The U.S. Geological Survey South Atlantic Water Science Center collected borehole geophysical logs and images and continuous water-level data near the GMH Electronics National Priorities List Superfund site near Roxboro, North Carolina, during December 2012 through July 2015. Previous work by the U.S. Geological Survey South Atlantic Water Science Center at the site involved the collection of borehole geophysical log data in 15 wells, in addition to surface geologic mapping and passive diffusion bag sampling. In a continued effort to assist the U.S. Environmental Protection Agency in developing a conceptual groundwater model to assess current contaminant distribution and future migration of contaminants, more than 900 subsurface features (primarily fracture orientations) in 10 open borehole wells were delineated and continuous water-level data information from 14 monitoring wells within close proximity of the initially drilled boreholes was collected to observe any induced water-level fluctuations during drilling operations
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1022","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Region 4 Superfund Section","usgsCitation":"Antolino, D.J., and Chapman, M.J., 2017, Continued geophysical logging near the GMH Electronics National Priorities List Superfund site near Roxboro, North Carolina: U.S. Geological Survey Data Series 1022, 37 p., https://doi.org/10.3133/ds1022.","productDescription":"Report: v, 37 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076902","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":438455,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FX77JP","text":"USGS data release","linkHelpText":"Continued Geophysical Logging in the vicinity of the GMH Electronics Superfund Site near Roxboro, North 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U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Cyanobacterial blooms degrade water quality in drinking water supply reservoirs by producing toxic and taste-and-odor causing secondary metabolites, which ultimately cause public health concerns and lead to increased treatment costs for water utilities. There have been numerous attempts to create models that predict cyanobacteria and their secondary metabolites, most using linear models; however, linear models are limited by assumptions about the data and have had limited success as predictive tools. Thus, lake and reservoir managers need improved modeling techniques that can accurately predict large bloom events that have the highest impact on recreational activities and drinking-water treatment processes. In this study, we compared 12 unique linear and nonlinear regression modeling techniques to predict cyanobacterial abundance and the cyanobacterial secondary metabolites microcystin and geosmin using 14 years of physiochemical water quality data collected from Cheney Reservoir, Kansas. Support vector machine (SVM), random forest (RF), boosted tree (BT), and Cubist modeling techniques were the most predictive of the compared modeling approaches. SVM, RF, and BT modeling techniques were able to successfully predict cyanobacterial abundance, microcystin, and geosmin concentrations <60,000 cells/mL, 2.5 µg/L, and 20 ng/L, respectively. Only Cubist modeling predicted maxima concentrations of cyanobacteria and geosmin; no modeling technique was able to predict maxima microcystin concentrations. Because maxima concentrations are a primary concern for lake and reservoir managers, Cubist modeling may help predict the largest and most noxious concentrations of cyanobacteria and their secondary metabolites.
","language":"English","publisher":"Informa UK Limited","doi":"10.1080/10402381.2016.1263694","usgsCitation":"Harris, T.D., and Graham, J., 2017, Predicting cyanobacterial abundance, microcystin, and geosmin in a eutrophic drinking-water reservoir using a 14-year dataset: Lake and Reservoir Management, no. 33, 17 p., https://doi.org/10.1080/10402381.2016.1263694.","productDescription":"17 p.","ipdsId":"IP-078030","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":335169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Cheney Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.94174194335936,\n 37.666429212090605\n ],\n [\n -97.94174194335936,\n 37.845037026243425\n ],\n [\n -97.72270202636717,\n 37.845037026243425\n ],\n [\n -97.72270202636717,\n 37.666429212090605\n ],\n [\n -97.94174194335936,\n 37.666429212090605\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"33","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-06","publicationStatus":"PW","scienceBaseUri":"589ffedfe4b099f50d3e0436","contributors":{"authors":[{"text":"Harris, Ted D.","contributorId":149758,"corporation":false,"usgs":false,"family":"Harris","given":"Ted","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":663305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":663304,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70179447,"text":"70179447 - 2017 - Estimating the settling velocity of bioclastic sediment using common grain-size analysis techniques","interactions":[],"lastModifiedDate":"2017-05-18T11:00:47","indexId":"70179447","displayToPublicDate":"2017-01-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3369,"text":"Sedimentology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the settling velocity of bioclastic sediment using common grain-size analysis techniques","docAbstract":"Most techniques for estimating settling velocities of natural particles have been developed for siliciclastic sediments. Therefore, to understand how these techniques apply to bioclastic environments, measured settling velocities of bioclastic sedimentary deposits sampled from a nearshore fringing reef in Western Australia were compared with settling velocities calculated using results from several common grain-size analysis techniques (sieve, laser diffraction and image analysis) and established models. The effects of sediment density and shape were also examined using a range of density values and three different models of settling velocity. Sediment density was found to have a significant effect on calculated settling velocity, causing a range in normalized root-mean-square error of up to 28%, depending upon settling velocity model and grain-size method. Accounting for particle shape reduced errors in predicted settling velocity by 3% to 6% and removed any velocity-dependent bias, which is particularly important for the fastest settling fractions. When shape was accounted for and measured density was used, normalized root-mean-square errors were 4%, 10% and 18% for laser diffraction, sieve and image analysis, respectively. The results of this study show that established models of settling velocity that account for particle shape can be used to estimate settling velocity of irregularly shaped, sand-sized bioclastic sediments from sieve, laser diffraction, or image analysis-derived measures of grain size with a limited amount of error. Collectively, these findings will allow for grain-size data measured with different methods to be accurately converted to settling velocity for comparison. This will facilitate greater understanding of the hydraulic properties of bioclastic sediment which can help to increase our general knowledge of sediment dynamics in these environments.
