For more than three decades, the U.S. Geological Survey (USGS) Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project has compiled paleoenvironmental data with the goal of reconstructing global conditions during the warm interval in the middle of the Piacenzian Age of the Pliocene Epoch (about 3.3 to 3.0 million years ago). Because this is the most recent interval of time in which climatic conditions were similar to those expected in the near future, a global reconstruction of conditions from this interval offers an imperfect yet useful representation of near future conditions. PRISM reconstructions have been used extensively as boundary conditions in general circulation model experiments aimed at better understanding Pliocene climate. They have also served as hindcasting targets when testing the ability of climate models to simulate real climates of the past, an exercise in estimating a model’s ability to accurately predict future climate. As data coverage has grown and model precision has improved, PRISM datasets have become important validation tools for pinpointing discrete areas of data-model disagreement and model-model disagreement. The Pliocene sea surface temperature (SST) dataset is the best developed component of the PRISM reconstructions and is the keystone of Pliocene paleoclimate research. For the first time, we compile all data related to PRISM SST estimation. This discussion chronicles the history of PRISM SST research as it evolved, responding to advances in paleochronology and paleotemperature estimation. Paleoclimatic considerations unique to each location are illustrated, as are any new developments since the initial publication of the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181148","usgsCitation":"Robinson, M.M., Dowsett, H.J., Foley, K.M., and Riesselman, C.R., 2018, PRISM marine sites—The history of PRISM sea surface temperature estimation: U.S. Geological Survey Open-File Report 2018–1148, 49 p., https://doi.org/10.3133/ofr20181148.","productDescription":"vi, 49 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087999","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":357306,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1148/ofr20181148.pdf","text":"Report","size":"1 MB","description":"OFR 2018-1148"},{"id":357305,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1148/coverthb3.jpg"}],"contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
926A National Center
Reston, VA 20192
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, to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey installed continuous data-collection stations to monitor discharge, salinity, and associated parameters at 22 sites prior to the commencement of dredging. The U.S. Geological Survey monitored stage and discharge at 13 sites, and water temperature, specific conductance, and salinity at 15 sites; some sites included all parameters.
This report contains information pertinent to the data collection sites from their installation date to September 2016, with additional information and data from Hurricane Matthew in October 2016. Site installations began in October 2015; all sites were installed and began collecting data by January 2016. All data available for each site after October 2015 are included in this report.
Discharge and salinity ranged widely during the data collection period, which included the effects of Hurricane Hermine in September 2016 and Hurricane Matthew in October 2016. Of the tributaries, annual mean discharge was greatest at Ortega River, followed by Cedar River, Julington Creek, Durbin Creek, and Clapboard Creek. Annual mean salinity for the main-stem sites indicates that salinity decreases with distance upstream, which is expected. The closest tributary site to the Atlantic Ocean (Clapboard Creek) produced the highest annual mean salinity of the tributaries, and Durbin Creek salinity was the lowest of all monitoring locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181108","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2018, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2016: U.S. Geological Survey Open-File Report 2018–1108, 28 p., https://doi.org/10.3133/ofr20181108.","productDescription":"viii, 28 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-086635","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":357273,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1108/coverthb.jpg"},{"id":357274,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1108/ofr20181108.pdf","text":"Report","size":"7.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1108"}],"country":"United States","state":"Florida","otherGeospatial":"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 -82,\n 29\n ],\n [\n -81,\n 29\n ],\n [\n -81,\n 30.5\n ],\n [\n -82,\n 30.5\n ],\n [\n -82,\n 29\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The 2014 update of the U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) for the conterminous United States (2014 NSHM; Petersen and others, 2014, 2015) included probabilistic ground motion maps for 2 percent and 10 percent probabilities of exceedance in 50 years, derived from seismic hazard curves for peak ground acceleration (PGA) and 0.2 and 1.0 second spectral accelerations (SAs) with 5 percent damping for the National Earthquake Hazards Reduction Program (NEHRP) site class boundary B/C (time-averaged shear wave velocity in the upper 30 meters [VS30]=760 meters per second [m/s]). We now provide uniform NEHRP site class maps for 2, 5, and 10 percent probabilities of exceedance in 50 years derived from hazard curves for additional spectral periods. For the central and eastern United States (CEUS) and western United States (WUS), hazard curves and maps for PGA, 0.1, 0.2, 0.3, 0.5, 1.0, and 2.0 second SAs are now available. The WUS additionally includes hazard curves and maps for 0.75, 3.0, 4.0, and 5.0 second SAs. The use of region-specific suites of weighted ground motion models (GMMs) in the 2014 NSHM precluded the calculation of ground motions for a uniform set of periods and site classes for the conterminous United States. At the time of the development of the 2014 NSHM, there was no consensus in the CEUS on an appropriate site-amplification model to use; therefore, we calculated hazard curves and maps for NEHRP site class A, for which most stable continental GMMs were originally developed, based on simulations for hard rock site conditions (VS30=2,000 m/s). In the WUS, however, the active crustal Next Generation Attenuation Relationships for the WUS (NGA-West2 GMMs) and subduction GMMs allow amplification of ground motions based on site class (defined by VS30); so we calculated hazard curves and maps for NEHRP site classes B (VS30=1,080 m/s), C (VS30=530 m/s), D (VS30=260 m/s), and E (VS30=150 m/s) and site class boundaries A/B (VS30=1,500 m/s), B/C (VS30=760 m/s), C/D (VS30=365 m/s), and D/E (VS30=185 m/s). The 2014 NSHM introduced a set of criteria for selecting GMMs for use in the NSHMs. When calculating additional period and site class maps, we verified whether the 2014 NSHM original suites of GMMs satisfied these ground motion selection criteria at all additional periods and site classes using GMM magnitude-distance scaling relation plots. Results of our analysis show that certain GMMs give unrealistic results at longer periods, distances, and softer soils in the WUS. In these rare instances, the GMM was removed from the original suite of GMMs (for all periods and site classes) and the weights of the remaining GMMs in the suite were renormalized. Ratio maps show these updated suites of weighted GMMs result in probabilistic ground motion changes of less than 10 percent in the WUS at PGA, as well as 0.2 and 1.0 second SAs, except in the Pacific Northwest, where differences as much as 20 percent are seen. Hazard curves and uniform hazard response spectra at test sites across the conterminous United States were produced to verify that results were reasonable. The additional period and site class maps, and the hazard curves from which they were derived, are available for download from the USGS ScienceBase Catalog.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181111","usgsCitation":"Shumway, A.M., Petersen, M.D., Powers, P.M., and Rezaeian, S., 2018, Additional period and site class maps for the 2014 National Seismic Hazard Model for the conterminous United States: U.S. Geological Survey Open-File Report 2018–1111, 46 p., https://doi.org/10.3133/ofr20181111.","productDescription":"Report: v, 46 p.; Data release","onlineOnly":"Y","ipdsId":"IP-098308","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":357217,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9I6BPX5","text":"USGS data release","linkHelpText":"Data Release for Additional Period and Site Class Maps for the 2014 National Seismic Hazard Model for the Conterminous United 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\"}}]}\n\n\n","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225
The ability of populations to persist and adapt to abiotic and biotic changes is reliant on genetic diversity. When connectivity across a species landscape is disrupted, the levels and distribution of genetic diversity can rapidly deteriorate as a result of genetic drift, leading to increased inbreeding and reduced adaptive potential. Therefore, understanding the distribution and degree of genetic variation within imperiled populations provides important information for conservation management and recovery strategies, especially when paired with translocation and repatriation programs. Here, we used genome-wide nuclear markers to study the population structure and genetic diversity from tissue samples collected between 2010 and 2016 of two threatened species of gartersnakes inhabiting the lower Colorado River Basin in the United States: Mogollon Narrow-headed gartersnake (Thamnophis rufipunctatus) and Northern Mexican gartersnake (Thamnophis eques megalops). Our specific objectives were to determine how populations inhabiting the lower Colorado River Basin were related to sister species and southern populations along the Sierra Madre Occidental in Mexico, to determine how genetic variation is partitioned among drainage basins in the lower Colorado River Basin, and to provide estimates of genetic diversity and effective sizes of sampled sites to aide species-specific conservation management of these threatened gartersnakes. For both species, we found that populations along the lower Colorado River Basin are highly differentiated from sister species and southern populations located further south in Mexico, and exhibit reduced genetic diversity relative to populations along the Sierra Madre Occidental. Within the lower Colorado River Basin, genetic analyses revealed highly structured genetic groups for both species of gartersnakes that point to shared contemporary and historical drivers of differentiation. We found that most sites throughout the lower Colorado River Basin have low genetic diversity and effective population sizes below the threshold required to retain adaptive potential. However, these trends were especially pronounced for T. rufipunctatus. If genetic management and translocation strategies are adopted in the future, these population genetic results can be used to highlight sites of particular concern and locate the most genetically similar sites for translocation or re-establishment efforts. Such measures could help curb further population genetic change, alleviate problems associated with low genetic diversity, and strengthen the adaptive potential across the range of these two gartersnake species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181141","collaboration":"Prepared for the U.S. Fish and Wildlife Service","usgsCitation":"Wood, D.A., Emmons, I.D., Nowak, E.M., Christman, B.L., Holycross, A.T., Jennings, R.D., and Vandergast, A.G., 2018, Conservation genomics of the Mogollon Narrow-headed gartersnake (Thamnophis rufipunctatus) and Northern Mexican gartersnake (Thamnophis eques megalops): U.S. Geological Survey Open-File Report 2018-1141, 47 p., https://doi.org/10.3133/ofr20181141.","productDescription":"Report: viii, 47 p.","onlineOnly":"Y","ipdsId":"IP-096783","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":356979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1141/coverthb_.jpg"},{"id":357008,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1141/ofr20181141_.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1141"}],"contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Changes in land-use practices and the extirpation (local extinction) of beaver populations in the early 20th century during European settlement are believed to have resulted in many changes in how streams in the Western United States function. Some of the negative changes that have resulted include stream channelization, soil erosion, changing vegetation, water turbidity, and a loss of overland flow. Efforts to restore streams and reduce soil erosion by water have included reintroductions of beaver, incorporating Native American traditional knowledge of dry-land farming techniques, and the installation of rigid check-dams. Many of these efforts have been successful in improving both intermittent and perennial stream function. Therefore, stakeholders in the Southern Rockies Landscape Conservation Cooperative (SRLCC) have identified a need to prioritize streams within their region of interest for the installation of check-dams to continue restoration and conservation efforts and to improve sediment catchment.
