Measurements of naturally occurring, short-lived radioisotopes from sediment cores on the Mississippi subaqueous delta have been used to infer event bed characteristics such as depositional thicknesses and accumulation rates. Specifically, the presence of Beryllium-7 (7Be) indicates recent riverine-derived terrestrial sediment deposition; while Thorium-234 (234Th) provides evidence of recent suspension in marine waters. Sediment transport models typically represent coastal flood and storm deposition via estimated grain size patterns and deposit thicknesses, however, and do not directly calculate radioisotope activities and profiles, which leads to a disconnect between the numerical model and field observations. Here, observed radioisotopic profiles from the Mississippi subaqueous delta cores were directly related to a numerical model that represented resuspension and deposition using a new approach to account for the behavior of short-lived radioisotopes. Appropriate selection of parameters such as the biodiffusion coefficient, sediment accumulation rate, and radioisotopic source terms enabled a good match between the modeled and observed cores. Comparisons of modelled profiles with geochronological analytical models that estimate accumulation rate and flood layer thickness revealed potential avenues for refining these tools, and highlight the importance of constraining the biodiffusion coefficient.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI85-092.1","usgsCitation":"Birchler, J.J., Harris, C.K., Kniskern, T.A., and Sherwood, C.R., 2018, Numerical model of geochronological tracers for deposition and reworking applied to the Mississippi subaqueous delta: Journal of Coastal Research, v. Special Issue 85, p. 456-460, https://doi.org/10.2112/SI85-092.1.","productDescription":"5 p.","startPage":"456","endPage":"460","ipdsId":"IP-092729","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468783,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2112/si85-092.1","text":"Publisher Index Page"},{"id":356848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico, Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.5,\n 28.5\n ],\n [\n -88,\n 28.5\n ],\n [\n -88,\n 30.5\n ],\n [\n -90.5,\n 30.5\n ],\n [\n -90.5,\n 28.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"Special Issue 85","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2cfe4b0702d0e842ff1","contributors":{"authors":[{"text":"Birchler, Justin J. 0000-0002-0379-2192 jbirchler@usgs.gov","orcid":"https://orcid.org/0000-0002-0379-2192","contributorId":169117,"corporation":false,"usgs":true,"family":"Birchler","given":"Justin","email":"jbirchler@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":743670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Courtney K.","contributorId":19620,"corporation":false,"usgs":false,"family":"Harris","given":"Courtney","email":"","middleInitial":"K.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":743671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kniskern, Tara A.","contributorId":207384,"corporation":false,"usgs":false,"family":"Kniskern","given":"Tara","email":"","middleInitial":"A.","affiliations":[{"id":37527,"text":"Virginia Institute of Marine Sciences, College of William & Mary","active":true,"usgs":false}],"preferred":false,"id":743672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":743673,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194712,"text":"ds1075 - 2018 - Groundwater-level data from an earthen dam site in southern Westchester County, New York","interactions":[],"lastModifiedDate":"2018-05-01T16:08:23","indexId":"ds1075","displayToPublicDate":"2018-05-01T13:45:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1075","title":"Groundwater-level data from an earthen dam site in southern Westchester County, New York","docAbstract":"In 2005, the U.S. Geological Survey began a cooperative study with New York City Department of Environmental Protection to characterize the local groundwater-flow system and identify potential sources of seeps on the southern embankment of the Hillview Reservoir in Westchester County, New York. Groundwater levels were collected at 49 wells at Hillview Reservoir, and 1 well in northern Bronx County, from April 2005 through November 2016. Groundwater levels were measured discretely with a chalked steel or electric tape, or continuously with a digital pressure transducer, or both, in accordance with U.S. Geological Survey groundwatermeasurement standards. These groundwater-level data were plotted as time series and are presented in this report as hydrographs. Twenty-eight of the 50 hydrographs have continuous record and discrete field groundwater-level measurements, 22 of the hydrographs contain only discrete measurements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1075","isbn":"978-1-4113-4200-2","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Noll, M.L., and Chu, Anthony, 2018, Groundwater-level data from an earthen dam site in southern Westchester County, New York: U.S. Geological Survey Data Series 1075, 35 p., https://doi.org/10.3133/ds1075.","productDescription":"Report: vii, 35 p.; Appendix 1","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-084388","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":351582,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1075/ds1075.pdf","text":"Report","size":"15.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1075"},{"id":351583,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1075/ds1075_app1.zip","text":"Appendix 1","size":"8.55 MB","linkHelpText":"- Groundwater-level measurements"},{"id":351581,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1075/coverthb.jpg"}],"country":"United States","state":"New York","county":"Westchester County","otherGeospatial":"Hillview Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.87460231781006,\n 40.90598813645525\n ],\n [\n -73.86430263519287,\n 40.90598813645525\n ],\n [\n -73.86430263519287,\n 40.917760911653126\n ],\n [\n -73.87460231781006,\n 40.917760911653126\n ],\n [\n -73.87460231781006,\n 40.90598813645525\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
2045 Route 112, Building 4
Coram, NY 11727
We describe a lightweight, accurate nowcasting model for electron flux levels measured by the Van Allen probes. Largely motivated by Rigler et al. (2004, https://doi.org/10.1029/2003SW000036), we turn to a time‐varying linear filter of previous flux levels and Kp. We train and test this model on data gathered from the 2.10 MeV channel of the Relativistic Electron‐Proton Telescope sensor onboard the Van Allen probes. Dynamic linear models are a specific case of state space models and can be made flexible enough to emulate the nonlinear behavior of particle fluxes within the radiation belts. Real‐time estimation of the parameters of the model is done using a Kalman filter, where the state of the model is exactly the parameters. Nowcast performance is assessed against several baseline interpolation schemes. Our model demonstrates significant improvements in performance over persistence nowcasting. In particular, during times of high geomagnetic activity, our model is able to attain performance substantially better than a persistence model. In addition, residual analysis is conducted in order to assess model fit and to suggest future improvements to the model.