","language":"English","publisher":"International Association of Sedimentologists","publisherLocation":"Oxford, United Kingdom","doi":"10.1111/sed.12338","usgsCitation":"Cuttler, M.V., Lowe, R.J., Falter, J.L., and Buscombe, D.D., 2017, Estimating the settling velocity of bioclastic sediment using common grain-size analysis techniques: Sedimentology, v. 64, no. 4, p. 987-1004, https://doi.org/10.1111/sed.12338.","productDescription":"18 p.","startPage":"987","endPage":"1004","ipdsId":"IP-073934","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470155,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://admin.research-repository.uwa.edu.au/en/publications/fe5b1cde-8ee4-4296-ba73-13808106388b","text":"External Repository"},{"id":332804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"64","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-29","publicationStatus":"PW","scienceBaseUri":"586cc68ce4b0f5ce109fa939","contributors":{"authors":[{"text":"Cuttler, Michael V. W.","contributorId":177844,"corporation":false,"usgs":false,"family":"Cuttler","given":"Michael","email":"","middleInitial":"V. W.","affiliations":[],"preferred":false,"id":657256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":657257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Falter, James L.","contributorId":177846,"corporation":false,"usgs":false,"family":"Falter","given":"James","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":657258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584 dbuscombe@usgs.gov","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":5020,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","email":"dbuscombe@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":657255,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70179446,"text":"70179446 - 2017 - Shallow water benthic imaging and substrate characterization using recreational-grade sidescan-sonar","interactions":[],"lastModifiedDate":"2017-01-03T11:42:07","indexId":"70179446","displayToPublicDate":"2017-01-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Shallow water benthic imaging and substrate characterization using recreational-grade sidescan-sonar","docAbstract":"In recent years, lightweight, inexpensive, vessel-mounted ‘recreational grade’ sonar systems have rapidly grown in popularity among aquatic scientists, for swath imaging of benthic substrates. To promote an ongoing ‘democratization’ of acoustical imaging of shallow water environments, methods to carry out geometric and radiometric correction and georectification of sonar echograms are presented, based on simplified models for sonar-target geometry and acoustic backscattering and attenuation in shallow water. Procedures are described for automated removal of the acoustic shadows, identification of bed-water interface for situations when the water is too turbid or turbulent for reliable depth echosounding, and for automated bed substrate classification based on singlebeam full-waveform analysis. These methods are encoded in an open-source and freely-available software package, which should further facilitate use of recreational-grade sidescan sonar, in a fully automated and objective manner. The sequential correction, mapping, and analysis steps are demonstrated using a data set from a shallow freshwater environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2016.12.003","usgsCitation":"Buscombe, D.D., 2017, Shallow water benthic imaging and substrate characterization using recreational-grade sidescan-sonar: Environmental Modelling and Software, p. 1-18, https://doi.org/10.1016/j.envsoft.2016.12.003.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-073207","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470156,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eartharxiv.org/gfxa6/","text":"External Repository"},{"id":332729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"89","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586cc68ce4b0f5ce109fa93b","contributors":{"authors":[{"text":"Buscombe, Daniel D. 0000-0001-6217-5584 dbuscombe@usgs.gov","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":5020,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","email":"dbuscombe@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":657254,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70179438,"text":"70179438 - 2017 - Spatial and temporal patterns of dissolved organic matter quantity and quality in the Mississippi River Basin, 1997–2013","interactions":[],"lastModifiedDate":"2017-02-15T15:39:56","indexId":"70179438","displayToPublicDate":"2017-01-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal patterns of dissolved organic matter quantity and quality in the Mississippi River Basin, 1997–2013","docAbstract":"Recent studies have found insignificant or decreasing trends in time-series dissolved organic carbon (DOC) datasets, questioning the assumption that long-term DOC concentrations in surface waters are increasing in response to anthropogenic forcing, including climate change, land use, and atmospheric acid deposition. We used the weighted regressions on time, discharge, and season (WRTDS) model to estimate annual flow-normalized concentrations and fluxes to determine if changes in DOC quantity and quality signal anthropogenic forcing at 10 locations in the Mississippi River Basin. Despite increases in agriculture and urban development throughout the basin, net increases in DOC concentration and flux were significant at only 3 of 10 sites from 1997 to 2013 and ranged between −3.5% to +18% and −0.1 to 19%, respectively. Positive shifts in DOC quality, characterized by increasing specific ultraviolet absorbance at 254 nm, ranged between +8% and +45%, but only occurred at one of the sites with significant DOC quantity increases. Basinwide reductions in atmospheric sulfate deposition did not result in large increases in DOC either, likely because of the high buffering capacity of the soil. Hydroclimatic factors including annual discharge, precipitation, and temperature did not significantly change during the 17-year timespan of this study, which contrasts with results from previous studies showing significant increases in precipitation and discharge over a century time scale. Our study also contrasts with those from smaller catchments, which have shown stronger DOC responses to climate, land use, and acidic deposition. This temporal and spatial analysis indicated that there was a potential change in DOC sources in the Mississippi River Basin between 1997 and 2013. However, the overall magnitude of DOC trends was not large, and the pattern in quantity and quality increases for the 10 study sites was not consistent throughout the basin.