There is a growing body of tools available for science support for determining the fate and behavior of industrial and agricultural chemicals that are rapidly injected (“spilled”) into aquatic environments. A 2-day roundtable-style workshop was held by the U.S. Geological Survey (USGS) in Middleton, Wisconsin, in December 2017 to describe and explore existing Federal science support for spill fate and behavior tools used for inland spills, ongoing and new fate and behavior studies, and science gaps in planning and response tools as part of the USGS Midcontinent Region’s efforts to include spill response as part of its strategic plans. A total of 28 attendees representing a variety of Federal, State, and regional entities presented on programs and tools used in various aspects of spill response. Most programs and tools discussed were for spills in riverine environments but tools and applications for spills in lakes, on land surfaces, in urban storm sewer networks, and groundwater also were discussed. A primary workshop focus was to facilitate communication and increase potential for future collaboration among agencies for inland spill science support. The role and need for more USGS science support within the inland spill community was discussed. Enhanced communication is needed within the USGS and the U.S. Department of the Interior science programs, as well as within and among other agencies that do emergency planning and response. A main conclusion of the workshop was that there are untapped resources of the USGS outlined in the agency’s science strategy that could strengthen science support for fate and behavior tools in inland areas, especially in the Upper Mississippi River, Ohio River, and Great Lakes Basins where large freshwater resources overlap with dense corridors of oil and hazardous substances, with transportation networks, and with large populations centers.
Fate and behavior tools are being developed quickly for inland spill response by multiple Federal agencies in partnership with local and regional entities. Applicability of these tools ranges from planning and preparedness, to the early stages of spill response for protection of human life and property, and to the application of monitoring and models to assess the long-term consequences of spills. Key findings from the workshop, with an emphasis on potential further development of USGS science support, include the following:
•The national and regional response to spills occurs within an established system that must be respected by all parties involved in spill response. The USGS’s role is to support spill responders who are physically working at a spill scene, deploying booms and using other efforts to contain and recover spilled materials.
•The USGS has tools that have been used throughout spill response operations, from early response to recovery and restoration. Developing a more formal role for the USGS to participate in science support for inland spills on a consistent basis is a desired outcome. This will require the USGS to improve internal and external communication and would be best accomplished by assigning one or more coordinator positions within the agency to plan and oversee USGS spill-response efforts. More involvement of the USGS on National and Regional Response Teams, especially in the realm of the Science and Technology Subcommittees, will gofar in increasing external communication and integration of fate and behavior tools.
•Rapid response to spills requires modeling and mapping of plumes and associated time-of-travel estimation for a range of stream sizes across the United States. Many existing models use USGS streamgage data and the USGS National Hydrography Dataset. Nearly all existing models would benefit from updated linkages to USGS StreamStats and its soon-to-be released time-of-travel estimates,real-time velocity, stream morphology, and slope data. Integrating USGS tools with those from other agencies could be done to better serve the larger spill response community.
• A problem is that existing models to rapidly predict plume extent, as well as more followup/longer-term fate and transport models, can be unknown or unavailable to spill responders. Thus, creating and strengthening linkages among USGS scientists skilled at using these tools is needed to support spill response with the on-scene responders.
• Research for inland spill fate and behavior done outside of an immediate spill response can assist with spill planning and preparedness by (1) revealing sites likely to experience spills in the future (high-risk sites) and (2) understanding how a spilled substance might behave under a range of environmental conditions. However, USGS research on this topic has been scarce and subject to funding availability. Examples include the 2010 Line 6B Spill release into the Kalamazoo River in Michigan, where the USGS provided science support for a variety of fate and behavior tools for stream and impoundment environments. A long-term research site in Bemidji, Minnesota, provides important insights into transformations and longevity of spilled oil in groundwater and groundwater-surface water interactions.
• Linking stream models to other components of this inland environment, including groundwater, overland flow, and karst, is needed. Stream network data can be linked to underground conduits such as storm sewers and karst groundwater systems. Stream models can also be linked with geospatial data such as that contained in U.S. Environmental Protection Agency’s
interactive mapping tools.
• The USGS is uniquely qualified to collect water-quality data during spills in the United States because of its many geographically dispersed water science centers, its knowledge and preparedness for flood measurement and documentation, and its cadre of skilled water-quality employees. Rapid-deployment gages, used for floods, could also be used for spills if they included spill-specific sensors. Coordinated expertise at USGS water and environmental science centers can be used for monitoring spill effects and for assessing risk to water quality and ecological communities.
