Global climate and environmental change studies require detailed land-use and land-cover(LULC) information about the past, present, and future. In this paper, we discuss a methodology for downscaling coarse-resolution (i.e., half-degree) future land use scenarios to finer (i.e., 1 km) resolutions at the global scale using a grid-based spatially explicit cellular automata (CA) model. We account for spatial heterogeneity from topography, climate, soils, and socioeconomic variables. The model uses a global 30 m land cover map (2010) as the base input, a variety of biogeographic and socioeconomic variables, and an empirical analysis to downscale coarse-resolution land use information (specifically urban, crop and pasture). The output of this model offers the most current and finest-scale future LULC dynamics from 2010 to 2100 (with four representative concentration pathway (RCP) scenarios—RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) at a 1 km resolution within a globally consistent framework. The data are freely available for download, and will enable researchers to study the impacts of LULC change at the local scale.
The lampricides 3-trifluoromethyl-4-nitrophenol (TFM) and 2′,5-dichloro-4′-nitrosalicylanilide (niclosamide) are directly added to many tributaries of the Great Lakes that harbor the invasive parasitic sea lamprey. Despite their long history of use, the fate of lampricides is not well understood. This study evaluates the rate and pathway of direct photodegradation of both lampricides under simulated sunlight. The estimated half-lives of TFM range from 16.6 ± 0.2 h (pH 9) to 32.9 ± 1.0 h (pH 6), while the half-lives of niclosamide range from 8.88 ± 0.52 days (pH 6) to 382 ± 83 days (pH 9) assuming continuous irradiation over a water depth of 55 cm. Both compounds degrade to form a series of aromatic intermediates, simple organic acids, ring cleavage products, and inorganic ions. Experimental data were used to construct a kinetic model which demonstrates that the aromatic products of TFM undergo rapid photolysis and emphasizes that niclosamide degradation is the rate-limiting step to dehalogenation and mineralization of the lampricide. This study demonstrates that TFM photodegradation is likely to occur on the time scale of lampricide applications (2–5 days), while niclosamide, the less selective lampricide, will undergo minimal direct photodegradation during its passage to the Great Lakes.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b02607","usgsCitation":"McConville, M.B., Hubert, T.D., and Remucal, C.K., 2016, Direct photolysis rates and transformation pathways of the lampricides TFM and niclosamide in simulated sunlight: Environmental Science & Technology, v. 50, no. 18, p. 9998-10006, https://doi.org/10.1021/acs.est.6b02607.","productDescription":"9 p.","startPage":"9998","endPage":"10006","ipdsId":"IP-076266","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":331398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"18","noUsgsAuthors":false,"publicationDate":"2016-08-26","publicationStatus":"PW","scienceBaseUri":"584144dee4b04fc80e507398","contributors":{"authors":[{"text":"McConville, Megan B.","contributorId":177099,"corporation":false,"usgs":false,"family":"McConville","given":"Megan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":654640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubert, Terrance D. 0000-0001-9712-1738 thubert@usgs.gov","orcid":"https://orcid.org/0000-0001-9712-1738","contributorId":3036,"corporation":false,"usgs":true,"family":"Hubert","given":"Terrance","email":"thubert@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":654641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Remucal, Christina K.","contributorId":177100,"corporation":false,"usgs":false,"family":"Remucal","given":"Christina","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":654642,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179804,"text":"70179804 - 2016 - Regional meteorological drivers and long term trends of winter-spring nitrate dynamics across watersheds in northeastern North America","interactions":[],"lastModifiedDate":"2017-01-19T10:24:25","indexId":"70179804","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Regional meteorological drivers and long term trends of winter-spring nitrate dynamics across watersheds in northeastern North America","docAbstract":"This study evaluated the contribution of winter rain-on-snow (ROS) events to annual and seasonal nitrate (N-NO3) export and identified the regional meteorological drivers of inter-annual variability in ROS N-NO3 export (ROS-N) at 9 headwater streams located across Ontario, Canada and the northeastern United States. Although on average only 3.3 % of annual precipitation fell as ROS during winter over the study period, these events contributed a significant proportion of annual and winter N-NO3 export at the majority of sites (average of 12 and 42 %, respectively); with the exception of the most northern catchment, where total winter precipitation was exceptionally low (average 77 mm). In years with a greater magnitude of ROS events, the timing of the peak N-NO3 export period (during spring melt) was redistributed to earlier in the year. Variability in ROS frequency and magnitude amongst sites was high and a generalised linear model demonstrated that this spatial variability could be explained by interactive effects between regional and site-specific drivers. Snowpack coverage was particularly important for explaining the site-specific ROS response. Specifically, ROS events were less common when higher temperatures eliminated snow cover despite increasing the proportion of winter rainfall, whereas ROS event frequency was greater at sites where sufficient snow cover remained. This research suggests that catchment response to changes in N deposition is sensitive to climate change; a vulnerability which appears to vary in intensity throughout the seasonally snow-covered temperate region. Furthermore, the sensitivity of stream N-NO3 export to ROS events and potential shifts (earlier) in the timing of N-NO3 export relative to other nutrients affect downstream nutrient stoichiometry and the community composition of phytoplankton and other algae.","language":"English","publisher":"Springer International Publishing Switzerland","doi":"10.1007/s10533-016-0255-z","collaboration":"USGS","usgsCitation":"Crossman, J., Eimers, M.C., Casson, N.J., Burns, D.A., Campbell, J.L., Likens, G.E., Mitchell, M., Nelson, S.J., Shanley, J.B., Watmough, S.A., and Webster, K.L., 2016, Regional meteorological drivers and long term trends of winter-spring nitrate dynamics across watersheds in northeastern North America: Biogeochemistry, v. 130, no. 3, p. 247-265, https://doi.org/10.1007/s10533-016-0255-z.","productDescription":"19 p. ","startPage":"247","endPage":"265","ipdsId":"IP-073759","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":333424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":333335,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007/s10533-016-0255-z"}],"country":"Canada, United States","state":"Maine, New Hampshire, New York, Ontario,Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.94873046875,\n 41.77131167976407\n ],\n [\n -74.94873046875,\n 42.342305278572816\n ],\n [\n -74.091796875,\n 42.342305278572816\n ],\n [\n -74.091796875,\n 41.77131167976407\n ],\n [\n -74.94873046875,\n 41.77131167976407\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.421875,\n 44.166444664458595\n ],\n [\n -72.421875,\n 44.512176171071054\n ],\n [\n -72.02636718749999,\n 44.512176171071054\n ],\n [\n -72.02636718749999,\n 44.166444664458595\n ],\n [\n -72.421875,\n 44.166444664458595\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.02636718749999,\n 43.37311218382002\n ],\n [\n -72.02636718749999,\n 43.96119063892024\n ],\n [\n -71.30126953124999,\n 43.96119063892024\n ],\n [\n -71.30126953124999,\n 43.37311218382002\n ],\n [\n -72.02636718749999,\n 43.37311218382002\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.5107421875,\n 44.5435052132082\n ],\n [\n -68.5107421875,\n 45.058001435398275\n ],\n [\n -67.69775390625,\n 45.058001435398275\n ],\n [\n -67.69775390625,\n 44.5435052132082\n ],\n [\n -68.5107421875,\n 44.5435052132082\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.8486328125,\n 45.1510532655634\n ],\n [\n -79.8486328125,\n 45.96642454131025\n ],\n [\n -78.5302734375,\n 45.96642454131025\n ],\n [\n -78.5302734375,\n 45.1510532655634\n ],\n [\n -79.8486328125,\n 45.1510532655634\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.814453125,\n 46.76996843356982\n ],\n [\n -84.814453125,\n 47.53203824675999\n ],\n [\n -83.84765625,\n 47.53203824675999\n ],\n [\n -83.84765625,\n 46.76996843356982\n ],\n [\n -84.814453125,\n 46.76996843356982\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.7021484375,\n 49.196064000723794\n ],\n [\n -94.7021484375,\n 49.76707407366792\n ],\n [\n -93.66943359374999,\n 49.76707407366792\n ],\n [\n -93.66943359374999,\n 49.196064000723794\n ],\n [\n -94.7021484375,\n 49.196064000723794\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"130","issue":"3","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-04","publicationStatus":"PW","scienceBaseUri":"5881dedae4b01192927d9f8d","contributors":{"authors":[{"text":"Crossman, Jill","contributorId":178408,"corporation":false,"usgs":false,"family":"Crossman","given":"Jill","email":"","affiliations":[],"preferred":false,"id":658759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eimers, M Catherine","contributorId":178409,"corporation":false,"usgs":false,"family":"Eimers","given":"M","email":"","middleInitial":"Catherine","affiliations":[],"preferred":false,"id":658760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casson, Nora J.","contributorId":169271,"corporation":false,"usgs":false,"family":"Casson","given":"Nora","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":658761,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":658758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, John L.","contributorId":178410,"corporation":false,"usgs":false,"family":"Campbell","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":658762,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Likens, Gene