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11072","usgsCitation":"Stackpoole, S.M., Stets, E., Clow, D.W., Burns, D.A., Aiken, G.R., Aulenbach, B.T., Creed, I., Hirsch, R.M., Laudon, H., Pellerin, B., and Striegl, R.G., 2017, Spatial and temporal patterns of dissolved organic matter quantity and quality in the Mississippi River Basin, 1997–2013: Hydrological Processes, v. 31, no. 4, p. 902-915, https://doi.org/10.1002/hyp.11072.","productDescription":"14 p.","startPage":"902","endPage":"915","ipdsId":"IP-066770","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470153,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.11072","text":"Publisher Index Page"},{"id":332738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-11","publicationStatus":"PW","scienceBaseUri":"586cc68ee4b0f5ce109fa93d","contributors":{"authors":[{"text":"Stackpoole, Sarah M. 0000-0002-5876-4922 sstackpoole@usgs.gov","orcid":"https://orcid.org/0000-0002-5876-4922","contributorId":3784,"corporation":false,"usgs":true,"family":"Stackpoole","given":"Sarah","email":"sstackpoole@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":657186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stets, Edward G. estets@usgs.gov","contributorId":174182,"corporation":false,"usgs":true,"family":"Stets","given":"Edward G.","email":"estets@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":657187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":657188,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":657189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":657281,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":657190,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Creed, Irena F.","contributorId":81209,"corporation":false,"usgs":false,"family":"Creed","given":"Irena F.","affiliations":[{"id":27655,"text":"Department of Biology, University of Western Ontario, London, ON Canada","active":true,"usgs":false}],"preferred":false,"id":657191,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":657192,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Laudon, Hjalmar","contributorId":46812,"corporation":false,"usgs":true,"family":"Laudon","given":"Hjalmar","affiliations":[],"preferred":false,"id":657193,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pellerin, Brian A. 0000-0003-3712-7884 bpeller@usgs.gov","orcid":"https://orcid.org/0000-0003-3712-7884","contributorId":147077,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":657194,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":657195,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70179448,"text":"70179448 - 2017 - Climatic controls on the global distribution, abundance, and species richness of mangrove forests","interactions":[],"lastModifiedDate":"2017-05-02T14:37:36","indexId":"70179448","displayToPublicDate":"2017-01-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Climatic controls on the global distribution, abundance, and species richness of mangrove forests","docAbstract":"Mangrove forests are highly productive tidal saline wetland ecosystems found along sheltered tropical and subtropical coasts. Ecologists have long assumed that climatic drivers (i.e., temperature and rainfall regimes) govern the global distribution, structure, and function of mangrove forests. However, data constraints have hindered the quantification of direct climate-mangrove linkages in many parts of the world. Recently, the quality and availability of global-scale climate and mangrove data have been improving. Here, we used these data to better understand the influence of air temperature and rainfall regimes upon the distribution, abundance, and species richness of mangrove forests. Although our analyses identify global-scale relationships and thresholds, we show that the influence of climatic drivers is best characterized via regional range limit-specific analyses. We quantified climatic controls across targeted gradients in temperature and/or rainfall within 14 mangrove distributional range limits. Climatic thresholds for mangrove presence, abundance, and species richness differed among the 14 studied range limits. We identified minimum temperature-based thresholds for range limits in eastern North America, eastern Australia, New Zealand, eastern Asia, eastern South America, and southeast Africa. We identified rainfall-based thresholds for range limits in western North America, western Gulf of Mexico, western South America, western Australia, Middle East, northwest Africa, east central Africa, and west central Africa. Our results show that in certain range limits (e.g., eastern North America, western Gulf of Mexico, eastern Asia), winter air temperature extremes play an especially important role. We conclude that rainfall and temperature regimes are both important in western North America, western Gulf of Mexico, and western Australia. With climate change, alterations in temperature and rainfall regimes will affect the global distribution, abundance, and diversity of mangrove forests. In general, warmer winter temperatures are expected to allow mangroves to expand poleward at the expense of salt marshes. However, dispersal and habitat availability constraints may hinder expansion near certain range limits. Along arid and semi-arid coasts, decreases or increases in rainfall are expected to lead to mangrove contraction or expansion, respectively. Collectively, our analyses quantify climate-mangrove linkages and improve our understanding of the expected global- and regional-scale effects of climate change upon mangrove forests.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1248","usgsCitation":"Osland, M.J., Feher, L.C., Griffith, K., Cavanaugh, K.C., Enwright, N.M., Day, R.H., Stagg, C.L., Krauss, K.W., Howard, R.J., Grace, J.B., and Rogers, K., 2017, Climatic controls on the global distribution, abundance, and species richness of mangrove forests: Ecological Monographs, v. 87, no. 2, p. 341-359, https://doi.org/10.1002/ecm.1248.","productDescription":"19 p.","startPage":"341","endPage":"359","ipdsId":"IP-076270","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470151,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Climatic_controls_on_the_global_distribution_abundance_and_species_richness_of_mangrove_forests/27744399","text":"External Repository"},{"id":438457,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78C9TDM","text":"USGS data release","linkHelpText":"Climatic controls on the global distribution, abundance, and species richness of mangrove forests"},{"id":332731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-08","publicationStatus":"PW","scienceBaseUri":"586cc689e4b0f5ce109fa937","contributors":{"authors":[{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research 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high-temporal-frequency maps of surface water extents and elevation variations of global water bodies (lakes/reservoirs, rivers, estuaries, oceans, and sea ice) at higher spatial resolution than is available with current technologies (Biancamaria et al. 2016; Alsdorf et al. 2007). The primary instrument on SWOT is based on a Ka-band radar interferometer (KaRIN), which uses radar interferometery technology. The satellite will fly two radar antennas at either end of a 10-m (33 ft) mast, allowing it to measure the elevation of the surface along a 120-km (75 mi)-wide swath below. The availability of high-frequency and high-resolution maps of elevations and extents for surface water bodies and oceans will present unique opportunities to address numerous societally relevant challenges around the globe (Srinivasan et al. 2015). These opportunities may include such diverse and far-ranging applications as fisheries management, flood inundation mapping/risk mitigation/forecasting, wildlife conservation, global data assimilation for improving forecast of ocean tides and weather, reservoir management, climate change impacts and adaptation, and river discharge estimation, among others.
Although SWOT is a research mission and not scheduled for launch for another 4 years, there is a need to build engagement within the application community now and to explore how best to advance the societal relevance and benefits of the SWOT mission from concept to reality. The SWOT Applications Working Group organized a workshop on 5–6 April 2017 at the U.S. Geological Survey (USGS) headquarters in Reston, Virginia. The goal of the workshop was to understand and communicate how the applications community can use SWOT data to address problems of profound societal relevance.
