Quantification of the economic value provided by migratory species can aid in targeting management efforts and funding to locations yielding the greatest benefits to society and species conservation. Here we illustrate a key step in this process by estimating hunting and birding values of the northern pintail (Anas acuta) within primary breeding and wintering habitats used during the species’ annual migratory cycle in North America. We used published information on user expenditures and net economic values (consumer surplus) for recreational viewing and hunting to determine the economic value of pintail-based recreation in three primary breeding areas and two primary wintering areas. Summed expenditures and consumer surplus for northern pintail viewing were annually valued at \\$70M, and annual sport hunting totaled \\$31M (2014 USD). Expenditures for viewing (\\$42M) were more than twice as high than those for hunting (\\$18M). Estimates of consumer surplus, defined as the amount consumers are willing to pay above their current expenditures, were $15M greater for viewing (\\$28M) than for hunting (\\$13M). We discovered substantial annual consumer surplus (\\$41M) available for pintail conservation from birders and hunters. We also found spatial differences in economic value among the primary regions used by pintails, with viewing generally valued more in breeding regions than in wintering regions and the reverse being true for hunting. The economic value of pintail-based recreation in the Western wintering region (\\$26M) exceeded that in any other region by at least a factor of three. Our approach of developing regionally explicit economic values can be extended to other taxonomic groups, and is particularly suitable for migratory game birds because of the availability of large amounts of data. When combined with habitat-linked population models, regionally explicit values could inform development of more effective conservation finance and policy mechanisms to enhance environmental management and societal benefits across the geographically dispersed areas used by migratory species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2017.11.048","usgsCitation":"Mattsson, B.J., Dubovsky, J.A., Thogmartin, W.E., Bagstad, K.J., Goldstein, J.H., Loomis, J., Diffendorfer, J., Semmens, D.J., Wiederholt, R., and Lopez-Hoffman, L., 2018, Recreation economics to inform migratory species conservation: Case study of the northern pintail: Journal of Environmental Management, v. 206, p. 971-979, https://doi.org/10.1016/j.jenvman.2017.11.048.","productDescription":"9 p.","startPage":"971","endPage":"979","ipdsId":"IP-090412","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":469143,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2017.11.048","text":"Publisher Index Page"},{"id":349885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"206","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad4e4b06e28e9c22759","contributors":{"authors":[{"text":"Mattsson, Brady J.","contributorId":201057,"corporation":false,"usgs":false,"family":"Mattsson","given":"Brady","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":724743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dubovsky, James A.","contributorId":201247,"corporation":false,"usgs":false,"family":"Dubovsky","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":724742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":724745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldstein, Joshua H.","contributorId":201248,"corporation":false,"usgs":false,"family":"Goldstein","given":"Joshua","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":724746,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loomis, John B.","contributorId":201249,"corporation":false,"usgs":false,"family":"Loomis","given":"John B.","affiliations":[],"preferred":false,"id":724747,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":724748,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":724749,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wiederholt, Ruscena","contributorId":149125,"corporation":false,"usgs":false,"family":"Wiederholt","given":"Ruscena","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":724750,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":724751,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70194558,"text":"sir20175109 - 2018 - Sequence stratigraphy, seismic stratigraphy, and seismic structures of the lower intermediate confining unit and most of the Floridan aquifer system, Broward County, Florida","interactions":[],"lastModifiedDate":"2018-01-25T09:03:53","indexId":"sir20175109","displayToPublicDate":"2017-12-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5109","title":"Sequence stratigraphy, seismic stratigraphy, and seismic structures of the lower intermediate confining unit and most of the Floridan aquifer system, Broward County, Florida","docAbstract":"Deep well injection and disposal of treated wastewater into the highly transmissive saline Boulder Zone in the lower part of the Floridan aquifer system began in 1971. The zone of injection is a highly transmissive hydrogeologic unit, the Boulder Zone, in the lower part of the Floridan aquifer system. Since the 1990s, however, treated wastewater injection into the Boulder Zone in southeastern Florida has been detected at three treated wastewater injection utilities in the brackish upper part of the Floridan aquifer system designated for potential use as drinking water. At a time when usage of the Boulder Zone for treated wastewater disposal is increasing and the utilization of the upper part of the Floridan aquifer system for drinking water is intensifying, there is an urgency to understand the nature of cross-formational fluid flow and identify possible fluid pathways from the lower to upper zones of the Floridan aquifer system. To better understand the hydrogeologic controls on groundwater movement through the Floridan aquifer system in southeastern Florida, the U.S. Geological Survey and the Broward County Environmental Planning and Community Resilience Division conducted a 3.5-year cooperative study from July 2012 to December 2015. The study characterizes the sequence stratigraphy, seismic stratigraphy, and seismic structures of the lower part of the intermediate confining unit aquifer and most of the Floridan aquifer system.
Data obtained to meet the study objective include 80 miles of high-resolution, two-dimensional (2D), seismic-reflection profiles acquired from canals in eastern Broward County. These profiles have been used to characterize the sequence stratigraphy, seismic stratigraphy, and seismic structures in a 425-square-mile study area. Horizon mapping of the seismic-reflection profiles and additional data collection from well logs and cores or cuttings from 44 wells were focused on construction of three-dimensional (3D) visualizations of eight sequence stratigraphic cycles that compose the Eocene to Miocene Oldsmar, Avon Park, and Arcadia Formations. The mapping of these seismic-reflection and well data has produced a refined Cenozoic sequence stratigraphic, seismic stratigraphic, and hydrogeologic framework of southeastern Florida. The upward transition from the Oldsmar Formation to the Avon Park Formation and the Arcadia Formation embodies the evolution from (1) a tropical to subtropical, shallow-marine, carbonate platform, represented by the Oldsmar and Avon Park Formations, to (2) a broad, temperate, mixed carbonate-siliciclastic shallow marine shelf, represented by the lower part of the Arcadia Formation, and to (3) a temperate, distally steepened carbonate ramp represented by the upper part of the Arcadia Formation.
In the study area, the depositional sequences and seismic sequences have a direct correlation with hydrogeologic units. The approximate upper boundary of four principal permeable units of the Floridan aquifer system (Upper Floridan aquifer, Avon Park permeable zone, uppermost major permeable zone of the Lower Floridan aquifer, and Boulder Zone) have sequence stratigraphic and seismic-reflection signatures that were identified on cross sections, mapped, or both, and therefore the sequence stratigraphy and seismic stratigraphy were used to guide the development of a refined spatial representation of these hydrogeologic units. In all cases, the permeability of the four permeable units is related to stratiform megaporosity generated by ancient dissolution of carbonate rock associated with subaerial exposure and unconformities at the upper surfaces of carbonate depositional cycles of several hierarchical scales ranging from high-frequency cycles to depositional sequences. Additionally, interparticle porosity also contributes substantially to the stratiform permeability in much of the Upper Floridan aquifer. Information from seismic stratigraphy allowed 3D geomodeling of hydrogeologic units—an approach never before applied to this area. Notably, the 3D geomodeling provided 3D visualizations and geocellular models of the depositional sequences, hydrostratigraphy, and structural features. The geocellular data could be used to update the hydrogeologic structure inherent to groundwater flow simulations that are designed to address the sustainability of the water resources of the Floridan aquifer system.
Two kinds of pathways that could enable upward cross-formational flow of injected treated wastewater from the Boulder Zone have been identified in the 80 miles of high-resolution seismic data collected for this study: a near-vertical reverse fault and karst collapse structures. The single reverse fault, inferred to be of tectonic origin, is in extreme northeastern Broward County and has an offset of about 19 feet at the level of the Arcadia Formation. Most of the 17 karst collapse structures identified manifest as columniform, vertically stacked sagging seismic reflections that span early Eocene to Miocene age rocks equivalent to much of the Floridan aquifer system and the lower part of the overlying intermediate confining unit. In some cases, the seismic-sag structures extend upward into strata of Pliocene age. The seismic-sag structures are interpreted to have a semicircular shape in plan view on the basis of comparison to (1) other seismic-sag structures in southeastern Florida mapped with two 2D seismic cross lines or 3D data, (2) comparison to these structures located in other carbonate provinces, and (3) plausible extensional ring faults detected with multi-attribute analysis. The seismic-sag structures in the study area have heights as great as 2,500 vertical feet, though importantly, one spans about 7,800 feet. Both multi-attribute analysis and visual detection of offset of seismic reflections within the seismic-sag structures indicate faults and fractures are associated with many of the structures. Multi-attribute analysis highlighting chimney fluid pathways also indicates that the seismic-sag structures have a high probability for potential vertical cross-formational fluid flow along the faulted and fractured structures. A collapse of the seismic-sag structures within a deep burial setting evokes an origin related to hypogenic karst processes by ascending flow of subsurface fluids. In addition, paleo-epigenic karst related to major regional subaerial unconformities within the Florida Platform generated collapse structures (paleo-sinkholes) that are much smaller in scale than the cross-formational seismic-sag structures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175109","collaboration":"Prepared in cooperation with Broward County Environmental Planning and Community Resilience Division, Florida","usgsCitation":"Cunningham, K.J., Kluesner, J.W., Westcott, R.L., Robinson, Edward, Walker, Cameron, and Khan, S.A., 2018, Sequence stratigraphy, seismic stratigraphy, and seismic structures of the lower intermediate confining unit and most of the Floridan aquifer system, Broward County, Florida (ver. 1.1, January 2018): U.S. Geological Survey Scientific Investigations Report 2017–5109, 71 p., 21 pls., https://doi.org/10.3133/sir20175109.","productDescription":"Report: ix, 71 p.; 21 Plates; 2 Data Releases","numberOfPages":"86","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066339","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":349725,"rank":20,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate18.pdf","text":"Plate 18","size":"10.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 18","linkHelpText":"Uninterpreted Seismic-Reflection Profiles Along the Eastern C–9 Canal, Oleta River, and Intracoastal Waterway, Miami-Dade County, Florida"},{"id":349728,"rank":23,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate21.pdf","text":"Plate 21","size":"5.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 21","linkHelpText":"Multi-Attribute Fault and Chimney Analyses of a Seismic-Reflection Profile Along the Hillsboro Canal, Eastern Broward County, Florida"},{"id":349721,"rank":16,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate14.pdf","text":"Plate 14","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 14","linkHelpText":"Uninterpreted Seismic-Reflection Profiles Along the C–11 Canal, Eastern Broward County, Florida"},{"id":349726,"rank":21,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate19.pdf","text":"Plate 19","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 19","linkHelpText":"Interpreted Seismic-Reflection Profiles Along the Eastern C–9 Canal, Oleta River, and Intracoastal Waterway, Miami-Dade County, Florida"},{"id":349710,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate03.pdf","text":"Plate 3","size":"9.