• Scientists at the USGS have proven capable of providing science coordination and technical assistance within the Incident Command Structure at the request of the lead on-scene coordinator. This external coordination, as well as internal communication within USGS Water, Hazards, and Ecosystems Mission Areas, could be improved by establishing and naming a USGS spills coordinator. Scott Morlock, Jo Ellen Hinck, and Faith Fitzpatrick are currently (2017) serving in informal coordination roles in addition to their traditional duties.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201063","usgsCitation":"Sullivan, D.J., and Fitzpatrick, F.A., 2020, Fate and behavior tools related to inland spill response—Workshop on the U.S. Geological Survey’s role in Federal science support: U.S. Geological Survey Open-File Report 2020–1063, 22 p., https://doi.org/10.3133/ofr20201063.","productDescription":"v, 22 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-111089","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":376920,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1063/ofr20201063.pdf","text":"Report","size":"8.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1063"},{"id":376919,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1063/coverthb.jpg"}],"contact":"Director, Upper Midwest Water Science Center
U.S Geological Survey
8505 Research Way
Middleton, WI 53562
Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled \"Building Capacity for Applied Short-Term Ecological Forecasting\" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS.
Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201073","usgsCitation":"Bradford, J.B., Weltzin, J.F., McCormick, M., Baron, J., Bowen, Z., Bristol, S., Carlisle, D., Crimmins, T., Cross, P., DeVivo, J., Dietze, M., Freeman, M., Goldberg, J., Hooten, M., Hsu, L., Jenni, K., Keisman, J., Kennen, J., Lee, K., Lesmes, D., Loftin, K., Miller, B.W., Murdoch, P., Newman, J., Prentice, K.L., Rangwala, I., Read, J., Sieracki, J., Sofaer, H., Thur, S., Toevs, G., Werner, F., White, C.L., White, T., and Wiltermuth, M., 2020, Ecological forecasting—21st century science for 21st century management: U.S. Geological Survey Open-File Report 2020–1073, 54 p., https://doi.org/10.3133/ofr20201073.","productDescription":"vii, 54 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114740","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":433,"text":"National Phenology Network","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":376787,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1073/ofr20201073.pdf","text":"Report","size":"598 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1073"},{"id":376786,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1073/coverthb.jpg"}],"contact":"Director, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
The accurate mapping of streams and their streamflow conditions in terms of presence or absence of surface water is important to both understanding physical, chemical, and biological processes in streams and to managing land, water, and ecological resources. This document describes a field form, FLOwPER (FLOw PERmanence), available within a mobile application (app), for standardized data collection of the presence or absence of surface flow in streams. The FLOwPER Database is a publicly available geodataset that can be used for research and management applications. This document provides instructions on how to (1) access and download the FLOwPER field form within the mobile app service, (2) use and complete a FLOwPER field form, and (3) view and download data from the FLOwPER Database.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201075","collaboration":"Prepared in cooperation with the United States Forest Service and the Bureau of Land Management","usgsCitation":"Jaeger, K.L., Burnett, J., Heaston, E.D., Wondzell, S.M., Chelgren, N., Dunham, J.B., Johnson, S., and Brown, M., 2020, FLOwPER user guide—For collection of FLOw PERmanence field observations: U.S. Geological Survey Open-File Report 2020–1075, 40 p., https://doi.org/10.3133/ofr20201075.","productDescription":"Report: vi, 40 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-118616","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":436839,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13WFKYW","text":"USGS data release","linkHelpText":"FLOwPER Database: StreamFLOw PERmanence field observations, Jan 2021 - Dec 2021"},{"id":407336,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5edea67582ce7e579c6e5845","text":"USGS data release","description":"USGS data release","linkHelpText":"FLOwPER Database: StreamFLOw PERmanence Field Observations"},{"id":376985,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1075/coverthb.jpg"},{"id":377862,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1075/ofr20201075_appendix01.pdf","text":"Appendix 1","size":"507 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1075 Appendix 1"},{"id":376986,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1075/ofr20201075.pdf","text":"Report","size":"5.