Diamondback terrapins (Malaclemys terrapin) are currently in decline across much of their historical range, and demographic data on a regional scale are needed to identify where their populations are at greatest risk. Because terrapins residing in salt marshes are difficult to capture, we designed a cylindrical bait trap (CBT) that could be deployed in shallow tidal waters. From 2003 to 2006, trials were conducted with CBTs in the Chesapeake Bay, Maryland (USA) to determine terrapin sex, size, and age distribution within 3 salt marsh interior habitats—open bays, tidal guts, and broken marshes—using 15 traps/habitat. Analyses based on 791 total captures with CBTs indicate that smaller terrapins, (i.e., adult male and subadult) were more prevalent within the transecting tidal guts and broken marshes, whereas the adult females were more evenly distributed among habitats, including open bays. Subadult females made up the largest percent of catch in the CBTs deployed within the 3 marsh interior habitats. During a 12-day trial in which we compared capture performance of CBTs and modified fyke nets along open shorelines during the nesting season, fyke nets outperformed CBTs by accounting for 95.2% of the 604 terrapin captures. Although the long drift leads of the fyke nets proved more effective for intercepting along-shore travel of adult female terrapins during the nesting season, CBTs provided a more effective means of live-trapping terrapins within the shallow interior marshes.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Washington, D.C.","doi":"10.1002/wsb.610","usgsCitation":"Henry, P.F., Haramis, G., and Day, D.D., 2016, Evaluating a portable cylindrical bait trap to capture diamondback terrapins in salt marsh: Wildlife Society Bulletin, v. 40, no. 1, p. 160-168, https://doi.org/10.1002/wsb.610.","productDescription":"9 p.","startPage":"160","endPage":"168","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060499","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":500067,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/665f61740326408db40866d1177de199","text":"External Repository"},{"id":319727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Glenn Martin National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.05182647705078,\n 38.017127786121506\n ],\n [\n -76.05182647705078,\n 38.012799997174575\n ],\n [\n -76.05096817016602,\n 38.00928348049952\n ],\n [\n -76.03878021240234,\n 38.00603731538592\n ],\n [\n -76.03689193725586,\n 38.00319680300937\n ],\n [\n -76.0305404663086,\n 38.00157360367438\n ],\n [\n -76.0279655456543,\n 37.99940928200236\n ],\n [\n -76.02161407470703,\n 37.995351006703814\n ],\n [\n -76.01972579956055,\n 37.99251008038448\n ],\n [\n -76.01869583129883,\n 37.990345491241776\n ],\n [\n -76.01285934448242,\n 37.990210202299636\n ],\n [\n -76.0114860534668,\n 37.9881808382286\n ],\n [\n -76.00959777832031,\n 37.98425724185128\n ],\n [\n -76.00753784179688,\n 37.98019812825676\n ],\n [\n -76.00547790527344,\n 37.97843910930459\n ],\n [\n -76.00393295288086,\n 37.97762724018384\n ],\n [\n -76.00255966186523,\n 37.973838398875515\n ],\n [\n -76.00135803222656,\n 37.97167325888967\n ],\n [\n -75.9979248046875,\n 37.96856075828048\n ],\n [\n -75.99294662475586,\n 37.96747811844137\n ],\n [\n -75.9898567199707,\n 37.970049361992054\n ],\n [\n -75.98917007446289,\n 37.97329711986601\n ],\n [\n -75.98814010620117,\n 37.9774919277906\n ],\n [\n -75.98779678344727,\n 37.98060404971996\n ],\n [\n -75.98745346069336,\n 37.982904228934125\n ],\n [\n -75.98487854003906,\n 37.98358073851119\n ],\n [\n -75.9811019897461,\n 37.98398664126368\n ],\n [\n -75.97698211669922,\n 37.98561022982037\n ],\n [\n -75.9759521484375,\n 37.990480779934416\n ],\n [\n -75.97509384155272,\n 37.99724489645483\n ],\n [\n -75.97578048706055,\n 38.00427891593761\n ],\n [\n -75.9785270690918,\n 38.00982449404459\n ],\n [\n -75.97972869873047,\n 38.01307049147015\n ],\n [\n -75.9814453125,\n 38.016451585943095\n ],\n [\n -75.98127365112305,\n 38.020373460133186\n ],\n [\n -75.98299026489256,\n 38.02348376284101\n ],\n [\n -75.98642349243164,\n 38.026458711461245\n ],\n [\n -75.99191665649414,\n 38.0282165788684\n ],\n [\n -75.99552154541016,\n 38.03105612173487\n ],\n [\n -75.99775314331055,\n 38.03457159374112\n ],\n [\n -76.00032806396484,\n 38.037410890266095\n ],\n [\n -76.0066795349121,\n 38.040385273328546\n ],\n [\n -76.01217269897461,\n 38.04173722569343\n ],\n [\n -76.01749420166016,\n 38.042142806535615\n ],\n [\n -76.02367401123047,\n 38.042142806535615\n ],\n [\n -76.02727890014648,\n 38.03984448539368\n ],\n [\n -76.03208541870117,\n 38.037546092117\n ],\n [\n -76.03414535522461,\n 38.03632926647352\n ],\n [\n -76.03860855102539,\n 38.03632926647352\n ],\n [\n -76.04324340820312,\n 38.03430117880767\n ],\n [\n -76.04633331298828,\n 38.031732187147\n ],\n [\n -76.04856491088867,\n 38.02808135979607\n ],\n [\n -76.05096817016602,\n 38.024024671574615\n ],\n [\n -76.05148315429688,\n 38.020373460133186\n ],\n [\n -76.05182647705078,\n 38.017127786121506\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-06","publicationStatus":"PW","scienceBaseUri":"56ff9be4e4b0328dcb7eaaa2","contributors":{"authors":[{"text":"Henry, Paula F. P. 0000-0002-7601-5546 phenry@usgs.gov","orcid":"https://orcid.org/0000-0002-7601-5546","contributorId":4485,"corporation":false,"usgs":true,"family":"Henry","given":"Paula","email":"phenry@usgs.gov","middleInitial":"F. P.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":625871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haramis, G. Michael mharamis@usgs.gov","contributorId":4001,"corporation":false,"usgs":true,"family":"Haramis","given":"G. Michael","email":"mharamis@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":625872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day, Daniel D. 0000-0001-9070-7170 dday@usgs.gov","orcid":"https://orcid.org/0000-0001-9070-7170","contributorId":3985,"corporation":false,"usgs":true,"family":"Day","given":"Daniel","email":"dday@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":625873,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70161832,"text":"sir20155188 - 2016 - Water balance monitoring for two bioretention gardens in Omaha, Nebraska, 2011–14","interactions":[],"lastModifiedDate":"2016-02-08T08:27:29","indexId":"sir20155188","displayToPublicDate":"2016-02-05T13:00:00","publicationYear":"2016","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":"2015-5188","title":"Water balance monitoring for two bioretention gardens in Omaha, Nebraska, 2011–14","docAbstract":"Bioretention gardens are used to help mitigate stormwater runoff in urban settings in an attempt to restore the hydrologic response of the developed land to a natural predevelopment response in which more water is infiltrated rather than routed directly to urban drainage networks. To better understand the performance of bioretention gardens in facilitating infiltration of stormwater in eastern Nebraska, the U.S. Geological Survey, in cooperation with the Douglas County Environmental Services and the Nebraska Environmental Trust, assessed the water balance of two bioretention gardens located in Omaha, Nebraska by monitoring the amount of stormwater entering and leaving the gardens. One garden is on the Douglas County Health Center campus, and the other garden is on the property of the Eastern Nebraska Office on Aging.
For the Douglas County Health Center, bioretention garden performance was evaluated on the basis of volume reduction by comparing total inflow volume to total outflow volume. The bioretention garden reduced inflow volumes from a minimum of 33 percent to 100 percent (a complete reduction in inflow volume) depending on the size of the event. Although variable, the percent reduction of the inflow volume tended to decrease with increasing total event rainfall. To assess how well the garden reduces stormwater peak inflow rates, peak inflows were plotted against peak outflows measured at the bioretention garden. Only 39 of the 255 events had any overflow, indicating 100 percent peak reduction in the other events. Of those 39 events having overflow, the mean peak reduction was 63 percent.