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 3","linkHelpText":"Block Models Showing Altitudes of Eight Depositional-Sequence Upper Boundaries of the Oldsmar Formation, Avon Park Formation, and Arcadia Formation, Eastern Broward County, Florida"},{"id":349724,"rank":19,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate17.pdf","text":"Plate 17","size":"24.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 17","linkHelpText":"Interpreted Seismic-Reflection Profiles Along the C–9 Canal, Miami-Dade and Broward Counties, Florida"},{"id":349723,"rank":18,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate16.pdf","text":"Plate 16","size":"24.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 16","linkHelpText":"Uninterpreted Seismic-Reflection Profiles Along the C–9 Canal, Miami-Dade and Broward Counties, Florida"},{"id":349708,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate01.pdf","text":"Plate 1","size":"4.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 1","linkHelpText":"Synthetic Seismograms from Floridan Aquifer System Wells, Eastern Broward County, Florida, Part 1"},{"id":349720,"rank":15,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate13.pdf","text":"Plate 13","size":"21.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 13","linkHelpText":"Interpreted Seismic-Reflection Profiles Along the North New River Canal, Eastern Broward County, Florida"},{"id":349706,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5109/coverthb2.jpg"},{"id":349707,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109.pdf","text":"Report","size":"36.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109"},{"id":349730,"rank":25,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77942R3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Marine seismic profiles used to assess the seismic stratigraphy and structure of the intermediate confining unit and Floridan aquifer system, Broward County, Florida"},{"id":350450,"rank":26,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5109/versionHist.txt","size":"1 MB","linkFileType":{"id":2,"text":"txt"}},{"id":349709,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate02.pdf","text":"Plate 2","size":"2.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 2","linkHelpText":"Synthetic Seismograms from Floridan Aquifer System Wells, Eastern Broward County, Florida, Part 2"},{"id":349711,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate04.pdf","text":"Plate 4","size":"16.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 4","linkHelpText":"Maps Showing Altitudes of Eight Depositional-Sequence Upper Boundaries of the Oldsmar Formation, Avon Park Formation, and Arcadia Formation, Eastern Broward County, Florida"},{"id":349712,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate05.pdf","text":"Plate 5","size":"2.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 5","linkHelpText":"Detailed Graphical Lithologic Log of the Avon Park Formation in the G–2984 Test Corehole"},{"id":349717,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate10.pdf","text":"Plate 10","size":"37.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 10","linkHelpText":"Uninterpreted Seismic-Reflection Profiles Along the L–35A and L–36 Canals, Eastern Broward County, Florida"},{"id":349716,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate09.pdf","text":"Plate 9","size":"33.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 9","linkHelpText":"Interpreted Seismic-Reflection Profiles Along the C–13 Canal, Eastern Broward County, Florida"},{"id":349722,"rank":17,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate15.pdf","text":"Plate 15","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 15","linkHelpText":"Interpreted Seismic-Reflection Profiles Along the C–11 Canal, Eastern Broward County, Florida"},{"id":349713,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate06.pdf","text":"Plate 6","size":"24.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 6","linkHelpText":"Uninterpreted Seismic-Reflection Profile Along the Hillsboro Canal, Eastern Broward County, Florida"},{"id":349719,"rank":14,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate12.pdf","text":"Plate 12","size":"20.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 12","linkHelpText":"Uninterpreted Seismic-Reflection Profiles Along the North New River Canal, Eastern Broward County, Florida"},{"id":349729,"rank":24,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72R3PVF","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Synthetic Seismogram Data for Correlation Between Seismic-Reflection Profiles and Well Data, Broward County, Florida"},{"id":349714,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate07.pdf","text":"Plate 7","size":"24.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 7","linkHelpText":"Interpreted Seismic-Reflection Profile Along the Hillsboro Canal, Eastern Broward County, Florida"},{"id":349727,"rank":22,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate20.pdf","text":"Plate 20","size":"711 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 20","linkHelpText":"Detailed Graphical Lithologic Log of the Arcadia Formation in the G–2984 Test Corehole"},{"id":349715,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate08.pdf","text":"Plate 8","size":"32.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 8","linkHelpText":"Uninterpreted Seismic-Reflection Profiles Along the C-13 Canal, Eastern Broward County, Florida"},{"id":349718,"rank":13,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5109/sir20175109_plate11.pdf","text":"Plate 11","size":"37.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5109 Plate 11","linkHelpText":"Interpreted Seismic-Reflection Profiles Along the L–35A and L–36 Canals, Eastern Broward County, Florida"}],"country":"United States","state":"Florida","county":"Broward County","otherGeospatial":"Floridan Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.44395446777344,\n 25.921614023117172\n ],\n [\n -80.06629943847656,\n 25.921614023117172\n ],\n [\n -80.06629943847656,\n 26.35742006833118\n ],\n [\n -80.44395446777344,\n 26.35742006833118\n ],\n [\n -80.44395446777344,\n 25.921614023117172\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally released December 8, 2017; Version 1.1: January 16, 2018","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Recent drought (2012–2016) caused unprecedented foliage dieback in giant sequoias (Sequoiadendron giganteum), a species endemic to the western slope of the southern Sierra Nevada in central California. As part of an effort to understand and map sequoia response to droughts, we studied the patterns of remotely sensed canopy water content (CWC), both within and among sequoia groves in two successive years during the drought period (2015 and 2016). Our aims were: (1) to quantify giant sequoia responses to severe drought stress at a landscape scale using CWC as an indicator of crown foliage status, and (2) to estimate the effect of environmental correlates that mediate CWC change within and among giant sequoia groves. We utilized airborne high fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) data from the Carnegie Airborne Observatory to assess giant sequoia foliage status during 2015 and 2016 of the 2012–2016 droughts. A series of statistical models were generated to classify giant sequoias and to map their location in Sequoia and Kings Canyon National Parks (SEKI) and vicinity. We explored the environmental correlates and the spatial patterns of CWC change at the landscape scale. The mapped CWC was highly variable throughout the landscape during the two observation years, and proved to be most closely related to geological substrates, topography, and site-specific water balance. While there was an overall net gain in sequoia CWC between 2015 and 2016, certain locations (lower elevations, steeper slopes, areas more distant from surface water sources, and areas with greater climate water deficit) showed CWC losses. In addition, we found greater CWC loss in shorter sequoias and those growing in areas with lower sequoia stem densities. Our results suggest that CWC change indicates sequoia response to droughts across landscapes. Long-term monitoring of giant sequoia CWC will likely be useful for modeling and predicting their population-level response to future climate change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2017.11.018","usgsCitation":"Paz-Kagan, T., Vaughn, N.R., Martin, R.E., Brodrick, P.G., Stephenson, N.L., Das, A., Nydick, K.R., and Asner, G.P., 2018, Landscape-scale variation in canopy water content of giant sequoias during drought: Forest Ecology and Management, v. 419-420, p. 291-304, https://doi.org/10.1016/j.foreco.2017.11.018.","productDescription":"14 p.","startPage":"291","endPage":"304","ipdsId":"IP-091087","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469144,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2017.11.018","text":"Publisher Index Page"},{"id":349874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada","volume":"419-420","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faeae4b06e28e9c22982","contributors":{"authors":[{"text":"Paz-Kagan, Tarin","contributorId":196597,"corporation":false,"usgs":false,"family":"Paz-Kagan","given":"Tarin","email":"","affiliations":[],"preferred":false,"id":724710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vaughn, Nicolas R.","contributorId":201233,"corporation":false,"usgs":false,"family":"Vaughn","given":"Nicolas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":724711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Roberta E.","contributorId":201234,"corporation":false,"usgs":false,"family":"Martin","given":"Roberta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":724712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brodrick, Philip G.","contributorId":201235,"corporation":false,"usgs":false,"family":"Brodrick","given":"Philip","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":724713,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":724709,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Das, Adrian 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":201236,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":724714,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nydick, Koren R.","contributorId":196601,"corporation":false,"usgs":false,"family":"Nydick","given":"Koren","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":724715,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Asner, Gregory P.","contributorId":25393,"corporation":false,"usgs":false,"family":"Asner","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":724716,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70194576,"text":"70194576 - 2018 - Oak habitat recovery on California's largest islands: Scenarios for the role of corvid seed dispersal","interactions":[],"lastModifiedDate":"2018-04-17T12:34:48","indexId":"70194576","displayToPublicDate":"2017-12-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Oak habitat recovery on California's largest islands: Scenarios for the role of corvid seed dispersal","docAbstract":"Seed dispersal by birds is central to the passive restoration of many tree communities. Reintroduction of extinct seed dispersers can therefore restore degraded forests and woodlands. To test this, we constructed a spatially explicit simulation model, parameterized with field data, to consider the effect of different seed dispersal scenarios on the extent of oak populations. We applied the model to two islands in California's Channel Islands National Park (USA), one of which has lost a key seed disperser.
We used an ensemble modelling approach to simulate island scrub oak (Quercus pacifica) demography. The model was developed and trained to recreate known population changes over a 20-year period on 250-km2 Santa Cruz Island, and incorporated acorn dispersal by island scrub-jays (Aphelocoma insularis), deer mice (Peromyscus maniculatus) and gravity, as well as seed predation. We applied the trained model to 215-km2 Santa Rosa Island to examine how reintroducing island scrub-jays would affect the rate and pattern of oak population expansion. Oak habitat on Santa Rosa Island has been greatly reduced from its historical extent due to past grazing by introduced ungulates, the last of which were removed by 2011.
Our simulation model predicts that a seed dispersal scenario including island scrub-jays would increase the extent of the island scrub oak population on Santa Rosa Island by 281% over 100 years, and by 544% over 200 years. Scenarios without jays would result in little expansion. Simulated long-distance seed dispersal by jays also facilitates establishment of discontinuous patches of oaks, and increases their elevational distribution.
Synthesis and applications. Scenario planning provides powerful decision support for conservation managers. We used ensemble modelling of plant demographic and seed dispersal processes to investigate whether the reintroduction of seed dispersers could provide cost-effective means of achieving broader ecosystem restoration goals on California's second-largest island. The simulation model, extensively parameterized with field data, suggests that re-establishing the mutualism with seed-hoarding jays would accelerate the expansion of island scrub oak, which could benefit myriad species of conservation concern.