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1075"}],"contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The Midcontinent Rift System (MRS) of North America is one of the world’s largest continental rifts and has an age of 1.1 Ga (giga-annum). The MRS hosts a diverse suite of magmatic and hydrothermal mineral deposits in the Lake Superior region where rift rocks are exposed at or near the surface. As part of the construction of a database summarizing information on mineral deposits in the MRS, data from regional mineral deposits were downloaded from the U.S. Geological Survey (USGS) Mineral Resources Data System (MRDS), the USGS Mineral Deposit Database (USMIN), and the Ontario Ministry of Energy, Northern Development and Mines Mineral Deposit Inventory (MDI). Deposits related to MRS rocks or mineralizing events were identified and compiled into a database to develop a space/time classification for MRS-related mineral deposits. Information from MRDS, USMIN, and MDI records and from the extensive literature describing MRS mineral deposits was used to classify each entry by deposit type, host rock age and type, and estimated mineralization age. Most deposits were readily classified because of unique mineralogy, location, or well-constrained host rock. These deposits were then put into a tectonic evolutionary framework for the MRS, which showed that many deposits formed within discrete spatial and temporal stages of rift evolution.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201069","usgsCitation":"Woodruff, L.G., Schulz, K.J., Dicken, C.L., and Nicholson, S.W., 2020, Mineral resource database for deposits related to the Mesoproterozoic Midcontinent Rift System, United States and Canada: U.S. Geological Survey Open-File Report 2020–1069, 20 p., https://doi.org/10.3133/ofr20201069.","productDescription":"Report: vi, 20 p.; 2 Tables","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-113694","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":436840,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HTATKY","text":"USGS data release","linkHelpText":"Database of mineral deposits related to the Mesoproterozoic Midcontinent Rift System (MRS) in the northern United States and northern Ontario, Canada"},{"id":376912,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1069/ofr20201069_table1.csv","text":"Table 1","size":"171 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Database of mineral deposits related to the Mesoproterozoic Midcontinent Rift System (MRS) in the northern United States and northern Ontario, Canada"},{"id":376911,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1069/ofr20201069_table1.xlsx","text":"Table 1","size":"124 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Database of mineral deposits related to the Mesoproterozoic Midcontinent Rift System (MRS) in the northern United States and northern Ontario, Canada"},{"id":376909,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1069/coverthb.jpg"},{"id":376910,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1069/ofr20201069.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1069"}],"country":"United States, Canada","otherGeospatial":"Mesoproterozoic Midcontinent Rift System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.2216796875,\n 40.245991504199026\n ],\n [\n -81.8701171875,\n 50.792047064406866\n ],\n [\n -96.6357421875,\n 51.23440735163459\n ],\n [\n -96.1083984375,\n 43.45291889355465\n ],\n [\n -97.5146484375,\n 43.739352079154706\n ],\n [\n -97.55859375,\n 41.541477666790286\n ],\n [\n -99.931640625,\n 41.376808565702355\n ],\n [\n -100.1513671875,\n 37.16031654673677\n ],\n [\n -94.7021484375,\n 37.09023980307208\n ],\n [\n -94.833984375,\n 39.53793974517628\n ],\n [\n -82.2216796875,\n 40.245991504199026\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Coordinator, Mineral Resources Program
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The U.S. Geological Survey National Crustal Model (NCM) is being developed to include spatially varying estimates of site response in seismic hazard assessments. Primary outputs of the NCM are continuous velocity and density profiles from the Earth’s surface to the mantle transition zone at 410-kilometer (km) depth for each location on a 1-km grid across the conterminous United States. Datasets used to produce the NCM may have a resolution of better than 1 km near the Earth’s surface in some regions, but, with increasing depth, NCM resolution decreases to tens to hundreds of kilometers in the mantle. Basic subsurface information is provided by the NCM geologic framework, thermal model, and petrologic and mineral physics database. In this report, the velocities and densities that can be extracted from the NCM are calibrated through the development of a porosity model based on Biot-Gassmann theory and more than 2,000 compressional- and (or) shear-wave velocity profiles less than 10 km deep from across the conterminous United States and southwestern Canada.
Sediment and rock porosities are derived from shear-wave velocity and are found to depend on effective pressure, rock type, and age (for sedimentary and extrusive volcanic deposits). Porosity-effective pressure functions are then estimated for each rock type (and age for sedimentary and extrusive volcanic deposits). Unconsolidated sediments are found to have higher porosities than consolidated units, which have higher porosities than unweathered igneous units; young sedimentary units (for example, Quaternary age units) tend to have higher porosities than older sedimentary units (for example, pre-Cenozoic age units); porosity decreases with increasing effective pressure; and porosities can decrease quickly through the weathered layer of intrusive rocks.