","language":"English","publisher":"AGU","doi":"10.1029/2017SW001788","usgsCitation":"Coleman, T., McCollough, J.P., Young, S.L., and Rigler, E.J., 2018, Operational nowcasting of electron flux levels in the outer zone of Earth's radiation belt: Space Weather, v. 16, no. 5, p. 501-518, https://doi.org/10.1029/2017SW001788.","productDescription":"18 p.","startPage":"501","endPage":"518","ipdsId":"IP-096545","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":361501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Coleman, Tim","contributorId":213545,"corporation":false,"usgs":false,"family":"Coleman","given":"Tim","email":"","affiliations":[],"preferred":false,"id":757979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCollough, James P.","contributorId":204030,"corporation":false,"usgs":false,"family":"McCollough","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":757980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Shawn L.","contributorId":204031,"corporation":false,"usgs":false,"family":"Young","given":"Shawn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":757981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":757982,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201557,"text":"70201557 - 2018 - Multi-year high-frequency hydrothermal monitoring of selected high-threat Cascade Range volcanoes","interactions":[],"lastModifiedDate":"2018-12-18T12:46:20","indexId":"70201557","displayToPublicDate":"2018-05-01T12:46:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Multi-year high-frequency hydrothermal monitoring of selected high-threat Cascade Range volcanoes","docAbstract":"From 2009 to 2015 the U.S. Geological Survey (USGS) systematically monitored hydrothermal behavior at selected Cascade Range volcanoes in order to define baseline hydrothermal and geochemical conditions. Gas and water data were collected regularly at 25 sites on 10 of the highest-risk volcanoes in the Cascade Range. These sites include near-summit fumarole groups and springs/streams that show clear evidence of magmatic influence (high 3He/4He ratios and/or large fluxes of magmatic CO2 or heat). Site records consist mainly of hourly temperature and hydrothermal-flux data. Having established baseline conditions during a multiyear quiescent period, the USGS reduced monitoring frequency from 2015 to present. The archived monitoring data are housed at (doi:10.5066/F72N5088). These data (1) are suitable for retrospective comparison with other continuous geophysical monitoring data and (2) will provide context during future episodes of volcanic unrest, such that unrest-related variations at these thoroughly characterized sites will be more clearly recognizable. Relatively high-frequency year-round data are essential to achieve these objectives, because many of the time series reveal significant diurnal, seasonal, and inter-annual variability that would tend to mask unrest signals in the absence of baseline data. Here we characterize normal variability for each site, suggest strategies to detect future volcanic unrest, and explore deviations from background associated with recent unrest.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2018.02.014","usgsCitation":"Crankshaw, I., Archfield, S.A., Newman, A.C., Bergfeld, D., Clor, L., Kelly, P.J., Evans, W.C., Spicer, K.R., and Ingebritsen, S.E., 2018, Multi-year high-frequency hydrothermal monitoring of selected high-threat Cascade Range volcanoes: Journal of Volcanology and Geothermal Research, v. 356, p. 24-35, https://doi.org/10.1016/j.jvolgeores.2018.02.014.","productDescription":"12 p.","startPage":"24","endPage":"35","ipdsId":"IP-091030","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468784,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2018.02.014","text":"Publisher Index Page"},{"id":360459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Cascades Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124,\n 40\n ],\n [\n -120,\n 40\n ],\n [\n -120,\n 49\n ],\n [\n -124,\n 49\n ],\n [\n -124,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"356","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1a1534e4b0708288c2353b","contributors":{"authors":[{"text":"Crankshaw, I.M. 0000-0003-0736-5478","orcid":"https://orcid.org/0000-0003-0736-5478","contributorId":211588,"corporation":false,"usgs":false,"family":"Crankshaw","given":"I.M.","email":"","affiliations":[{"id":17863,"text":"Sonoma County Water Agency","active":true,"usgs":false}],"preferred":false,"id":754436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":754438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newman, A. C. 0000-0001-6621-2717","orcid":"https://orcid.org/0000-0001-6621-2717","contributorId":211589,"corporation":false,"usgs":false,"family":"Newman","given":"A.","email":"","middleInitial":"C.","affiliations":[{"id":38269,"text":"Aarhus, Denmark","active":true,"usgs":false}],"preferred":false,"id":754437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergfeld, Deborah 0000-0003-4570-7627 dbergfel@usgs.gov","orcid":"https://orcid.org/0000-0003-4570-7627","contributorId":152531,"corporation":false,"usgs":true,"family":"Bergfeld","given":"Deborah","email":"dbergfel@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":754439,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clor, Laura E. 0000-0003-2633-5100","orcid":"https://orcid.org/0000-0003-2633-5100","contributorId":209969,"corporation":false,"usgs":true,"family":"Clor","given":"Laura E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":754440,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754540,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":754539,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":754441,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":754435,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70197548,"text":"70197548 - 2018 - Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS","interactions":[],"lastModifiedDate":"2018-09-26T12:40:44","indexId":"70197548","displayToPublicDate":"2018-05-01T12:40:37","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS","docAbstract":"On the open coast, flooding is largely driven by tides, storm surge, waves, and in areas near coastal inlets, the magnitude and co-occurrence of high fluvial discharges. Statistical methods are typically used to estimate the individual probability of coastal storm and fluvial discharge occurrences for use in sophisticated flood hazard models. A challenge arises when considering possible future climate changes and the relation between the intensity of extreme coastal water levels and high fluvial discharges.
In this study, the Coastal Storm Modeling System (CoSMoS) is used to dynamically downscale global climate projections to local-scale storm-driven coastal water levels, including associated fluvial discharges. An efficient approach to derive 21st century projected fluvial discharges for rivers within San Francisco Bay was developed, leveraging a readily-available time-series of projected (2010 – 2100) discharge rates of the predominant river system (the “Delta”). Delta projections were used to estimate flow rates of 8 Bay rivers for the IPCC's CMIP5 RCP4.5 climate scenario. Relationships describing discharge rates, normalized by respective watershed areas, were developed and applied to projected data to generate 21st century fluvial discharge time-series for each river. Results indicate decreasing discharge rates throughout the 21st century with the exception of extreme flows.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI85-159.1","usgsCitation":"Erikson, L.H., O'Neill, A., and Barnard, P., 2018, Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS: Journal of Coastal Research, v. Special Issue No. 85, p. 791-795, https://doi.org/10.2112/SI85-159.1.","productDescription":"5 p.","startPage":"791","endPage":"795","ipdsId":"IP-092829","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":357779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.387451171875,\n 36.94989178681327\n ],\n [\n -121.201171875,\n 36.94989178681327\n ],\n [\n -121.201171875,\n 38.565347844885466\n ],\n [\n -123.387451171875,\n 38.565347844885466\n ],\n [\n -123.387451171875,\n 36.94989178681327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"Special Issue No. 85","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02ff9e4b0fc368eb539b6","contributors":{"authors":[{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":737616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Neill, Andrea C. 0000-0003-1656-4372 aoneill@usgs.gov","orcid":"https://orcid.org/0000-0003-1656-4372","contributorId":5351,"corporation":false,"usgs":true,"family":"O'Neill","given":"Andrea C.","email":"aoneill@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":737617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746347,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201554,"text":"70201554 - 2018 - Atmospheric and surface climate associated with 1986–2013 wildfires in North America","interactions":[],"lastModifiedDate":"2018-12-18T12:39:58","indexId":"70201554","displayToPublicDate":"2018-05-01T12:40:05","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric and surface climate associated with 1986–2013 wildfires in North America","docAbstract":"We analyze climate simulations conducted with the RegCM3 regional climate model on 50‐ and 15‐km model grids to diagnose the dependence of wildfire incidence and area burned variations on monthly climate long‐term means and anomalies over North America for the period 1986–2013. We created a new wildfire database by merging the Fire Program Analysis Fire‐Occurrence Database, the National Interagency Fire Center Fire History Data, and the Canadian National Fire Database. The database includes 2,083,865 daily fire starts that burned a total of 1.25 × 108 ha in North America. We derive long‐term climatologies, standardized gamma indices, and composite climate anomalies of atmospheric circulation (500‐hPa height and wind) and various surface fields (e.g., solar radiation, soil moisture, vapor pressure deficit, and latent and sensible heat fluxes) to illustrate the climatology of burned area. The immediate and lagged monthly atmospheric circulation and surface climate anomalies differentiate high‐ and low‐fire years and the role of El Niño–Southern Oscillation in wildfire occurrence. Our approach demonstrates the association of the seasonal cycles of wildfire and climate and the strong role of climatic variability in modulating the seasonal cycle as a control of wildfire on monthly time scales.
","language":"English","publisher":"AGU","doi":"10.1029/2017JG004195","usgsCitation":"Hostetler, S.W., Bartlein, P.J., and Alder, J.R., 2018, Atmospheric and surface climate associated with 1986–2013 wildfires in North America: Journal of Geophysical Research: Biogeosciences, v. 123, no. 5, p. 1588-1609, https://doi.org/10.1029/2017JG004195.","productDescription":"22 p.","startPage":"1588","endPage":"1609","ipdsId":"IP-090909","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468785,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jg004195","text":"Publisher Index Page"},{"id":360457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-16","publicationStatus":"PW","scienceBaseUri":"5c1a1534e4b0708288c2353e","contributors":{"authors":[{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":754432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartlein, Patrick J. 0000-0001-7657-5685","orcid":"https://orcid.org/0000-0001-7657-5685","contributorId":211587,"corporation":false,"usgs":false,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":33397,"text":"U of Oregon","active":true,"usgs":false}],"preferred":false,"id":754433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":754434,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198040,"text":"70198040 - 2018 - Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions","interactions":[],"lastModifiedDate":"2018-08-07T12:07:51","indexId":"70198040","displayToPublicDate":"2018-05-01T12:07:45","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions","docAbstract":"Enhanced reservoir connectivity generally requires maximizing the intersection between hydraulic fracture (HF) and preexisting underground natural fractures (NF), while having the hydraulic fracture cross the natural fractures (and not arrest). We have studied the interaction between a hydraulic fracture and a polished saw-cut fault. The experiments include a hydraulic fracture initiating from a pressurized axial borehole (using water) that approaches a dry fault that is inclined at an angle θ with respect to the borehole axis. The experiments are conducted on Poly(methyl) Meta Acrylate (PMMA) and Solnhofen limestone, a finely grained (<5 μm grain), low permeability (<10 nD) carbonate. The confining pressure in all experiments is 5 MPa, while the differential stress (1-80 MPa) and approach angle, θ (30, 45, 60, 90°) are experimental variables. During the hydraulic fracture, acoustic emissions (AE), slip velocity, slip magnitude, stress drop and pore pressure are recorded at a 5 MHz sampling rate. A Doppler laser vibrometer measures piston velocity outside the pressure vessel to infer fault slip duration and a strain gauge adjacent to the saw-cut provides a near-field measure of axial stress.