E","contributorId":178411,"corporation":false,"usgs":false,"family":"Likens","given":"Gene","email":"","middleInitial":"E","affiliations":[],"preferred":false,"id":658763,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mitchell, Myron J","contributorId":178412,"corporation":false,"usgs":false,"family":"Mitchell","given":"Myron J","affiliations":[],"preferred":false,"id":658764,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nelson, Sarah J.","contributorId":167269,"corporation":false,"usgs":false,"family":"Nelson","given":"Sarah","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":658767,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":658765,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Watmough, Shaun A.","contributorId":178413,"corporation":false,"usgs":false,"family":"Watmough","given":"Shaun","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":658766,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Webster, Kara L","contributorId":178414,"corporation":false,"usgs":false,"family":"Webster","given":"Kara","email":"","middleInitial":"L","affiliations":[],"preferred":false,"id":658768,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70179744,"text":"70179744 - 2016 - Evaluation of gas production potential from gas hydrate deposits in National Petroleum Reserve Alaska using numerical simulations","interactions":[],"lastModifiedDate":"2017-01-17T10:26:02","indexId":"70179744","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5264,"text":"Journal of Natural Gas Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of gas production potential from gas hydrate deposits in National Petroleum Reserve Alaska using numerical simulations","docAbstract":"An evaluation of the gas production potential of Sunlight Peak gas hydrate accumulation in the eastern portion of the National Petroleum Reserve Alaska (NPRA) of Alaska North Slope (ANS) is conducted using numerical simulations, as part of the U.S. Geological Survey (USGS) gas hydrate Life Cycle Assessment program. A field scale reservoir model for Sunlight Peak is developed using Advanced Processes & Thermal Reservoir Simulator (STARS) that approximates the production design and response of this gas hydrate field. The reservoir characterization is based on available structural maps and the seismic-derived hydrate saturation map of the study region. A 3D reservoir model, with heterogeneous distribution of the reservoir properties (such as porosity, permeability and vertical hydrate saturation), is developed by correlating the data from the Mount Elbert well logs. Production simulations showed that the Sunlight Peak prospect has the potential of producing 1.53 × 109 ST m3 of gas in 30 years by depressurization with a peak production rate of around 19.4 × 104 ST m3/day through a single horizontal well. To determine the effect of uncertainty in reservoir properties on the gas production, an uncertainty analysis is carried out. It is observed that for the range of data considered, the overall cumulative production from the Sunlight Peak will always be within the range of ±4.6% error from the overall mean value of 1.43 × 109 ST m3. A sensitivity analysis study showed that the proximity of the reservoir from the base of permafrost and the base of hydrate stability zone (BHSZ) has significant effect on gas production rates. The gas production rates decrease with the increase in the depth of the permafrost and the depth of BHSZ. From the overall analysis of the results it is concluded that Sunlight Peak gas hydrate accumulation behaves differently than other Class III reservoirs (Class III reservoirs are composed of a single layer of hydrate with no underlying zone of mobile fluids) due to its smaller thickness and high angle of dip.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jngse.2016.11.021","usgsCitation":"Nandanwar, M.S., Anderson, B.J., Ajayi, T., Collett, T.S., and Zyrianova, M.V., 2016, Evaluation of gas production potential from gas hydrate deposits in National Petroleum Reserve Alaska using numerical simulations: Journal of Natural Gas Science and Engineering, v. 36, no. A, p. 760-772, https://doi.org/10.1016/j.jngse.2016.11.021.","productDescription":"13 p.","startPage":"760","endPage":"772","ipdsId":"IP-079065","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":333231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.86328125,\n 69.38804929116819\n ],\n [\n -154.86328125,\n 70.90226826757711\n ],\n [\n -151.402587890625,\n 70.90226826757711\n ],\n [\n -151.402587890625,\n 69.38804929116819\n ],\n [\n -154.86328125,\n 69.38804929116819\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"A","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"587f3c31e4b0d96de2564547","contributors":{"authors":[{"text":"Nandanwar, Manish S.","contributorId":178323,"corporation":false,"usgs":false,"family":"Nandanwar","given":"Manish","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":658498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Brian J.","contributorId":147120,"corporation":false,"usgs":false,"family":"Anderson","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":658499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ajayi, Taiwo","contributorId":178324,"corporation":false,"usgs":false,"family":"Ajayi","given":"Taiwo","email":"","affiliations":[],"preferred":false,"id":658500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"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":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":658501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zyrianova, Margarita V. 0000-0002-3669-1320 rita@usgs.gov","orcid":"https://orcid.org/0000-0002-3669-1320","contributorId":1203,"corporation":false,"usgs":true,"family":"Zyrianova","given":"Margarita","email":"rita@usgs.gov","middleInitial":"V.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":658497,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194545,"text":"70194545 - 2016 - A glacier runoff extension to the Precipitation Runoff Modeling System","interactions":[],"lastModifiedDate":"2017-12-05T11:00:44","indexId":"70194545","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"A glacier runoff extension to the Precipitation Runoff Modeling System","docAbstract":"A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while maintaining model usability. PRMSglacier is validated on two basins in Alaska, Wolverine, and Gulkana Glacier basin, which have been studied since 1966 and have a substantial amount of data with which to test model performance over a long period of time covering a wide range of climatic and hydrologic conditions. When error in field measurements is considered, the Nash-Sutcliffe efficiencies of streamflow are 0.87 and 0.86, the absolute bias fractions of the winter mass balance simulations are 0.10 and 0.08, and the absolute bias fractions of the summer mass balances are 0.01 and 0.03, all computed over 42 years for the Wolverine and Gulkana Glacier basins, respectively. Without taking into account measurement error, the values are still within the range achieved by the more computationally expensive codes tested over shorter time periods.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JF003789","usgsCitation":"Van Beusekom, A.E., and Viger, R.J., 2016, A glacier runoff extension to the Precipitation Runoff Modeling System: Journal of Geophysical Research F: Earth Surface, v. 121, no. 11, p. 2001-2021, https://doi.org/10.1002/2015JF003789.","productDescription":"21 p.","startPage":"2001","endPage":"2021","ipdsId":"IP-081396","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":438520,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75T3HMV","text":"USGS data release","linkHelpText":"Supporting data for A Glacier Runoff Extension to the Precipitation Runoff Modeling System"},{"id":349679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-04","publicationStatus":"PW","scienceBaseUri":"5a60fc9be4b06e28e9c24045","contributors":{"authors":[{"text":"Van Beusekom, Ashley E. 0000-0002-6996-978X beusekom@usgs.gov","orcid":"https://orcid.org/0000-0002-6996-978X","contributorId":3992,"corporation":false,"usgs":true,"family":"Van Beusekom","given":"Ashley","email":"beusekom@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":724413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":724414,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185012,"text":"70185012 - 2016 - Calibrated acoustic emission system records M -3.5 to M -8 events generated on a saw-cut granite sample","interactions":[],"lastModifiedDate":"2017-03-14T14:47:05","indexId":"70185012","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3306,"text":"Rock Mechanics and Rock Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Calibrated acoustic emission system records M -3.5 to M -8 events generated on a saw-cut granite sample","docAbstract":"Acoustic emission (AE) analyses have been used for decades for rock mechanics testing, but because AE systems are not typically calibrated, the absolute sizes of dynamic microcrack growth and other physical processes responsible for the generation of AEs are poorly constrained. We describe a calibration technique for the AE recording system as a whole (transducers + amplifiers + digitizers + sample + loading frame) that uses the impact of a 4.76-mm free-falling steel ball bearing as a reference source. We demonstrate the technique on a 76-mm diameter cylinder of westerly granite loaded in a triaxial deformation apparatus at 40 MPa confining pressure. The ball bearing is dropped inside a cavity within the sample while inside the pressure vessel. We compare this reference source to conventional AEs generated during loading of a saw-cut fault in a second granite sample. All located AEs occur on the saw-cut surface and have moment magnitudes ranging from M −5.7 down to at least M −8. Dynamic events rupturing the entire simulated fault surface (stick–slip events) have measurable stress drop and macroscopic slip and radiate seismic waves similar to those from a M −3.5 earthquake. The largest AE events that do not rupture the entire fault are M −5.7. For these events, we also estimate the corner frequency (200–300 kHz), and we assume the Brune model to estimate source dimensions of 4–6 mm. These AE sources are larger than the 0.2 mm grain size and smaller than the 76 × 152 mm fault surface.