The salt marshes of Jamaica Bay serve as a recreational outlet for New York City residents, mitigate wave impacts during coastal storms, and provide habitat for critical wildlife species. Hurricanes have been recognized as one of the critical drivers of coastal wetland morphology due to their effects on hydrodynamics and sediment transport, deposition, and erosion processes. In this study, the Delft3D modeling suite was utilized to examine the effects of Hurricane Sandy (2012) on salt marsh morphology in Jamaica Bay. Observed marsh elevation change and accretion from rod Surface Elevation Tables and feldspar Marker Horizons (SET-MH) and hydrodynamic measurements during Hurricane Sandy were used to calibrate and validate the wind-waves-surge-sediment transport-morphology coupled model. The model results agreed well with in situ field measurements. The validated model was then used to detect salt marsh morphological change due to Sandy across Jamaica Bay. Model results indicate that the island-wide morphological changes in the bay's salt marshes due to Sandy were in the range of −30 mm (erosion) to +15 mm (deposition), and spatially complex and heterogeneous. The storm generated paired deposition and erosion patches at local scales. Salt marshes inside the west section of the bay showed erosion overall while marshes inside the east section showed deposition from Sandy. The net sediment amount that Sandy brought into the bay is only about 1% of the total amount of reworked sediment within the bay during the storm. Numerical experiments show that waves and vegetation played a critical role in sediment transport and associated wetland morphological change in Jamaica Bay. Furthermore, without the protection of vegetation, the marsh islands of Jamaica Bay would experience both more erosion and less accretion in coastal storms.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2017.11.001","usgsCitation":"Hu, K., Chen, Q., Wang, H., Hartig, E., and Orton, P.M., 2018, Numerical modeling of salt marsh morphological change induced by Hurricane Sandy: Coastal Engineering, v. 132, p. 63-81, https://doi.org/10.1016/j.coastaleng.2017.11.001.","productDescription":"19 p.","startPage":"63","endPage":"81","ipdsId":"IP-083439","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469146,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2017.11.001","text":"Publisher Index Page"},{"id":349863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Jamaica Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.81782531738281,\n 40.65147128144057\n ],\n [\n -73.85181427001953,\n 40.648085029646715\n ],\n [\n -73.87687683105469,\n 40.64079098062354\n ],\n [\n -73.90193939208984,\n 40.627763910481185\n ],\n [\n -73.91189575195312,\n 40.60092013543081\n ],\n [\n -73.89644622802734,\n 40.577977105192225\n ],\n [\n -73.86932373046875,\n 40.57093618838665\n ],\n [\n -73.81473541259766,\n 40.58814601026153\n ],\n [\n -73.76667022705078,\n 40.595706501568905\n ],\n [\n -73.75980377197266,\n 40.622291783092706\n ],\n [\n -73.81782531738281,\n 40.65147128144057\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad5e4b06e28e9c2276e","contributors":{"authors":[{"text":"Hu, Kelin","contributorId":177218,"corporation":false,"usgs":false,"family":"Hu","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":724671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":724672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":724670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartig, Ellen K.","contributorId":179351,"corporation":false,"usgs":false,"family":"Hartig","given":"Ellen K.","affiliations":[],"preferred":false,"id":724673,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orton, Philip M.","contributorId":179354,"corporation":false,"usgs":false,"family":"Orton","given":"Philip","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724674,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217670,"text":"70217670 - 2018 - Drought-induced recharge promotes long-term storage of porewater salinity beneath a prairie wetland","interactions":[],"lastModifiedDate":"2021-01-28T00:53:32.739205","indexId":"70217670","displayToPublicDate":"2017-12-06T18:50:57","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Drought-induced recharge promotes long-term storage of porewater salinity beneath a prairie wetland","docAbstract":"Subsurface storage of sulfate salts allows closed-basin wetlands in the semiarid Prairie Pothole Region (PPR) of North America to maintain moderate surface water salinity (total dissolved solids [TDS] from 1 to 10 g L−1), which provides critical habitat for communities of aquatic biota. However, it is unclear how the salinity of wetland ponds will respond to a recent shift in mid-continental climate to wetter conditions. To understand better the mechanisms that control surface-subsurface salinity exchanges during regional dry-wet climate cycles, we made a detailed geoelectrical study of a closed-basin prairie wetland (P1 in the Cottonwood Lake Study Area, North Dakota) that is currently experiencing record wet conditions. We found saline lenses of sulfate-rich porewater (TDS > 10 g L−1) contained in fine-grained wetland sediments 2–4 m beneath the bathymetric low of the wetland and within the currently ponded area along the shoreline of a prior pond stand (c. 1983). During the most recent drought (1988–1993), the wetland switched from a groundwater discharge to recharge function, allowing salts dissolved in surface runoff to move into wetland sediments beneath the bathymetric low of the basin. However, groundwater levels during this time did not decline to the elevation of the saline lenses, suggesting these features formed during more extended paleo-droughts and are stable in the subsurface on at least centennial timescales. We hypothesize a “drought-induced recharge” mechanism that allows wetland ponds to maintain moderate salinity under semiarid climate. Discharge of drought-derived saline groundwater has the potential to increase the salinity of wetland ponds during wet climate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2017.12.005","usgsCitation":"Levy, Z.F., Rosenberry, D.O., Moucha, R., Mushet, D.M., Goldhaber, M.B., LaBaugh, J.W., Fiorentino, A.J., and Siegel, D.I., 2018, Drought-induced recharge promotes long-term storage of porewater salinity beneath a prairie wetland: Journal of Hydrology, v. 557, p. 391-409, https://doi.org/10.1016/j.jhydrol.2017.12.005.","productDescription":"19 p.","startPage":"391","endPage":"409","ipdsId":"IP-086339","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":469147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2017.12.005","text":"Publisher Index Page"},{"id":382739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Cottonwood Lake Study Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.69725036621094,\n 47.848187594394815\n ],\n [\n -100.64849853515625,\n 47.848187594394815\n ],\n [\n -100.64849853515625,\n 47.884348247770006\n ],\n [\n -100.69725036621094,\n 47.884348247770006\n ],\n [\n -100.69725036621094,\n 47.848187594394815\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"557","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Levy, Zeno F","contributorId":248464,"corporation":false,"usgs":false,"family":"Levy","given":"Zeno","email":"","middleInitial":"F","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":809207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":809208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moucha, Robert","contributorId":173102,"corporation":false,"usgs":false,"family":"Moucha","given":"Robert","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":809209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":809210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldhaber, Martin B. 0000-0002-1785-4243 mgold@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-4243","contributorId":1339,"corporation":false,"usgs":true,"family":"Goldhaber","given":"Martin","email":"mgold@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":809211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaBaugh, James W. 0000-0002-4112-2536 jlabaugh@usgs.gov","orcid":"https://orcid.org/0000-0002-4112-2536","contributorId":1311,"corporation":false,"usgs":true,"family":"LaBaugh","given":"James","email":"jlabaugh@usgs.gov","middleInitial":"W.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":809212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fiorentino, Anthony J","contributorId":248465,"corporation":false,"usgs":false,"family":"Fiorentino","given":"Anthony","email":"","middleInitial":"J","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":809213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siegel, Donald I.","contributorId":178130,"corporation":false,"usgs":false,"family":"Siegel","given":"Donald","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":809214,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216707,"text":"70216707 - 2018 - Dual-phase mass balance modeling of small mineral particle losses from sedimentary rock-derived soils","interactions":[],"lastModifiedDate":"2020-12-01T23:49:24.495158","indexId":"70216707","displayToPublicDate":"2017-12-06T17:45:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Dual-phase mass balance modeling of small mineral particle losses from sedimentary rock-derived soils","docAbstract":"Losses of small mineral particles can be a significant physical process that affects the elemental composition of soils derived from sedimentary rocks. Shales, in particular, contain abundant clay-sized minerals that can be mobilized by simple disaggregation, and solutional weathering is limited because the parent rock is composed primarily of recalcitrant minerals previously subjected to continental weathering. Here, the dual-phase mass balance model is employed to quantify losses of small mineral particles as water dispersible colloids (WDCs) from three previously studied soil profiles along a hill slope at the Susquehanna Shale Hills Critical Zone Observatory (SSHO). WDCs were isolated from soil in the laboratory to determine their mineralogical and elemental compositions. Clay minerals dominated WDCs, including illite, vermiculite, and chlorite inherited from the parent shale, along with neoformed kaolinite. Quartz present in bulk soil was generally excluded from WDCs. Elements of low solubility and/or bound in recalcitrant forms, like Rb in illite, were employed in tracer ratios in the dual-phase model. Aluminum, Ga, and Rb were enriched in WDCs, and Zr and Hf were partially excluded. Six different combinations of elements into tracer ratios (Al/Zr, Ga/Zr, Rb/Zr, Al/Hf, Ga/Hf, Rb/Hf) each yielded similar model results. Mass losses of WDCs were large, ranging from − 68 ± 7% to − 15 ± 5% relative to soil parent material in different parts of the profiles. Mass losses via solution were smaller, ranging from − 7 ± 2% to a gain of 6 ± 1% in part of one profile. Losses of WDCs account for > 90% of total mass loss, surpassing chemical dissolution, and therefore dominate the weathering portion of denudation at SSHO. Zirconium concentrations were 97–158 ppm in the generally ≤ 1 μm WDCs, suggesting colloidal, Zr-bearing phases. Model-quantified losses of Zr via WDCs were large, with a median loss of 41% relative to parent material. Such losses indicate systematic underestimates of weathering by traditional mass balance that uses Zr as an index element. Losses of Ca, Mg, and K via WDCs exceeded losses via solution, countering assumptions of base cation losses primarily via mineral dissolution. The results illustrate a geochemical fingerprint of physical weathering and the ability of the dual-phase model to quantify that weathering process.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2017.11.040","usgsCitation":"Bern, C.R., and Yesavage, T., 2018, Dual-phase mass balance modeling of small mineral particle losses from sedimentary rock-derived soils: Chemical Geology, v. 476, p. 441-455, https://doi.org/10.1016/j.chemgeo.2017.11.040.","productDescription":"15 p.","startPage":"441","endPage":"455","ipdsId":"IP-082614","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":380911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"476","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bern, Carleton R. 0000-0002-8980-1781 cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":201152,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yesavage, Tiffany","contributorId":175456,"corporation":false,"usgs":false,"family":"Yesavage","given":"Tiffany","affiliations":[{"id":27571,"text":"USGS volunteer","active":true,"usgs":false}],"preferred":false,"id":805956,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223128,"text":"70223128 - 2018 - The timing and origin of pre- and post-caldera volcanism associated with the Mesa Falls Tuff, Yellowstone Plateau volcanic field","interactions":[],"lastModifiedDate":"2021-08-11T20:47:46.785575","indexId":"70223128","displayToPublicDate":"2017-12-06T15:36:01","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":"The timing and origin of pre- and post-caldera volcanism associated with the Mesa Falls Tuff, Yellowstone Plateau volcanic field","docAbstract":"We present new sanidine 40Ar/39Ar ages and paleomagnetic data for pre- and post-caldera rhyolites from the second volcanic cycle of the Yellowstone Plateau volcanic field, which culminated in the caldera-forming eruption of the Mesa Falls Tuff at ca. 1.3 Ma. These data allow for a detailed reconstruction of the eruptive history of the second volcanic cycle and provide new insights into the petrogenesis of rhyolite domes and flows erupted during this time period. 