For PMMA, the coefficient of friction was 0.30 and sliding was unstable (stick-slip). The approaching HF in PMMA created a tensile fracture detected by AE transducers ~100 μs before the significant stick-slip event (45% stress drop and slip velocity of ~60 mm/s) and was arrested by the fault at all fault orientations and differential stresses, even at 90° fault orientation and 80 MPa differential stress. For Solnhofen limestone, we observed stable sliding at a coefficient of friction of 0.12. In contrast to PMMA, the HF in Solnhofen consistently crossed to the other side of the fault. When the HF crossed the fault, it produced a small stress drop (<10%) and slip velocity of only 0.5 mm/s. Theoretical models by Blanton (1986) and Renshaw and Pollard (1995) predict that HF will be arrested for Solnhofen limestone and cross PMMA 90° fault at 80 MPa differential stress. Although the exact cause for the discrepancy between experiments and the theory is not known, one feature present in the experiments but not considered in the models, is the diffusion of fluid driven by the fault slip. Thus, the formation of a \"fluid-filled patch\" on the fault surface as it is intersected by the HF may substantially impact the crossing/arrest behavior. The approach angle and differential stress also influence the HF initiation azimuth and breakdown pressure. In most cases, the HF initiation azimuth was normal to the fault strike. These observations suggest that the presence of natural fractures could result in rotation of hydraulic fractures to be more normal to their strike and a subsequent change in the downhole pressure recordings. The latter could be used as a diagnostic tool for predicting this interaction.
","largerWorkTitle":"SPE Hydraulic Fracturing Technology Conference and Exhibition","conferenceTitle":"SPE Hydraulic Fracturing Technology Conference and Exhibition","conferenceDate":"January 23-25, 2018","conferenceLocation":"The Woodlands, TX","language":"English","publisher":"Society of Petroleum Engineers","doi":"10.2118/189901-MS","usgsCitation":"Mighani, S., Lockner, D.A., Kilgore, B.D., Sheibani, F., and Evans, B., 2018, Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions, in SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, TX, January 23-25, 2018, 26 p., https://doi.org/10.2118/189901-MS.","productDescription":"26 p.","ipdsId":"IP-095560","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":437926,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQOE6D","text":"USGS data release","linkHelpText":"Data Release for "Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions""},{"id":356278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-23","publicationStatus":"PW","scienceBaseUri":"5b6fc45ce4b0f5d57878ea61","contributors":{"authors":[{"text":"Mighani, Saied","contributorId":206821,"corporation":false,"usgs":false,"family":"Mighani","given":"Saied","email":"","affiliations":[],"preferred":false,"id":741866,"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":741867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kilgore, Brian D. 0000-0003-0530-7979 bkilgore@usgs.gov","orcid":"https://orcid.org/0000-0003-0530-7979","contributorId":3887,"corporation":false,"usgs":true,"family":"Kilgore","given":"Brian","email":"bkilgore@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":741868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sheibani, Farrokh 0000-0002-5105-4792","orcid":"https://orcid.org/0000-0002-5105-4792","contributorId":205992,"corporation":false,"usgs":false,"family":"Sheibani","given":"Farrokh","email":"","affiliations":[{"id":37205,"text":"Post-Doctoral researcher at M.I.T. Cambridge MA","active":true,"usgs":false}],"preferred":false,"id":741869,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evans, Brian 0000-0003-0324-0969","orcid":"https://orcid.org/0000-0003-0324-0969","contributorId":205993,"corporation":false,"usgs":false,"family":"Evans","given":"Brian","email":"","affiliations":[{"id":37206,"text":"Professor, Massachusetts Institute of Technology: Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":741870,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200075,"text":"70200075 - 2018 - Identifying and eliminating sources of recreational water quality degradation along an urban coast","interactions":[],"lastModifiedDate":"2018-10-11T10:48:41","indexId":"70200075","displayToPublicDate":"2018-05-01T10:48:35","publicationYear":"2018","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":"Identifying and eliminating sources of recreational water quality degradation along an urban coast","docAbstract":"Restoration of highly degraded urban coastal waters often requires large-scale, complex projects, but in the interim, smaller-scale efforts can provide immediate improvements to water quality conditions for visitor use. We examined short-term efforts to improve recreational water quality near the Grand Calumet River (GC) in the Laurentian Great Lakes. Identified as an Area of Concern (AOC) by the International Joint Commission, the GC has experienced years of industrial and municipal waste discharges, and as a result, coastal beaches have some of the highest rates of beach closings (>70%) in the United States. Project objectives were to identify sources of microbial contamination and to evaluate a short-term management solution to decrease beach closings: during 2015 (partial) and 2016 (season-long), canines were used to deter gull presence. Water samples were analyzed for Escherichia coli in 2015 and 2016, and fecal sources were evaluated using microbial source tracking markers (2015): human (Bacteroides HF183, Methanobrevibacter nifH), gull (Gull2), and dog (DogBact). Hydrometeorological conditions were simultaneously measured. Results indicated that human, gull, and canine fecal sources were present, with gulls being the dominant source. Escherichia coli densities were highly correlated with number of gulls present, Gull2 marker, and turbidity. Gull deterrence decreased E. coli and Gull2 marker detection during 2015, but numbers rebounded after program completion. The full-season program in 2016 resulted in lower E. coli densities and fewer beach closings. Large-scale restoration efforts are underway at this location, but short-term, small-scale projects can be useful for reducing beach closings and restoring ecosystem services.
","language":"English","publisher":"American Society of Agronomy, Crop Science Society of America, Soil Science Society of America","doi":"10.2134/jeq2017.11.0461","usgsCitation":"Nevers, M., Byappanahalli, M., Shively, D., Buszka, P.M., Jackson, P.R., and Phanikumar, M.S., 2018, Identifying and eliminating sources of recreational water quality degradation along an urban coast: Journal of Environmental Quality, v. 47, no. 5, p. 1042-1050, https://doi.org/10.2134/jeq2017.11.0461.","productDescription":"9 p.","startPage":"1042","endPage":"1050","ipdsId":"IP-092824","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":437928,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M8Y8F3","text":"USGS data release","linkHelpText":"Identify sources of high E. coli concentrations, Grand Calumet River Area of Concern beaches of southern Lake Michigan, 2016-2018"},{"id":437927,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H70F3D","text":"USGS data release","linkHelpText":"Identify sources of high E. coli concentrations, beaches of southern Lake Michigan, 2015, (version 2.0, July 2020)"},{"id":358271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.52464294433594,\n 41.580525125613846\n ],\n [\n -87.24655151367188,\n 41.580525125613846\n ],\n [\n -87.24655151367188,\n 41.72725537359254\n ],\n [\n -87.52464294433594,\n 41.72725537359254\n ],\n [\n -87.52464294433594,\n 41.580525125613846\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02ff9e4b0fc368eb539b8","contributors":{"authors":[{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":748279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":748280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shively, Dawn 0000-0002-6119-924X dshively@usgs.gov","orcid":"https://orcid.org/0000-0002-6119-924X","contributorId":201533,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":748281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buszka, Paul M. 0000-0001-8218-826X pmbuszka@usgs.gov","orcid":"https://orcid.org/0000-0001-8218-826X","contributorId":1786,"corporation":false,"usgs":true,"family":"Buszka","given":"Paul","email":"pmbuszka@usgs.gov","middleInitial":"M.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748283,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Phanikumar, Mantha S.","contributorId":208872,"corporation":false,"usgs":false,"family":"Phanikumar","given":"Mantha","email":"","middleInitial":"S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":748284,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199214,"text":"70199214 - 2018 - The influence of sea level rise on the regional interdependence of coastal infrastructure","interactions":[],"lastModifiedDate":"2018-09-11T10:18:00","indexId":"70199214","displayToPublicDate":"2018-05-01T10:17:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"The influence of sea level rise on the regional interdependence of coastal infrastructure","docAbstract":"Sea level rise (SLR) is placing both immediate and long‐term pressures on coastal communities to take protective actions. Projects in the United States, and in many locations throughout the world, generally involve local jurisdictions raising the elevation of shoreline protection elements, with limited or no analysis of the feedback between shoreline management decisions and the impacts to water levels regionally. Our study examines the impact of local shoreline development on regional flood risk and considers SLR scenarios up to 1.5 m using a large‐scale numerical model, as an example, for San Francisco Bay. Here we show that measures to prevent flooding along an embayment shoreline in one location or subregion may increase inundation elsewhere in the system. The network of interactions occurs not only within subbasins of the Bay but also across the greater geographic extent from one end of the Bay to the other, and local jurisdiction may have either reciprocal relationships with or asymmetric impacts on one other. Importantly, the nature of the interaction network is seen to evolve with SLR: interactions are purely subregional at current sea level but with higher sea level (e.g., 1 m of SLR), not only do the subregional interdependencies strengthen but also regional interdependences emerge.