Comparing two Los Angeles area velocity models and the U.S. Geological Survey Bay Area velocity model with the NCM, the NCM does a better job on average of reproducing observed shear-wave velocities below 1 km per second because it has less bias and uncertainty. Approaching and above 1 km per second, the NCM tends to underpredict observed shear-wave velocity. Whereas several factors could contribute to this, the primary factor is probably bias in the NCM geologic framework. For example, the NCM will predict lower velocities in places where the depth to bedrock and basement appear shallower in the measured velocity profiles than specified in the NCM geologic framework. With regard to observed compressional-wave velocity and density, the NCM has significantly less bias than California models for the former, especially below 2 km per second, and all models tend to overpredict density for densities less than about 2,200 kilograms per cubic meter.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201052","usgsCitation":"Boyd, O.S., 2020, Calibration of the U.S. Geological Survey National Crustal Model: U.S. Geological Survey Open-File Report 2020–1052, 23 p., https://doi.org/10.3133/ofr20201052.","productDescription":"Report: vi, 23 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115717","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436847,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NQ5LNU","text":"USGS data release","linkHelpText":"GeoPhys"},{"id":376928,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1052/ofr20201052.pdf","text":"Report","size":"6.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1052"},{"id":376929,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GO3CP8","text":"USGS 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U.S. Geological Survey
Box 25046, MS-966
Denver, CO 80225-0046
The seawaveQ R package provides functionality and help to fit a parametric regression model, SEAWAVE-Q, to pesticide concentration data from stream-water samples to assess trends. The model incorporates the strong seasonality and high degree of censoring common in pesticide data, and users can incorporate numerous ancillary variables such as streamflow anomalies. The model is fitted to pesticide data using maximum likelihood methods for censored data and is robust in terms of pesticide, stream location, and degree of censoring of the concentration data. This R package standardizes this methodology for trend analysis, documents the code, and provides help and tutorial information.
In previous investigations, the SEAWAVE-Q model assumed a linear trend across the period analyzed. For short trend periods, this assumption of a linear trend is adequate. However, as the period of record analyzed becomes longer, the assumption of linearity is problematic because of changes in pesticide regulation and use, some of which can be abrupt. In this update to the model, a restricted cubic spline option was added for long trend periods. This option allows for more flexibility in the time component of the model. Bootstrap functionality is included to determine statistical significance. Model results with the new restricted cubic spline option are compared to the linear trend option for two pesticide-site combinations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201082","collaboration":"National Water Quality Program","usgsCitation":"Ryberg, K.R., and York, B.C., 2020, seawaveQ—An R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables, version 2.0.0: U.S. Geological Survey Open-File Report 2020–1082, 25 p., https://doi.org/10.3133/ofr20201082.","productDescription":"Report: vi, 25; 3 Appendixes","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101011","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":376796,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082_appendix_1.pdf","text":"Appendix 1.","size":"356 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082 Appendix 1","linkHelpText":"— Vignette for seawaveQ—An R Package Providing a Model and Utilities for Analyzing Trends in Chemical Concentrations in Streams with a Seasonal Wave (seawave) and Adjustment for Streamflow (Q) and Other Ancillary Variables"},{"id":376797,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082_appendix_2.pdf","text":"Appendix 2.","size":"228 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082 Appendix 2","linkHelpText":"— R Documentation"},{"id":376798,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082_appendix_4.pdf","text":"Appendix 4.","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082 Appendix 4","linkHelpText":"— Model Comparisons Using seawaveQ"},{"id":376794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1082/coverthb.jpg"},{"id":376795,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082.pdf","text":"Report","size":"2.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082"}],"contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD
The U.S. Army Fort Belvoir (FTBL) installation is on the banks of the Potomac River in Fairfax County, northeastern Virginia. The installation was founded by the U.S. Army during World War I. It has been home to a variety of military organizations over the course of its more than 100-year history and currently houses more than 145 mission partners. The installation consists of two noncontiguous units, the Main Post, and a smaller area to the northwest, Fort Belvoir North Area (FTNA). FTBL encompasses 8.91 square miles.
There is concern that activities on FTBL, including a long history of training, operations, and maintenance, may have resulted in contamination of stream water, streambed sediment, and (or) soils. Of particular concern is the U.S. Environmental Protection Agency (EPA) Target Analyte List (TAL). TAL refers to “the list of inorganic compounds/elements designated for analysis as contained in the version of the EPA Contract Laboratory Program Statement of Work for Inorganics Analysis, Multi-Media, Multi-Concentration in effect as of the date on which the laboratory is performing the analysis” (https://www.nj.gov/dep/srp/guidance/tcl_tal/). Because of the potential for TAL contamination at FTBL, the U.S. Geological Survey (USGS), in cooperation with U.S. Army Fort Belvoir, conducted a survey of FTBL’s stream water, streambed sediment, and soils during calendar year 2019.