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Unfortunately, applying theory to learn about the role of spatial structure on populations has been hindered by the lack of mechanistic spatial models and inability to make precise observations of population state and structure. Spatial capture–recapture (SCR) represents an individual‐based analytic framework for overcoming this fundamental obstacle that has limited the utility of ecological theory. SCR methods make explicit use of spatial encounter information on individuals in order to model density and other spatial aspects of animal population structure, and they have been widely adopted in the last decade. We review the historical context and emerging developments in SCR models that enable the integration of explicit ecological hypotheses about landscape connectivity, movement, resource selection, and spatial variation in density, directly with individual encounter history data obtained by new technologies (e.g. camera trapping, non‐invasive DNA sampling). We describe ways in which SCR methods stand to advance the study of animal population ecology.
","language":"English","publisher":"Nordic Society Oikos","doi":"10.1111/ecog.03170","usgsCitation":"Royle, J.A., Fuller, A.K., and Sutherland, C., 2017, Unifying population and landscape ecology with spatial capture-recapture: Ecography, v. 41, no. 3, p. 444-456, https://doi.org/10.1111/ecog.03170.","productDescription":"13 p.","startPage":"444","endPage":"456","numberOfPages":"13","ipdsId":"IP-081473","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470160,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.03170","text":"Publisher Index Page"},{"id":362501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2017-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":760180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":760181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutherland, Christopher","contributorId":214549,"corporation":false,"usgs":false,"family":"Sutherland","given":"Christopher","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":760182,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201880,"text":"70201880 - 2017 - Geophysical expression of buried range-front embayment structure: Great Sand Dunes National Park, Rio Grande rift, Colorado","interactions":[],"lastModifiedDate":"2019-01-31T15:21:20","indexId":"70201880","displayToPublicDate":"2017-01-01T15:21:14","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical expression of buried range-front embayment structure: Great Sand Dunes National Park, Rio Grande rift, Colorado","docAbstract":"Great Sand Dunes National Park and Preserve (GRSA, Colorado) lies along the eastern margin of the San Luis Basin and the tectonically active Sangre de Cristo fault system that are part of the northern Rio Grande rift. GRSA lies within a prominent embayment in the range front where two separate sections of the Sangre de Cristo fault system intersect. Fault scarps are observed along both intersecting fault zones within older basin-fill alluvium, but have been obscured by the actively migrating dunefield. The dune sand is also strongly magnetic, locally limiting the usefulness of aeromagnetic methods for mapping concealed structure. This study uses airborne geophysical methods, primarily airborne gravity gradient data, along with constraints from geologic mapping and limited subsurface data and groundwater modeling, to interpret the subsurface basin geometry and range-front structure of the embayment. Using forward modeling of the gravity gradient data and locations of faults inferred from gravity gradient and aeromagnetic lineaments, several previously unrecognized tectonic elements are interpreted adjacent to the range front. Some of the largest rift-related fault offsets are demonstrated to be basinward of the normal fault zones mapped at the surface along the range front of the Sangre de Cristo Mountains, along faults concealed under the dunefield and subparallel to the two fault sections. A fault-bounded structural bench, likely composed of Proterozoic rocks, underlies most of the high dunefield at depths of 500 m to 1 km. The bench is truncated on its southwest margin by a northwest-trending, southwest-dipping normal fault. A northeast-trending, northwest-dipping normal fault with ∼600 m of estimated relief lies under the southern margin of the dunefield and bounds a structurally higher bench of Proterozoic rocks concealed at <400 m depth near the range front. The northwest- and northeast-trending geophysical lineaments generally correspond well with the trends of faults mapped at the surface, and with both pre- and syn-rift structures in the Sangre de Cristo Mountains. Aeromagnetic anomalies are explained by variations in the magnetization of pre-rift rocks, and the strongly magnetic dune sand.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01439.1","usgsCitation":"Drenth, B.J., Grauch, V.J., Ruleman, C.A., and Schenk, J.A., 2017, Geophysical expression of buried range-front embayment structure: Great Sand Dunes National Park, Rio Grande rift, Colorado: Geosphere, v. 13, no. 3, p. 974-990, https://doi.org/10.1130/GES01439.1.","productDescription":"17 p.","startPage":"974","endPage":"990","ipdsId":"IP-080301","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":470161,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01439.1","text":"Publisher Index Page"},{"id":360890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Great Sand Dunes National Park, Rio Grande rift","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.64453124999999,\n 37.661809012124635\n ],\n [\n -105.48763275146483,\n 37.661809012124635\n ],\n [\n -105.48763275146483,\n 37.83636090929915\n ],\n [\n -105.64453124999999,\n 37.83636090929915\n ],\n [\n -105.64453124999999,\n 37.661809012124635\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":755752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grauch, V. J. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":152256,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":755753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755755,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schenk, Judith A","contributorId":212229,"corporation":false,"usgs":false,"family":"Schenk","given":"Judith","email":"","middleInitial":"A","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":755754,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237031,"text":"70237031 - 2017 - Responses of a 64-story unique San Francisco, CA. building to four earthquakes and ambient motions","interactions":[],"lastModifiedDate":"2022-09-27T19:24:47.26479","indexId":"70237031","displayToPublicDate":"2017-01-01T14:22:44","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Responses of a 64-story unique San Francisco, CA. building to four earthquakes and ambient motions","docAbstract":"We analyze the ambient and earthquake responses of a 64-story, instrumented, concrete core shear wall building in San Francisco, Calif. equipped