outside of the inlet and suggest that the current configuration of the nearshore dredge placement sites can be improved to more efficiently enhance the sediment budget of Benson Beach to reduce erosion and mitigate associated coastal change hazards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201045","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers Portland District and Northwest Association of Networked Ocean Observing Systems","usgsCitation":"Stevens, A.W., Elias, E., Pearson, S., Kaminsky, G.M., Ruggiero, P.R., Weiner, H.M., and Gelfenbaum, G.R., 2020, Observations of coastal change and numerical modeling of sediment-transport pathways at the mouth of the Columbia River and its adjacent littoral cell: U.S. Geological Survey Open-File Report 2020–1045, 82 p., https://doi.org//10.3133/ofr20201045.","productDescription":"Report: xii, 82 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-114630","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":375095,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1045/coverthb.jpg"},{"id":375096,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1045/ofr20201045.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":375097,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org//10.5066/P9W15JX8","linkHelpText":"Beach topography and nearshore bathymetry of the Columbia River littoral cell, Washington and Oregon"}],"country":"United States","state":"Oregon, Washinton","otherGeospatial":"Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.07135009765625,\n 46.10180436619509\n ],\n [\n -123.57147216796875,\n 46.10180436619509\n ],\n [\n -123.57147216796875,\n 46.35261512930026\n ],\n [\n -124.07135009765625,\n 46.35261512930026\n ],\n [\n -124.07135009765625,\n 46.10180436619509\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
A 2-year radiotelemetry study was completed to monitor the movements of adult winter steelhead (Oncorhynchus mykiss) in the upper Cowlitz River Basin. A reintroduction program was established to restore healthy and harvestable populations of steelhead because volitional access to the area was blocked in the 1960s after construction of dams in the lower river. A trap-and-haul program is used to move adult steelhead and salmon (Oncorhynchus spp.) upstream, around the dams and large reservoirs, and release them in the upper basin to spawn naturally. Fish are released into Lake Scanewa, the uppermost reservoir in the system, and into the Cowlitz and Cispus Rivers. The goal of this study was to describe the behavior, movement, and tributary use of adult steelhead in the upper Cowlitz River Basin to assist in evaluating the trap-and-haul program and reintroduction program. We were specifically interested in learning more about the locations where steelhead spawn. Individual fish were assigned one of four fates, based on their location during the spawning period: Cowlitz River, Cispus River, Lake Scanewa, or fallback below the dam that impounds the reservoir. A total of 215 steelhead were tagged for the 2017–18 study. Of these, 5 fish regurgitated their transmitters before or shortly after release, so 210 tagged fish were used for analyses, including 121 fish (57.6 percent) released into the Cispus River and 89 fish (42.4 percent) released into Lake Scanewa. The Cowlitz River release site was not evaluated. Hatchery-origin (HOR) and natural-origin (NOR) steelhead were included in the study. Within the first 10 days after release, most steelhead had moved at least 2 river kilometers away from their release site. Fish released into Lake Scanewa, however, moved from their release site significantly sooner than fish released into the Cispus River, regardless of origin or sex. Most radio-tagged steelhead (93–100 percent) made no more than one trip between the reservoir and one of the rivers prior to spawning.
Steelhead were predominantly assigned fates in the river closest to where they were released, but origin also played a role. Steelhead released into the Cispus River were assigned Cispus River fates more than 80 percent of the time, including both origins and both years. About 13 percent of NOR fish had fates in the Cowlitz River, but the proportion was lower for HOR fish (0–2 percent). Fallback was the least common fate for Cispus-released steelhead (three HOR fish in 2017), followed by the reservoir fate, ranging from 5 to 9 percent in 2017, and zero in 2018. The steelhead released into Lake Scanewa were almost exclusively NOR fish, which had primarily Cowlitz River fates (55–57 percent). We released only six HOR steelhead into Lake Scanewa, and they all had Cowlitz River fates. The reservoir fate was uncommon for both release sites, and it was consistently lower in 2018 compared to 2017. Flow conditions were higher in 2017, which may have affected steelhead movement patterns or timing. The three HOR steelhead released in the Cispus River in 2017 were the only fish that fell back over Cowlitz Falls Dam, which represented 1.4 percent of the total study fish, 5.7 percent of the Cispus-released fish in 2017, and 9.4 percent of the Cispus-released HOR fish in 2017.