40Ar/39Ar age data for the biotite-bearing Bishop Mountain flow demonstrate that it erupted approximately 150 kyr prior to the Mesa Falls Tuff. Integrating 40Ar/39Ar ages and paleomagnetic data for the post-caldera Island Park rhyolite domes suggests that these five crystal-rich rhyolites erupted over a centuries-long time interval at 1.2905 ± 0.0020 Ma (2σ). The biotite-bearing Moonshine Mountain rhyolite dome was originally thought to be the downfaulted vent dome for the pre-caldera Bishop Mountain flow due to their similar petrographic and oxygen isotope characteristics, but new 40Ar/39Ar dating suggest that it erupted near contemporaneously with the Island Park rhyolite domes at 1.2931 ± 0.0018 Ma (2σ) and is a post-caldera eruption. Despite their similar eruption ages, the Island Park rhyolite domes and the Moonshine Mountain dome are chemically and petrographically distinct and are not derived from the same source. Integrating these new data with field relations and existing geochemical data, we present a petrogenetic model for the formation of the post-Mesa Falls Tuff rhyolites. Renewed influx of basaltic and/or silicic recharge magma into the crust at 1.2905 ± 0.0020 Ma led to [1] the formation of the Island Park rhyolite domes from the source region that earlier produced the Mesa Falls Tuff and [2] the formation of Moonshine Mountain dome from the source region that earlier produced the biotite-bearing Bishop Mountain flow. These magmas were stored in the crust for less than a few thousand years before being erupted contemporaneously along a 30 km long, structurally controlled vent zone related to extracaldera Basin and Range faults. These data highlight the rapidity with which magma can be generated and erupted over large distances at Yellowstone.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.12.002","usgsCitation":"Stelten, M.E., Champion, D.E., and Kuntz, M.A., 2018, The timing and origin of pre- and post-caldera volcanism associated with the Mesa Falls Tuff, Yellowstone Plateau volcanic field: Journal of Volcanology and Geothermal Research, v. 350, p. 47-60, https://doi.org/10.1016/j.jvolgeores.2017.12.002.","productDescription":"14 p.","startPage":"47","endPage":"60","ipdsId":"IP-090651","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469148,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2017.12.002","text":"Publisher Index Page"},{"id":438064,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MSBGDW","text":"USGS data release","linkHelpText":"Ar isotope data for pre- and post-caldera rhyolites associated with the Mesa Falls Tuff, Yellowstone Plateau volcanic field"},{"id":387883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Wyoming","otherGeospatial":"Mesa Falls Tuff, Yellowstone Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.03857421875,\n 43.75919263886012\n ],\n [\n -109.86602783203125,\n 43.75919263886012\n ],\n [\n -109.86602783203125,\n 44.84223815129917\n ],\n [\n -112.03857421875,\n 44.84223815129917\n ],\n [\n -112.03857421875,\n 43.75919263886012\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"350","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":821070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champion, Duane E. 0000-0001-7854-9034 dchamp@usgs.gov","orcid":"https://orcid.org/0000-0001-7854-9034","contributorId":2912,"corporation":false,"usgs":true,"family":"Champion","given":"Duane","email":"dchamp@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":821071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuntz, Mel A. 0000-0001-8828-5474","orcid":"https://orcid.org/0000-0001-8828-5474","contributorId":264175,"corporation":false,"usgs":true,"family":"Kuntz","given":"Mel","email":"","middleInitial":"A.","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":821072,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194586,"text":"70194586 - 2018 - From salmon to shad: Shifting sources of marine-derived nutrients in the Columbia River Basin","interactions":[],"lastModifiedDate":"2017-12-08T10:27:17","indexId":"70194586","displayToPublicDate":"2017-12-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"From salmon to shad: Shifting sources of marine-derived nutrients in the Columbia River Basin","docAbstract":"Like Pacific salmon (Oncorhynchus spp.), nonnative American shad (Alosa sapidissima) have the potential to convey large quantities of nutrients between the Pacific Ocean and freshwater spawning areas in the Columbia River Basin (CRB). American shad are now the most numerous anadromous fish in the CRB, yet the magnitude of the resulting nutrient flux owing to the shift from salmon to shad is unknown. Nutrient flux models revealed that American shad conveyed over 15,000 kg of nitrogen (N) and 3,000 kg of phosphorus (P) annually to John Day Reservoir, the largest mainstem reservoir in the lower Columbia River. Shad were net importers of N, with juveniles and postspawners exporting just 31% of the N imported by adults. Shad were usually net importers of P, with juveniles and postspawners exporting 46% of the P imported by adults on average. American shad contributed <0.2% of the total annual P load into John Day Reservoir, but during June when most adult shad are migrating into John Day Reservoir, they contributed as much as 2.0% of the P load. Nutrient inputs by American shad were similar to current but far less than historical inputs of Pacific salmon owing to their smaller size. Given the relatively high background P levels and low retention times in lower Columbia River reservoirs, it is unlikely that shad marine-derived nutrients affect nutrient balances or food web productivity through autotrophic pathways. However, a better understanding of shad spawning aggregations in the CRB is needed.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12348","usgsCitation":"Haskell, C.A., 2018, From salmon to shad: Shifting sources of marine-derived nutrients in the Columbia River Basin: Ecology of Freshwater Fish, v. 27, no. 1, p. 310-322, https://doi.org/10.1111/eff.12348.","productDescription":"13 p.","startPage":"310","endPage":"322","ipdsId":"IP-083307","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":469149,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12348","text":"Publisher Index Page"},{"id":349864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Columbia River, John Day Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.29993629455566,\n 45.94380909875069\n ],\n [\n -119.37572479248045,\n 45.93563185238015\n ],\n [\n -119.50069427490233,\n 45.91604931139518\n ],\n [\n -119.55631256103516,\n 45.93563185238015\n ],\n [\n -119.62841033935548,\n 45.92822950933618\n ],\n [\n -119.69158172607422,\n 45.90076057374647\n ],\n [\n -119.75784301757811,\n 45.86228122137575\n ],\n [\n -119.84264373779295,\n 45.874473216900626\n ],\n [\n -119.90684509277344,\n 45.845542755655856\n ],\n [\n -119.97928619384766,\n 45.83023460679437\n ],\n [\n -120.02735137939453,\n 45.8149222464981\n ],\n [\n -120.11592864990234,\n 45.790748860419896\n ],\n [\n -120.17360687255861,\n 45.77374940971673\n ],\n [\n -120.2065658569336,\n 45.75075599455506\n ],\n [\n -120.24089813232422,\n 45.73446325857703\n ],\n [\n -120.28209686279295,\n 45.730868632600014\n ],\n [\n -120.32604217529295,\n 45.7205627558654\n ],\n [\n -120.40603637695312,\n 45.71097418682745\n ],\n [\n -120.4695510864258,\n 45.70498049568787\n ],\n [\n -120.50525665283203,\n 45.71121392110517\n ],\n [\n -120.52808761596681,\n 45.731827222149356\n ],\n [\n -120.55675506591797,\n 45.74656346539698\n ],\n [\n -120.59640884399413,\n 45.75339113741727\n ],\n [\n -120.63074111938477,\n 45.75231313946647\n ],\n [\n -120.66267013549805,\n 45.74404779674727\n ],\n [\n -120.69013595581055,\n 45.73398398848103\n ],\n [\n -120.70421218872069,\n 45.72212074293355\n ],\n [\n -120.68601608276367,\n 45.70725817402955\n ],\n [\n -120.65460205078125,\n 45.72355884628182\n ],\n [\n -120.60104370117186,\n 45.729191061299915\n ],\n [\n -120.49530029296875,\n 45.68603620740324\n ],\n [\n -120.38131713867186,\n 45.68315803253308\n ],\n [\n -120.20416259765625,\n 45.71097418682745\n ],\n [\n -120.04417419433594,\n 45.786679041363726\n ],\n [\n -119.92263793945312,\n 45.81540082150529\n ],\n [\n -119.83268737792967,\n 45.83358362421937\n ],\n [\n -119.73930358886717,\n 45.82640691154487\n ],\n [\n -119.65896606445312,\n 45.84219445795288\n ],\n [\n -119.58755493164061,\n 45.90434424945917\n ],\n [\n -119.52850341796875,\n 45.89598197962566\n ],\n [\n -119.42276000976562,\n 45.90601655229453\n ],\n [\n -119.29512977600098,\n 45.9273339976278\n ],\n [\n -119.29993629455566,\n 45.94380909875069\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-16","publicationStatus":"PW","scienceBaseUri":"5a60fad5e4b06e28e9c22779","contributors":{"authors":[{"text":"Haskell, Craig A. 0000-0002-3604-1758 chaskell@usgs.gov","orcid":"https://orcid.org/0000-0002-3604-1758","contributorId":3458,"corporation":false,"usgs":true,"family":"Haskell","given":"Craig","email":"chaskell@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":724576,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70194638,"text":"70194638 - 2018 - The influence of bed friction variability due to land cover on storm-driven barrier island morphodynamics","interactions":[],"lastModifiedDate":"2017-12-07T16:37:20","indexId":"70194638","displayToPublicDate":"2017-12-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"The influence of bed friction variability due to land cover on storm-driven barrier island morphodynamics","docAbstract":"Variations in bed friction due to land cover type have the potential to influence morphologic change during storm events; the importance of these variations can be studied through numerical simulation and experimentation at locations with sufficient observational data to initialize realistic scenarios, evaluate model accuracy and guide interpretations. Two-dimensional in the horizontal plane (2DH) morphodynamic (XBeach) simulations were conducted to assess morphodynamic sensitivity to spatially varying bed friction at Dauphin Island, AL using hurricanes Ivan (2004) and Katrina (2005) as experimental test cases. For each storm, three bed friction scenarios were simulated: (1) a constant Chezy coefficient across land and water, (2) a constant Chezy coefficient across land and depth-dependent Chezy coefficients across water, and (3) spatially varying Chezy coefficients across land based on land use/land cover (LULC) data and depth-dependent Chezy coefficients across water. Modeled post-storm bed elevations were compared qualitatively and quantitatively with post-storm lidar data. Results showed that implementing spatially varying bed friction influenced the ability of XBeach to accurately simulate morphologic change during both storms. Accounting for frictional effects due to large-scale variations in vegetation and development reduced cross-barrier sediment transport and captured overwash and breaching more accurately. Model output from the spatially varying friction scenarios was used to examine the need for an existing sediment transport limiter, the influence of pre-storm topography and the effects of water level gradients on storm-driven morphodynamics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2017.11.005","usgsCitation":"Passeri, D., Long, J.W., Plant, N.G., Bilskie, M.V., and Hagen, S.C., 2018, The influence of bed friction variability due to land cover on storm-driven barrier island morphodynamics: Coastal Engineering, v. 132, p. 82-94, https://doi.org/10.1016/j.coastaleng.2017.11.005.","productDescription":"13 p.","startPage":"82","endPage":"94","ipdsId":"IP-088110","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469150,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2017.11.005","text":"Publisher Index Page"},{"id":349878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.36509704589844,\n 30.19202472180581\n ],\n [\n -88.06777954101562,\n 30.19202472180581\n ],\n [\n -88.06777954101562,\n 30.295832146790442\n ],\n [\n -88.36509704589844,\n 30.295832146790442\n ],\n [\n -88.36509704589844,\n 30.19202472180581\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad5e4b06e28e9c22776","contributors":{"authors":[{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":724686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":724687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":724688,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bilskie, Matthew V.","contributorId":166891,"corporation":false,"usgs":false,"family":"Bilskie","given":"Matthew","email":"","middleInitial":"V.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":724689,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hagen, Scott C.","contributorId":166890,"corporation":false,"usgs":false,"family":"Hagen","given":"Scott","email":"","middleInitial":"C.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":724690,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194556,"text":"70194556 - 2018 - Loss of dendritic connectivity in southern California's urban riverscape facilitates decline of an endemic freshwater fish","interactions":[],"lastModifiedDate":"2018-03-26T14:26:39","indexId":"70194556","displayToPublicDate":"2017-12-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Loss of dendritic connectivity in southern California's urban riverscape facilitates decline of an endemic freshwater fish","docAbstract":"Life history adaptations and spatial configuration of metapopulation networks allow certain species to persist in extreme fluctuating environments, yet long-term stability within these systems relies on the maintenance of linkage habitat. Degradation of such linkages in urban riverscapes can disrupt this dynamic in aquatic species, leading to increased extinction debt in local populations experiencing environment-related demographic flux. We used microsatellites and mtDNA to examine the effects of collapsed network structure in the endemic Santa Ana sucker Catostomus santaanae of southern California, a threatened species affected by natural flood-drought cycles, ‘boom-and-bust’ demography, hybridization, and presumed artificial transplantation. Our results show a predominance of drift-mediated processes in shaping population structure, and that reverse mechanisms for counterbalancing the genetic effects of these phenomena have dissipated with the collapse of dendritic connectivity. We use approximate Bayesian models to support two cases of artificial transplantation, and provide evidence that one of the invaded systems better represents the historic processes that maintained genetic variation within watersheds than any remaining drainages where C. santaanae is considered native. We further show that a stable dry gap in the northern range is preventing genetic dilution of pure C. santaanae persisting upstream of a hybrid assemblage involving a non-native sucker, and that local accumulation of genetic variation in the same drainage is influenced by position within the network. This work has important implications for declining species that have historically relied on dendritic metapopulation networks to maintain source-sink dynamics in phasic environments, but no longer possess this capacity in urban-converted landscapes.","language":"English","publisher":"Wiley","doi":"10.1111/mec.14445","usgsCitation":"Richmond, J.Q., Backlin, A.R., Galst-Cavalcante, C., O’Brien, J.W., and