Most time series of geophysical phenomena have temporally correlated errors. From these measurements, various parameters are estimated. For instance, from geodetic measurements of positions, the rates and changes in rates are often estimated and are used to model tectonic processes. Along with the estimates of the size of the parameters, the error in these parameters needs to be assessed. If temporal correlations are not taken into account, or each observation is assumed to be independent, it is likely that any estimate of the error of these parameters will be too low and the estimated value of the parameter will be biased. Inclusion of better estimates of uncertainties is limited by several factors, including selection of the correct model for the background noise and the computational requirements to estimate the parameters of the selected noise model for cases where there are numerous observations. Here, I address the second problem of computational efficiency using maximum likelihood estimates (MLE). Most geophysical time series have background noise processes that can be represented as a combination of white and power-law noise,
Deepwater sculpin are important in oligotrophic lakes as one of the few fishes that use deep profundal habitats and link invertebrates in those habitats to piscivores. In Lake Ontario the species was once abundant, however drastic declines in the mid-1900s led some to suggest the species had been extirpated and ultimately led Canadian and U.S. agencies to elevate the species' conservation status. Following two decades of surveys with no captures, deepwater sculpin were first caught in low numbers in 1996 and by the early 2000s there were indications of population recovery. We updated the status of Lake Ontario deepwater sculpin through 2016 to inform resource management and conservation. Our data set was comprised of 8431 bottom trawls sampled from 1996 to 2016, in U.S. and Canadian waters spanning depths from 5 to 225 m. Annual density estimates generally increased from 1996 through 2016, and an exponential model estimated the rate of population increase was ~ 59% per year. The mean total length and the proportion of fish greater than the estimated length at maturation (~ 116 mm) generally increased until a peak in 2013. In addition, the mean length of all deepwater sculpin captured in a trawl significantly increased with depth. Across all years examined, deepwater sculpin densities generally increased with depth, increasing sharply at depths > 150 m. Bottom trawl observations suggest the Lake Ontario deepwater sculpin population has recovered and current densities and biomass densities may now be similar to the other Great Lakes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2016.12.011","usgsCitation":"Weidel, B., Walsh, M., Connerton, M., Lantry, B.F., Lantry, J.R., Holden, J.P., Yuille, M.J., and Hoyle, J., 2017, Deepwater sculpin status and recovery in Lake Ontario: Journal of Great Lakes Research, v. 43, no. 5, p. 854-862, https://doi.org/10.1016/j.jglr.2016.12.011.","productDescription":"9 p.","startPage":"854","endPage":"862","ipdsId":"IP-082229","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469680,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2016.12.011","text":"Publisher Index Page"},{"id":343808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.91455078125,\n 43.14909399920127\n ],\n [\n -76.025390625,\n 43.14909399920127\n ],\n [\n -76.025390625,\n 44.276671273775186\n ],\n [\n -79.91455078125,\n 44.276671273775186\n ],\n [\n -79.91455078125,\n 43.14909399920127\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5968869be4b0d1f9f05f5955","contributors":{"authors":[{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Maureen 0000-0001-7846-5025 mwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-7846-5025","contributorId":3659,"corporation":false,"usgs":true,"family":"Walsh","given":"Maureen","email":"mwalsh@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connerton, Michael J.","contributorId":190416,"corporation":false,"usgs":false,"family":"Connerton","given":"Michael J.","affiliations":[],"preferred":false,"id":704846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lantry, Jana R.","contributorId":28495,"corporation":false,"usgs":false,"family":"Lantry","given":"Jana","email":"","middleInitial":"R.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":704848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holden, Jeremy P.","contributorId":190415,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","email":"","middleInitial":"P.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":704849,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yuille, Michael J.","contributorId":194647,"corporation":false,"usgs":false,"family":"Yuille","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":704850,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":" Hoyle, James A.","contributorId":141108,"corporation":false,"usgs":false,"family":" Hoyle","given":"James A.","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":704851,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70188452,"text":"sim3381 - 2017 - Land area change in coastal Louisiana (1932 to 2016)","interactions":[],"lastModifiedDate":"2017-07-12T10:37:54","indexId":"sim3381","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3381","title":"Land area change in coastal Louisiana (1932 to 2016)","docAbstract":"Coastal Louisiana wetlands are one of the most critically threatened environments in the United States. These wetlands are in peril because Louisiana currently experiences greater coastal wetland loss than all other States in the contiguous United States combined. The analyses of landscape change presented here have utilized historical surveys, aerial, and satellite data to quantify landscape changes from 1932 to 2016. Analyses show that coastal Louisiana has experienced a net change in land area of approximately -4,833 square kilometers (modeled estimate: -5,197 +/- 443 square kilometers) from 1932 to 2016. This net change in land area amounts to a decrease of approximately 25 percent of the 1932 land area. Previous studies have presented linear rates of change over multidecadal time periods which unintentionally suggest that wetland change occurs at a constant rate, although in many cases, wetland change rates vary with time. A penalized regression spline technique was used to determine the model that best fit the data, rather than fitting the data with linear trends. Trend analyses from model fits indicate that coastwide rates of wetland change have varied from -83.5 +/- 11.8 square kilometers per year to -28.01 +/- 16.37 square kilometers per year. To put these numbers into perspective, this equates to long-term average loss rates of approximately an American football field’s worth of coastal wetlands within 34 minutes when losses are rapid to within 100 minutes at more recent, slower rates. Of note is the slowing of the rate of wetland change since its peak in the mid- 1970s. Not only have rates of wetland loss been decreasing since that time, a further rate reduction has been observed since 2010. Possible reasons for this reduction include recovery from lows affected by the hurricanes of 2005 and 2008, the lack of major storms in the past 8 years, a possible slowing of subsidence rates, the reduction in and relocation of oil and gas extraction and infrastructure since the peak of such activities in the late 1960s, and restoration activities. In addition, many wetlands in more exposed positions in the landscape have already been lost. Most notable of the factors listed above is the lack of major storms over the past 8 years. The observed coastwide net “stability” in land area observed over the past 6–8 years does not imply that loss has ceased. Future disturbance events such as a major hurricane impact could change the trajectory of the rates. Sea-level rise is projected to increase at an exponential rate, and that would also expedite the rate of wetland loss.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3381","usgsCitation":"Couvillion, B.R., Beck, Holly, Schoolmaster, Donald, and Fischer, Michelle, 2017, Land area change in coastal Louisiana 1932 to 2016: U.S. Geological Survey Scientific Investigations Map 3381, 16 p. pamphlet, https://doi.org/10.3133/sim3381.","productDescription":"Pamphlet: vi, 16 p.; Map: 80 x 42 inches","onlineOnly":"N","ipdsId":"IP-085820","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":438270,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74B30JM","text":"USGS data release","linkHelpText":"Land area change in Coastal Louisiana (1932 to 2016) - persistent land change spatial data"},{"id":343518,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3381/sim3381.pdf","text":"Map","size":"11.3 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29.698789407596585 ], [ -93.33160400390625, 29.69640358280457 ], [ -93.30276489257811, 29.71071768156533 ], [ -93.28765869140625, 29.723837146389066 ] ] ] } } ] }","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
The 2016 Mw 5.8 Pawnee earthquake occurred in a region with active wastewater injection into a basal formation group. Prior to the earthquake, fluid injection rates at most wells were relatively steady, but newly collected data show significant increases in injection rate in the years leading up to earthquake. For the same time period, the total volumes of injected wastewater were roughly equivalent between variable‐rate and constant‐rate wells. To understand the possible influence of these changes in injection, we simulate the variable‐rate injection history and its constant‐rate equivalent in a layered poroelastic half‐space to explore the interplay between pore‐pressure effects and poroelastic effects on the fault leading up to the mainshock. In both cases, poroelastic stresses contribute a significant proportion of Coulomb failure stresses on the fault compared to pore‐pressure increases alone, but the resulting changes in seismicity rate, calculated using a rate‐and‐state frictional model, are many times larger when poroelastic effects are included, owing to enhanced stressing rates. In particular, the variable‐rate simulation predicts more than an order of magnitude increase in seismicity rate above background rates compared to the constant‐rate simulation with equivalent volume. The observed cumulative density of earthquakes prior to the mainshock within 10 km of the injection source exhibits remarkable agreement with seismicity predicted by the variable‐rate injection case.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170003","usgsCitation":"Barbour, A., Norbeck, J.H., and Rubinstein, J.L., 2017, The effects of varying injection rates in Osage County, Oklahoma, on the 2016 Mw5.8 Pawnee earthquake: Seismological Research Letters, v. 88, no. 4, p. 1040-1053, https://doi.org/10.1785/0220170003.","productDescription":"14 p.","startPage":"1040","endPage":"1053","ipdsId":"IP-082545","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":343760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-03","publicationStatus":"PW","scienceBaseUri":"5967353ee4b0d1f9f05dd7bb","contributors":{"authors":[{"text":"Barbour, Andrew J. 0000-0002-6890-2452 abarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":140443,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew J.","email":"abarbour@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":704578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norbeck, Jack H.","contributorId":194536,"corporation":false,"usgs":true,"family":"Norbeck","given":"Jack","email":"","middleInitial":"H.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":704580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785 jrubinstein@usgs.gov","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":2404,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"jrubinstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":704579,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190049,"text":"70190049 - 2017 - The estimation of growth dynamics for Pomacea maculata from hatchling to adult","interactions":[],"lastModifiedDate":"2017-08-07T16:58:46","indexId":"70190049","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The estimation of growth dynamics for Pomacea maculata from hatchling to adult","title":"The estimation of growth dynamics for Pomacea maculata from hatchling to adult","docAbstract":"Pomacea maculata is a relatively new invasive species to the Gulf Coast region and potentially threatens local agriculture (rice) and ecosystems (aquatic vegetation). The population dynamics of P. maculata have largely been unquantified, and therefore, scientists and field-workers are ill-equipped to accurately project population sizes and the resulting impact of this species. We studied the growth of P. maculata ranging in weights from 6 to 105 g, identifying the sex of the animals when possible. Our studied population had a 4:9 male:female sex ratio. We present the findings from initial analysis of the individual growth data of males and females, from which it was apparent that females were generally larger than males and that small snails grew faster than larger snails. Since efforts to characterize the male and female growth rates from individual data do not yield statistically supported estimates, we present the estimation of several parameterized growth rate functions within a population-level mathematical model. We provide a comparison of the results using these various growth functions and discuss which best characterizes the dynamics of our observed population. We conclude that both males and females exhibit biphasic growth rates, and thus, their growth is size-dependent. Further, our results suggest that there are notable differences between males and females that are important to take into consideration in order to accurately model this species' population dynamics. Lastly, we include preliminary analyses of ongoing experiments to provide initial estimates of growth in the earliest life stages (hatchling to ≈6 g).
