No abstract available.
","language":"English","publisher":"Virginia Journal of Science","usgsCitation":"Angermeier, P.L., and Pinder, M.J., 2015, Viewing the status of Virginia’s environment through the lens of freshwater fishes: Virginia Journal of Science, v. 66, p. 147-169.","productDescription":"13 p.","startPage":"147","endPage":"169","ipdsId":"IP-065711","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"66","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fec7e4b06e28e9c25353","contributors":{"authors":[{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pinder, M. J.","contributorId":200292,"corporation":false,"usgs":false,"family":"Pinder","given":"M.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721803,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189910,"text":"70189910 - 2015 - PhreeqcRM: A reaction module for transport simulators based on the geochemical model PHREEQC","interactions":[],"lastModifiedDate":"2017-08-03T14:32:23","indexId":"70189910","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"PhreeqcRM: A reaction module for transport simulators based on the geochemical model PHREEQC","docAbstract":"PhreeqcRM is a geochemical reaction module designed specifically to perform equilibrium and kinetic reaction calculations for reactive transport simulators that use an operator-splitting approach. The basic function of the reaction module is to take component concentrations from the model cells of the transport simulator, run geochemical reactions, and return updated component concentrations to the transport simulator. If multicomponent diffusion is modeled (e.g., Nernst–Planck equation), then aqueous species concentrations can be used instead of component concentrations. The reaction capabilities are a complete implementation of the reaction capabilities of PHREEQC. In each cell, the reaction module maintains the composition of all of the reactants, which may include minerals, exchangers, surface complexers, gas phases, solid solutions, and user-defined kinetic reactants.
PhreeqcRM assigns initial and boundary conditions for model cells based on standard PHREEQC input definitions (files or strings) of chemical compositions of solutions and reactants. Additional PhreeqcRM capabilities include methods to eliminate reaction calculations for inactive parts of a model domain, transfer concentrations and other model properties, and retrieve selected results. The module demonstrates good scalability for parallel processing by using multiprocessing with MPI (message passing interface) on distributed memory systems, and limited scalability using multithreading with OpenMP on shared memory systems. PhreeqcRM is written in C++, but interfaces allow methods to be called from C or Fortran. By using the PhreeqcRM reaction module, an existing multicomponent transport simulator can be extended to simulate a wide range of geochemical reactions. Results of the implementation of PhreeqcRM as the reaction engine for transport simulators PHAST and FEFLOW are shown by using an analytical solution and the reactive transport benchmark of MoMaS.
The authors regret that the application of the t-plot to determine the presence of micropores in the three sorbents needs the following corrections: (1) Fig. 1a, c, e are N2(g) adsorption and desorption isotherms” (remove “BET”). This correction applies to descriptions in the text as well. (2) Table 2, the column titled “Micropores” is mislabelled, and should be labelled “Film thickness”, which may not equal the pore width. The column titled “Micropore volume” is a correct description for laterite volume 0.0022 cm3 g−1 (t = 0.3–0.5 nm), but the other pore volumes listed cannot be identified as corresponding to micropores. They likely comprise both micropores and mesopores in laterite, while the presence of micropores in activated alumina is not clear. The positive y-intercept for the lowest linear portion of the laterite t-plot curve indicates micropores (Fig. 1f), and the shape of the t-plot curve suggests the presence of both micropores and mesopores. The shape of the activated alumina t-plot curve suggests the presence of micropores and mesopores, but the zero intercept for the lowest linear portion of the curve (Fig. 1b) creates uncertainty regarding the presence of micropores. Also see Storck et al., 1998; Hay et al. 2011 and references therein. (Additional note: analytical instrument Micromeritics® was misspelled as “Micrometrics”).
The authors would like to apologise for any inconvenience caused.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.06.016","usgsCitation":"Craig, L., Stillings, L.L., Decker, D.L., and Thomas, J.M., 2015, Corrigendum to “Comparing activated alumina with indigenous laterite and bauxite as potential sorbents for removing fluoride from drinking water in Ghana” [Appl. Geochem. 56 (2015) 50–66]: Applied Geochemistry, v. 63, p. 451-451, https://doi.org/10.1016/j.apgeochem.2015.06.016.","productDescription":"1 p.","startPage":"451","endPage":"451","ipdsId":"IP-088988","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":472426,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2015.06.016","text":"Publisher Index Page"},{"id":344273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59770751e4b0ec1a48889f88","contributors":{"authors":[{"text":"Craig, Laura","contributorId":173675,"corporation":false,"usgs":false,"family":"Craig","given":"Laura","affiliations":[{"id":27270,"text":"American Rivers","active":true,"usgs":false}],"preferred":false,"id":706242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stillings, Lisa L. 0000-0002-9011-8891 stilling@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-8891","contributorId":193548,"corporation":false,"usgs":true,"family":"Stillings","given":"Lisa","email":"stilling@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":706241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Decker, David L.","contributorId":193549,"corporation":false,"usgs":false,"family":"Decker","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":706243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, James M.","contributorId":195094,"corporation":false,"usgs":false,"family":"Thomas","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":706244,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70182723,"text":"70182723 - 2015 - Paleoseismic evidence for late Holocene tectonic deformation along the Saddle mountain fault zone, Southeastern Olympic Peninsula, Washington","interactions":[],"lastModifiedDate":"2017-02-27T14:52:34","indexId":"70182723","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Paleoseismic evidence for late Holocene tectonic deformation along the Saddle mountain fault zone, Southeastern Olympic Peninsula, Washington","docAbstract":"Trench and wetland coring studies show that northeast‐striking strands of the Saddle Mountain fault zone ruptured the ground about 1000 years ago, generating prominent scarps. Three conspicuous subparallel fault scarps can be traced for 15 km on Light Detection and Ranging (LiDAR) imagery, traversing the foothills of the southeast Olympic Mountains: the Saddle Mountain east fault, the Saddle Mountain west fault, and the newly identified Sund Creek fault. Uplift of the Saddle Mountain east fault scarp impounded stream flow, forming Price Lake and submerging an existing forest, thereby leaving drowned stumps still rooted in place. Stratigraphy mapped in two trenches, one across the Saddle Mountain east fault and the other across the Sund Creek fault, records one and two earthquakes, respectively, as faulting juxtaposed Miocene‐age bedrock against glacial and postglacial deposits. Although the stratigraphy demonstrates that reverse motion generated the scarps, slip indicators measured on fault surfaces suggest a component of left‐lateral slip. From trench exposures, we estimate the postglacial slip rate to be 0.2 mm/yr and between 0.7 and 3.2 mm/yr during the past 3000 years. Integrating radiocarbon data from this study with earlier Saddle Mountain fault studies into an OxCal Bayesian statistical chronology model constrains the most recent paleoearthquake age of rupture across all three Saddle Mountain faults to 1170–970 calibrated years (cal B.P.), which overlaps with the nearby Mw 7.5 1050–1020 cal B.P. Seattle fault earthquake. An earlier earthquake recorded in the Sund Creek trench exposure, dates to around 3500 cal B.P. The geometry of the Saddle Mountain faults and their near‐synchronous rupture to nearby faults 1000 years ago suggest that the Saddle Mountain fault zone forms a western boundary fault along which the fore‐arc blocks migrate northward in response to margin‐parallel shortening across the Puget Lowland.
","language":"English","publisher":"GeoScience World ","doi":"10.1785/0120140086","usgsCitation":"Barnett, E., Sherrod, B.L., Hughes, J.F., Kelsey, H.M., Czajkowski, J.L., Walsh, T.J., Contreras, T.A., Schermer, E.R., and Carson, R.J., 2015, Paleoseismic evidence for late Holocene tectonic deformation along the Saddle mountain fault zone, Southeastern Olympic Peninsula, Washington: Bulletin of the Seismological Society of America, v. 105, no. 1, p. 38-71, https://doi.org/10.1785/0120140086.","productDescription":"34 p. ","startPage":"38","endPage":"71","ipdsId":"IP-048994","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":336292,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-13","publicationStatus":"PW","scienceBaseUri":"58b548c3e4b01ccd54fddfd0","contributors":{"authors":[{"text":"Barnett, Elizabeth eli@usgs.gov","contributorId":2156,"corporation":false,"usgs":true,"family":"Barnett","given":"Elizabeth","email":"eli@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":673456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":673457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hughes, Jonathan F.","contributorId":184055,"corporation":false,"usgs":false,"family":"Hughes","given":"Jonathan","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":673458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelsey, Harvey M.","contributorId":184057,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":673460,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Czajkowski, Jessica L.","contributorId":184056,"corporation":false,"usgs":false,"family":"Czajkowski","given":"Jessica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":673459,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walsh, Timothy J.","contributorId":184058,"corporation":false,"usgs":false,"family":"Walsh","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":673461,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Contreras, Trevor A.","contributorId":184059,"corporation":false,"usgs":false,"family":"Contreras","given":"Trevor","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":673462,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schermer, Elizabeth R.","contributorId":184060,"corporation":false,"usgs":false,"family":"Schermer","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":673463,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carson, Robert J.","contributorId":184061,"corporation":false,"usgs":false,"family":"Carson","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":673464,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70182729,"text":"70182729 - 2015 - Effects of rapid urbanization on streamflow, erosion, and sedimentation in a desert stream in the American Southwest","interactions":[],"lastModifiedDate":"2017-04-28T09:35:11","indexId":"70182729","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":815,"text":"Anthropocene","active":true,"publicationSubtype":{"id":10}},"title":"Effects of rapid urbanization on streamflow, erosion, and sedimentation in a desert stream in the American Southwest","docAbstract":"Rapid urbanization has resulted in a series of sequential effects on a desert stream in the American Southwest. Lower Las Vegas Wash was a dry wash characterized by infrequent flood deposition when Las Vegas, Nevada was established in 1905. Wastewater effluent was discharged into the wash in low volumes for over 3 decades. Wastewater volumes increased commensurably with accelerated population growth during the late 20th century and created a sequence of feedback effects on the floodplain. Initially slow saturation of the valley fill created a desert oasis of dense floodplain vegetation and wetlands. Annual streamflow began in 1958 and erosion began a decade later with shallow incision in discontinuous channel segments. Increasing baseflow gradually enlarged channels; headcutting was active during the 1970s to 1984. The incised channels concentrated storm runoff, which accelerated local channel erosion, and in 1984 the headcuts were integrated during a series of monsoon floods. Wetlands were drained and most floodplain vegetation destroyed. Channel erosion continued unabated until engineering interventions began in the 21st century. No natural channel recovery occurred after initial urbanization effects because streamflow never stabilized in the late 20th century. A 6.6 M m3 sediment slug, eroded from the wash in ∼25 years, was deposited in Las Vegas Bay in Lake Mead. Falling reservoir levels during the 21st century are responsible for sediment redistribution and infilling of the bay. Close monitoring of impacts is recommended when urban wastewater and storm runoff are discharged on a desert wash. Channel interventions, when necessary, are advised in order to prevent costly engineering schemes of channel stabilization, flood control, and floodplain restoration.