","language":"English","publisher":"Springer","doi":"10.1007/s00603-016-1082-1","usgsCitation":"McLaskey, G.C., and Lockner, D.A., 2016, Calibrated acoustic emission system records M -3.5 to M -8 events generated on a saw-cut granite sample: Rock Mechanics and Rock Engineering, v. 49, no. 11, p. 4527-4536, https://doi.org/10.1007/s00603-016-1082-1.","productDescription":"10 p.","startPage":"4527","endPage":"4536","ipdsId":"IP-063673","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":337524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-10","publicationStatus":"PW","scienceBaseUri":"58c90125e4b0849ce97abccf","chorus":{"doi":"10.1007/s00603-016-1082-1","url":"http://dx.doi.org/10.1007/s00603-016-1082-1","publisher":"Springer Nature","authors":"McLaskey Gregory C., Lockner David A.","journalName":"Rock Mechanics and Rock Engineering","publicationDate":"9/10/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"9/10/2016"},"contributors":{"authors":[{"text":"McLaskey, Gregory C. gmclaskey@usgs.gov","contributorId":4112,"corporation":false,"usgs":true,"family":"McLaskey","given":"Gregory","email":"gmclaskey@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":683953,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":683952,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70184976,"text":"70184976 - 2016 - Using thermal limits to assess establishment of fish dispersing to high-latitude and high-elevation watersheds","interactions":[],"lastModifiedDate":"2017-03-14T15:59:14","indexId":"70184976","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Using thermal limits to assess establishment of fish dispersing to high-latitude and high-elevation watersheds","docAbstract":"Distributional shifts of biota to higher latitudes and elevations are presumably influenced by species-specific physiological tolerances related to warming temperatures. However, it is establishment rather than dispersal that may be limiting colonizations in these cold frontier areas. In freshwater ecosystems, perennial groundwater springs provide critical winter thermal refugia in these extreme environments. By reconciling the thermal characteristics of these refugia with the minimum thermal tolerances of life stages critical for establishment, we develop a strategy to focus broad projections of northward and upward range shifts to the specific habitats that are likely for establishments. We evaluate this strategy using chum salmon (Oncorhynchus keta) and pink salmon (Oncorhynchus gorbuscha) that seem poised to colonize Arctic watersheds. Stream habitats with a minimum temperature of 4 °C during spawning and temperatures above 2 °C during egg incubation were most vulnerable to establishments by chum and pink salmon. This strategy will improve modelling forecasts of range shifts for cold freshwater habitats and focus proactive efforts to conserve both newly emerging fisheries and native species at northern and upper distributional extremes.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2016-0051","usgsCitation":"Dunmall, K.M., Mochnacz, N.J., Zimmerman, C.E., Lean, C., and Reist, J.D., 2016, Using thermal limits to assess establishment of fish dispersing to high-latitude and high-elevation watersheds: Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 12, p. 1750-1758, https://doi.org/10.1139/cjfas-2016-0051.","productDescription":"9 p.","startPage":"1750","endPage":"1758","ipdsId":"IP-057378","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":470452,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/73094","text":"External Repository"},{"id":337544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c90125e4b0849ce97abcd1","contributors":{"authors":[{"text":"Dunmall, Karen M.","contributorId":189272,"corporation":false,"usgs":false,"family":"Dunmall","given":"Karen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":684319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mochnacz, Neil J.","contributorId":189273,"corporation":false,"usgs":false,"family":"Mochnacz","given":"Neil","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":684320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":683797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lean, Charles","contributorId":189274,"corporation":false,"usgs":false,"family":"Lean","given":"Charles","email":"","affiliations":[],"preferred":false,"id":684321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reist, James D.","contributorId":189275,"corporation":false,"usgs":false,"family":"Reist","given":"James","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":684322,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174906,"text":"fs20163053 - 2016 - Water clarity of the Colorado River—Implications for food webs and fish communities","interactions":[],"lastModifiedDate":"2016-11-01T15:36:18","indexId":"fs20163053","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3053","title":"Water clarity of the Colorado River—Implications for food webs and fish communities","docAbstract":"The closure of Glen Canyon Dam in 1963 resulted in drastic changes to water clarity, temperature, and flow of the Colorado River in Glen, Marble, and Grand Canyons. The Colorado River is now much clearer, water temperature is less variable throughout the year, and the river is much colder in the summer months. The flow—regulated by the dam—is now less variable annually, but has larger daily fluctuations than during pre-dam times. All of these changes have resulted in a different fish community and different food resources for fish than existed before the dam was built. Recent monitoring of water clarity, by measuring turbidity, has helped scientists and river managers understand modern water-clarity patterns in the dam-regulated Colorado River. These data were then used to estimate pre-dam turbidity in the Colorado River in order to make comparisons of pre-dam and dam-regulated conditions, which are useful for assessing biological changes in the river over time. Prior to dam construction, the large sediment load resulted in low water clarity almost all of the time, a condition which was more favorable for the native fish community.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163053","usgsCitation":"Voichick, N., Kennedy, T.A., Topping, D.J., Griffiths, R.E., and Fry, K.L., 2016, Water clarity of the Colorado River—Implications for food webs and fish communities: U.S. Geological Survey Fact Sheet 2016–5053, 4 p., https://dx.doi.org/10.3133/fs20163053.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-067865","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":330598,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3053/fs20163053.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3053"},{"id":330597,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3053/coverthb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Nevada Utah, New Mexico","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.52392578125,\n 39.87601941962116\n ],\n [\n -104.62280273437499,\n 39.06184913429154\n ],\n [\n -106.226806640625,\n 38.487994609214795\n ],\n [\n -107.962646484375,\n 38.039438891821746\n ],\n [\n -108.06152343749999,\n 37.31775185163688\n ],\n [\n -108.6328125,\n 36.359374956015856\n ],\n [\n -109.16015624999999,\n 35.24561909420681\n ],\n [\n -109.127197265625,\n 32.90726224488304\n ],\n [\n -109.13818359375,\n 31.484893386890164\n ],\n [\n -111.126708984375,\n 31.316101383495624\n ],\n [\n -114.80712890625,\n 32.47269502206151\n ],\n [\n -114.697265625,\n 32.731840896865684\n ],\n [\n -114.93896484374999,\n 34.415973384481866\n ],\n [\n -114.97192382812499,\n 35.594785665487244\n ],\n [\n -114.78515624999999,\n 36.85325222344018\n ],\n [\n -114.32373046875,\n 37.49229399862877\n ],\n [\n -113.477783203125,\n 37.49229399862877\n ],\n [\n -112.19238281249999,\n 37.60552821745789\n ],\n [\n -111.236572265625,\n 38.09998264736481\n ],\n [\n -110.0830078125,\n 38.7283759182398\n ],\n [\n -109.281005859375,\n 39.554883059924016\n ],\n [\n -108.182373046875,\n 39.9434364619742\n ],\n [\n -106.3916015625,\n 39.93501296038254\n ],\n [\n -104.52392578125,\n 39.87601941962116\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GCMRC Staff, Southwest Biological Science Center
U.S. Geological Survey
Grand Canyon Monitoring and Research Center
2255 N. Gemini Drive
Flagstaff, AZ 86001
http://www.gcmrc.gov/
Climate change is facilitating rapid changes in the composition and distribution of vegetation at northern latitudes, raising questions about the responses of wildlife that rely on arctic ecosystems. One widely observed change occurring in arctic tundra ecosystems is an increasing dominance of deciduous shrub vegetation. Our goals were to examine the tolerance of arctic-nesting bird species to existing gradients of vegetation along the boreal forest-tundra ecotone, to predict the abundance of species across different heights and densities of shrubs, and to identify species that will be most or least responsive to ongoing expansion of shrubs in tundra ecosystems. We conducted 1,208 point counts on 12 study blocks from 2012–2014 in northwestern Alaska, using repeated surveys to account for imperfect detection of birds. We considered the importance of shrub height, density of low and tall shrubs (i.e. shrubs >0.5 m tall), percent of ground cover attributed to shrubs (including dwarf shrubs <0.5 m tall), and percent of herbaceous plant cover in predicting bird abundance. Among 17 species considered, only gray-cheeked thrush (Catharus minimus) abundance was associated with the highest values of all shrub metrics in its top predictive model. All other species either declined in abundance in response to one or more shrub metrics or reached a threshold where further increases in shrubs did not contribute to greater abundance. In many instances the relationship between avian abundance and shrubs was nonlinear, with predicted abundance peaking at moderate values of the covariate, then declining at high values. In particular, a large number of species were responsive to increasing values of average shrub height with six species having highest abundance at near-zero values of shrub height and abundance of four other species decreasing once heights reached moderate values (≤ 33 cm). Our findings suggest that increases in shrub cover and density will negatively affect abundance of only a few bird species and may potentially be beneficial for many others. As shrub height increases further, however, a considerable number of tundra bird species will likely find habitat increasingly unsuitable.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0164755","usgsCitation":"Thompson, S.J., Handel, C.M., Richardson, R.M., and McNew, L.B., 2016, When winners become losers: Predicted nonlinear responses of arctic birds to increasing woody vegetation: PLoS ONE, v. 11, no. 11, p. 1-17, https://doi.org/10.1371/journal.pone.0164755.","productDescription":"e0164755; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-075257","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470519,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0164755","text":"Publisher Index Page"},{"id":438515,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CN722Z","text":"USGS data release","linkHelpText":"Avian Point Count, Habitat, and Covariate Data for Subarctic Bird Abundance, Seward Peninsula, Alaska, 2012-2014"},{"id":339308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.22265625,\n 64.33039136366138\n ],\n [\n -161.60888671875,\n 64.33039136366138\n ],\n [\n -161.60888671875,\n 66.63119845535732\n ],\n [\n -168.22265625,\n 66.63119845535732\n ],\n [\n -168.22265625,\n 64.33039136366138\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"11","tableOfContents":"Climate change is facilitating rapid changes in the composition and distribution of vegetation at northern latitudes, raising questions about the responses of wildlife that rely on arctic ecosystems. One widely observed change occurring in arctic tundra ecosystems is an increasing dominance of deciduous shrub vegetation. Our goals were to examine the tolerance of arctic-nesting bird species to existing gradients of vegetation along the boreal forest-tundra ecotone, to predict the abundance of species across different heights and densities of shrubs, and to identify species that will be most or least responsive to ongoing expansion of shrubs in tundra ecosystems. We conducted 1,208 point counts on 12 study blocks from 2012–2014 in northwestern Alaska, using repeated surveys to account for imperfect detection of birds. We considered the importance of shrub height, density of low and tall shrubs (i.e. shrubs >0.5 m tall), percent of ground cover attributed to shrubs (including dwarf shrubs <0.5 m tall), and percent of herbaceous plant cover in predicting bird abundance. Among 17 species considered, only gray-cheeked thrush (Catharus minimus) abundance was associated with the highest values of all shrub metrics in its top predictive model. All other species either declined in abundance in response to one or more shrub metrics or reached a threshold where further increases in shrubs did not contribute to greater abundance. In many instances the relationship between avian abundance and shrubs was nonlinear, with predicted abundance peaking at moderate values of the covariate, then declining at high values. In particular, a large number of species were responsive to increasing values of average shrub height with six species having highest abundance at near-zero values of shrub height and abundance of four other species decreasing once heights reached moderate values (≤ 33 cm). Our findings suggest that increases in shrub cover and density will negatively affect abundance of only a few bird species and may potentially be beneficial for many others. As shrub height increases further, however, a considerable number of tundra bird species will likely find habitat increasingly unsuitable.
