Although uranium series (U-series) ages of growth-position fossil corals are important to Quaternary sea-level history, coral clast reworking from storms can yield ages on a terrace dating to more than one high-sea stand, confounding interpretations of sea-level history. On northern Barbados, U-series ages corals from a thick storm deposit are not always younger with successively higher stratigraphic positions, but all date to the last interglacial period (~127 ka to ~112 ka), Marine Isotope Substage (MIS) 5.5. The storm deposit ages are consistent with the ages of growth-position corals found at the base of the section and at landward localities on this terrace. Thus, in this case, analysis of only a few corals would not have led to an error in interpreting sea-level history. In contrast, a notch cut into older Pleistocene limestone below the MIS 5.5 terrace contains corals that date to both MIS 5.5 (~125 ka) and MIS 5.3 (~108 ka). We infer that the notch formed during MIS 5.3 and the MIS 5.5 corals are reworked. Similar multiple ages of corals on terraces have been reported elsewhere on Barbados. Thus, care must be taken in interpreting U-series ages of corals that are reported without consideration of taphonomy.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2017.70","usgsCitation":"Muhs, D., and Simmons, K.R., 2017, Taphonomic problems in reconstructing sea-level history from the late Quaternary marine terraces of Barbados: Quaternary Research, v. 88, no. 3, p. 409-429, https://doi.org/10.1017/qua.2017.70.","productDescription":"21 p.","startPage":"409","endPage":"429","ipdsId":"IP-077778","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":348167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Barbados","volume":"88","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-11","publicationStatus":"PW","scienceBaseUri":"59fd8028e4b0531197b5013d","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":168575,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel R.","email":"dmuhs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":719984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simmons, Kathleen R. 0000-0002-7920-094X ksimmons@usgs.gov","orcid":"https://orcid.org/0000-0002-7920-094X","contributorId":199770,"corporation":false,"usgs":true,"family":"Simmons","given":"Kathleen","email":"ksimmons@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":719986,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193728,"text":"70193728 - 2017 - Oiling accelerates loss of salt marshes, southeastern Louisiana","interactions":[],"lastModifiedDate":"2017-11-03T18:59:09","indexId":"70193728","displayToPublicDate":"2017-11-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Oiling accelerates loss of salt marshes, southeastern Louisiana","docAbstract":"The 2010 BP Deepwater Horizon (DWH) oil spill damaged thousands of km2 of intertidal marsh along shorelines that had been experiencing elevated rates of erosion for decades. Yet, the contribution of marsh oiling to landscape-scale degradation and subsequent land loss has been difficult to quantify. Here, we applied advanced remote sensing techniques to map changes in marsh land cover and open water before and after oiling. We segmented the marsh shorelines into non-oiled and oiled reaches and calculated the land loss rates for each 10% increase in oil cover (e.g. 0% to >70%), to determine if land loss rates for each reach oiling category were significantly different before and after oiling. Finally, we calculated background land-loss rates to separate natural and oil-related erosion and land loss. Oiling caused significant increases in land losses, particularly along reaches of heavy oiling (>20% oil cover). For reaches with ≥20% oiling, land loss rates increased abruptly during the 2010–2013 period, and the loss rates during this period are significantly different from both the pre-oiling (p < 0.0001) and 2013–2016 post-oiling periods (p < 0.0001). The pre-oiling and 2013–2016 post-oiling periods exhibit no significant differences in land loss rates across oiled and non-oiled reaches (p = 0.557). We conclude that oiling increased land loss by more than 50%, but that land loss rates returned to background levels within 3–6 years after oiling, suggesting that oiling results in a large but temporary increase in land loss rates along the shoreline.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0181197","usgsCitation":"Beland, M., Biggs, T.W., Roberts, D.A., Peterson, S.H., Kokaly, R.F., and Piazza, S., 2017, Oiling accelerates loss of salt marshes, southeastern Louisiana: PLoS ONE, v. 12, no. 8, Article e0181197; 20 p., https://doi.org/10.1371/journal.pone.0181197.","productDescription":"Article e0181197; 20 p.","ipdsId":"IP-084021","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":469352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0181197","text":"Publisher Index Page"},{"id":348181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.95139,\n 29.5\n ],\n [\n -89.82083,\n 29.5\n ],\n [\n -89.82083,\n 29.415\n ],\n [\n -89.95139,\n 29.415\n ],\n [\n -89.95139,\n 29.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-02","publicationStatus":"PW","scienceBaseUri":"59fd8026e4b0531197b50136","contributors":{"authors":[{"text":"Beland, Michael","contributorId":139569,"corporation":false,"usgs":false,"family":"Beland","given":"Michael","email":"","affiliations":[{"id":12805,"text":"Univ. of California at San Diego","active":true,"usgs":false}],"preferred":false,"id":720086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biggs, Trent W.","contributorId":187592,"corporation":false,"usgs":false,"family":"Biggs","given":"Trent","email":"","middleInitial":"W.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":720087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Dar A.","contributorId":100503,"corporation":false,"usgs":false,"family":"Roberts","given":"Dar","email":"","middleInitial":"A.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":720088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Seth H.","contributorId":139568,"corporation":false,"usgs":false,"family":"Peterson","given":"Seth","email":"","middleInitial":"H.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":720089,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":150717,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"raymond@usgs.gov","middleInitial":"F.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":720085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piazza, Sarai 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":169024,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":720090,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193737,"text":"70193737 - 2017 - Biocrust ecology: Unifying micro- and macro-scales to confront global change","interactions":[],"lastModifiedDate":"2017-11-03T17:49:33","indexId":"70193737","displayToPublicDate":"2017-11-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Biocrust ecology: Unifying micro- and macro-scales to confront global change","docAbstract":"Biological soil crusts (biocrusts) are communities of microbes, lichens and bryophytes living at the soil surface in drylands (Fig. 1; Belnap et al., 2016). Biocrusts occur on all continents and can comprise a majority of cover in some systems (Belnap et al., 2016). While species diversity and distributions have long been a research focus, interest in controls on community composition and cover has expanded as biocrusts are increasingly recognized for their roles in ecosystem functioning (Deane-Coe and Stanton, 2017). For example, biocrust organisms can stabilize soils (Belnap et al., 2016; Faist et al., 2017), fix atmospheric carbon (C) (Sancho et al., 2016), and serve as the foremost source of ‘new’ soil nitrogen (N) in drylands, via N2 fixation (Barger et al., 2016) These contributions to gross primary production and soil fertility could be quite large, as high-end estimates suggest biocrusts and similar communities of bryophytes and lichens might account for 10% of terrestrial C- and 50% of N-fixation globally (Elbert et al., 2012). Yet verifying these and other biocrust roles in ecosystem functioning is complicated by limited knowledge of biocrust cover and composition across the vast dryland biome (Ferrenberg et al., 2017).
It was against this backdrop that ‘Biocrust3: the 3rd International workshop on biological soil crusts’ was held in Moab, UT, USA, on 26-30 September 2016. The workshop brought together over 50 scientists from 21 countries and six continents, and included numerous biocrust science pioneers (Fig. 2). The meeting was notable for its cross-scale focus, discussion of novel molecular and imaging techniques, and sessions on mapping and restoring biocrusts in a changing world. Here, we synthesize a central theme that emerged from Biocrust3, namely the potential for combining cutting edge tools with studies focused on organismal traits, ecosystem functions, and global change biology to advance the frontier of biocrust ecology.