","language":"English","publisher":"Elsevier ","doi":"10.1016/j.ancene.2015.09.002","collaboration":"Southern Nevada Water Authority","usgsCitation":"Whitney, J.W., Glancy, P.A., Buckingham, S.E., and Ehrenberg, A.C., 2015, Effects of rapid urbanization on streamflow, erosion, and sedimentation in a desert stream in the American Southwest: Anthropocene, v. 10, p. 29-42, https://doi.org/10.1016/j.ancene.2015.09.002.","productDescription":"14 p. ","startPage":"29","endPage":"42","ipdsId":"IP-060177","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":336297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b548c3e4b01ccd54fddfcc","contributors":{"authors":[{"text":"Whitney, John W. 0000-0003-3824-3692 jwhitney@usgs.gov","orcid":"https://orcid.org/0000-0003-3824-3692","contributorId":804,"corporation":false,"usgs":true,"family":"Whitney","given":"John","email":"jwhitney@usgs.gov","middleInitial":"W.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":673480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glancy, Patrick A.","contributorId":184076,"corporation":false,"usgs":false,"family":"Glancy","given":"Patrick","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":673505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckingham, Susan E.","contributorId":184077,"corporation":false,"usgs":false,"family":"Buckingham","given":"Susan","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":673506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ehrenberg, Arthur C.","contributorId":184078,"corporation":false,"usgs":false,"family":"Ehrenberg","given":"Arthur","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":673507,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70182726,"text":"70182726 - 2015 - Climate change and vulnerability of bull trout (Salvelinus confluentus) in a fire-prone landscape.","interactions":[],"lastModifiedDate":"2017-11-20T14:24:45","indexId":"70182726","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","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":"Climate change and vulnerability of bull trout (Salvelinus confluentus) in a fire-prone landscape.","docAbstract":"Linked atmospheric and wildfire changes will complicate future management of native coldwater fishes in fire-prone landscapes, and new approaches to management that incorporate uncertainty are needed to address this challenge. We used a Bayesian network (BN) approach to evaluate population vulnerability of bull trout (Salvelinus confluentus) in the Wenatchee River basin, Washington, USA, under current and future climate and fire scenarios. The BN was based on modeled estimates of wildfire, water temperature, and physical habitat prior to, and following, simulated fires throughout the basin. We found that bull trout population vulnerability depended on the extent to which climate effects can be at least partially offset by managing factors such as habitat connectivity and fire size. Moreover, our analysis showed that local management can significantly reduce the vulnerability of bull trout to climate change given appropriate management actions. Tools such as our BN that explicitly integrate the linked nature of climate and wildfire, and incorporate uncertainty in both input data and vulnerability estimates, will be vital in effective future management to conserve native coldwater fishes.
SO2 camera measurements at Kīlauea Volcano, Hawaii, in May of 2010 captured two occurrences of lava lake rise and fall within the Halema'um'au Crater summit vent. During high lava stands we observed diminished SO2 emission rates and decreased seismic tremor. Similar events at Kīlauea have been described as the result of sporadic degassing following gas accumulation beneath a mostly impermeable lava lake surface. Incorporation of SO2 camera data into a multi-parameter dataset gives credence to the likelihood of shallow gas accumulation as the cause of these high stand events, with accumulated gas release upon lake-level drop compensating for the gas deficit reached during accumulation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2014.12.005","usgsCitation":"Nadeau, P., Werner, C.A., Waite, G.P., Carn, S.A., Brewer, I.D., Elias, T., Sutton, A., and Kern, C., 2015, Using SO2 camera imagery and seismicity to examine degassing and gas accumulation at Kīlauea Volcano, May 2010: Journal of Volcanology and Geothermal Research, v. 300, p. 70-80, https://doi.org/10.1016/j.jvolgeores.2014.12.005.","productDescription":"11 p.","startPage":"70","endPage":"80","ipdsId":"IP-056694","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":340007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.32041549682617,\n 19.344998502547103\n ],\n [\n -155.25501251220703,\n 19.344998502547103\n ],\n [\n -155.25501251220703,\n 19.4303341116379\n ],\n [\n -155.32041549682617,\n 19.4303341116379\n ],\n [\n -155.32041549682617,\n 19.344998502547103\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"300","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f877bae4b0b7ea54521c2c","contributors":{"authors":[{"text":"Nadeau, Patricia A","contributorId":191164,"corporation":false,"usgs":false,"family":"Nadeau","given":"Patricia A","affiliations":[],"preferred":false,"id":692049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werner, Cynthia A. cwerner@usgs.gov","contributorId":2540,"corporation":false,"usgs":true,"family":"Werner","given":"Cynthia","email":"cwerner@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":692048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waite, Gregory P.","contributorId":146613,"corporation":false,"usgs":false,"family":"Waite","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":692050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carn, Simon A","contributorId":191165,"corporation":false,"usgs":false,"family":"Carn","given":"Simon","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":692051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brewer, Ian D","contributorId":191166,"corporation":false,"usgs":false,"family":"Brewer","given":"Ian","email":"","middleInitial":"D","affiliations":[],"preferred":false,"id":692052,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elias, Tamar 0000-0002-9592-4518 telias@usgs.gov","orcid":"https://orcid.org/0000-0002-9592-4518","contributorId":3916,"corporation":false,"usgs":true,"family":"Elias","given":"Tamar","email":"telias@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":692053,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sutton, Andrew ajsutton@usgs.gov","contributorId":156244,"corporation":false,"usgs":true,"family":"Sutton","given":"Andrew","email":"ajsutton@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":692054,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":692055,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70178249,"text":"70178249 - 2015 - Integrating climate change into northeast and midwest State Wildlife Action Plans","interactions":[],"lastModifiedDate":"2020-07-29T13:59:36.026052","indexId":"70178249","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Integrating climate change into northeast and midwest State Wildlife Action Plans","docAbstract":"The Department of Interior Northeast Climate Science Center (NE CSC) conducts research that responds to the regional natural resource management community’s needs to anticipate, monitor, and adapt to climate change. The NE CSC is supported by a consortium of partners that includes the University of Massachusetts Amherst, College of Menominee Nation, Columbia University, Marine Biological Laboratory, University of Minnesota, University of Missouri Columbia, and University of Wisconsin. The NE CSC also engages and collaborates with a diversity of other federal, state, academic, tribal, and non-governmental organizations (NGOs) to conduct collaborative, stakeholder-driven, and climate-focused work.
The State Wildlife Action Plans (SWAPs) are revised every 10 years; states are currently working towards a target deadline of October 2015. SWAP coordinators have been challenged to incorporate climate change impacts and species responses into their current revisions. This synthesis is intended to inform the science going into Northeast and Midwest SWAPs across the 22 NE CSC states ranging from Maine to Virginia, and Minnesota and Missouri in the eastern United States. It is anticipated that this synthesis will help guide SWAP authors in writing specific sections, help revise and finalize existing sections, or be incorporated as an appendix or addendum.
The purpose of this NE CSC-led cooperative report is to provide a synthesis of what is known and what is uncertain about climate change and its impacts across the NE CSC region, with a particular focus on the responses and vulnerabilities of Regional Species of Greatest Conservation Need (RSGCN) and the habitats they depend on. Another goal is to describe a range of climate change adaptation approaches, processes, tools, and potential partnerships that are available to State natural resource managers across the Northeast and Midwest regions of the United States. Through illustrative case studies submitted by the NE CSC and partners, we demonstrate climate change adaptation efforts being explored and implemented across local and large-landscape scales.
This document is divided into four sections and addresses the following climate and management relevant questions:
The outline and content for this document were developed with input from State Coordinators, members of the Northeast Association of Fish and Wildlife Agencies and Midwest Association of Fish and Wildlife Agencies, DOI Northeast Climate Science Center affiliated researchers, and other partners including the Landscape Conservation Cooperatives, the Northern Institute of Applied Climate Science, the Wildlife Conservation Society, and The Nature Conservancy. Terwilliger Consulting, Inc., was especially instrumental in helping connect and coordinate the authors of this report with State representatives through conference calls and email surveys to develop the most needed and effective information for current SWAP revisions.
On a final note, the SWAPs are living documents that can be added to and evolve on timescales beyond the 10-year revision cycle. The development of this report was timed such that SWAP coordinators and writers would have sufficient time to implement this input before their October 2015 deadline. However, this document is also meant to serve as a starting point for coordinated and collaborative climate science and adaptation across the region; the NE CSC 5 endeavors to continue to provide actionable science during the coming years in collaboration with its diverse federal, state, NGO, and academic partners.