The terminology “ambient concentrations” is used in this report to represent the concentrations of the TAL and other constituents at the time of sampling. This is in contrast to “background concentrations,” a term that “refers to areas in which the concentrations of chemicals have not been elevated by site activities”. Although some of the samples collected for this project may represent “background concentrations,” there is no assurance that they do, so all data collected are described as having “ambient concentrations.”
The purpose of the study was to obtain environmental data to characterize ambient concentrations of EPA TAL constituents in stream water, streambed sediment, and soils in FTBL, Virginia. This report describes methods and results of sampling stream water, streambed sediment, and soils during 2019. The purpose of this report is four-fold: (1) to describe the field sampling methods used to collect stream water, streambed sediment, and soils; (2) to describe the laboratory methods used to analyze the samples; (3) to report summaries of the field and laboratory results; and (4) to report the quality assurance and quality control results.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201059","collaboration":"Prepared in cooperation with the U.S. Army, Fort Belvoir","usgsCitation":"Rice, K.C., and Chambers, D.B., 2020, Chemical constituent concentrations in stream water, streambed sediment, and soils of Fort Belvoir, Virginia—A characterization of ambient conditions in 2019: U.S. Geological Survey Open-File Report 2020–1059, 20 p., https://doi.org/10.3133/ofr20201059.","productDescription":"Report: vi, 20 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-116519","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":376670,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91P7OZJ","text":"USGS data release","linkHelpText":"Fort Belvoir, Virginia, stream-water, streambed-sediment, and soil data collected in 2019"},{"id":376668,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1059/coverthb.jpg"},{"id":376669,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1059/ofr20201059.pdf","text":"Report","size":"6.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1059"}],"country":"United States","state":"Virginia","city":"Fort Belvoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.19388961791992,\n 38.71096464102174\n ],\n [\n -77.20212936401367,\n 38.69033348573663\n ],\n [\n -77.12900161743163,\n 38.67117065551123\n ],\n [\n -77.11492538452148,\n 38.695290864945804\n ],\n [\n -77.12608337402344,\n 38.741766321754575\n ],\n [\n -77.14050292968749,\n 38.753012320665185\n ],\n [\n -77.16659545898438,\n 38.74390855335671\n ],\n [\n -77.18238830566406,\n 38.73051855149164\n ],\n [\n -77.19388961791992,\n 38.71096464102174\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.2184371948242,\n 38.73935623438332\n ],\n [\n -77.17826843261717,\n 38.73935623438332\n ],\n [\n -77.17826843261717,\n 38.7591700932071\n ],\n [\n -77.2184371948242,\n 38.7591700932071\n ],\n [\n -77.2184371948242,\n 38.73935623438332\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
This document describes a standard operating procedure (SOP) for the preparation of purposely killed juvenile salmon, implanted with telemetry transmitters, to be released into rivers, lakes, or streams to test one of the survival model assumptions. Procedures for releases of purposely killed fish (hereinafter dead fish releases) were developed by staff from the U.S. Geological Survey’s Columbia River Research Laboratory, on the basis of laboratory experiments and practical experience with telemetry studies in the Columbia River Basin. Initially, we used extended exposure to high dose anesthetic baths to euthanize fish for dead fish releases. This approach was selected on the basis of euthanization procedures described in the literature for studies that required an effective and rapid procedure, such as stress physiology assessments. Ultimately, this technique was deemed insufficient because detection records suggested that some fish seemed to revive and continue their migration with limited effect. That is, the detection histories of dead fish were very similar to those of live fish. To overcome this challenge, we adapted our procedures to require a combination of euthanization procedures on individual fish to ensure that there was no opportunity for revival. A combination of euthanization procedures for dead fish releases was used in one study in Germany. This SOP has been used by the U.S. Geological Survey to test survival model assumptions in several field studies and has consistently performed well. In addition, limited laboratory tests were completed to ensure that no live juvenile salmon were found in holding tanks for 24 hours following the procedures described in this SOP.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201083","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Tomka, R.G., Liedtke, T.L., Frost, C., and Smith, C.D., 2020, A standard operating procedure for the preparation of purposely killed juvenile salmon used to test survival model assumptions: U.S. Geological Survey Open-File Report 2020–1083, 11 p., https://doi.org/10.3133/ofr20201083.","productDescription":"iv, 11 p.","onlineOnly":"Y","ipdsId":"IP-116988","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":376754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1083/coverthb.jpg"},{"id":376755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1083/ofr20201083.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1083"}],"contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The Chattahoochee River National Recreation Area (CRNRA) is a National Park Service unit/park with 48 miles of urban waterway in the Atlanta metropolitan area. The Chattahoochee River within the CRNRA is a popular place for water-based recreation but is known to periodically experience elevated levels of fecal-coliform bacteria associated with warm-blooded animals that can result in a variety of pathogen-related human illnesses. In 2000, the National Park Service entered into a public-private partnership with the U.S. Geological Survey (USGS) and the Chattahoochee Riverkeeper, called the Chattahoochee River BacteriALERT program, to monitor Escherichia coli (E. coli), which is a fecal indicator bacteria and a proxy for human health risk from waterborne pathogens. The BacteriALERT network monitors E. coli densities at three stations on the Chattahoochee River within the CRNRA, at Norcross (USGS station 02335000), Powers Ferry (USGS station 02335880), and Atlanta (USGS station 02336000). E. coli densities determined from water samples were compared to the U.S. Environmental Protection Agency’s Beach Action Value (BAV) of 235 colony forming units per 100 milliliters to assess whether conditions were considered safe for freshwater, primary contact recreational use. Sample E. coli densities exceeded the BAV for 15.5 percent of the samples collected at Norcross (n = 1,969) and 30.3 percent of the samples at Atlanta (n = 1,938) for the study period October 23, 2000, to May 23, 2019, and 33.6 percent of the samples from Powers Ferry (n = 134) for the study period May 5, 2016, to May 23, 2019.