","language":"English","publisher":"Wiley","doi":"10.1111/nph.14826","usgsCitation":"Ferrenberg, S., and Reed, S.C., 2017, Biocrust ecology: Unifying micro- and macro-scales to confront global change: New Phytologist, v. 216, no. 3, p. 643-646, https://doi.org/10.1111/nph.14826.","productDescription":"4 p.","startPage":"643","endPage":"646","ipdsId":"IP-088643","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469351,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.14826","text":"Publisher Index Page"},{"id":348175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"216","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-16","publicationStatus":"PW","scienceBaseUri":"59fd8024e4b0531197b5012f","contributors":{"authors":[{"text":"Ferrenberg, Scott 0000-0002-3542-0334 sferrenberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3542-0334","contributorId":147684,"corporation":false,"usgs":true,"family":"Ferrenberg","given":"Scott","email":"sferrenberg@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":720122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":720123,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198784,"text":"70198784 - 2017 - Reply to ‘Marsh vulnerability to sea-level rise’","interactions":[],"lastModifiedDate":"2018-08-24T12:23:20","indexId":"70198784","displayToPublicDate":"2017-11-02T16:29:16","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Reply to ‘Marsh vulnerability to sea-level rise’","docAbstract":"Response to Parkinson et al. Rebuttal of Kirwan, M. L., Temmerman, S., Skeehan, E. E., Guntenspergen, G. R.,& Fagherazzi, S. (2016). Overestimation of marsh vulnerability to sea level rise. Nature Climate Change, 6(3):253-2601.","language":"English","publisher":"Springer","doi":"10.1038/nclimate3425","usgsCitation":"Kirwan, M.L., Temmerman, S., Guntenspergen, G.R., and Fagherazzi, S., 2017, Reply to ‘Marsh vulnerability to sea-level rise’: Nature Climate Change, v. 7, p. 756-757, https://doi.org/10.1038/nclimate3425.","productDescription":"2 p.","startPage":"756","endPage":"757","ipdsId":"IP-087588","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":356633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-01","publicationStatus":"PW","scienceBaseUri":"5b98a381e4b0702d0e843051","contributors":{"authors":[{"text":"Kirwan, Matthew L.","contributorId":191373,"corporation":false,"usgs":false,"family":"Kirwan","given":"Matthew","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":742944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Temmerman, Stijn","contributorId":189204,"corporation":false,"usgs":false,"family":"Temmerman","given":"Stijn","email":"","affiliations":[],"preferred":false,"id":742945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":742943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagherazzi, Sergio","contributorId":207153,"corporation":false,"usgs":false,"family":"Fagherazzi","given":"Sergio","email":"","affiliations":[{"id":37465,"text":"Boston University, Earth and Environment, Boston, 02215, USA.","active":true,"usgs":false}],"preferred":false,"id":742946,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191040,"text":"ds1068 - 2017 - Vulnerable transportation and utility assets near actively migrating streams in Indiana","interactions":[],"lastModifiedDate":"2017-11-03T11:16:31","indexId":"ds1068","displayToPublicDate":"2017-11-02T11:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1068","title":"Vulnerable transportation and utility assets near actively migrating streams in Indiana","docAbstract":"An investigation was completed by the U.S. Geological Survey in cooperation with the Indiana Office of Community and Rural Affairs that found 1,132 transportation and utility assets in Indiana are vulnerable to fluvial erosion hazards due to close proximity to actively migrating streams. Locations of transportation assets (bridges, roadways, and railroad lines) and selected utility assets (high-capacity overhead power-transmission lines, underground pipelines, water treatment facilities, and in-channel dams) were determined using aerial imagery hosted by the Google Earth platform. Identified assets were aggregated by stream reach, county, and class. Accompanying the report is a polyline shapefile of the stream reaches documented by Robinson. The shapefile, derived from line work in the National Hydrography Dataset and attributed with channel migration rates, is released with complete Federal Geographic Data Committee metadata. The data presented in this report are intended to help stakeholders and others identify high-risk areas where transportation and utility assets may be threatened by fluvial erosion hazards thus warranting consideration for mitigation strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1068","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Sperl, B.J., 2017, Vulnerable transportation and utility assets near actively migrating streams in Indiana: U.S. Geological Survey Data Series 1068, 11 p., https://doi.org/10.3133/ds1068.","productDescription":"Report: iv, 11 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086741","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":347784,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1068/ds1068.pdf","text":"Report","size":"4.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 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\"}}]}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
Hurricane Matthew moved adjacent to the coasts of Florida, Georgia, South Carolina, and North Carolina. The hurricane made landfall once near McClellanville, South Carolina, on October 8, 2016, as a Category 1 hurricane on the Saffir-Simpson Hurricane Wind Scale. The U.S. Geological Survey (USGS) deployed a temporary monitoring network of storm-tide sensors at 284 sites along the Atlantic coast from Florida to North Carolina to record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by Hurricane Matthew. Storm tide, as defined by the National Oceanic and Atmospheric Administration, is the water-level rise generated by a combination of storm surge and astronomical tide during a coastal storm.
The deployment for Hurricane Matthew was the largest deployment of storm-tide sensors in USGS history and was completed as part of a coordinated Federal emergency response as outlined by the Stafford Act (Public Law 92–288, 42 U.S.C. 5121–5207) under a directed mission assignment by the Federal Emergency Management Agency. In total, 543 high-water marks (HWMs) also were collected after Hurricane Matthew, and this was the second largest HWM recovery effort in USGS history after Hurricane Sandy in 2012.
During the hurricane, real-time water-level data collected at temporary rapid deployment gages (RDGs) and long-term USGS streamgage stations were relayed immediately for display on the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#MatthewOctober2016). These data provided emergency managers and responders with critical information for tracking flood-effected areas and directing assistance to effected communities. Data collected from this hurricane can be used to calibrate and evaluate the performance of storm-tide models for maximum and incremental water level and flood extent, and the site-specific effects of storm tide on natural and anthropogenic features of the environment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171122","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Frantz, E.R., Byrne, M.J., Sr., Caldwell, A.W., and Harden, S.L., 2017, Monitoring storm tide and flooding from Hurricane Matthew along the Atlantic coast of the United States, October 2016: U.S. Geological Survey Open-File Report 2017–1122, 37 p., https://doi.org/10.3133/ofr20171122.","productDescription":"vi, 37 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081187","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":347956,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1122/ofr20171122.pdf","text":"Report","size":"5.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1122"},{"id":347955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1122/coverthb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.57421875,\n 36.56260003738545\n ],\n [\n -78.50830078125,\n 35.585851593232356\n ],\n [\n -79.69482421875,\n 34.903952965590065\n ],\n [\n -81.9140625,\n 33.358061612778876\n ],\n [\n -82.44140625,\n 31.70947636001935\n ],\n [\n -82.7490234375,\n 30.713503990354965\n ],\n [\n -82.0458984375,\n 28.998531814051795\n ],\n [\n -81.2548828125,\n 27.00040800352175\n ],\n [\n -81.650390625,\n 25.224820176765036\n ],\n [\n -80.595703125,\n 24.666986385216273\n ],\n [\n -79.3212890625,\n 25.20494115356912\n ],\n [\n -79.4970703125,\n 26.96124577052697\n ],\n [\n -79.82666015625,\n 27.994401411046148\n ],\n [\n -80.26611328125,\n 29.592565403314087\n ],\n [\n -80.35400390625,\n 31.259769987394286\n ],\n [\n -78.57421875,\n 32.80574473290688\n ],\n [\n -76.3330078125,\n 33.46810795527896\n ],\n [\n -74.619140625,\n 34.397844946449865\n ],\n [\n -73.32275390625,\n 36.56260003738545\n ],\n [\n -78.57421875,\n 36.56260003738545\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
The Regional Ocean Modeling System (ROMS) has been coupled with the Water Quality Analysis Simulation Program (WASP) to be used in a comprehensive analysis of water quality in Barnegat Bay, New Jersey. The coupler can spatially aggregate hydrodynamic information in ROMS cells into larger WASP segments. It can also be used to resample ROMS output at a finer temporal scale to meet WASP time-stepping requirements. The coupler aggregates flow components, temperature, and salinity in ROMS output for input to WASP via a hydrodynamic linkage file. The coupler was tested initially with idealized cases designed to verify the water mass balance and conservation of constituent mass using one-to-one and one-to-many connectivity options between segments. A realistic example from the Toms River embayment, a subdomain of Barnegat Bay, was used to demonstrate the functionality of the coupling. A WASP eutrophication model accounting for dissolved oxygen (DO), nitrogen, and constant phytoplankton concentrations was applied to explore the distribution and trends in DO and nitrogen in the embayment for the period of July–August 2012. Results of DO modeling indicate satisfactory agreement with measurements collected at in-bay stations and also indicate that this coupled approach, despite substantial differences in spatiotemporal discretization between the models, provides adequate predictive capabilities.