No overflow events were recorded at the bioretention garden at the Eastern Nebraska Office on Aging; therefore, data were not available for an event-based overflow analysis.Monitoring period summary of the water balance at both bio-retention gardens indicates that most of the stormwater in the bioretention gardens is stored in the subsurface.
Evapotranspiration was attributed to a small percentage of the outputs on an annual basis (3 percent at Douglas County Health Center site and 5 percent at Eastern Nebraska Office onAging site), which indicates that vegetative water uptake is not a primary factor in the water budget.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155188","collaboration":"Prepared in cooperation with Douglas County Environmental Services and the Nebraska Environmental Trust","usgsCitation":"Strauch, K.R., Rus, D.L., Holm, K.E., 2016, Water balance monitoring for two bioretention gardens in Omaha, Nebraska, 2011–14, U.S. Geological Survey Scientific Investigation Report 2015–5188, 19 p., https://dx.doi.org/10.3133/sir20155188.","productDescription":"vi, 19 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066874","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":438638,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TS1H1R","text":"USGS data release","linkHelpText":"Water Balance Monitoring Data for Two Biorentention Gardens in Omaha, Nebraska 2011-17"},{"id":315021,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5188/coverthb.jpg"},{"id":315022,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5188/sir20155188.pdf","text":"Report","size":"3.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5188"}],"country":"United States","state":"Nebraska","county":"Douglas County","city":"Omaha","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96,\n 41.2\n ],\n [\n -96,\n 41.3\n ],\n [\n -95.9,\n 41.3\n ],\n [\n -95.9,\n 41.2\n ],\n [\n -96,\n 41.2\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Nebraska Water Science Center
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The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored suspended sediment within constructed Missouri River chutes during March through October 2012. Chutes were constructed at selected river bends by the U.S. Army Corps of Engineers to help mitigate aquatic habitat lost through the creation and maintenance of the navigation channel on the Missouri River. The restoration and development of chutes is one method for creating shallow-water habitat within the Missouri River to meet requirements established by the amended 2000 Biological Opinion. Understanding geomorphic channel-evolution processes and sediment transport is important for the design of chutes, monitoring and maintenance of existing chutes, and characterizing the habitat that the chutes provide. This report describes the methods used to monitor suspended sediment at two Missouri River chutes and presents the results of the data analysis to help understand the suspended-sediment characteristics of each chute and the effect the chutes have on the Missouri River. Upper Hamburg chute, near Nebraska City, Nebraska, and Kansas chute, near Peru, Nebraska, were selected for monitoring. At each study site, monthly discrete samples were collected from April through October in the Missouri River main-channel transects upstream from the chute inlet, downstream from the chute outlet, at the outlet (downstream transect) of both chutes, and at the inlet (upstream transect) of Kansas chute. In addition, grab samples from all chute sampling locations were collected using autosamplers. Suspended-sediment concentration (SSC) and grain-size metrics were determined for all samples (discrete and grab). Continuous water-quality monitors recorded turbidity and water temperature at 15-minute intervals at the three chute sampling locations. Two acoustic Doppler velocimeters, one within each chute, measured water depth and current velocities continuously. The depth and velocity data were used to estimate streamflow within each chute. The sampling design was developed to understand the suspended-sediment differences within each chute and between the chute and the Missouri River main channel during discrete sampling. The sampling design also allowed for site-specific surrogate relations between SSC and turbidity to be developed, which could be used to compute real-time estimates of SSC and sediment loads within the chutes. Real-time estimates of SSC and sediment loads enable a better understanding of sediment transport within the chutes during times when physical samples are not collected, including periods of high flow.
\nHigh flows during the summer of 2011 resulted in substantial alterations to both studied chutes; therefore, the U.S. Army Corps of Engineers repaired and modified both chutes during 2012. These unforeseen repairs and modifications within the chutes added uncertainty to the analysis because concentrations were altered by construction equipment and flow alteration.
\nDaily suspended-sediment and suspended-silt loads were estimated based on surrogate relations with turbidity. A linear regression was used to estimate equal-width increment (EWI)-equivalent SSC from autosampler SSC before using the model-calibration dataset to determine the best-fit model for prediction of SSC from the turbidity and, in some cases, discharge. Correlation between suspended-sand concentration (SSandC) in EWI samples and concurrent samples collected by an autosampler was low; therefore, SSandC was excluded from development of surrogate relations because a large part of the calibration dataset was from autosamples. Instead, SSandC was estimated as SSC minus suspended-silt-clay concentration (SSiltC). At all sites, the best-fit models included the base-10 logarithm of concentration and turbidity, and at Kansas chute upstream, the base-10 logarithm of streamflow was also included in the best-fit models. These surrogate models were used to estimate continuous time series of SSC and SSiltC. Estimated concentrations of suspended sediment were used to estimate instantaneous and daily loads for total suspended sediment, suspended silt-clay, and suspended sand. Estimated daily suspended-sediment loads were not significantly different between upstream and downstream transects within the Kansas chute, and most individual daily loads within the chute were not significantly different between upstream and downstream transects when evaluated using overlap in daily 95-percent confidence intervals. The comparison of daily load values for upstream and downstream chute transects, as estimated from turbidity-based surrogate models for Kansas chute, documents the daily dynamic nature of sediment transport within the chute with a temporal resolution that is not practical with discrete suspended-sediment sampling alone.
\nComparisons of concentrations and loads from EWI samples collected from different transects within a study site resulted in few significant differences, but comparisons are limited by small sample sizes and large within-transect variability. When comparing the Missouri River upstream transect to the chute inlet transect, similar results were determined in 2012 as were determined in 2008—the chute inlet affected the amount of sediment entering the chute from the main channel. In addition, the Kansas chute is potentially affecting the sediment concentration within the Missouri River main channel, but small sample size and construction activities within the chute limit the ability to fully understand either the effect of the chute in 2012 or the effect of the chute on the main channel during a year without construction. Finally, some differences in SSC were detected between the Missouri River upstream transects and the chute downstream transects; however, the effect of the chutes on the Missouri River main-channel sediment transport was difficult to isolate because of construction activities and sampling variability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165002","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Omaha District","usgsCitation":"Densmore, B.K., Rus, D.L., Moser, M.T., Hall, B.M., and Andersen, M.J., 2016, Sediment loads and transport at constructed chutes along the Missouri River—Upper Hamburg chute near Nebraska City, Nebraska, and Kansas chute near Peru, Nebraska, 2012: U.S. Geological Survey Scientific Investigations Report 2016–5002, 47 p. https://dx.doi.org/10.3133/sir20165002.","productDescription":"vii, 47 p.","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064671","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":316553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5002/coverthb.jpg"},{"id":316554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5002/sir20165002.pdf","text":"Report","size":"20.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5002"}],"country":"United States","state":"Nebraska","city":"Nebraska City, Peru","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.78601837158203,\n 40.564937785967224\n ],\n [\n -95.78601837158203,\n 40.61681920737131\n ],\n [\n -95.74241638183592,\n 40.61681920737131\n ],\n [\n -95.74241638183592,\n 40.564937785967224\n ],\n [\n -95.78601837158203,\n 40.564937785967224\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.73881149291991,\n 40.513277131087484\n ],\n [\n -95.73881149291991,\n 40.53050177574321\n ],\n [\n -95.70259094238281,\n 40.53050177574321\n ],\n [\n -95.70259094238281,\n 40.513277131087484\n ],\n [\n -95.73881149291991,\n 40.513277131087484\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Nebraska Water Science Center
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Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center conducted a seasonal collection of surficial sediments from Chincoteague Bay and Tom's Cove, between Assateague Island and the Delmarva Peninsula in late March/early April 2014 and October 2014. The sampling efforts were part of a larger U.S. Geological Survey study to assess the effects of storm events on sediment distribution in back-barrier environments of the United States. By sampling during the spring and fall, a more complete understanding of seasonal variability in the area can help determine baseline conditions. The objective of this study was to characterize the sediments of Chincoteague Bay in order to create baseline conditions to incorporate with the hydrodynamic and sediment transport models used to evaluate pre- and post-storm change and compare with future field measurements.