","language":"English","publisher":"AGU","doi":"10.1002/2017EF000742","usgsCitation":"Wang, R., Stacey, M., Herdman, L.M., Barnard, P., and Erikson, L.H., 2018, The influence of sea level rise on the regional interdependence of coastal infrastructure: Earth's Future, v. 6, no. 5, p. 677-688, https://doi.org/10.1002/2017EF000742.","productDescription":"12 p.","startPage":"677","endPage":"688","ipdsId":"IP-086793","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468786,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017ef000742","text":"Publisher Index Page"},{"id":357219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.67333984374999,\n 37.391981943533544\n ],\n [\n -121.75872802734375,\n 37.391981943533544\n ],\n [\n -121.75872802734375,\n 38.26406296833961\n ],\n [\n -122.67333984374999,\n 38.26406296833961\n ],\n [\n -122.67333984374999,\n 37.391981943533544\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-02","publicationStatus":"PW","scienceBaseUri":"5b98a2cfe4b0702d0e842ff3","contributors":{"authors":[{"text":"Wang, Ruo-Quian","contributorId":206190,"corporation":false,"usgs":false,"family":"Wang","given":"Ruo-Quian","email":"","affiliations":[{"id":37278,"text":"University of Dundee","active":true,"usgs":false}],"preferred":false,"id":744708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stacey, Mark T.","contributorId":94531,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark T.","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":744709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":744707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":744710,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":744711,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227668,"text":"70227668 - 2018 - Effects of water-level management and hatchery supplementation on kokanee recruitment in Lake Pend Oreille, Idaho","interactions":[],"lastModifiedDate":"2022-01-26T15:33:15.901065","indexId":"70227668","displayToPublicDate":"2018-05-01T09:31:59","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Effects of water-level management and hatchery supplementation on kokanee recruitment in Lake Pend Oreille, Idaho","docAbstract":"Resource managers have been attempting to recover the kokanee (Oncorhynchus nerka) population in Lake Pend Oreille, Idaho for more than three decades using an annual stocking program and an experimental water-level management strategy. This study evaluated the effect of both management actions on kokanee recruitment. A bootstrap-based generalized Ricker model was used to test if wild kokanee recruitment was significantly influenced by water-level management, while accounting for error due to sampling variability and differential survival of wild- and hatchery-origin fish within age-classes. Wild kokanee exhibited a compensatory stock-recruitment relationship, whereas hatchery recruitment was positively and linearly related to stocking. The model did not identify a significant relationship between water level and wild kokanee recruitment. Density dependence and variable stocking appeared to explain the synchronized and cyclic recruitment of wild and hatchery fry.
","language":"English","publisher":"Washington State University Press","doi":"10.3955/046.092.0206","usgsCitation":"Whitlock, S., Quist, M.C., and Dux, A.M., 2018, Effects of water-level management and hatchery supplementation on kokanee recruitment in Lake Pend Oreille, Idaho, v. 92, no. 2, p. 136-148, https://doi.org/10.3955/046.092.0206.","productDescription":"13 p.","startPage":"136","endPage":"148","ipdsId":"IP-053519","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":394866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Lake Pend Oreille","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.69677734375,\n 47.93934692855592\n ],\n [\n -116.19415283203125,\n 47.93934692855592\n ],\n [\n -116.19415283203125,\n 48.32612605157941\n ],\n [\n -116.69677734375,\n 48.32612605157941\n ],\n [\n -116.69677734375,\n 47.93934692855592\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"92","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Whitlock, Steven L.","contributorId":267708,"corporation":false,"usgs":false,"family":"Whitlock","given":"Steven L.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":831780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":831668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dux, Andrew M.","contributorId":212798,"corporation":false,"usgs":false,"family":"Dux","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":831781,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236152,"text":"70236152 - 2018 - Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States","interactions":[],"lastModifiedDate":"2022-08-30T14:26:41.124038","indexId":"70236152","displayToPublicDate":"2018-05-01T09:19:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States","docAbstract":"Winter snowfall and accumulation is an important component of the surface water supply in the western United States. In these areas, increasing winter temperatures T associated with global warming can influence the amount of winter precipitation P that falls as snow S. In this study we examine long-term trends in the fraction of winter P that falls as S (Sfrac) for 175 hydrologic units (HUs) in snow-covered areas of the western United States for the period 1951–2014. Because S is a substantial contributor to runoff R across most of the western United States, we also examine long-term trends in water-year runoff efficiency [computed as water-year R/water-year P (Reff)] for the same 175 HUs. In that most S records are short in length, we use model-simulated S and R from a monthly water balance model. Results for Sfrac indicate long-term negative trends for most of the 175 HUs, with negative trends for 139 (~79%) of the HUs being statistically significant at a 95% confidence level (p = 0.05). Additionally, results indicate that the long-term negative trends in Sfrac have been largely driven by increases in T. In contrast, time series of Reff for the 175 HUs indicate a mix of positive and negative long-term trends, with few trends being statistically significant (at p = 0.05). Although there has been a notable shift in the timing of R to earlier in the year for most HUs, there have not been substantial decreases in water-year R for the 175 HUs.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-17-0227.1","usgsCitation":"McCabe, G.J., Wolock, D.M., and Valentin, M., 2018, Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States: Journal of Hydrometeorology, v. 19, p. 803-814, https://doi.org/10.1175/JHM-D-17-0227.1.","productDescription":"12 p.","startPage":"803","endPage":"814","ipdsId":"IP-080058","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":468787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-17-0227.1","text":"Publisher Index Page"},{"id":405909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.7734375,\n 32.39851580247402\n ],\n [\n -107.70996093749999,\n 31.840232667909365\n ],\n [\n -106.69921875,\n 33.394759218577995\n ],\n [\n -106.4794921875,\n 35.209721645221386\n ],\n [\n -104.67773437499999,\n 35.92464453144099\n ],\n [\n -104.7216796875,\n 37.64903402157866\n ],\n [\n -104.5458984375,\n 38.89103282648846\n ],\n [\n -104.94140625,\n 39.80853604144591\n ],\n [\n -104.80957031249999,\n 40.48038142908172\n ],\n [\n -105.64453124999999,\n 41.343824581185686\n ],\n [\n -104.94140625,\n 42.19596877629178\n ],\n [\n -106.787109375,\n 43.35713822211053\n ],\n [\n -106.6552734375,\n 44.308126684886126\n ],\n [\n -107.9296875,\n 45.36758436884978\n ],\n [\n -110.25878906249999,\n 45.85941212790755\n ],\n [\n -111.09374999999999,\n 46.76996843356982\n ],\n [\n -112.67578124999999,\n 47.66538735632654\n ],\n [\n -113.51074218749999,\n 49.06666839558117\n ],\n [\n -123.53027343749999,\n 49.06666839558117\n ],\n [\n -123.26660156249999,\n 48.37084770238366\n ],\n [\n -125.3759765625,\n 48.60385760823255\n ],\n [\n -124.4091796875,\n 45.336701909968134\n ],\n [\n -124.93652343749999,\n 43.004647127794435\n ],\n [\n -124.76074218749999,\n 40.38002840251183\n ],\n [\n -124.18945312500001,\n 38.75408327579141\n ],\n [\n -122.3876953125,\n 36.35052700542763\n ],\n [\n -120.9375,\n 34.19817309627726\n ],\n [\n -117.7734375,\n 32.39851580247402\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2018-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valentin, Melissa","contributorId":202218,"corporation":false,"usgs":false,"family":"Valentin","given":"Melissa","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":850264,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200606,"text":"70200606 - 2018 - Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU","interactions":[],"lastModifiedDate":"2018-11-21T09:14:01","indexId":"70200606","displayToPublicDate":"2018-05-01T09:13:26","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU","docAbstract":"The portion of the Snake River fall Chinook Salmon Oncorhynchus tshawytscha ESU that spawns upstream of Lower Granite Dam transitioned from low to high abundance during 1992–2017 in association with U.S. Endangered Species Act recovery efforts and other federally mandated actions. This annual report focuses on (1) numeric and habitat use responses by natural- and hatchery-origin spawners, (2) phenotypic and numeric responses by natural-origin juveniles, (3) USGS use of a small unmanned aerial system (sUAS) to search for fall Chinook salmon redds and carcasses, and (4) the detection of 8-mm PIT tags at Lower Granite Dam. Spawners have located and used most of the available spawning habitat and that habitat is gradually approaching redd capacity. Timing of spawning and fry emergence has been relatively stable; whereas the timing of parr dispersal from riverine rearing habitat into Lower Granite Reservoir has become earlier as apparent abundance of juveniles has increased. Growth rate (g/d) and dispersal size of parr also declined as apparent abundance of juveniles increased. Passage timing of smolts from the two Snake River reaches has become earlier and downstream movement rate faster as estimated abundance of fall Chinook Salmon smolts in Lower Granite Reservoir has increased. These findings coupled with stock-recruitment analyses presented in this report provide evidence for density-dependence in the Snake River reaches and in Lower Granite Reservoir that was influenced by the expansion of the recovery program. The long-term goal is to use the information covered here in a comprehensive modeling effort to conduct action effectiveness and uncertainty research and to inform Fish Population, Hydrosystem, Harvest, Hatchery, and Predation and Invasive Species Management RM&E.