The 3D Elevation Program (3DEP) of the U.S. Geological Survey (USGS) acquires high-resolution elevation data for the Nation. This program has been operating under an opportunity-oriented approach, acquiring light detection and ranging (lidar) projects of varying sizes scattered across the United States. As a result, the national 3DEP elevation layer is subject to data gaps or unnecessary overlap between adjacent collections. To mitigate this problem, 3DEP is adopting a strategic, systematic approach to national data acquisition that will create efficiencies in efforts to achieve nationwide elevation data coverage and help capture additional Federal and non-Federal investments resulting from advance awareness of proposed acquisitions and partnership opportunities. The 3DEP Working Group, an interagency group managed by the USGS, has agreed that all future 3DEP collections within the lower 48 States should be coordinated by using a 1-kilometer by 1-kilometer tiling scheme for the conterminous United States. Fiscal Year 2018 is being considered a transition year, and in Fiscal Year 2019 the national indexing scheme will be fully implemented, so that all 3DEP-supported projects will be acquired and delivered in the national indexing scheme and projected into the Albers Equal Area projection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173073","issn":"2327-6916","usgsCitation":"Thatcher, C.A., Heidemann, H.K., Stoker, J.M., and Eldridge, D.F., 2017, The 3D Elevation Program national indexing scheme: U.S. Geological Survey Fact Sheet 2017-3073, 2 p., https://doi.org/10.3133/fs20173073.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088200","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":346327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3073/fs20173073.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3073"},{"id":346326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3073/coverthb.jpg"}],"contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov
Or visit the National Geospatial Program website at https://www2.usgs.gov/ngpo/
","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-11-02","noUsgsAuthors":false,"publicationDate":"2017-11-02","publicationStatus":"PW","scienceBaseUri":"59fc2ea2e4b0531197b27f7b","contributors":{"authors":[{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":710269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heidemann, Hans Karl 0000-0003-4306-359X kheidemann@usgs.gov","orcid":"https://orcid.org/0000-0003-4306-359X","contributorId":3755,"corporation":false,"usgs":true,"family":"Heidemann","given":"Hans","email":"kheidemann@usgs.gov","middleInitial":"Karl","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":710272,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":710270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eldridge, Diane F. 0000-0002-2821-6239 deldridge@usgs.gov","orcid":"https://orcid.org/0000-0002-2821-6239","contributorId":196409,"corporation":false,"usgs":true,"family":"Eldridge","given":"Diane","email":"deldridge@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":false,"id":710271,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193690,"text":"70193690 - 2017 - Patterns of spatial distribution of golden eagles across North America: How do they fit into existing landscape-scale mapping systems?","interactions":[],"lastModifiedDate":"2017-11-22T16:55:01","indexId":"70193690","displayToPublicDate":"2017-11-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of spatial distribution of golden eagles across North America: How do they fit into existing landscape-scale mapping systems?","docAbstract":"Conserving wide-ranging animals requires knowledge about their year-round movements and resource use. Golden Eagles (Aquila chrysaetos) exhibit a wide range of movement patterns across North America. We combined tracking data from 571 Golden Eagles from multiple independent satellite-telemetry projects from North America to provide a comprehensive look at the magnitude and extent of these movements on a continental scale. We compared patterns of use relative to four alternative administrative and ecological mapping systems, namely Bird Conservation Regions (BCRs), U.S. administrative migratory bird flyways, Migratory Bird Joint Ventures, and Landscape Conservation Cooperatives. Our analyses suggested that eagles initially captured in eastern North America used space differently than those captured in western North America. Other groups of eagles that exhibited distinct patterns in space use included long-distance migrants from northern latitudes, and southwestern and Californian desert residents. There were also several groupings of eagles in the Intermountain West. Using this collaborative approach, we have identified large-scale movement patterns that may not have been possible with individual studies. These results will support landscape-scale conservation measures for Golden Eagles across North America.
","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-16-72.1","usgsCitation":"Brown, J.L., Bedrosian, B., Bell, D.A., Braham, M.A., Cooper, J., Crandall, R.H., DiDonato, J., Domenech, R., Duerr, A.E., Katzner, T., Lanzone, M.J., LaPlante, D.W., McIntyre, C.L., Miller, T.A., Murphy, R.K., Shreading, A., Slater, S.J., Smith, J.P., Smith, B.W., Watson, J.W., and Woodbridge, B., 2017, Patterns of spatial distribution of golden eagles across North America: How do they fit into existing landscape-scale mapping systems?: Journal of Raptor Research, v. 51, no. 3, p. 197-215, https://doi.org/10.3356/JRR-16-72.1.","productDescription":"19 p.","startPage":"197","endPage":"215","ipdsId":"IP-082399","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":461353,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-16-72.1","text":"Publisher Index Page"},{"id":348145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"51","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2ea1e4b0531197b27f75","contributors":{"authors":[{"text":"Brown, Jessi L.","contributorId":44817,"corporation":false,"usgs":false,"family":"Brown","given":"Jessi","email":"","middleInitial":"L.","affiliations":[{"id":13184,"text":"Program in Ecology, Evolution and Conservation Biology, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":719895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Bryan","contributorId":199738,"corporation":false,"usgs":false,"family":"Bedrosian","given":"Bryan","affiliations":[{"id":35591,"text":"Teton Raptor Center","active":true,"usgs":false}],"preferred":false,"id":719896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Douglas A.","contributorId":199739,"corporation":false,"usgs":false,"family":"Bell","given":"Douglas","email":"","middleInitial":"A.","affiliations":[{"id":24634,"text":"East Bay Regional Park District","active":true,"usgs":false}],"preferred":false,"id":719897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braham, Melissa A.","contributorId":199740,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":34303,"text":"West Virginia University, Department of Geology & Geography","active":true,"usgs":false}],"preferred":false,"id":719898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooper, Jeff","contributorId":199741,"corporation":false,"usgs":false,"family":"Cooper","given":"Jeff","affiliations":[{"id":35592,"text":"Virginia Department of Game and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":719899,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crandall, Ross H.","contributorId":198926,"corporation":false,"usgs":false,"family":"Crandall","given":"Ross","email":"","middleInitial":"H.","affiliations":[{"id":6657,"text":"Craighead Beringia South","active":true,"usgs":false}],"preferred":false,"id":719900,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DiDonato, Joe","contributorId":199742,"corporation":false,"usgs":false,"family":"DiDonato","given":"Joe","email":"","affiliations":[{"id":35593,"text":"Wildlife Consulting and Photography","active":true,"usgs":false}],"preferred":false,"id":719901,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Domenech, Robert","contributorId":199743,"corporation":false,"usgs":false,"family":"Domenech","given":"Robert","email":"","affiliations":[{"id":35594,"text":"Raptor View Research Institute","active":true,"usgs":false}],"preferred":false,"id":719902,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Duerr, Adam E.","contributorId":190590,"corporation":false,"usgs":false,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":719903,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":719894,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lanzone, Michael J.","contributorId":147851,"corporation":false,"usgs":false,"family":"Lanzone","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13392,"text":"Cellular Tracking Technologies","active":true,"usgs":false}],"preferred":false,"id":719904,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"LaPlante, David W.","contributorId":199744,"corporation":false,"usgs":false,"family":"LaPlante","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":35595,"text":"Natural Resource Geospatial","active":true,"usgs":false}],"preferred":false,"id":719905,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McIntyre, Carol L.","contributorId":196673,"corporation":false,"usgs":false,"family":"McIntyre","given":"Carol","email":"","middleInitial":"L.","affiliations":[{"id":20307,"text":"US National Park Service","active":true,"usgs":false}],"preferred":false,"id":719906,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":719907,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Murphy, Robert K.","contributorId":67643,"corporation":false,"usgs":false,"family":"Murphy","given":"Robert","email":"","middleInitial":"K.","affiliations":[{"id":56253,"text":"Eagle Environmental, Inc","active":true,"usgs":false}],"preferred":false,"id":719908,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Shreading, Adam","contributorId":199745,"corporation":false,"usgs":false,"family":"Shreading","given":"Adam","email":"","affiliations":[{"id":35594,"text":"Raptor View Research Institute","active":true,"usgs":false}],"preferred":false,"id":719909,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Slater, Steven J.","contributorId":199746,"corporation":false,"usgs":false,"family":"Slater","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":35596,"text":"HawkWatch International","active":true,"usgs":false}],"preferred":false,"id":719910,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Smith, Jeff P.","contributorId":199747,"corporation":false,"usgs":false,"family":"Smith","given":"Jeff","email":"","middleInitial":"P.","affiliations":[{"id":35597,"text":"H.T. Harvey & Associates","active":true,"usgs":false}],"preferred":false,"id":719911,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Smith, Brian W.","contributorId":199748,"corporation":false,"usgs":false,"family":"Smith","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":719912,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Watson, James W.","contributorId":198921,"corporation":false,"usgs":false,"family":"Watson","given":"James","email":"","middleInitial":"W.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":719913,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Woodbridge, Brian","contributorId":198923,"corporation":false,"usgs":false,"family":"Woodbridge","given":"Brian","email":"","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":719914,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70193559,"text":"70193559 - 2017 - Home range, den selection and habitat use of Carolina northern flying squirrels (Glaucomys sabrinus coloratus)","interactions":[],"lastModifiedDate":"2017-11-02T15:47:54","indexId":"70193559","displayToPublicDate":"2017-11-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Home range, den selection and habitat use of Carolina northern flying squirrels (Glaucomys sabrinus coloratus)","title":"Home range, den selection and habitat use of Carolina northern flying squirrels (Glaucomys sabrinus coloratus)","docAbstract":"Context: Understanding habitat selection is important for determining conservation and management strategies for endangered species. The Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus) is an endangered subspecies found in the high-elevation montane forests of the southern Appalachians, USA. The primary use of nest boxes to monitor CNFS has provided biased information on habitat use for this subspecies, as nest boxes are typically placed in suitable denning habitat.