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1840","usgsCitation":"Sutton, K.L., Zhao, L., and Carter, J., 2017, The estimation of growth dynamics for Pomacea maculata from hatchling to adult: Ecosphere, v. 8, no. 7, e01840: 22 p., https://doi.org/10.1002/ecs2.1840.","productDescription":"e01840: 22 p.","ipdsId":"IP-081732","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469683,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1840","text":"Publisher Index Page"},{"id":438268,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q23XFZ","text":"USGS data release","linkHelpText":"Data for the estimation of growth dynamics for Pomacea maculata from hatchling to adult, 10/10/13 to 9/25/15"},{"id":344621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"7","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-28","publicationStatus":"PW","scienceBaseUri":"59897c15e4b09fa1cb0c2bff","contributors":{"authors":[{"text":"Sutton, Karyn L.","contributorId":195516,"corporation":false,"usgs":false,"family":"Sutton","given":"Karyn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":707324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhao, Lihong","contributorId":187552,"corporation":false,"usgs":false,"family":"Zhao","given":"Lihong","email":"","affiliations":[],"preferred":false,"id":707325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":707323,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188613,"text":"sir20175066 - 2017 - Synthesis of data from high-frequency nutrient and associated biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California","interactions":[],"lastModifiedDate":"2017-07-12T09:16:30","indexId":"sir20175066","displayToPublicDate":"2017-07-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5066","title":"Synthesis of data from high-frequency nutrient and associated biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California","docAbstract":"This report is the second in a series of three reports that provide information about high-frequency (HF) nutrient and biogeochemical monitoring in the Sacramento–San Joaquin Delta of northern California (Delta). The purpose of this report is to synthesize the data available from a nutrient and water-quality HF (about every 15 minutes) monitoring network operated by the U.S. Geological Survey in the northern Delta. In this report, we describe the network and focus on the purpose of each station. We then present and discuss the available data, at various timescales—first at the monthly, seasonal, and inter-annual timescales, and second, for comparison, at the tidal and event timescales. As expected, we determined that there is substantial variability in nitrate-N concentrations at short timescales within hours, but also significant variability at longer timescales such as months or years. Resolving this variability is made possible by the HF data, with the largest variability caused by storms, tides, and diel biological processes. Given this large temporal variability, calculations of cumulative nutrient fluxes (for example, daily, monthly, or annual loads) is difficult without HF data. For example, in the Cache Slough, calculation of the annual load without the tidal variability resulted in a 30 percent underestimation of the true annual load value. We conclude that HF measurements are important for accurate determination of fluxes and loads in tidal environments, but, more importantly, provide important insights into processes and rates of nutrient cycling.
This report, along with the other two reports of this series (Bergamaschi and others, 2017; Kraus, Bergamaschi, and others, 2017), was drafted in cooperation with the Delta Regional Monitoring Program to help scientists, managers, and planners understand how HF data improve our understanding of nutrient sources and sinks, drivers, and effects in the Delta. The first report in the series (Kraus, Bergamaschi, and others, 2017) provides an introduction to the reasons for and fundamental concepts behind using HF monitoring measurements, including a brief summary of nutrient status and trends in the Delta and an extensive literature review showing how and where other research and monitoring programs have used HF monitoring to improve our understanding of nutrient cycling. The report covers the various technologies available for HF nutrient monitoring and presents the different ways HF monitoring instrumentation may be used for fixed station and spatial assessments. Finally, it presents numerous examples of how HF measurements are currently (2017) being used in the Delta to examine how nutrients and nutrient cycling are related to aquatic habitat conditions.
The third report in the series (Bergamaschi and others, 2017) provides the background, principles, and considerations for designing an HF nutrient-monitoring network for the Delta to address high-priority, nutrient-management questions. The report starts with discussion of the high‑priority management questions to be addressed, continues through discussion of the questions and considerations that place demands and constraints on network design, discusses the principles applicable to network design, and concludes with the presentation of three example nutrient-monitoring network designs for the Delta, proposed to address high-priority questions identified by the Delta Regional Monitoring Program (Delta Regional Monitoring Program Technical Advisory Committee, 2015).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175066","collaboration":"Prepared in cooperation with the Delta Regional Monitoring Program","usgsCitation":"Downing, B.D., Bergamaschi, B.A., and Kraus, T.E.C., 2017, Synthesis of data from high-frequency nutrient and associated biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California: U.S. Geological Survey Scientific Investigations Report 2017–5066, 28 p., https://doi.org/10.3133/sir20175066.","productDescription":"vi, 28 p.","onlineOnly":"Y","ipdsId":"IP-081533","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343628,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5066/sir20175066.pdf","text":"Report","size":"7.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5066"},{"id":343629,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175058","text":"SIR 2017–5058 —","description":"SIR 2017-5058","linkHelpText":"Designing a High-Frequency Nutrient and Biogeochemical Monitoring Network for the Sacramento–San Joaquin Delta, Northern California"},{"id":343627,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5066/coverthb.jpg"},{"id":343630,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175071","text":"SIR 2017–5071 —","description":"SIR 2017-5071","linkHelpText":"An Introduction to High-Frequency Nutrient and Biogeochemical Monitoring for the Sacramento–San Joaquin Delta, Northern California"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.15,\n 37.6\n ],\n [\n -121.15,\n 37.6\n ],\n [\n -121.15,\n 38.61\n ],\n [\n -122.15,\n 38.61\n ],\n [\n -122.15,\n 37.6\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
California State University Placer Hall
6000 J Street
Sacramento, California 95819-6129
This report is the first in a series of three reports that provide information about high-frequency (HF) nutrient and biogeochemical monitoring in the Sacramento–San Joaquin Delta of northern California (Delta). This first report provides an introduction to the reasons for and fundamental concepts behind collecting HF measurements, and describes the benefits associated with a real-time, continuous, HF, multi-parameter water quality monitoring station network that is co-located with flow stations. It then provides examples of how HF nutrient measurements have improved our understating of nutrient sources and cycling in aquatic systems worldwide, followed by specific examples from the Delta. These examples describe the ways in which HF instrumentation may be used for both fixed-station and spatial assessments. The overall intent of this document is to describe how HF measurements currently (2017) are being used in the Delta to examine the relationship between nutrient concentrations, nutrient cycling, and aquatic habitat conditions.
The second report in the series (Downing and others, 2017) summarizes information about HF nutrient and associated biogeochemical monitoring in the northern Delta. The report synthesizes data available from the nutrient and water quality monitoring network currently operated by the U.S. Geological Survey in this ecologically important region of the Delta. In the report, we present and discuss the available data at various timescales—first, at the monthly, seasonal, and inter-annual timescales; and, second, for comparison, at the tidal and event (for example, storms, reservoir releases, phytoplankton blooms) timescales. As expected, we determined that there is substantial variability in nitrate concentrations at short timescales within hours, but also significant variability at longer timescales such as months or years. This multi-scale, high variability affects calculation of fluxes and loads, indicating that HF monitoring is necessary for understanding and assessing flux-based processes and outcomes in tidal environments, such as the Delta.