\nThis report is an archive for sedimentological data derived from the surface sediment of Chincoteague Bay. Data are available for the spring (March/April 2014) and fall (October 2014) samples collected. Downloadable data are provided as Excel spreadsheets and as JPEG files. Additional files include ArcGIS shapefiles of the sampling sites, detailed results of sediment grain-size analyses, and formal Federal Geographic Data Committee metadata (data downloads).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151219","usgsCitation":"Ellis, A.M., Marot, M.E., Wheaton, C.J., Bernier, J.C., and Smith, C.G., 2015, A seasonal comparison of surface sediment characteristics in Chincoteague Bay, Maryland and Virginia, USA: U.S. Geological Survey Open-File Report 2015-1219, https://dx.doi.org/10.3133/ofr20151219.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065701","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":315341,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1219","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1219"},{"id":316535,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chincoteague Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.19317626953125,\n 38.28778081436419\n ],\n [\n -75.50628662109375,\n 37.88677656291023\n ],\n [\n -75.3717041015625,\n 37.83364941345968\n ],\n [\n -75.17532348632812,\n 38.09241741843045\n ],\n [\n -75.09292602539062,\n 38.272688535980976\n ],\n [\n -75.19317626953125,\n 38.28778081436419\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
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Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, scientific research, national security, recreation, and many others. For the Commonwealth of Puerto Rico, elevation data are critical for flood risk management, landslide mitigation, natural resources conservation, sea level rise and subsidence, coastal zone management, infrastructure and construction management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, U.S. territorial, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States, Hawaii, and selected U.S. territories, and quality level 5 interferometric synthetic aperture radar (IfSAR) data for Alaska, all with a 6- to 10-year acquisition cycle, provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A‒16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other three-dimensional (3D) representations of the Nation’s natural and constructed features.
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U.S. Geological Survey
511 National Center
Reston, VA 20192
http://www.usgs.gov/ngpo/
http://nationalmap.gov/3DEP/
The ability to infect a host is a key trait of a virus, and differences in infectivity could put one virus at an evolutionary advantage over another. In this study we have quantified the infectivity of two strains of infectious hematopoietic necrosis virus (IHNV) that are known to differ in fitness and virulence. By exposing juvenile rainbow trout (Oncorhynchus mykiss) hosts to a wide range of virus doses, we were able to calculate the infectious dose in terms of ID50 values for the two genotypes. Lethal dose experiments were also conducted to confirm the virulence difference between the two virus genotypes, using a range of virus doses and holding fish either in isolation or in batch so as to calculate LD50values. We found that infectivity is positively correlated with virulence, with the more virulent genotype having higher infectivity. Additionally, infectivity increases more steeply over a short range of doses compared to virulence, which has a shallower increase. We also examined the data using models of virion interaction and found no evidence to suggest that virions have either an antagonistic or a synergistic effect on each other, supporting the independent action hypothesis in the process of IHNV infection of rainbow trout.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.virusres.2015.12.020","usgsCitation":"McKenney, D., Kurath, G., and Wargo, A., 2016, Characterization of infectious dose and lethal dose of two strains of infectious hematopoietic necrosis virus (IHNV): Virus Research, v. 214, p. 80-89, https://doi.org/10.1016/j.virusres.2015.12.020.","productDescription":"10 p.","startPage":"80","endPage":"89","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068876","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":471260,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://scholarworks.wm.edu/vimsarticles/810","text":"Publisher Index Page"},{"id":316512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"214","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56b324a9e4b0cc79997f04d3","contributors":{"authors":[{"text":"McKenney, Douglas dmckenney@usgs.gov","contributorId":156278,"corporation":false,"usgs":true,"family":"McKenney","given":"Douglas","email":"dmckenney@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":597135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":597136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wargo, Andrew","contributorId":73480,"corporation":false,"usgs":true,"family":"Wargo","given":"Andrew","affiliations":[],"preferred":false,"id":597137,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70164377,"text":"70164377 - 2016 - Timing of translocation influences birth rate and population dynamics in a forest carnivore","interactions":[],"lastModifiedDate":"2017-11-22T17:33:16","indexId":"70164377","displayToPublicDate":"2016-02-03T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Timing of translocation influences birth rate and population dynamics in a forest carnivore","docAbstract":"Timing can be critical for many life history events of organisms. Consequently, the timing of management activities may affect individuals and populations in numerous and unforeseen ways. Translocations of organisms are used to restore or expand populations but the timing of translocations is largely unexplored as a factor influencing population success. We hypothesized that the process of translocation negatively influences reproductive rates of individuals that are moved just before their birthing season and, therefore, the timing of releases could influence translocation success. Prior to reintroducing fishers (Pekania pennanti) into northern California and onto the Olympic Peninsula of Washington, we predicted that female fishers released in November and December (early) would have a higher probability of giving birth to kits the following March or April than females released in January, February, and March (late), just prior to or during the period of blastocyst implantation and gestation. Over four winters (2008–2011), we translocated 56 adult female fishers that could have given birth in the spring immediately after release. Denning rates, an index of birth rate, for females released early were 92% in California and 38% in Washington. In contrast, denning rates for females released late were 40% and 11%, in California and Washington, a net reduction in denning rate of 66% across both sites. To understand how releasing females nearer to parturition could influence population establishment and persistence, we used stochastic population simulations using three-stage Lefkovitch matrices. These simulations showed that translocating female fishers early had long-term positive influences on the mean population size and on quasi-extinction thresholds compared to populations where females were released late. The results from both empirical data and simulations show that the timing of translocation, with respect to life history events, should be considered during planning of translocations and implemented before the capture, movement, and release of organisms for translocation.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.1223","usgsCitation":"Facka, A., Lewis, J.C., Happe, P., Jenkins, K.J., Callas, R., and Powell, R.A., 2016, Timing of translocation influences birth rate and population dynamics in a forest carnivore: Ecosphere, v. 7, no. 1, e01223; 18 p., https://doi.org/10.1002/ecs2.1223.","productDescription":"e01223; 18 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068426","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":471259,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1223","text":"Publisher Index Page"},{"id":316513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-02","publicationStatus":"PW","scienceBaseUri":"56b324ade4b0cc79997f04ef","contributors":{"authors":[{"text":"Facka, Aaron N","contributorId":156275,"corporation":false,"usgs":false,"family":"Facka","given":"Aaron N","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":597120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewis, Jeffrey C.","contributorId":141090,"corporation":false,"usgs":false,"family":"Lewis","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":13674,"text":"WDFW","active":true,"usgs":false}],"preferred":false,"id":597121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Happe, Patricia","contributorId":83248,"corporation":false,"usgs":true,"family":"Happe","given":"Patricia","affiliations":[],"preferred":false,"id":597122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenkins, Kurt J. 0000-0003-1415-6607 kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":597119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Callas, Richard","contributorId":156276,"corporation":false,"usgs":false,"family":"Callas","given":"Richard","email":"","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":597123,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Powell, Roger A.","contributorId":9163,"corporation":false,"usgs":true,"family":"Powell","given":"Roger","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":597124,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70164450,"text":"70164450 - 2016 - Toward a national animal telemetry network for aquatic observations in the United States","interactions":[],"lastModifiedDate":"2016-02-05T15:49:36","indexId":"70164450","displayToPublicDate":"2016-02-03T01:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Toward a national animal telemetry network for aquatic observations in the United States","docAbstract":"Animal telemetry is the science of elucidating the movements and behavior of animals in relation to their environment or habitat. Here, we focus on telemetry of aquatic species (marine mammals, sharks, fish, sea birds and turtles) and so are concerned with animal movements and behavior as they move through and above the world’s oceans, coastal rivers, estuaries and great lakes. Animal telemetry devices (“tags”) yield detailed data regarding animal responses to the coupled ocean–atmosphere and physical environment through which they are moving. Animal telemetry has matured and we describe a developing US Animal Telemetry Network (ATN) observing system that monitors aquatic life on a range of temporal and spatial scales that will yield both short- and long-term benefits, fill oceanographic observing and knowledge gaps and advance many of the U.S. National Ocean Policy Priority Objectives. ATN has the potential to create a huge impact for the ocean observing activities undertaken by the U.S. Integrated Ocean Observing System (IOOS) and become a model for establishing additional national-level telemetry networks worldwide.