Using Natural Resource Conservation Service soil databases, topographic features derived from digital elevation models, stream networks, and regional climatic patterns, I developed a ranking system for watershed potential erosion rates and suitability for check-dam placement across the SRLCC. This ranking system serves as a first step for land managers to prioritize areas for check-dam installation based on relatively static factors (soil properties, topography, and hydrology) that can contribute to rates of soil erosion by water and the stability of check-dams. Many other relatively dynamic factors over time can contribute to rates of soil erosion by water, such as recent wildfire events, changes in weather patterns and extreme climate events, and changing land-use such as grazing, logging, mining, development, and cultivation. These factors that influence vegetative and biological soil crusts cover are also important elements to the potential erosion of soil by water. Because of this, SRLCC stakeholders might consider further evaluation of the watersheds identified here as high ranking. Final watershed prioritization among the high-ranking watersheds identified here should include current knowledge of land-use and land-cover estimates to identify areas at risk for soil erosion or degree of existing erosion problems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181127","usgsCitation":"Ironside, K.E., 2018, Southern Rockies Landscape Conservation Cooperative unit watershed erosion potential prioritization for check-dam installation: U.S. Geological Survey Open-File Report 2018–1127, 15 p., https://doi.org/10.3133/ofr20181127.","productDescription":"Report: v, 15 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-096570","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":356855,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SEUC93","text":"Data release","description":"USGS Data Release","linkHelpText":"Watershed potential erosion rate ranking system and check-dam placement suitability data within the Southern Rockies Landscape Conservation Cooperative (SRLCC)"},{"id":356853,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1127/coverthb.jpg"},{"id":356854,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1127/ofr20181127.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1127"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.173197,\n 32.416412\n ],\n [\n -103.499364,\n 32.416412\n ],\n [\n -103.499364,\n 43.335375\n ],\n [\n -116.173197,\n 43.335375\n ],\n [\n -116.173197,\n 32.416412\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff,
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Earthquake early warning (EEW) is the rapid detection of an earthquake and issuance of an alert or notification to people and vulnerable systems likely to experience potentially damaging ground shaking. The level of ground shaking that is considered damaging is defined by the specific application; for example, manufacturing equipment may experience damage at a lower intensity ground shaking than would cause damage to a building. Along the West Coast of the United States, the warning times for ground shaking could range as high as tens of seconds for moderate levels of ground shaking, or potentially longer, if a lower ground-shaking threshold is used to issue alerts. However, it is not always possible to provide advance warning of ground shaking, particularly for locations close to an earthquake that are most likely to experience very strong ground shaking. EEW alerts may be useful to individuals who can use a few seconds to move to a safe zone and to electromechanical systems that can take automatic actions to reduce damage and injuries. An EEW system, ShakeAlert, has been under development in the United States since 2006. Federal and State governments, as well as the private sector, are now investing in the ShakeAlert prototype system that will, when completed, become an operational public system for the West Coast of the United States.
While the current prototype is delivering alerts to test users, improvements to the accuracy, timeliness, and utility of the alerts are needed. For this reason, it is essential that the ShakeAlert system be continuously improved through targeted research, involving not only the current ShakeAlert partner organizations, but also the broader scientific, engineering, and emergencyresponse communities. To this end, this report describes the opportunities for improvement that can be addressed through research and development over the next 5 years.
Our recommendations are organized into four areas: (1) understand EEW capabilities and user needs, (2) make alerts as fast and accurate as possible, (3) ensure reliability when it counts, and (4) explore the use of new instrumentation.
The first challenge is to understand EEW capabilities and user needs. EEW must deliver actionable information to people and to automated systems to mitigate short- and longterm impacts of damaging ground shaking, so development of EEW must be motivated by the needs of users. Within this challenge, we must study the technical capabilities and limitations of EEW in general, and the ShakeAlert system specifically. This includes development of performance metrics that assess the timeliness and accuracy of alerts to understand the value and utility of the ShakeAlert EEW product(s) for various user groups, including different industry sectors, emergency-management agencies, and the public. Research is needed to define the alerting choices that maximize the utility of the system for users and to determine what the available communication pathways are for providing timely alert information. Additionally, we engage users to assess how alerts will be used by different sectors to mitigate losses and to inform EEW product design. Further, social-science research is needed to develop alert messaging, including what relevant prior and follow-up information are required, to ensure effective use of alerts.
The second challenge is to make alerts as fast and as accurate as possible. The timeliness and accuracy of an EEW alert is important because it will set in motion a series of actions and downstream products. An EEW alert will trigger notification across emergency-alert systems and across multiple communication channels to populations in impacted regions. The EEW alert region may grow as the earthquake fault-rupture length increases, and the EEW system’s characterization of it, evolves. We must continue research into new or improved seismic and geodetic waveform-processing methods necessary to rapidly characterize the expected ground shaking and associated uncertainties. It is important to thoroughly evaluate whether new methods improve alerts through more accurate ground-motion estimates and (or) reduced latencies (that is, longer warning times). New methods could include tracking the extent of a large rupture in real time (known as finite-fault algorithms) and ground-motionbased EEW algorithms. Additionally, ground motion predictions could be optimized for each earthquake as the earthquake fault rupture progresses by using, for example, event terms to shift ground-motion curves for more (or less) energetic ruptures.
The third challenge is to ensure reliability when it counts. This challenge requires us to explore approaches that assess the expected performance of ShakeAlert across the range of earthquake magnitudes, locations, and depths that may occur within the alerting region. Large, damaging earthquakes and their associated aftershock sequences matter most for hazard and for EEW, but these large-earthquake sequences occur infrequently. We expect ShakeAlert to respond robustly to these large-earthquake sequences despite potentially long periods of relative seismic quiescence in the intervening years, and in spite of inevitable communication challenges that arise during and after a large earthquake. We must develop methods to utilize the broadest available datasets to test EEW performance, including ground-motion data recorded in other parts of the world. The observational period for large, damaging earthquakes in any particular region has been short in comparison to estimated large-earthquake recurrence times. Ground-motion records for very large, damaging western United States events and major aftershock sequences do not yet exist, nor do data exist for all potential sources of noise and spurious signals that ShakeAlert must be “tuned” to reject. In addition, robust synthetic data could provide the flexibility to test a wider range of earthquake magnitude, tectonic-setting, and noise scenarios than are covered by existing observational data. Synthetic ground-motion data must be thoroughly vetted against records of smaller magnitude earthquakes to ensure that they accurately capture both the onset and the amplitude of the ground shaking.