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\"}}]}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58259561e4b01fad86db2417","contributors":{"editors":[{"text":"Staudinger, Michelle D. 0000-0002-4535-2005 mstaudinger@usgs.gov","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":4057,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle","email":"mstaudinger@usgs.gov","middleInitial":"D.","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":653446,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Morelli, Toni L. 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":189143,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":653447,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Bryan, Alexander 0000-0003-2040-7636 abryan@usgs.gov","orcid":"https://orcid.org/0000-0003-2040-7636","contributorId":168822,"corporation":false,"usgs":true,"family":"Bryan","given":"Alexander","email":"abryan@usgs.gov","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":653448,"contributorType":{"id":2,"text":"Editors"},"rank":3}]}} ,{"id":70189826,"text":"70189826 - 2015 - Analysis and selection of magnitude relations for the Working Group on Utah Earthquake Probabilities","interactions":[],"lastModifiedDate":"2017-07-27T16:10:12","indexId":"70189826","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Analysis and selection of magnitude relations for the Working Group on Utah Earthquake Probabilities","docAbstract":"Prior to calculating time-independent and -dependent earthquake probabilities for faults in the Wasatch Front region, the Working Group on Utah Earthquake Probabilities (WGUEP) updated a seismic-source model for the region (Wong and others, 2014) and evaluated 19 historical regressions on earthquake magnitude (M). These regressions relate M to fault parameters for historical surface-faulting earthquakes, including linear fault length (e.g., surface-rupture length [SRL] or segment length), average displacement, maximum displacement, rupture area, seismic moment (Mo ), and slip rate. These regressions show that significant epistemic uncertainties complicate the determination of characteristic magnitude for fault sources in the Basin and Range Province (BRP). For example, we found that M estimates (as a function of SRL) span about 0.3–0.4 units (figure 1) owing to differences in the fault parameter used; age, quality, and size of historical earthquake databases; and fault type and region considered.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Basin and Range Province Seismic Hazards Summit III, Utah Geological Survey Miscellaneous Publication 15-5","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"conferenceTitle":"Basin and Range Province Seismic Hazards Summit III","language":"English","publisher":"Utah Geological Survey","usgsCitation":"DuRoss, C., Olig, S., and Schwartz, D., 2015, Analysis and selection of magnitude relations for the Working Group on Utah Earthquake Probabilities, in Basin and Range Province Seismic Hazards Summit III, Utah Geological Survey Miscellaneous Publication 15-5, 30 p.","productDescription":"30 p.","ipdsId":"IP-064153","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344412,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":344373,"type":{"id":15,"text":"Index Page"},"url":"https://ugspub.nr.utah.gov/publications/misc_pubs/mp-15-5/mp-15-5_technical_sessions1-2.pdf"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"597afba7e4b0a38ca2750b6a","contributors":{"authors":[{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":706480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olig, Susan","contributorId":195184,"corporation":false,"usgs":false,"family":"Olig","given":"Susan","affiliations":[],"preferred":false,"id":706481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwartz, David","contributorId":195185,"corporation":false,"usgs":false,"family":"Schwartz","given":"David","affiliations":[],"preferred":false,"id":706482,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70117684,"text":"70117684 - 2015 - Global Cropland Area Database (GCAD) derived from Remote Sensing in Support of Food Security in the Twenty-first Century: Current Achievements and Future Possibilities","interactions":[],"lastModifiedDate":"2015-10-16T16:20:40","indexId":"70117684","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Global Cropland Area Database (GCAD) derived from Remote Sensing in Support of Food Security in the Twenty-first Century: Current Achievements and Future Possibilities","docAbstract":"The precise estimation of the global agricultural cropland- extents, areas, geographic locations, crop types, cropping intensities, and their watering methods (irrigated or rainfed; type of irrigation) provides a critical scientific basis for the development of water and food security policies (Thenkabail et al., 2012, 2011, 2010). By year 2100, the global human population is expected to grow to 10.4 billion under median fertility variants or higher under constant or higher fertility variants (Table 1) with over three quarters living in developing countries, in regions that already lack the capacity to produce enough food. With current agricultural practices, the increased demand for food and nutrition would require in about 2 billion hectares of additional cropland, about twice the equivalent to the land area of the United States, and lead to significant increases in greenhouse gas productions (Tillman et al., 2011). For example, during 1960-2010 world population more than doubled from 3 billion to 7 billion. The nutritional demand of the population also grew swiftly during this period from an average of about 2000 calories per day per person in 1960 to nearly 3000 calories per day per person in 2010. The food demand of increased population along with increased nutritional demand during this period (1960-2010) was met by the “green revolution” which more than tripled the food production; even though croplands decreased from about 0.43 ha/capita to 0.26 ha/capita (FAO, 2009). The increase in food production during the green revolution was the result of factors such as: (a) expansion in irrigated areas which increased from 130 Mha in 1960s to 278.4 Mha in year 2000 (Siebert et al., 2006) or 399 Mha when you do not consider cropping intensity (Thenkabail et al., 2009a, 2009b, 2009c) or 467 Mha when you consider cropping intensity (Thenkabail et al., 2009a; Thenkabail et al., 2009c); (b) increase in yield and per capita food production (e.g., cereal production from 280 kg/person to 380 kg/person and meat from 22 kg/person to 34 kg/person (McIntyre, 2008); (c) new cultivar types (e.g., hybrid varieties of wheat and rice, biotechnology); and (d) modern agronomic and crop management practices (e.g., fertilizers, herbicide, pesticide applications). However, some of the factors that lead to the green revolution have stressed the environment to limits leading to salinization and decreasing water quality. For example, from 1960 to 2000, the phosphorous use doubled from 10 million tons to 20 MT, pesticide use tripled from near zero to 3 MT, and nitrogen use as fertilizer increased to a staggering 80 MT from just 10 MT (Foley et al., 2007; Khan and Hanjra, 2008). Further, diversion of croplands to bio-fuels is already taking water away from food production; the economics, carbon sequestration, environmental, and food security impacts of biofuel production are net negative (Lal and Pimentel, 2009), leaving us with a carbon debt (Gibbs et al., 2008; Searchinger et al., 2008). Climate models predict that in most regions of the world the hottest seasons on record will become the norm by the end of the century-an outcome that bodes ill for feeding the world (Kumar and Singh, 2005). Also, crop yield increases of the green revolution era have now stagnated (Hossain et al., 2005). Thereby, further increase in food production through increase in cropland areas and\\or increased allocations of water for croplands are widely considered unsustainable and\\or infeasible. Indeed, cropland areas have even begun to decrease in many 3 parts of the World due to factors such as urbanization, industrialization, and salinization. Furthermore, ecological and environmental imperatives such as biodiversity conservation and atmospheric carbon sequestration have put a cap on the possible expansion of cropland areas to other lands such as forests and rangelands. Other important factors limit food security. These include factors such as diversion of croplands to biofuels (Bindraban et al., 2009), limited water resources for irrigation expansion (Turral et al., 2009), limits on agricultural intensifications, loss of croplands to urbanization (Khan and Hanjra, 2008), increasing meat consumption (and associated demands on land and water) (Vinnari and Tapio, 2009), environmental infeasibility for cropland expansion (Gordon et al., 2009), and changing climate have all put pressure on our continued ability to sustain global food security in the twenty-first century. So, how does the World continue to meet its food and nutrition needs?. Solutions may come from bio-technology and precision farming, however developments in these fields are not currently moving at rates that will ensure global food security over next few decades. Further, there is a need for careful consideration of possible harmful effects of bio-technology. We should not be looking back 30– 50 years from now, like we have been looking back now at many mistakes made during the green revolution. During the green revolution the focus was only on getting more yield per unit area. Little thought was put about serious damage done to our natural environments, water resources, and human health as a result of detrimental factors such as uncontrolled use of herbicides-pesticides-nutrients, drastic groundwater mining, and salinization of fertile soils due to over irrigation. Currently, there is talk of a “second green revolution” or even an “ever green revolution”, but clear ideas on what these terms actually mean are still debated and are evolving. One of the biggest issues that are not given adequate focus is the use of large quantities of water for food production. Indeed, an overwhelming proportion (60-90%) of all human water use in India goes for producing their food (Falkenmark, M., & Rockström, 2006). But such intensive water use for food production is no longer tenable due to increasing pressure for water use alternatives such as increasing urbanization, industrialization, environmental flows, bio-fuels, and recreation. This has brought into sharp focus the need to grow more food per drop of water leading to a “blue revolution”
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Land resources: monitoring, modelling, and mapping","language":"English","publisher":"Taylor & Francis","publisherLocation":"Boca Raton, Florida","usgsCitation":"Teluguntla, P.G., Thenkabail, P.S., Xiong, J., Gumma, M., Giri, C., Milesi, C., Ozdogan, M., Congalton, R., Tilton, J., Sankey, T.T., Massey, R., Phalke, A., and Yadav, K., 2015, Global Cropland Area Database (GCAD) derived from Remote Sensing in Support of Food Security in the Twenty-first Century: Current Achievements and Future Possibilities, chap. of Land resources: monitoring, modelling, and mapping, 45 p.","productDescription":"45 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054785","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":309997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56221fb0e4b06217fc47921f","contributors":{"authors":[{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":519106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":519105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xiong, Jun 0000-0002-2320-0780 jxiong@usgs.gov","orcid":"https://orcid.org/0000-0002-2320-0780","contributorId":5276,"corporation":false,"usgs":true,"family":"Xiong","given":"Jun","email":"jxiong@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":519107,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":577764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Giri, Chandra cgiri@usgs.gov","contributorId":2403,"corporation":false,"usgs":true,"family":"Giri","given":"Chandra","email":"cgiri@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":577765,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Milesi, Cristina","contributorId":107590,"corporation":false,"usgs":true,"family":"Milesi","given":"Cristina","email":"","affiliations":[],"preferred":false,"id":577766,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ozdogan, Mutlu","contributorId":32060,"corporation":false,"usgs":true,"family":"Ozdogan","given":"Mutlu","affiliations":[],"preferred":false,"id":577767,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Congalton, Russ","contributorId":149288,"corporation":false,"usgs":false,"family":"Congalton","given":"Russ","email":"","affiliations":[],"preferred":false,"id":577768,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tilton, James","contributorId":149289,"corporation":false,"usgs":false,"family":"Tilton","given":"James","email":"","affiliations":[],"preferred":false,"id":577769,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sankey, Temuulen Tsagaan","contributorId":149290,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"Tsagaan","affiliations":[],"preferred":false,"id":577770,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Massey, Richard","contributorId":149291,"corporation":false,"usgs":false,"family":"Massey","given":"Richard","affiliations":[],"preferred":false,"id":577771,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Phalke, Aparna","contributorId":149292,"corporation":false,"usgs":false,"family":"Phalke","given":"Aparna","email":"","affiliations":[],"preferred":false,"id":577772,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Yadav, Kamini","contributorId":138720,"corporation":false,"usgs":false,"family":"Yadav","given":"Kamini","affiliations":[{"id":12507,"text":"Department of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA","active":true,"usgs":false}],"preferred":false,"id":577773,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70195147,"text":"70195147 - 2015 - Truncorotalia crassaformis from its type locality: Comparison with Caribbean plankton and Pliocene relatives","interactions":[],"lastModifiedDate":"2018-02-07T15:31:54","indexId":"70195147","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2673,"text":"Marine Micropaleontology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Truncorotalia crassaformis from its type locality: Comparison with Caribbean plankton and Pliocene relatives","title":"Truncorotalia crassaformis from its type locality: Comparison with Caribbean plankton and Pliocene relatives","docAbstract":"Truncorotalia crassaformis has been identified in Pliocene-Holocene assemblages globally but there has been little analysis of specimens from its type locality at Lomita Quarry, California. This has led to confusion about some diagnostic criteria, particularly the presence of a peripheral keel. To better understand variation specimens are studied from the type locality (Pleistocene, c. 400–600 ka), supplemented by material from a plankton trap in Cariaco Basin and from ODP 925, Ceara Rise (Pliocene, c. 4.3 Ma). The damaged holotype has a weak topographic ridge (keel) at the periphery of early chambers of the outer whorl. Several well-preserved specimens have a keel on all chambers of the whorl. Encrustation obscures the periphery on some and masks shell shape. Several outliers in a morphometric analysis of axial shape have distinctive discoidal outlines but ventroconical (cone-like) forms are common. Lomita Marl was deposited on a sheltered, shallow shelf in Chron 1. Foraminifera reworked from the unconformably underlying Repetto Siltstone are present. Specimens resembling the holotype are very rare and often damaged. Morphological disparity is high. It is unlikely that an autochthonous population was sampled. The weak peripheral keel present on some living specimens from Cariaco Basin is built incrementally by a thin featureless calcitic veneer deposited between the morphogenesis of each chamber. The process progressively obscures pores in the primary wall. Its earliest stages have been misidentified as a poreless zone. Ventroconical form is weak in the Ceara Rise Pliocene specimens and is distinguishable from the Cariaco sample. There is only a veneer at the periphery. Although the study does not provide a population-based diagnosis of T. crassaformis it indicates that the name should not be applied to early Pliocene forms.