Aims: We conducted a radio-telemetry study on CNFS to determine home range, den site selection and habitat use at multiple spatial scales.
Methods: We radio-collared 21 CNFS in 2012 and 2014–15. We tracked squirrels to diurnal den sites and during night-time activity.
Key results: The MCP (minimum convex polygon) home range at 95% for males was 5.2 ± 1.2 ha and for females was 4.0 ± 0.7. The BRB (biased random bridge) home range at 95% for males was 10.8 ± 3.8 ha and for females was 8.3 ± 2.1. Den site (n = 81) selection occurred more frequently in montane conifer dominate forests (81.4%) vs northern hardwood forests or conifer–northern hardwood forests (9.9% and 8.7%, respectively). We assessed habitat selection using Euclidean distance-based analysis at the 2nd order and 3rd order scale. We found that squirrels were non-randomly selecting for habitat at both 2nd and 3rd order scales.
Conclusions: At both spatial scales, CNFS preferentially selected for montane conifer forests more than expected based on availability on the landscape. Squirrels selected neither for nor against northern hardwood forests, regardless of availability on the landscape. Additionally, CNFS denned in montane conifer forests more than other habitat types.
Implications: Our results highlight the importance of montane conifer to CNFS in the southern Appalachians. Management and restoration activities that increase the quality, connectivity and extent of this naturally rare forest type may be important for long-term conservation of this subspecies, especially with the impending threat of anthropogenic climate change.
","language":"English","publisher":"Csiro Publishing","doi":"10.1071/WR16203","usgsCitation":"Diggins, C.A., Silvis, A., Kelly, C.A., and Ford, W.M., 2017, Home range, den selection and habitat use of Carolina northern flying squirrels (Glaucomys sabrinus coloratus): Wildlife Research, v. 44, no. 5, p. 427-237, https://doi.org/10.1071/WR16203.","productDescription":"11 p.","startPage":"427","endPage":"237","ipdsId":"IP-078733","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Appalachian Mountains","volume":"44","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2ea2e4b0531197b27f77","contributors":{"authors":[{"text":"Diggins, Corinne A.","contributorId":171667,"corporation":false,"usgs":false,"family":"Diggins","given":"Corinne","email":"","middleInitial":"A.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":719359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Silvis, Alexander","contributorId":171585,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","email":"","affiliations":[{"id":26923,"text":"Virginia Polytechnic Institute, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":719360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelly, Christine A.","contributorId":171661,"corporation":false,"usgs":false,"family":"Kelly","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":35598,"text":"North Carolina Wildlife Resources Commission ","active":true,"usgs":false}],"preferred":false,"id":719361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark wford@usgs.gov","contributorId":3858,"corporation":false,"usgs":true,"family":"Ford","given":"W.","email":"wford@usgs.gov","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":719358,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191750,"text":"sir20175123 - 2017 - Flood-inundation maps for the White River at Noblesville, Indiana","interactions":[],"lastModifiedDate":"2017-11-06T09:55:58","indexId":"sir20175123","displayToPublicDate":"2017-11-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5123","title":"Flood-inundation maps for the White River at Noblesville, Indiana","docAbstract":"Digital flood-inundation maps for a 7.5-mile reach of the White River at Noblesville, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the White River at Noblesville, Ind., streamgage (USGS station number 03349000). Real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at the same site as the USGS streamgage (NWS site NBLI3).
Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current (2016) stage-discharge rating at the USGS streamgage 03349000, White River at Noblesville, Ind., and documented high-water marks from the floods of September 4, 2003, and May 6, 2017. The hydraulic model was then used to compute 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum ranging from 10.0 ft (the NWS “action stage”) to 24.0 ft, which is the highest stage interval of the current (2016) USGS stage-discharge rating curve and 2 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each stage.
The availability of these maps, along with internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175123","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Martin, Z.W., 2017, Flood-inundation maps for the White River at Noblesville, Indiana: U.S. Geological Survey Scientific Investigations Report 2017–5123, 11 p., https://doi.org/10.3133/sir20175123.","productDescription":"Report: vi, 11 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-086871","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":347858,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5123/sir20175123.pdf","text":"Report","size":"1.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5123"},{"id":347859,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MG7N0J","text":"USGS data release","description":"USGS Data Release","linkHelpText":"White River at Noblesville, Indiana, flood-inundation model and GIS data"},{"id":347857,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5123/coverthb.jpg"}],"country":"United States","state":"Indiana","city":"Noblesville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.03616714477539,\n 40.033792168980135\n ],\n [\n -85.95720291137695,\n 40.033792168980135\n ],\n [\n -85.95720291137695,\n 40.10919420673381\n ],\n [\n -86.03616714477539,\n 40.10919420673381\n ],\n [\n -86.03616714477539,\n 40.033792168980135\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278–1996
The Upper Mississippian Heath Formation, which accumulated in the Big Snowy Trough of central Montana, has been known for three decades to contain mudrocks highly enriched in Zn, V, Mo, Ni and other metals, and source rocks for oil. The unit has more recently been recognized as a prospective tight oil play. Here we present petrographic, paleontologic, geochemical, and carbon and sulfur isotope data on seven continuous drill cores spanning ≤146 m of immature to marginally mature strata in order to improve understanding of the depositional setting of the Heath.
The unit consists of five third-order transgressive-regressive cycles (C1–C5 from bottom to top) that were deposited during a fluctuating climatic regime. Cycles comprise thinly interbedded gray to black mudrock and carbonate strata capped by either coal, implying a humid climate (C1, C3 and C4), or gypsum, implying more arid conditions (C2); the upper part of C5 is not preserved in our study area. Mfs (maximum flooding surfaces) in C1, C2, C4, and C5 lie within black mudrock beds ~0.5–3-m thick with >10% TOC (total organic carbon), type I and type II kerogen (determined by programmed pyrolysis), high contents of Zn, V, Mo, and other metals, relatively low values of δ13CTOC and δ34Spyrite, and a limited-diversity fauna of locally abundant, thin-shelled pelecypods (Dunbarella? sp.).
The mfs in C2 is within the Cox Ranch oil shale bed, which is known from previous studies to be metalliferous; new analyses reported here show ≤28 wt % TOC, 5140 ppm Zn, 1910 ppm V, 1590 ppm Mo, and 509 ppm Ni. Strata that contain the mfs of C1, C4, and C5 are shown here for the first time to also have high metal contents, with maximum values of 1030–7340 ppm Zn, 446–1980 ppm V, 72–859 ppm Mo, and 221–452 ppm Ni. Cycle C3, which contains more gray mudrock and carbonate beds than the other cycles, has lower TOC (≤4.2 wt %), lower metals, and mainly type III kerogen. Carbonate beds include normal-marine crinoidal mudstone to packstone and lesser (dolo)mudstone with fenestral fabric, peloids, intraclasts, and a euryhaline fauna. Mid-Chesterian (early Serpukhovian) foraminifers in C3, combined with previously published fossil data, suggest that third-order cycles in the Heath Formation were ~1–2 myr in duration. They formed during a time of active block faulting in the Big Snowy Trough and global cooling linked to Gondwanan glaciation.