","language":"English","publisher":"BioMed Central","doi":"10.1186/s40317-015-0092-1","usgsCitation":"Block, B.A., Holbrook, C., Simmons, S.E., Holland, K.N., Ault, J.S., Costa, D.P., Mate, B., Seitz, A.C., Arendt, M.D., Payne, J., Mahmoudi, B., Moore, P.L., Price, J., Levenson, J.J., Wilson, D., and Kochevar, R.E., 2016, Toward a national animal telemetry network for aquatic observations in the United States: Animal Biotelemetry, v. 4, no. 6, 8 p., https://doi.org/10.1186/s40317-015-0092-1.","productDescription":"8 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069947","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471261,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-015-0092-1","text":"Publisher Index 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cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":597413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simmons, Samantha E.","contributorId":156320,"corporation":false,"usgs":false,"family":"Simmons","given":"Samantha","email":"","middleInitial":"E.","affiliations":[{"id":20313,"text":"Marine Mammal Commission","active":true,"usgs":false}],"preferred":false,"id":597417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holland, Kim N","contributorId":156321,"corporation":false,"usgs":false,"family":"Holland","given":"Kim","email":"","middleInitial":"N","affiliations":[{"id":20314,"text":"Hawaii Institute of Marine Biology, University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":597418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ault, Jerald S.","contributorId":59286,"corporation":false,"usgs":true,"family":"Ault","given":"Jerald","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":597419,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costa, Daniel P.","contributorId":141212,"corporation":false,"usgs":false,"family":"Costa","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":597421,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mate, Bruce R","contributorId":156323,"corporation":false,"usgs":false,"family":"Mate","given":"Bruce R","affiliations":[{"id":20316,"text":"Oregon State University Marine Mammal 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John","contributorId":146663,"corporation":false,"usgs":false,"family":"Payne","given":"John","email":"","affiliations":[],"preferred":false,"id":597427,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mahmoudi, Behzad","contributorId":156325,"corporation":false,"usgs":false,"family":"Mahmoudi","given":"Behzad","email":"","affiliations":[{"id":20317,"text":"Florida Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":597428,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moore, Peter L.","contributorId":54504,"corporation":false,"usgs":true,"family":"Moore","given":"Peter","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":597430,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Price, James","contributorId":156327,"corporation":false,"usgs":false,"family":"Price","given":"James","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":false,"id":597431,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Levenson, J. J.","contributorId":156326,"corporation":false,"usgs":false,"family":"Levenson","given":"J.","email":"","middleInitial":"J.","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":false,"id":597429,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wilson, Doug","contributorId":7581,"corporation":false,"usgs":true,"family":"Wilson","given":"Doug","email":"","affiliations":[],"preferred":false,"id":597432,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Kochevar, Randall E","contributorId":156328,"corporation":false,"usgs":false,"family":"Kochevar","given":"Randall","email":"","middleInitial":"E","affiliations":[{"id":16719,"text":"Hopkins Marine Station, Stanford University, Pacific Grove, CA 909350, USA","active":true,"usgs":false}],"preferred":false,"id":597433,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70161858,"text":"ofr20161002 - 2016 - Quality of surface-water supplies in the Triangle area of North Carolina, water years 2010-11","interactions":[],"lastModifiedDate":"2016-12-08T17:09:07","indexId":"ofr20161002","displayToPublicDate":"2016-02-02T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1002","title":"Quality of surface-water supplies in the Triangle area of North Carolina, water years 2010-11","docAbstract":"Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, during October 2009 through September 2010 (water year 2010) and October 2010 through September 2011 (water year 2011). Major findings for this data-collection effort include
\nDirector, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Okmok, a ~10-km wide caldera that occupies most of the northeastern end of Umnak Island, is one of the most active volcanoes in the Aleutian arc. The most recent eruption at Okmok during July-August 2008 was by far its largest and most explosive since at least the early 19th century. We investigate post-eruptive magma supply and storage at the volcano during 2008–2014 by analyzing all available synthetic aperture radar (SAR) images of Okmok acquired during that time period using the multi-temporal InSAR technique. Data from the C-band Envisat and X-band TerraSAR-X satellites indicate that Okmok started inflating very soon after the end of 2008 eruption at a time-variable rate of 48-130 mm/y, consistent with GPS measurements. The “model-assisted” phase unwrapping method is applied to improve the phase unwrapping operation for long temporal baseline pairs. The InSAR time-series is used as input for deformation source modeling, which suggests magma accumulating at variable rates in a shallow storage zone at ~3.9 km below sea level beneath the summit caldera, consistent with previous studies. The modeled volume accumulation in the 6 years following the 2008 eruption is ~75% of the 1997 eruption volume and ~25% of the 2008 eruption volume.
","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/rs71215839","usgsCitation":"Qu, F., Lu, Z., Poland, M.P., Freymueller, J.T., Zhang, Q., and Jung, H., 2016, Post-eruptive inflation of Okmok Volcano, Alaska, from InSAR, 2008–2014: Remote Sensing, v. 7, no. 12, p. 16778-16794, https://doi.org/10.3390/rs71215839.","productDescription":"17 p.","startPage":"16778","endPage":"16794","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069602","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471268,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs71215839","text":"Publisher Index Page"},{"id":316377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Okmok Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.46572875976562,\n 53.26685566290742\n ],\n [\n -168.46572875976562,\n 53.570491879287\n ],\n [\n -167.772216796875,\n 53.570491879287\n ],\n [\n -167.772216796875,\n 53.26685566290742\n ],\n [\n -168.46572875976562,\n 53.26685566290742\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-09","publicationStatus":"PW","scienceBaseUri":"56b081bde4b010e2af2a11ad","contributors":{"authors":[{"text":"Qu, Feifei","contributorId":156236,"corporation":false,"usgs":false,"family":"Qu","given":"Feifei","email":"","affiliations":[{"id":20301,"text":"SMU","active":true,"usgs":false}],"preferred":false,"id":596945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":596946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":596944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freymueller, Jeffrey T.","contributorId":97458,"corporation":false,"usgs":true,"family":"Freymueller","given":"Jeffrey","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":596947,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Qin","contributorId":156237,"corporation":false,"usgs":false,"family":"Zhang","given":"Qin","email":"","affiliations":[{"id":20301,"text":"SMU","active":true,"usgs":false}],"preferred":false,"id":596948,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jung, Hyung-Sup","contributorId":58382,"corporation":false,"usgs":true,"family":"Jung","given":"Hyung-Sup","email":"","affiliations":[],"preferred":false,"id":596949,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70164449,"text":"70164449 - 2016 - Reflectance spectroscopy (0.35–8 μm) of ammonium-bearing minerals and qualitative comparison to Ceres-like asteroids","interactions":[],"lastModifiedDate":"2016-02-05T09:15:58","indexId":"70164449","displayToPublicDate":"2016-02-01T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Reflectance spectroscopy (0.35–8 μm) of ammonium-bearing minerals and qualitative comparison to Ceres-like asteroids","docAbstract":"Ammonium-bearing minerals have been suggested to be present on Mars, Ceres, and various asteroids and comets. We undertook a systematic study of the spectral reflectance properties of ammonium-bearing minerals and compounds that have possible planetary relevance (i.e., ammonium carbonates, chlorides, nitrates, oxalates, phosphates, silicates, and sulfates). Various synthetic and natural NH4+-bearing minerals were analyzed using reflectance spectroscopy in the long-wave ultraviolet, visible, near-infrared, and mid-infrared regions (0.35–8 μm) in order to identify spectral features characteristic of the NH4+ molecule, and to evaluate if and