","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"58e753ede4b09da6799c0c4f","contributors":{"authors":[{"text":"Thompson, Sarah J. 0000-0002-5733-8198 sjthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-5733-8198","contributorId":5434,"corporation":false,"usgs":true,"family":"Thompson","given":"Sarah","email":"sjthompson@usgs.gov","middleInitial":"J.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":688154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":688155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Rachel M. 0000-0001-8501-250X rrichardson@usgs.gov","orcid":"https://orcid.org/0000-0001-8501-250X","contributorId":205918,"corporation":false,"usgs":true,"family":"Richardson","given":"Rachel","email":"rrichardson@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":688156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNew, Lance B.","contributorId":190322,"corporation":false,"usgs":false,"family":"McNew","given":"Lance","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":688157,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192022,"text":"70192022 - 2016 - Microrefuges and the occurrence of thermal specialists: implications for wildlife persistence amidst changing temperatures","interactions":[],"lastModifiedDate":"2017-10-19T15:05:42","indexId":"70192022","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5385,"text":"Climate Change Responses","active":true,"publicationSubtype":{"id":10}},"title":"Microrefuges and the occurrence of thermal specialists: implications for wildlife persistence amidst changing temperatures","docAbstract":"Background
Contemporary climate change is affecting nearly all biomes, causing shifts in animal distributions, phenology, and persistence. Favorable microclimates may buffer organisms against rapid changes in climate, thereby allowing time for populations to adapt. The degree to which microclimates facilitate the local persistence of climate-sensitive species, however, is largely an open question. We addressed the importance of microrefuges in mammalian thermal specialists, using the American pika (Ochotona princeps) as a model organism. Pikas are sensitive to ambient temperatures, and are active year-round in the alpine where conditions are highly variable. We tested four hypotheses about the relationship between microrefuges and pika occurrence: 1) Local-habitat Hypothesis (local-habitat conditions are paramount, regardless of microrefuge); 2) Surface-temperature Hypothesis (surrounding temperatures, unmoderated by microrefuge, best predict occurrence); 3) Interstitial-temperature Hypothesis (temperatures within microrefuges best predict occurrence), and 4) Microrefuge Hypothesis (the degree to which microrefuges moderate the surrounding temperature facilitates occurrence, regardless of other habitat characteristics). We examined pika occurrence at 146 sites across an elevational gradient. We quantified pika presence, physiographic habitat characteristics and forage availability at each site, and deployed paired temperature loggers at a subset of sites to measure surface and subterranean temperatures.
Results
We found strong support for the Microrefuge Hypothesis. Pikas were more likely to occur at sites where the subsurface environment substantially moderated surface temperatures, especially during the warm season. Microrefugium was the strongest predictor of pika occurrence, independent of other critical habitat characteristics, such as forage availability.
Conclusions
By modulating surface temperatures, microrefuges may strongly influence where temperature-limited animals persist in rapidly warming environments. As climate change continues to manifest, efforts to understand the changing dynamics of animal-habitat relationships will be enhanced by considering the quality of microrefuges.
Volcanic eruptions fundamentally alter landscapes, paving over channels, decimating biota, and emplacing fresh, unweathered material. The fluvial incision of blocky lava flows is a geomorphic puzzle. First, high surface permeability and lack of sediment should preclude geomorphically effective surface runoff and dissection. Furthermore, past work has demonstrated the importance of extreme floods in driving incision via column toppling and plucking in columnar basalt, but it is unclear how incision occurs in systems where surface blocks are readily mobile. We examine rapid fluvial incision of the Collier lava flow, an andesitic Holocene lava flow in the High Cascades of Oregon. Since lava flow emplacement ∼1600 yr ago, White Branch Creek has incised bedrock gorges up to 8 m deep into the coherent core of the lava flow and deposited >0.2 km3 of sediment on the lava flow surface. Field observation points to a bimodal discharge regime in the channel, with evidence for both annual snowmelt runoff and outburst floods from Collier glacier, as well as historical evidence of vigorous glacial meltwater. To determine the range of discharge events capable of incision in White Branch Creek, we used a mechanistic model of fluvial abrasion. We show that the observed incision implies that moderate flows are capable of both initiating channel formation and sustaining incision. Our results have implications for the evolution of volcanic systems worldwide, where glaciation and/or mass wasting may accelerate fluvial processes by providing large amounts of sediment to otherwise porous, sediment-starved landscapes.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31537.1","usgsCitation":"Sweeney, K., and Roering, J., 2016, Rapid fluvial incision of a late Holocene lava flow: Insights from LiDAR, alluvial stratigraphy, and numerical modeling: GSA Bulletin, v. 129, no. 3-4, p. 500-512, https://doi.org/10.1130/B31537.1.","productDescription":"13 p.","startPage":"500","endPage":"512","ipdsId":"IP-074312","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":343408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"129","issue":"3-4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-09","publicationStatus":"PW","scienceBaseUri":"595f4c3de4b0d1f9f057e341","contributors":{"authors":[{"text":"Sweeney, Kristin 0000-0002-5674-1217 ksweeney@usgs.gov","orcid":"https://orcid.org/0000-0002-5674-1217","contributorId":194296,"corporation":false,"usgs":true,"family":"Sweeney","given":"Kristin","email":"ksweeney@usgs.gov","affiliations":[],"preferred":true,"id":703670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roering, Joshua J.","contributorId":194297,"corporation":false,"usgs":false,"family":"Roering","given":"Joshua J.","affiliations":[],"preferred":false,"id":703671,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192473,"text":"70192473 - 2016 - Seismic imaging of the metamorphism of young sediment into new crystalline crust in the actively rifting Imperial Valley, California","interactions":[],"lastModifiedDate":"2017-10-31T14:17:49","indexId":"70192473","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Seismic imaging of the metamorphism of young sediment into new crystalline crust in the actively rifting Imperial Valley, California","docAbstract":"Plate-boundary rifting between transform faults is opening the Imperial Valley of southern California and the rift is rapidly filling with sediment from the Colorado River. Three 65–90 km long seismic refraction profiles across and along the valley, acquired as part of the 2011 Salton Seismic Imaging Project, were analyzed to constrain upper crustal structure and the transition from sediment to underlying crystalline rock. Both first arrival travel-time tomography and frequency-domain full-waveform inversion were applied to provide P-wave velocity models down to ∼7 km depth. The valley margins are fault-bounded, beyond which thinner sediment has been deposited on preexisting crystalline rocks. Within the central basin, seismic velocity increases continuously from ∼1.8 km/s sediment at the surface to >6 km/s crystalline rock with no sharp discontinuity. Borehole data show young sediment is progressively metamorphosed into crystalline rock. The seismic velocity gradient with depth decreases approximately at the 4 km/s contour, which coincides with changes in the porosity and density gradient in borehole core samples. This change occurs at ∼3 km depth in most of the valley, but at only ∼1.5 km depth in the Salton Sea geothermal field. We interpret progressive metamorphism caused by high heat flow to be creating new crystalline crust throughout the valley at a rate comparable to the ≥2 km/Myr sedimentation rate. The newly formed crystalline crust extends to at least 7–8 km depth, and it is shallower and faster where heat flow is higher. Most of the active seismicity occurs within this new crust.