The final challenge is to explore the use of new instrumentation. The development of EEW around the world to date has focused on the use of high-quality, scientific-grade seismic and geodetic instrumentation. The use of additional types of instrumentation or information may also improve EEW products by filling gaps in sensor coverage in countries that already have dense seismic networks or enable EEW in countries without such networks. We must keep up with these developments and continuously assess their value in supplementing existing EEW systems, such as ShakeAlert, or enabling EEW where such systems do not exist. Such developments include low-cost instrumentation with microelectromechanical system (MEMS) sensors and global positioning system (GPS)/global navigation satellite system (GNSS) antennas embedded in low-cost consumer electronics, sea-floor seismometers, geodetic instrumentation deployed along the Cascadia and Alaska megathrust margins of western North America, and borehole strainmeters that are already deployed across the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181131","usgsCitation":"Cochran, E.S., Aagaard, B.T., Allen, R.M., Andrews, J., Baltay, A.S., Barbour, A.J., Bodin, P., Brooks, B.A., Chung, A., Crowell, B.W., Given, D.D., Hanks, T.C., Hartog, J.R., Hauksson, E., Heaton, T.H., McBride, S., Meier, M-A., Melgar, D., Minson, S.E., Murray, J.R., Strauss, J.A., and Toomey, D., 2018, Research to improve ShakeAlert earthquake early warning products and their utility: U.S. Geological Survey Open-File Report 2018–1131, 17 p., https://doi.org/10.3133/ofr20181131.","productDescription":"iv, 17 p.","onlineOnly":"Y","ipdsId":"IP-098968","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":356971,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1131/coverthb.jpg"},{"id":356972,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1131/ofr20181131.pdf","text":"Report","size":"600 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1131"}],"contact":"Earthquake Science Center-Pasadena Field Office
U.S. Geological Survey
525 South Wilson Ave.
Pasadena, CA 91106-3212
This chapter presents information pertinent to the geologic carbon dioxide (CO2) sequestration potential within saline aquifers located in the Atlantic Coastal Plain and Eastern Mesozoic Rift Basins of the Eastern United States. The Atlantic Coastal Plain is underlain by a Jurassic to Quaternary succession of sedimentary strata that onlap westward onto strata of the Appalachian Piedmont physiographic province and generally thicken eastward toward the present-day Atlantic coastline and onto the present-day continental shelf. Although no significant petroleum discoveries have been made on the coastal plain, the deep saline aquifers of the region appear to contain porous strata (potential reservoirs, or “storage formations”) that are overlain by fine-grained, laterally continuous strata (potential seals), which are prospective CO2 sequestration targets. For the Atlantic Coastal Plain, we identify two storage assessment units (SAUs), both of which consist of Cretaceous strata. The two SAUs are the Lower Cretaceous Composite SAU C50700101 and the Upper Cretaceous Composite SAU C50700102.
The Eastern Mesozoic Rift Basins are a chain of generally southwest- to northeast-trending, elongate sedimentary basins that either underlie the Atlantic Coastal Plain or crop out within adjacent geologic provinces to the west. Similar to the Atlantic Coastal Plain, there has been no significant oil and gas production from any of the basins, although there is a proven petroleum system in several of them. At least three of these basins appear to contain potential storage formations overlain by potential seal units. Most of the other basins were not assessed because a storage and (or) seal formation could not be established in the timeframe of the assessment, often because of the paucity of subsurface data for these basins in comparison to other petroliferous basins of the United States. Thus, we present information supporting one quantitative assessment in the Newark basin, as well as information supporting two nonquantitative assessments, one for strata in the Gettysburg basin and the other for strata in the Culpeper basin. We briefly discuss six other basins within the Eastern Mesozoic Rift Basins that were not assessed.
For all SAUs, we discuss the areal distribution of suitable CO2 reservoir rock. We also describe the overlying sealing unit and the geologic characteristics that influence the potential CO2 storage volume and reservoir characteristics. These characteristics include storage formation depth, gross thickness, net thickness, porosity, permeability, and groundwater salinity. Case-by-case strategies for estimating the pore volume existing within structurally and (or) stratigraphically closed traps are presented. Although assessment results are not contained in this chapter, the geologic information included herein was used to calculate the potential storage space in the SAUs.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geologic framework for the national assessment of carbon dioxide storage resources","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121024N","usgsCitation":"Craddock, W.H., Merrill, M.D., Roberts-Ashby, T.L., Brennan, S.T., Buursink, M.L., Drake, R.M., II, Warwick, P.D., Cahan, S.M., DeVera, C.A., Freeman, P.A., Gosai, M.A., and Lohr, C.D., 2018, Geologic framework for the national assessment of carbon dioxide storage resources—Atlantic Coastal Plain and Eastern Mesozoic Rift Basins, chap. N of Warwick, P.D., and Corum, M.D., eds., Geologic framework for the national assessment of carbon dioxide storage resources: U.S. Geological Survey Open-File Report 2012–1024, 32 p., https://doi.org/10.3133/ofr20121024N.","productDescription":"Report: vi, 32 p.; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082323","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":356831,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2012/1024/n/ofr20121024n_acp-cell-c5070.zip","text":"Atlantic Coastal Plain Well Density","size":"1.77 GB","linkFileType":{"id":6,"text":"zip"}},{"id":356832,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2012/1024/n/ofr20121024n_emrb_sau-c5068.zip","text":"Eastern Mesozoic Rift Basins Storage Assessment Units","size":"1.77 GB","linkFileType":{"id":6,"text":"zip"}},{"id":356833,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2012/1024/n/ofr20121024n_emrb-cell-c5068.zip","text":"Eastern Mesozoic Rift Basins Well Density","size":"1.77 GB","linkFileType":{"id":6,"text":"zip"}},{"id":356830,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2012/1024/n/ofr20121024n_acp-sau-c5070.zip","text":"Atlantic Coastal Plain Storage Assessment Units","size":"1.77 GB","linkFileType":{"id":6,"text":"zip"}},{"id":356407,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2012/1024/n/coverthb.jpg"},{"id":356408,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1024/n/ofr20121024n.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2012 1024 N"}],"country":"United States","otherGeospatial":"Atlantic Coastal Plain and Eastern Mesozoic Rift Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.72607421875,\n 27.235094607795503\n ],\n [\n -71.34521484375,\n 27.235094607795503\n ],\n [\n -71.34521484375,\n 42.71473218539458\n ],\n [\n -86.72607421875,\n 42.71473218539458\n ],\n [\n -86.72607421875,\n 27.235094607795503\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Energy Resources Program
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
Email: gd-energyprogram@usgs.gov
Zebra mussels (Dreissena polymorpha, Pallas, 1771) are an aquatic invasive species in the
United States, and new infestations of zebra mussels can rapidly expand into dense colonies. Zebra
mussels were first reported in Marion Lake, Dakota County, Minnesota, in September 2017, and
surveys indicated the infestation was likely isolated near a public boat access. A 2.4-hectare area
containing the known zebra mussel infestation was enclosed and treated by area resource managers for
9 days with EarthTec QZ (target concentration: 0.5 milligrams per liter as copper), a copper-based
molluscicide, to eradicate the zebra mussels. Researchers led an onsite bioassay to provide an estimate
of the treatment efficacy within the enclosure. The bioassay was conducted in a mobile assay trailer that
received a continuous flow of treated lake water. Bioassay tanks (n=9; 350 liters) within the trailer were
stocked with zebra mussels (25 mussels per containment bag; 7 bags per tank) collected from White
Bear Lake, Ramsey County, Minn. Mortality in the treated bioassay tanks reached a mean of 99 percent
(95-percent confidence interval: 98–100 percent), there were no mortalities in the control tanks.