Tectonic, climatic, and paleogeographic factors shaped the cycles of the Heath Formation. Faunal and geochemical evidence indicate that conditions were most favorable for marine life during C3. Molybdenum concentrations >100 ppm and organic geochemical data suggest euxinic conditions during deposition of the black mudrock in C2, C4, and C5, but the presence of shell beds (1 mm–6-cm thick) within this mudrock requires bottom water with sufficient oxygen to support life, at least periodically. The apparent conflict between the geochemical and paleontologic observations likely reflects the different time scales of these two environmental proxies: 1000s of yrs vs <1–10s of yrs, respectively.
Metal- and organic-rich strata in the Heath Formation formed by slow, condensed sedimentation from periodically anoxic or euxinic bottom waters in a marine basin. Fossil data indicate that anoxia was episodic, perhaps seasonal and/or linked to longer-duration climate shifts. On a millennial time scale, metal enrichments in the Heath reflect a balance between primary productivity that was high enough for oxygen to be consumed by sinking organic matter and oxic seawater inflow that was strong enough to maintain a supply of metals without compromising anoxia. Organic-rich mudrock in the Heath shares intriguing lithologic and geochemical similarities with mudrock in other Middle to Upper Paleozoic units such as the Devonian-Mississippian Bakken Formation and Pennsylvanian cyclothems (e.g., Excello Shale).
","language":"English","publisher":"Micropress","doi":"10.29041/strat.14.1-4.97-122","usgsCitation":"Dumoulin, J.A., Johnson, C.A., Kelley, K.D., Botterell, P.J., Hackley, P.C., Scott, C., and Slack, J.F., 2017, Transgressive-regressive cycles in the metalliferous, oil-shale-bearing Heath Formation (Upper Mississippian), central Montana: Stratigraphy, v. 14, no. 1-4, p. 97-122, https://doi.org/10.29041/strat.14.1-4.97-122.","productDescription":"26 p.","startPage":"97","endPage":"122","ipdsId":"IP-077939","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":438158,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7668BPP","text":"USGS data release","linkHelpText":"Appendices for Transgressive-regressive cycles in the metalliferous, oil shale-bearing Heath Formation (Upper Mississippian), central Montana"},{"id":358777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Heath Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.75,\n 46.75\n ],\n [\n -108.8,\n 46.75\n ],\n [\n -108.8,\n 47\n ],\n [\n -109.75,\n 47\n ],\n [\n -109.75,\n 46.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"1-4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-28","publicationStatus":"PW","scienceBaseUri":"5c10aacce4b034bf6a7e5cfd","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":749684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Karen D. 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":749686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Botterell, Palma J. 0000-0001-7140-0915 pjarboe@usgs.gov","orcid":"https://orcid.org/0000-0001-7140-0915","contributorId":5805,"corporation":false,"usgs":true,"family":"Botterell","given":"Palma","email":"pjarboe@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749690,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70199247,"text":"70199247 - 2017 - Synopsis of the Fourth International Percid Fishes Symposia","interactions":[],"lastModifiedDate":"2018-09-13T15:48:43","indexId":"70199247","displayToPublicDate":"2017-11-01T15:48:37","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Synopsis of the Fourth International Percid Fishes Symposia","docAbstract":"The surface mass balance (SMB) of the Larsen C ice shelf (LCIS), Antarctica, is poorly constrained due to a dearth of in situ observations. Combining several geophysical techniques, we reconstruct spatial and temporal patterns of SMB over the LCIS. Continuous time series of snow height (2.5–6 years) at five locations allow for multi-year estimates of seasonal and annual SMB over the LCIS. There is high interannual variability in SMB as well as spatial variability: in the north, SMB is 0.40 ± 0.06 to 0.41 ± 0.04 m w.e. year−1, while farther south, SMB is up to 0.50 ± 0.05 m w.e. year−1. This difference between north and south is corroborated by winter snow accumulation derived from an airborne radar survey from 2009, which showed an average snow thickness of 0.34 m w.e. north of 66° S, and 0.40 m w.e. south of 68° S. Analysis of ground-penetrating radar from several field campaigns allows for a longer-term perspective of spatial variations in SMB: a particularly strong and coherent reflection horizon below 25–44 m of water-equivalent ice and firn is observed in radargrams collected across the shelf. We propose that this horizon was formed synchronously across the ice shelf. Combining snow height observations, ground and airborne radar, and SMB output from a regional climate model yields a gridded estimate of SMB over the LCIS. It confirms that SMB increases from north to south, overprinted by a gradient of increasing SMB to the west, modulated in the west by föhn-induced sublimation. Previous observations show a strong decrease in firn air content toward the west, which we attribute to spatial patterns of melt, refreezing, and densification rather than SMB.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/tc-11-2411-2017","usgsCitation":"Kuipers Munneke, P., Mcgrath, D., Medley, B., Luckman, A., Bevan, S., Kulessa, B., Jansen, D., Booth, A., Smeets, P., Hubbard, B., Ashmore, D., Van den Broeke, M., Sevestre, H., Steffen, K., Shepard, A., and Gourmelen, N., 2017, Observationally constrained surface mass balance of Larsen C ice shelf, Antarctica: The Cryosphere, v. 11, p. 2411-2426, https://doi.org/10.5194/tc-11-2411-2017.","productDescription":"16 p.","startPage":"2411","endPage":"2426","ipdsId":"IP-086024","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":469354,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-11-2411-2017","text":"Publisher Index Page"},{"id":369082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Antarctica","otherGeospatial":"Larsen C Ice Shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.7197265625,\n -74.91370815675299\n ],\n [\n -59.19433593750001,\n -74.91370815675299\n ],\n [\n -59.19433593750001,\n -69.17818443567214\n ],\n [\n -67.7197265625,\n -69.17818443567214\n ],\n [\n -67.7197265625,\n -74.91370815675299\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Kuipers Munneke, Peter","contributorId":220418,"corporation":false,"usgs":false,"family":"Kuipers Munneke","given":"Peter","email":"","affiliations":[{"id":40168,"text":"IMAU, Utrecht University","active":true,"usgs":false}],"preferred":false,"id":774929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mcgrath, Daniel 0000-0002-9462-6842","orcid":"https://orcid.org/0000-0002-9462-6842","contributorId":220417,"corporation":false,"usgs":true,"family":"Mcgrath","given":"Daniel","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":774928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Medley, Brooke","contributorId":220419,"corporation":false,"usgs":false,"family":"Medley","given":"Brooke","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":774930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luckman, Adrian","contributorId":220420,"corporation":false,"usgs":false,"family":"Luckman","given":"Adrian","email":"","affiliations":[{"id":16759,"text":"Swansea University","active":true,"usgs":false}],"preferred":false,"id":774931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bevan, Suzanne 0000-0003-2649-2982","orcid":"https://orcid.org/0000-0003-2649-2982","contributorId":220451,"corporation":false,"usgs":false,"family":"Bevan","given":"Suzanne","email":"","affiliations":[],"preferred":false,"id":774958,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kulessa, Bernd","contributorId":220452,"corporation":false,"usgs":false,"family":"Kulessa","given":"Bernd","email":"","affiliations":[],"preferred":false,"id":774959,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jansen, Daniela","contributorId":220453,"corporation":false,"usgs":false,"family":"Jansen","given":"Daniela","email":"","affiliations":[],"preferred":false,"id":774960,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Booth, Adam","contributorId":220454,"corporation":false,"usgs":false,"family":"Booth","given":"Adam","affiliations":[],"preferred":false,"id":774961,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smeets, Paul","contributorId":220455,"corporation":false,"usgs":false,"family":"Smeets","given":"Paul","email":"","affiliations":[],"preferred":false,"id":774962,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hubbard, B.","contributorId":7056,"corporation":false,"usgs":true,"family":"Hubbard","given":"B.","email":"","affiliations":[],"preferred":false,"id":774963,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ashmore, David","contributorId":220456,"corporation":false,"usgs":false,"family":"Ashmore","given":"David","email":"","affiliations":[],"preferred":false,"id":774964,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Van den Broeke, Michiel","contributorId":220457,"corporation":false,"usgs":false,"family":"Van den Broeke","given":"Michiel","affiliations":[],"preferred":false,"id":774965,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sevestre, Heidi","contributorId":220458,"corporation":false,"usgs":false,"family":"Sevestre","given":"Heidi","email":"","affiliations":[],"preferred":false,"id":774966,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Steffen, K.","contributorId":90914,"corporation":false,"usgs":true,"family":"Steffen","given":"K.","email":"","affiliations":[],"preferred":false,"id":774967,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Shepard, Andrew","contributorId":220459,"corporation":false,"usgs":false,"family":"Shepard","given":"Andrew","affiliations":[],"preferred":false,"id":774968,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Gourmelen, Noel","contributorId":220460,"corporation":false,"usgs":false,"family":"Gourmelen","given":"Noel","email":"","affiliations":[],"preferred":false,"id":774969,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70236853,"text":"70236853 - 2017 - Before and after retrofit behavior and performance of a 55-story tall building inferred from distant earthquake and ambient vibration data","interactions":[],"lastModifiedDate":"2022-09-20T13:28:51.954428","indexId":"70236853","displayToPublicDate":"2017-11-01T08:21:29","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Before and after retrofit behavior and performance of a 55-story tall building inferred from distant earthquake and ambient vibration data","docAbstract":"A sparsely instrumented 55-story building in Osaka, Japan, had recorded unprecedented, severe, and long-duration, long-period resonating responses during the 11 March 2011 M9.0 Tohoku earthquake that occurred at 767 km distance. Thereafter, studies of the records resulted in the implementation of a significant retrofit design, comprising dampers and buckling restrained braces (BRBs). The responses of the retrofitted building were also recorded during the 24 April 2016 M7.3 Kumamoto earthquake that occurred at 478 km. The earthquake and on-demand acquired ambient response data are analyzed in this study to assess the impact of this rare, retrofitted and instrumented tall building subjected to long period strong shaking from events originating at far distances. As expected, the fundamental frequency and critical damping ratio of the building increased, albeit small, after the retrofit as compared to before the retrofit. Increase of damping percentage is a positive finding and indicates that even larger percentages may be attained under shaking stronger than the 2016 event. The records indicate that the building still experiences significant resonance, torsion, as well as a beating effect.