The third report in the series (Bergamaschi and others, 2017) provides information about how to design HF nutrient and biogeochemical monitoring for assessment of nutrient inputs and dynamics in the Delta. The report provides background, principles, and considerations for designing an HF nutrient-monitoring network for the Sacramento–San Joaquin Delta to address high-priority, nutrient-management questions. The report starts with high-priority management questions to be addressed, continues with questions and considerations that place demands and constraints on network design, discusses the principles applicable to network design, and concludes with the presentation of three example nutrient‑monitoring network designs for the Delta. For the three example networks, we assess how they would address high-priority questions identified by the Delta Regional Monitoring Program (Delta Regional Monitoring Program Technical Advisory Committee, 2015).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175071","collaboration":"Prepared in cooperation with the Delta Regional Monitoring Program","usgsCitation":"Kraus, T.E.C., Bergamaschi, B.A., and Downing, B.D., 2017, An introduction to high-frequency nutrient and biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California: U.S. Geological Survey Scientific Investigations Report 2017–5071, 41 p., https://doi.org/10.3133/sir20175071.","productDescription":"vi, 41 p.","onlineOnly":"Y","ipdsId":"IP-081539","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343632,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175058","text":"SIR 2017–5058 —","description":"SIR 2017-5058","linkHelpText":"Designing a High-Frequency Nutrient and Biogeochemical Monitoring Network for the Sacramento–San Joaquin Delta, Northern California"},{"id":343624,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5071/coverthb.jpg"},{"id":343625,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5071/sir20175071.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5071"},{"id":343633,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175066","text":"SIR 2017–5066 —","description":"SIR 2017-5066","linkHelpText":"Synthesis of Data from High-Frequency Nutrient and Associated Biogeochemical Monitoring for the Sacramento–San Joaquin Delta, Northern California"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.15,\n 37.6\n ],\n [\n -121.15,\n 37.6\n ],\n [\n -121.15,\n 38.61\n ],\n [\n -122.15,\n 38.61\n ],\n [\n -122.15,\n 37.6\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
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Sacramento, California 95819-6129
Isopach maps from tephra eruptions from Mount St. Helens were reported in Carey et al. (1995) and for tephra eruptions from Glacier Peak in Gardner et al. (1998). For exponential thinning, the isopach data only define a single slope on a log thickness versus square root of area plot. Carey et al. (1995) proposed a model that was used to estimate a second slope, and volumes were presented in both studies using this model. A study by Sulpizio (2005) for estimating the second slope and square root of area where the lines intersect involves a systematic analysis of many eruptions to provide correlation equations. The purpose of this paper is to recalculate the volumes of Cascades eruptions and compare results from the two methods. In order to gain some perspective on the methods for estimating the second slope, we use data for thickness versus distance beyond the last isopach that are available for some of the larger eruptions in the Cascades. The thickness versus square root of area method is extended to thickness versus distance by developing an approximate relation between the two assuming elliptical isopachs with the source at one of the foci. Based on the comparisons made between the Carey et al. (1995) and Sulpizio (2005) methods, it is felt that the later method provides a better estimate of the second slope. For Mount St. Helens, the estimates of total volume using the Sulpizio (2005) method are generally smaller than those using the Carey et al. (1995) method. For the volume estimates of Carey et al. (1995), the volume of the May 18, 1980, eruption of Mount St. Helens is smaller than six of the eight previous eruptions. With the new volumes using the Sulpizio (2005) method, the 1980 eruption is smaller in volume than the upper end of the range for only three of the layers (Wn, Ye, and Yn) and is the same size as layer We. Thus the 1980 eruption becomes representative of the mid-range of volumes rather than being in the lower range.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.04.021","usgsCitation":"Nathenson, M., 2017, Revised tephra volumes for Cascade Range volcanoes: Journal of Volcanology and Geothermal Research, v. 341, p. 42-52, https://doi.org/10.1016/j.jvolgeores.2017.04.021.","productDescription":"11 p.","startPage":"42","endPage":"52","ipdsId":"IP-082574","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":343573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Cascade Range volcanoes","volume":"341","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1b4e4b0d1f9f05b378e","contributors":{"authors":[{"text":"Nathenson, Manuel 0000-0002-5216-984X mnathnsn@usgs.gov","orcid":"https://orcid.org/0000-0002-5216-984X","contributorId":1358,"corporation":false,"usgs":true,"family":"Nathenson","given":"Manuel","email":"mnathnsn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":704187,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187574,"text":"sim3380 - 2017 - Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016","interactions":[],"lastModifiedDate":"2017-07-11T16:39:14","indexId":"sim3380","displayToPublicDate":"2017-07-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3380","title":"Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016","docAbstract":"The inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, was mapped in 2011. Since that time, the saltwater interface has continued to move inland. The interface is near several active well fields; therefore, an updated approximation of the inland extent of saltwater and an improved understanding of the rate of movement of the saltwater interface are necessary. A geographic information system was used to create a map using the data collected by the organizations that monitor water salinity in this area. An average rate of saltwater interface movement of 140 meters per year was estimated by dividing the distance between two monitoring wells (TPGW-7L and Sec34-MW-02-FS) by the travel time. The travel time was determined by estimating the dates of arrival of the saltwater interface at the wells and computing the difference. This estimate assumes that the interface is traveling east to west between the two monitoring wells. Although monitoring is spatially limited in this area and some of the wells are not ideally designed for salinity monitoring, the monitoring network in this area is improving in spatial distribution and most of the new wells are well designed for salinity monitoring. The approximation of the inland extent of the saltwater interface and the estimated rate of movement of the interface are dependent on existing data. Improved estimates could be obtained by installing uniformly designed monitoring wells in systematic transects extending landward of the advancing saltwater interface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3380","collaboration":"Prepared in cooperation with Miami-Dade County","usgsCitation":"Prinos, S.T., 2017, Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016: U.S. Geological Survey Scientific Investigations Map 3380, 8-p. pamphlet, 1 sheet, https://doi.org/10.3133/sim3380.","productDescription":"Pamphlet: vi, 8 p.; Sheet: 20.00 x 19.64 inches; Data Release","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080722","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":343395,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R78CF8","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data pertaining to mapping the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016"},{"id":343258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3380/coverthb.jpg"},{"id":343259,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3380/sim3380.pdf","text":"Map","size":"867 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3380"},{"id":343260,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3380/sim3380_pamphlet.pdf","text":"Pamphlet","size":"503 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3380 Pamphlet"}],"country":"United States","state":"Florida","county":"Miami-Dade County","otherGeospatial":"Biscayne Aquifer, Model Land Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.595703125,\n 25.243453810607868\n ],\n [\n -80.25787353515625,\n 25.243453810607868\n ],\n [\n -80.25787353515625,\n 25.58456258101669\n ],\n [\n -80.595703125,\n 25.58456258101669\n ],\n [\n -80.595703125,\n 25.243453810607868\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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This report is the third in a series of three reports that provide information about how high-frequency (HF) nutrient monitoring may be used to assess nutrient inputs and dynamics in the Sacramento–San Joaquin Delta, California (Delta). The purpose of this report is to provide the background, principles, and considerations for designing an HF nutrient-monitoring network for the Delta to address high-priority, nutrient-management questions. The report starts with discussion of the high-priority management questions to be addressed, continues through discussion of the questions and considerations that place demands and constraints on network design, discusses the principles applicable to network design, and concludes with the presentation of three example nutrient-monitoring network designs for the Delta. For three example network designs, we assess how they would address high-priority questions that have been identified by the Delta Regional Monitoring Program (Delta Regional Monitoring Program Technical Advisory Committee, 2015).
This report, along with the other two reports of this series (Kraus and others, 2017; Downing and others, 2017), was drafted in cooperation with the Delta Regional Monitoring Program to help scientists, managers, and planners understand how HF data improve our understanding of nutrient sources and sinks, drivers, and effects in the Delta. The first report in the series (Kraus and others, 2017) provides an introduction to the reasons for and fundamental concepts behind using HF monitoring measurements, including a brief summary of nutrient status and trends in the Delta and an extensive literature review showing how and where other research and monitoring programs have used HF monitoring to improve our understanding of nutrient cycling. The report covers the various technologies available for HF nutrient monitoring and presents the different ways HF monitoring instrumentation may be used for both fixed station and spatial assessments. Finally, it presents numerous examples of how HF measurements are currently (2017) being used in the Delta to examine how nutrients and nutrient cycling are related to aquatic habitat conditions.
The second report in the series (Downing and others, 2017) summarizes information about HF nutrient and associated biogeochemical monitoring in the north Delta. The report synthesizes data available from the nutrient and water quality monitoring network currently (2017) operated by the U.S. Geological Survey in this ecologically important region of the Delta. In the report, we present and discuss the available data at various timescales—first at the monthly, seasonal, and inter-annual timescales; and, second, for comparison, at the tidal and event timescales. As expected, we determined that there is substantial variability in nitrate concentrations at short timescales, such as within a few hours, but also significant variability at longer timescales such as months or years. This high variability affects calculation of fluxes and loads, indicating that HF monitoring is necessary for understanding and assessing flux-based processes and outcomes in Delta tidal environments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175058","collaboration":"Prepared in cooperation with the Delta Regional Monitoring Program","usgsCitation":"Bergamaschi, B.A., Downing, B.D., Kraus, T.E.C., and Pellerin, B.A., 2017, Designing a high-frequency nutrient and biogeochemical monitoring network for the Sacramento–San Joaquin Delta, northern California: U.S. Geological Survey Scientific Investigations Report 2017–5058, 40 p., https://doi.org/10.3133/sir20175058.","productDescription":"v, 40 p.","onlineOnly":"Y","ipdsId":"IP-070995","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343622,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5058/coverthb.jpg"},{"id":343623,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5058/sir20175058.pdf","text":"Report","size":"7.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5058"},{"id":343634,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175066","text":"SIR 2017–5066 —","description":"SIR 2017-5066","linkHelpText":"Synthesis of Data from High-Frequency Nutrient and Associated Biogeochemical Monitoring for the Sacramento–San Joaquin Delta, Northern California"},{"id":343635,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175071","text":"SIR 2017–5071 —","description":"SIR 2017-5071","linkHelpText":"An Introduction to High-Frequency Nutrient and Biogeochemical Monitoring for the Sacramento–San Joaquin Delta, Northern California"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.15,\n 37.6\n ],\n [\n -121.15,\n 37.6\n ],\n [\n -121.15,\n 38.61\n ],\n [\n -122.15,\n 38.61\n ],\n [\n -122.15,\n 37.6\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
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California State University Placer Hall
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Sacramento, California 95819-6129
Laurel Hill Creek is considered one of the most pristine waterways in southwestern Pennsylvania and has high recreational value as a high-quality cold-water fishery; however, the upper parts of the basin have documented water-quality impairments. Groundwater and surface water are withdrawn for public water supply and the basin has been identified as a Critical Water Planning Area (CWPA) under the State Water Plan. The U.S. Geological Survey, in cooperation with the Somerset County Conservation District, collected data and developed modeling tools to support the assessment of water-quality and water-quantity issues for a basin designated as a CWPA. Streams, springs, and groundwater wells were sampled for water quality in 2007. Streamflows were measured concurrent with water-quality sampling at main-stem sites on Laurel Hill Creek and tributaries in 2007. Stream temperatures were monitored continuously at five main-stem sites from 2007 to 2010. Water usage in the basin was summarized for 2003 and 2009 and a Water-Analysis Screening Tool (WAST) developed for the Pennsylvania State Water Plan was implemented to determine whether the water use in the basin exceeded the “safe yield” or “the amount of water that can be withdrawn from a water resource over a period of time without impairing the long-term utility of a water resource.” A groundwater and surface-water flow (GSFLOW) model was developed for Laurel Hill Creek and calibrated to the measured daily streamflow from 1991 to 2007 for the streamflow-gaging station near the outlet of the basin at Ursina, Pa. The CWPA designation requires an assessment of current and future water use. The calibrated GSFLOW model can be used to assess the hydrologic effects of future changes in water use and land use in the basin.