\n\nIn 2017, the USGS searched 15 shallow water spawning sites in conjunction with the Idaho Power Company (IPC). Redd counts agreed with those of IPC for a little more than half the sites suggesting that we need more training in redd counting. We recovered 67 carcasses, and tissue samples are currently being analyzed for parentage to ultimately determine the percentage of hatchery-origin spawners on the spawning grounds. Redd fading was examined to determine the frequency at which aerial surveys should be conducted. Most redds surveyed through time were visible for at least 4 weeks after the redd was initially constructed. Redd fading was variable amongst sites and depended on location.\n\nIn 2017, we conducted a second year of evaluating detection efficiency of 8-mm PIT tags in the Lower Granite Dam juvenile fish collection system. Groups of 75–78 fish were tagged\nwith 8-mm Biomark, 8-mm Oregon RFID, 9-mm Biomark, and 12-mm Biomark PIT tags and released into the bypass upstream of the upwell. From 97.4 to 100% (depending on tag type) of tagged fish were detected on at least one antenna in the Lower Granite Dam bypass system. Mean detection efficiency within the predominant passage route (i.e., diversion river exit) exceeded 0.98 for all tag types in both years. These results suggest that fish tagged in the field with 8-mm PIT tags should be detected at rates similar to larger tags at main-stem hydroelectric dams.","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Tiffan, K., Plumb, J.M., Perry, R.W., Erhardt, J., Hemingway, R.J., Bickford, B., Rhodes, T., Connor, W., and Mullins, F.L., 2018, Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU, 67 p.","productDescription":"67 p.","ipdsId":"IP-097295","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":359627,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358776,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/DocumentViewer/P160478/75986-1.pdf"}],"country":"United States","otherGeospatial":"Snake River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.35546875000001,\n 44.715513732021336\n ],\n [\n -114.6478271484375,\n 44.715513732021336\n ],\n [\n -114.6478271484375,\n 47.10378387099161\n ],\n [\n -119.35546875000001,\n 47.10378387099161\n ],\n [\n -119.35546875000001,\n 44.715513732021336\n ]\n ]\n ]\n }\n }\n ]\n}","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bf67cf5e4b045bfcae2cffe","contributors":{"authors":[{"text":"Tiffan, Kenneth 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":210058,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":751889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":751890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erhardt, John 0000-0002-5170-285X jerhardt@usgs.gov","orcid":"https://orcid.org/0000-0002-5170-285X","contributorId":210059,"corporation":false,"usgs":true,"family":"Erhardt","given":"John","email":"jerhardt@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749720,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hemingway, Rulon J. 0000-0001-8143-0325 rhemingway@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-0325","contributorId":194697,"corporation":false,"usgs":true,"family":"Hemingway","given":"Rulon","email":"rhemingway@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":751891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bickford, Brad 0000-0003-3756-6588 bbickford@usgs.gov","orcid":"https://orcid.org/0000-0003-3756-6588","contributorId":210056,"corporation":false,"usgs":true,"family":"Bickford","given":"Brad","email":"bbickford@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749717,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rhodes, Tobyn N. 0000-0002-4023-4827","orcid":"https://orcid.org/0000-0002-4023-4827","contributorId":210057,"corporation":false,"usgs":true,"family":"Rhodes","given":"Tobyn N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749718,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Connor, William P.","contributorId":115438,"corporation":false,"usgs":true,"family":"Connor","given":"William P.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID 83544","active":true,"usgs":false}],"preferred":false,"id":751892,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mullins, Frank L.","contributorId":146343,"corporation":false,"usgs":false,"family":"Mullins","given":"Frank","email":"","middleInitial":"L.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID 83544","active":true,"usgs":false}],"preferred":false,"id":751893,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198860,"text":"70198860 - 2018 - Wetlands receiving water treated with coagulants improve water quality by removing dissolved organic carbon and disinfection byproduct precursors","interactions":[],"lastModifiedDate":"2018-08-24T12:12:27","indexId":"70198860","displayToPublicDate":"2018-05-01T07:55:36","publicationYear":"2018","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":"Wetlands receiving water treated with coagulants improve water quality by removing dissolved organic carbon and disinfection byproduct precursors","docAbstract":"
Constructed wetlands are used worldwide to improve water quality while also providing critical wetland habitat. However, wetlands have the potential to negatively impact drinking water quality by exporting dissolved organic carbon (DOC) that upon disinfection can form disinfection byproducts (DBPs) like trihalomethanes (THMs) and haloacetic acids (HAAs). We used a replicated field-scale study located on organic rich soils in California's Sacramento-San Joaquin Delta to test whether constructed flow-through wetlands which receive water high in DOC that is treated with either iron- or aluminum-based coagulants can improve water quality with respect to DBP formation. Coagulation alone removed DOC (66–77%) and THM (67–70%) precursors, and was even more effective at removing HAA precursors (77–90%). Passage of water through the wetlands increased DOC concentrations (1.5–7.5 mg L− 1), particularly during the warmer summer months, thereby reversing some of the benefits from coagulant addition. Despite this addition, water exiting the wetlands treated with coagulants had lower DOC and DBP precursor concentrations relative to untreated source water. Benefits of the coagulation-wetland systems were greatest during the winter months (approx. 50–70% reduction in DOC and DBP precursor concentrations) when inflow water DOC concentrations were higher and wetland DOC production was lower. Optical properties suggest DOC in this system is predominantly comprised of high molecular weight, aromatic compounds, likely derived from degraded peat soils.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.11.205","usgsCitation":"Hansen, A., Kraus, T.E., Bachand, S.M., Horwath, W.R., and Bachand, P., 2018, Wetlands receiving water treated with coagulants improve water quality by removing dissolved organic carbon and disinfection byproduct precursors: Science of the Total Environment, v. 622-623, p. 603-613, https://doi.org/10.1016/j.scitotenv.2017.11.205.","productDescription":"11 p.","startPage":"603","endPage":"613","ipdsId":"IP-084915","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":468789,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2017.11.205","text":"Publisher Index Page"},{"id":356678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"622-623","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2d0e4b0702d0e842ff5","contributors":{"authors":[{"text":"Hansen, Angela M. 0000-0003-0938-7611","orcid":"https://orcid.org/0000-0003-0938-7611","contributorId":204702,"corporation":false,"usgs":true,"family":"Hansen","given":"Angela M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bachand, Sandra M.","contributorId":147304,"corporation":false,"usgs":false,"family":"Bachand","given":"Sandra","email":"","middleInitial":"M.","affiliations":[{"id":12526,"text":"Bachand & Associates","active":true,"usgs":false}],"preferred":false,"id":743116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horwath, William R.","contributorId":147305,"corporation":false,"usgs":false,"family":"Horwath","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":7246,"text":"University of California, Davis, CA, USA","active":true,"usgs":false}],"preferred":false,"id":743118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bachand, Philip","contributorId":81013,"corporation":false,"usgs":false,"family":"Bachand","given":"Philip","email":"","affiliations":[{"id":12526,"text":"Bachand & Associates","active":true,"usgs":false}],"preferred":false,"id":743117,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216330,"text":"70216330 - 2018 - Genetic structure in Elk persists after translocation","interactions":[],"lastModifiedDate":"2020-11-12T13:47:07.095085","indexId":"70216330","displayToPublicDate":"2018-05-01T07:43:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Genetic structure in Elk persists after translocation","docAbstract":"Elk (Cervus canadensis) translocation success is thought to be facilitated by high post‐release herd cohesion and limited movements; both should ensure genetic mixing following release. Such mixing is important to reduce potential effects of inbreeding or genetic drift, which can be especially important in small founding populations. We had a natural experiment where we could evaluate genetic mixing of 2 distinct lineages of elk after translocation to the same area. Founding elk ultimately came from north and south of a road barrier at Elk Island National Park (EINPN or EINPS, respectively), Alberta, Canada and the 2 groups were genetically distinct. During 2000 to 2003, elk originating from Elk Island National Park were translocated to Cumberland Mountains, Tennessee (TNCM) and Great Smoky Mountains National Park, North Carolina (GSMNP), USA (some elk spent time at Land Between the Lakes Recreation Area, Kentucky, USA, before their final translocation). At TNCM, translocated elk were hard released, whereas at GSMNP elk were held in pens up to 60 days before release (i.e., soft