with tuned sloshing liquid dampers (TSDs) and buckling restraining braces (BRBs). In an earlier paper [1], only ambient data were used to identify dynamic characteristics. Recently, the 72-channel instrumental array of the building recorded the 24 August 2014 Mw6.0 South Napa and three other earthquakes – allowing comparison of the dynamic characteristics using ambient and earthquake data. Peak accelerations of ambient and the larger South Napa EQ responses at the basement are 0.12 and 5.2 cm/s/s, respectively – a factor of ~ 42 and, at the 61st level, are 0.30 and 16.8 cm/s/s, respectively –a factor of ~56. Fundamental frequencies determined from spectral ratios for the NS (~0.3Hz), EW (0.27Hz) and torsional accelerations for the earthquake response vary within an insignificant frequency band of ~ 0.02-0.03 Hz as compared to those determined from ambient data. At the level of shaking, BRBs or TSDs are not effective enough to alter dynamic characteristics (frequency or damping). Under future stronger (e.g. design level) shaking of the building, the nonlinearities caused by actions of TSDs and BRBs can substantially shift the dynamic characteristics of the building.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 16th World Conference on Earthquake Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"16th World Conference on Earthquake Engineering","conferenceDate":"January 9-13, 2017","conferenceLocation":"Santiago, Chile","language":"English","publisher":"National Information Centre of Earthquake Engineering","usgsCitation":"Celebi, M., Hooper, J., and Klemencic, R., 2017, Responses of a 64-story unique San Francisco, CA. building to four earthquakes and ambient motions, in Proceedings of the 16th World Conference on Earthquake Engineering, Santiago, Chile, January 9-13, 2017, 12 p.","productDescription":"12 p.","ipdsId":"IP-073184","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407472,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":407471,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wcee.nicee.org/wcee/sixteenth_conf_Santiago/"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.67608642578126,\n 37.568528265476075\n ],\n [\n -122.28607177734376,\n 37.568528265476075\n ],\n [\n -122.28607177734376,\n 37.90953361677018\n ],\n [\n -122.67608642578126,\n 37.90953361677018\n ],\n [\n -122.67608642578126,\n 37.568528265476075\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"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":853117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooper, J.","contributorId":66872,"corporation":false,"usgs":false,"family":"Hooper","given":"J.","email":"","affiliations":[],"preferred":false,"id":853151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klemencic, Ron","contributorId":146973,"corporation":false,"usgs":false,"family":"Klemencic","given":"Ron","email":"","affiliations":[],"preferred":false,"id":853152,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202107,"text":"70202107 - 2017 - Validation of NEXRAD data and models of bird migration stopover sites in the Northeast U.S.","interactions":[],"lastModifiedDate":"2019-02-11T14:15:20","indexId":"70202107","displayToPublicDate":"2017-01-01T14:15:14","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Validation of NEXRAD data and models of bird migration stopover sites in the Northeast U.S.","docAbstract":"The national network of weather surveillance radars (NEXRAD) detects birds in flight, and has proven to be a useful remote-sensing tool for ornithological study. We used data collected during Fall 2008 to 2014 by 16 NEXRAD and four terminal Doppler weather radars (TDWR) in the northeastern U.S. to map and study the spatial distribution of landbirds shortly after they leave daytime stopover sites to embark on nocturnal migratory flights. Given observed variability in the precise timing of migratory exodus, we developed a new method to sample the onset of migration at the point of maximum rate of increase in bird densities aloft to consistently sample exodus across radars and days.
The mean linear trend in aggregate stopover densities of migrants indicated a 4% decline per year from the 2008 baseline density (29% decline over the seven years). Regionally, coastal Virginia and Maine had the steepest declines. The steepest increases in migrant densities across years occurred within the Delmarva Peninsula and in coastal Connecticut.
We used NEXRAD observations to develop models to predict potentially important stopover sites throughout USFWS Region 5. Observed NEXRAD data were positively correlated to observations from TDWR and NASA’s S-Band Dual-Polarimetric Radar (NPOL), though not strongly. Predicted densities increased with increasing hardwood cover across multiple scales and with vegetation productivity. Contrastingly, predicted densities decreased with increasing agricultural, emergent marsh and coniferous land cover, but did not change with fraction of urban cover. Stopover density increased closer to bright areas and the Atlantic coast. Moreover, interactive effects indicated that migrants were more concentrated in forested areas that were both brightly lit and near the Atlantic coast. Large areas of predicted regionally important stopover sites were located along the coastlines of Maine, Long Island Sound, New Jersey, the lower Delmarva Peninsula, within the Adirondack Mountains, Catskill Mountains, and eastern Virginia.
We also created maps of classified stopover use during bimonthly periods and at multiple-scales. Migrant densities peaked along the Adirondack Mountains early in September, and along the Atlantic coast in late September with the passage of Neotropical migrants. Stopover densities peaked in the most northern extent of Maine and New England States in late October with the departure of temperate migrants.
Ground surveys conducted at 48 forested sites within the Delmarva Peninsula and Tidewater Virginia during Fall 2013 and 2014 revealed that nocturnal migrant densities pooled across species and for 14 individual species, after accounting for temporal phenology in their passage timing, were related to factors operating at multiple scales including food resources (primarily arthropod abundance in understory) and understory shrub density at a patch scale, and latitude and proximity to the Atlantic coast at a regional scale.
We integrated field survey and radar data to estimate relative stopover duration and to identify stopover functional types among 45 sites that included data from a past study near the Gulf of Mexico. We identified four functional types spanning the gradient of short rest stops to refueling stops with variable duration of stopover in relation to food abundance. The Mid-Atlantic sites were dominated by rest stops near coastal areas and lacked quick refueling stops due to low overall food abundance. The maps and ecological understanding produced can help inform conservation planning to protect and enhance stopover sites for migratory landbirds in the future.