","language":"English","publisher":"Sage","doi":"10.1193/122216EQS249M","usgsCitation":"Celebi, M., Kashima, T., Ghahari, S.F., Koyama, S., Tacirogle, E., and Okawa, I., 2017, Before and after retrofit behavior and performance of a 55-story tall building inferred from distant earthquake and ambient vibration data: Earthquake Spectra, v. 33, no. 4, p. 1599-1626, https://doi.org/10.1193/122216EQS249M.","productDescription":"28 p.","startPage":"1599","endPage":"1626","ipdsId":"IP-082394","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 140.86669921875,\n 41.623655390686395\n ],\n [\n 140.11962890625,\n 41.22824901518529\n ],\n [\n 139.74609375,\n 40.68063802521456\n ],\n [\n 139.6142578125,\n 39.50404070558415\n ],\n [\n 137.8564453125,\n 38.09998264736481\n ],\n [\n 136.40625,\n 37.33522435930639\n ],\n [\n 135.59326171875,\n 35.99578538642032\n ],\n [\n 132.25341796875,\n 35.65729624809628\n ],\n [\n 129.00146484375,\n 33.119150226768866\n ],\n [\n 130.166015625,\n 30.637912028341123\n ],\n [\n 131.50634765625,\n 31.372399104880525\n ],\n [\n 134.560546875,\n 33.284619968887675\n ],\n [\n 136.31835937499997,\n 33.32134852669881\n ],\n [\n 139.4384765625,\n 34.59704151614417\n ],\n [\n 140.77880859374997,\n 35.28150065789119\n ],\n [\n 141.13037109375,\n 35.99578538642032\n ],\n [\n 142.14111328125,\n 39.65645604812829\n ],\n [\n 141.63574218749997,\n 41.409775832009565\n ],\n [\n 140.86669921875,\n 41.623655390686395\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2017-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":852361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kashima, Toshihide","contributorId":176614,"corporation":false,"usgs":false,"family":"Kashima","given":"Toshihide","email":"","affiliations":[],"preferred":false,"id":852362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ghahari, S. F.","contributorId":147707,"corporation":false,"usgs":false,"family":"Ghahari","given":"S.","email":"","middleInitial":"F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":852363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koyama, Shin","contributorId":149525,"corporation":false,"usgs":false,"family":"Koyama","given":"Shin","email":"","affiliations":[],"preferred":false,"id":852364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tacirogle, Ertugrul","contributorId":296749,"corporation":false,"usgs":false,"family":"Tacirogle","given":"Ertugrul","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":852365,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Okawa, Izuru","contributorId":65508,"corporation":false,"usgs":true,"family":"Okawa","given":"Izuru","affiliations":[],"preferred":false,"id":852384,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208431,"text":"70208431 - 2017 - Assessing the risk of non-native marine species in the Bering Sea","interactions":[],"lastModifiedDate":"2020-02-11T06:42:26","indexId":"70208431","displayToPublicDate":"2017-11-01T06:52:53","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Assessing the risk of non-native marine species in the Bering Sea","docAbstract":"Invasive species are one of the leading global conservation concerns, which can have strong, negative impacts on ecosystems, vulnerable species, and valuable natural resources. Arctic regions have experienced a relatively low number of biological introductions to date. Their geographical remoteness, cold waters, and presence of sea ice present challenging conditions for both non-native organisms and the vessels that transport them, presumably leading to low rates of introduction and establishment. However, observed increases in water temperatures reductions in sea ice, and projected increases in shipping traffic are expected to render arctic marine regions more susceptible to the arrival and colonization of marine invasives. Risk assessments for these Arctic regions are important to inform management and monitoring priorities by determining which species pose the greatest risk. To this end, we developed a ranking system for non-native marine species and used this system to assess the risk of non-native species to the Bering Sea. Using species’ published physiological tolerances, we mapped habitat suitability under current and future climate scenarios to identify geographic areas of current and future concern. In addition, we described shipping traffic from commercial and fishing vessels to identify ports of entry for non-native species. Collectively, these analyses identify which marine species have the greatest risk for invasion, where in the Bering Sea invasion risk and species establishment is greatest, and which ports are most likely to serve as an entry point for marine invasives into Alaska’s Bering Sea. The ranking system we developed for non-native marine species consists of 33 questions grouped into five categories. The first four categories evaluate a species’ ability to arrive and establish in the Bering Sea, its reliance on humans for introductions, its biology, and its impacts on ecological and human systems. The fifth category is not included in the total ranking score, but provides information on management considerations. The ranking system has methods to account for data deficiencies and calculates these deficiencies to allow readers to weigh the lack of knowledge with the ranking score. We prioritized non-native species for ranking based on their geographic proximity to the Bering Sea. We evaluated 46 species and ranking scores ranged from 29.1 to 74.3 (out of a possible 100), with highest scores indicating greatest risk. Taxonomy at the level of phylum did not explain variation in ranking values, likely due to the substantial biological variation relative to our ranking criteria among members of the same phylum. To investigate where non-native species may survive and persist in the Bering Sea, we compared species’ temperature and salinity thresholds to environmental conditions of the Bering Sea. Environmental conditions were obtained from three Regional Ocean Modeling Systems (ROMS) and investigated under two time periods: current (2003-2012) and mid-century (2030-2039). We identified potential habitat for survival for 42 species, and potential habitat for reproduction for 29 species. Under current conditions, all species had temperature and salinity thresholds that would allow survival in the Bering Sea for at least part of the year, and most species (79% to 83%) had thresholds that would allow for survival year-round. For species with temperature and salinity thresholds unsuitable for survival in the Bering Sea, winter temperatures appear to be the limiting factor. Most species had six to nine weeks of suitable conditions for reproduction. Future increases in water temperatures are expected to open more habitat for marine invasives. Two of the three ROMs project an increase in the number of non-native species that would be able to survive year-round by mid-century. Moreover, models project between 37% and 60% of the Bering Sea shelf habitat to become more suitable under mid-century climate condition.