release). We hypothesized that associations formed in the source population would affect genetic structure in the future population. We predicted that matrilineal groups would stay closer together and have similar movements after translocation. We used 16 microsatellite markers to analyze genetic composition and structure of translocated elk and their offspring in the years after release. Most source elk used for translocation strongly assigned to either EINPN or EINPS (93.2%, n = 204). Evaluating the genetic structure of offspring after translocation, we found the 2 genetic groups mostly persisted ≥11 years following release. We measured the Euclidean distance between all possible pairs of telemetered female elk during each season and year and calculated the maximum distance moved from the release sites for females surviving >1 year. Mean Euclidean distances between pairwise locations of female elk were similar for each genetic cluster for each area. The mean distances for all paired locations (genetic clusters combined) in TNCM were 14.67 km (n = 4,576 ± 13.23 [SD]) and in GSMNP were 9.30 km (n = 1,468 ± 9.75). However, when looking at only simultaneous locations <50 m apart, the frequency of occurrence was higher (P < 0.001) for elk with the same genetic structure (71.1%) compared with those with different structure (28.9%). The maximum distance travelled from the release site was not different for the 2 genetic groups, but EINPN females tended to travel farther. Pairwise female distances were lower in GSMNP where we used a soft release. Release methodology and social structure appear to affect movements and possibly genetic mixing after translocation. Given that restoration success can depend on maintaining genetic diversity and number of founders, our analyses suggest that within‐cluster breeding bias can result in lower genetic variability and a smaller effective population size than previously assumed.
Review of Meriluoto, Jussi, Lisa Spoof, and GeoffreyA. Codd [eds.]. 2017. Handbook of Cyanobacterial Monitoring and Cyanotoxin Analysis. John Wiley & Sons, Ltd.: Chichester, West Sussex, UK, ISBN 978‐1‐119‐06868‐6 (978‐1‐119‐06876‐1 eBook), DOI 10.1002/9781119068761.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lob.10227","usgsCitation":"Graham, J., and Loftin, K.A., 2018, Book review: Handbook of cyanobacterial monitoring and cyanotoxin analysis: Limnology and Oceanography Bulletin, v. 27, no. 2, p. 61-62, https://doi.org/10.1002/lob.10227.","productDescription":"2 p.","startPage":"61","endPage":"62","ipdsId":"IP-092798","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":468798,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lob.10227","text":"Publisher Index Page"},{"id":354718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-17","publicationStatus":"PW","scienceBaseUri":"5b46e58ee4b060350a15d1d8","contributors":{"authors":[{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":737200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":737201,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197428,"text":"70197428 - 2018 - Forecasting an invasive species’ distribution with global distribution data, local data, and physiological information","interactions":[],"lastModifiedDate":"2018-06-04T10:36:56","indexId":"70197428","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting an invasive species’ distribution with global distribution data, local data, and physiological information","docAbstract":"Understanding invasive species distributions and potential invasions often requires broad‐scale information on the environmental tolerances of the species. Further, resource managers are often faced with knowing these broad‐scale relationships as well as nuanced environmental factors related to their landscape that influence where an invasive species occurs and potentially could occur. Using invasive buffelgrass (Cenchrus ciliaris), we developed global models and local models for Saguaro National Park, Arizona, USA, based on location records and literature on physiological tolerances to environmental factors to investigate whether environmental relationships of a species at a global scale are also important at local scales. In addition to correlative models with five commonly used algorithms, we also developed a model using a priori user‐defined relationships between occurrence and environmental characteristics based on a literature review. All correlative models at both scales performed well based on statistical evaluations. The user‐defined curves closely matched those produced by the correlative models, indicating that the correlative models may be capturing mechanisms driving the distribution of buffelgrass. Given climate projections for the region, both global and local models indicate that conditions at Saguaro National Park may become more suitable for buffelgrass. Combining global and local data with correlative models and physiological information provided a holistic approach to forecasting invasive species distributions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2279","usgsCitation":"Jarnevich, C.S., Young, N.E., Talbert, M., and Talbert, C., 2018, Forecasting an invasive species’ distribution with global distribution data, local data, and physiological information: Ecosphere, v. 9, no. 5, p. 1-12, https://doi.org/10.1002/ecs2.2279.","productDescription":"e02279; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-097154","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468799,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2279","text":"Publisher Index Page"},{"id":437929,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y99UFF","text":"USGS data release","linkHelpText":"Data for forecasting buffelgrass distribution with global distribution data, local data, and physiological information"},{"id":354686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Saguaro National Park","volume":"9","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-29","publicationStatus":"PW","scienceBaseUri":"5b155d84e4b092d9651e1b61","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":737118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nicholas E.","contributorId":58572,"corporation":false,"usgs":true,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":737119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Talbert, Marian 0000-0003-0588-0265 mtalbert@usgs.gov","orcid":"https://orcid.org/0000-0003-0588-0265","contributorId":196740,"corporation":false,"usgs":true,"family":"Talbert","given":"Marian","email":"mtalbert@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":737120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbert, Colin 0000-0002-9505-1876 talbertc@usgs.gov","orcid":"https://orcid.org/0000-0002-9505-1876","contributorId":181913,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":737121,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196796,"text":"70196796 - 2018 - Demographic response of Louisiana Waterthrush, a stream obligate songbird of conservation concern, to shale gas development","interactions":[],"lastModifiedDate":"2018-05-01T15:45:19","indexId":"70196796","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Demographic response of Louisiana Waterthrush, a stream obligate songbird of conservation concern, to shale gas development","docAbstract":"Shale gas development continues to outpace the implementation of best management practices for wildlife affected by development. We examined demographic responses of the Louisiana Waterthrush (Parkesia motacilla) to shale gas development during 2009–2011 and 2013–2015 in a predominantly forested landscape in West Virginia, USA. Forest cover across the study area decreased from 95% in 2008 to 91% in 2015, while the area affected by shale gas development increased from 0.4% to 3.9%. We quantified nest survival and productivity, a source–sink threshold, riparian habitat quality, territory density, and territory length by monitoring 58.1 km of forested headwater streams (n = 14 streams). Across years, we saw annual variability in nest survival, with a general declining trend over time. Of 11 a priori models tested to explain nest survival (n = 280 nests), 4 models that included temporal, habitat, and shale gas covariates were supported, and 2 of these models accounted for most of the variation in daily nest survival rate. After accounting for temporal effects (rainfall, nest age, and time within season), shale gas development had negative effects on nest survival. Population-level nest productivity declined and individual productivity was lower in areas disturbed by shale gas development than in undisturbed areas, and a source–sink threshold suggested that disturbed areas were more at risk of being sink habitat. Riparian habitat quality scores, as measured by a U.S. Environmental Protection Agency index and a waterthrush-specific habitat suitability index, differed by year and were negatively related to the amount of each territory disturbed by shale gas development. Territory density was not related to the amount of shale gas disturbance, but decreased over time as territory lengths increased. Overall, our results suggest a decline in waterthrush site quality as shale gas development increases, despite relatively small site-wide forest loss.