Analyses of samples collected for surface-water quality during base-flow conditions indicate that the highest nutrient concentrations in the main stem of Laurel Hill Creek were at sites in the northeastern part of the basin where agricultural activity is prominent. All of the total nitrogen (N) and a majority of the total phosphorus (P) concentrations in the main stem exceeded regional nutrient criteria levels of 0.31 and 0.01 milligrams per liter (mg/L), respectively. The highest total N and total P concentrations in the main stem were 1.42 and 0.06 mg/L, respectively. Tributary sites with the highest nutrient concentrations are in subbasins where treated wastewater is discharged, such as Kooser Run and Lost Creek. The highest total N and total P concentrations in subbasins were 3.45 and 0.11 mg/L, respectively. Dissolved chloride and sodium concentrations were highest in the upper part of the basin downstream from Interstate 76 because of road deicing salts. The mean base-flow concentrations of dissolved chloride and sodium were 117 and 77 mg/L, respectively, in samples from the main stem just below Interstate 76, and the mean concentrations in Clear Run were 210 and 118 mg/L, compared to concentrations less than 15 mg/L in tributaries that were not affected by highway runoff. Water quality in forested tributary subbasins underlain by the Allegheny and Pottsville Formations was influenced by acidic precipitation and, to a lesser extent, the underlying geology as indicated by pH values less than 5.0 and corresponding specific conductance ranging from 26 to 288 microsiemens per centimeter at 25 degrees Celsius for some samples; in contrast, pH values for main stem sites ranged from 6.6 to 8.5. Manganese (Mn) was the only dissolved constituent in the surface-water samples that exceeded the secondary maximum contaminant level (SMCL). More than one-half the samples from the main stem had Mn concentrations exceeding the SMCL level of 50 micrograms per liter (μg/L), whereas only 19 percent of samples from tributaries exceeded the SMCL for Mn.
Stream temperatures along the main stem of Laurel Hill Creek became higher moving downstream. During the summer months of June through August, the daily mean temperatures at the five sites exceeded the limit of 18.9 degrees Celsius (°C) for a cold-water fishery. The maximum instantaneous values for each site ranged from 27.2 to 32.8 °C.
Water-quality samples collected at groundwater sites (wells and springs) indicate that wells developed within the Mauch Chunk Formation had the best water quality, whereas wells developed within the Allegheny and Pottsville Formations yielded the poorest water quality. Waters from the Mauch Chunk Formation had the highest median pH (7.6) and alkalinity (80 mg/L calcium carbonate) values. The lowest pH and alkalinity median values were in waters from the Allegheny and Pottsville Formations. Groundwater samples collected from wells in the Allegheny and Pottsville Formations also had the highest concentrations of dissolved iron (Fe) and dissolved Mn. Seventy-eight percent of the groundwater samples collected from the Allegheny Formation exceeded the SMCL of 300 μg/L for Fe and 50 μg/L for Mn. Forty-three and 62 percent of the groundwater samples collected from the Pottsville Formation exceeded the SMCL for iron and Mn, respectively. The highest Fe and Mn concentrations for surface waters were measured for tributaries draining the Pottsville Formation. The highest median Fe concentration for tributaries was in samples from streams draining the Allegheny Formation.
During base-flow conditions, the streamflow per unit area along the main stem of Laurel Hill Creek was lowest in the upper parts of the basin [farthest upstream site 0.07 cubic foot per second per square mile (ft3/s/mi2)] and highest (two sites averaging about 0.20 (ft3/s/mi2) immediately downstream from Laurel Hill Lake in the center of the basin. Tributaries with the highest streamflow per unit area were those subbasins that drain the western ridge of the Laurel Hill Creek Basin. The mean streamflow per unit area for tributaries draining areas that extend into the western ridge and draining eastern or central sections was 0.24 and 0.05 ft3/s/mi2, respectively. In general, as the drainage area increased for tributary basins, the streamflow per unit area increased.
Criteria established by the Pennsylvania Department of Environmental Protection indicate that the safe yield of water withdrawals from the Laurel Hill Creek Basin is 1.43 million gallons per day (Mgal/d). Water-use data for 2009 indicate that net (water withdrawals subtracted by water discharges) water withdrawals from groundwater and surface-water sources in the basin were approximately 1.93 Mgal/d. Water withdrawals were concentrated in the upper part of the basin with approximately 80 percent of the withdrawals occurring in the upper 36 mi2 of the basin. Three subbasins—Allen Creek, Kooser Run, and Shafer Run— in the upper part were affected the most by water withdrawals such that safe yields were exceeded by more than 1,000 percent in the first two and more than 500 percent in the other. In the subbasin of Shafer Run, intermittent streamflow characterizes sections that historically have been perennial.
The GSFLOW model of the Laurel Hill Creek Basin is a simple one-layer representation of the groundwater flow system. The GSFLOW model was primarily calibrated to reduce the error term associated with base-flow periods. The total amount of observed streamflow at the Laurel Hill Creek at Ursina, Pa. streamflow-gaging station and the simulated streamflow were within 0.1 percent over the entire modeled period; however, annual differences between simulated and observed streamflow showed a range of -27 to 24 percent from 1992 to 2007 with nine of the years having less than a 10-percent difference. The primary source of simulated streamflow in the GSFLOW model was the subsurface (interflow; 62 percent), followed by groundwater (25 percent) and surface runoff (13 percent). Most of the simulated subsurface flow that reached the stream was in the form of slow flow as opposed to preferential (fast) interflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165082","collaboration":"Prepared in cooperation with the Somerset County Conservation District","usgsCitation":"Galeone, D.G., Risser, D.W., Eicholtz, L.W., and Hoffman, S.A., 2017, Water quality and quantity and simulated surface-water and groundwater flow in the Laurel Hill Creek Basin, southwestern Pennsylvania, 1991–2007: U.S. Geological Survey Scientific Investigations Report 2016–5082, 85 p., https://doi.org/10.3133/sir20165082.","productDescription":"Report: vii, 85 p.; Appendices 1, 4","startPage":"1","endPage":"85","numberOfPages":"97","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-006526","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":343501,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5082/sir20165082_appendix4.xlsx","text":"Appendix 4","linkHelpText":"- Concentrations of selected water-quality constituents and values of selected physical characteristics in groundwater samples collected in the Laurel Hill Creek Basin, southwestern, Pennsylvania, summer and fall 2007"},{"id":343499,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5082/sir20165082.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5082"},{"id":343498,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5082/coverthb.jpg"},{"id":343500,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5082/sir20165082_appendix1.xlsx","text":"Appendix 1","linkHelpText":"- Concentrations of selected water-quality constituents and values of selected physical characteristics in surface-water samples collected during low-flow conditions in the Laurel Hill Creek Basin, southwestern, Pennsylvania, June and September 2007"}],"country":"United 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U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Recent reductions in thickness and extent have increased drift rates of Arctic sea ice. Increased ice drift could significantly affect the movements and the energy balance of polar bears (Ursus maritimus) which forage, nearly exclusively, on this substrate. We used radio-tracking and ice drift data to quantify the influence of increased drift on bear movements, and we modeled the consequences for energy demands of adult females in the Beaufort and Chukchi seas during two periods with different sea ice characteristics. Westward and northward drift of the sea ice used by polar bears in both regions increased between 1987–1998 and 1999–2013. To remain within their home ranges, polar bears responded to the higher westward ice drift with greater eastward movements, while their movements north in the spring and south in fall were frequently aided by ice motion. To compensate for more rapid westward ice drift in recent years, polar bears covered greater daily distances either by increasing their time spent active (7.6%–9.6%) or by increasing their travel speed (8.5%–8.9%). This increased their calculated annual energy expenditure by 1.8%–3.6% (depending on region and reproductive status), a cost that could be met by capturing an additional 1–3 seals/year. Polar bears selected similar habitats in both periods, indicating that faster drift did not alter habitat preferences. Compounding reduced foraging opportunities that result from habitat loss; changes in ice drift, and associated activity increases, likely exacerbate the physiological stress experienced by polar bears in a warming Arctic.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13746","usgsCitation":"Durner, G.M., Douglas, D.C., Albeke, S., Whiteman, J.P., Amstrup, S.C., Richardson, E., Wilson, R.H., and Ben-David, M., 2017, Increased Arctic sea ice drift alters adult female polar bear movements and energetics: Global Change Biology, v. 23, no. 9, p. 3460-3473, https://doi.org/10.1111/gcb.13746.","productDescription":"14 p.","startPage":"3460","endPage":"3473","ipdsId":"IP-075197","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":343520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-06","publicationStatus":"PW","scienceBaseUri":"59649231e4b0d1f9f05acd0f","contributors":{"authors":[{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":704053,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":704054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albeke, Shannon","contributorId":194426,"corporation":false,"usgs":false,"family":"Albeke","given":"Shannon","affiliations":[],"preferred":false,"id":704055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whiteman, John P.","contributorId":194427,"corporation":false,"usgs":false,"family":"Whiteman","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":704056,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":704057,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richardson, Evan","contributorId":194428,"corporation":false,"usgs":false,"family":"Richardson","given":"Evan","affiliations":[],"preferred":false,"id":704058,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":704059,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ben-David, Merav","contributorId":190901,"corporation":false,"usgs":false,"family":"Ben-David","given":"Merav","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":704060,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70232549,"text":"70232549 - 2017 - Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon","interactions":[],"lastModifiedDate":"2022-07-07T12:12:01.261898","indexId":"70232549","displayToPublicDate":"2017-07-07T07:08:45","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"chapter":"8","title":"Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon","docAbstract":"In 1992, Snake River basin fall Chinook salmon (Oncorhynchus tshawytscha) were listed for protection under the U.S. Endangered Species Act (NMFS 1992) and the population remained below 1000 individuals until 2000. Since then, returns from natural production has rebounded to over 20,000 spawners owing to a host of factors including reduced harvest (Peters et al. 2001), stable minimum spawning flows (Groves and Chandler 1999), summer flow augmentation (Connor et al. 2003), predator control (Beamesderfer et al. 1996), hatchery supplementation (Rosenberger et al. 2017), improved juvenile passage structures (Adams et al.\n2014), summer spill operations (Perry et al. 2006; Adams et al. 2008), and periods of favorable ocean conditions and food availability (Logerwell et al. 2003; Peterson et al. 2014). Given this change in abundance coincident with numerous management actions and fluctuation in environmental drivers, quantifying which factors contributed to the observed rebound in natural \nproduction can provide critical insights into future management actions for this at-risk population.