","language":"English","usgsCitation":"Buler, J.J., McLaren, J., Schreckengost, T., Smolinsky, J.A., Walters, E., Arnold, J.A., and Dawson, D.K., 2017, Validation of NEXRAD data and models of bird migration stopover sites in the Northeast U.S., viii, 112 p.","productDescription":"viii, 112 p.","ipdsId":"IP-081122","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":361147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361129,"type":{"id":15,"text":"Index Page"},"url":"https://lccnetwork.org/resource/final-report-validation-nexrad-data-and-models-bird-migration-stopover-sites-northeast-us"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":756915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaren, James","contributorId":213085,"corporation":false,"usgs":false,"family":"McLaren","given":"James","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":756916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schreckengost, Timothy","contributorId":213086,"corporation":false,"usgs":false,"family":"Schreckengost","given":"Timothy","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":756917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smolinsky, Jaclyn A.","contributorId":202723,"corporation":false,"usgs":false,"family":"Smolinsky","given":"Jaclyn","email":"","middleInitial":"A.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":756918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, Eric","contributorId":213087,"corporation":false,"usgs":false,"family":"Walters","given":"Eric","affiliations":[{"id":36518,"text":"Old Dominion University","active":true,"usgs":false}],"preferred":false,"id":756919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arnold, J. Andrew","contributorId":213088,"corporation":false,"usgs":false,"family":"Arnold","given":"J.","email":"","middleInitial":"Andrew","affiliations":[{"id":36518,"text":"Old Dominion University","active":true,"usgs":false}],"preferred":false,"id":756920,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dawson, Deanna K. 0000-0001-7531-212X ddawson@usgs.gov","orcid":"https://orcid.org/0000-0001-7531-212X","contributorId":202720,"corporation":false,"usgs":true,"family":"Dawson","given":"Deanna","email":"ddawson@usgs.gov","middleInitial":"K.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":756914,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200604,"text":"70200604 - 2017 - Impacts of mastication fuel treatments on California, USA, chaparral vegetation structure and composition","interactions":[],"lastModifiedDate":"2018-10-25T12:08:09","indexId":"70200604","displayToPublicDate":"2017-01-01T12:08:02","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of mastication fuel treatments on California, USA, chaparral vegetation structure and composition","docAbstract":"Mechanical fuel treatments are a primary pre-fire strategy for potentially mitigating the threat of wildland fire, yet there is limited information on how they impact shrubland ecosystems. Our goal was to assess the impact of mechanical mastication fuel treatments on chaparral vegetation and to determine the extent to which they emulate early post-fire succession. Mastication treatments significantly reduced the height and cover of woody vegetation and increased herbaceous cover and diversity. Non-native cover, density, and diversity were also significantly higher in masticated treatments. Comparisons with post-fire data from two studies showed that certain ephemeral post-fire endemics were absent or of limited occurrence from masticated plots in comparison to their abundance on adjacent burned plots. Structurally, masticated sites differed in the dense woody debris cover, whereas burned sites had little such ground cover. Regional comparison of masticated plots to previously published post-fire studies found that burned sites had greater cover, density, and diversity of native species. However, masticated sites and burned sites were broadly similar in distribution of different growth forms. Results from our study show that the use of mastication fuel treatments in chaparral are not in alignment with some resource conservation goals, but in some cases it is recognized that such sacrifice of natural resources may be an acceptable tradeoff to potentially mitigating fire hazard.
","language":"English","publisher":"Association for Fire Ecology","doi":"10.4996/fireecology.130312013","usgsCitation":"Brennan, T.J., and Keeley, J.E., 2017, Impacts of mastication fuel treatments on California, USA, chaparral vegetation structure and composition: Fire Ecology, v. 13, no. 3, p. 120-138, https://doi.org/10.4996/fireecology.130312013.","productDescription":"19 p.","startPage":"120","endPage":"138","ipdsId":"IP-076074","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470162,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4996/fireecology.130312013","text":"Publisher Index Page"},{"id":438458,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73776V9","text":"USGS data release","linkHelpText":"Survey Data for Chaparral Vegetation in Masticated Fuel Treatments on the four Southern California National Forests (2011-2012)"},{"id":358812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.7674560546875,\n 32.56996256044998\n ],\n [\n -115.99914550781249,\n 32.56996256044998\n ],\n [\n -115.99914550781249,\n 35.106428057364255\n ],\n [\n -119.7674560546875,\n 35.106428057364255\n ],\n [\n -119.7674560546875,\n 32.56996256044998\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-01","publicationStatus":"PW","scienceBaseUri":"5c10acd3e4b034bf6a7e6e3f","contributors":{"authors":[{"text":"Brennan, Teresa J. 0000-0002-0646-3298 tjbrennan@usgs.gov","orcid":"https://orcid.org/0000-0002-0646-3298","contributorId":4323,"corporation":false,"usgs":true,"family":"Brennan","given":"Teresa","email":"tjbrennan@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":749710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":749709,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238858,"text":"70238858 - 2017 - USGS revision of global iron ore production data—Clarification of the reporting of iron ore production in China and application of a uniform comparison methodology (2000-2015)","interactions":[],"lastModifiedDate":"2025-03-05T15:17:29.764006","indexId":"70238858","displayToPublicDate":"2017-01-01T09:05:32","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"displayTitle":"USGS revision of global iron ore production data—Clarification of the reporting of iron ore production in China and application of a uniform comparison methodology (2000-2015)","title":"USGS revision of global iron ore production data—Clarification of the reporting of iron ore production in China and application of a uniform comparison methodology (2000-2015)","docAbstract":"Iron ore is the source of primary iron for the world’s iron and steel industries. Its production can be reported as crude ore, usable ore or iron content of ore. Historically, the U.S. Geological Survey (USGS) used reported crude ore production from China in tabulations of world iron ore production while other countries have typically reported their production in terms of usable iron ore. When China’s crude ore production was tabulated with usable ore production from other countries, world iron ore production totals have been overestimated by 10 percent to a high of 32 percent (Figs. 1, 2). The significant increase in iron ore production in China from 2000 through 2015 amplified the overestimation resulting from tabulating inconsistent forms of the material. Sources of data for usable iron ore production in China, beginning in 2000, have become available. This article documents the revision of world iron ore production totals and augments historical China iron ore production figures to show both crude and usable ore values.