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marmicro.2015.02.001","usgsCitation":"Scott, G., Ingle, J.C., McCane, B., Powell, C.L., and Thunell, R.C., 2015, Truncorotalia crassaformis from its type locality: Comparison with Caribbean plankton and Pliocene relatives: Marine Micropaleontology, v. 117, p. 1-12, https://doi.org/10.1016/j.marmicro.2015.02.001.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-063615","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":351295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e7ce4b00f54eb22935c","contributors":{"authors":[{"text":"Scott, George H.","contributorId":201892,"corporation":false,"usgs":false,"family":"Scott","given":"George H.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":727158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ingle, James C. Jr.","contributorId":75809,"corporation":false,"usgs":false,"family":"Ingle","given":"James","suffix":"Jr.","email":"","middleInitial":"C.","affiliations":[{"id":7033,"text":"School of Earth Sciences, Stanford University","active":true,"usgs":false}],"preferred":false,"id":727159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCane, Brendan","contributorId":201894,"corporation":false,"usgs":false,"family":"McCane","given":"Brendan","email":"","affiliations":[{"id":36279,"text":"Department of Computer Science, University of Otago","active":true,"usgs":false}],"preferred":false,"id":727160,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, Charles L. II 0000-0002-1913-555X cpowell@usgs.gov","orcid":"https://orcid.org/0000-0002-1913-555X","contributorId":3243,"corporation":false,"usgs":true,"family":"Powell","given":"Charles","suffix":"II","email":"cpowell@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":727157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thunell, Robert C.","contributorId":71028,"corporation":false,"usgs":false,"family":"Thunell","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":36280,"text":"Department of Earth and Ocean Sciences, University of South Carolina,","active":true,"usgs":false}],"preferred":false,"id":727161,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173418,"text":"70173418 - 2015 - Fishes of the Blackwater River Drainage, Tucker County, West Virginia","interactions":[],"lastModifiedDate":"2016-06-16T16:29:02","indexId":"70173418","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Fishes of the Blackwater River Drainage, Tucker County, West Virginia","docAbstract":"The Blackwater River, a tributary of the upper Cheat River of the Monongahela River, hosts a modest fish fauna. This relatively low diversity of fish species is partly explained by its drainage history. The Blackwater was once part of the prehistoric, northeasterly flowing St. Lawrence River. During the Pleistocene Epoch, the fauna was significantly affected by glacial advance and by proglacial lakes and their associated overflows. After the last glacial retreat, overflow channels, deposits, and scouring altered drainage courses and connected some of the tributaries of the ancient Teays and Pittsburgh drainages. These major alterations allowed the invasion of fishes from North America's more species-rich southern waters. Here we review fish distributions based on 67 surveys at 34 sites within the Blackwater River drainage, and discuss the origin and status of 37 species. Within the Blackwater River watershed, 30 species (20 native, 10 introduced) have been reported from upstream of Blackwater Falls, whereas 29 (26 native, 3 introduced) have been documented below the Falls. Acid mine drainage, historic lumbering, and human encroachment have impacted the Blackwater's ichthyofauna. The fishes that have been most affected are Salvelinus fontinalis (Brook Trout), Clinostomus elongatus (Redside Dace), Nocomis micropogon (River Chub), Hypentelium nigricans (Northern Hog Sucker), Etheostoma flabellare (Fantail Darter), and Percina maculata(Blackside Darter). The first two species incurred range reductions, whereas the latter four were probably extirpated. In the 1990s, acid remediation dramatically improved the water quality of the river below Davis. Recent surveys in the lower drainage revealed 15 fishes where none had been observed since at least the 1940s; seven of these (Cyprinella spiloptera [Spotfin Shiner], Luxilus chrysocephalus [Striped Shiner], Notropis photogenis [Silver Shiner], N. rubellus [Rosyface Shiner];Micropterus dolomieu [Smallmouth Bass]; and Etheostoma camurum [Bluebreast Darter] and E. variatum [Variegate Darter]) represent additions to the faunal list of the Blackwater River.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.014.sp725","usgsCitation":"Cincotta, D.A., Welsh, S., Wegman, D.P., Oldham, T.E., and Hedrick, L.B., 2015, Fishes of the Blackwater River Drainage, Tucker County, West Virginia: Southeastern Naturalist, v. 14, no. 7, p. 297-313, https://doi.org/10.1656/058.014.sp725.","productDescription":"17 p.","startPage":"297","endPage":"313","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055315","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Blackwater River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.63645935058594,\n 39.07677595221322\n ],\n [\n -79.61894989013672,\n 39.087169549791966\n ],\n [\n -79.56676483154297,\n 39.09756161605432\n ],\n [\n -79.5303726196289,\n 39.11221449135899\n ],\n [\n -79.51869964599608,\n 39.11674294565931\n ],\n [\n -79.49775695800781,\n 39.11727568585595\n ],\n [\n -79.4747543334961,\n 39.13085919986185\n ],\n [\n -79.44419860839844,\n 39.14177738036501\n ],\n [\n -79.4205093383789,\n 39.144972625112224\n ],\n [\n -79.39476013183594,\n 39.14603767446419\n ],\n [\n -79.38583374023436,\n 39.133522326822394\n ],\n [\n -79.37965393066406,\n 39.102091011833686\n ],\n [\n -79.3937301635742,\n 39.07011258429051\n ],\n [\n -79.42531585693358,\n 39.03171933700477\n ],\n [\n -79.4366455078125,\n 39.033052785617514\n ],\n [\n -79.42119598388672,\n 39.066913944207876\n ],\n [\n -79.41192626953125,\n 39.10182458484289\n ],\n [\n -79.40711975097656,\n 39.127663314571826\n ],\n [\n -79.42497253417967,\n 39.13645165015623\n ],\n [\n -79.45449829101562,\n 39.122602866278996\n ],\n [\n -79.48917388916016,\n 39.106886525487596\n ],\n [\n -79.52247619628906,\n 39.10315670972795\n ],\n [\n -79.552001953125,\n 39.089567854849314\n ],\n [\n -79.60487365722656,\n 39.07970763477322\n ],\n [\n -79.62959289550781,\n 39.074110680545374\n ],\n [\n -79.63645935058594,\n 39.07677595221322\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5763cdb5e4b07657d19ba775","contributors":{"authors":[{"text":"Cincotta, Daniel A.","contributorId":172052,"corporation":false,"usgs":false,"family":"Cincotta","given":"Daniel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":637102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wegman, Douglas P.","contributorId":172053,"corporation":false,"usgs":false,"family":"Wegman","given":"Douglas","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":639458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oldham, Thomas E.","contributorId":172054,"corporation":false,"usgs":false,"family":"Oldham","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":639459,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hedrick, Lara B.","contributorId":50346,"corporation":false,"usgs":true,"family":"Hedrick","given":"Lara","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":639460,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195363,"text":"70195363 - 2015 - Crowdsourced earthquake early warning","interactions":[],"lastModifiedDate":"2018-02-12T11:05:50","indexId":"70195363","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Crowdsourced earthquake early warning","docAbstract":"Earthquake early warning (EEW) can reduce harm to people and infrastructure from earthquakes and tsunamis, but it has not been implemented in most high earthquake-risk regions because of prohibitive cost. Common consumer devices such as smartphones contain low-cost versions of the sensors used in EEW. Although less accurate than scientific-grade instruments, these sensors are globally ubiquitous. Through controlled tests of consumer devices, simulation of an Mw (moment magnitude) 7 earthquake on California’s Hayward fault, and real data from the Mw 9 Tohoku-oki earthquake, we demonstrate that EEW could be achieved via crowdsourcing.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.1500036","usgsCitation":"Minson, S.E., Brooks, B.A., Glennie, C.L., Murray, J.R., Langbein, J.O., Owen, S.E., Heaton, T.H., Iannucci, R.A., and Hauser, D.L., 2015, Crowdsourced earthquake early warning: Science Advances, v. 1, no. 3, p. 1-7, https://doi.org/10.1126/sciadv.1500036.","productDescription":"e1500036; 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-059358","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472551,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.1500036","text":"Publisher Index Page"},{"id":351463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeebeee4b0da30c1bfc69a","contributors":{"authors":[{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":728144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":728143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glennie, Craig L.","contributorId":198143,"corporation":false,"usgs":false,"family":"Glennie","given":"Craig","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":728145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":728146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Langbein, John O. 0000-0002-7821-8101 langbein@usgs.gov","orcid":"https://orcid.org/0000-0002-7821-8101","contributorId":3293,"corporation":false,"usgs":true,"family":"Langbein","given":"John","email":"langbein@usgs.gov","middleInitial":"O.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":728147,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Owen, Susan E.","contributorId":202337,"corporation":false,"usgs":false,"family":"Owen","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":728148,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heaton, Thomas H.","contributorId":84739,"corporation":false,"usgs":true,"family":"Heaton","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":728149,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Iannucci, Robert A.","contributorId":202339,"corporation":false,"usgs":false,"family":"Iannucci","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":36393,"text":"Carnegie Mellon University - Silicon Valley","active":true,"usgs":false}],"preferred":false,"id":728150,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hauser, Darren L.","contributorId":202340,"corporation":false,"usgs":false,"family":"Hauser","given":"Darren","email":"","middleInitial":"L.","affiliations":[{"id":36391,"text":"University of Houston","active":true,"usgs":false}],"preferred":false,"id":728151,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70135743,"text":"70135743 - 2015 - Use of flux and morphologic sediment budgets for sandbar monitoring on the Colorado River in Marble Canyon, Arizona","interactions":[],"lastModifiedDate":"2018-04-23T13:12:06","indexId":"70135743","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Use of flux and morphologic sediment budgets for sandbar monitoring on the Colorado River in Marble Canyon, Arizona","docAbstract":"The magnitude and pfattern of streamflow and sediment supply of the Colorado River in Grand Canyon (Figure 1) has been affected by the existence and operations of Glen Canyon Dam since filling of Lake Powell Reservoir began in March 1963. In the subsequent 30 years, fine sediment was scoured from the downstream channel (Topping et al., 2000; Grams et al., 2007), resulting in a decline in the number and size of sandbars in the eastern half of Grand Canyon National Park (Wright et al., 2005; Schmidt et al., 2004). The Glen Canyon Dam Adaptive Management Program (GCDAMP) administered by the U.S. Department of Interior oversees efforts to manage the Colorado River ecosystem downstream from Glen Canyon Dam. One of the goals of the GCDAMP is to maintain and increase the number and size of sandbars in this context of a limited sand supply. Management actions to benefit sandbars have included curtailment of daily streamflow fluctuations, which occur for hydropower generation, and implementation of controlled floods, also called high-flow experiments.