","language":"English","publisher":"AGU","doi":"10.1002/2016GC006610","usgsCitation":"Han, L., Hole, J., Stock, J., Fuis, G.S., Williams, C.F., Delph, J., Davenport, K., and Livers, A., 2016, Seismic imaging of the metamorphism of young sediment into new crystalline crust in the actively rifting Imperial Valley, California: Geochemistry, Geophysics, Geosystems, v. 17, no. 11, p. 4566-4584, https://doi.org/10.1002/2016GC006610.","productDescription":"19 p.","startPage":"4566","endPage":"4584","ipdsId":"IP-081132","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":462045,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gc006610","text":"Publisher Index Page"},{"id":347889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Imperial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.42211914062499,\n 32.667124733120325\n ],\n [\n -114.70825195312501,\n 32.667124733120325\n ],\n [\n -114.70825195312501,\n 33.72662401401029\n ],\n [\n -116.42211914062499,\n 33.72662401401029\n ],\n [\n -116.42211914062499,\n 32.667124733120325\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-18","publicationStatus":"PW","scienceBaseUri":"59f98bbbe4b0531197afa00f","contributors":{"authors":[{"text":"Han, Liang","contributorId":49690,"corporation":false,"usgs":true,"family":"Han","given":"Liang","email":"","affiliations":[],"preferred":false,"id":716024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hole, John","contributorId":198438,"corporation":false,"usgs":false,"family":"Hole","given":"John","affiliations":[],"preferred":false,"id":716025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stock, Joann","contributorId":198439,"corporation":false,"usgs":false,"family":"Stock","given":"Joann","affiliations":[],"preferred":false,"id":716026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuis, Gary S. 0000-0002-3078-1544 fuis@usgs.gov","orcid":"https://orcid.org/0000-0002-3078-1544","contributorId":2639,"corporation":false,"usgs":true,"family":"Fuis","given":"Gary","email":"fuis@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":716023,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Colin F. 0000-0003-2196-5496 colin@usgs.gov","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":274,"corporation":false,"usgs":true,"family":"Williams","given":"Colin","email":"colin@usgs.gov","middleInitial":"F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":716027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delph, Jonathan","contributorId":198440,"corporation":false,"usgs":false,"family":"Delph","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":716028,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davenport, Kathy","contributorId":198441,"corporation":false,"usgs":false,"family":"Davenport","given":"Kathy","email":"","affiliations":[],"preferred":false,"id":716029,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Livers, Amanda","contributorId":198442,"corporation":false,"usgs":false,"family":"Livers","given":"Amanda","email":"","affiliations":[],"preferred":false,"id":716030,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70185036,"text":"70185036 - 2016 - Review of footnotes and annotations to the 1949–2013 tables of standard atomic weights and tables of isotopic compositions of the elements (IUPAC Technical Report)","interactions":[],"lastModifiedDate":"2017-03-13T16:56:17","indexId":"70185036","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3207,"text":"Pure and Applied Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Review of footnotes and annotations to the 1949–2013 tables of standard atomic weights and tables of isotopic compositions of the elements (IUPAC Technical Report)","docAbstract":"The Commission on Isotopic Abundances and Atomic Weights uses annotations given in footnotes that are an integral part of the Tables of Standard Atomic Weights to alert users to the possibilities of quite extraordinary occurrences, as well as sources with abnormal atomic-weight values outside an otherwise acceptable range. The basic need for footnotes to the Standard Atomic Weights Table and equivalent annotations to the Table of Isotopic Compositions of the Elements arises from the necessity to provide users with information that is relevant to one or more elements, but that cannot be provided using numerical data in columns. Any desire to increase additional information conveyed by annotations to these Tables is tempered by the need to preserve a compact format and a style that can alert users, who would not be inclined to consult either the last full element-by-element review or the full text of a current Standard Atomic Weights of the Elements report. Since 1989, the footnotes of the Tables of Standard Atomic Weights and the annotations in column 5 of the Table of Isotopic Compositions of the Elements have been harmonized by use of three lowercase footnotes, “g”, “m”, and “r”, that signify geologically exceptionally specimens (“g”), modified isotopic compositions in material subjected to undisclosed or inadvertent isotopic fractionation (“m”), and the range in isotopic composition of normal terrestrial material prevents more precise atomic-weight value being given (“r”). As some elements are assigned intervals for their standard atomic-weight values (applies to 12 elements since 2009), footnotes “g” and “r” are no longer needed for these elements.
","language":"English","publisher":"IUPAC","doi":"10.1515/pac-2016-0203","usgsCitation":"Coplen, T.B., and Holden, N.E., 2016, Review of footnotes and annotations to the 1949–2013 tables of standard atomic weights and tables of isotopic compositions of the elements (IUPAC Technical Report): Pure and Applied Chemistry, v. 88, no. 7, p. 689-699, https://doi.org/10.1515/pac-2016-0203.","productDescription":"11 p.","startPage":"689","endPage":"699","ipdsId":"IP-072769","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470470,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1515/pac-2016-0203","text":"Publisher Index Page"},{"id":337476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-28","publicationStatus":"PW","scienceBaseUri":"58c7af9fe4b0849ce9795e94","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":684029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holden, Norman E.","contributorId":189167,"corporation":false,"usgs":false,"family":"Holden","given":"Norman","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":684030,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185051,"text":"70185051 - 2016 - Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses","interactions":[],"lastModifiedDate":"2017-03-13T16:21:41","indexId":"70185051","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses","docAbstract":"Mixing models are a commonly used method for hydrograph separation, but can be hindered by the subjective choice of the end-member tracer concentrations. This work tests a new variant of mixing model that uses high-frequency measures of two tracers and streamflow to separate total streamflow into water from slowflow and fastflow sources. The ratio between the concentrations of the two tracers is used to create a time-variable estimate of the concentration of each tracer in the fastflow end-member. Multiple synthetic data sets, and data from two hydrologically diverse streams, are used to test the performance and limitations of the new model (two-tracer ratio-based mixing model: TRaMM). When applied to the synthetic streams under many different scenarios, the TRaMM produces results that were reasonable approximations of the actual values of fastflow discharge (±0.1% of maximum fastflow) and fastflow tracer concentrations (±9.5% and ±16% of maximum fastflow nitrate concentration and specific conductance, respectively). With real stream data, the TRaMM produces high-frequency estimates of slowflow and fastflow discharge that align with expectations for each stream based on their respective hydrologic settings. The use of two tracers with the TRaMM provides an innovative and objective approach for estimating high-frequency fastflow concentrations and contributions of fastflow water to the stream. This provides useful information for tracking chemical movement to streams and allows for better selection and implementation of water quality management strategies.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR018797","usgsCitation":"Kronholm, S.C., and Capel, P.D., 2016, Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses: Water Resources Research, v. 52, no. 9, p. 6881-6896, https://doi.org/10.1002/2016WR018797.","productDescription":"16 p.","startPage":"6881","endPage":"6896","ipdsId":"IP-075597","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":470473,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr018797","text":"Publisher Index Page"},{"id":438519,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6NMQ","text":"USGS data release","linkHelpText":"Real and synthetic data used to test the Two-tracer Ratio-based Mixing Model (TRaMM)"},{"id":337470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-10","publicationStatus":"PW","scienceBaseUri":"58c7af9ee4b0849ce9795e8e","contributors":{"authors":[{"text":"Kronholm, Scott C.","contributorId":184190,"corporation":false,"usgs":false,"family":"Kronholm","given":"Scott","email":"","middleInitial":"C.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":684079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":684078,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192622,"text":"70192622 - 2016 - Dynamic social networks based on movement","interactions":[],"lastModifiedDate":"2017-11-10T11:06:28","indexId":"70192622","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5549,"text":"The Annals of Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic social networks based on movement","docAbstract":"Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.
","language":"English","publisher":"The Institute of Mathematical Statistics","doi":"10.1214/16-AOAS970","usgsCitation":"Scharf, H., Hooten, M., Fosdick, B.K., Johnson, D., London, J.M., and Durban, J., 2016, Dynamic social networks based on movement: The Annals of Applied Statistics, v. 10, no. 4, p. 2182-2202, https://doi.org/10.1214/16-AOAS970.","productDescription":"21 p.","startPage":"2182","endPage":"2202","ipdsId":"IP-071447","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470448,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://arxiv.org/abs/1512.07607","text":"Publisher Index Page"},{"id":348567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8d2e4b09af898c86151","contributors":{"authors":[{"text":"Scharf, Henry","contributorId":200238,"corporation":false,"usgs":false,"family":"Scharf","given":"Henry","affiliations":[],"preferred":false,"id":721562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":716572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fosdick, Bailey K.","contributorId":200239,"corporation":false,"usgs":false,"family":"Fosdick","given":"Bailey","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":721563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":721564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"London, Joshua M.","contributorId":171522,"corporation":false,"usgs":false,"family":"London","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721565,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Durban, John W.","contributorId":200240,"corporation":false,"usgs":false,"family":"Durban","given":"John W.","affiliations":[],"preferred":false,"id":721566,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70182084,"text":"70182084 - 2016 - New findings of twisted-wing parasites (Strepsiptera) in Alaska","interactions":[],"lastModifiedDate":"2017-03-29T11:48:55","indexId":"70182084","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5299,"text":"Newsletter of the Alaska Entomological Society","active":true,"publicationSubtype":{"id":10}},"title":"New findings of twisted-wing parasites (Strepsiptera) in Alaska","docAbstract":"Strepsipterans are a group of insects with a gruesome life history and an enigmatic evolutionary past. Called ‘twisted-wing parasites’, they are minute parasitoids with a very distinct morphology (Figure 1). Alternatively thought to be related to ichneumon wasps, Diptera (flies), Coleoptera (beetles), and even Neuroptera (net-winged insects) (Pohl and Beutel, 2013); the latest genetic and morphological data support the sister order relationship of Strepsiptera and Coleoptera (Niehuis et al., 2012). Strepsipterans are highly modified, males having two hind wings and halteres instead of front wings or elytra. Unlike most parasitoids, they develop inside active, living insects who are sexually sterilized but not killed until or after emergence (Kathirithamby et al., 2015).