","language":"English","publisher":"Society for Mining, Metallurgy, & Exploration","usgsCitation":"Tuck, C.C., Xun, S., and Singerling, S.A., 2017, USGS revision of global iron ore production data—Clarification of the reporting of iron ore production in China and application of a uniform comparison methodology (2000-2015): Mining Engineering, v. 69, no. 2, p. 20-23.","productDescription":"4 p.","startPage":"20","endPage":"23","ipdsId":"IP-081862","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":410473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":410540,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70238858/report.pdf","text":"USGS Accepted Manuscript","size":"295 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":410448,"rank":3,"type":{"id":15,"text":"Index 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trawl surveys. Biomass of total catch per hectare has decreased 75 percent since 2013. Declines were observed across all functional groups, but most notable was the decline of Emerald Shiner, which decreased from 25.3 kg/ha in spring 2013 to <0.01 kg/ha by autumn 2013. The four primary predator species – Walleye, Yellow Perch, White Perch, and White Bass – all decreased from 2013 to 2015. In 2016, White Bass and Yellow Perch (all lifestages combined) continued to decline, while Walleye and White Perch (all ages combined) increased slightly from 5.6 kg/ha and 3.4 kg/ha to 9.0 kg/ha and 5.0 kg/ha, respectively (autumn catches). Despite decreasing trends in biomass, there was little change in biodiversity. Declines in forage biomass, i.e. Emerald Shiner and age-0 White Perch, resulted in an increased mean trophic level of catches. Forage fish to piscivore ratios reflected marked shifts in species composition toward greater forage in 2014 and 2016.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Bodamer Scarbro, B.L., Kraus, R.T., Kocovsky, P., and Vandergoot, C., 2017, Fisheries research and monitoring activities of the Lake Erie Biological Station, 2016.","ipdsId":"IP-084961","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":352813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.83042561866203,\n 42.83947998725651\n ],\n [\n -79.05419559710549,\n 42.84445044266204\n ],\n [\n -79.34723947607836,\n 42.867505439860906\n ],\n [\n -79.63042902700818,\n 42.82979611449315\n ],\n [\n -80.19300640647401,\n 42.78683833970689\n ],\n [\n -80.48946185253618,\n 42.56830684920794\n ],\n [\n -80.75505536977545,\n 42.63058927982553\n ],\n [\n -81.2649125281849,\n 42.65947723113632\n ],\n [\n -81.68254937098362,\n 42.473095041315446\n ],\n [\n -81.94779341039089,\n 42.28566242550343\n ],\n [\n -82.45261137533379,\n 42.096617816981166\n ],\n [\n -82.50875433470178,\n 41.97702258755987\n ],\n [\n -82.6129085481856,\n 42.05303192857255\n ],\n [\n -82.96796357699394,\n 41.990378987810516\n ],\n [\n -83.11885623553695,\n 42.06549924415452\n ],\n [\n -83.11015681923705,\n 42.20201225480912\n ],\n [\n -83.20183479728604,\n 42.17539076035257\n ],\n [\n -83.24447886978825,\n 42.02138217144653\n ],\n [\n -83.29964209129852,\n 41.9183418231263\n ],\n [\n -83.46689589644896,\n 41.71125094657418\n ],\n [\n -83.17885165327081,\n 41.629872982739954\n ],\n [\n -82.94864727645425,\n 41.530145155769816\n ],\n [\n -82.94754108395134,\n 41.46190281418288\n ],\n [\n -82.68519761720665,\n 41.430232650244335\n ],\n [\n -82.45731725777486,\n 41.38919538555325\n ],\n [\n -82.18488329829222,\n 41.44165749902834\n ],\n [\n -82.00315923989179,\n 41.50180730835157\n ],\n [\n -81.76429181925941,\n 41.46784487565424\n ],\n [\n -81.43346949978508,\n 41.65468891025833\n ],\n [\n -81.07814633503381,\n 41.806259431479276\n ],\n [\n -80.6642163266489,\n 41.91355784022605\n ],\n [\n -80.08467398415922,\n 42.10240274001927\n ],\n [\n -79.65015538905237,\n 42.30010672051813\n ],\n [\n -79.23498337452526,\n 42.488602008238786\n ],\n [\n -78.83042561866203,\n 42.83947998725651\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8f8e4b0da30c1bfc500","contributors":{"authors":[{"text":"Bodamer Scarbro, Betsy L. 0000-0002-9022-7027 bbodamerscarbro@usgs.gov","orcid":"https://orcid.org/0000-0002-9022-7027","contributorId":5857,"corporation":false,"usgs":true,"family":"Bodamer Scarbro","given":"Betsy","email":"bbodamerscarbro@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher 0000-0003-4128-3329 cvandergoot@usgs.gov","orcid":"https://orcid.org/0000-0003-4128-3329","contributorId":178356,"corporation":false,"usgs":true,"family":"Vandergoot","given":"Christopher","email":"cvandergoot@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688359,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186169,"text":"70186169 - 2017 - Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska","interactions":[],"lastModifiedDate":"2017-03-30T15:13:22","indexId":"70186169","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska","docAbstract":"Sexual segregation occurs frequently in sexually dimorphic species, and it may be influenced by differential habitat requirements between sexes or by social or evolutionary mechanisms that maintain separation of sexes regardless of habitat selection. Understanding the degree of sex-specific habitat specialization is important for management of wildlife populations and the design of monitoring and research programs. Using mid-summer aerial survey data for Dall’s sheep (Ovis dalli dalli) in southern Alaska during 1983–2011, we assessed differences in summer habitat selection by sex and reproductive status at the landscape scale in Wrangell-St. Elias National Park and Preserve (WRST). Males and females were highly segregated socially, as were females with and without young. Resource selection function (RSF) models containing rugged terrain, intermediate values of the normalized difference vegetation index (NDVI), and open landcover types best explained resource selection by each sex, female reproductive classes, and all sheep combined. For male and all female models, most coefficients were similar, suggesting little difference in summer habitat selection between sexes at the landscape scale. A combined RSF model therefore may be used to predict the relative probability of resource selection by Dall’s sheep in WRST regardless of sex or reproductive status.