However, a predictive model produced for timely delivery to area resource managers indicated zebra
mussel mortality within the treated enclosure may have been as low as 85 percent. Onsite bioassays are
a viable and important tool for treatment evaluation particularly in newly infested waterbodies with low
zebra mussel densities.
Director, Upper Midwest Environmental Science Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
Mercury (Hg) analyses were conducted on samples of water and sport fish collected from selected sampling sites in the Boise and Snake Rivers and Brownlee Reservoir, in Idaho and Oregon, to meet National Pollution Discharge and Elimination System permit requirements for the City of Boise, Idaho, from 2013 to 2017. City of Boise personnel collected water samples from six sites in October and November of 2013, 2015 and 2017, and sampled one site in 2014 and 2016. Total Hg concentrations in unfiltered water samples ranged from 0.41 to 8.78 nanograms per liter (ng/L), with the highest value (8.78 ng/L) observed in Brownlee Reservoir in 2013. All samples were less than the U.S. Environmental Protection Agency aquatic life criterion of 12 ng/L.
Individual fillets of mountain whitefish (Prosopium williamsoni), rainbow trout (Oncorhynchus mykiss), smallmouth bass (Micropterus dolomieu), and channel catfish (Ictalurus punctatus) were collected and analyzed for Hg. The tissue Hg concentrations were compared with regulatory or advisory values for wet-weight methylmercury in fish tissue. In this report, methylmercury concentrations in fish tissue are considered similar to total Hg in fish muscle tissue and are simply referred to as Hg. The 2013 average Hg concentration for smallmouth bass (0.32 mg/kg) collected at Brownlee Reservoir and for channel catfish (0.33 mg/kg) collected at the Boise River mouth, exceeded the Idaho water quality criterion (>0.3 mg/kg). The 2017 Hg concentrations in smallmouth bass from Brownlee Reservoir (geometric mean of 0.22 mg/kg) was at the Idaho Fish Consumption Advisory Program action level.
Selenium (Se) interacts with Hg to reduce the health risks of Hg, such that tissues with Se-to-Hg molar ratios greater than 1 are considered to present less potential health risks for a given Hg concentration than are tissues with lower Se-to-Hg ratios. One composite fish tissue sample per site was analyzed for Se. Selenium-to-Hg molar ratios in the fish tissue samples ranged from 0.99 to 24.7.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181122","collaboration":"Prepared in cooperation with the City of Boise, Idaho","usgsCitation":"MacCoy, D.E., and Mebane, C.A., 2018, Mercury concentrations in water and mercury and selenium concentrations in fish from Brownlee Reservoir and selected sites in the Boise and Snake Rivers, Idaho and Oregon, 2013-17: U.S. Geological Survey Open-File Report 2018-1122, 37 p., https://doi.org/10.3133/ofr20181122.","productDescription":"iv, 37 p.","onlineOnly":"Y","ipdsId":"IP-091972","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":356923,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1122/coverthb.jpg"},{"id":356924,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1122/ofr20181122.pdf","text":"Report","size":"7.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1122"}],"country":"United States","state":"Idaho, Oregon","otherGeospatial":"Boise River, Brownlee Reservoir, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.27081298828125,\n 43.241201214257885\n ],\n [\n -116.0540771484375,\n 43.241201214257885\n ],\n [\n -116.0540771484375,\n 44.40827836571936\n ],\n [\n -117.27081298828125,\n 44.40827836571936\n ],\n [\n -117.27081298828125,\n 43.241201214257885\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
A Delft3D model was developed to evaluate the potential effects of proposed navigation
channel deepening and widening in Mobile Harbor, Alabama. The model performance was
assessed through comparisons of modeled and observed data of water levels, velocities, and bed
level changes; the model captured hydrodynamic and sediment transport patterns in the study
area with skill. The validated model was used to simulate changes in sediment transport for existing
conditions and with the proposed modifications to the navigational channel (with-project),
with and without accounting for 0.5 meter (m) of sea level rise (SLR). Each scenario was simulated
for 1 year with a wave climatology representative of the year 2010 as well as for 10 years
with a longer-term wave climatology spanning from 1988 to 2016. Bed level differences for the
existing and with-project 2010 simulations were minimal, ranging from −0.11 to 0.11 m offshore
of Pelican Island and −0.81 to 0.22 m offshore of the Fort Morgan Peninsula. For the simulations
accounting for 0.5 m of SLR, differences in bed levels from −0.20 to 0.32 m near Pelican
Island and −0.38 to 0.34 m offshore of the Fort Morgan Peninsula. The proposed modifications
reduced the channel shoaling volume by 4.77 and 8.09 percent for the 2010 simulations without
and with 0.5 m of SLR, respectively. For the 10-year simulations, bed level differences for the
existing and with-project simulations ranged from −3.17 to 3.94 m for the simulation without
SLR and −1.92 to 1.47 m for the simulation with 0.5 m of SLR. The with-project condition reduced
the entrance channel shoaling volume by 5.54 percent for the simulation without SLR and
14.98 percent for the simulation with 0.5 m of SLR.
Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Sea-Bird Scientific’s HydroCycle-PO4 phosphate sensor is a single-analyte wet-chemistry sensor designed for in situ environmental monitoring. The unit was evaluated at the U.S. Geological Survey Hydrologic Instrumentation Facility to assess the accuracy of the sensor in solutions with known phosphorous concentration and to test the effects of chromophoric (colored) dissolved organic matter (CDOM) and natural water matrixes on sensor accuracy. Accuracy was tested with three standards: 0.110, 0.174, and 0.260 milligram per liter, as phosphorous (mg/L as P). The 0.110- and 0.260-mg/L standards were made from a dilution of a National Institute of Standards and Technology-traceable phosphate-phosphorous standard with Type I deionized water (DIW). Average measured phosphate concentrations of the tested standards (0.110, 0.174, and 0.260 mg/L as P) in DIW were 0.132, 0.181, and 0.310 mg/L as P, for differences of 20, 4, and 19 percent, respectively.
Measured phosphate concentration of a tested standard was biased by the addition of tea water filtered through a 0.45-micrometer pore size filter (filtered tea water [FTW]) simulating the effect of CDOM. An aliquot of the filtered tea solution was sent to a certified environmental laboratory, which reported a less than reporting level (<0.004 mg/L as P) phosphate concentration. True color of the FTW was measured at 380 platinum-cobalt units by using Standard Methods 8025. For this FTW test, the measured phosphate concentration for the clear 0.260 mg/L as P standard averaged 0.366 mg/L as P. This concentration increased to an average of 0.653 mg/L as P with the addition of 10 percent FTW, and to an average of 0.859 mg/L as P with the addition of 20 percent FTW. These test results indicate a positive bias of up to 40 percent of the concentrations of the measured phosphate concentrations when CDOM is present and indicate a proportional increase in an apparent concentration of phosphorus instrument response as CDOM concentration increases.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181120","usgsCitation":"Snazelle, T.T., 2018, Laboratory evaluation of the Sea-Bird Scientific HydroCycle-PO4 phosphate sensor: U.S. Geological Survey Open-File Report 2018–1120, 10 p., https://doi.org/ofr20181120.","productDescription":"vi, 10 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-090916","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":356807,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1120/coverthb5.jpg"},{"id":356711,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1120/ofr20181120.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1120"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
Since the early 1990s, substantial effort and funding have been expended to conduct research to guide development of a 20-year Elk and Vegetation Management Plan for Rocky Mountain National Park (RMNP) in Colorado. One goal of the plan is to maintain the elk (Cervus elaphus) population size at the lower end of the natural range of variation. To implement management actions called for in the plan, accurate and reliable population estimates are needed, as well as a better understanding of the spatial and temporal distribution of elk. The previous aerial survey protocol and population estimation model used by the park had not been updated since the model’s initial calibration more than 15 years ago and the model was developed with an insufficient number (n=44) of observations. Thus we initiated research to reevaluate, update, and improve elk population estimation protocols for RMNP.
We considered several alternative survey and analysis methods, and concluded that a hybrid population-estimation model using a simultaneous double-observer technique with sighting covariates was the most appropriate and effective aerial survey methodology for this population and the environmental conditions in RMNP. Instructional protocols for conducting these surveys in the future, along with datasheets, are provided in this report’s appendixes.