","language":"English","publisher":"Alaska Entomological Society","usgsCitation":"Mcdermott, M., 2016, New findings of twisted-wing parasites (Strepsiptera) in Alaska: Newsletter of the Alaska Entomological Society, v. 9, no. 1, p. 6-8.","productDescription":"3 p.","startPage":"6","endPage":"8","ipdsId":"IP-074440","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":335675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335665,"type":{"id":15,"text":"Index Page"},"url":"https://www.akentsoc.org/newsletter-v9-n1","linkFileType":{"id":5,"text":"html"}}],"volume":"9","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58a6c82de4b025c46428626c","contributors":{"authors":[{"text":"Mcdermott, Molly 0000-0002-0000-0831 mmcdermott@usgs.gov","orcid":"https://orcid.org/0000-0002-0000-0831","contributorId":181770,"corporation":false,"usgs":true,"family":"Mcdermott","given":"Molly","email":"mmcdermott@usgs.gov","affiliations":[],"preferred":true,"id":669493,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70178010,"text":"70178010 - 2016 - Effects of consumption-oriented versus trophy-oriented fisheries on Muskellunge population size structure in northern Wisconsin","interactions":[],"lastModifiedDate":"2016-11-01T13:56:10","indexId":"70178010","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of consumption-oriented versus trophy-oriented fisheries on Muskellunge population size structure in northern Wisconsin","docAbstract":"To determine whether a consumption-oriented fishery was compatible with a trophy-oriented fishery for Muskellunge Esox masquinongy, we modeled effects of a spearing fishery and recreational angling fishery on population size structure (i.e., numbers of fish ≥ 102, 114, and 127 cm) in northern Wisconsin. An individual-based simulation model was used to quantify the effect of harvest mortality at currently observed levels of recreational angling and tribal spearing fishery exploitation, along with simulated increases in exploitation, for three typical growth potentials (i.e., low, moderate, and high) of Muskellunge in northern Wisconsin across a variety of minimum length limits (i.e., 71, 102, 114, and 127 cm). Populations with moderate to high growth potential and minimum length limits ≥ 114 cm were predicted to have lower declines in numbers of trophy Muskellunge when subjected to angling-only and mixed fisheries at observed and increased levels of exploitation, which suggested that fisheries with disparate motivations may be able to coexist under certain conditions such as restrictive length limits and low levels of exploitation. However, for most Muskellunge populations in northern Wisconsin regulated by a 102-cm minimum length limit, both angling and spearing fisheries may reduce numbers of trophy Muskellunge as larger declines were predicted across all growth potentials. Our results may be useful if Muskellunge management options in northern Wisconsin are re-examined in the future.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2016.1214646","usgsCitation":"Faust, M.D., and Hansen, M.J., 2016, Effects of consumption-oriented versus trophy-oriented fisheries on Muskellunge population size structure in northern Wisconsin: North American Journal of Fisheries Management, v. 36, no. 6, p. 1336-1346, https://doi.org/10.1080/02755947.2016.1214646.","productDescription":"11 p.","startPage":"1336","endPage":"1346","ipdsId":"IP-075344","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":330629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-28","publicationStatus":"PW","scienceBaseUri":"5819a9c2e4b0bb36a4c9100f","contributors":{"authors":[{"text":"Faust, Matthew D.","contributorId":145776,"corporation":false,"usgs":false,"family":"Faust","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":652538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Michael J. 0000-0001-8522-3876 michaelhansen@usgs.gov","orcid":"https://orcid.org/0000-0001-8522-3876","contributorId":5006,"corporation":false,"usgs":true,"family":"Hansen","given":"Michael","email":"michaelhansen@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":652537,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178027,"text":"70178027 - 2016 - Analyses of infrequent (quasi-decadal) large groundwater recharge events in the northern Great Basin: Their importance for groundwater availability, use, and management","interactions":[],"lastModifiedDate":"2017-01-11T16:32:00","indexId":"70178027","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Analyses of infrequent (quasi-decadal) large groundwater recharge events in the northern Great Basin: Their importance for groundwater availability, use, and management","docAbstract":"There has been a considerable amount of research linking climatic variability to hydrologic responses in the western United States. Although much effort has been spent to assess and predict changes in surface water resources, little has been done to understand how climatic events and changes affect groundwater resources. This study focuses on characterizing and quantifying the effects of large, multiyear, quasi-decadal groundwater recharge events in the northern Utah portion of the Great Basin for the period 1960–2013. Annual groundwater level data were analyzed with climatic data to characterize climatic conditions and frequency of these large recharge events. Using observed water-level changes and multivariate analysis, five large groundwater recharge events were identified with a frequency of about 11–13 years. These events were generally characterized as having above-average annual precipitation and snow water equivalent and below-average seasonal temperatures, especially during the spring (April through June). Existing groundwater flow models for several basins within the study area were used to quantify changes in groundwater storage from these events. Simulated groundwater storage increases per basin from a single recharge event ranged from about 115 to 205 Mm3. Extrapolating these amounts over the entire northern Great Basin indicates that a single large quasi-decadal recharge event could result in billions of cubic meters of groundwater storage. Understanding the role of these large quasi-decadal recharge events in replenishing aquifers and sustaining water supplies is crucial for long-term groundwater management.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR019060","usgsCitation":"Masbruch, M.D., Rumsey, C., Gangopadhyay, S., Susong, D.D., and Pruitt, T., 2016, Analyses of infrequent (quasi-decadal) large groundwater recharge events in the northern Great Basin: Their importance for groundwater availability, use, and management: Water Resources Research, v. 52, no. 10, p. 7819-7836, https://doi.org/10.1002/2016WR019060.","productDescription":"18 p.","startPage":"7819","endPage":"7836","ipdsId":"IP-069809","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":470453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr019060","text":"Publisher Index Page"},{"id":330630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.08203125,\n 38.47939467327645\n ],\n [\n -114.08203125,\n 42.00032514831621\n ],\n [\n -109.0283203125,\n 42.00032514831621\n ],\n [\n -109.0283203125,\n 38.47939467327645\n ],\n [\n -114.08203125,\n 38.47939467327645\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"5819a9c2e4b0bb36a4c9100d","contributors":{"authors":[{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rumsey, Christine 0000-0001-7536-750X crumsey@usgs.gov","orcid":"https://orcid.org/0000-0001-7536-750X","contributorId":146240,"corporation":false,"usgs":true,"family":"Rumsey","given":"Christine","email":"crumsey@usgs.gov","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652543,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":652544,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Susong, David D. ddsusong@usgs.gov","contributorId":1040,"corporation":false,"usgs":true,"family":"Susong","given":"David","email":"ddsusong@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652545,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pruitt, Tom 0000-0002-3543-1324","orcid":"https://orcid.org/0000-0002-3543-1324","contributorId":173440,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","email":"","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":652546,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193724,"text":"70193724 - 2016 - Volcano dome dynamics at Mount St. Helens: Deformation and intermittent subsidence monitored by seismicity and camera imagery pixel offsets","interactions":[],"lastModifiedDate":"2017-11-04T13:22:46","indexId":"70193724","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Volcano dome dynamics at Mount St. Helens: Deformation and intermittent subsidence monitored by seismicity and camera imagery pixel offsets","docAbstract":"The surface deformation field measured at volcanic domes provides insights into the effects of magmatic processes, gravity- and gas-driven processes, and the development and distribution of internal dome structures. Here we study short-term dome deformation associated with earthquakes at Mount St. Helens, recorded by a permanent optical camera and seismic monitoring network. We use Digital Image Correlation (DIC) to compute the displacement field between successive images and compare the results to the occurrence and characteristics of seismic events during a 6 week period of dome growth in 2006. The results reveal that dome growth at Mount St. Helens was repeatedly interrupted by short-term meter-scale downward displacements at the dome surface, which were associated in time with low-frequency, large-magnitude seismic events followed by a tremor-like signal. The tremor was only recorded by the seismic stations closest to the dome. We find a correlation between the magnitudes of the camera-derived displacements and the spectral amplitudes of the associated tremor. We use the DIC results from two cameras and a high-resolution topographic model to derive full 3-D displacement maps, which reveals internal dome structures and the effect of the seismic activity on daily surface velocities. We postulate that the tremor is recording the gravity-driven response of the upper dome due to mechanical collapse or depressurization and fault-controlled slumping. Our results highlight the different scales and structural expressions during growth and disintegration of lava domes and the relationships between seismic and deformation signals.