","language":"English","publisher":"North Pacific Research Board","collaboration":"University of Alaska Anchorage, NOAA, Aleutian Bering Sea Islands Landscape Conservation Cooperative","usgsCitation":"Reimer, J., Droghini, A., Fischbach, A., Watson, J., Bernard, B., and Poe, A., 2017, Assessing the risk of non-native marine species in the Bering Sea, 46 p.","productDescription":"46 p.","ipdsId":"IP-094656","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":372180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372163,"type":{"id":15,"text":"Index Page"},"url":"https://accs.uaa.alaska.edu/wp-content/uploads/Reimeretal2017_FinalReport.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -172.79296875,\n 51.890053935216926\n ],\n [\n -161.89453125,\n 51.890053935216926\n ],\n [\n -161.89453125,\n 65.94647177615738\n ],\n [\n -172.79296875,\n 65.94647177615738\n ],\n [\n -172.79296875,\n 51.890053935216926\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reimer, Jesika","contributorId":222311,"corporation":false,"usgs":false,"family":"Reimer","given":"Jesika","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":781853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Droghini, Amanda 0000-0001-6692-2348","orcid":"https://orcid.org/0000-0001-6692-2348","contributorId":222312,"corporation":false,"usgs":false,"family":"Droghini","given":"Amanda","email":"","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":781854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":200780,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony S.","email":"afischbach@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":781852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watson, Jordan 0000-0002-1686-0377","orcid":"https://orcid.org/0000-0002-1686-0377","contributorId":222313,"corporation":false,"usgs":false,"family":"Watson","given":"Jordan","email":"","affiliations":[{"id":40517,"text":"NOAA Alaska Fisheries Science Center Auke Bay Laboratories","active":true,"usgs":false}],"preferred":false,"id":781855,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernard, Bonnie","contributorId":222314,"corporation":false,"usgs":false,"family":"Bernard","given":"Bonnie","email":"","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":781856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Poe, Aaron","contributorId":222315,"corporation":false,"usgs":false,"family":"Poe","given":"Aaron","email":"","affiliations":[{"id":40518,"text":"Aleutian and Bering Sea Islands LCC U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":781857,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193545,"text":"70193545 - 2017 - Refined conservation strategies for Golden-winged Warblers in the West Virginia highlands with implications for the broader avian community","interactions":[],"lastModifiedDate":"2017-11-14T13:08:41","indexId":"70193545","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Refined conservation strategies for Golden-winged Warblers in the West Virginia highlands with implications for the broader avian community","docAbstract":"Golden-winged Warbler (Vermivora chrysoptera) populations in the Appalachian Mountains region of North America are imperiled, warranting species-specific conservation. However, management for Golden-winged Warblers can affect both early-successional and forest species, many of which are also declining in the region. We conducted point counts in sites representing a range of successional stages within the Golden-winged Warbler's breeding range in West Virginia, USA, during 2008–2015. We identified plausible models of Golden-winged Warbler density using covariates at 4 spatial scales representing annual dispersal (5-km radius), extraterritorial movement (1.5-km radius), intraterritorial movement (100-m radius), and local resource utilization (11.3-m radius). Golden-winged Warbler density peaked at an intermediate elevation at the 1.5-km radius scale, but was negatively associated with 100-m radius minimum elevation. Density was positively associated with 100-m radius shrubland cover. Southerly latitudes were associated with higher densities when modeled alone, but there was no association when controlling for other covariates. We then examined the relationship between covariates from these plausible models and avian community structure using canonical correspondence analysis to assess the value of Golden-winged Warbler conservation for the broader avian community. We identified 5 species likely to benefit from management for Golden-winged Warblers and 21 species likely to be affected positively or negatively to varying degrees depending on their affinity for early-successional vegetation communities. Golden-winged Warblers were plotted higher along the 100-m shrubland cover gradient than any other bird species, suggesting that they may be the most shrubland area–sensitive songbird in our study area. However, the species also requires heavily forested landscapes. Therefore, a species-specific conservation strategy that balances shrubland (patches of 9–13 ha in size, comprising 15% of the landscape) and contiguous forest area (≥75% of the landscape) could concurrently meet the needs of Golden-winged Warblers and the 26 other species identified.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-49.1","usgsCitation":"Aldinger, K.R., Wood, P.B., and Johnson, C.M., 2017, Refined conservation strategies for Golden-winged Warblers in the West Virginia highlands with implications for the broader avian community: The Condor, v. 119, no. 4, p. 762-786, https://doi.org/10.1650/CONDOR-17-49.1.","productDescription":"25 p.","startPage":"762","endPage":"786","ipdsId":"IP-085074","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469358,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-17-49.1","text":"Publisher Index Page"},{"id":348822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.8868408203125,\n 37.470498470798724\n ],\n [\n -78.9697265625,\n 37.470498470798724\n ],\n [\n -78.9697265625,\n 39.71986348549764\n ],\n [\n -80.8868408203125,\n 39.71986348549764\n ],\n [\n -80.8868408203125,\n 37.470498470798724\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"119","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d1a","contributors":{"authors":[{"text":"Aldinger, Kyle R.","contributorId":171892,"corporation":false,"usgs":false,"family":"Aldinger","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":719321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Catherine M.","contributorId":53939,"corporation":false,"usgs":true,"family":"Johnson","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":719322,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193410,"text":"70193410 - 2017 - Mediterranean California’s water use future under multiple scenarios of developed and agricultural land use change","interactions":[],"lastModifiedDate":"2017-11-13T11:02:58","indexId":"70193410","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mediterranean California’s water use future under multiple scenarios of developed and agricultural land use change","docAbstract":"With growing demand and highly variable inter-annual water supplies, California’s water use future is fraught with uncertainty. Climate change projections, anticipated population growth, and continued agricultural intensification, will likely stress existing water supplies in coming decades. Using a state-and-transition simulation modeling approach, we examine a broad suite of spatially explicit future land use scenarios and their associated county-level water use demand out to 2062. We examined a range of potential water demand futures sampled from a 20-year record of historical (1992–2012) data to develop a suite of potential future land change scenarios, including low/high change scenarios for urbanization and agriculture as well as “lowest of the low” and “highest of the high” anthropogenic use. Future water demand decreased 8.3 billion cubic meters (Bm3) in the lowest of the low scenario and decreased 0.8 Bm3 in the low agriculture scenario. The greatest increased water demand was projected for the highest of the high land use scenario (+9.4 Bm3), high agricultural expansion (+4.6 Bm3), and high urbanization (+2.1 Bm3) scenarios. Overall, these scenarios show agricultural land use decisions will likely drive future demand more than increasing municipal and industrial uses, yet improved efficiencies across all sectors could lead to potential water use savings. Results provide water managers with information on diverging land use and water use futures, based on historical, observed land change trends and water use histories.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0187181","usgsCitation":"Wilson, T., Sleeter, B.M., and Cameron, D.R., 2017, Mediterranean California’s water use future under multiple scenarios of developed and agricultural land use change: PLoS ONE, v. 12, no. 10, p. 1-21, https://doi.org/10.1371/journal.pone.0187181.","productDescription":"e0187181; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-085977","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0187181","text":"Publisher Index Page"},{"id":348592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Pacific blue mussels (Mytilus trossulus) are common residents of intertidal habitats in protected waters of the North Pacific, serving as a conduit of primary production to a wide range of nearshore consumers including predatory invertebrates, sea ducks, shorebirds, sea otters, humans, and other terrestrial mammals. We monitored seven metrics of intertidal Pacific blue mussel abundance at five sites in each of three regions across the northern Gulf of Alaska: Katmai National Park and Preserve (Katmai) (2006–2015), Kenai Fjords National Park (Kenai Fjords) (2008–2015) and western Prince William Sound (WPWS) (2007–2015). Metrics included estimates of: % cover at two tide heights in randomly selected rocky intertidal habitat; and in selected mussel beds estimates of: the density of large mussels (≥ 20 mm); density of all mussels > 2 mm estimated from cores extracted from those mussel beds; bed size; and total abundance of large and all mussels, i.e. the product of density and bed size. We evaluated whether these measures of mussel abundance differed among sites or regions, whether mussel abundance varied over time, and whether temporal patterns in abundance were site specific, or synchronous at regional or Gulf-wide spatial scales. We found that, for all metrics, mussel abundance varied on a site-by-site basis. After accounting for site differences, we found similar temporal patterns in several measures of abundance (both % cover metrics, large mussel density, large mussel abundance, and mussel abundance estimated from cores), in which abundance was initially high, declined significantly over several years, and subsequently recovered. Averaged across all sites, we documented declines of 84% in large mussel abundance through 2013 with recovery to 41% of initial abundance by 2015. These findings suggest that factors operating across the northern Gulf of Alaska were affecting mussel survival and subsequently abundance. In contrast, density of primarily small mussels obtained from cores (as an index of recruitment), varied markedly by site, but did not show meaningful temporal trends. We interpret this to indicate that settlement was driven by site-specific features rather than Gulf wide factors. By extension, we hypothesize that temporal changes in mussel abundance observed was not a result of temporal variation in larval supply leading to variation in recruitment, but rather suggestive of mortality as a primary demographic factor driving mussel abundance. Our results highlight the need to better understand underlying mechanisms of change in mussels, as well as implications of that change to nearshore consumers.