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-130.1","usgsCitation":"Frantz, M.W., Wood, P.B., Sheehan, J., and George, G., 2018, Demographic response of Louisiana Waterthrush, a stream obligate songbird of conservation concern, to shale gas development: Condor, v. 120, no. 2, p. 265-282, https://doi.org/10.1650/CONDOR-17-130.1.","productDescription":"18 p.","startPage":"265","endPage":"282","ipdsId":"IP-081181","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468794,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1650/CONDOR-17-130.1","text":"External Repository"},{"id":353898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Lewis Wetzel Wildlife Management Area","volume":"120","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c5e4b0da30c1bfbe0a","contributors":{"authors":[{"text":"Frantz, Mack W.","contributorId":191486,"corporation":false,"usgs":false,"family":"Frantz","given":"Mack","email":"","middleInitial":"W.","affiliations":[{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":734475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheehan, James","contributorId":169745,"corporation":false,"usgs":false,"family":"Sheehan","given":"James","email":"","affiliations":[],"preferred":false,"id":734476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Gregory","contributorId":204601,"corporation":false,"usgs":false,"family":"George","given":"Gregory","affiliations":[],"preferred":false,"id":734477,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196788,"text":"70196788 - 2018 - Rivers are social–ecological systems: Time to integrate human dimensions into riverscape ecology and management","interactions":[],"lastModifiedDate":"2018-07-03T11:23:17","indexId":"70196788","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5067,"text":"WIREs Water","active":true,"publicationSubtype":{"id":10}},"title":"Rivers are social–ecological systems: Time to integrate human dimensions into riverscape ecology and management","docAbstract":"Incorporation of concepts from landscape ecology into understanding and managing riverine ecosystems has become widely known as riverscape ecology. Riverscape ecology emphasizes interactions among processes at different scales and their consequences for valued ecosystem components, such as riverine fishes. Past studies have focused strongly on understanding the ecological processes in riverscapes and how human actions modify those processes. It is increasingly clear, however, that an understanding of the drivers behind actions that lead to human modification also merit consideration, especially regarding how those drivers influence management efficacy. These indirect drivers of riverscape outcomes can be understood in the context of a diverse array of social processes, which we collectively refer to as human dimensions. Like ecological phenomena, social processes also exhibit complex interactions across spatiotemporal scales. Greater emphasis on feedbacks between social and ecological processes will lead scientists and managers to more completely understand riverscapes as complex, dynamic, interacting social–ecological systems. Emerging applications in riverscapes, as well as studies of other ecosystems, provide examples that can lead to stronger integration of social and ecological science. We argue that conservation successes within riverscapes may not come from better ecological science, improved ecosystem service analyses, or even economic incentives if the fundamental drivers of human behaviors are not understood and addressed in conservation planning and implementation.
","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1291","usgsCitation":"Dunham, J.B., Angermeier, P.L., Crausbay, S.D., Cravens, A.E., Gosnell, H., McEvoy, J., Moritz, M.A., Raheem, N., and Sanford, T., 2018, Rivers are social–ecological systems: Time to integrate human dimensions into riverscape ecology and management: WIREs Water, v. 5, no. 4, p. 1-10, https://doi.org/10.1002/wat2.1291.","productDescription":"e1291; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-086232","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":353886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-23","publicationStatus":"PW","scienceBaseUri":"5afee6cce4b0da30c1bfbe0c","contributors":{"authors":[{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":734406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. biota@usgs.gov","contributorId":1432,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":613,"text":"Virginia Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":734407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crausbay, Shelley D.","contributorId":197220,"corporation":false,"usgs":false,"family":"Crausbay","given":"Shelley","email":"","middleInitial":"D.","affiliations":[{"id":54831,"text":"Conservation Science Partners, Inc","active":true,"usgs":false}],"preferred":false,"id":734408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cravens, Amanda E. 0000-0002-0271-7967 aecravens@usgs.gov","orcid":"https://orcid.org/0000-0002-0271-7967","contributorId":196752,"corporation":false,"usgs":true,"family":"Cravens","given":"Amanda","email":"aecravens@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":734409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gosnell, Hannah","contributorId":192214,"corporation":false,"usgs":false,"family":"Gosnell","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":734410,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McEvoy, Jamie","contributorId":204581,"corporation":false,"usgs":false,"family":"McEvoy","given":"Jamie","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":734411,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moritz, Max A.","contributorId":182434,"corporation":false,"usgs":false,"family":"Moritz","given":"Max","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734412,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Raheem, Nejem","contributorId":197227,"corporation":false,"usgs":false,"family":"Raheem","given":"Nejem","email":"","affiliations":[],"preferred":false,"id":734413,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sanford, Todd","contributorId":197228,"corporation":false,"usgs":false,"family":"Sanford","given":"Todd","email":"","affiliations":[],"preferred":false,"id":734414,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70196783,"text":"70196783 - 2018 - Response of moose to a high‐density road network","interactions":[],"lastModifiedDate":"2018-07-03T11:24:35","indexId":"70196783","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Response of moose to a high‐density road network","docAbstract":"Road networks and the disturbance associated with vehicle traffic alter animal behavior, movements, and habitat selection. The response of moose (Alces americanus) to roads has been documented in relatively rural areas, but less is known about moose response to roads in more highly roaded landscapes. We examined road‐crossing frequencies and habitat use of global positioning system (GPS)‐collared moose in Massachusetts, USA, where moose home ranges have road densities approximately twice that of previous studies. We compared seasonal road‐crossing frequencies of moose with a null movement model. We estimated moose travel speeds during road‐crossing events and compared them with speeds during other home range movements. To estimate the extent of the road effect zone and determine how roads influenced moose habitat use, we fit a third‐order resource selection function. With the exception of the lowest use road class (<10 vehicles/day), we found moose crossed roads less than expected based on the null movement model and frequency decreased with increasing road size and traffic. Moose crossed roads faster than they traveled during other times. This effect increased with increasing road use intensity. Overall, roads were a major factor determining what portions of Massachusetts moose used and how they moved among habitat patches. Our results suggest that moose in Massachusetts can adapt to a high‐density road network, but the road effect is still strongly negative and, in some cases, is more pronounced than in study areas with lower road densities. Future road construction and the expansion of road networks may have a large effect on moose and other wildlife.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21459","usgsCitation":"Wattles, D.W., Zeller, K.A., and DeStefano, S., 2018, Response of moose to a high‐density road network: Journal of Wildlife Management, v. 82, no. 5, p. 929-939, https://doi.org/10.1002/jwmg.21459.","productDescription":"11 p.","startPage":"929","endPage":"939","ipdsId":"IP-076431","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":353884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-06","publicationStatus":"PW","scienceBaseUri":"5afee6cce4b0da30c1bfbe0e","contributors":{"authors":[{"text":"Wattles, David W.","contributorId":204573,"corporation":false,"usgs":false,"family":"Wattles","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":734379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zeller, Katherine A.","contributorId":204574,"corporation":false,"usgs":false,"family":"Zeller","given":"Katherine","email":"","middleInitial":"A.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":734380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeStefano, Stephen 0000-0003-2472-8373 destef@usgs.gov","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":166706,"corporation":false,"usgs":true,"family":"DeStefano","given":"Stephen","email":"destef@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":734378,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197866,"text":"70197866 - 2018 - The intensity signature of induced seismicity","interactions":[],"lastModifiedDate":"2018-06-22T14:47:02","indexId":"70197866","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"The intensity signature of induced seismicity","docAbstract":"We analyze a comprehensive database of
SBSC Staff,