","language":"English","publisher":"AGU","doi":"10.1002/2016JB013045","usgsCitation":"Salzer, J.T., Thelen, W.A., James, M.R., Walter, T.R., Moran, S.C., and Denlinger, R.P., 2016, Volcano dome dynamics at Mount St. Helens: Deformation and intermittent subsidence monitored by seismicity and camera imagery pixel offsets: Journal of Geophysical Research B: Solid Earth, v. 121, no. 11, p. 7882-7902, https://doi.org/10.1002/2016JB013045.","productDescription":"21 p.","startPage":"7882","endPage":"7902","ipdsId":"IP-079733","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470550,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jb013045","text":"Publisher Index Page"},{"id":348193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.48245239257812,\n 46.02271417608516\n ],\n [\n -121.90841674804686,\n 46.02271417608516\n ],\n [\n -121.90841674804686,\n 46.40472314125321\n ],\n [\n -122.48245239257812,\n 46.40472314125321\n ],\n [\n -122.48245239257812,\n 46.02271417608516\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-14","publicationStatus":"PW","scienceBaseUri":"59fedfb5e4b0531197b573c8","contributors":{"authors":[{"text":"Salzer, Jacqueline T.","contributorId":199801,"corporation":false,"usgs":false,"family":"Salzer","given":"Jacqueline","email":"","middleInitial":"T.","affiliations":[{"id":16947,"text":"German Research Centre for Geosciences","active":true,"usgs":false}],"preferred":false,"id":720072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thelen, Weston A. 0000-0003-2534-5577 wthelen@usgs.gov","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":4126,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","email":"wthelen@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":720071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"James, Mike R.","contributorId":199802,"corporation":false,"usgs":false,"family":"James","given":"Mike","email":"","middleInitial":"R.","affiliations":[{"id":13133,"text":"Lancaster Environment Centre, Lancaster University, Lancaster, UK","active":true,"usgs":false}],"preferred":false,"id":720073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walter, Thomas R.","contributorId":199803,"corporation":false,"usgs":false,"family":"Walter","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":16947,"text":"German Research Centre for Geosciences","active":true,"usgs":false}],"preferred":false,"id":720074,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":720075,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":720076,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70185054,"text":"70185054 - 2016 - Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios","interactions":[],"lastModifiedDate":"2017-03-13T15:11:54","indexId":"70185054","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios","docAbstract":"Complex watershed simulation models are powerful tools that can help scientists and policy-makers address challenging topics, such as land use management and water security. In the Western Lake Erie Basin (WLEB), complex hydrological models have been applied at various scales to help describe relationships between land use and water, nutrient, and sediment dynamics. This manuscript evaluated the capacity of the current Soil and Water Assessment Tool (SWAT2012) to predict hydrological and water quality processes within WLEB at the finest resolution watershed boundary unit (NHDPlus) along with the current conditions and conservation scenarios. The process based SWAT model was capable of the fine-scale computation and complex routing used in this project, as indicated by measured data at five gaging stations. The level of detail required for fine-scale spatial simulation made the use of both hard and soft data necessary in model calibration, alongside other model adaptations. Limitations to the model's predictive capacity were due to a paucity of data in the region at the NHDPlus scale rather than due to SWAT functionality. Results of treatment scenarios demonstrate variable effects of structural practices and nutrient management on sediment and nutrient loss dynamics. Targeting treatment to acres with critical outstanding conservation needs provides the largest return on investment in terms of nutrient loss reduction per dollar spent, relative to treating acres with lower inherent nutrient loss vulnerabilities. Importantly, this research raises considerations about use of models to guide land management decisions at very fine spatial scales. Decision makers using these results should be aware of data limitations that hinder fine-scale model interpretation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.06.202","usgsCitation":"Yen, H., White, M.J., Arnold, J.G., Keitzer, S.C., Johnson, M.V., Atwood, J.D., Daggupati, P., Herbert, M.E., Sowa, S.P., Ludsin, S.A., Robertson, D.M., Srinivasan, R., and Rewa, C.A., 2016, Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios: Science of the Total Environment, v. 569-570, p. 1265-1281, https://doi.org/10.1016/j.scitotenv.2016.06.202.","productDescription":"17 p.","startPage":"1265","endPage":"1281","ipdsId":"IP-075988","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":470472,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.06.202","text":"Publisher Index Page"},{"id":337455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie Basin","volume":"569-570","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7af9ee4b0849ce9795e8c","contributors":{"authors":[{"text":"Yen, Haw 0000-0002-5509-8792","orcid":"https://orcid.org/0000-0002-5509-8792","contributorId":169564,"corporation":false,"usgs":false,"family":"Yen","given":"Haw","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":684085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Michael J.","contributorId":172348,"corporation":false,"usgs":false,"family":"White","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":684087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnold, Jeffrey G.","contributorId":172345,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":684097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keitzer, S. Conor 0000-0002-8164-4099","orcid":"https://orcid.org/0000-0002-8164-4099","contributorId":189196,"corporation":false,"usgs":false,"family":"Keitzer","given":"S.","email":"","middleInitial":"Conor","affiliations":[],"preferred":false,"id":684096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Mari-Vaughn V. 0000-0002-2944-2529","orcid":"https://orcid.org/0000-0002-2944-2529","contributorId":189195,"corporation":false,"usgs":false,"family":"Johnson","given":"Mari-Vaughn","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":684095,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Atwood, Jay D.","contributorId":189194,"corporation":false,"usgs":false,"family":"Atwood","given":"Jay","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":684094,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Daggupati, Prasad 0000-0002-7044-3435","orcid":"https://orcid.org/0000-0002-7044-3435","contributorId":189193,"corporation":false,"usgs":false,"family":"Daggupati","given":"Prasad","email":"","affiliations":[],"preferred":false,"id":684093,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Herbert, Matthew E.","contributorId":189192,"corporation":false,"usgs":false,"family":"Herbert","given":"Matthew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":684092,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sowa, Scott P. 0000-0002-5425-2591 sowasp@missouri.edu","orcid":"https://orcid.org/0000-0002-5425-2591","contributorId":146672,"corporation":false,"usgs":false,"family":"Sowa","given":"Scott","email":"sowasp@missouri.edu","middleInitial":"P.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":684091,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ludsin, Stuart A. 0000-0002-3866-2216","orcid":"https://orcid.org/0000-0002-3866-2216","contributorId":175425,"corporation":false,"usgs":false,"family":"Ludsin","given":"Stuart","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":684090,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":684086,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Srinivasan, Raghavan","contributorId":189191,"corporation":false,"usgs":false,"family":"Srinivasan","given":"Raghavan","affiliations":[],"preferred":false,"id":684089,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rewa, Charles A.","contributorId":189190,"corporation":false,"usgs":false,"family":"Rewa","given":"Charles","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":684088,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70178341,"text":"70178341 - 2016 - Prediction of pesticide toxicity in Midwest streams","interactions":[],"lastModifiedDate":"2018-09-26T12:40:43","indexId":"70178341","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Prediction of pesticide toxicity in Midwest streams","docAbstract":"The occurrence of pesticide mixtures is common in stream waters of the United States, and the impact of multiple compounds on aquatic organisms is not well understood. Watershed Regressions for Pesticides (WARP) models were developed to predict Pesticide Toxicity Index (PTI) values in unmonitored streams in the Midwest and are referred to as WARP-PTI models. The PTI is a tool for assessing the relative toxicity of pesticide mixtures to fish, benthic invertebrates, and cladocera in stream water. One hundred stream sites in the Midwest were sampled weekly in May through August 2013, and the highest calculated PTI for each site was used as the WARP-PTI model response variable. Watershed characteristics that represent pesticide sources and transport were used as the WARP-PTI model explanatory variables. Three WARP-PTI models—fish, benthic invertebrates, and cladocera—were developed that include watershed characteristics describing toxicity-weighted agricultural use intensity, land use, agricultural management practices, soil properties, precipitation, and hydrologic properties. The models explained between 41 and 48% of the variability in the measured PTI values. WARP-PTI model evaluation with independent data showed reasonable performance with no clear bias. The models were applied to streams in the Midwest to demonstrate extrapolation for a regional assessment to indicate vulnerable streams and to guide more intensive monitoring.