To develop an improved method for aerial elk surveys, we used elk radio-collar location data from our study and other studies, and applied geographic information system analyses to define the survey area and develop effective, repeatable survey transect lines. We used telemetry data from radio-collared elk to inform our understanding of the temporal and spatial scale of elk movements across the park boundary, elk use of tree cover during potential survey hours, and elk use of different elevations within their range. Determining where elk were during surveys helped to fine-tune a survey design that improved spatial cover-age and decreased costs where possible, while standardizing the method to make it repeatable from year to year. We conducted aerial helicopter surveys to test our methodology in an adaptive, iterative process during three winters: 2007–2008, 2008–2009, and 2009–2010. We gained new information on each survey and used results to refine subsequent surveys.
Our results confirm that elk movements were highly dynamic with respect to park boundary crossings; an average of six round trips from the park to Estes Park, Colorado, and back per month were taken by global positioning system-collared bull elk. We observed a strong diurnal temporal pattern of bull elk use of trees; elk were found in dense tree cover from 15:00−22:00 but not as often during morning and early afternoon hours when surveys were conducted. We used information on elk use of different altitudes to refine and establish a more efficient survey area.
During the time of our study, a concurrent study in the park deployed 120 very high frequency radio collars on elk cows. We used those collar locations during our flights to increase sample size and to evaluate the level of precision we would gain by using “known fates analysis” (in which elk were known to be in the survey area, out of the survey area, or deceased based on radio-collar locations collected simultaneously during aerial surveys). Using radio-collar locations reduced bias by 1.1–8.8 percent and increased precision (that is, reduced the width of confidence intervals). This report provides final population estimates analyzed with and without radio-collar data to demonstrate what is gained by using marked individuals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181085","collaboration":"Prepared in cooperation with Colorado State University and the National Park Service","usgsCitation":"Schoenecker, K.A., Lubow, B.C., and Johnson, T.L., 2018, Development of an aerial population survey method for elk (Cervus elaphus) in Rocky Mountain National Park, Colorado: U.S. Geological Survey Open–File Report 2018–1085, 45 p., https://doi.org/10.3133/ofr20181085.","productDescription":"vii, 45 p.","onlineOnly":"Y","ipdsId":"IP-053382","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":356646,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1085/ofr20181085.pdf","text":"Report","size":"10.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1085"},{"id":356645,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1085/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Estes Valley, Rocky Mountain National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 40\n ],\n [\n -105.1667,\n 40\n ],\n [\n -105.1667,\n 40.5833\n ],\n [\n -106,\n 40.5833\n ],\n [\n -106,\n 40\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 Coastal and Marine Geology Program uses three methods to derive a datum-based, mean high water shoreline on open-ocean coasts from light detection and ranging (lidar) elevation surveys. This work compared the shorelines produced by the three methods for two different surveys: one survey with simple beach morphology, and one survey with complex beach morphology. For the survey with simple beach morphology, the three methods gave very similar results. The mean differences were less than 0.1 meter, and the root mean square differences were all less than 1.0 meter. For the survey of a beach with complex morphology, the quality control used in the Profile method and Smoothed Contour/Manual Hybrid method produced cleaner shorelines than the Grid method. Only the Profile method can extrapolate if there is no data around mean high water. The Grid and Profile methods produce a point by point estimate of uncertainty which is needed for some applications. Only the Contour method can be easily transferred to external users.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181121","usgsCitation":"Farris, A.S., Weber, K.M., Doran, K.S., and List, J.H., 2018, Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data: U.S. Geological Survey Open-File Report 2018–1121, 13 p., https://doi.org/10.3133/ofr20181121.","productDescription":"iv, 13 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-097675","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":356712,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1121/coverthb.jpg"},{"id":356713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1121/ofr20181121.pdf","text":"Report","size":"977 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1121"}],"contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
To address the 2008/2010 and Supplemental 2014 National Oceanic and Atmospheric Administration Fisheries Biological Opinion for operation of the Federal Columbia River Power System, the U.S. Army Corps of Engineers (USACE) and the Bureau of Reclamation (Reclamation) developed and began implementation of Caspian tern (Hydroprogne caspia) management plans. This implementation includes redistribution of the Caspian terns in the Columbia River estuary and the mid-Columbia River region to reduce predation on salmonids listed under the Endangered Species Act. Key elements of the plans are (1) reduction of nesting habitat for Caspian terns in the Columbia River estuary and the mid-Columbia River region, and (2) creation or modification of nesting habitat at alternative sites within the Caspian tern breeding range. As part of this effort, USACE and Reclamation developed Caspian tern nesting habitat at the U.S. Fish and Wildlife Service Don Edwards San Francisco Bay National Wildlife Refuge (DENWR), California, prior to the 2015 nesting season. Furthermore, nesting habitat for western snowy plovers (Charadrius alexandrinus nivosus) also was developed to provide separate nesting opportunities in the same managed ponds to reduce potential conflicts with Caspian terns. Specifically, seven recently constructed islands within two managed ponds (Ponds A16 and SF2) of DENWR were modified to provide habitat attractive to nesting Caspian terns (5 islands) and snowy plovers (2 islands). These 7 islands were a subset of 46 islands recently constructed in Ponds A16 and SF2 to provide waterbird nesting habitat as part of the South Bay Salt Pond (SBSP) Restoration Project.
We used social attraction methods (decoys and electronic call systems) to attract Caspian terns and snowy plovers to these seven modified islands, and conducted surveys from March to September of 2015, 2016, and 2017 to evaluate nest numbers, nest density, and productivity. Results from the 2015 nesting season, the first year of the study, indicated that island modifications and social attraction measures were successful in establishing Caspian tern breeding colonies at Ponds A16 and SF2 of DENWR. Prior to 2015, there was no history of Caspian terns nesting in either Pond A16 or Pond SF2. The success of 2015 continued in 2016 and 2017. In 2017, the third and final year of the project, Caspian terns initiated at least 664 nests, fledged at least 239 chicks, and had a breeding success rate of 0.36 fledged chicks per breeding pair. This represents a 171 percent increase in the number of breeding pairs and a 41 percent increase in the number of chicks fledged, but a 48 percent decrease in the fledglings produced per breeding pair in 2017 compared to 2015, the first year the colonies were established. The two new large and growing Caspian tern nesting colonies at Ponds A16 and SF2 demonstrate the effectiveness of social attraction measures in helping to establish tern nesting colonies in San Francisco Bay. Social attraction measures similar to those used in this study, but targeting other colonial species such as Forster’s terns (Sterna forsteri) and American avocets (Recurvirostra americana), may help to establish waterbird breeding colonies at wetlands enhanced as part of the SBSP Restoration Project.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181136","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and the Bureau of Reclamation","usgsCitation":"Hartman, C.A., Ackerman, J.T., Herzog, M.P., Strong, C., Trachtenbarg, D., and Shore, C.A., 2018, Social attraction used to establish Caspian tern (Hydroprogne caspia) nesting colonies on modified islands at the Don Edwards San Francisco Bay National Wildlife Refuge, California—Final report: U.S. Geological Survey Open-File Report 2018-1136, 41 p., https://doi.org/10.3133/ofr20181136.","productDescription":"vi, 41 p.","onlineOnly":"Y","ipdsId":"IP-096017","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":356703,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1136/coverthb.jpg"},{"id":356704,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1136/ofr20181136.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1136"}],"country":"United States","state":"California","otherGeospatial":"Don Edwards San Francisco Bay 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 -122.30667114257812,\n 37.38488959341307\n ],\n [\n -121.87889099121092,\n 37.38488959341307\n ],\n [\n -121.87889099121092,\n 37.637616213035884\n ],\n [\n -122.30667114257812,\n 37.637616213035884\n ],\n [\n -122.30667114257812,\n 37.38488959341307\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
In their recently published report, State of the Mountain Lion: A Call to End Trophy Hunting of America’s Lion, the Humane Society of the United States suggested that mountain lion (Puma concolor) hunting should be abolished in the United States. The report claims this recommendation is based on scientific arguments that demonstrate the overharvest of mountain lions throughout much of their current range in the United States. We reviewed the science presented by the Humane Society to support their call for the cessation of mountain lion hunting. Rather than provide a rigorous assessment of the peer-reviewed scientific literature and available data on mountain lion ecology, population dynamics and management, the report uses a fundamentally unscientific approach that starts with an a priori assumption that hunting is detrimental to the long-term persistence of mountain lion populations, then attempts to use scientific arguments to support this value-based position. The report frequently ignores or selectively interprets relevant peer-reviewed literature, weakening the scientific credibility of the report. The report relies on imprecise and inadequate demographic measures, questionable data, and simplistic methodologies to derive dubious estimates of potential lion densities; it compares these estimates to various measures produced by State agencies (which themselves vary in reliability as estimates of abundance) to purportedly illustrate the detrimental effects of hunting. The approach used in the report to support the predetermined supposition that mountain lion populations are over-hunted fails to serve as a scientifically defensible foundation for management recommendations range-wide or at the State level.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181128","usgsCitation":"Cain, J.W., III, and Mitchell, M.S., 2018, Evaluation of key scientific issues in the report, “State of the mountain lion—A call to end trophy hunting of America’s lion”: U.S. Geological Survey Open-File Report 2018-1128, 14 p., https://doi.org/10.3133/ofr20181128.","productDescription":"iv, 14 p.","onlineOnly":"Y","ipdsId":"IP-098716","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356705,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1128/coverthb.jpg"},{"id":356706,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1128/ofr20181128.pdf","text":"Report","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1128"}],"contact":"Leader, Washington Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
Fishery Sciences Building, Box 355020
University of Washington
Seattle, Washington, 98195
The U.S. Geological Survey (USGS) uses Maintenance of Variance Extension Type 1 (MOVE.1) regression to transfer streamflows measured at long-term continuous-record streamgaging stations to partial-record (PR) streamgaging stations where intermittent base-flow measurements are available. MOVE.1 regression is used widely throughout the hydrologic community to extend historic low flows and low-flow statistics at continuous-record streamgaging stations to streamgaging stations that have access to only a partial record of low flows. The method correlates base-flow measurements at PR streamgaging stations with daily mean streamflows measured at index stations that exhibit similar streamflow characteristics.