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Determining the influences of anthropogenic perturbations on side channel dynamics in large rivers is important from both assessment and monitoring perspectives because side channels provide critical habitat to numerous aquatic species. Side channel extents are decreasing in large rivers worldwide. Although riprap and other linear structures have been shown to reduce side channel extents in large rivers, we hypothesized that small “anthropogenic plugs” (flow obstructions such as dikes or berms) across side channels modify whole-river geomorphology via accelerating side channel senescence. To test this hypothesis, we conducted a geospatial assessment, comparing digitized side channel areas from aerial photographs taken during the 1950s and 2001 along 512 km of the Yellowstone River floodplain. We identified longitudinal patterns of side channel recruitment (created/enlarged side channels) and side channel attrition (destroyed/senesced side channels) across n = 17 river sections within which channels were actively migrating. We related areal measures of recruitment and attrition to the density of anthropogenic side channel plugs across river sections. Consistent with our hypothesis, a positive spatial relationship existed between the density of anthropogenic plugs and side channel attrition, but no relationship existed between plug density and side channel recruitment. Our work highlights important linkages among side channel plugs and the persistence and restoration of side channels across floodplain landscapes. Specifically, management of small plugs represents a low-cost, high-benefit restoration opportunity to facilitate scouring flows in side channels to enable the persistence of these habitats over time.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-018-6673-8","usgsCitation":"Reinhold, A.M., Poole, G., Bramblett, R.G., Zale, A.V., and Roberts, D.W., 2018, Landscape assessment of side channel plugs and associated cumulative side channel attrition across a large river floodplain: Environmental Monitoring and Assessment, v. 190, p. 1-15, https://doi.org/10.1007/s10661-018-6673-8.","productDescription":"Article 305; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-064957","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Yellowstone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.7646484375,\n 45.65244828675087\n ],\n [\n -104.04602050781249,\n 45.65244828675087\n ],\n [\n -104.04602050781249,\n 47.82790816919329\n ],\n [\n -108.7646484375,\n 47.82790816919329\n ],\n [\n -108.7646484375,\n 45.65244828675087\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"190","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-24","publicationStatus":"PW","scienceBaseUri":"5afee6c4e4b0da30c1bfbdfe","contributors":{"authors":[{"text":"Reinhold, Ann Marie","contributorId":200043,"corporation":false,"usgs":false,"family":"Reinhold","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":734921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poole, Geoffrey C.","contributorId":25540,"corporation":false,"usgs":true,"family":"Poole","given":"Geoffrey C.","affiliations":[],"preferred":false,"id":734922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bramblett, Robert G.","contributorId":169857,"corporation":false,"usgs":false,"family":"Bramblett","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":734923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, David W.","contributorId":56235,"corporation":false,"usgs":true,"family":"Roberts","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":734924,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196898,"text":"70196898 - 2018 - Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA","interactions":[],"lastModifiedDate":"2018-05-17T15:35:17","indexId":"70196898","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA","docAbstract":"Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R2 values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2017.1382065","usgsCitation":"Boyte, S.P., Wylie, B.K., Rigge, M.B., and Dahal, D., 2018, Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA: GIScience and Remote Sensing, v. 55, no. 3, p. 376-399, https://doi.org/10.1080/15481603.2017.1382065.","productDescription":"24 p.","startPage":"376","endPage":"399","ipdsId":"IP-087872","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499993,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/d0da5ee1cd9c49fab95dfe363f4d48a7","text":"External Repository"},{"id":437930,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R20ZVX","text":"USGS data release","linkHelpText":"Downscaled 30 m weekly MODIS NDVI for the Central Great Basin"},{"id":354284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin rangelands","volume":"55","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-28","publicationStatus":"PW","scienceBaseUri":"5afee6c4e4b0da30c1bfbdfc","contributors":{"authors":[{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":139238,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":734937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":734938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":734939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":734940,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196801,"text":"70196801 - 2018 - A suite of exercises for verifying dynamic earthquake rupture codes","interactions":[],"lastModifiedDate":"2018-05-02T11:36:53","indexId":"70196801","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"A suite of exercises for verifying dynamic earthquake rupture codes","docAbstract":"We describe a set of benchmark exercises that are designed to test if computer codes that simulate dynamic earthquake rupture are working as intended. These types of computer codes are often used to understand how earthquakes operate, and they produce simulation results that include earthquake size, amounts of fault slip, and the patterns of ground shaking and crustal deformation. The benchmark exercises examine a range of features that scientists incorporate in their dynamic earthquake rupture simulations. These include implementations of simple or complex fault geometry, off‐fault rock response to an earthquake, stress conditions, and a variety of formulations for fault friction. Many of the benchmarks were designed to investigate scientific problems at the forefronts of earthquake physics and strong ground motions research. The exercises are freely available on our website for use by the scientific community.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170222","usgsCitation":"Harris, R.A., Barall, M., Aagaard, B.T., Ma, S., Roten, D., Olsen, K., Duan, B., Liu, D., Luo, B., Bai, K., Ampuero, J., Kaneko, Y., Gabriel, A., Duru, K., Ulrich, T., Wollherr, S., Shi, Z., Dunham, E., Bydlon, S., Zhang, Z., Chen, X., Somala, S.N., Pelties, C., Tago, J., Cruz-Atienza, V.M., Kozdon, J., Daub, E., Aslam, K., Kase, Y., Withers, K., and Dalguer, L., 2018, A suite of exercises for verifying dynamic earthquake rupture codes: Seismological Research Letters, v. 89, no. 3, p. 1146-1162, https://doi.org/10.1785/0220170222.","productDescription":"17 p.","startPage":"1146","endPage":"1162","ipdsId":"IP-090832","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":502555,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/10945/59234","text":"External 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,{"id":70196807,"text":"70196807 - 2018 - Quantifying temporal trends in fisheries abundance using Bayesian dynamic linear models: A case study of riverine Smallmouth Bass populations","interactions":[],"lastModifiedDate":"2018-05-02T10:48:08","indexId":"70196807","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","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":"Quantifying temporal trends in fisheries abundance using Bayesian dynamic linear models: A case study of riverine Smallmouth Bass populations","docAbstract":"Detecting temporal changes in fish abundance is an essential component of fisheries management. Because of the need to understand short‐term and nonlinear changes in fish abundance, traditional linear models may not provide adequate information for management decisions. This study highlights the utility of Bayesian dynamic linear models (DLMs) as a tool for quantifying temporal dynamics in fish abundance. To achieve this goal, we quantified temporal trends of Smallmouth Bass Micropterus dolomieu catch per effort (CPE) from rivers in the mid‐Atlantic states, and we calculated annual probabilities of decline from the posterior distributions of annual rates of change in CPE. We were interested in annual declines because of recent concerns about fish health in portions of the study area. In general, periods of decline were greatest within the Susquehanna River basin, Pennsylvania. The declines in CPE began in the late 1990s—prior to observations of fish health problems—and began to stabilize toward the end of the time series (2011). In contrast, many of the other rivers investigated did not have the same magnitude or duration of decline in CPE. Bayesian DLMs provide information about annual changes in abundance that can inform management and are easily communicated with managers and stakeholders.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10051","usgsCitation":"Schall, M.K., Blazer, V., Lorantas, R.M., Smith, G., Mullican, J.E., Keplinger, B.J., and Wagner, T., 2018, Quantifying temporal trends in fisheries abundance using Bayesian dynamic linear models: A case study of riverine Smallmouth Bass populations: North American Journal of Fisheries Management, v. 38, no. 2, p. 493-501, https://doi.org/10.1002/nafm.10051.","productDescription":"9 p.","startPage":"493","endPage":"501","ipdsId":"IP-085001","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":353909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Pennsylvania, West Virginia","otherGeospatial":"Allegheny River, Delaware River, Juniata River, Potomac River. Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.09033203125,\n 37.90953361677018\n ],\n [\n -74.696044921875,\n 37.90953361677018\n ],\n [\n -74.696044921875,\n 42.15525946577863\n ],\n [\n -80.09033203125,\n 42.15525946577863\n ],\n [\n -80.09033203125,\n 37.90953361677018\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-10","publicationStatus":"PW","scienceBaseUri":"5afee6c5e4b0da30c1bfbe04","contributors":{"authors":[{"text":"Schall, Megan K.","contributorId":115964,"corporation":false,"usgs":false,"family":"Schall","given":"Megan","email":"","middleInitial":"K.","affiliations":[{"id":17758,"text":"Pennsylvania State Univ.","active":true,"usgs":false}],"preferred":false,"id":734549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":734532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorantas, Robert M.","contributorId":204631,"corporation":false,"usgs":false,"family":"Lorantas","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":36966,"text":"Pennsylvania Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":734550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Geoffrey","contributorId":115958,"corporation":false,"usgs":true,"family":"Smith","given":"Geoffrey","affiliations":[],"preferred":false,"id":734551,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mullican, John E.","contributorId":203245,"corporation":false,"usgs":false,"family":"Mullican","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":734552,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keplinger, Brandon J.","contributorId":204644,"corporation":false,"usgs":false,"family":"Keplinger","given":"Brandon","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":734553,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734531,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}