Fisher, R.N., 2018, Loss of dendritic connectivity in southern California's urban riverscape facilitates decline of an endemic freshwater fish: Molecular Ecology, v. 27, no. 2, p. 369-386, https://doi.org/10.1111/mec.14445.","productDescription":"18 p.","startPage":"369","endPage":"386","ipdsId":"IP-079187","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438065,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z31XMZ","text":"USGS data release","linkHelpText":"Microsatellite genotype scores for a contemporary, range-wide sample of Santa Ana sucker in southern California"},{"id":349687,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"27","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-27","publicationStatus":"PW","scienceBaseUri":"5a60faf4e4b06e28e9c229f8","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":724455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":724456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galst-Cavalcante, Carey","contributorId":201155,"corporation":false,"usgs":false,"family":"Galst-Cavalcante","given":"Carey","email":"","affiliations":[],"preferred":false,"id":724457,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Brien, John W.","contributorId":201156,"corporation":false,"usgs":false,"family":"O’Brien","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":724458,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":724454,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194515,"text":"70194515 - 2018 - Estimating the per-capita contribution of habitats and pathways in a migratory network: A modelling approach","interactions":[],"lastModifiedDate":"2018-04-27T16:47:13","indexId":"70194515","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the per-capita contribution of habitats and pathways in a migratory network: A modelling approach","docAbstract":"Every year, migratory species undertake seasonal movements along different pathways between discrete regions and habitats. The ability to assess the relative demographic contributions of these different habitats and pathways to the species’ overall population dynamics is critical for understanding the ecology of migratory species, and also has practical applications for management and conservation. Metrics for assessing habitat contributions have been well-developed for metapopulations, but an equivalent metric is not currently available for migratory populations. Here, we develop a framework for estimating the demographic contributions of the discrete habitats and pathways used by migratory species throughout the annual cycle by estimating the per capita contribution of cohorts using these locations. Our framework accounts for seasonal movements between multiple breeding and non-breeding habitats and for both resident and migratory cohorts. We illustrate our framework using a hypothetical migratory network of four habitats, which allows us to better understand how variations in habitat quality affect per capita contributions. Results indicate that per capita contributions for any habitat or pathway are dependent on habitat-specific survival probabilities in all other areas used as part of the migratory circuit, and that contribution metrics are spatially linked (e.g. reduced survival in one habitat also decreases the contribution metric for other habitats). Our framework expands existing theory on the dynamics of spatiotemporally structured populations by developing a generalized approach to estimate the habitat- and pathway-specific contributions of species migrating between multiple breeding and multiple non-breeding habitats for a range of life histories or migratory strategies. Most importantly, it provides a means of prioritizing conservation efforts towards those migratory pathways and habitats that are most critical for the population viability of migratory species.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.02718","usgsCitation":"Wiederholt, R., Mattsson, B.J., Thogmartin, W.E., Runge, M.C., Diffendorfer, J.E., Erickson, R.A., Federico, P., Lopez-Hoffman, L., Fryxell, J., Norris, D.R., and Sample, C., 2018, Estimating the per-capita contribution of habitats and pathways in a migratory network: A modelling approach: Ecography, v. 41, no. 5, p. 815-824, https://doi.org/10.1111/ecog.02718.","productDescription":"10 p.","startPage":"815","endPage":"824","ipdsId":"IP-076968","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":349625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-21","publicationStatus":"PW","scienceBaseUri":"5a60faf7e4b06e28e9c22a32","contributors":{"authors":[{"text":"Wiederholt, Ruscena","contributorId":149125,"corporation":false,"usgs":false,"family":"Wiederholt","given":"Ruscena","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":724217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mattsson, Brady J.","contributorId":201057,"corporation":false,"usgs":false,"family":"Mattsson","given":"Brady","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":724218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":724216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":724219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diffendorfer, Jay E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":55137,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"Jay","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":724220,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":724221,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Federico, Paula","contributorId":201058,"corporation":false,"usgs":false,"family":"Federico","given":"Paula","email":"","affiliations":[],"preferred":false,"id":724222,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":724223,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fryxell, John","contributorId":201059,"corporation":false,"usgs":false,"family":"Fryxell","given":"John","email":"","affiliations":[],"preferred":false,"id":724224,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Norris, D. Ryan","contributorId":59734,"corporation":false,"usgs":true,"family":"Norris","given":"D.","email":"","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":724225,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sample, Christine","contributorId":201060,"corporation":false,"usgs":false,"family":"Sample","given":"Christine","email":"","affiliations":[],"preferred":false,"id":724226,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70194518,"text":"70194518 - 2018 - Inferring epidemiologic dynamics from viral evolution: 2014–2015 Eurasian/North American highly pathogenic avian influenza viruses exceed transmission threshold, R0 = 1, in wild birds and poultry in North America","interactions":[],"lastModifiedDate":"2018-04-17T12:36:20","indexId":"70194518","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Inferring epidemiologic dynamics from viral evolution: 2014–2015 Eurasian/North American highly pathogenic avian influenza viruses exceed transmission threshold, R0 = 1, in wild birds and poultry in North America","title":"Inferring epidemiologic dynamics from viral evolution: 2014–2015 Eurasian/North American highly pathogenic avian influenza viruses exceed transmission threshold, R0 = 1, in wild birds and poultry in North America","docAbstract":"Highly pathogenic avian influenza virus (HPAIV) is a multihost pathogen with lineages that pose health risks for domestic birds, wild birds, and humans. One mechanism of intercontinental HPAIV spread is through wild bird reservoirs, and wild birds were the likely sources of a Eurasian (EA) lineage HPAIV into North America in 2014. The introduction resulted in several reassortment events with North American (NA) lineage low-pathogenic avian influenza viruses and the reassortant EA/NA H5N2 went on to cause one of the largest HPAIV poultry outbreaks in North America. We evaluated three hypotheses about novel HPAIV introduced into wild and domestic bird hosts: (i) transmission of novel HPAIVs in wild birds was restricted by mechanisms associated with highly pathogenic phenotypes; (ii) the HPAIV poultry outbreak was not self-sustaining and required viral input from wild birds; and (iii) reassortment of the EA H5N8 generated reassortant EA/NA AIVs with a fitness advantage over fully Eurasian lineages in North American wild birds. We used a time-rooted phylodynamic model that explicitly incorporated viral population dynamics with evolutionary dynamics to estimate the basic reproductive number (R0) and viral migration among host types in domestic and wild birds, as well as between the EA H5N8 and EA/NA H5N2 in wild birds. We did not find evidence to support hypothesis (i) or (ii) as our estimates of the transmission parameters suggested that the HPAIV outbreak met or exceeded the threshold for persistence in wild birds (R0 > 1) and poultry (R0 ≈ 1) with minimal estimated transmission among host types. There was also no evidence to support hypothesis (iii) because R0 values were similar among EA H5N8 and EA/NA H5N2 in wild birds. Our results suggest that this novel HPAIV and reassortments did not encounter any transmission barriers sufficient to prevent persistence when introduced to wild or domestic birds.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.12576","usgsCitation":"Grear, D.R., Hall, J.S., Dusek, R.J., and Ip, S., 2018, Inferring epidemiologic dynamics from viral evolution: 2014–2015 Eurasian/North American highly pathogenic avian influenza viruses exceed transmission threshold, R0 = 1, in wild birds and poultry in North America: Evolutionary Applications, v. 11, no. 4, p. 547-557, https://doi.org/10.1111/eva.12576.","productDescription":"11 p.","startPage":"547","endPage":"557","ipdsId":"IP-084949","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":461103,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.12576","text":"Publisher Index Page"},{"id":349623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf7e4b06e28e9c22a2c","contributors":{"authors":[{"text":"Grear, Daniel R. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":201066,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":725397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":724244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":174374,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":724245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ip, S. 0000-0003-4844-7533 hip@usgs.gov","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":727,"corporation":false,"usgs":true,"family":"Ip","given":"S.","email":"hip@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":724246,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194344,"text":"70194344 - 2018 - Viscous relaxation as a prerequisite for tectonic resurfacing on Ganymede: Insights from numerical models of lithospheric extension","interactions":[],"lastModifiedDate":"2018-03-19T11:25:07","indexId":"70194344","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Viscous relaxation as a prerequisite for tectonic resurfacing on Ganymede: Insights from numerical models of lithospheric extension","docAbstract":"Ganymede’s bright terrain formed during a near-global resurfacing event (or events) that produced both heavily tectonized and relatively smooth terrains. The mechanism(s) by which resurfacing occurred on Ganymede (e.g., cryovolcanic or tectonic), and the relationship between the older, dark and the younger, bright terrain are fundamental to understanding the geological evolution of the satellite. Using a two-dimensional numerical model of lithospheric extension that has previously been used to successfully simulate surface deformation consistent with grooved terrain morphologies, we investigate whether large-amplitude preexisting topography can be resurfaced (erased) by extension (i.e., tectonic resurfacing). Using synthetically produced initial topography, we show that when the total relief of the initial topography is larger than 25–50 m, periodic groove-like structures fail to form. Instead, extension is localized in a few individual, isolated troughs. These results pose a challenge to the tectonic resurfacing hypothesis. We further investigate the effects of preexisting topography by performing suites of simulations initialized with topography derived from digital terrain models of Ganymede’s surface. These include dark terrain, fresh (relatively deep) impact craters, smooth bright terrain, and a viscously relaxed impact crater. The simulations using dark terrain and fresh impact craters are consistent with our simulations using synthetic topography: periodic groove-like deformation fails to form. In contrast, when simulations were initialized with bright smooth terrain topography, groove-like deformation results from a wide variety of heat flow and surface temperature conditions. Similarly, when a viscously relaxed impact crater was used, groove-like structures were able to form during extension. These results suggest that tectonic resurfacing may require that the amplitude of the initial topography be reduced before extension begins. We emphasize that viscous relaxation may be the key to enabling tectonic resurfacing, as the heat fluxes associated with groove terrain formation are also capable of reducing crater topography through viscous relaxation. For long-wavelength topography (large craters) viscous relaxation is unavoidable. We propose that the resurfacing of Ganymede occurred through a combination of viscous relaxation, tectonic resurfacing, cryovolcanism and, at least in a few cases, band formation. Variations in heat flow and strain magnitudes across Ganymede likely produced the complex variety of terrain types currently observed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2017.10.017","usgsCitation":"Bland, M.T., and McKinnon, W.B., 2018, Viscous relaxation as a prerequisite for tectonic resurfacing on Ganymede: Insights from numerical models of lithospheric extension: Icarus, v. 306, p. 285-305, https://doi.org/10.1016/j.icarus.2017.10.017.","productDescription":"21 p.","startPage":"285","endPage":"305","ipdsId":"IP-085490","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":349426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"306","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ad7","contributors":{"authors":[{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":723383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKinnon, William B.","contributorId":196152,"corporation":false,"usgs":false,"family":"McKinnon","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":16661,"text":"Washington