Following changes in the computing platform for storing, processing, retrieving, and publishing National Water Information System (NWIS) hydrologic data, legacy Statistical Analysis System (SAS) code developed by the USGS to implement the MOVE.1 regression was no longer suitable for reading and processing NWIS streamflow data. To migrate the MOVE.1 program so that it could continue to read streamflow data using the new hydrologic data platform, the SAS code was re-written in R, an open source programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The work described in this report was performed in a study conducted by USGS in cooperation with the New Jersey Department of Environmental Protection.
During migration from SAS to R, graphical and tabular output generated by the R script was compared to output produced by the legacy SAS code to ensure that equations used to perform the MOVE.1 regression remained the same. An option to perform censored MOVE.1 regression was added to extend the MOVE.1 methodology to cases where one or more measured continuous-record or PR streamgaging station flows are zero valued. In addition to permitting censored regression, the new R script includes an option to perform piecewise MOVE.1 regression when the relation between PR station and index station low flows varies significantly across the range of index station streamflows.
Together with traditional MOVE.1 regression, censored, and piecewise MOVE.1 regression methods implemented by the R script offer less biased estimates than ordinary least squares regression for the annual 7-day 10-year and other low-flow statistics at PR stations for a range of base-flow conditions. The R script is used to implement the MOVE.1 regression methods across a variety of computing platforms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181089","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Colarullo, S.J., Sullivan, S.L., and McHugh, A.R., 2018, Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey: U.S. Geological Survey Open-File Report 2018–1089, 20 p., https://doi.org/10.3133/ofr20181089.","productDescription":"v, 20 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-089567","costCenters":[{"id":470,"text":"New Jersey Water Science 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Jersey\",\"nation\":\"USA \"}}]}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The availability of cold-water refugia during summertime river-water temperature maximums is important for cold-water fish species including Endangered Species Act listed salmonids since water temperature influences metabolism, growth, and phenology. The U.S. Geological Survey monitored water temperature at 10 sites approximately evenly-spaced along the lower Quinault River on the Olympic Peninsula, Washington, from June 2016 to August 2017 to assess thermal conditions in the lower river. During this 15-month period, there was a near-continuous, 15-minute record at 7 of the sites; complications with thermistors at 3 of the 10 sites limited the temperature dataset to include only summer 2016. In addition, near-streambed and water-surface temperatures were measured along the lower river during a longitudinal survey from August 9 to 12, 2016, during summer baseflow conditions to potentially identify cold or cooler water regions. Measured August water temperatures were warmer than model-predicted August temperatures for the period, 1993–2011. Summertime (July–September) daily minimum temperatures exceeded established salmon habitat threshold temperatures of 16 °C (core summer season) and 17.5 °C (spawning, rearing, and migration periods) for 122 and 65 days, respectively, on average at all monitoring sites with a complete 15-month record that included two summer baseflow periods. Summertime water temperatures at those sites were generally cooler in the downstream direction along the lower Quinault River but became warmer in the downstream direction during the rest of the year, suggesting the river was influenced by diffuse discharge of groundwater with a relatively constant annual temperature. The August longitudinal temperature survey did not detect cold-water refugia (features more than 3 °C cooler than ambient stream water), although it did identify 11 cooler water features (CWF) approximately 100–800 m in length that were 0.1 °C cooler than adjacent upstream or downstream water. The CWFs appeared to correspond to local geomorphic conditions. In August 2017, 10 of the 11 CWFs were field surveyed, and 5 appeared to be influenced by shading from solar radiation by riparian vegetation or steep cliff banks. In addition, field observations suggest that finer scale (that is, less than 10 m) CWFs, specifically individual side pools associated with large, in-channel wood, increased in frequency in the downstream direction along the lower Quinault River. However, this study did not quantify the density or water temperatures associated with these fine-scale features that may serve as cool- or cold-water pockets or patches.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181129","collaboration":"Prepared in cooperation with the Quinault Indian Nation","usgsCitation":"Jaeger, K.L., Curran, C.A., Wulfkuhle, E.J., and Opatz, C.O., 2018, Water temperature in the lower Quinault River, Olympic Peninsula, Washington, June 2016–August 2017: U.S. Geological Survey Open-File Report 2018-1129, 24 p., https://doi.org/10.3133/ofr20181129.","productDescription":"Report: iv, 24 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-094010","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":356563,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1129/ofr20181129.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 20181129"},{"id":356562,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1129/coverthb.jpg"},{"id":363267,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7C53J2D","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water temperature and depth data for the lower Quinault River during summer baseflow, Washington, August 2016 and 2017"}],"country":"United States","state":"Washington","otherGeospatial":"Lower Quinault RIver, Olympic Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.35,\n 47.55\n ],\n [\n -123.5,\n 47.55\n ],\n [\n -123.5,\n 47.25\n ],\n [\n -124.35,\n 47.25\n ],\n [\n -124.35,\n 47.55\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The Gold Basin landslide is located along the South Fork Stillaguamish River, within the Mount Baker-Snoqualmie National Forest in western Washington State. Recent concerns related to slope stability after the 2014 State Route 530 Landslide near Oso, Washington, forced the closure of the U.S. Forest Service Gold Basin Campground in May of 2014. In addition to safety concerns for National Forest visitors, the landslide-derived sediment pulses shed into the South Fork Stillaguamish River may harm migrant salmon spawning grounds, an important resource for the Stillaguamish Tribe of Indians and for public anglers.
The Gold Basin landslide is composed of three active lobes and has an approximate footprint of 566,560 m2. Each lobe consists of steep topographic escarpments contained largely within Pleistocene glacial outwash sediments and debris flow and earth flow deposits at the base. In addition to landslides confined within the Pleistocene glacial strata, bedrock landslides are also apparent on lidar imagery of the study area. Bedrock landslides may pose additional hazard to the area, either during stochastic hillslope failure or during strong ground motion events. Potential seismic sources include the proximal Darrington-Devils Mountain and southern Whidbey Island fault zones, as well as the offshore Cascadia Subduction Zone. Previous analyses of hillslope stability in the Cascade Range suggests that rock mass strength is a useful way of characterizing bedrock and fracture patterns in order to understand potential landslide-prone landscape.
The goals of this investigation are to assess the glacial strata and bedrock geology of the Gold Basin landslide and adjacent areas and to assess how the geology and geomorphology within the study area affect the likelihood of coseismic landsliding.
Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
A study conducted by the U.S. Geological Survey, in cooperation with the New Jersey Pinelands Commission and Montclair State University, was designed to compare pesticide concentrations and the presence and prevalence of amphibian pathogens between natural ponds and two types of created wetlands, excavated ponds and stormwater basins, throughout the New Jersey Pinelands. The study described herein is part of a larger study by the New Jersey Pinelands Commission designed to compare the functional equivalency of natural and created wetlands throughout the New Jersey Pinelands. Sites were selected on the basis of land-use classifications within a 500-meter radius around each wetland from a pool of natural ponds, excavated ponds, and stormwater basins determined by the New Jersey Pinelands Commission. Water, bed-sediment, anuran-food, and composite larval-anuran-tissue samples were collected from four reference (minimum land-use effects) and four degraded (maximum land-use effects) sites from each wetland type for a total of 24 ponds or basins throughout the New Jersey Pinelands during 2014–16. Prevalence of Ranavirus was determined on the basis of tail clips collected from 60 individual larval anurans in each wetland, and 10 animals from each wetland also were swabbed for the presence of Batrachochytrium dendrobatidis (Bd). Other constituents measured included turbidity, pH, specific conductance, dissolved oxygen, dissolved organic carbon, percent organic carbon in sediment, and composite larval-anuran lipid content.
The amount of altered land (percent agricultural plus percent developed) ranged from 0 to 62.4 percent for the natural ponds, 0 to 63.6 percent for the excavated ponds, and 23.3 to 80.2 percent for the stormwater basins. The herbicides atrazine and metolachlor were observed in 60 and 89 percent of the water samples, respectively. The insecticide bifenthrin was the most frequently detected current-use pesticide (greater than 25 percent of the samples) in bed-sediment, anuran-food, and composite larval-anuran-tissue samples. The legacy insecticide p,p'-DDT and its primary degradates p,p'-DDD and p,p'-DDE were the most frequently detected compounds in bed-sediment and anuran-food samples (32–76 percent in sediment samples and 24–72 percent in anuran-food samples). Significantly, greater numbers of pesticides and higher total pesticide concentrations were observed in stormwater basins than in natural and excavated ponds. Reference wetlands had fewer pesticides and lower total pesticide concentrations compared to degraded wetlands, indicating a positive relation between percent altered land and pesticides throughout the New Jersey Pinelands. Ranavirus was observed in larvae from 4 wetlands, including 1 reference natural pond, 1 degraded natural pond, and 2 degraded stormwater basins, with prevalence ranging from 3 to 43 percent. Bd was detected in swabs from 18 animals and in 4 natural ponds (1 reference and 3 degraded), 3 excavated ponds (all reference), and 2 stormwater basins (1 reference and 1 degraded); however, detection probability was low. In the wetlands with Bd detections, between 10 and 30 percent (between 1 and 3) of the animal’s swabbed tested positive for Bd. Owing to the limited number of positive detections for both Bd and Ranavirus, no statistical comparisons between wetland types and land-use classifications were possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181077","collaboration":"Prepared in cooperation with the New Jersey Pinelands Commission and Montclair State University","usgsCitation":"Smalling, K.L., Bunnell, J.F., Cohl, J., Romanok, K.M., Hazard, L., Monsen, K., Akob, D.M., Hansen, A., Hladik, M.L., Abdallah, N., Ahmed, Q., Assan, A., De Parsia, M., Griggs, A., McWayne-Holmes, M., Patel, N., Sanders, C., Shrestha, Y., Stout, S., and Williams, B., 2018, An initial comparison of pesticides and amphibian pathogens between natural and created wetlands in the New Jersey Pinelands, 2014–16: U.S. Geological Survey Open-File Report 2018–1077, 18 p., https://doi.org/10.3133/ofr20181077.","productDescription":"Report: vii, 18 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092514","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":355889,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/F71G0K6G","text":"USGS data release","description":"USGS data release","linkHelpText":"Current-use pesticides and emerging amphibian pathogens in natural ponds, excavated ponds and stormwater basins from 24 sites varying in land-use classifications throughout the New Jersey Pinelands, 2014–2016"},{"id":437781,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71G0K6G","text":"USGS data release","linkHelpText":"Current-use pesticides and emerging amphibian pathogens in natural ponds, excavated ponds, and stormwater basins from 24 sites varying in land-use classifications throughout the New Jersey Pinelands, 2014-2016"},{"id":355954,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://www.state.nj.us/pinelands/science/complete/wetlands/index.shtml","linkHelpText":"- Natural and Created Wetlands Study. Final report submitted to the U.S. Environmental Protection Agency: New Lisbon, N.J., Pinelands Commission"},{"id":355887,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1077/coverthb.jpg"},{"id":355888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1077/ofr20181077.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1077"}],"country":"United States","state":"New Jersey","otherGeospatial":"New Jersey Pinelands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.9339,\n 39.2872\n ],\n [\n -74.24,\n 39.2872\n ],\n [\n -74.24,\n 39.94\n ],\n [\n -74.9339,\n 39.94\n ],\n [\n -74.9339,\n 39.2872\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The Mexican wolf recovery team proposed to establish other populations of Mexican wolves (Canis lupus baileyi) in the Southwest (U.S. Fish and Wildlife Service, 1982). We were tasked to conduct an extensive simulation modeling exercise to determine release strategies (in conjunction with management actions) that best predict establishment of a new Mexican wolf population. Our objectives were to determine optimal release and management strategies for population establishment and growth. This is a retrospective analysis utilizing data from 1998 to 2014, and during this period, we divided management strategies into two phases; (1) 1998–2008, where nuisance wolves (i.e., wolves that exhibit nuisance behavior or depredate livestock) were managed primarily through lethal removals and removals to captivity, and (2) 2009–2014, when lethal removals ceased and diversionary feeding was provided to denning packs to dissuade wolves from conflict with humans. Management strategies from the second phase are being used for management of the current Mexican wolf population, and demographic rates derived from alternate population modeling in Vortex incorporating post-2008 wolf data are being used to guide future recovery efforts. Therefore, demographic rates estimated from our retrospective analysis will differ (i.e., due to our unique approach to the analyses and the demographic rates being derived from a different dataset), and are intended solely to address the objectives of this report, and are not intended as basis for the development of management recommendations for the current Mexican wolf population. Using individual-based models, we tested dozens of scenarios and derived an optimal release strategy that had the highest probability of establishing a new population and which maximized subsequent post-release growth, and in this report, we present these model results. Findings from this research will improve our understanding of release strategies that yield growing populations, advance our understanding of the demands of reintroducing large carnivores, and provide insight into beneficial strategies that could aid other species reintroduction programs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181126","collaboration":"Prepared for U.S. Fish and Wildlife Service, Agreement: G12AC20098","usgsCitation":"Gedir, J.V., and Cain, J.W., III, 2018, An individual-based model for predicting dynamics of a newly established Mexican wolf (Canis lupus baileyi) population—Final report: U.S. Geological Survey Open-File Report 2018-1126, 16 p., https://doi.org/10.3133/ofr20181126.","productDescription":"iv, 16 p.","onlineOnly":"Y","ipdsId":"IP-085609","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356548,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1126/ofr20181126.pdf","text":"Report","size":"904 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1126"},{"id":356547,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1126/coverthb.jpg"}],"country":"United States","state":"Arizona, New Mexico","contact":"Leader, Washington Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
Fishery Sciences Building, Box 355020
University of Washington
Seattle, Washington, 98195
https://www.coopunits.org/Washington/
From December 2 to 4, 2015, NatureServe and the U.S. Geological Survey organized and hosted a biodiversity and ecological informatics workshop at the U.S. Department of the Interior in Washington, D.C. The workshop objective was to identify user-driven future directions and areas of collaboration in advanced applications of environmental data applied to forecasting and decision making for the sustainability of biodiversity and ecosystem services. Substantial effort to recruit attendees from diverse Federal, State, and private sector organizations successfully attracted participants from 20 Federal agencies and 48 different institutions in the academic, nonprofit, State government, and commercial sectors; the total number of attendees ranged from 100 to 144 during the 3-day workshop. The first one-half of the workshop was divided into 7 plenary sessions and 3 sets of lightning talk sessions organized by sector, providing 48 oral and visual plenary presentations that shared diverse perspectives on biodiversity and ecological informatics, including original biospatial analyses from 6 graduate student map contest winners. The second one-half of the workshop focused on 10 breakout sessions with participant-driven themes from the environmental data sphere and concluded with an address by the Director of the U.S. Fish and Wildlife Service. The workshop was structured to encourage interactivity. About 80–90 percent of attendees provided direct feedback using clicker devices for specific questions related to biodiversity and ecological data uses and needs, and 10 breakout session leaders shared the highlights of their group discussions during the final workshop plenary sessions. Participants were encouraged to use the Twitter hashtag #ShareUrData. Over lunch on day 2 there were 20 simultaneous presentations of tools and apps during a special “Tools Café” session.