Studies of controlled floods, defined as intentional releases that exceed the maximum discharge capacity of the Glen Canyon Dam powerplant, implemented between 1996 and 2008, have demonstrated that these events cause increases in sandbar size throughout Marble and Grand Canyons (Hazel et al., 2010; Schmidt and Grams, 2011; Mueller et al., 2014), although the magnitude of response is spatially variable (Hazel et al., 1999; 2010). Controlled floods may build some sandbars at the expense of erosion of sand from other, upstream, sandbars (Schmidt, 1999). To increase the frequency and effectiveness of sandbar building, the U.S. Department of Interior adopted a “high-flow experimental protocol” to implement controlled floods regularly under conditions of enriched sand supply (U.S. Department of Interior, 2012). Because the supply of sand available to build sandbars has been substantially reduced by Glen Canyon Dam (Topping et al., 2000) and depends entirely on infrequent tributary floods, monitoring of both sandbars and gross sand storage (the sand budget) is required to evaluate whether the high-flow protocol is having the intended effect of increasing sandbar size without progressively depleting sand from the system.
There are many challenges associated with monitoring sand storage and active sand deposits in a river system as large and complex as the 450-km segment of the Colorado River between Glen Canyon Dam and Lake Mead. Previous studies have demonstrated the temporal variation in sand storage associated with sand-supply limitation (Topping et al., 2000) and the spatial variability in the amount of sand stored in eddies and the channel associated with channel hydraulics (Grams et al., 2013). In this study, we report on companion measurements of sand flux and morphologic change to quantify, for the first time, the relation between changes in sand mass balance, changes in within-channel sand storage, and changes in sandbars comprehensively for a 50-km river segment of the Colorado River in lower Marble Canyon within Grand Canyon National Park.
We show that, when measured over the scale of a 50-km river segment, these complementary measurements of the sand budget agree within measurement uncertainty and provide a rare opportunity to integrate the temporally rich sand-flux record with the spatially rich morphologic measurements. Both methods show that sediment was evacuated from lower Marble Canyon over the 3-year study period. The flux-based budget shows the timing of changes in storage relative to dam-release patterns, while the morphologic measurements depict the spatial distribution of erosion and deposition among different depositional settings.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the joint federal interagency conference 2015","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"3rd Joint Federal Interagency Conference on Sedimentation and Hydrologic Modeling","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","publisherLocation":"Joint Federal Interagency Conference","usgsCitation":"Grams, P.E., Buscombe, D.D., Topping, D.J., Hazel, J.E., and Kaplinski, M., 2015, Use of flux and morphologic sediment budgets for sandbar monitoring on the Colorado River in Marble Canyon, Arizona, in Proceedings of the joint federal interagency conference 2015, Reno, NV, April 19-23, 2015, p. 1144-1155.","productDescription":"12 p.","startPage":"1144","endPage":"1155","ipdsId":"IP-061038","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":339682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339680,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2015/openconf/modules/request.php?module=oc_program&action=summary.php&id=108"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Lower Marble Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.81198120117188,\n 36.58355488335723\n ],\n [\n -111.89300537109375,\n 36.56811502180857\n ],\n [\n -111.95205688476562,\n 36.50411700054829\n ],\n [\n -111.97402954101561,\n 36.424597524795146\n ],\n [\n -111.98638916015625,\n 36.37264499608118\n ],\n [\n -112.00973510742188,\n 36.28745625417975\n ],\n [\n -111.97128295898438,\n 36.20549882293361\n ],\n [\n -111.8023681640625,\n 36.19220033141526\n ],\n [\n -111.75979614257812,\n 36.22322663069841\n ],\n [\n -111.73507690429688,\n 36.28856319836237\n ],\n [\n -111.7474365234375,\n 36.34499652561904\n ],\n [\n -111.75430297851562,\n 36.421282443649496\n ],\n [\n -111.74880981445311,\n 36.48424477824479\n ],\n [\n -111.7529296875,\n 36.55377524336089\n ],\n [\n -111.81198120117188,\n 36.58355488335723\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f08e62e4b06911a29fa85c","contributors":{"authors":[{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":536789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584 dbuscombe@usgs.gov","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":5020,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","email":"dbuscombe@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":536790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":715,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":536791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hazel, Joseph E. Jr.","contributorId":19500,"corporation":false,"usgs":true,"family":"Hazel","given":"Joseph","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":536792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaplinski, Matt","contributorId":22709,"corporation":false,"usgs":true,"family":"Kaplinski","given":"Matt","email":"","affiliations":[],"preferred":false,"id":536793,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70134263,"text":"70134263 - 2015 - Hyperspectral remote sensing for terrestrial applications","interactions":[],"lastModifiedDate":"2016-12-15T13:32:56","indexId":"70134263","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Hyperspectral remote sensing for terrestrial applications","docAbstract":"Remote sensing data are considered hyperspectral when the data are gathered from numerous wavebands, contiguously over an entire range of the spectrum (e.g., 400–2500 nm). Goetz (1992) defines hyperspectral remote sensing as “The acquisition of images in hundreds of registered, contiguous spectral bands such that for each picture element of an image it is possible to derive a complete reflectance spectrum.” However, Jensen (2004) defines hyperspectral remote sensing as “The simultaneous acquisition of images in many relatively narrow, contiguous and/or non contiguous spectral bands throughout the ultraviolet, visible, and infrared portions of the electromagnetic spectrum.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Land resources monitoring, modeling, and mapping with remote sensing","language":"English","publisher":"CRC ","usgsCitation":"Thenkabail, P.S., Teluguntla, P.G., Gumma, M.K., and Dheeravath, V., 2015, Hyperspectral remote sensing for terrestrial applications, chap. of Land resources monitoring, modeling, and mapping with remote sensing, p. 201-233.","productDescription":"33 p. ","startPage":"201","endPage":"233","ipdsId":"IP-060632","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":332168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":332166,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcnetbase.com/doi/abs/10.1201/b19322-12"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5853ba43e4b0e2663625f2ca","contributors":{"authors":[{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":525772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":525774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gumma, Murali Krishna","contributorId":127590,"corporation":false,"usgs":false,"family":"Gumma","given":"Murali","email":"","middleInitial":"Krishna","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":525775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dheeravath, Venkateswarlu","contributorId":127591,"corporation":false,"usgs":false,"family":"Dheeravath","given":"Venkateswarlu","email":"","affiliations":[{"id":7070,"text":"UN World Food Program","active":true,"usgs":false}],"preferred":false,"id":525776,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70154808,"text":"70154808 - 2015 - Fisheries research and monitoring activities of the Lake Erie Biological Station, 2014","interactions":[],"lastModifiedDate":"2016-10-20T10:12:18","indexId":"70154808","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Fisheries research and monitoring activities of the Lake Erie Biological Station, 2014","docAbstract":"In 2014, the USGS LEBS successfully completed large vessel surveys in all three of Lake Erie’s basins. Lake Erie Biological Station’s primary vessel surveys included the Western Basin Forage Fish Assessment and East Harbor Forage Fish Assessment as well as contributing to the cooperative multi-agency Central Basin Hydroacoustics Assessment, the Eastern Basin Coldwater Community Assessment, and LTLA (see FTG, CWTG, and FTG reports, respectively). Results from the surveys contribute to Lake Erie Committee Task Group data needs and analyses of trends in Lake Erie’s fish communities. The cruise survey schedule in 2014 was greatly increased by LEBS’s participation in the Lake Erie CSMI, which consisted of up-to two weeks of additional sampling per month from April to October. CSMI is a bi-national effort that occurs at Lake Erie every five years with the purpose of addressing data and knowledge gaps necessary to management agencies and the Lake Erie LaMP. LEBS deepwater science capabilities also provided a platform for data collection by Lake Erie investigators from multiple agencies and universities including: the USGS GLSC, ODW, KSU, OSU, UM, PU, UT, and the USNRL. Samples from this survey are being processed and a separate report of the findings will be made available in a separate document.
Our 2014 vessel operations were initiated in mid-April, as soon after ice-out as possible, and continued into early December. During this time, crews of the R/V Muskie and R/V Bowfin deployed 196 bottom trawls covering 48.5 km of lake-bottom, nearly 6 km of gillnet, collected data from 60 hydroacoustics transects, 285 lower trophic (i.e., zooplankton and benthos) samples, and 330 water quality measures (e.g., temperature profiles, water samples). Thus, 2014 was an intensive year of field activity.