University in Saint Louis","active":true,"usgs":false}],"preferred":false,"id":723384,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194450,"text":"70194450 - 2018 - Characterizing storm response and recovery using the beach change envelope: Fire Island, New York","interactions":[],"lastModifiedDate":"2017-11-29T13:02:00","indexId":"70194450","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing storm response and recovery using the beach change envelope: Fire Island, New York","docAbstract":"Hurricane Sandy at Fire Island, New York presented unique challenges in the quantification of storm impacts using traditional metrics of coastal change, wherein measured changes (shoreline, dune crest, and volume change) did not fully reflect the substantial changes in sediment redistribution following the storm. We used a time series of beach profile data at Fire Island, New York to define a new contour-based morphologic change metric, the Beach Change Envelope (BCE). The BCE quantifies changes to the upper portion of the beach likely to sustain measurable impacts from storm waves and capture a variety of storm and post-storm beach states. We evaluated the ability of the BCE to characterize cycles of beach change by relating it to a conceptual beach recovery regime, and demonstrated that BCE width and BCE height from the profile time series correlate well with established stages of recovery. We also investigated additional applications of this metric to capture impacts from storms and human modification by applying it to several post-storm historical datasets in which impacts varied considerably; Nor'Ida (2009), Hurricane Irene (2011), Hurricane Sandy (2012), and a 2009 community replenishment. In each case, the BCE captured distinctive upper beach morphologic change characteristic of these different beach building and erosional events. Analysis of the beach state at multiple profile locations showed spatial trends in recovery consistent with recent morphologic island evolution, which other studies have linked with sediment availability and the geologic framework. Ultimately we demonstrate a new way of more effectively characterizing beach response and recovery cycles to evaluate change along sandy coasts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2017.08.004","usgsCitation":"Brenner, O.T., Lentz, E.E., Hapke, C.J., Henderson, R.E., Wilson, K., and Nelson, T., 2018, Characterizing storm response and recovery using the beach change envelope: Fire Island, New York: Geomorphology, v. 300, p. 189-202, https://doi.org/10.1016/j.geomorph.2017.08.004.","productDescription":"14 p.","startPage":"189","endPage":"202","ipdsId":"IP-081355","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":461105,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2017.08.004","text":"Publisher Index Page"},{"id":349532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.2242202758789,\n 40.62177060472069\n ],\n [\n -73.14216613769531,\n 40.62177060472069\n ],\n [\n -73.14216613769531,\n 40.65485736139743\n ],\n [\n -73.2242202758789,\n 40.65485736139743\n ],\n [\n -73.2242202758789,\n 40.62177060472069\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"300","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad6e4b06e28e9c22791","contributors":{"authors":[{"text":"Brenner, Owen T. 0000-0002-1588-721X obrenner@usgs.gov","orcid":"https://orcid.org/0000-0002-1588-721X","contributorId":4933,"corporation":false,"usgs":true,"family":"Brenner","given":"Owen","email":"obrenner@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":723886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":723889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":723887,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henderson, Rachel E. 0000-0001-5810-7941 rehenderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5810-7941","contributorId":194022,"corporation":false,"usgs":true,"family":"Henderson","given":"Rachel","email":"rehenderson@usgs.gov","middleInitial":"E.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":723890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Kathleen 0000-0002-2810-7585 kwilson@usgs.gov","orcid":"https://orcid.org/0000-0002-2810-7585","contributorId":195620,"corporation":false,"usgs":true,"family":"Wilson","given":"Kathleen","email":"kwilson@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":723888,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nelson, Timothy 0000-0002-5005-7617 trnelson@usgs.gov","orcid":"https://orcid.org/0000-0002-5005-7617","contributorId":191933,"corporation":false,"usgs":true,"family":"Nelson","given":"Timothy","email":"trnelson@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":723891,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194430,"text":"70194430 - 2018 - Living on the edge: Opportunities for Amur tiger recovery in China","interactions":[],"lastModifiedDate":"2018-07-26T13:08:41","indexId":"70194430","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Living on the edge: Opportunities for Amur tiger recovery in China","docAbstract":"Sporadic sightings of the endangered Amur tiger Panthera tigris altaica along the China-Russia border during the late 1990s sparked efforts to expand this subspecies distribution and abundance by restoring potentially suitable habitats in the Changbai Mountains. To guide science-based recovery efforts and provide a baseline for future monitoring of this border population, empirical, quantitative information is needed on what resources and management practices promote or limit the occurrence of tigers in the region. We established a large-scale field camera-trapping network to estimate tiger density, survival and recruitment in the Hunchun Nature Reserve and the surrounding area using an open population spatially explicit capture-recapture model. We then fitted an occupancy model that accounted for detectability and spatial autocorrelation to assess the relative influence of habitat, major prey, disturbance and management on tiger habitat use patterns. Our results show that the ranges of most tigers abut the border with Russia. Tiger densities ranged between 0.20 and 0.27 individuals/100 km2 over the study area; in the Hunchun Nature Reserve, the tiger density was three times higher than that in the surrounding inland forested area. Tiger occupancy was strongly negatively related to heavy cattle grazing, human settlements and roads and was positively associated with sika deer abundance and vegetation cover. These findings can help to identify the drivers of tiger declines and dispersal limits and refine strategies for tiger conservation in the human-dominated transboundary landscape. Progressively alleviating the impacts of cattle and human disturbances on the forest, and simultaneously addressing the economic needs of local communities, should be key priority actions to increase tiger populations. The long-term goal is to expand tiger distribution by improving habitats for large ungulates.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2017.11.008","usgsCitation":"Wang, T., Royle, A., Smith, J., Zou, L., Lu, X., Li, T., Yang, H., Li, Z., Feng, R., Bian, Y., Feng, L., and Ge, J., 2018, Living on the edge: Opportunities for Amur tiger recovery in China: Biological Conservation, v. 217, p. 269-279, https://doi.org/10.1016/j.biocon.2017.11.008.","productDescription":"11 p.","startPage":"269","endPage":"279","ipdsId":"IP-090114","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":349415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","state":"Jilin Province","otherGeospatial":"Changbai Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 129.869384765625,\n 42.35042512243457\n ],\n [\n 131.19873046875,\n 42.35042512243457\n ],\n [\n 131.19873046875,\n 43.27720532212024\n ],\n [\n 129.869384765625,\n 43.27720532212024\n ],\n [\n 129.869384765625,\n 42.35042512243457\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"217","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fafee4b06e28e9c22ac2","contributors":{"authors":[{"text":"Wang, Tianming","contributorId":200892,"corporation":false,"usgs":false,"family":"Wang","given":"Tianming","email":"","affiliations":[],"preferred":false,"id":723742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":723741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, J.L.D.","contributorId":18480,"corporation":false,"usgs":true,"family":"Smith","given":"J.L.D.","email":"","affiliations":[],"preferred":false,"id":723743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zou, Liang","contributorId":200894,"corporation":false,"usgs":false,"family":"Zou","given":"Liang","email":"","affiliations":[],"preferred":false,"id":723744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lu, Xinyue","contributorId":200895,"corporation":false,"usgs":false,"family":"Lu","given":"Xinyue","email":"","affiliations":[],"preferred":false,"id":723745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Tong","contributorId":200896,"corporation":false,"usgs":false,"family":"Li","given":"Tong","email":"","affiliations":[],"preferred":false,"id":723746,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yang, Haitao","contributorId":200897,"corporation":false,"usgs":false,"family":"Yang","given":"Haitao","email":"","affiliations":[],"preferred":false,"id":723747,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Li, Zhilin","contributorId":200898,"corporation":false,"usgs":false,"family":"Li","given":"Zhilin","email":"","affiliations":[],"preferred":false,"id":723748,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Feng, Rongna","contributorId":200899,"corporation":false,"usgs":false,"family":"Feng","given":"Rongna","email":"","affiliations":[],"preferred":false,"id":723749,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bian, Yajing","contributorId":200900,"corporation":false,"usgs":false,"family":"Bian","given":"Yajing","email":"","affiliations":[],"preferred":false,"id":723750,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Feng, Limin","contributorId":200901,"corporation":false,"usgs":false,"family":"Feng","given":"Limin","email":"","affiliations":[],"preferred":false,"id":723751,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ge, Jianping","contributorId":200902,"corporation":false,"usgs":false,"family":"Ge","given":"Jianping","email":"","affiliations":[],"preferred":false,"id":723752,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70194286,"text":"70194286 - 2018 - 6th international conference on Mars polar science and exploration: Conference summary and five top questions","interactions":[],"lastModifiedDate":"2018-05-04T15:21:15","indexId":"70194286","displayToPublicDate":"2017-11-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"6th international conference on Mars polar science and exploration: Conference summary and five top questions","docAbstract":"We provide a historical context of the International Conference on Mars Polar Science and Exploration and summarize the proceedings from the 6th iteration of this meeting. In particular, we identify five key Mars polar science questions based primarily on presentations and discussions at the conference and discuss the overlap between some of those questions. We briefly describe the seven scientific field trips that were offered at the conference, which greatly supplemented conference discussion of Mars polar processes and landforms. We end with suggestions for measurements, modeling, and laboratory and field work that were highlighted during conference discussion as necessary steps to address key knowledge gaps.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2017.06.027","usgsCitation":"Smith, I.B., Diniega, S., Beaty, D.W., Thorsteinsson, T., Becerra, P., Bramson, A., Clifford, S.M., Hvidberg, C.S., Portyankina, G., Piqueux, S., Spiga, A., and Titus, T.N., 2018, 6th international conference on Mars polar science and exploration: Conference summary and five top questions: Icarus, v. 308, p. 2-14, https://doi.org/10.1016/j.icarus.2017.06.027.","productDescription":"13 p.","startPage":"2","endPage":"14","ipdsId":"IP-081480","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":349272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"308","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb01e4b06e28e9c22af9","contributors":{"authors":[{"text":"Smith, Isaac B.","contributorId":200695,"corporation":false,"usgs":false,"family":"Smith","given":"Isaac","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":723084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diniega, Serina","contributorId":80532,"corporation":false,"usgs":true,"family":"Diniega","given":"Serina","affiliations":[],"preferred":false,"id":723085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beaty, David W.","contributorId":127511,"corporation":false,"usgs":false,"family":"Beaty","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":723086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorsteinsson, Thorsteinn","contributorId":200698,"corporation":false,"usgs":false,"family":"Thorsteinsson","given":"Thorsteinn","email":"","affiliations":[],"preferred":false,"id":723087,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Becerra, Patricio","contributorId":173341,"corporation":false,"usgs":false,"family":"Becerra","given":"Patricio","email":"","affiliations":[],"preferred":false,"id":723088,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bramson, Ali","contributorId":189477,"corporation":false,"usgs":false,"family":"Bramson","given":"Ali","email":"","affiliations":[],"preferred":false,"id":723089,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clifford, Stephen M.","contributorId":7984,"corporation":false,"usgs":true,"family":"Clifford","given":"Stephen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723090,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hvidberg, Christine S.","contributorId":200702,"corporation":false,"usgs":false,"family":"Hvidberg","given":"Christine","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":723091,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Portyankina, Ganna","contributorId":200703,"corporation":false,"usgs":false,"family":"Portyankina","given":"Ganna","email":"","affiliations":[],"preferred":false,"id":723092,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Piqueux, Sylvain","contributorId":56986,"corporation":false,"usgs":false,"family":"Piqueux","given":"Sylvain","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":723291,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Spiga, Aymeric","contributorId":200704,"corporation":false,"usgs":false,"family":"Spiga","given":"Aymeric","email":"","affiliations":[],"preferred":false,"id":723093,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":723083,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70222616,"text":"70222616 - 2018 - The 2015 Gorkha (Nepal) Earthquake sequence: I. Source modeling and deterministic 3D ground shaking","interactions":[],"lastModifiedDate":"2021-08-09T13:26:10.316998","indexId":"70222616","displayToPublicDate":"2017-11-21T08:21:12","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"The 2015 Gorkha (Nepal) Earthquake sequence: I. Source modeling and deterministic 3D ground shaking","docAbstract":"To better quantify the relatively long period (< 0.3 Hz) shaking experienced during the 2015 Gorkha (Nepal) earthquake sequence, we study the finite rupture processes and the associated 3D ground motion of the Mw7.8 mainshock and the Mw7.2 aftershock. The 3D synthetics are then used in the broadband ground shaking in Kathmandu with a hybrid approach, summarized in a companion paper (Chen and Wei, 2017, submitted together). We determined the coseismic rupture process of the mainshock by joint inversion of InSAR/SAR, GPS (static and high-rate), strong motion and teleseismic waveforms. Our inversion for the mainshock indicates unilateral rupture towards the ESE, with an average rupture speed of 3.0 km/s and a total duration of ~ 60 s. Additionally, we find that the beginning part of the rupture (5–18 s) has about 40% longer rise time than the rest of the rupture, as well as slower rupture velocity. Our model shows two strong asperities occurring ~ 24 s and ~ 36 s after the origin and located ~ 30 km to the northwest and northeast of the Kathmandu valley, respectively. In contrast, the Mw7.2 aftershock is more compact both in time and space, as revealed by joint inversion of teleseismic body waves and InSAR data. The different rupture features between the mainshock and the aftershock could be related to difference in fault zone structure. The mainshock and aftershock ground motions in the Kathmandu valley, recorded by both strong motion and high-rate GPS stations, exhibited strong amplification around 0.2 Hz. A simplified 3D basin model, calibrated by an Mw5.2 aftershock, can match the observed waveforms reasonably well at 0.3 Hz and lower frequency. The 3D simulations indicate that the basin structure trapped the wavefield and produced an extensive ground vibration. Our study suggests that the combination of rupture characteristics and propagational complexity are required to understand the ground shaking produced by hazardous earthquakes such as the Gorkha event.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2017.11.024","usgsCitation":"Wei, S., Chen, M., Wang, X., Graves, R., Lindsey, E., Wang, T., Karakas, C., and Helmberger, D., 2018, The 2015 Gorkha (Nepal) Earthquake sequence: I. Source modeling and deterministic 3D ground shaking: Tectonophysics, v. 722, p. 447-461, https://doi.org/10.1016/j.tecto.2017.11.024.","productDescription":"15 p.","startPage":"447","endPage":"461","ipdsId":"IP-090039","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.tecto.2017.11.024","text":"Publisher Index Page"},{"id":387776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 86.539306640625,\n 26.696545111585152\n ],\n [\n 86.802978515625,\n 27.848790459862073\n ],\n [\n 82.650146484375,\n 29.6594160549124\n ],\n [\n 82.034912109375,\n 28.159189634046708\n ],\n [\n 85.4296875,\n 27.127591028502078\n ],\n [\n 86.539306640625,\n 26.696545111585152\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"722","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wei, Shengji","contributorId":192953,"corporation":false,"usgs":false,"family":"Wei","given":"Shengji","email":"","affiliations":[],"preferred":false,"id":820768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Meng","contributorId":261912,"corporation":false,"usgs":false,"family":"Chen","given":"Meng","email":"","affiliations":[{"id":48937,"text":"Earth Observatory of Singapore, Nanyang Technological University, Singapore","active":true,"usgs":false}],"preferred":false,"id":820769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Xin","contributorId":177411,"corporation":false,"usgs":false,"family":"Wang","given":"Xin","email":"","affiliations":[],"preferred":false,"id":820770,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":820771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsey, Eric","contributorId":261913,"corporation":false,"usgs":false,"family":"Lindsey","given":"Eric","email":"","affiliations":[{"id":48937,"text":"Earth Observatory of Singapore, Nanyang Technological University, Singapore","active":true,"usgs":false}],"preferred":false,"id":820772,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Teng","contributorId":156235,"corporation":false,"usgs":false,"family":"Wang","given":"Teng","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":820773,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karakas, Cagil","contributorId":261914,"corporation":false,"usgs":false,"family":"Karakas","given":"Cagil","email":"","affiliations":[{"id":48937,"text":"Earth Observatory of Singapore, Nanyang Technological University, Singapore","active":true,"usgs":false}],"preferred":false,"id":820774,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Helmberger, Don","contributorId":192954,"corporation":false,"usgs":false,"family":"Helmberger","given":"Don","email":"","affiliations":[],"preferred":false,"id":820775,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70194250,"text":"70194250 - 2018 - A Holocene record of ocean productivity and upwelling from the northern California continental slope","interactions":[],"lastModifiedDate":"2018-04-27T16:49:28","indexId":"70194250","displayToPublicDate":"2017-11-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3217,"text":"Quaternary International","active":true,"publicationSubtype":{"id":10}},"title":"A Holocene record of ocean productivity and upwelling from the northern California continental slope","docAbstract":"The Holocene upwelling history of the northern California continental slope is examined using the high-resolution record of TN062-O550 (40.9°N, 124.6°W, 550 m water depth). This 7-m-long marine sediment core spans the last ∼7500 years, and we use it to test the hypothesis that marine productivity in the California Current System (CCS) driven by coastal upwelling has co-varied with Holocene millennial-scale warm intervals. A combination of biogenic sediment concentrations (opal, total organic C, and total N), stable isotopes (organic matter δ13C and bulk sedimentary δ15N), and key microfossil indicators of upwelling were used to test this hypothesis. The record of biogenic accumulation in TN062-O550 shows considerable Holocene variability despite being located within 50 km of the mouth of the Eel River, which is one of the largest sources of terrigenous sediment to the Northeast Pacific Ocean margin. A key time interval beginning at ∼2900 calibrated years before present (cal yr BP) indicates the onset of modern upwelling in the CCS, and this period also corresponds to the most intense period of upwelling in the last 7500 years. When these results are placed into a regional CCS context during the Holocene, it was found that the timing of upwelling intensification at TN062-O550 corresponds closely to that seen at nearby ODP Site 1019, as well as in the Santa Barbara Basin of southern California. Other CCS records with less refined age control show similar results, which suggest late Holocene upwelling intensification may be synchronous throughout the CCS. Based on the strong correspondence between the alkenone sea surface temperature record at ODP Site 1019 and the onset of late Holocene upwelling in northern California, we suggest that CCS warming may be conducive to upwelling intensification, though future changes are unclear as the mechanisms forcing SST variability may differ.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2017.02.021","usgsCitation":"Addison, J.A., Barron, J.A., Finney, B.P., Kusler, J.E., Bukry, D., Heusser, L.E., and Alexander, C.R., 2018, A Holocene record of ocean productivity and upwelling from the northern California continental slope: Quaternary International, v. 469, no. B, p. 96-108, https://doi.org/10.1016/j.quaint.2017.02.021.","productDescription":"13 p.","startPage":"96","endPage":"108","ipdsId":"IP-076086","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":461109,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quaint.2017.02.021","text":"Publisher Index Page"},{"id":349137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124,\n 40\n ],\n [\n -126,\n 40\n ],\n [\n -126,\n 42\n ],\n [\n -124,\n 42\n ],\n [\n -124,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"469","issue":"B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb03e4b06e28e9c22b0c","contributors":{"authors":[{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":722854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barron, John A. 0000-0002-9309-1145 jbarron@usgs.gov","orcid":"https://orcid.org/0000-0002-9309-1145","contributorId":2222,"corporation":false,"usgs":true,"family":"Barron","given":"John","email":"jbarron@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":722855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finney, Bruce P.","contributorId":199658,"corporation":false,"usgs":false,"family":"Finney","given":"Bruce","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":722858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kusler, Jennifer E. jkusler@usgs.gov","contributorId":5151,"corporation":false,"usgs":true,"family":"Kusler","given":"Jennifer","email":"jkusler@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":722857,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bukry, David 0000-0003-4540-890X dbukry@usgs.gov","orcid":"https://orcid.org/0000-0003-4540-890X","contributorId":3550,"corporation":false,"usgs":true,"family":"Bukry","given":"David","email":"dbukry@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":722856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Heusser, Linda E.","contributorId":178365,"corporation":false,"usgs":false,"family":"Heusser","given":"Linda","email":"","middleInitial":"E.","affiliations":[{"id":28041,"text":"Lamont-Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":722860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alexander, Clark R.","contributorId":149400,"corporation":false,"usgs":false,"family":"Alexander","given":"Clark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":722859,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216340,"text":"70216340 - 2018 - Characterizing uncertainty in daily streamflow estimates at ungauged locations for the Massachusetts sustainable yield estimator","interactions":[],"lastModifiedDate":"2020-11-13T20:50:23.999745","indexId":"70216340","displayToPublicDate":"2017-11-17T10:40:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing uncertainty in daily streamflow estimates at ungauged locations for the Massachusetts sustainable yield estimator","docAbstract":"Hydrologic characterization at ungauged locations is one of the quintessential challenges of hydrology. Beyond simulation of historical streamflows, it is similarly important to characterize the level of uncertainty in hydrologic estimates. In tandem with updates to Massachusetts Sustainable Yield Estimator, this work explores the application of global uncertainty estimates to daily streamflow simulations. Expanding on a method developed for deterministic modeling, this approach produces confidence intervals on daily streamflow developed through nonlinear spatial interpolation of daily streamflow using flow duration curves; the 95% confidence is examined. Archived cross‐validations of daily streamflows from 66 watersheds in and around Massachusetts are used to evaluate an approach to uncertainty characterization. Neighboring sites are treated as ungauged, producing relative errors that can be resampled and applied to target sites. The method, with some modification, is found to provide appropriately narrow confidence intervals that contain 95% of the observed streamflows in cross‐validation. Further characterizing uncertainty, multiday means of daily streamflow are evaluated. Working through cross‐validation in Massachusetts, two‐ to three‐month averages of daily streamflow show the best performance. These two approaches to uncertainty characterization inform how streamflow simulation produced for prediction in ungauged basins can be used for water resources management.
Poaching can have devastating impacts on animal and plant numbers, and in many countries has reached crisis levels, with illegal hunters employing increasingly sophisticated techniques. Here, we show how geographic profiling – a mathematical technique originally developed in criminology and recently applied to animal foraging and epidemiology – can be adapted for use in investigations of wildlife crime, using data from an eight-year study in Savé Valley Conservancy, Zimbabwe that in total includes more than 10,000 incidents of illegal hunting and the deaths of 6,454 wild animals. Using a subset of these data for which the illegal hunters’ identities are known, we show that the model can successfully identify the illegal hunters’ home villages using the spatial locations of hunting incidences (for example, snares) as input, and show how this can be improved by manipulating the probability surface inside the Conservancy to reflect the fact that – although the illegal hunters mostly live outside the Conservancy, the majority of hunting occurs inside (in criminology, ‘commuter crime’). The results of this analysis – combined with rigorous simulations – show for the first time how geographic profiling can be combined with GIS data and applied to situations with more complex spatial patterns – for example, where landscape heterogeneity means that some parts of the study area are unsuitable (e.g. aquatic areas for terrestrial animals, or vice versa), or where landscape permeability differs (for example, forest bats tending not to fly over open areas). More broadly, these results show how geographic profiling can be used to target anti-poaching interventions more effectively and more efficiently, with important implications for the development of management strategies and conservation plans in a range of conservation scenarios.