\n\nMultistage life cycle models provide a powerful analytical framework for understating how each life stage of a population contributes to population growth rate (Moussalli and Hilborn 1986; Greene and Beechie 2004). Multistage models may also be used as an analytical framework to explicitly estimate demographic parameters of a population model. This approach has an advantage over single-stage stock-recruitment models by allowing population growth rates to be partitioned among life stages rather than aggregated over an entire life cycle. Such partitioning allows for estimating 1) stage-specific density dependence, and 2) stage-specific effects of environmental factors or management actions. For example, Zabel et al. (2006) estimated parameters of a multistage model used in the context of a population viability analysis for spring/summer Chinook salmon in the Snake River, but such an approach has yet to be applied to fall Chinook salmon in the Snake River basin.\n\nTypically, data informing estimates of abundance at particular “check points” in the life cycle determines the complexity of the multistage model that can be fit to the data. For fall Chinook salmon, we are developing a two-stage model that encompasses: 1) upstream passage of spawners at Lower Granite Dam (LGR) to the subsequent downstream passage of their progeny at the dam, and 2) downstream passage of juveniles at LGR to their subsequent return from the ocean and passage at the Dam 2‒6 years later. This approach partitions the life cycle of fall Chinook salmon both spatially and temporally, which allows us to fit and compare alternative models with covariates specific to each stage. Our previous report to the ISAB (Zabel et al.\n2013) detailed methods for estimating abundance of naturally produced adults and juveniles passing Lower Granite Dam, which provides the requisite data for fitting a two-stage model.\n \nThe intent of this report is to describe the structure of the two-stage life cycle model, present preliminary results from fitting the model to data, and outline future directions and developments.\n\nAs is clear from the diversity of models presented in this report, “life cycle models” range from very simple theoretically based population models (e.g., the Beverton-Holt stock- recruitment model) to very complex spatially explicit simulation models linked to hydrosystem hydrodynamic models (e.g., the COMPASS model for a single transition in a life cycle model, Zabel et al. 2008). We chose to develop a model of intermediate complexity that casts the two- stage life cycle model in a state-space framework (Newman et al. 2014). We chose to use a state-space framework implemented in a Bayesian framework because:\n\n• It provides both a statistical estimation framework for retrospective statistical analysis and a stochastic simulation framework for prospective analysis to evaluate alternative management actions.\n• Abundance estimates are uncertain. A state-space framework accounts for observation uncertainty in the abundance estimates and other data (e.g., age structure) while simultaneously estimating process uncertainty.\n• It allows for missing data. By drawing missing data from an appropriate probability model, uncertainty owing to missing data can be propagated without having to omit data or assume fixed values for missing data.\n\nThus, a two-stage state-space life cycle model for fall Chinook salmon strikes an appropriate balance between model complexity, tractability, and applicability given the goals of performing both retrospective and prospective analysis to guide future management of this population.","language":"English","publisher":"Independent Scientific Advisory Board for the Northwest Power and Conservation Council","collaboration":"Bonneville Power Administration","usgsCitation":"Perry, R., Plumb, J., Tiffan, K., Connor, W.P., Cooney, T.D., and Young, W., 2017, Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon, 32 p.","productDescription":"32 p.","ipdsId":"IP-087390","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":403131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403116,"type":{"id":15,"text":"Index Page"},"url":"https://www.nwcouncil.org/reports/review-of-noaa-fisheries-interior-columbia-basin-life-cycle-modeling-draft-report/"}],"country":"United States","state":"Idaho, Oregon, Washington, Wyoming","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.42138671875,\n 41.623655390686395\n ],\n [\n -109.3359375,\n 41.623655390686395\n ],\n [\n -109.3359375,\n 47.14489748555398\n ],\n [\n -119.42138671875,\n 47.14489748555398\n ],\n [\n -119.42138671875,\n 41.623655390686395\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":845935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":223219,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":845936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tiffan, Kenneth 0000-0002-5831-2846","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":217812,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":845937,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Connor, William P.","contributorId":107589,"corporation":false,"usgs":false,"family":"Connor","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID 83544","active":true,"usgs":false}],"preferred":false,"id":845938,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooney, Thomas D.","contributorId":138838,"corporation":false,"usgs":false,"family":"Cooney","given":"Thomas","email":"","middleInitial":"D.","affiliations":[{"id":12540,"text":"National Marine Fisheries Service, Northwest Fisheries Science Center, Conservation Biology Division, 525 Northeast Oregon Street, Portland, OR 97232","active":true,"usgs":false}],"preferred":false,"id":845939,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, William","contributorId":138842,"corporation":false,"usgs":false,"family":"Young","given":"William","email":"","affiliations":[{"id":12542,"text":"Washington Dept. of Fish and Wildlife, Snake River Laboratory, 401 South Cottonwood St., Dayton WA 99328","active":true,"usgs":false}],"preferred":false,"id":845940,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189277,"text":"70189277 - 2017 - Mapping burned areas using dense time-series of Landsat data","interactions":[],"lastModifiedDate":"2022-04-22T15:43:05.359179","indexId":"70189277","displayToPublicDate":"2017-07-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Mapping burned areas using dense time-series of Landsat data","docAbstract":"Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, in many areas existing fire occurrence datasets are known to be incomplete. Consequently, the need to systematically collect burned area information has been recognized by the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change, which have both called for the production of essential climate variables (ECVs), including information about burned area. In this paper, we present an algorithm that identifies burned areas in dense time-series of Landsat data to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm uses gradient boosted regression models to generate burn probability surfaces using band values and spectral indices from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference predictors. Burn classifications are generated from the burn probability surfaces using pixel-level thresholding in combination with a region growing process. The algorithm can be applied anywhere Landsat and training data are available. For this study, BAECV products were generated for the conterminous United States from 1984 through 2015. These products consist of pixel-level burn probabilities for each Landsat scene, in addition to, annual composites including: the maximum burn probability and a burn classification. We compared the BAECV burn classification products to the existing Global Fire Emissions Database (GFED; 1997–2015) and Monitoring Trends in Burn Severity (MTBS; 1984–2013) data. We found that the BAECV products mapped 36% more burned area than the GFED and 116% more burned area than MTBS. Differences between the BAECV products and the GFED were especially high in the West and East where the BAECV products mapped 32% and 88% more burned area, respectively. However, the BAECV products found less burned area than the GFED in regions with frequent agricultural fires. Compared to the MTBS data, the BAECV products identified 31% more burned area in the West, 312% more in the Great Plains, and 233% more in the East. Most pixels in the MTBS data were detected by the BAECV, regardless of burn severity. The BAECV products document patterns of fire similar to those in the GFED but also showed patterns of fire that are not well characterized by the existing MTBS data. We anticipate the BAECV products will be useful to studies that seek to understand past patterns of fire occurrence, the drivers that created them, and the impacts fires have on natural and human systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.06.027","usgsCitation":"Hawbaker, T., Vanderhoof, M.K., Beal, Y.G., Takacs, J., Schmidt, G.L., Falgout, J.T., Williams, B., Brunner, N.M., Caldwell, M., Picotte, J.J., Howard, S.M., Stitt, S., and Dwyer, J.L., 2017, Mapping burned areas using dense time-series of Landsat data: Remote Sensing of Environment, v. 198, p. 504-522, https://doi.org/10.1016/j.rse.2017.06.027.","productDescription":"19 p.","startPage":"504","endPage":"522","ipdsId":"IP-077532","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":469690,"rank":1,"type":{"id":40,"text":"Open Access Publisher 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Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":703878,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Howard, Stephen M. 0000-0001-5255-5882 smhoward@usgs.gov","orcid":"https://orcid.org/0000-0001-5255-5882","contributorId":3483,"corporation":false,"usgs":true,"family":"Howard","given":"Stephen","email":"smhoward@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":703879,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stitt, Susan 0000-0002-0663-2696","orcid":"https://orcid.org/0000-0002-0663-2696","contributorId":194383,"corporation":false,"usgs":false,"family":"Stitt","given":"Susan","affiliations":[],"preferred":false,"id":703880,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":703881,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70200982,"text":"70200982 - 2017 - The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA","interactions":[],"lastModifiedDate":"2018-11-20T10:46:43","indexId":"70200982","displayToPublicDate":"2017-07-06T10:46:25","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA","docAbstract":"A synthesis of field, biostratigraphic, detrital zircon geochronologic, and remote sensing data across north-central Nevada, United States, defines a thick, regionally extensive sheet of Middle–Upper Ordovician Valmy Formation quartzite that structurally overlies deformed early Paleozoic units of the Roberts Mountains allochthon. Late Paleozoic regional unconformities that record tectonic disruptions have been recognized in the foreland of central and eastern Nevada and locally within the Roberts Mountains allochthon; these identify multiple, regional tectonic events between the Devonian–Mississippian initiation of the Antler orogeny and the Permian–Triassic Sonoma orogeny. However, few studies have documented the regional kinematic history of the Robert Mountains allochthon sensu stricto. In the Independence Mountains of northern Nevada, emplacement of the Roberts Mountains allochthon is restricted to the Mississippian. In the Tuscarora Mountains, the range west and southwest of the Independence Mountains, several deformation events have been identified, and emplacement of the thrust sheet containing the Valmy Formation is restricted to the Late Pennsylvanian–Early Permian. These structural and temporal relations, reflected in the Antler foreland basin adjacent to the Roberts Mountains allochthon and overlap sequences, suggest that the Roberts Mountains allochthon is a composite stratigraphic terrane assembled along the Cordilleran margin during two or more late Paleozoic contractional events.
Valmy Formation deposits likely represent the development of coalescing submarine fans below or within bypass channels in a deep slope or rise environment. Petrographic characteristics, biostratigraphy, and detrital zircon U-Pb age populations of the Valmy Formation link it to coeval slope and rise turbidites of the Vinini Formation and shelfal Eureka Quartzite; Valmy Formation detrital zircon age populations are dissimilar to the rift-to-drift facies of the Neoproterozoic–Cambrian Prospect Mountain Quartzite. Throughout north-central Nevada, the Valmy Formation is in fault contact with units of the Roberts Mountains allochthon, including the Devonian–Mississippian Slaven Chert, Silurian–Devonian Elder Sandstone, and Cambrian(?)–Ordovician Vinini Formation, which were deformed prior to, or during, emplacement of the thrust sheet containing Valmy Formation quartzite. Our mapping and data synthesis, guided by regional quartz maps based on remote sensing (Advanced Spaceborne Thermal Emission and Reflection Radiometer [ASTER]) data, delineate similar structural relationships discontinuously for >200 km along strike of the Roberts Mountains allochthon.