Our June and September bottom trawl surveys in the Western Basin were numerically dominated by Emerald Shiner, White Perch, and Yellow Perch; however, Freshwater Drum were dominant by biomass. Age-2+ Yellow Perch and White Perch diets from our western basin trawl had highest occurrences of benthic invertebrates in spring and fall. Hexagenia spp. accounted for >25% of Yellow Perch and White Perch diet composition (dry weight) in spring. We conducted an analysis using data from the past 6 years of our East Harbor survey to determine to what degree our new research vessel and trawl is affecting our ability to detect trends across the 50+ year time series. We also evaluated trends in water temperatue, dissolved oxygen, secchi depth and total Phosphorus from our LTLA sites near Vermilion, Ohio. Within the following report sections, we describe specific results from our primary surveys conducted in 2014.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Compiled reports to the Great Lakes Fishery commission of the annual bottom trawl and acoustics surveys, 2014","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Bodamer Scarbro, B.L., Edwards, W., Gawne, C., Kocovsky, P.M., Kraus, R.T., Rogers, M.W., and Stewart, T., 2015, Fisheries research and monitoring activities of the Lake Erie Biological Station, 2014, 30 p.","productDescription":"30 p.","startPage":"3","endPage":"32","ipdsId":"IP-064179","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":330133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":330132,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.glfc.org/lakecom/common_docs/Compiled%20Reports%20from%20USGS%202015.pdf"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5809d7c4e4b0f497e78fca6f","contributors":{"authors":[{"text":"Bodamer Scarbro, Betsy L. 0000-0002-9022-7027 bbodamerscarbro@usgs.gov","orcid":"https://orcid.org/0000-0002-9022-7027","contributorId":5857,"corporation":false,"usgs":true,"family":"Bodamer Scarbro","given":"Betsy","email":"bbodamerscarbro@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":564217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, William wedwards@usgs.gov","contributorId":3668,"corporation":false,"usgs":true,"family":"Edwards","given":"William","email":"wedwards@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":564218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gawne, Carrie cgawne@usgs.gov","contributorId":145493,"corporation":false,"usgs":true,"family":"Gawne","given":"Carrie","email":"cgawne@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":564219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kocovsky, Patrick M. 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":3429,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","middleInitial":"M.","affiliations":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":564220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":564216,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564221,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stewart, Taylor trstewart@usgs.gov","contributorId":145494,"corporation":false,"usgs":true,"family":"Stewart","given":"Taylor","email":"trstewart@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":564222,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70156793,"text":"70156793 - 2015 - Geologic framework and evidence for neotectonism in the epicentral area of the 2011 Mineral, Virginia, earthquake","interactions":[],"lastModifiedDate":"2017-04-19T12:45:41","indexId":"70156793","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Geologic framework and evidence for neotectonism in the epicentral area of the 2011 Mineral, Virginia, earthquake","docAbstract":"The epicenters of the main shock and associated aftershocks of the 2011 moment magnitude, Mw 5.8 Mineral, Virginia (USA), earthquake, and the updip projection of the possible fault plane that triggered the quakes, are contained in the areas of 2 adjoining 7.5′ quadrangles in the central Virginia Piedmont. These quadrangles have therefore been the focus of concentrated geologic study in the form of bedrock and surficial mapping and near-surface trenching in order to identify potential seismogenic structures. Bedrock mapping has outlined a series of northeast-southwest–trending lithologic belts that include the Ordovician Chopawamsic and Quantico Formations, the narrow neck of the Late Ordovician Ellisville pluton, and mélange zone III of the Mine Run Complex. The region was affected by at least two ductile deformational events, one in the early Paleozoic that was broadly synchronous with the intrusion of the pluton, and one later in the Paleozoic. The earlier deformation produced the Quantico synclinorium and other regional folds, and the later deformation produced faults with associated high-strain zones. Two of these faults have been trenched at their intersection along the east-dipping eastern contact of the Ellisville neck, near where the causative fault for the earthquake projects to the surface. The trenches have exposed abundant evidence of post-Paleozoic fracturing and faulting, including brecciated quartz-tourmaline veins, slickensided thrust and strike-slip faults, and clay-filled fractures. Fluvial and colluvial gravels that overlie these brittle structures have yielded optically stimulated luminescence ages ranging from ca. 27 to 10 ka. These structures are likely representative of surface features associated with Quaternary earthquakes in the Central Virginia seismic zone.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2015.2509(20)","usgsCitation":"Burton, W.C., Harrison, R., Spears, D., Evans, N.H., and Mahan, S.A., 2015, Geologic framework and evidence for neotectonism in the epicentral area of the 2011 Mineral, Virginia, earthquake: GSA Special Papers, v. 509, p. 345-376, https://doi.org/10.1130/2015.2509(20).","productDescription":"32 p.","startPage":"345","endPage":"376","ipdsId":"IP-053258","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":339965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"509","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f877bfe4b0b7ea54521c36","contributors":{"authors":[{"text":"Burton, William C. 0000-0001-7519-5787 bburton@usgs.gov","orcid":"https://orcid.org/0000-0001-7519-5787","contributorId":1293,"corporation":false,"usgs":true,"family":"Burton","given":"William","email":"bburton@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":570563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Richard W. rharriso@usgs.gov","contributorId":544,"corporation":false,"usgs":true,"family":"Harrison","given":"Richard W.","email":"rharriso@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":570564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spears, David B.","contributorId":147157,"corporation":false,"usgs":false,"family":"Spears","given":"David B.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":570565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, Nicholas H.","contributorId":147158,"corporation":false,"usgs":false,"family":"Evans","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":570566,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":570567,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157120,"text":"70157120 - 2015 - Tsunami geology in paleoseismology","interactions":[],"lastModifiedDate":"2016-09-09T13:47:56","indexId":"70157120","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Tsunami geology in paleoseismology","docAbstract":"The 2004 Indian Ocean and 2011 Tohoku-oki disasters dramatically demonstrated the destructiveness and deadliness of tsunamis. For the assessment of future risk posed by tsunamis it is necessary to understand past tsunami events. Recent work on tsunami deposits has provided new information on paleotsunami events, including their recurrence interval and the size of the tsunamis (e.g. [187–189]). Tsunamis are observed not only on the margin of oceans but also in lakes. The majority of tsunamis are generated by earthquakes, but other events that displace water such as landslides and volcanic eruptions can also generate tsunamis. These non-earthquake tsunamis occur less frequently than earthquake tsunamis; it is, therefore, very important to find and study geologic evidence for past eruption and submarine landslide triggered tsunami events, as their rare occurrence may lead to risks being underestimated. Geologic investigations of tsunamis have historically relied on earthquake geology. Geophysicists estimate the parameters of vertical coseismic displacement that tsunami modelers use as a tsunami's initial condition. The modelers then let the simulated tsunami run ashore. This approach suffers from the relationship between the earthquake and seafloor displacement, the pertinent parameter in tsunami generation, being equivocal. In recent years, geologic investigations of tsunamis have added sedimentology and micropaleontology, which focus on identifying and interpreting depositional and erosional features of tsunamis. For example, coastal sediment may contain deposits that provide important information on past tsunami events [190, 191]. In some cases, a tsunami is recorded by a single sand layer. Elsewhere, tsunami deposits can consist of complex layers of mud, sand, and boulders, containing abundant stratigraphic evidence for sediment reworking and redeposition. These onshore sediments are geologic evidence for tsunamis and are called ‘tsunami deposits’ (Figs. 26 and 27). Tsunami deposits can be classified into two groups: modern tsunami deposits and paleotsunami deposits. A modern tsunami deposit is a deposit whose source event is known. A paleotsunami deposit is a deposit whose age is estimated and has a source that is either inferred to be a historical event or is unknown.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The Contribution of Palaeoseismology to Seismic Hazard Assessment in Site Evaluation for Nuclear Installations","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"International Atomic Energy Agency","collaboration":"IAEA","usgsCitation":"Nishimura, Y., and Jaffe, B.E., 2015, Tsunami geology in paleoseismology, 16 p.","productDescription":"16 p.","startPage":"66","endPage":"81","ipdsId":"IP-057890","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":307971,"type":{"id":15,"text":"Index Page"},"url":"https://www-pub.iaea.org/MTCD/Publications/PDF/TE-1767_web.pdf"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d3dd3ee4b0571647d19ae1","contributors":{"authors":[{"text":"Nishimura, Yuichi","contributorId":147449,"corporation":false,"usgs":false,"family":"Nishimura","given":"Yuichi","email":"","affiliations":[{"id":16855,"text":"Hokkaido University","active":true,"usgs":false}],"preferred":false,"id":571733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":571732,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148496,"text":"70148496 - 2015 - 2014 National Park visitor spending effects: economic contributions to local communities, states, and the nation","interactions":[],"lastModifiedDate":"2016-08-18T16:29:28","indexId":"70148496","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NRSS/EQD/NRR—2015/947","title":"2014 National Park visitor spending effects: economic contributions to local communities, states, and the nation","docAbstract":"The National Park System covers more than 84 million acres and is comprised of more than 401 sites across the Nation. These lands managed by the National Park Service (NPS) serve as recreational destinations for visitors from across the Nation and around the world. On vacations or on day trips, NPS visitors spend time and money in the gateway communities surrounding NPS sites. Spending by NPS visitors generates and supports a considerable amount of economic activity within park gateway economies. The NPS has been measuring and reporting visitor spending and economic effects for the past 25 years. The 2012 analysis marked a major revision to the NPS visitor spending effects analyses, with the development of the Visitor Spending Effects model (VSE model) which replaced the previous Money Generation Model (see Cullinane Thomas et al. (2014) for a description of how the VSE model differs from the previous model). This report provides updated VSE estimates associated with 2014 NPS visitation.
\nSystem-wide visitation estimates in 2014 increased by 7% (or 19.2 million visits) compared to 2013 (Ziesler, 2015). Visitation in 2014 rebounded from a 2013 decline that included a 16-day government shutdown and many park closures for repairs after Superstorm Sandy hit the Northeast in late 2012. The re-opening of the Washington Monument, some 21 months after it was rocked by an earthquake and repaired, also added to 2014 visitation numbers. Additionally, several national parks saw record-breaking visitation in 2014, including Joshua Tree, Rocky Mountain, Grand Teton and Glacier national parks.
\nThis report begins by presenting an overview of economic effects analyses, followed by details about the data and methods used for this analysis and 2014 model updates. Estimates of NPS visitor spending in 2014 and resulting economic effects at the local, state, regional, and national levels are then presented. The report concludes with a description of current data limitations. Park-level spending and economic effects estimates are included in the appendix.
\nNew this year, results from the Visitor Spending Effects report series are available online via an interactive tool. Users can explore current year visitor spending, jobs, labor income, value added, and output effects by sector for national, state, and local economies. This interactive tool is available via the NPS Social Science Program webpage at http://www.nature.nps.gov/socialscience/economics.cfm.