","language":"English","publisher":"Wiley","doi":"10.1111/cobi.13027","usgsCitation":"Faulkner, S.C., Stevens, M.C., Romanach, S.S., Lindsey, P.A., and LeComber, S.C., 2018, A spatial approach to combatting wildlife crime: Conservation Biology, v. 32, no. 3, p. 685-693, https://doi.org/10.1111/cobi.13027.","productDescription":"9 p.","startPage":"685","endPage":"693","ipdsId":"IP-085198","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469158,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://qmro.qmul.ac.uk/xmlui/handle/123456789/25863","text":"External Repository"},{"id":349057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-06","publicationStatus":"PW","scienceBaseUri":"5a60fb0fe4b06e28e9c22b82","contributors":{"authors":[{"text":"Faulkner, Sally C.","contributorId":198703,"corporation":false,"usgs":false,"family":"Faulkner","given":"Sally","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":716891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevens, Michael C.A.","contributorId":198704,"corporation":false,"usgs":false,"family":"Stevens","given":"Michael","email":"","middleInitial":"C.A.","affiliations":[],"preferred":false,"id":716892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":716890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsey, Peter A.","contributorId":198705,"corporation":false,"usgs":false,"family":"Lindsey","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LeComber, Steven C.","contributorId":198706,"corporation":false,"usgs":false,"family":"LeComber","given":"Steven","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":716894,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217712,"text":"70217712 - 2018 - Using halogens (Cl, Br, I) to understand the hydrogeochemical evolution of drought-derived saline porewater beneath a prairie wetland","interactions":[],"lastModifiedDate":"2021-01-29T13:31:55.808394","indexId":"70217712","displayToPublicDate":"2017-11-16T07:25:49","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Using halogens (Cl, Br, I) to understand the hydrogeochemical evolution of drought-derived saline porewater beneath a prairie wetland","docAbstract":"Numerous closed-basin prairie wetlands throughout the Prairie Pothole Region (PPR) of North America maintain moderate surface pond salinities (total dissolved solids [TDS] from 1 to 10 g L− 1) under semiarid climate by accumulation of gypsum and saline lenses of sulfate-rich porewater (TDS > 10 g L− 1) in wetland sediments during droughts. In order to understand the hydrogeochemical origin and composition of these saline porewaters, we made a detailed geochemical survey of Cl−, SO42 −, Br, and I in the porewater, pondwater, and upland groundwater of a typical closed-basin prairie wetland (P1 in the Cottonwood Lake study area, North Dakota). Concentrations of Cl− ranged up to 5.9 mM in the saline porewaters, and was strongly correlated with SO42 − and Br (Pearson's r > 0.7, p < 0.05; concentrations ranging up to 131 mM and 39 μM, respectively) due to the conservative effects of surface water evaporation. In contrast, total dissolved I was not significantly correlated with Cl− (Pearson's r = 0.18, p = 0.273) and was concentrated in porewaters located above the saline lenses with a peak concentration of 4.1 μM beneath the center of the wetland— the highest value for dissolved I ever measured in a terrestrial aquatic system and an order of magnitude above that of seawater. We hypothesize that chromatographic separation between more mobile anions (Cl−, SO42 −, Br−) and I occurs during droughts when wetland ponds dry and sedimentary iodide (I−) oxidizes to its less-mobile form, iodate (IO3−). Understanding the origin and geochemical composition of porewater salinity that develops beneath prairie wetlands during drought can help to fingerprint sources of salinity to wetland ponds during wet climate and elucidate halogen systematics in saline and organic-rich subsurface environments associated with hydrocarbon generation.
A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi-model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi-model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13900","usgsCitation":"Renwick, K.M., Curtis, C., Kleinhesselink, A.R., Schlaepfer, D., Bradley, B.A., Aldridge, C.L., Poulter, B., and Adler, P.B., 2018, Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub: Global Change Biology, v. 24, no. 1, p. 424-438, https://doi.org/10.1111/gcb.13900.","productDescription":"15 p.","startPage":"424","endPage":"438","ipdsId":"IP-087416","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469159,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.13900","text":"External Repository"},{"id":349003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.16845703125,\n 34.19817309627726\n ],\n [\n -103.99658203125,\n 34.19817309627726\n ],\n [\n -103.99658203125,\n 48.980216985374994\n ],\n [\n -120.16845703125,\n 48.980216985374994\n ],\n [\n -120.16845703125,\n 34.19817309627726\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-11","publicationStatus":"PW","scienceBaseUri":"5a60fad7e4b06e28e9c227aa","contributors":{"authors":[{"text":"Renwick, Katherine M.","contributorId":200471,"corporation":false,"usgs":false,"family":"Renwick","given":"Katherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":722465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Curtis, Caroline","contributorId":200472,"corporation":false,"usgs":false,"family":"Curtis","given":"Caroline","email":"","affiliations":[],"preferred":false,"id":722466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleinhesselink, Andrew R.","contributorId":192387,"corporation":false,"usgs":false,"family":"Kleinhesselink","given":"Andrew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":722467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":722469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradley, Bethany A.","contributorId":40117,"corporation":false,"usgs":true,"family":"Bradley","given":"Bethany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":722470,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":722464,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Poulter, Benjamin 0000-0002-9493-8600","orcid":"https://orcid.org/0000-0002-9493-8600","contributorId":200477,"corporation":false,"usgs":false,"family":"Poulter","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":722471,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":722468,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70194133,"text":"70194133 - 2018 - Estimating disperser abundance using open population models that incorporate data from continuous detection PIT arrays","interactions":[],"lastModifiedDate":"2018-08-31T11:07:02","indexId":"70194133","displayToPublicDate":"2017-11-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Estimating disperser abundance using open population models that incorporate data from continuous detection PIT arrays","docAbstract":"Autonomous passive integrated transponder (PIT) tag antenna systems continuously detect individually marked organisms at one or more fixed points over long time periods. Estimating abundance using data from autonomous antennae can be challenging, because these systems do not detect unmarked individuals. Here we pair PIT antennae data from a tributary with mark-recapture sampling data in a mainstem river to estimate the number of fish moving from the mainstem to the tributary. We then use our model to estimate abundance of non-native rainbow trout Oncorhynchus mykiss that move from the Colorado River to the Little Colorado River (LCR), the latter of which is important spawning and rearing habitat for federally-endangered humpback chub Gila cypha. We estimate 226 rainbow trout (95% CI: 127-370) entered the LCR from October 2013-April 2014. We discuss the challenges of incorporating detections from autonomous PIT antenna systems into mark-recapture population models, particularly in regards to using information about spatial location to estimate movement and detection probabilities.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0304","usgsCitation":"Dzul, M.C., Yackulic, C.B., and Korman, J., 2018, Estimating disperser abundance using open population models that incorporate data from continuous detection PIT arrays: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 9, p. 1393-1404, https://doi.org/10.1139/cjfas-2017-0304.","productDescription":"12 p.","startPage":"1393","endPage":"1404","ipdsId":"IP-081814","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438073,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NZ86JV","text":"USGS data release","linkHelpText":"Continuous Detection PIT Array Data & Model"},{"id":349027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.9342041015625,\n 36.121236902880185\n ],\n [\n -111.66778564453125,\n 36.121236902880185\n ],\n [\n -111.66778564453125,\n 36.465471886798134\n ],\n [\n -111.9342041015625,\n 36.465471886798134\n ],\n [\n -111.9342041015625,\n 36.121236902880185\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb10e4b06e28e9c22b91","contributors":{"authors":[{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":722302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":722304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Korman, Josh","contributorId":139960,"corporation":false,"usgs":false,"family":"Korman","given":"Josh","email":"","affiliations":[{"id":13333,"text":"Ecometric Research Inc.","active":true,"usgs":false}],"preferred":false,"id":722306,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194143,"text":"70194143 - 2018 - Influences of landscape heterogeneity on home-range sizes of brown bears","interactions":[],"lastModifiedDate":"2018-05-20T18:27:17","indexId":"70194143","displayToPublicDate":"2017-11-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2653,"text":"Mammalian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Influences of landscape heterogeneity on home-range sizes of brown bears","docAbstract":"Animal space use is influenced by many factors and can affect individual survival and fitness. Under optimal foraging theory, individuals use landscapes to optimize high-quality resources while minimizing the amount of energy used to acquire them. The spatial resource variability hypothesis states that as patchiness of resources increases, individuals use larger areas to obtain the resources necessary to meet energetic requirements. Additionally, under the temporal resource variability hypothesis, seasonal variation in available resources can reduce distances moved while providing a variety of food sources. Our objective was to determine if seasonal home ranges of brown bears (Ursus arctos) were influenced by temporal availability and spatial distribution of resources and whether individual reproductive status, sex, or size (i.e., body mass) mediated space use. To test our hypotheses, we radio collared brown bears (n = 32 [9 male, 23 female]) in 2014–2016 and used 18 a prioriselected linear models to evaluate seasonal utilization distributions (UD) in relation to our hypotheses. Our top-ranked model by AICc, supported the spatial resource variability hypothesis and included percentage of like adjacency (PLADJ) of all cover types (P < 0.01), reproductive class (P > 0.17 for males, solitary females, and females with dependent young), and body mass (kg; P = 0.66). Based on this model, for every percentage increase in PLADJ, UD area was predicted to increase 1.16 times for all sex and reproductive classes. Our results suggest that landscape heterogeneity influences brown bear space use; however, we found that bears used larger areas when landscape homogeneity increased, presumably to gain a diversity of food resources. Our results did not support the temporal resource variability hypothesis, suggesting that the spatial distribution of food was more important than seasonal availability in relation to brown bear home range size.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.mambio.2017.09.002","usgsCitation":"Mangipane, L.S., Belant, J.L., Hiller, T.L., Colvin, M., Gustine, D., Mangipane, B.A., and Hilderbrand, G., 2018, Influences of landscape heterogeneity on home-range sizes of brown bears: Mammalian Biology, v. 88, p. 1-7, https://doi.org/10.1016/j.mambio.2017.09.002.","productDescription":"7 p.","startPage":"1","endPage":"7","ipdsId":"IP-084597","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":461115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.mambio.2017.09.002","text":"Publisher Index Page"},{"id":349011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Lake Clark National Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.0830078125,\n 59.772991625706695\n ],\n [\n -152.9791259765625,\n 59.772991625706695\n ],\n [\n -152.9791259765625,\n 60.98110228438945\n ],\n [\n -155.0830078125,\n 60.98110228438945\n ],\n [\n -155.0830078125,\n 59.772991625706695\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad7e4b06e28e9c227ae","contributors":{"authors":[{"text":"Mangipane, Lindsey S.","contributorId":200447,"corporation":false,"usgs":false,"family":"Mangipane","given":"Lindsey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":722343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belant, Jerrold L.","contributorId":108394,"corporation":false,"usgs":false,"family":"Belant","given":"Jerrold","email":"","middleInitial":"L.","affiliations":[{"id":35599,"text":"Carnivore Ecology Laboratory, Mississippi State University, Mississippi State, MS","active":true,"usgs":false}],"preferred":false,"id":722344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hiller, Tim L.","contributorId":200448,"corporation":false,"usgs":false,"family":"Hiller","given":"Tim","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":722345,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":171431,"corporation":false,"usgs":false,"family":"Colvin","given":"Michael E.","affiliations":[{"id":26913,"text":"Iowa State University, Ames, Iowa","active":true,"usgs":false}],"preferred":false,"id":722346,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gustine, David","contributorId":200449,"corporation":false,"usgs":false,"family":"Gustine","given":"David","affiliations":[],"preferred":false,"id":722347,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mangipane, Buck A.","contributorId":200450,"corporation":false,"usgs":false,"family":"Mangipane","given":"Buck","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":722348,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hilderbrand, Grant V. 0000-0002-0051-8315 ghilderbrand@usgs.gov","orcid":"https://orcid.org/0000-0002-0051-8315","contributorId":199764,"corporation":false,"usgs":true,"family":"Hilderbrand","given":"Grant V.","email":"ghilderbrand@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":false,"id":722342,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}