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SOS boundaries exhibit trade-offs such that decreases in harvest can compensate to some degree for losses of habitat, increases in predation and increasing value of fishing time to anglers. Conversely, high levels of harvest can be sustained if habitat is intact, predation is low, and value of fishing effort is moderate. The SOS approach recognizes limits in several dimensions: at overly high levels of harvest, habitat loss, predation, or value of fishing effort, the stock falls to a low equilibrium biomass. Recreational fisheries managers can influence harvest and perhaps predation, but they must cope with trends that are beyond their control such as changes in climate, loss of aquatic habitat or social factors that affect the value of fishing effort for anglers. The SOS illustrates opportunities to manage harvest or predation to maintain quality fisheries in the presence of trends in climate, social preferences or other factors that are not manageable.
","language":"English","publisher":"Wiley","doi":"10.1111/faf.12230","usgsCitation":"Carpenter, S.R., Brock, W.A., Hansen, G.J., Hansen, J.F., Hennessy, J., Isermann, D.A., Pedersen, E.J., Perales, K.M., Rypel, A.L., Sass, G., Tunney, T.D., and Vander Zanden, M.J., 2017, Defining a Safe Operating Space for inland recreational fisheries: Fish and Fisheries, v. 18, no. 6, p. 1150-1160, https://doi.org/10.1111/faf.12230.","productDescription":"11 p.","startPage":"1150","endPage":"1160","ipdsId":"IP-082123","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-23","publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d1d","contributors":{"authors":[{"text":"Carpenter, Stephen R. 0000-0001-8097-8700","orcid":"https://orcid.org/0000-0001-8097-8700","contributorId":196945,"corporation":false,"usgs":false,"family":"Carpenter","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":719287,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brock, William A.","contributorId":199492,"corporation":false,"usgs":false,"family":"Brock","given":"William","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":719288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Gretchen J. 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In wildlife ecological studies, satellite-based data and methodology have provided a wealth of information about animal space use and the investigation of individual-based animal–environment relationships. With the technology for data collection improving dramatically over time, we are left with massive archives of historical animal telemetry data of varying quality. While many contemporary statistical approaches for inferring movement behavior are specified in discrete time, we develop a flexible continuous-time stochastic integral equation framework that is amenable to reduced-rank second-order covariance parameterizations. We demonstrate how the associated first-order basis functions can be constructed to mimic behavioral characteristics in realistic trajectory processes using telemetry data from mule deer and mountain lion individuals in western North America. Our approach is parallelizable and provides inference for heterogenous trajectories using nonstationary spatial modeling techniques that are feasible for large telemetry datasets. Supplementary materials for this article are available online.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01621459.2016.1246250","usgsCitation":"Hooten, M., and Johnson, D., 2017, Basis function models for animal movement: Journal of the American Statistical Association, v. 112, no. 518, p. 578-589, https://doi.org/10.1080/01621459.2016.1246250.","productDescription":"12 p.","startPage":"578","endPage":"589","ipdsId":"IP-072343","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469371,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Basis_Function_Models_for_Animal_Movement/4052175","text":"External Repository"},{"id":348569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"518","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-13","publicationStatus":"PW","scienceBaseUri":"5a06c8c7e4b09af898c860ee","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":716569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":716570,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193277,"text":"70193277 - 2017 - Alternative pathways to landscape transformation: Invasive grasses, burn severity and fire frequency in arid ecosystems","interactions":[],"lastModifiedDate":"2017-11-06T13:06:31","indexId":"70193277","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Alternative pathways to landscape transformation: Invasive grasses, burn severity and fire frequency in arid ecosystems","docAbstract":"This paper proposes a geospatial analysis framework and software to interpret water-quality sampling data from towed undulating vehicles in near-real time. The framework includes data quality assurance and quality control processes, automated kriging interpolation along undulating paths, and local hotspot and cluster analyses. These methods are implemented in an interactive Web application developed using the Shiny package in the R programming environment to support near-real time analysis along with 2- and 3-D visualizations. The approach is demonstrated using historical sampling data from an undulating vehicle deployed at three rivermouth sites in Lake Michigan during 2011. The normalized root-mean-square error (NRMSE) of the interpolation averages approximately 10% in 3-fold cross validation. The results show that the framework can be used to track river plume dynamics and provide insights on mixing, which could be related to wind and seiche events.
","language":"English","publisher":"Elevier","doi":"10.1016/j.envsoft.2017.06.049","usgsCitation":"Collingsworth, P.D., Xu, W., Bailey, B., Carlson Mazur, M.L., Schaeffer, J., and Minsker, B., 2017, Detecting spatial patterns of rivermouth processes using a geostatistical framework for near-real-time analysis: Environmental Modelling and Software, v. 97, p. 72-85, https://doi.org/10.1016/j.envsoft.2017.06.049.","productDescription":"14 p.","startPage":"72","endPage":"85","ipdsId":"IP-071315","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469375,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2017.06.049","text":"Publisher Index Page"},{"id":349016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.67364501953124,\n 43.058854606434494\n ],\n [\n -86.27288818359375,\n 43.058854606434494\n ],\n [\n -86.27288818359375,\n 44.10533762552548\n ],\n [\n -87.67364501953124,\n 44.10533762552548\n ],\n [\n -87.67364501953124,\n 43.058854606434494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"97","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d13","contributors":{"authors":[{"text":"Xu, Wenzhao","contributorId":200526,"corporation":false,"usgs":false,"family":"Xu","given":"Wenzhao","email":"","affiliations":[],"preferred":false,"id":722554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collingsworth, Paris D.","contributorId":145526,"corporation":false,"usgs":false,"family":"Collingsworth","given":"Paris","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":722555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailey, Barbara","contributorId":200527,"corporation":false,"usgs":false,"family":"Bailey","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":722556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlson Mazur, Martha L.","contributorId":95377,"corporation":false,"usgs":true,"family":"Carlson Mazur","given":"Martha","email":"","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":722557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schaeffer, Jeff 0000-0003-3430-0872 jschaeffer@usgs.gov","orcid":"https://orcid.org/0000-0003-3430-0872","contributorId":2041,"corporation":false,"usgs":true,"family":"Schaeffer","given":"Jeff","email":"jschaeffer@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":722558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Minsker, Barbara","contributorId":200528,"corporation":false,"usgs":false,"family":"Minsker","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":722559,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191540,"text":"70191540 - 2017 - Identity, reproductive potential, distribution, ecology and management of invasive Pomacea maculata in the southern United States","interactions":[],"lastModifiedDate":"2017-11-30T12:55:58","indexId":"70191540","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Identity, reproductive potential, distribution, ecology and management of invasive Pomacea maculata in the southern United States","docAbstract":"Established populations of introduced Pomacea maculata, a highly fecund, large species of apple snail native to South America, now occur throughout southeast Asia, in Spain and extensively across the southern United States. Substantial research on nonnative apple snails takes place in Southeast Asia and has frequently identified apple snails as P. canaliculata. That these Asian populations represent at least two Pomacea species, P. canaliculata and P. maculata, has been confirmed through anatomical and genetic\nevidence. However, the two species are often still confused because of their similar shell morphologies and life history traits. This contribution reviews the distribution, life history, ecology and management of P. maculata introduced to the southern USA. So far the agricultural impacts of P. maculata in the USA fail to match those of non-native applesnails elsewhere, but the invasion of wetlands by this species suggests the need for increased vigilance to prevent further spread and avoid the ecological impacts that have been associated elsewhere with P. canaliculata.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Biology and management of invasive apple snails","language":"English","publisher":"Philippine Rice Research Institute","usgsCitation":"Burks, R.L., Bernatis, J., Byers, J.E., Carter, J., Martin, C.M., McDowell, W.G., and Van Dyke, J., 2017, Identity, reproductive potential, distribution, ecology and management of invasive Pomacea maculata in the southern United States, chap. of Biology and management of invasive apple snails, p. 293-333.","productDescription":"41 p.","startPage":"293","endPage":"333","ipdsId":"IP-053402","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":349589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb23e4b06e28e9c22d2b","contributors":{"editors":[{"text":"Joshi, R. 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