About 62 percent of the steelhead released in Lake Scanewa spawned in the Cowlitz River, with the remaining 38 percent in the Cispus River. Within the Cowlitz River, close to one-half (about 47 percent) of the fish spawned in the upper reach, and about 16 percent spawned in the lower reach. Steelhead released into Lake Scanewa that spawned in the Cispus River were minimal in reach 5 (4 percent) and distributed in approximately equal proportions in the middle (reach 6; 16 percent) and upper (reach 7; 18 percent) reaches. Steelhead released into the Cispus River spawned almost exclusively in the Cispus River (94 percent). The upper Cispus River reach (reach 7) was used by more fish (72 percent) than the middle Cispus reach (reach 6; 16 percent). Taken together, the upper Cowlitz River reach (reach 4) and upper Cispus River reach (reach 7) accounted for more than 71 percent of the spawning locations for radio-tagged steelhead. When the middle Cispus River reach (reach 6) is included with the upper reaches, they account for 87 percent of our described spawning sites. We described 12 tributaries in the Cowlitz River and 8 tributaries in the Cispus River where steelhead spawned. After spawning, about 53–63 percent of steelhead moved downstream as kelts, either being collected at Cowlitz Falls Dam or being detected downstream from the dam. More fish were collected from both release sites in 2018 compared to 2017. Across release sites and years, more NOR fish and females moved downstream as kelts. This study added to the understanding of the behavior and movement of adult steelhead in the upper Cowlitz River Basin, supporting the findings of previous studies in the basin and describing spawning sites in the system’s two main rivers and their tributaries. Future research efforts in this system may use additional telemetry studies, genetic analyses, and spawning ground surveys to provide further insights into the progress of the reintroduction effort.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201054","usgsCitation":"Liedtke, T.L., Kock, T.J., Hansen, A.C., Ekstrom, B.K., and Tomka, R.G., 2020, Behavior and movement of adult winter steelhead (Oncorhynchus mykiss) in the upper Cowlitz River Basin, Washington, 2017–18: U.S. Geological Survey Open-File Report 2020–1054, 35 p., https://doi.org/10.3133/ofr20201054.","productDescription":"vi, 35 p.","numberOfPages":"35","onlineOnly":"Y","ipdsId":"IP-116465","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":375037,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1054/coverthb.jpg"},{"id":375038,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1054/ofr20201054.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Washington","otherGeospatial":"Upper Cowlitz River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.22265625000001,\n 45.767522962149876\n ],\n [\n -120.498046875,\n 45.767522962149876\n ],\n [\n -120.498046875,\n 46.98025235521881\n ],\n [\n -123.22265625000001,\n 46.98025235521881\n ],\n [\n -123.22265625000001,\n 45.767522962149876\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
A recent U.S. Geological Survey data compilation of stream-sediment geochemistry for Alaska contains decades of analyses collected under numerous Federal and State programs. The compiled data were determined by various analytical methods. Some samples were reanalyzed by a different analytical method than the original, resulting in some elements having concentrations reported by multiple analytical methods. Consideration of the analytical methods used to determine the elemental concentrations is an important step in a mineral prospectivity analysis. We used the compiled data to compare concentrations of barium (Ba), cobalt (Co), copper (Cu), chromium (Cr), nickel (Ni), lead (Pb), and zinc (Zn) determined by different analytical methods to show how simple data comparisons can identify bias and provide a general sense of the comparability of different analytical methods. The elements were selected because they have a range of geochemical properties that may affect the performance of different analytical procedures.
Generally, agreement between Ba, Co, Cu, Cr, Ni, Pb, and Zn concentrations is good for most quantitative methods that use a total decomposition of the sample. However, Cr concentrations typically were lower for methods using quantitative-instrumental analysis following a multi-acid dissolution technique that included hydrofluoric acid compared to those using sinter decomposition. Additionally, low- to middle-range concentrations for Co, Cr, Cu, Ni, Pb, and Zn by instrumental neutron activation (NA) and energy-dispersive x-ray spectroscopy (EDX) analyzed by the National Uranium Resource Evaluation (NURE) program have high uncertainty. Concentrations determined by methods that use partial decomposition of the sample generally correspond well to concentrations determined by methods that use a total decomposition technique, except for Ba and Cr. For Ba and Cr, partial decomposition techniques yield lower concentrations than those determined by methods that use a total decomposition technique. Comparison of Ba, Co, Cr, Cu, Ni, Pb, and Zn concentrations determined by semiquantitative visual six-step direct-current arc emission spectrography (ES_SQ) to those determined by quantitative methods using either a total or partial decomposition technique consistently show scatter that exceeds the values expected based on the range represented by the semiquantitative concentration.
The data compilation includes a best-value determination that was selected based on the analytical method from the all concentration data for that sample. Ba, Cr, Co, and Zn concentrations determined by NA usually are selected as the best-value determination. However, the NURE-NA method was designed for high throughput and the uncertainty associated with low- and mid-range concentrations is greater than that of the multi-acid method used to reanalyze many samples. Selection of the multi-acid method over the NURE-NA method for Ba, Co, and Zn could be warranted. Additionally, concentrations determined by ES_SQ usually are selected as the best-value determination over all methods that use a partial decomposition of the sample. Substitution of concentrations determined by methods that use a partial decomposition for those of ES_SQ may be warranted for Co, Cu, Ni, Pb, and Zn. Regardless of the selection of the best-value determination, the dataset remains a mixed method dataset and the uncertainty due to differences in analytical methodology must be considered when using the dataset.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201038","usgsCitation":"Wang, B, Ellefsen, K.J., Granitto, M., Kelley, K.D., Karl, S.M., Case, G.N.D., Kreiner, D.C., and Amundson, C.L., 2020, Evaluation of the analytical methods used to determine the elemental concentrations found in the stream geochemical dataset compiled for Alaska: U.S. Geological Survey Open-File Report 2020-1038, 66 p., https://doi.org/10.3133/ofr20201038.","productDescription":"xii, 66 p.","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-109726","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":375022,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1038/coverthb.jpg"},{"id":375023,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1038/ofr20201038.pdf","text":"Report","size":"8 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Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508