","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2015.12.0624","usgsCitation":"Shoda, M.E., Stone, W.W., and Nowell, L.H., 2016, Prediction of pesticide toxicity in Midwest streams: Journal of Environmental Quality, v. 45, no. 6, p. 1856-1864, https://doi.org/10.2134/jeq2015.12.0624.","productDescription":"9 p.","startPage":"1856","endPage":"1864","ipdsId":"IP-064521","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":470462,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2015.12.0624","text":"Publisher Index Page"},{"id":330980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Midwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.41552734375,\n 36.65079252503471\n ],\n [\n -98.41552734375,\n 45.336701909968134\n ],\n [\n -81.71630859375,\n 45.336701909968134\n ],\n [\n -81.71630859375,\n 36.65079252503471\n ],\n [\n -98.41552734375,\n 36.65079252503471\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582adb45e4b0c253bdfff0af","contributors":{"authors":[{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":653652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":653654,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179079,"text":"70179079 - 2016 - Do rivermouths alter nutrient and seston delivery to the nearshore?","interactions":[],"lastModifiedDate":"2017-02-15T14:11:03","indexId":"70179079","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Do rivermouths alter nutrient and seston delivery to the nearshore?","docAbstract":"Sea ice dominates marine ecosystems in the Arctic, and recent reductions in sea ice may alter food webs throughout the region. Sea ice loss may also stress Pacific walruses (Odobenus rosmarus divergens), which feed on benthic macroinvertebrates in the Bering and Chukchi seas. However, no studies have examined the effects of sea ice on foraging Pacific walrus space use patterns. We tested a series of hypotheses that examined walrus foraging resource selection as a function of proximity to resting substrates and prey biomass. We quantified walrus prey biomass with 17 benthic invertebrate families, which included bivalves, polychaetes, amphipods, tunicates, and sipunculids. We included covariates for distance to sea ice and distance to land, and systematically developed a series of candidate models to examine interactions among benthic prey biomass and resting substrates. We ranked candidate models with Bayesian Information Criterion and made inferences on walrus resource selection based on the top-ranked model. Based on the top model, biomass of the bivalve family Tellinidae, distance to ice, distance to land, and the interaction of distances to ice and land all positively influenced walrus foraging resource selection. Standardized model coefficients indicated that distance to ice explained the most variation in walrus foraging resource selection followed by Tellinidae biomass. Distance to land and the interaction of distances to ice and land accounted for similar levels of variation. Tellinidae biomass likely represented an index of overall bivalve biomass, indicating walruses focused foraging in areas with elevated levels of bivalve and tellinid biomass. Our results also emphasize the importance of sea ice to walruses. Projected sea ice loss will increase the duration of the open water season in the Chukchi Sea, altering the spatial distribution of resting sites relative to current foraging areas and possibly affecting the spatial structure of benthic communities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2016.08.035","usgsCitation":"Beatty, W.S., Jay, C.V., Fischbach, A.S., Grebmeier, J.M., Taylor, R.L., Blanchard, A.L., and Jewett, S.C., 2016, Space use of a dominant Arctic vertebrate: Effects of prey, sea ice, and land on Pacific walrus resource selection: Biological Conservation, v. 203, p. 25-32, https://doi.org/10.1016/j.biocon.2016.08.035.","productDescription":"8 p.","startPage":"25","endPage":"32","ipdsId":"IP-076003","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":470455,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2016.08.035","text":"Publisher Index Page"},{"id":438517,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78G8HTX","text":"USGS data release","linkHelpText":"Walrus used and available resource units for northeast Chukchi Sea, 2008-2012"},{"id":331815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.533203125,\n 71.38514208411495\n ],\n [\n -166.904296875,\n 65.96437717203096\n ],\n [\n -177.18749999999997,\n 68.30190453001559\n ],\n [\n -167.16796875,\n 72.86793049861396\n ],\n [\n -156.533203125,\n 71.38514208411495\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"203","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"584bd0dce4b077fc20250e02","contributors":{"authors":[{"text":"Beatty, William S. 0000-0003-0013-3113 wbeatty@usgs.gov","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":173946,"corporation":false,"usgs":true,"family":"Beatty","given":"William","email":"wbeatty@usgs.gov","middleInitial":"S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":646626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":646627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":646628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grebmeier, Jacqueline M.","contributorId":48815,"corporation":false,"usgs":false,"family":"Grebmeier","given":"Jacqueline","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":646629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":646630,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blanchard, Arny L.","contributorId":173948,"corporation":false,"usgs":false,"family":"Blanchard","given":"Arny","email":"","middleInitial":"L.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":646631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jewett, Stephen C.","contributorId":94397,"corporation":false,"usgs":true,"family":"Jewett","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":646632,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192859,"text":"70192859 - 2016 - Hanson Russian River Ponds floodplain restoration: Feasibility study and conceptual design; Appendix G: Physical evaluation of the restoration alternatives","interactions":[],"lastModifiedDate":"2018-02-14T13:17:54","indexId":"70192859","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Hanson Russian River Ponds floodplain restoration: Feasibility study and conceptual design; Appendix G: Physical evaluation of the restoration alternatives","docAbstract":"Appendix G: Hanson Russian River Ponds Floodplain Restoration: Feasibility Study and Conceptual Design |G-1Appendix GPhysical Evaluation of the Restoration AlternativesRichard McDonald and Jonathan Nelson, PhDU.S. Geological Survey Geomorphology and Sediment Transport Laboratory, Golden, ColoradoIntroductionTo assess the relative and overall impacts of the scenarios proposed in Chapters 7 and 9,(Stage I-A–I-D and Stage II-A –II-E), each of the topographic configurations were evaluated over a range of flows. Thisevaluation was carried out using computational flow modeling tools available in the iRIC public-domain river modeling interface (www.i-ric.org, Nelsonet al.in press). Using the iRIC modeling tools described in more detail below, basic hydraulic computations of water-surface elevation, velocity, shear stress, and other hydraulic variables were carried out for the alternatives in the reach surrounding the project area, from the confluence of Dry Creek upstream to the Wohler road bridge downstream, for the full range of observed flows. This methodology allows comparison of the current channel configuration with the proposed alternatives in terms of inundation period and frequency, depth, water velocity, and other hydraulic information. By integrating this kind of information over the reach of interest and the flow record, critical metrics assessing the impacts of various topographic modifications can be compared to those same metrics for the existing condition or other modification scenarios. In addition, because the iRIC tools include predictions of sediment mobility, suspension of fines, and the potential evolution of the land surface in response to flow, these methods provide evaluation of sediment transport, stability of current and proposed surfaces, and evaluation of how these surfaces might evolve into the future. This hydraulic and sediment transport information is critically important for understanding theimpacts of various proposed alternatives on the physical system; perhaps even more importantly given the objectives of the proposed restoration, this information can be related to biological impacts, as is discussed in subsequent chapters of this document.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Hanson Russian River Ponds floodplain restoration: Feasibility study and conceptual design","language":"English","publisher":"California Coastal Commision","usgsCitation":"McDonald, R.R., and Nelson, J.M., 2016, Hanson Russian River Ponds floodplain restoration: Feasibility study and conceptual design; Appendix G: Physical evaluation of the restoration alternatives, chap. of Hanson Russian River Ponds floodplain restoration: Feasibility study and conceptual design, 103 p.","productDescription":"103 p.","ipdsId":"IP-067536","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":351609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee952e4b0da30c1bfc54c","contributors":{"authors":[{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":717230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":717231,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192728,"text":"70192728 - 2016 - Static and dynamic controls on fire activity at moderate spatial and temporal scales in the Alaskan boreal forest","interactions":[],"lastModifiedDate":"2017-11-08T13:37:40","indexId":"70192728","displayToPublicDate":"2016-11-01T00:00:00","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":"Static and dynamic controls on fire activity at moderate spatial and temporal scales in the Alaskan boreal forest","docAbstract":"
Wildfire, a dominant disturbance in boreal forests, is highly variable in occurrence and behavior at multiple spatiotemporal scales. New data sets provide more detailed spatial and temporal observations of active fires and the post-burn environment in Alaska. In this study, we employ some of these new data to analyze variations in fire activity by developing three explanatory models to examine the occurrence of (1) seasonal periods of elevated fire activity using the number of MODIS active fire detections data set (MCD14DL) within an 11-day moving window, (2) unburned patches within a burned area using the Monitoring Trends in Burn Severity fire severity product, and (3) short-to-moderate interval (<60 yr) fires using areas of burned area overlap in the Alaska Large Fire Database. Explanatory variables for these three models included dynamic variables that can change over the course of the fire season, such as weather and burn date, as well as static variables that remain constant over a fire season, such as topography, drainage, vegetation cover, and fire history. We found that seasonal periods of high fire activity are associated with both seasonal timing and aggregated weather conditions, as well as the landscape composition of areas that are burning. Important static inputs to the model of seasonal fire activity indicate that when fire weather conditions are suitable, areas that typically resist fire (e.g., deciduous stands) may become more vulnerable to burning and therefore less effective as fire breaks. The occurrence of short-to-moderate interval fires appears to be primarily driven by weather conditions, as these were the only relevant explanatory variables in the model. The unique importance of weather in explaining short-to-moderate interval fires implies that fire return intervals (FRIs) will be sensitive to projected climate changes in the region. Unburned patches occur most often in younger stands, which may be related to a greater deciduous fraction of vegetation as well as lower fuel loads compared with mature stands. The fraction of unburned patches may therefore increase in response to decreasing FRIs and increased deciduousness in the region, or these may decrease if fire weather conditions become more severe.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1572","usgsCitation":"Barrett, K., Loboda, T., McGuire, A.D., Genet, H., Hoy, E., and Kasischke, E., 2016, Static and dynamic controls on fire activity at moderate spatial and temporal scales in the Alaskan boreal forest: Ecosphere, v. 7, no. 11, p. 1-21, https://doi.org/10.1002/ecs2.1572.","productDescription":"e01572; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-071622","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":482070,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1572","text":"Publisher Index Page"},{"id":348461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"7","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-09","publicationStatus":"PW","scienceBaseUri":"5a0425bee4b0dc0b45b453e2","contributors":{"authors":[{"text":"Barrett, Kirsten","contributorId":26600,"corporation":false,"usgs":true,"family":"Barrett","given":"Kirsten","affiliations":[],"preferred":false,"id":721265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loboda, Tatiana","contributorId":172797,"corporation":false,"usgs":false,"family":"Loboda","given":"Tatiana","email":"","affiliations":[],"preferred":false,"id":721266,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716781,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Genet, Hélène","contributorId":195179,"corporation":false,"usgs":false,"family":"Genet","given":"Hélène","affiliations":[],"preferred":false,"id":721267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoy, Elizabeth","contributorId":200169,"corporation":false,"usgs":false,"family":"Hoy","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":721268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kasischke, Eric","contributorId":91980,"corporation":false,"usgs":true,"family":"Kasischke","given":"Eric","affiliations":[],"preferred":false,"id":721269,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}