","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","collaboration":"National Park Service","usgsCitation":"Cullinane Thomas, C., Huber, C., and Koontz, L., 2015, 2014 National Park visitor spending effects: economic contributions to local communities, states, and the nation: Natural Resource Report NPS/NRSS/EQD/NRR—2015/947, vi, 42 p.","productDescription":"vi, 42 p.","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064070","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":326860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":301102,"type":{"id":11,"text":"Document"},"url":"https://www.nature.nps.gov/socialscience/docs/VSE2014_Final.pdf"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57b6dc2ee4b03fd6b7d94bf5","contributors":{"authors":[{"text":"Cullinane Thomas, Catherine 0000-0001-8168-1271 ccullinanethomas@usgs.gov","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":141097,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine","email":"ccullinanethomas@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":548431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":548432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koontz, Lynne koontzl@usgs.gov","contributorId":2174,"corporation":false,"usgs":false,"family":"Koontz","given":"Lynne","email":"koontzl@usgs.gov","affiliations":[{"id":7016,"text":"Environmental Quality Division, National Park Service, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":548433,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176591,"text":"70176591 - 2015 - Suspended-sediment dynamics in the tidal reach of a San Francisco Bay tributary","interactions":[],"lastModifiedDate":"2017-02-28T12:27:40","indexId":"70176591","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Suspended-sediment dynamics in the tidal reach of a San Francisco Bay tributary","docAbstract":"To better understand suspended-sediment transport in a tidal slough adjacent to a large wetland restoration project, we deployed continuously-measuring temperature, salinity, depth, turbidity, and velocity sensors since 2010, and added a dissolved-oxygen sensor in 2012, at a near-bottom location in Alviso Slough (Alviso, California USA). Alviso Slough is the downstream reach of the Guadalupe River and flows into the far southern end of San Francisco Bay. River flow is influenced by the Mediterranean climate, with high flows correlated to episodic winter storms (~85 m3 s-1) and low base flow during the summer (~0.85 m3 s-1). Storms and associated runoff have the greatest influence on sediment flux. Strong spring tides promote upstream sediment flux and weak neap tides have only a small net flux. During neap tides, stratification likely suppresses sediment transport during weaker flood and ebb tides.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 17th physics of estuaries and coastal seas (PECS) conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"17th physics of estuaries and coastal seas (PECS) conference","conferenceDate":"19–24 October 2014","conferenceLocation":"Porto de Galinhas, Pernambuco, Brazil","language":"English","collaboration":"California State Coastal Conservancy","usgsCitation":"Shellenbarger, G., Downing-Kunz, M.A., and Schoellhamer, D., 2015, Suspended-sediment dynamics in the tidal reach of a San Francisco Bay tributary, in Proceedings of the 17th physics of estuaries and coastal seas (PECS) conference, Porto de Galinhas, Pernambuco, Brazil, 19–24 October 2014, 4 p.","productDescription":"4 p.","ipdsId":"IP-058075","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":336337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328849,"type":{"id":15,"text":"Index Page"},"url":"https://www.southbayrestoration.org/documents/technical/shellenbarger_etal_PECS2014_final.pdf"}],"country":"United States","state":"California","otherGeospatial":"Southern reach of San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.05810546875,\n 37.42688834526727\n ],\n [\n -121.07894897460938,\n 36.20660692859011\n ],\n [\n -120.80017089843749,\n 35.94688293218141\n ],\n [\n -120.574951171875,\n 36.1245647481333\n ],\n [\n -121.90979003906249,\n 37.47485808497102\n ],\n [\n -122.05810546875,\n 37.42688834526727\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b69a42e4b01ccd54ff3fac","contributors":{"authors":[{"text":"Shellenbarger, Gregory gshellen@usgs.gov","contributorId":174805,"corporation":false,"usgs":true,"family":"Shellenbarger","given":"Gregory","email":"gshellen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Downing-Kunz, Maureen A. 0000-0002-4879-0318 mdowning-kunz@usgs.gov","orcid":"https://orcid.org/0000-0002-4879-0318","contributorId":3690,"corporation":false,"usgs":true,"family":"Downing-Kunz","given":"Maureen","email":"mdowning-kunz@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649293,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70112434,"text":"70112434 - 2015 - Sea lamprey mark type, wounding rate, and parasite-host preference and abundance relationships for lake trout and other species in Lake Ontario","interactions":[],"lastModifiedDate":"2020-09-25T13:30:47.140171","indexId":"70112434","displayToPublicDate":"2014-12-31T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Sea lamprey mark type, wounding rate, and parasite-host preference and abundance relationships for lake trout and other species in Lake Ontario","docAbstract":"We examined how the frequency of attacks by Sea Lamprey on fishes in Lake Ontario varied in response to Sea Lamprey abundance and preferred host abundance (Lake Trout >432mm). For this analysis we assembled seven data sets. Two fishery independent surveys for Lake Trout: US Geological Survey (USGS)/New York State Department of Environmental Conservation (NYSDEC) south shore September gillnet assessment of adult Lake Trout (USGS/NYSDEC SGNS)(Lantry and Lantry 2011); and Ontario Ministry of Natural Resources (OMNR) monthly June-November community index gillnetting in northeastern Lake Ontario (OMNR CIS) (Ontario Ministry of Natural Resources 2011). One angler survey: NYSDEC April-September Fishing Boat Survey data collected along the south shore for Chinook and Coho salmon, and Rainbow and Brown trout (NYSDEC FBS) (Lantry and Eckert 2012). Two spawning run datasets: OMNR north shore data including spring spawning runs of Rainbow Trout in the Ganaraska River and electroshocking data for fall spawning runs of Chinook and Coho salmon in the Credit River (Ontario Ministry of Natural Resources 2011); and NYSDEC data from the Salmon River on the southeastern shore including October spawning runs of Chinook and Coho salmon. One Sea Lamprey spawning survey: Department of Fisheries and Oceans Canada (DFO)/US Fish and Wildlife Service (USFWS) data for spawning-phase Sea Lamprey abundance collected from known spawning streams distributed throughout the Lake Ontario drainage basin (Mullet et al. 2003). One assessment of the abundance of dead Lake Trout: USGS/NYSDEC October-November bottom trawl collection of Lake Trout carcasses (Schneider et al. 1996).
Annual patterns in A1, A2 and A3 wound stages did not track well in plots of wounding rates for the USGS/NYSDEC SGNS and correlations between A1 and later stages did not exist. A1 rates were not correlated to either Lake Trout abundance or Sea Lamprey numbers when considered alone, but were strongly correlated to the ratio between Sea Lamprey numbers and Lake Trout abundance (parasite/host ratio). While A2 and A3 rates were correlated to each other, neither was consistently correlated to any of the Lake Trout abundance or Sea Lamprey abundance parameters and sums of A1 to A3 rates did not improve correlations over those for A1 rates considered alone. Our analysis of the strain-specific susceptibility of Lake Trout to attack by Sea Lampreys extended the previous Schneider et al. (1996) analysis of three strains (SUP, CWL, and SEN) and 11 years of data 1982-1992 to an analysis of seven strains (SUP, CWL, SEN, JEN, LEW, ONT, and OXS) and two groups of unmarked fish (1983-1995 and 1996-2010) and included 18 more years of data through 2010. The susceptibility to attack for CWLs and SENs were below SUPs and nearly identical to the earlier values, new values for LEWs were greater than SUPS and values of unmarked Lake Trout prior to 1996 were unexpectedly greater than SUPs. By reexamining the Schneider et al. (1996) regression relationship between A1 wounding on Lake Trout and the incidence of Lake Trout carcasses recovered in fall bottom trawls (including three additional years of data), and substituting A1 wounding rate for total numbers of A1s observed which was used as the independent variable in the previous version, we were able to increase the variance explained by the relationship from an r2 of 0.60 to 0.88. Healing rate of wounds was explored by examining the monthly incidence of A1 and A2 wounds on Lake Trout from the OMNR CIS. Because wounding intensity varied between years and monthly sample size was frequently low, the ratio of A2 to A1s wounds was used to index how wounds accumulated or disappeared from the Lake Trout populations across seasons. The A2/A1 ratio decreased between June/July and October. A simple wounding model for Lake Trout was constructed to simulate the pattern of ratios by inflicting wounds on the population each month according to a predetermined distribution and including parameters for lethality (fixed distribution) and healing rate of A1 and A2 wounds (discretely varied between simulations). The best simulated representation (ratio size and monthly pattern) of the OMNR CIS data came from an A1 healing rate of 0.5 months and an A2 rate of 2 months. To examine whether alternate hosts provided reliable data to index damage caused by Sea Lampreys we compared September values of abundance and A1 wounding rates on Lake Trout, Sea Lamprey abundance, and the parasite/host ratio with NYSDEC Creel data for observations of Sea lampreys attached to sport-caught salmonids and to wounding observations for salmonids sampled in OMNR and NYSDEC spawning run assessments. Attachment frequency on NYSDEC Creel Chinook Salmon, Brown Trout, and Rainbow Trout were strongly correlated to all measures of Lake Trout abundance and wounding and to the parasite/host ratio. Chinook Salmon and Coho Salmon wounding observations for the NYSDEC Salmon River spawning run assessments and Rainbow Trout from the OMNR Ganaraska River spawning run assessment were strongly correlated to wounding measures for nearly all salmonids and to the parasite/host ratio.
","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Toronto","usgsCitation":"Lantry, B.F., Adams, J., Christie, G., Schaner, T., Bowlby, J., Keir, M., Lantry, J., Sullivan, P., Bishop, D., Treska, T., and Morrison, B., 2015, Sea lamprey mark type, wounding rate, and parasite-host preference and abundance relationships for lake trout and other species in Lake Ontario.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043637","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":312940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378722,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/pubs/pdfs/research/reports/Lantry_2014.html"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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Our algorithm partitions a time series of water levels into discrete recharge episodes and intervals of no episodic recharge. It correlates each recharge episode with a specific interval of rainfall, so storm characteristics such as intensity and duration can be associated with the amount of recharge that results. To be useful in humid climates, the algorithm evaluates the separability of events, so that those whose recharge cannot be associated with a single storm can be appropriately lumped together. Elements of this method that are subject to subjectivity in the application of hydrologic judgment are values of lag time, fluctuation tolerance, and master recession parameters. Because these are determined once for a given site, they do not contribute subjective influences affecting episode-to-episode comparisons. By centralizing the elements requiring scientific judgment, our method facilitates such comparisons by keeping the most subjective elements openly apparent, making it easy to maintain consistency. If applied to a period of data long enough to include recharge episodes with broadly diverse characteristics, the method has value for predicting how climatic alterations in the distribution of storm intensities and seasonal duration may affect recharge.