how these features vary among different species. Mineral phases were confirmed through structural and compositional analyses using X-ray diffraction, X-ray fluorescence, and elemental combustion analysis. Characteristic absorption features associated with NH4 can be seen in the reflectance spectra at wavelengths as short as ∼1 μm. In the near-infrared region, the most prominent absorption bands are located near 1.6, 2.0, and 2.2 μm. Absorption features characteristic of NH4+ occurred at slightly longer wavelengths in the mineral-bound NH4+ spectra than for free NH4+ for most of the samples. Differences in wavelength position are attributable to various factors, including differences in the type and polarizability of the anion(s) attached to the NH4+, degree and type of hydrogen bonding, molecule symmetry, and cation substitutions. Multiple absorption features, usually three absorption bands, in the mid-infrared region between ∼2.8 and 3.8 μm were seen in all but the most NH4-poor sample spectra, and are attributed to fundamentals, combinations, and overtones of stretching and bending vibrations of the NH4+ molecule. These features appear even in reflectance spectra of water-rich samples which exhibit a strong 3 μm region water absorption feature. While many of the samples examined in this study have NH4 absorption bands at unique wavelength positions, in order to discriminate between different NH4+-bearing phases, absorption features corresponding to molecules other than NH4+ should be included in spectral analysis. A qualitative comparison of the laboratory results to telescopic spectra of Asteroids 1 Ceres, 10 Hygiea, and 324 Bamberga for the 3 μm region demonstrates that a number of NH4-bearing phases are consistent with the observational data in terms of exhibiting an absorption band in the 3.07 μm region.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.icarus.2015.10.028","usgsCitation":"Berg, B.L., Cloutis, E.A., Beck, P., Vernazza, P., Bishop, J., Takir, D., Reddy, V., Applin, D., and Mann, P., 2016, Reflectance spectroscopy (0.35–8 μm) of ammonium-bearing minerals and qualitative comparison to Ceres-like asteroids: Icarus, v. 265, p. 218-237, https://doi.org/10.1016/j.icarus.2015.10.028.","productDescription":"10 p.","startPage":"218","endPage":"237","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066433","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":316593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"265","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56b5d658e4b0cc799981738d","contributors":{"authors":[{"text":"Berg, Breanne L.","contributorId":156312,"corporation":false,"usgs":false,"family":"Berg","given":"Breanne","email":"","middleInitial":"L.","affiliations":[{"id":20308,"text":"Department of Geography, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9","active":true,"usgs":false}],"preferred":false,"id":597404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cloutis, Edward A.","contributorId":156313,"corporation":false,"usgs":false,"family":"Cloutis","given":"Edward","email":"","middleInitial":"A.","affiliations":[{"id":20308,"text":"Department of Geography, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9","active":true,"usgs":false}],"preferred":false,"id":597405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beck, P.","contributorId":43700,"corporation":false,"usgs":true,"family":"Beck","given":"P.","affiliations":[],"preferred":false,"id":597406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vernazza, P.","contributorId":156314,"corporation":false,"usgs":false,"family":"Vernazza","given":"P.","email":"","affiliations":[{"id":20309,"text":"Aix Marseille Université, CNRS, LAM (Laboratoire d’Astrophysique de Marseille) UMR 7326, 13388 Marseille, France","active":true,"usgs":false}],"preferred":false,"id":597407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bishop, Janice L","contributorId":156315,"corporation":false,"usgs":false,"family":"Bishop","given":"Janice L","affiliations":[{"id":20310,"text":"SETI Institute, 89 Bernardo Ave, Suite 100, Mountain View, CA, USA 94043","active":true,"usgs":false}],"preferred":false,"id":597408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Takir, Driss dtakir@usgs.gov","contributorId":152190,"corporation":false,"usgs":true,"family":"Takir","given":"Driss","email":"dtakir@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":597403,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reddy, V.","contributorId":156316,"corporation":false,"usgs":false,"family":"Reddy","given":"V.","email":"","affiliations":[{"id":20311,"text":"Planetary Science Institute, 1700 East Fort Lowell, Suite 106, Tucson, AZ, USA 85719-2395","active":true,"usgs":false}],"preferred":false,"id":597409,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Applin, D.","contributorId":156317,"corporation":false,"usgs":false,"family":"Applin","given":"D.","email":"","affiliations":[{"id":20308,"text":"Department of Geography, University of Winnipeg, Winnipeg, MB, Canada R3B 2E9","active":true,"usgs":false}],"preferred":false,"id":597410,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mann, Paul","contributorId":57729,"corporation":false,"usgs":true,"family":"Mann","given":"Paul","email":"","affiliations":[],"preferred":false,"id":597411,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70159446,"text":"70159446 - 2016 - Book review: Mineral resource estimation","interactions":[],"lastModifiedDate":"2016-06-30T14:12:14","indexId":"70159446","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Book review: Mineral resource estimation","docAbstract":"Mineral Resource Estimation is about estimating mineral resources at the scale of an ore deposit and is not to be mistaken with mineral resource assessment, which is undertaken at a significantly broader scale, even if similar data and geospatial/geostatistical methods are used. The book describes geological, statistical, and geostatistical tools and methodologies used in resource estimation and modeling, and presents case studies for illustration. The target audience is the expert, which includes professional mining geologists and engineers, as well as graduate-level and advanced undergraduate students.
\nReview info: Mineral Resource Estimation. By Mario E. Rossi, Clayton V. Deutsch. 2014. ISBN 978-1-4020-5716-8 332 pp.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.1.272","usgsCitation":"Mihalasky, M.J., 2016, Book review: Mineral resource estimation: Economic Geology, v. 111, no. 1, p. 272-274, https://doi.org/10.2113/econgeo.111.1.272.","productDescription":"3 [.","startPage":"272","endPage":"274","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070293","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":324690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-08","publicationStatus":"PW","scienceBaseUri":"577642ade4b07dd077c873ef","contributors":{"authors":[{"text":"Mihalasky, Mark J. 0000-0002-0082-3029 mjm@usgs.gov","orcid":"https://orcid.org/0000-0002-0082-3029","contributorId":3692,"corporation":false,"usgs":true,"family":"Mihalasky","given":"Mark","email":"mjm@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":578734,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70156877,"text":"70156877 - 2016 - Mapping extent and change in surface mines within the United States for 2001 to 2006","interactions":[],"lastModifiedDate":"2017-04-06T17:07:18","indexId":"70156877","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2597,"text":"Land Degradation and Development","active":true,"publicationSubtype":{"id":10}},"title":"Mapping extent and change in surface mines within the United States for 2001 to 2006","docAbstract":"A complete, spatially explicit dataset illustrating the 21st century mining footprint for the conterminous United States does not exist. To address this need, we developed a semi-automated procedure to map the country's mining footprint (30-m pixel) and establish a baseline to monitor changes in mine extent over time. The process uses mine seed points derived from the U.S. Energy Information Administration (EIA), U.S. Geological Survey (USGS) Mineral Resources Data System (MRDS), and USGS National Land Cover Dataset (NLCD) and recodes patches of barren land that meet a “distance to seed” requirement and a patch area requirement before mapping a pixel as mining. Seed points derived from EIA coal points, an edited MRDS point file, and 1992 NLCD mine points were used in three separate efforts using different distance and patch area parameters for each. The three products were then merged to create a 2001 map of moderate-to-large mines in the United States, which was subsequently manually edited to reduce omission and commission errors. This process was replicated using NLCD 2006 barren pixels as a base layer to create a 2006 mine map and a 2001–2006 mine change map focusing on areas with surface mine expansion. In 2001, 8,324 km2 of surface mines were mapped. The footprint increased to 9,181 km2 in 2006, representing a 10·3% increase over 5 years. These methods exhibit merit as a timely approach to generate wall-to-wall, spatially explicit maps representing the recent extent of a wide range of surface mining activities across the country.