The 10 participant-defined breakout session topics are listed below:
Numerous common themes that emerged from the workshop include the following:
Director, Core Science Analytics Synthesis and Libraries Program
U.S. Geological Survey
W 6th Ave Kipling Street
Lakewood, CO 80225
The U.S. Geological Survey (USGS) National Strong Motion Project (NSMP) operates numerous strong-motion seismographs to monitor ground shaking and structural response caused by large, nearby earthquakes. This report describes a problem NSMP scientists encountered communicating over the Internet with several Kinemetrics, Inc., Granite strong-motion recorders.
The Granite strong-motion recorders (“Granites”) get into a state where they cannot be reached from the Internet and they cannot reach the Internet, yet they can reach and be reached from the local Ethernet subnet. The reason is that the Internet Protocol (IP) network default route has disappeared; only the local route is available. Diagnosis is complicated by the unpredictability of the circumstances leading to the failure. The failures have happened at several field sites but cannot be reproduced in the lab.
This report describes the IP networking behavior of a Granite system and provides modifications to the Granite Ethernet device drivers to send Ethernet link (carrier) state-change event notifications to the Linux kernel. With these modifications, the Linux netplugd daemon can be configured to properly reconfigure Granite IP networking when the Ethernet interface link state changes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181117","usgsCitation":"Baker, L.M., 2018, Granite IP network default route disappearance—Diagnosis and solution: U.S. Geological Survey Open-File Report 2018–1117, 35 p., https://doi.org/10.3133/ofr20181117.","productDescription":"Report: iv; 35 p.; Electronic Supplement","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078989","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":356156,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1117/coverthb.jpg"},{"id":356157,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1117/ofr20181117.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2018-1117"},{"id":356158,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2018/1117/ofr20181117_electronic_supplement.zip","text":"Electronic Supplement","size":"20 KB","linkFileType":{"id":6,"text":"zip"},"description":"Fact Sheet 2018-1117"}],"contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
Methods for grouping specific avian influenza virus (AIV) hemagglutinin (HA) and neuraminidase (NA) subtype reverse-transcription polymerase chain reaction (RT-PCR) products into HA:NA subtypes when egg incubation is technically not feasible were evaluated. These approaches were adopted for use as post hoc methods after melt curve analysis. The methods are based on ratios obtained from amplicon copy count and amplicon molarity and were founded on the premise that infectious particles contain an equal copy count of single-stranded ribonucleic acid segments that encode HA or NA, and thus subtype-specific amplicons from a single AIV isolate should yield a theoretical HA:NA ratio of 1. Single and mixed HA:NA AIV subtype samples were evaluated to determine whether the calculated HA:NA ratios would approach the theoretical value. With these samples, preference was given to the molarity methods to better define and correct for the effects of multiple potential amplicons in the amplification mix. Further, the molarity method was used to evaluate pond sediment spiked with intact virus of known HA:NA subtype to determine whether the method is sufficiently robust to be used with complex samples, such as those acquired from waterfowl habitat. This was a proof-of-concept study intended to guide future methods development. The methods here are not meant to be applied in any other context.
From the analysis of fully characterized isolates of North American AIV, the HA:NA molarity-based ratios were found to be 1.63 ± 0.75 (mean ± standard deviation) when corrected for the difference in amplification strength and the production of multiple amplicons in some reactions using equations developed in this study. Copy count HA:NA ratios, obtained from HA and NA subtype (RT-qPCR), were 1.146 ± 0.124 (mean ± standard deviation) when corrected for amplification efficiency. Correct associations of HA:NA subtype sample composition were made with mixed samples containing 1 HA and 2 NA, and 2 HA and 2 NA. When spiked pond sediment was evaluated, the molar ratio obtained for the H4 and N6 identified in the sample was 1.28 with correction and 1.14 without correction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181102","usgsCitation":"Ottinger, C.A., Iwanowicz, D.D., Iwanowicz, L.R., Adams, C.R., Sanders, L.R., and Densmore, C.L., 2018, A method for determining avian influenza virus hemagglutinin and neuraminidase subtype association: U.S. Geological Survey Open-File Report 2018–1102, 15 p., https://doi.org/10.3133/ofr20181102.","productDescription":"v, 15 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-096308","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":355970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1102/ofr20181102.pdf","text":"Report","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1102"},{"id":355969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1102/coverthb.jpg"}],"contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
The Community for Data Integration (CDI) is a group that helps members grow their expertise on all aspects of working with scientific data. The CDI’s activities advance data and information integration capabilities in the U.S. Geological Survey and in the wider Earth and biological sciences. This annual report describes the presentations, activities, collaboration areas, workshop, and other CDI-sponsored events in fiscal year 2017. The report also describes the objectives of the 11 CDI-funded projects in fiscal year 2017. The report shows how the CDI activities fulfill the strategic objective of the U.S. Geological Survey’s Core Science Systems Mission Area to develop a workplace model for interdisciplinary science.
Core Science Analytics, Synthesis, and Library
U.S. Geological Survey
108 National Center
12201 Sunrise Valley Drive,
Reston, VA 20192
We operated a bird banding station on the Naval Base Coronado, Remote Training Site, Warner Springs (RTSWS), in northeastern San Diego County, California, during the bird breeding season (spring/summer) from 2013 to 2017 and during migration (fall) from 2013 to 2016. The station was established in spring 2013 as part of the Monitoring Avian Productivity and Survivorship (MAPS) program and continued into the fall for the first 4 years as part of a long-term monitoring program for neotropical migratory birds.
We captured 705 individuals of 58 species during the MAPS/breeding season from 2013 to 2017 (12–13 days each year in April through August), 79 percent of which were newly banded during the MAPS season (555), 8 percent of which were recaptures banded in previous years (57), and 13 percent of which we released unbanded (64 hummingbirds and 29 other birds that were released or escaped prior to banding). Sixty individuals were captured more than once within a year during MAPS. Bird capture rate averaged 19 ± 1 captures per 100 net-hours (range 17–20) across 5 years. Annual species richness ranged from 28 (2017) to 42 (2014). The average species richness per day was highest in 2014 (9 ± 3) and lowest in 2016 (6 ± 2). Bushtit (Psaltriparus minimus) was the most abundant breeding species captured, followed by Spotted Towhee (Pipilo maculatus), Oak Titmouse (Baeolophus inornatus), Anna’s Hummingbird (Calypte anna), House Wren (Troglodytes aedon), Ash-throated Flycatcher (Myiarchus cinerascens), California Scrub-jay (Aphelocoma californica), Bewick’s Wren (Thryomanes bewickii), Acorn Woodpecker (Melanerpes formicivorus), California Towhee (Melozone crissalis), and Western Bluebird (Sialia mexicana). Each of these 11 breeding species accounted for at least 5 percent of captures in any 1 year. Fifty-seven percent of known-sex captures were female and 43 percent were male. Thirty-three percent of known-age captures were juveniles. Peaks in number of birds captured were in the first and last weeks of April, and the greatest number of species was captured in early May.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181112","usgsCitation":"Lynn, S., Hall, K.A., Madden, M.C., and Kus, B.E., 2018, Monitoring breeding and migration of neotropical migratory birds at Naval Base Coronado, Remote Training Site, Warner Springs, San Diego County, California, 5-year summary, 2013–17: U.S. Geological Survey Open-File Report 2018–1112, 98 p., https://doi.org/10.3133/ofr20181112.","productDescription":"viii, 98 p.","onlineOnly":"Y","ipdsId":"IP-096573","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":355910,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1112/coverthb.jpg"},{"id":355911,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1112/ofr20181112.pdf","text":"Report","size":"8.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1112"}],"country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Naval Base Coronado, Remote Training Site","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819