Exploration for concealed gold deposits within reach of drilling requires knowledge of the relative thicknesses of the Roberts Mountains allochthon and the Valmy Formation. Overall thicknesses of deformed Roberts Mountains allochthon units between the Valmy Formation and underlying carbonate rocks, which host large, world-class Carlin-type gold deposits, vary by hundreds of meters, but are generally less than 700 m in three of the areas studied here. Recognition of windows through and klippen of the Roberts Mountains allochthon is essential for identification of areas where deposits may be at or near the surface. Correspondingly, most ongoing exploration for Carlin-type gold deposits subjacent to the Roberts Mountains allochthon targets concealed deposits. The model proposed in this study is applicable to determining depth to rocks prospective for undiscovered deposits.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31491.1","usgsCitation":"Holm-Denoma, C.S., Hofstra, A.H., Rockwell, B., and Noble, P.J., 2017, The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA: GSA Bulletin, v. 129, no. 11-12, p. 1521-1536, https://doi.org/10.1130/B31491.1.","productDescription":"16 p.","startPage":"1521","endPage":"1536","ipdsId":"IP-077542","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":359600,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 40\n ],\n [\n -115.5,\n 40\n ],\n [\n -115.5,\n 42\n ],\n [\n -117,\n 42\n ],\n [\n -117,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"129","issue":"11-12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-06","publicationStatus":"PW","scienceBaseUri":"5bf52b6ae4b045bfcae28010","contributors":{"authors":[{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440 cholm-denoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":2442,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher","email":"cholm-denoma@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":203924,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noble, Paula J.","contributorId":40455,"corporation":false,"usgs":true,"family":"Noble","given":"Paula","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":751548,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188893,"text":"ds1055 - 2017 - Evidence of absence (v2.0) software user guide","interactions":[],"lastModifiedDate":"2020-08-21T22:26:18.261745","indexId":"ds1055","displayToPublicDate":"2017-07-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1055","title":"Evidence of absence (v2.0) software user guide","docAbstract":"Evidence of Absence software (EoA) is a user-friendly software application for estimating bird and bat fatalities at wind farms and for designing search protocols. The software is particularly useful in addressing whether the number of fatalities is below a given threshold and what search parameters are needed to give assurance that thresholds were not exceeded. The software also includes tools (1) for estimating carcass persistence distributions and searcher efficiency parameters (\uD835\uDC5D and \uD835\uDC58) from field trials, (2) for projecting future mortality based on past monitoring data, and (3) for exploring the potential consequences of various choices in the design of long-term incidental take permits for protected species. The software was designed specifically for cases where tolerance for mortality is low and carcass counts are small or even 0, but the tools also may be used for mortality estimates when carcass counts are large.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1055","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Dalthorp, Daniel, Huso, Manuela, and Dail, David, 2017, Evidence of absence (v2.0) software user guide: U.S. Geological Survey Data Series 1055, 109 p., https://doi.org/10.3133/ds1055.","productDescription":"Report: viii, 109 p.; Additional Report Pieces","onlineOnly":"Y","ipdsId":"IP-086433","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":343451,"rank":8,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/ds1055_eoa_csv-templates.zip","text":"CSV templates for data entry","size":"1 KB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1055 CSV templates for data entry"},{"id":343762,"rank":7,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/software_revision_history.txt","text":"Evidence of Absence software revision history","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1055 Evidence of Absence software revision history"},{"id":377775,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/r4_0_2/eoa_2.0.7.tar.gz","text":"Evidence of Absence software for MAC-UNIX, with R version >=4.0.2","size":"3.3 MB (tar.gz)","description":"DS 1055 Evidence of Absence software for MAC-UNIX, with R version >=4.0.2"},{"id":377774,"rank":5,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/r4_0_2/eoa_2.0.7.zip","text":"Evidence of Absence software for Windows, with R version >=4.0.2","size":"1.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1055 Evidence of Absence software for Windows, with R version >=4.0.2"},{"id":343450,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/eoa_2.0.7.tar.gz","text":"Evidence of Absence software for MAC-UNIX, with R versions 3.3.0 through 3.6.3","size":"3.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1055 Evidence of Absence software for MAC-UNIX, with R versions 3.3.0 through 3.6.3"},{"id":343449,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/eoa_2.0.7.zip","text":"Evidence of Absence software for Windows, with R versions 3.3.0 through 3.6.3","size":"1.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1055 Evidence of Absence software for Windows, with R versions 3.3.0 through 3.6.3"},{"id":343448,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1055/ds1055.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1055"},{"id":343447,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1055/coverthb.jpg"},{"id":343452,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/0881/","text":"Data Series 881—Evidence of Absence Software (1.0)","description":"Evidence of Absence Software User Guide (1.0)"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Prescribed fire is used to reverse invasion by woody vegetation on grasslands, but managers often are uncertain whether influences of shrub and tree reduction outweigh potential effects of fire on nest survival of grassland birds. During the 2001–2003 breeding seasons, we examined relationships of prescribed fire and woody vegetation to nest survival of clay-colored sparrow (Spizella pallida) and Savannah sparrow (Passerculus sandwichensis) in mixed-grass prairie at Des Lacs National Wildlife Refuge in northwestern North Dakota, USA. We assessed relationships of nest survival to 1) recent fire history, in terms of number of breeding seasons (2, 3, or 4–5) since the last prescribed fire, and 2) prevalence of trees and tall (>1.5 m) shrubs in the landscape and of low (≤1.5 m) shrubs within 5 m of nests. Nest survival of both species exhibited distinct patterns related to age of the nest and day of year, but bore no relationship to fire history. Survival of clay-colored sparrow nests declined as the amount of trees and tall shrubs within 100 m increased, but we found no relationship to suggest nest parasitism by brown-headed cowbirds (Molothrus ater) as an underlying mechanism. We found little evidence linking nest survival of Savannah sparrow to woody vegetation. Our results suggest that fire can be used to restore northern mixed-grass prairies without adversely affecting nest survival of ≥2 widespread passerine species. Survival of nests of clay-colored sparrow may increase when tall woody cover is reduced by fire. Our data lend support to the use of fire for reducing scattered patches of tall woody cover to enhance survival of nests of ≥1 grassland bird species in northern mixed-grass prairies, but further study is needed that incorporates experimental approaches and assessments of shorter term effects of fire on survival of nests of grassland passerines.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.780","usgsCitation":"Murphy, R.K., Shaffer, T.L., Grant, T.A., Derrig, J.L., Rubin, C.S., and Kerns, C.K., 2017, Sparrow nest survival in relation to prescribed fire and woody plant invasion in a northern mixed-grass prairie: Wildlife Society Bulletin, v. 41, no. 3, p. 442-452, https://doi.org/10.1002/wsb.780.","productDescription":"11 p.","startPage":"442","endPage":"452","ipdsId":"IP-045948","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":499888,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/d19b29daa58a454f9da6891f214753d5","text":"External Repository"},{"id":343421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Des Lacs National Wildlife Refuge","volume":"41","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-24","publicationStatus":"PW","scienceBaseUri":"595f4c37e4b0d1f9f057e303","contributors":{"authors":[{"text":"Murphy, Robert K.","contributorId":67643,"corporation":false,"usgs":false,"family":"Murphy","given":"Robert","email":"","middleInitial":"K.","affiliations":[{"id":56253,"text":"Eagle Environmental, Inc","active":true,"usgs":false}],"preferred":false,"id":703417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaffer, Terry L. 0000-0001-6950-8951 tshaffer@usgs.gov","orcid":"https://orcid.org/0000-0001-6950-8951","contributorId":3192,"corporation":false,"usgs":true,"family":"Shaffer","given":"Terry","email":"tshaffer@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":703413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grant, Todd A.","contributorId":194194,"corporation":false,"usgs":false,"family":"Grant","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":703415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Derrig, James L.","contributorId":194193,"corporation":false,"usgs":false,"family":"Derrig","given":"James","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":703414,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rubin, Cory S.","contributorId":194196,"corporation":false,"usgs":false,"family":"Rubin","given":"Cory","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":703418,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kerns, Courtney K.","contributorId":194195,"corporation":false,"usgs":false,"family":"Kerns","given":"Courtney","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":703416,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189263,"text":"70189263 - 2017 - A 184-year record of river meander migration from tree rings, aerial imagery, and cross sections","interactions":[],"lastModifiedDate":"2017-07-06T20:55:01","indexId":"70189263","displayToPublicDate":"2017-07-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"A 184-year record of river meander migration from tree rings, aerial imagery, and cross sections","docAbstract":"Channel migration is the primary mechanism of floodplain turnover in meandering rivers and is essential to the persistence of riparian ecosystems. Channel migration is driven by river flows, but short-term records cannot disentangle the effects of land use, flow diversion, past floods, and climate change. We used three data sets to quantify nearly two centuries of channel migration on the Powder River in Montana. The most precise data set came from channel cross sections measured an average of 21 times from 1975 to 2014. We then extended spatial and temporal scales of analysis using aerial photographs (1939–2013) and by aging plains cottonwoods along transects (1830–2014). Migration rates calculated from overlapping periods across data sets mostly revealed cross-method consistency. Data set integration revealed that migration rates have declined since peaking at 5 m/year in the two decades after the extreme 1923 flood (3000 m3/s). Averaged over the duration of each data set, cross section channel migration occurred at 0.81 m/year, compared to 1.52 m/year for the medium-length air photo record and 1.62 m/year for the lengthy cottonwood record. Powder River peak annual flows decreased by 48% (201 vs. 104 m3/s) after the largest flood of the post-1930 gaged record (930 m3/s in 1978). Declining peak discharges led to a 53% reduction in channel width and a 29% increase in sinuosity over the 1939–2013 air photo record. Changes in planform geometry and reductions in channel migration make calculations of floodplain turnover rates dependent on the period of analysis. We found that the intensively studied last four decades do not represent the past two centuries
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2017.06.001","usgsCitation":"Schook, D.M., Rathburn, S.L., Friedman, J.M., and Wolf, J.M., 2017, A 184-year record of river meander migration from tree rings, aerial imagery, and cross sections: Geomorphology, v. 293, no. Part A, p. 227-239, https://doi.org/10.1016/j.geomorph.2017.06.001.","productDescription":"13 p.","startPage":"227","endPage":"239","ipdsId":"IP-087820","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469693,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2017.06.001","text":"Publisher Index Page"},{"id":343460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"293","issue":"Part A","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595f4c32e4b0d1f9f057e2d5","contributors":{"authors":[{"text":"Schook, Derek M.","contributorId":178325,"corporation":false,"usgs":false,"family":"Schook","given":"Derek","email":"","middleInitial":"M.","affiliations":[{"id":13539,"text":"Department of Geosciences, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":703800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rathburn, Sara L.","contributorId":140606,"corporation":false,"usgs":false,"family":"Rathburn","given":"Sara","email":"","middleInitial":"L.","affiliations":[{"id":13539,"text":"Department of Geosciences, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":703801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663 friedmanj@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":2473,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","email":"friedmanj@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":703799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolf, J. Marshall","contributorId":194350,"corporation":false,"usgs":false,"family":"Wolf","given":"J.","email":"","middleInitial":"Marshall","affiliations":[{"id":17860,"text":"Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":703802,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189211,"text":"70189211 - 2017 - Quantifying the heterogeneity of the tectonic stress field using borehole data","interactions":[],"lastModifiedDate":"2017-09-25T13:53:59","indexId":"70189211","displayToPublicDate":"2017-07-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the heterogeneity of the tectonic stress field using borehole data","docAbstract":"The heterogeneity of the tectonic stress field is a fundamental property which influences earthquake dynamics and subsurface engineering. Self-similar scaling of stress heterogeneities is frequently assumed to explain characteristics of earthquakes such as the magnitude-frequency relation. However, observational evidence for such scaling of the stress field heterogeneity is scarce.