","language":"English","publisher":"John Wiley and Sons","doi":"10.1002/ldr.2412","usgsCitation":"Soulard, C.E., Acevedo, W., Stehman, S.V., and Parker, O.P., 2016, Mapping extent and change in surface mines within the United States for 2001 to 2006: Land Degradation and Development, v. 27, no. 2, p. 248-257, https://doi.org/10.1002/ldr.2412.","productDescription":"10 p.","startPage":"248","endPage":"257","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054963","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":324655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-14","publicationStatus":"PW","scienceBaseUri":"5774f27ce4b07dd077c6a55d","contributors":{"authors":[{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":570924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acevedo, William wacevedo@usgs.gov","contributorId":2689,"corporation":false,"usgs":true,"family":"Acevedo","given":"William","email":"wacevedo@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":570925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stehman, Stephen V.","contributorId":77283,"corporation":false,"usgs":true,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":641373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Owen P.","contributorId":147263,"corporation":false,"usgs":false,"family":"Parker","given":"Owen","email":"","middleInitial":"P.","affiliations":[{"id":6785,"text":"USGS Contractor, Minerals & Environmental Resources Sci Ctr","active":true,"usgs":false}],"preferred":false,"id":570926,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178028,"text":"70178028 - 2016 - Density, distribution, and genetic structure of grizzly bears in the Cabinet-Yaak Ecosystem","interactions":[],"lastModifiedDate":"2021-08-31T15:34:06.340966","indexId":"70178028","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Density, distribution, and genetic structure of grizzly bears in the Cabinet-Yaak Ecosystem","docAbstract":"The conservation status of the 2 threatened grizzly bear (Ursus arctos) populations in the Cabinet-Yaak Ecosystem (CYE) of northern Montana and Idaho had remained unchanged since designation in 1975; however, the current demographic status of these populations was uncertain. No rigorous data on population density and distribution or analysis of recent population genetic structure were available to measure the effectiveness of conservation efforts. We used genetic detection data from hair corral, bear rub, and opportunistic sampling in traditional and spatial capture–recapture models to generate estimates of abundance and density of grizzly bears in the CYE. We calculated mean bear residency on our sampling grid from telemetry data using Huggins and Pledger models to estimate the average number of bears present and to correct our superpopulation estimates for lack of geographic closure. Estimated grizzly bear abundance (all sex and age classes) in the CYE in 2012 was 48–50 bears, approximately half the population recovery goal. Grizzly bear density in the CYE (4.3–4.5 grizzly bears/1,000 km2) was among the lowest of interior North American populations. The sizes of the Cabinet (n = 22–24) and Yaak (n = 18–22) populations were similar. Spatial models produced similar estimates of abundance and density with comparable precision without requiring radio-telemetry data to address assumptions of geographic closure. The 2 populations in the CYE were demographically and reproductively isolated from each other and the Cabinet population was highly inbred. With parentage analysis, we documented natural migrants to the Cabinet and Yaak populations by bears born to parents in the Selkirk and Northern Continental Divide populations. These events supported data from other sources suggesting that the expansion of neighboring populations may eventually help sustain the CYE populations. However, the small size, isolation, and inbreeding documented by this study demonstrate the need for comprehensive management designed to support CYE population growth and increased connectivity and gene flow with other populations.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.1019","usgsCitation":"Kendall, K.C., Macleod, A., Boyd, K.L., Boulanger, J., Royle, J., Kasworm, W.F., Paetkau, D., Proctor, M.F., Graves, T.A., and Annis, K., 2016, Density, distribution, and genetic structure of grizzly bears in the Cabinet-Yaak Ecosystem: Journal of Wildlife Management, v. 80, no. 2, p. 314-331, https://doi.org/10.1002/jwmg.1019.","productDescription":"18 p.","startPage":"314","endPage":"331","ipdsId":"IP-058746","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":330592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.5045166015625,\n 47.53203824675999\n ],\n [\n -116.5045166015625,\n 49.001843917978526\n ],\n [\n -115.02685546875,\n 49.001843917978526\n ],\n [\n -115.02685546875,\n 47.53203824675999\n ],\n [\n -116.5045166015625,\n 47.53203824675999\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"2","noUsgsAuthors":false,"publicationDate":"2015-11-15","publicationStatus":"PW","scienceBaseUri":"5819a9c4e4b0bb36a4c9102d","chorus":{"doi":"10.1002/jwmg.1019","url":"http://dx.doi.org/10.1002/jwmg.1019","publisher":"Wiley-Blackwell","authors":"Kendall Katherine C., Macleod Amy C., Boyd Kristina L., Boulanger John, Royle J. Andrew, Kasworm Wayne F., Paetkau David, Proctor Michael F., Annis Kim, Graves Tabitha A.","journalName":"The Journal of Wildlife Management","publicationDate":"11/15/2015"},"contributors":{"authors":[{"text":"Kendall, Katherine C. 0000-0002-4831-2287 kkendall@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-2287","contributorId":3081,"corporation":false,"usgs":true,"family":"Kendall","given":"Katherine","email":"kkendall@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":822258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Macleod, Amy C.","contributorId":65739,"corporation":false,"usgs":true,"family":"Macleod","given":"Amy C.","affiliations":[],"preferred":false,"id":652549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyd, Kristina L.","contributorId":150937,"corporation":false,"usgs":false,"family":"Boyd","given":"Kristina","email":"","middleInitial":"L.","affiliations":[{"id":18146,"text":"Yaak Valley Forest Council","active":true,"usgs":false}],"preferred":false,"id":652550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boulanger, John","contributorId":176494,"corporation":false,"usgs":false,"family":"Boulanger","given":"John","email":"","affiliations":[],"preferred":false,"id":652551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":652552,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kasworm, Wayne F.","contributorId":150938,"corporation":false,"usgs":false,"family":"Kasworm","given":"Wayne","email":"","middleInitial":"F.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":652553,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paetkau, David","contributorId":97712,"corporation":false,"usgs":false,"family":"Paetkau","given":"David","email":"","affiliations":[],"preferred":false,"id":652554,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Proctor, Michael F.","contributorId":150939,"corporation":false,"usgs":false,"family":"Proctor","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":18147,"text":"Birchdale Ecological","active":true,"usgs":false}],"preferred":false,"id":652555,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Graves, Tabitha A. 0000-0001-5145-2400 tgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":5898,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha","email":"tgraves@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":652557,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Annis, Kim","contributorId":150940,"corporation":false,"usgs":false,"family":"Annis","given":"Kim","email":"","affiliations":[{"id":18148,"text":"MT Fish, Wildlife, and Parks","active":true,"usgs":false}],"preferred":false,"id":652556,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70192535,"text":"70192535 - 2016 - Ungulate reproductive parameters track satellite observations of plant phenology across latitude and climatological regimes","interactions":[],"lastModifiedDate":"2017-10-26T13:15:55","indexId":"70192535","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Ungulate reproductive parameters track satellite observations of plant phenology across latitude and climatological regimes","docAbstract":"The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus) across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km) in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004–2011). Regionally, both the start and peak of growing season (“Start” and “Peak”, respectively) are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual production, across latitude and changing climatological regimes. Practically, this demonstrates the potential for broad-scale modeling of couplings between climate, plant phenology, and animal populations using space-borne observations.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0148780","usgsCitation":"Stoner, D., Sexton, J.O., Nagol, J., Bernales, H.H., and Edwards, T., 2016, Ungulate reproductive parameters track satellite observations of plant phenology across latitude and climatological regimes: PLoS ONE, v. 11, no. 2, p. 1-19, https://doi.org/10.1371/journal.pone.0148780.","productDescription":"e0148780; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-061623","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471281,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0148780","text":"Publisher Index Page"},{"id":347470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, Utah","otherGeospatial":"Chihuahuan Desert, Colorado Plateau, Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.06005859375,\n 33.63291573870479\n ],\n [\n -108.61083984375,\n 33.63291573870479\n ],\n [\n -108.61083984375,\n 42.65012181368022\n ],\n [\n -114.06005859375,\n 42.65012181368022\n ],\n [\n -114.06005859375,\n 33.63291573870479\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-05","publicationStatus":"PW","scienceBaseUri":"5a07ea6ce4b09af898c8cc86","contributors":{"authors":[{"text":"Stoner, David","contributorId":191912,"corporation":false,"usgs":false,"family":"Stoner","given":"David","affiliations":[],"preferred":false,"id":716338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sexton, Joseph O.","contributorId":191918,"corporation":false,"usgs":false,"family":"Sexton","given":"Joseph","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":716339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagol, Jyoteshwar","contributorId":198512,"corporation":false,"usgs":false,"family":"Nagol","given":"Jyoteshwar","affiliations":[],"preferred":false,"id":716340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernales, Heather H.","contributorId":198513,"corporation":false,"usgs":false,"family":"Bernales","given":"Heather","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":716341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":191916,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas C.","suffix":"Jr.","email":"tce@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716135,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188368,"text":"70188368 - 2016 - Lithospheric rheology constrained from twenty-five years of postseismic deformation following the 1989 Mw 6.9 Loma Prieta earthquake","interactions":[],"lastModifiedDate":"2017-06-07T11:21:27","indexId":"70188368","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Lithospheric rheology constrained from twenty-five years of postseismic deformation following the 1989 Mw 6.9 Loma Prieta earthquake","title":"Lithospheric rheology constrained from twenty-five years of postseismic deformation following the 1989 Mw 6.9 Loma Prieta earthquake","docAbstract":"The October 17, 1989 Mw 6.9 Loma Prieta earthquake provides the first opportunity of probing the crustal and upper mantle rheology in the San Francisco Bay Area since the 1906 Mw 7.9 San Francisco earthquake. Here we use geodetic observations including GPS and InSAR to characterize the Loma Prieta earthquake postseismic displacements from 1989 to 2013. Pre-earthquake deformation rates are constrained by nearly 20 yr of USGS trilateration measurements and removed from the postseismic measurements prior to the analysis. We observe GPS horizontal displacements at mean rates of 1–4 mm/yr toward Loma Prieta Mountain until 2000, and ∼2 mm/yr surface subsidence of the northern Santa Cruz Mountains between 1992 and 2002 shown by InSAR, which is not associated with the seasonal and longer-term hydrological deformation in the adjoining Santa Clara Valley. Previous work indicates afterslip dominated in the early (1989–1994) postseismic period, so we focus on modeling the postseismic viscoelastic relaxation constrained by the geodetic observations after 1994. The best fitting model shows an elastic 19-km-thick upper crust above an 11-km-thick viscoelastic lower crust with viscosity of ∼6 × 1018 Pas, underlain by a viscous upper mantle with viscosity between 3 × 1018 and 2 × 1019 Pas. The millimeter-scale postseismic deformation does not resolve the viscosity in the different layers very well, and the lower-crustal relaxation may be localized in a narrow shear zone. However, the inferred lithospheric rheology is consistent with previous estimates based on post-1906 San Francisco earthquake measurements along the San Andreas fault system. The viscoelastic relaxation may also contribute to the enduring increase of aseismic slip and repeating earthquake activity on the San Andreas fault near San Juan Bautista, which continued for at least a decade after the Loma Prieta event.