Models to predict E. coli densities in near real-time were developed for the three BacteriALERT stations. Models were developed using forward-stepwise multiple linear regression with the Bayesian Information Criteria and were calibrated with samples collected between October 4, 2007, and May 23, 2019. Explanatory variables included season, turbidity, water temperature, streamflow, upstream tributary streamflows, and temporal trend. The most statistically significant explanatory variables in the models were turbidity, upstream tributary streamflows, and season. The Norcross model had an increasing trend in E. coli densities of 2.3 percent per year. A significant trend was not detected for the Atlanta station, while trends were not assessed for Powers Ferry models due to the short (3-year) calibration period. Model adjusted R2s ranged from 0.686 (Atlanta) to 0.795 (Norcross with time trend) indicating that the models explained a substantial portion of the variations in E. coli densities. Evaluation of model predictions and residuals indicated that models were well posed and exhibited little bias. The models performed well in accurately determining compliance and exceedance of the BAV with low misidentification rates ranging from 3.5 percent (Norcross) to 11.3 percent (Powers Ferry). Misidentification was most common for densities near the BAV, and misidentification rates in the study were low despite fairly low model precisions because E. coli densities were infrequently near the BAV. The precisions of the models developed herein were comparable to the more complex models developed by Lawrence (2012) that were never implemented in the BacteriALERT program due to their computational complexity. The predictive E. coli models developed herein will improve the ability to assess the health risks of water-based recreational activities in the CRNRA in near real-time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201048","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Aulenbach, B.T., and McKee, A.M., 2020, Monitoring and real-time modeling of Escherichia coli bacteria for the Chattahoochee River, Chattahoochee River National Recreation Area, Georgia, 2000–2019: U.S. Geological Survey Open-File Report 2020–1048, 43 p., https://doi.org/10.3133/ofr20201048.","productDescription":"x, 43 p.","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-113124","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":376643,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1048/coverthb.jpg"},{"id":376663,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1048/ofr20201048.pdf","text":"Report","size":"5.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1048"}],"country":"United States","state":"Georgia","city":"Atlanta","otherGeospatial":"Chattahoochee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.1168212890625,\n 34.17772537282446\n ],\n [\n -84.48211669921875,\n 34.01396527491264\n ],\n [\n -84.44915771484375,\n 33.747180448149855\n ],\n [\n -84.29809570312499,\n 33.76544869849223\n ],\n [\n -84.1387939453125,\n 33.902336404480685\n ],\n [\n -84.0509033203125,\n 34.075412438417395\n ],\n [\n -84.04541015625,\n 34.14363482031264\n ],\n [\n -84.1168212890625,\n 34.17772537282446\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Surface-water and suspended-sediment samples were collected and analyzed by the U.S. Geological Survey for multiple current-use pesticides and pesticide degradates approximately every 2 weeks at up to five sites in the Yolo Bypass and Cache Slough Complex before, during, and after augmented flow pulses in summer and fall 2016 and 2018 as well as during ambient flow conditions in summer and fall 2017 (no flow pulse). In 2016, augmented flows occurred during the summer (July) and required the pumping of Sacramento River water by local Reclamation Districts into the Colusa Basin Drain and Yolo Bypass Toe Drain. In contrast, augmented flows in 2018 occurred in the fall (August–September) and used agricultural tailwater (primarily rice field discharge water) to create the flow pulse. Water samples were analyzed by the U.S. Geological Survey for a suite of 175 current-use pesticides and pesticide degradates using gas chromatography with mass spectrometry and liquid chromatography with tandem mass spectrometry laboratory methods. Suspended sediments filtered from the water samples were analyzed for 143 pesticides and degradates by gas chromatography with mass spectrometry.