","language":"English","publisher":"Wiley-Blackwell Publishing, Inc.","doi":"10.1111/gwat.12177","usgsCitation":"Nimmo, J.R., Horowittz, C., and Mitchell, L., 2015, Discrete-storm water-table fluctuation method to estimate episodic recharge.: Groundwater, v. 53, no. 2, p. 282-292, https://doi.org/10.1111/gwat.12177.","productDescription":"11 p.","startPage":"282","endPage":"292","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046105","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":297223,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-03","publicationStatus":"PW","scienceBaseUri":"54dd2a6ce4b08de9379b3050","chorus":{"doi":"10.1111/gwat.12177","url":"http://dx.doi.org/10.1111/gwat.12177","publisher":"Wiley-Blackwell","authors":"Nimmo John R., Horowitz Charles, Mitchell Lara","journalName":"Groundwater","publicationDate":"3/3/2014","auditedOn":"3/4/2015"},"contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":538091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horowittz, Charles","contributorId":138611,"corporation":false,"usgs":false,"family":"Horowittz","given":"Charles","email":"","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":538090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, Lara","contributorId":138612,"corporation":false,"usgs":false,"family":"Mitchell","given":"Lara","email":"","affiliations":[{"id":12466,"text":"Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":538092,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189610,"text":"70189610 - 2015 - Validation of the SCEC broadband platform V14.3 simulation methods using pseudo spectral acceleration data","interactions":[],"lastModifiedDate":"2017-07-19T10:10:30","indexId":"70189610","displayToPublicDate":"2014-12-31T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Validation of the SCEC broadband platform V14.3 simulation methods using pseudo spectral acceleration data","docAbstract":"This paper summarizes the evaluation of ground motion simulation methods implemented on the SCEC Broadband Platform (BBP), version 14.3 (as of March 2014). A seven-member panel, the authorship of this article, was formed to evaluate those methods for the prediction of pseudo-‐spectral accelerations (PSAs) of ground motion. The panel’s mandate was to evaluate the methods using tools developed through the validation exercise (Goulet et al. ,2014), and to define validation metrics for the assessment of the methods’ performance. This paper summarizes the evaluation process and conclusions from the panel. The five broadband, finite-source simulation methods on the BBP include two deterministic approaches herein referred to as CSM (Anderson, 2014) and UCSB (Crempien and Archuleta, 2014); a band-‐limited stochastic white noise method called EXSIM (Atkinson and Assatourians, 2014); and two hybrid approaches, referred to as G&P (Graves and Pitarka, 2014) and SDSU (Olsen and Takedatsu, 2014), which utilize a deterministic Green’s function approach for periods longer than 1 second and stochastic methods for periods shorter than 1 second. \n\nTwo acceptance tests were defined to validate the broadband finite‐source ground methods (Goulet et al., 2014). Part A compared observed and simulated PSAs for periods from 0.01 to 10 seconds for 12 moderate to large earthquakes located in California, Japan, and the eastern US. Part B compared the median simulated PSAs to published NGA-‐West1 (Abrahamson and Silva, 2008; Boore and Atkinson, 2008; Campbell and Bozorgnia, 2008; and Chiou and Youngs, 2008) ground motion prediction equations (GMPEs) for specific magnitude and distance cases using a pass-‐fail criteria based on a defined acceptable range around the spectral shape of the GMPEs. For the initial Part A and Part B validation exercises during the summer of 2013, the software for the five methods was locked in at version 13.6 (see Maechling et al., 2014). In the spring of 2014, additional moderate events were considered for the Part A validation, and additional magnitude and distance cases were considered for the Part B validation, for the software locked in at version 14.3. Several of the simulation procedures, specifically UCSB and SDSU, changed significantly between versions 13.6 and 14.3. The CSM code was not submitted in time for the v14.3 evaluation and its detailed performance is not addressed in this paper. \n\nAs described in Goulet et al. (2014) and Maechling et al. (2014), the BBP generates a variety of products, including three-‐component acceleration time series. A series of post-‐processing codes were developed to provide individual component PSAs and average median horizontal-‐component PSA (referred to as RotD50; Boore, 2010) for oscillator periods ranging from 0.01 to 10 seconds, as well as median PSA values computed using the NGA-‐West 1 GMPEs. The BBP was also configured to provide statistical analysis of simulation results relative to recordings (Part A) and GMPEs (Part B) as described further in sections below. \n\nAs part of our evaluation, we reviewed documentation provided by each of the developers, which included the technical basis behind the methods and the developer’s self-‐assessments regarding the extrapolation capabilities (in terms of magnitude and distance ranges) of their methods. Two workshops were held in which methods and results were presented, and the panel was given the opportunity to question the developers and to have detailed technical discussions. A SCEC report (Dreger et al., 2013) describes the results of this review for BBP version 13.6. This paper summarizes that work and presents results for the more recent BBP 14.3 validation.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220140118","usgsCitation":"Dreger, D.S., Beroza, G.C., Day, S.M., Goulet, C.A., Jordan, T.H., Spudich, P.A., and Stewart, J.P., 2015, Validation of the SCEC broadband platform V14.3 simulation methods using pseudo spectral acceleration data: Seismological Research Letters, v. 86, no. 1, p. 39-47, https://doi.org/10.1785/0220140118.","productDescription":"9 p.","startPage":"39","endPage":"47","ipdsId":"IP-059822","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-17","publicationStatus":"PW","scienceBaseUri":"59706fbae4b0d1f9f065a8db","contributors":{"authors":[{"text":"Dreger, Douglas S.","contributorId":55600,"corporation":false,"usgs":false,"family":"Dreger","given":"Douglas","email":"","middleInitial":"S.","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":705405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":705406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day, Steven M.","contributorId":194804,"corporation":false,"usgs":false,"family":"Day","given":"Steven","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":705407,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goulet, Christine A. 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":194805,"corporation":false,"usgs":false,"family":"Goulet","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":705408,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jordan, Thomas H","contributorId":194144,"corporation":false,"usgs":false,"family":"Jordan","given":"Thomas","email":"","middleInitial":"H","affiliations":[],"preferred":false,"id":705409,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spudich, Paul A. 0000-0002-9484-4997 spudich@usgs.gov","orcid":"https://orcid.org/0000-0002-9484-4997","contributorId":2372,"corporation":false,"usgs":true,"family":"Spudich","given":"Paul","email":"spudich@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":705404,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":705410,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70158934,"text":"70158934 - 2015 - Automated lidar-derived canopy height estimates for the Upper Mississippi River System","interactions":[],"lastModifiedDate":"2017-05-08T14:16:30","indexId":"70158934","displayToPublicDate":"2014-12-31T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":21,"text":"Thesis"},"publicationSubtype":{"id":28,"text":"Thesis"},"title":"Automated lidar-derived canopy height estimates for the Upper Mississippi River System","docAbstract":"Land cover/land use (LCU) classifications serve as important decision support products for researchers and land managers. The LCU classifications produced by the U.S. Geological Survey’s Upper Midwest Environmental Sciences Center (UMESC) include canopy height estimates that are assigned through manual aerial photography interpretation techniques. In an effort to improve upon these techniques, this project investigated the use of high-density lidar data for the Upper Mississippi River System to determine canopy height. An ArcGIS tool was developed to automatically derive height modifier information based on the extent of land cover features for forest classes. The measurement of canopy height included a calculation of the average height from lidar point cloud data as well as the inclusion of a local maximum filter to identify individual tree canopies. Results were compared to original manually interpreted height modifiers and to field survey data from U.S. Forest Service Forest Inventory and Analysis plots. This project demonstrated the effectiveness of utilizing lidar data to more efficiently assign height modifier attributes to LCU classifications produced by the UMESC.","language":"English","publisher":"University of Redlands","usgsCitation":"Hlavacek, E., 2015, Automated lidar-derived canopy height estimates for the Upper Mississippi River System, xviI, 70 p.","productDescription":"xviI, 70 p.","ipdsId":"IP-061233","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":340736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":309736,"type":{"id":15,"text":"Index Page"},"url":"https://inspire.redlands.edu/gis_gradproj/218/"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.22875213623045,\n 43.57392416032963\n ],\n [\n -91.22188568115234,\n 43.6159452654277\n ],\n [\n -91.22222900390625,\n 43.645019610189216\n ],\n [\n -91.22085571289061,\n 43.6599240747891\n ],\n [\n -91.219482421875,\n 43.68574971761676\n ],\n [\n -91.20712280273438,\n 43.705608034103555\n ],\n [\n -91.20162963867188,\n 43.766135280960974\n ],\n [\n -91.22909545898436,\n 43.78299262890581\n ],\n [\n -91.25106811523438,\n 43.8028187190472\n ],\n [\n -91.24969482421875,\n 43.82660134505382\n ],\n [\n -91.26480102539062,\n 43.86720808597874\n ],\n [\n -91.27578735351561,\n 43.8909650585739\n ],\n [\n -91.33621215820312,\n 43.88502670347002\n ],\n [\n -91.30050659179688,\n 43.85631630786513\n ],\n [\n -91.30050659179688,\n 43.83947964604012\n ],\n [\n -91.307373046875,\n 43.823629034783124\n ],\n [\n -91.29364013671875,\n 43.81372026502735\n ],\n [\n -91.285400390625,\n 43.80876526350847\n ],\n [\n -91.29226684570312,\n 43.79588033566535\n ],\n [\n -91.28952026367188,\n 43.7859669617277\n ],\n [\n -91.28059387207031,\n 43.78447981381514\n ],\n [\n -91.263427734375,\n 43.7824968923812\n ],\n [\n -91.25518798828125,\n 43.77406874252176\n ],\n [\n -91.25724792480469,\n 43.75919263886012\n ],\n [\n -91.26274108886719,\n 43.73736766145917\n ],\n [\n -91.27372741699219,\n 43.71652730498859\n ],\n [\n -91.27372741699219,\n 43.69716905314008\n ],\n [\n -91.27922058105469,\n 43.68326696566219\n ],\n [\n -91.28059387207031,\n 43.67532146891089\n ],\n [\n -91.28196716308594,\n 43.667871610117494\n ],\n [\n -91.27922058105469,\n 43.64899449575356\n ],\n [\n -91.2744140625,\n 43.614205328810954\n ],\n [\n -91.27784729003906,\n 43.601278509333646\n ],\n [\n -91.28368377685545,\n 43.597797737126044\n ],\n [\n -91.28059387207031,\n 43.57591398669178\n ],\n [\n -91.27029418945312,\n 43.561486255932145\n ],\n [\n -91.23115539550781,\n 43.560491112629286\n ],\n [\n -91.22875213623045,\n 43.57392416032963\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59099aafe4b0fc4e44915800","contributors":{"authors":[{"text":"Hlavacek, Enrika 0000-0002-9872-2305 ehlavacek@usgs.gov","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":149114,"corporation":false,"usgs":true,"family":"Hlavacek","given":"Enrika","email":"ehlavacek@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576947,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70160314,"text":"70160314 - 2015 - Complex interactions between global change drivers influence mountain forest and slpine GHG sequestration and stream chemistry","interactions":[],"lastModifiedDate":"2018-02-21T17:55:11","indexId":"70160314","displayToPublicDate":"2014-12-31T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Complex interactions between global change drivers influence mountain forest and slpine GHG sequestration and stream chemistry","docAbstract":"Many mountain ecosystems are experiencing coincident increases\nin temperature, levels of atmospheric carbon dioxide (CO2) and\natmospheric nitrogen (N) deposition. All are important controls\non rates of plant growth, soil microbial activity, nutrient cycling,\nand stream N export. It is difficult for experimental studies to\nexplore ecosystem responses to more than one or two treatments\nat plot, let alone catchment, scale. One might expect, however,\necosystems to respond differently to the combined global change\ndrivers than to climate, CO2, or N alone. We explored this\nquestion for nine mountain catchments over the period 1980-\n2075 with a simulation model.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mountain Views","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"USDA Forest Service","usgsCitation":"Baron, J., and Hartman, M.D., 2015, Complex interactions between global change drivers influence mountain forest and slpine GHG sequestration and stream chemistry, in Mountain Views, v. 8, no. 1, p. 24-26.","productDescription":"3 p.","startPage":"24","endPage":"26","ipdsId":"IP-056121","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":340469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340468,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.fed.us/psw/cirmount/publications/mtnviews.shtml"}],"country":"United States","volume":"8","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5901b1bfe4b0c2e071a99bae","contributors":{"authors":[{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":582509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartman, Melannie D.","contributorId":98836,"corporation":false,"usgs":true,"family":"Hartman","given":"Melannie","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":582510,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}