We analyze the local stress orientations using image logs of two closely spaced boreholes in the Coso Geothermal Field with sub-vertical and deviated trajectories, respectively, each spanning about 2 km in depth. Both the mean and the standard deviation of stress orientation indicators (borehole breakouts, drilling-induced fractures and petal-centerline fractures) determined from each borehole agree to the limit of the resolution of our method although measurements at specific depths may not. We find that the standard deviation in these boreholes strongly depends on the interval length analyzed, generally increasing up to a wellbore log length of about 600 m and constant for longer intervals. We find the same behavior in global data from the World Stress Map. This suggests that the standard deviation of stress indicators characterizes the heterogeneity of the tectonic stress field rather than the quality of the stress measurement. A large standard deviation of a stress measurement might be an expression of strong crustal heterogeneity rather than of an unreliable stress determination. Robust characterization of stress heterogeneity requires logs that sample stress indicators along a representative sample volume of at least 1 km.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014370","usgsCitation":"Schoenball, M., and Davatzes, N.C., 2017, Quantifying the heterogeneity of the tectonic stress field using borehole data: Journal of Geophysical Research B: Solid Earth, v. 122, no. 8, p. 6737-6756, https://doi.org/10.1002/2017JB014370.","productDescription":"20 p.","startPage":"6737","endPage":"6756","ipdsId":"IP-079145","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":343397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595f4c36e4b0d1f9f057e2f5","contributors":{"authors":[{"text":"Schoenball, Martin mschoenball@usgs.gov","contributorId":5760,"corporation":false,"usgs":true,"family":"Schoenball","given":"Martin","email":"mschoenball@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":703528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davatzes, Nicholas C.","contributorId":138855,"corporation":false,"usgs":false,"family":"Davatzes","given":"Nicholas","email":"","middleInitial":"C.","affiliations":[{"id":12547,"text":"Temple University","active":true,"usgs":false}],"preferred":false,"id":703529,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70263786,"text":"70263786 - 2017 - Determination of earthquake magnitude for early warning from the time-dependence of P-wave amplitudes","interactions":[],"lastModifiedDate":"2025-02-24T15:51:02.184943","indexId":"70263786","displayToPublicDate":"2017-07-04T09:48:16","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Determination of earthquake magnitude for early warning from the time-dependence of P-wave amplitudes","title":"Determination of earthquake magnitude for early warning from the time-dependence of P-wave amplitudes","docAbstract":"We propose a method that utilizes the time dependence of P‐wave displacement amplitudes to estimate the final magnitude (M) for earthquake early warning (EEW) before the arrival of the peak amplitude. A relation between M and P‐wave displacement amplitude is employed for the method. Its value is set as a function of time from the P arrival, and is determined using a K‐NET dataset recorded in Japan from a scaling relation between M and the time dependence of P‐wave displacement. A test to check the performance of the proposed equation demonstrates in a statistical sense that this technique enables us to estimate M more rapidly than conventional methods without loss of accuracy. We conclude that the approach proposed in this article effectively gains a longer lead time as well as reduces the blind zone for EEW.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170048","usgsCitation":"Noda, S., and Ellsworth, W.L., 2017, Determination of earthquake magnitude for early warning from the time-dependence of P-wave amplitudes: Bulletin of the Seismological Society of America, v. 107, no. 4, p. 1860-1867, https://doi.org/10.1785/0120170048.","productDescription":"8 p.","startPage":"1860","endPage":"1867","ipdsId":"IP-076689","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"4","noUsgsAuthors":false,"publicationDate":"2017-07-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Noda, Shunta 0000-0002-5897-3409","orcid":"https://orcid.org/0000-0002-5897-3409","contributorId":351252,"corporation":false,"usgs":true,"family":"Noda","given":"Shunta","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928271,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellsworth, William L. 0000-0001-8378-4979 ellsworth@usgs.gov","orcid":"https://orcid.org/0000-0001-8378-4979","contributorId":206685,"corporation":false,"usgs":true,"family":"Ellsworth","given":"William","email":"ellsworth@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928272,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189151,"text":"70189151 - 2017 - The difficulty of measuring the absorption of scattered sunlight by H2O and CO2 in volcanic plumes: A comment on Pering et al. “A novel and inexpensive method for measuring volcanic plume water fluxes at high temporal resolution,” Remote Sens. 2017, 9, 146","interactions":[],"lastModifiedDate":"2017-07-03T09:24:14","indexId":"70189151","displayToPublicDate":"2017-07-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The difficulty of measuring the absorption of scattered sunlight by H2O and CO2 in volcanic plumes: A comment on Pering et al. “A novel and inexpensive method for measuring volcanic plume water fluxes at high temporal resolution,” Remote Sens. 2017, 9, 146","title":"The difficulty of measuring the absorption of scattered sunlight by H2O and CO2 in volcanic plumes: A comment on Pering et al. “A novel and inexpensive method for measuring volcanic plume water fluxes at high temporal resolution,” Remote Sens. 2017, 9, 146","docAbstract":"In their recent study, Pering et al. (2017) presented a novel method for measuring volcanic water vapor fluxes. Their method is based on imaging volcanic gas and aerosol plumes using a camera sensitive to the near-infrared (NIR) absorption of water vapor. The imaging data are empirically calibrated by comparison with in situ water measurements made within the plumes. Though the presented method may give reasonable results over short time scales, the authors fail to recognize the sensitivity of the technique to light scattering on aerosols within the plume. In fact, the signals measured by Pering et al. are not related to the absorption of NIR radiation by water vapor within the plume. Instead, the measured signals are most likely caused by a change in the effective light path of the detected radiation through the atmospheric background water vapor column. Therefore, their method is actually based on establishing an empirical relationship between in-plume scattering efficiency and plume water content. Since this relationship is sensitive to plume aerosol abundance and numerous environmental factors, the method will only yield accurate results if it is calibrated very frequently using other measurement techniques.","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/rs9060534","usgsCitation":"Kern, C., 2017, The difficulty of measuring the absorption of scattered sunlight by H2O and CO2 in volcanic plumes: A comment on Pering et al. “A novel and inexpensive method for measuring volcanic plume water fluxes at high temporal resolution,” Remote Sens. 2017, 9, 146: Remote Sensing, v. 9, no. 6, Article 534: 11 p., https://doi.org/10.3390/rs9060534.","productDescription":"Article 534: 11 p.","ipdsId":"IP-086338","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469700,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9060534","text":"Publisher Index Page"},{"id":343265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-27","publicationStatus":"PW","scienceBaseUri":"595b5795e4b0d1f9f0536da4","contributors":{"authors":[{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":703180,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70193524,"text":"70193524 - 2017 - Diel periodicity and chronology of upstream migration in yellow-phase American eels (Anguilla rostrata)","interactions":[],"lastModifiedDate":"2017-11-02T14:10:10","indexId":"70193524","displayToPublicDate":"2017-07-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Diel periodicity and chronology of upstream migration in yellow-phase American eels (Anguilla rostrata)","title":"Diel periodicity and chronology of upstream migration in yellow-phase American eels (Anguilla rostrata)","docAbstract":"Yellow-phase American eel (Anguilla rostrata) upstream migration is temporally punctuated, yet migration chronology within diel time periods is not well-understood. This study examined diel periodicity, chronology, and total length (TL) of six multi-day, high-count (285–1,868 eels) passage events of upstream migrant yellow-phase American eels at the Millville Dam eel ladder, lower Shenandoah River, West Virginia during 2011–2014. We categorized passage by diel periods (vespertine, nocturnal, matutinal, diurnal) and season (spring, summer, late summer/early fall, fall). We depicted passage counts as time-series histograms and used time-series spectral analysis (Fast Fourier Transformation) to identify cyclical patterns and diel periodicity of upstream migration. We created histograms to examine movement patterns within diel periods for each passage event and fit normal mixture models (2–9 mixtures) to describe multiple peaks of passage counts. Periodicity of movements for each passage event followed a 24-h activity cycle with mostly nocturnal movement. Multimodal models were supported by the data; most modes represented nocturnal movements, but modes at or near the transition between twilight and night were also common. We used mixed-model methodology to examine relationships among TL, diel period, and season. An additive-effects model of diel period + season was the best approximating model. A decreasing trend of mean TL occurred across diel movement periods, with the highest mean TL occurring during fall relative to similar mean values of TL for spring, summer, and late summer/early fall. This study increased our understanding of yellow-phase American eels by demonstrating the non-random nature of their upstream migration.