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2015.12.018","usgsCitation":"Huang, M., Burgmann, R., and Pollitz, F., 2016, Lithospheric rheology constrained from twenty-five years of postseismic deformation following the 1989 Mw 6.9 Loma Prieta earthquake: Earth and Planetary Science Letters, v. 435, p. 147-158, https://doi.org/10.1016/j.epsl.2015.12.018.","productDescription":"12 p.","startPage":"147","endPage":"158","ipdsId":"IP-068757","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471290,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2015.12.018","text":"Publisher Index Page"},{"id":342215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United states","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.35,\n 37.6\n ],\n [\n -121.25,\n 37.6\n ],\n [\n -121.25,\n 36.8\n ],\n [\n -122.35,\n 36.8\n ],\n [\n -122.35,\n 37.6\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"435","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593910ade4b0764e6c5e8863","contributors":{"authors":[{"text":"Huang, Mong-Han","contributorId":192699,"corporation":false,"usgs":false,"family":"Huang","given":"Mong-Han","email":"","affiliations":[],"preferred":false,"id":697433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgmann, Roland","contributorId":192700,"corporation":false,"usgs":false,"family":"Burgmann","given":"Roland","affiliations":[],"preferred":false,"id":697420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697418,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193142,"text":"70193142 - 2016 - A decision support tool for adaptive management of native prairie ecosystems","interactions":[],"lastModifiedDate":"2017-11-21T13:38:30","indexId":"70193142","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2013,"text":"Interfaces","active":true,"publicationSubtype":{"id":10}},"title":"A decision support tool for adaptive management of native prairie ecosystems","docAbstract":"The Native Prairie Adaptive Management initiative is a decision support framework that provides cooperators with management-action recommendations to help them conserve native species and suppress invasive species on prairie lands. We developed a Web-based decision support tool (DST) for the U.S. Fish and Wildlife Service and the U.S. Geological Survey initiative. The DST facilitates cross-organizational data sharing, performs analyses to improve conservation delivery, and requires no technical expertise to operate. Each year since 2012, the DST has used monitoring data to update ecological knowledge that it translates into situation-specific management-action recommendations (e.g., controlled burn or prescribed graze). The DST provides annual recommendations for more than 10,000 acres on 20 refuge complexes in four U.S. states. We describe how the DST promotes the long-term implementation of the program for which it was designed and may facilitate decision support and improve ecological outcomes of other conservation efforts.
","language":"English","publisher":"Informs","doi":"10.1287/inte.2015.0822","usgsCitation":"Hunt, V.M., Jacobi, S., Gannon, J., Zorn, J.E., Moore, C.T., and Lonsdorf, E.V., 2016, A decision support tool for adaptive management of native prairie ecosystems: Interfaces, v. 46, no. 4, p. 334-344, https://doi.org/10.1287/inte.2015.0822.","productDescription":"11 p.","startPage":"334","endPage":"344","ipdsId":"IP-053560","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fd7ae4b06e28e9c24ef8","contributors":{"authors":[{"text":"Hunt, Victoria M.","contributorId":200688,"corporation":false,"usgs":false,"family":"Hunt","given":"Victoria","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobi, Sarah","contributorId":149496,"corporation":false,"usgs":false,"family":"Jacobi","given":"Sarah","email":"","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":723060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gannon, Jill J.","contributorId":12722,"corporation":false,"usgs":true,"family":"Gannon","given":"Jill J.","affiliations":[],"preferred":false,"id":723061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zorn, Jennifer E.","contributorId":200689,"corporation":false,"usgs":false,"family":"Zorn","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":723062,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718090,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lonsdorf, Eric V.","contributorId":149495,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":723063,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174965,"text":"70174965 - 2016 - Prospecting for marine gas hydrate resources","interactions":[],"lastModifiedDate":"2016-07-25T13:07:03","indexId":"70174965","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3906,"text":"Interpretation","active":true,"publicationSubtype":{"id":10}},"title":"Prospecting for marine gas hydrate resources","docAbstract":"As gas hydrate energy assessment matures worldwide, emphasis has evolved away from confirmation of the mere presence of gas hydrate to the more complex issue of prospecting for those specific accumulations that are viable resource targets. Gas hydrate exploration now integrates the unique pressure and temperature preconditions for gas hydrate occurrence with those concepts and practices that are the basis for conventional oil and gas exploration. We have aimed to assimilate the lessons learned to date in global gas hydrate exploration to outline a generalized prospecting approach as follows: (1) use existing well and geophysical data to delineate the gas hydrate stability zone (GHSZ), (2) identify and evaluate potential direct indications of hydrate occurrence through evaluation of interval of elevated acoustic velocity and/or seismic events of prospective amplitude and polarity, (3) mitigate geologic risk via regional seismic and stratigraphic facies analysis as well as seismic mapping of amplitude distribution along prospective horizons, and (4) mitigate further prospect risk through assessment of the evidence of gas presence and migration into the GHSZ. Although a wide range of occurrence types might ultimately become viable energy supply options, this approach, which has been tested in only a small number of locations worldwide, has directed prospect evaluation toward those sand-hosted, high-saturation occurrences that were presently considered to have the greatest future commercial potential.
","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/INT-2015-0036.1","usgsCitation":"Boswell, R., Shipp, C., Reichel, T., Shelander, D., Saeki, T., Frye, M., Shedd, W., Collett, T.S., and McConnell, D.R., 2016, Prospecting for marine gas hydrate resources: Interpretation, v. 4, no. 1, p. SA13-SA24, https://doi.org/10.1190/INT-2015-0036.1.","productDescription":"12 p.","startPage":"SA13","endPage":"SA24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063515","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":325593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57973831e4b021cadec8ff4a","contributors":{"authors":[{"text":"Boswell, Ray","contributorId":12307,"corporation":false,"usgs":true,"family":"Boswell","given":"Ray","affiliations":[],"preferred":false,"id":643418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shipp, Craig","contributorId":40522,"corporation":false,"usgs":true,"family":"Shipp","given":"Craig","email":"","affiliations":[],"preferred":false,"id":643419,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reichel, Thomas","contributorId":173141,"corporation":false,"usgs":false,"family":"Reichel","given":"Thomas","email":"","affiliations":[{"id":27158,"text":"Statoil ASA, Inc.","active":true,"usgs":false}],"preferred":false,"id":643420,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shelander, Dianna","contributorId":40463,"corporation":false,"usgs":true,"family":"Shelander","given":"Dianna","email":"","affiliations":[],"preferred":false,"id":643478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saeki, Tetsuo","contributorId":173142,"corporation":false,"usgs":false,"family":"Saeki","given":"Tetsuo","email":"","affiliations":[{"id":27159,"text":"JOGMEC, Inc.","active":true,"usgs":false}],"preferred":false,"id":643421,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frye, Matthew","contributorId":48428,"corporation":false,"usgs":true,"family":"Frye","given":"Matthew","affiliations":[],"preferred":false,"id":643422,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shedd, William","contributorId":13851,"corporation":false,"usgs":true,"family":"Shedd","given":"William","affiliations":[],"preferred":false,"id":643423,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":643417,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McConnell, Daniel R.","contributorId":47628,"corporation":false,"usgs":true,"family":"McConnell","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":643424,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70177901,"text":"70177901 - 2016 - An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach","interactions":[],"lastModifiedDate":"2018-03-09T09:30:18","indexId":"70177901","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach","docAbstract":"We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for the cultivated cropland class in NLCD 2006. The majority of the commission and omission errors in NLCD 2006 are in areas where cultivated cropland is not the most dominant land cover type. The errors are primarily attributed to the less accurate training dataset derived from the National Agricultural Statistics Service Cropland Data Layer dataset. In contrast, error rates are low in areas where cultivated cropland is the dominant land cover. Agreement between model-identified commission errors and independently interpreted reference data was high (79%). Agreement was low (40%) for omission error comparison. The majority of the commission errors in the NLCD 2006 cultivated crops were confused with low-intensity developed classes, while the majority of omission errors were from herbaceous and shrub classes. Some errors were caused by inaccurate land cover change from misclassification in NLCD 2001 and the subsequent land cover post-classification process.