During the study, 53 pesticides were detected, and all the samples contained mixtures of multiple pesticides at concentrations ranging from below method detection limits to 8,780 nanograms per liter. Pesticides used in growing rice were the dominant pesticides present at four of the five sites sampled and urban-use pesticides dominated at the remaining site. Overall, total pesticide concentrations tended to be higher at sites in the northern part of the Yolo Bypass and lower at southern sites, except for the farthest downstream site which received additional pesticide inputs from the Sacramento River. Flow-pulse water source influenced total pesticide concentrations in the Yolo Bypass and Cache Slough Complex, and the highest total pesticide concentrations at each site were detected either immediately before or during the flow pulse generated with agricultural tailwater in 2018. Data gathered during this study will aid the California Department of Water Resources and other agencies working in the region in adaptively managing pulse flows in the Yolo Bypass and Cache Slough Complex, as one of several California Natural Resources Agency’s Delta Smelt Resiliency strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201076","collaboration":"Prepared in cooperation with the California Department of Water Resources and the State and Federal Contractors Water Agency","usgsCitation":"Orlando, J.L., De Parsia, M., Sanders, C., Hladik, M., and Frantzich, J., 2020, Pesticide concentrations associated with augmented flow pulses in the Yolo Bypass and Cache Slough Complex, California: U.S. Geological Survey Open-File Report 2020–1076, 101 p., https://doi.org/10.3133/ofr20201076.","productDescription":"Report: vi, 101 p.; Data release","numberOfPages":"112","onlineOnly":"Y","ipdsId":"IP-109449","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":376629,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","linkHelpText":"U.S. Geological Survey, 2019, National Water Information System: U.S. Geological Survey Web interface"},{"id":376628,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1076/ofr20201076.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":376627,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1076/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yolo Bypass and Cache Slough Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.85760498046875,\n 38.45789034424927\n ],\n [\n -121.35772705078125,\n 38.45789034424927\n ],\n [\n -121.35772705078125,\n 39.06184913429154\n ],\n [\n -121.85760498046875,\n 39.06184913429154\n ],\n [\n -121.85760498046875,\n 38.45789034424927\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Forster’s terns (Sterna forsteri), historically one of the most numerous colonial-breeding waterbirds in South San Francisco Bay, California, have experienced recent decreases in the number of nesting colonies and overall breeding population size. The South Bay Salt Pond Restoration Project aims to restore 50–90 percent of former salt evaporation ponds to tidal marsh habitat in South San Francisco Bay. During phase 1 of the South Bay Salt Pond Restoration Project, the breaching of several pond levees to begin the process of tidal marsh restoration inundated island nesting habitat that had been used by Forster’s terns, American avocets (Recurvirostra americana), and other waterbirds. Additional nesting habitat could be lost as more managed ponds are converted to tidal marsh in the future. To address this issue, the South Bay Salt Pond Restoration Project organized the construction of new nesting islands in managed ponds that will not be restored to tidal marsh, thereby providing enduring island nesting habitat for waterbirds. In 2012, 16 new islands were constructed in Pond A16 in the Alviso complex of the Don Edwards San Francisco Bay National Wildlife Refuge, which increased the number of islands in this pond from 4 to 20. However, despite a long history of nesting on the four islands in Pond A16 before the 2012 construction activities, no Forster’s terns have nested in Pond A16 during the 7-year period (2012–18) after island construction.
During the 2017 and 2019 breeding seasons, we used social attraction measures (decoys and colony call playback systems) to attract Forster’s terns to islands within Pond A16 to re-establish nesting colonies. We maintained these systems from March through August in each year. To evaluate the effect of these social attraction measures, we completed surveys (between April and August) where we recorded the number and location of all Forster’s terns and other waterbirds using Pond A16, and we monitored waterbird nests. We compared bird survey and nest monitoring data collected in 2017 and 2019 to data collected in 2015 and 2016, prior to the implementation of social attraction measures, allowing for direct evaluation of the effect of social attraction efforts on Forster’s terns.