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-017-0614-1","usgsCitation":"Aldinger, J.L., and Welsh, S.A., 2017, Diel periodicity and chronology of upstream migration in yellow-phase American eels (Anguilla rostrata): Environmental Biology of Fishes, v. 100, no. 7, p. 829-838, https://doi.org/10.1007/s10641-017-0614-1.","productDescription":"10 p.","startPage":"829","endPage":"838","ipdsId":"IP-079381","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Millville Dam","volume":"100","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-09","publicationStatus":"PW","scienceBaseUri":"59fc2ea4e4b0531197b27f7f","contributors":{"authors":[{"text":"Aldinger, Joni L.","contributorId":171886,"corporation":false,"usgs":false,"family":"Aldinger","given":"Joni","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":719832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":1483,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"swelsh@usgs.gov","middleInitial":"A.","affiliations":[{"id":205,"text":"Cooperative Research Units","active":false,"usgs":true}],"preferred":false,"id":719265,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189589,"text":"70189589 - 2017 - USGS Integration of New Science and Technology, Appendix A","interactions":[],"lastModifiedDate":"2019-07-12T14:52:13","indexId":"70189589","displayToPublicDate":"2017-07-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"USGS Integration of New Science and Technology, Appendix A","docAbstract":"This product summarizes the USGS plans for integration of new science and technology into Asian Carp control efforts for 2017. This includes the 1) implementation and evaluation of new tactics and behavioral information for monitoring, surveillance, control and containment; 2) understanding behavior and reproduction of Asian carp in established and emerging populations to inform deterrent deployment, rapid response, and removal efforts; and 3) development and evaluation of databases, decision support tools and performance measures.","largerWorkTitle":"2017 Asian Carp Monitoring and Response Plan","language":"English","publisher":"Monitoring and Response Work Group (MRWG) of the Asian Carp Regional Coordinating Committee (ACRCC)","usgsCitation":"Brey, M.K., Knights, B.C., Cupp, A.R., Amberg, J., Chapman, D., Calfee, R.D., and Duncker, J.J., 2017, USGS Integration of New Science and Technology, Appendix A, 5 p.","productDescription":"5 p.","startPage":"A-1","endPage":"A-5","ipdsId":"IP-086655","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":344003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343969,"type":{"id":15,"text":"Index Page"},"url":"https://www.asiancarp.us/PlansReports.html"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e24e4b0d1f9f0640752","contributors":{"authors":[{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705316,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":705317,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":705318,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705319,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202396,"text":"70202396 - 2017 - How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications","interactions":[],"lastModifiedDate":"2019-02-27T13:02:14","indexId":"70202396","displayToPublicDate":"2017-07-01T13:02:07","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications","docAbstract":"Streamflow data are used for important environmental and economic decisions, such as specifying and regulating minimum flows, managing water supplies, and planning for flood hazards. Despite significant uncertainty in most flow data, the flow series for these applications are often communicated and used without uncertainty information. In this commentary, we argue that proper analysis of uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. We substantiate our argument by providing case studies from Norway and New Zealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial water management policy, and tested the accuracy of water quality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flow series realizations rather than simple error bounds. Although examples of such tools are in development, considerable barriers for uncertainty analysis and communication still exist for practitioners, and future research must aim to provide easier access and usability of uncertainty estimates. We conclude that flow uncertainty analysis is critical for good water management decisions.
","language":"English","publisher":"AGU","doi":"10.1002/2016WR020328","usgsCitation":"McMilan, H., Seibert, J., Petersen-Overleir, A., Lang, M., White, P., Snelder, T., Rutherford, K., Krueger, T., Mason,, R., and Kiang, J.E., 2017, How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications: Water Resources Research, v. 53, no. 7, p. 5220-5228, https://doi.org/10.1002/2016WR020328.","productDescription":"9 p.","startPage":"5220","endPage":"5228","ipdsId":"IP-088336","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":469702,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2016wr020328","text":"External Repository"},{"id":361589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"McMilan, Hilary","contributorId":213624,"corporation":false,"usgs":false,"family":"McMilan","given":"Hilary","email":"","affiliations":[{"id":38824,"text":"Department of Geology; San Diego State University, USA","active":true,"usgs":false}],"preferred":false,"id":758172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seibert, Jan","contributorId":176322,"corporation":false,"usgs":false,"family":"Seibert","given":"Jan","email":"","affiliations":[],"preferred":false,"id":758173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen-Overleir, Asgeir","contributorId":213625,"corporation":false,"usgs":false,"family":"Petersen-Overleir","given":"Asgeir","email":"","affiliations":[{"id":38825,"text":"Market Operations Hydrology, Statkraft Energi AS, Norway","active":true,"usgs":false}],"preferred":false,"id":758174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lang, Michel","contributorId":213626,"corporation":false,"usgs":false,"family":"Lang","given":"Michel","email":"","affiliations":[{"id":38826,"text":"Irstea, UR HHLY, Hydrology-Hydraulics, Villeurbanne, France","active":true,"usgs":false}],"preferred":false,"id":758175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Paul","contributorId":213695,"corporation":false,"usgs":false,"family":"White","given":"Paul","affiliations":[],"preferred":false,"id":758176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Snelder, Ton","contributorId":213627,"corporation":false,"usgs":false,"family":"Snelder","given":"Ton","email":"","affiliations":[{"id":38827,"text":"LWP Let, 145c Colombo Street, Christchurch, New Zealand","active":true,"usgs":false}],"preferred":false,"id":758177,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rutherford, Kit","contributorId":213628,"corporation":false,"usgs":false,"family":"Rutherford","given":"Kit","email":"","affiliations":[{"id":38828,"text":"National Institute of Water and Atmospheric Research, Napier, New Zealand","active":true,"usgs":false}],"preferred":false,"id":758178,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krueger, Tobias","contributorId":213629,"corporation":false,"usgs":false,"family":"Krueger","given":"Tobias","email":"","affiliations":[{"id":38829,"text":"IRI THESys, Humboldt-Universitat zu Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":758179,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mason,, Robert R. Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":176493,"corporation":false,"usgs":true,"family":"Mason,","given":"Robert R.","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":758171,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":758180,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70189309,"text":"70189309 - 2017 - Does bioelectrical impedance analysis accurately estimate the condition of threatened and endangered desert fish species?","interactions":[],"lastModifiedDate":"2017-07-11T09:29:00","indexId":"70189309","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Does bioelectrical impedance analysis accurately estimate the condition of threatened and endangered desert fish species?","docAbstract":"Bioelectrical impedance analysis (BIA) is a nonlethal tool with which to estimate the physiological condition of animals that has potential value in research on endangered species. However, the effectiveness of BIA varies by species, the methodology continues to be refined, and incidental mortality rates are unknown. Under laboratory conditions we tested the value of using BIA in addition to morphological measurements such as total length and wet mass to estimate proximate composition (lipid, protein, ash, water, dry mass, energy density) in the endangered Humpback Chub Gila cypha and Bonytail G. elegans and the species of concern Roundtail Chub G. robusta and conducted separate trials to estimate the mortality rates of these sensitive species. Although Humpback and Roundtail Chub exhibited no or low mortality in response to taking BIA measurements versus handling for length and wet-mass measurements, Bonytails exhibited 14% and 47% mortality in the BIA and handling experiments, respectively, indicating that survival following stress is species specific. Derived BIA measurements were included in the best models for most proximate components; however, the added value of BIA as a predictor was marginal except in the absence of accurate wet-mass data. Bioelectrical impedance analysis improved the R2 of the best percentage-based models by no more than 4% relative to models based on morphology. Simulated field conditions indicated that BIA models became increasingly better than morphometric models at estimating proximate composition as the observation error around wet-mass measurements increased. However, since the overall proportion of variance explained by percentage-based models was low and BIA was mostly a redundant predictor, we caution against the use of BIA in field applications for these sensitive fish species.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2017.1302993","usgsCitation":"Dibble, K.L., Yard, M.D., Ward, D.L., and Yackulic, C.B., 2017, Does bioelectrical impedance analysis accurately estimate the condition of threatened and endangered desert fish species?: Transactions of the American Fisheries Society, v. 146, no. 5, p. 888-902, https://doi.org/10.1080/00028487.2017.1302993.","productDescription":"15 p.","startPage":"888","endPage":"902","ipdsId":"IP-076886","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488591,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/dataset/Does_Bioelectrical_Impedance_Analysis_Accurately_Estimate_the_Physiological_Condition_of_Threatened_and_Endangered_Desert_Fish_Species_/5177047","text":"External Repository"},{"id":438281,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CF9NMV","text":"USGS data release","linkHelpText":"Bioelectrical impedance analysis for an endangered desert fish—Data"},{"id":343551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"146","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-05","publicationStatus":"PW","scienceBaseUri":"5965b1b8e4b0d1f9f05b379e","contributors":{"authors":[{"text":"Dibble, Kimberly L. 0000-0003-0799-4477 kdibble@usgs.gov","orcid":"https://orcid.org/0000-0003-0799-4477","contributorId":5174,"corporation":false,"usgs":true,"family":"Dibble","given":"Kimberly","email":"kdibble@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yard, Micheal D. myard@usgs.gov","contributorId":147386,"corporation":false,"usgs":true,"family":"Yard","given":"Micheal","email":"myard@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":704089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ward, David L. 0000-0002-3355-0637 dlward@usgs.gov","orcid":"https://orcid.org/0000-0002-3355-0637","contributorId":3879,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dlward@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704090,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704091,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}