","language":"English","publisher":"MDPI","doi":"10.3390/rs8020101","usgsCitation":"Danielson, P., Yang, L., Jin, S., Homer, C.G., and Napton, D., 2016, An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach: Remote Sensing, v. 8, no. 2, Article 101; 16 p., https://doi.org/10.3390/rs8020101.","productDescription":"Article 101; 16 p.","ipdsId":"IP-072277","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471276,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8020101","text":"Publisher Index Page"},{"id":330407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-28","publicationStatus":"PW","scienceBaseUri":"5811c0f3e4b0f497e79a5a81","contributors":{"authors":[{"text":"Danielson, Patrick 0000-0002-2990-2783 pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","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":652089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Napton, Darrell","contributorId":176288,"corporation":false,"usgs":false,"family":"Napton","given":"Darrell","affiliations":[],"preferred":false,"id":652091,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70182721,"text":"70182721 - 2016 - Comparison of measurement- and proxy-based Vs30 values in California","interactions":[],"lastModifiedDate":"2017-02-27T14:42:27","indexId":"70182721","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of measurement- and proxy-based Vs30 values in California","docAbstract":"This study was prompted by the recent availability of a significant amount of openly accessible measured VS30 values and the desire to investigate the trend of using proxy-based models to predict VS30 in the absence of measurements. Comparisons between measured and model-based values were performed. The measured data included 503 VS30 values collected from various projects for 482 seismographic station sites in California. Six proxy-based models—employing geologic mapping, topographic slope, and terrain classification—were also considered. Included was a new terrain class model based on the Yong et al. (2012) approach but recalibrated with updated measured VS30 values. Using the measured VS30 data as the metric for performance, the predictive capabilities of the six models were determined to be statistically indistinguishable. This study also found three models that tend to underpredict VS30 at lower velocities (NEHRP Site Classes D–E) and overpredict at higher velocities (Site Classes B–C).
","language":"English","publisher":"Earthquake Engineering Research Institute ","doi":"10.1193/013114EQS025M","usgsCitation":"Yong, A.K., 2016, Comparison of measurement- and proxy-based Vs30 values in California: Earthquake Spectra, v. 32, no. 1, p. 171-192, https://doi.org/10.1193/013114EQS025M.","productDescription":"22 p. ","startPage":"171","endPage":"192","ipdsId":"IP-056058","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":336289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-01","publicationStatus":"PW","scienceBaseUri":"58b548c1e4b01ccd54fddfba","contributors":{"authors":[{"text":"Yong, Alan K. 0000-0003-1807-5847 yong@usgs.gov","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":1554,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","email":"yong@usgs.gov","middleInitial":"K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":673454,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70168700,"text":"70168700 - 2016 - Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data","interactions":[],"lastModifiedDate":"2018-03-26T13:37:12","indexId":"70168700","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data","docAbstract":"Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.
A new 3D seismic reflection data volume acquired in 2012 has allowed for the detailed mapping and characterization of gas hydrate distribution in the Pearl River Mouth Basin in the South China Sea. Previous studies of core and logging data showed that gas hydrate occurrence at high concentrations is controlled by the presence of relatively coarse-grained sediment and the upward migration of thermogenic gas from the deeper sediment section into the overlying gas hydrate stability zone (BGHSZ); however, the spatial distribution of the gas hydrate remains poorly defined. We used a constrained sparse spike inversion technique to generate acoustic-impedance images of the hydrate-bearing sedimentary section from the newly acquired 3D seismic data volume. High-amplitude reflections just above the bottom-simulating reflectors (BSRs) were interpreted to be associated with the accumulation of gas hydrate with elevated saturations. Enhanced seismic reflections below the BSRs were interpreted to indicate the presence of free gas. The base of the BGHSZ was established using the occurrence of BSRs. In areas absent of well-developed BSRs, the BGHSZ was calculated from a model using the inverted P-wave velocity and subsurface temperature data. Seismic attributes were also extracted along the BGHSZ that indicate variations reservoir properties and inferred hydrocarbon accumulations at each site. Gas hydrate saturations estimated from the inversion of acoustic impedance of conventional 3D seismic data, along with well-log-derived rock-physics models were also used to estimate gas hydrate saturations. Our analysis determined that the gas hydrate petroleum system varies significantly across the Pearl River Mouth Basin and that variability in sedimentary properties as a product of depositional processes and the upward migration of gas from deeper thermogenic sources control the distribution of gas hydrates in this basin.
","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/INT-2015-0020.1","usgsCitation":"Wang, X., Qiang, J., Collett, T.S., Shi, H., Yang, S., Yan, C., Li, Y., Wang, Z., and Chen, D., 2016, Characterization of gas hydrate distribution using conventional 3D seismic data in the Pearl River Mouth Basin, South China Sea: Interpretation, v. 4, no. 1, p. 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Since the golden-cheeked warbler Setophaga chrysoparia was first listed as endangered, much effort has taken place to monitor warbler abundance, occupancy, reproduction and survival. Yet, despite being directly related to local population dynamics, movement rates have not been estimated for the species. We used an integrated population model to investigate the relationship between immigration rate, fledging rate, survival probabilities and population growth rate for warblers in central Texas, USA. Furthermore, using a deterministic projection model, we examined the response required by vital rates to maintain a viable population across varying levels of immigration. Warbler abundance fluctuated with an overall positive trend across years. In the absence of immigration, the abundance would have decreased. However, the population could remain viable without immigration if both adult and juvenile survival increased by almost half or if juvenile survival more than doubled. We also investigated the response required by fledging rates across a range of immigration in order to maintain a viable population. Overall, we found that immigration was required to maintain warbler target populations, indicating that warbler conservation and management programs need to be implemented at larger spatial scales than current efforts to be effective. This study also demonstrates that by using limited data within integrated population models, biologists are able to monitor multiple key demographic parameters simultaneously to gauge the efficacy of strategies designed to maximize warbler viability in a changing landscape.
","language":"English","publisher":"Wiley","doi":"10.1111/acv.12217","usgsCitation":"Duarte, A., Weckerly, F., Schaub, M., and Hatfield, J., 2016, Estimating golden-cheeked warbler immigration: Implications for the spatial scale of conservation: Animal Conservation, v. 19, no. 1, p. 65-74, https://doi.org/10.1111/acv.12217.","productDescription":"10 p.","startPage":"65","endPage":"74","ipdsId":"IP-064743","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":329754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2015-06-17","publicationStatus":"PW","scienceBaseUri":"58088688e4b0f497e78e24d1","contributors":{"authors":[{"text":"Duarte, A.","contributorId":46405,"corporation":false,"usgs":true,"family":"Duarte","given":"A.","email":"","affiliations":[],"preferred":false,"id":651413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weckerly, F.W.","contributorId":77877,"corporation":false,"usgs":true,"family":"Weckerly","given":"F.W.","email":"","affiliations":[],"preferred":false,"id":651414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaub, M.","contributorId":70897,"corporation":false,"usgs":true,"family":"Schaub","given":"M.","email":"","affiliations":[],"preferred":false,"id":651415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatfield, Jeffrey S. jhatfield@usgs.gov","contributorId":151,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeffrey S.","email":"jhatfield@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":651416,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}