To increase the visibility and stakeholder involvement of this project, we engaged in multiple outreach activities in 2017, 2019, and 2020, including the development of a project website and educational video; publication of popular articles in 2017 and 2020; the development of outreach materials describing the project to the general public; and public presentations to relay findings to managers, stakeholders, and the general public.
The relative abundance of Forster’s terns in Pond A16, after adjusting for the overall South San Francisco Bay breeding population each year, was higher during the nesting period in 2017 and 2019 (when social attraction was used) than in 2015 and 2016 (before social attraction was used). Furthermore, more Forster’s terns were observed during the pre-nesting and nesting periods in the areas of Pond A16 where decoys and call systems were deployed. Although no Forster’s tern nests were observed in Pond A16 before social attraction was implemented (2015, 2016), or during the first-year social attraction was implemented (2017), 35 Forster’s tern nests were recorded during the second year of social attraction implementation in 2019. These 35 nests represent a re-establishment of a Forster’s tern nesting colony to Pond A16 for the first time in 8 years. As social attraction efforts often benefit from multiple years of decoy and call system deployment, results from 2017 and 2019 suggest that continued implementation of social attraction measures could help to ensure Forster’s tern breeding colonies persist in Pond A16 and other areas of South San Francisco Bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201081","collaboration":"Prepared in cooperation with the San Francisco Bay Bird Observatory","usgsCitation":"Hartman, C.A., Ackerman, J.T., Herzog, M.P., Wang, Y., and Strong, C., 2020, Establishing Forster’s Tern (Sterna forsteri) nesting sites at pond A16 using social attraction for the South Bay Salt Pond restoration project: U.S. Geological Survey Open-File Report 2020–1081, 28 p., https://doi.org/10.3133/ofr20201081.","productDescription":"vii, 28 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-118152","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":376595,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1081/covrthb.jpg"},{"id":376596,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1081/ofr20201081.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.28057861328124,\n 37.40452830389465\n ],\n [\n -121.90155029296875,\n 37.40452830389465\n ],\n [\n -121.90155029296875,\n 37.55709809310769\n ],\n [\n -122.28057861328124,\n 37.55709809310769\n ],\n [\n -122.28057861328124,\n 37.40452830389465\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Strix occidentalis caurina (northern spotted owl; hereinafter referred to as spotted owl) have rapidly declined throughout the subspecies’ geographic range. Competition with invading Strix varia (barred owl) has been identified as an immediate cause of those declines. A pilot study in California showed that removal of barred owls coupled with conservation of suitable habitat conditions can slow or even reverse population declines of spotted owls. It is unknown, however, whether similar results can be obtained in areas with different forest conditions, greater densities of barred owls, and fewer remaining spotted owls. We used a before-after-control-impact experimental design on three study areas with long-term demographic information on spotted owls to determine if removal of barred owls can improve population trends of spotted owls. This report summarizes research accomplishments and initial results from the first 4.5 years (from March 2015 to August 2019) of implementing barred owl removal experiments in Washington and Oregon.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201089","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service, Bureau of Land Management, and U.S. Forest Service","usgsCitation":"Wiens, J.D., Dugger, K.M., Lesmeister, D.B., Dilione, K.E., and Simon, D.C., 2020, Effects of barred owl (Strix varia) removal on population demography of northern spotted owls (Strix occidentalis caurina) in Washington and Oregon—2019 annual report: U.S. Geological Survey Open-File Report 2020–1089, 19 p., https://doi.org/10.3133/ofr20201089.","productDescription":"iv, 19 p.","onlineOnly":"Y","ipdsId":"IP-117976","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":376560,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1089/coverthb2.jpg"},{"id":376531,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1089/ofr20201089.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1089"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.28906250000001,\n 46.483264729155586\n ],\n [\n -119.59716796875,\n 46.483264729155586\n ],\n [\n -119.59716796875,\n 47.54687159892238\n ],\n [\n -121.28906250000001,\n 47.54687159892238\n ],\n [\n -121.28906250000001,\n 46.483264729155586\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.99169921875,\n 43.723474896114794\n ],\n [\n -122.98095703125,\n 43.723474896114794\n ],\n [\n -122.98095703125,\n 44.824708282300236\n ],\n [\n -123.99169921875,\n 44.824708282300236\n ],\n [\n -123.99169921875,\n 43.723474896114794\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.21142578125,\n 42.47209690919285\n ],\n [\n -122.23388671874999,\n 42.47209690919285\n ],\n [\n -122.23388671874999,\n 43.24520272203356\n ],\n [\n -124.21142578125,\n 43.24520272203356\n ],\n [\n -124.21142578125,\n 42.47209690919285\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
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