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyw135","usgsCitation":"Roffler, G.H., Adams, L., and Hebblewhite, M., 2017, Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska: Journal of Mammalogy, v. 98, no. 1, p. 94-105, https://doi.org/10.1093/jmammal/gyw135.","productDescription":"12 p.","startPage":"94","endPage":"105","ipdsId":"IP-060082","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyw135","text":"Publisher Index Page"},{"id":338838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"98","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-17","publicationStatus":"PW","scienceBaseUri":"58de194fe4b02ff32c699ca1","chorus":{"doi":"10.1093/jmammal/gyw135","url":"http://dx.doi.org/10.1093/jmammal/gyw135","publisher":"Oxford University Press (OUP)","authors":"Roffler Gretchen H., Adams Layne G., Hebblewhite Mark","journalName":"Journal of Mammalogy","publicationDate":"9/17/2016"},"contributors":{"authors":[{"text":"Roffler, Gretchen H. groffler@usgs.gov","contributorId":1946,"corporation":false,"usgs":true,"family":"Roffler","given":"Gretchen","email":"groffler@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":687742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":687741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hebblewhite, Mark","contributorId":190188,"corporation":false,"usgs":false,"family":"Hebblewhite","given":"Mark","email":"","affiliations":[],"preferred":false,"id":687743,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70182810,"text":"70182810 - 2017 - Geochemical evidence for a complex origin for the Kelso dunes, Mojave National Preserve, California USA","interactions":[],"lastModifiedDate":"2017-04-28T09:41:46","indexId":"70182810","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical evidence for a complex origin for the Kelso dunes, Mojave National Preserve, California USA","docAbstract":"The Kelso Dune field in southern California is intriguing because although it is of limited areal extent (~ 100 km2), it has a wide variety of dune forms and contains many active dunes (~ 40 km2), which is unusual in the Mojave Desert. Studies over the past eight decades have concluded that the dunes are derived primarily from a single source, Mojave River alluvium, under a dominant, westerly-to-northwesterly wind regime. The majority of these studies did not, however, present data to support the Mojave River as the only source. We conducted mineralogical and geochemical studies of most of the 14 geomorphically defined dune groups of the Kelso Dune field as well as potential sand sources, alluvial sediments from the surrounding mountain ranges. Results indicate that sands in the nine western dune groups have K/Rb and K/Ba (primarily from K-feldspar) compositions that are indistinguishable from Mojave River alluvium (westerly/northwesterly winds) and Budweiser Wash alluvium (southwesterly winds), permitting an interpretation of two sources. In contrast, sands from the five eastern dune groups have K/Rb and K/Ba values that indicate significant inputs from alluvial fan deposits of the Providence Mountains. This requires either rare winds from the east or southeast or, more likely, aeolian reworking of distal Providence Mountain fan sediments by winds from the west, at a rate greater than input from the Mojave River or other western sources. The results indicate that even a small dune field can have a complex origin, either from seasonally varying winds or complex alluvial-fan-dune interaction. Application of K/Rb and K/Ba in K-feldspar as a provenance indicator could be used in many of the world's ergs or sand seas, where dune origins are still not well understood or are controversial. Four examples are given from Africa and the Middle East where such an approach could yield useful new information about dune sand provenance.
","language":"English","publisher":"Elsevier ","doi":"10.1016/j.geomorph.2016.10.002","usgsCitation":"Muhs, D., Lancaster, N., and Skipp, G.L., 2017, Geochemical evidence for a complex origin for the Kelso dunes, Mojave National Preserve, California USA: Geomorphology, v. 276, p. 222-243, https://doi.org/10.1016/j.geomorph.2016.10.002.","productDescription":"22 p. ","startPage":"222","endPage":"243","ipdsId":"IP-072968","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":470172,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://zenodo.org/record/1258997","text":"Publisher Index Page"},{"id":336730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"276","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b7eba1e4b01ccd5500bad7","chorus":{"doi":"10.1016/j.geomorph.2016.10.002","url":"http://dx.doi.org/10.1016/j.geomorph.2016.10.002","publisher":"Elsevier BV","authors":"Muhs Daniel R., Lancaster Nicholas, Skipp Gary L.","journalName":"Geomorphology","publicationDate":"1/2017"},"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":673844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lancaster, Nicholas","contributorId":184242,"corporation":false,"usgs":false,"family":"Lancaster","given":"Nicholas","email":"","affiliations":[],"preferred":false,"id":673845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skipp, Gary L. 0000-0002-9404-0980 gskipp@usgs.gov","orcid":"https://orcid.org/0000-0002-9404-0980","contributorId":2102,"corporation":false,"usgs":true,"family":"Skipp","given":"Gary","email":"gskipp@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":673846,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179824,"text":"70179824 - 2017 - New techniques to measure cliff change from historical oblique aerial photographs and structure-from-motion photogrammetry","interactions":[],"lastModifiedDate":"2017-01-19T10:18:05","indexId":"70179824","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"New techniques to measure cliff change from historical oblique aerial photographs and structure-from-motion photogrammetry","docAbstract":"Oblique aerial photograph surveys are commonly used to document coastal landscapes. Here it is shown that adequate overlap may exist in these photographic records to develop topographic models with Structure-from-Motion (SfM) photogrammetric techniques. Using photographs of Fort Funston, California, from the California Coastal Records Project, imagery were combined with ground control points in a four-dimensional analysis that produced topographic point clouds of the study area’s cliffs for 5 years spanning 2002 to 2010. Uncertainty was assessed by comparing point clouds with airborne LIDAR data, and these uncertainties were related to the number and spatial distribution of ground control points used in the SfM analyses. With six or more ground control points, the root mean squared errors between the SfM and LIDAR data were less than 0.30 m (minimum 1⁄4 0.18 m), and the mean systematic error was less than 0.10 m. The SfM results had several benefits over traditional airborne LIDAR in that they included point coverage on vertical- to-overhanging sections of the cliff and resulted in 10–100 times greater point densities. Time series of the SfM results revealed topographic changes, including landslides, rock falls, and the erosion of landslide talus along the Fort Funston beach. Thus, it was concluded that SfM photogrammetric techniques with historical oblique photographs allow for the extraction of useful quantitative information for mapping coastal topography and measuring coastal change. The new techniques presented here are likely applicable to many photograph collections and problems in the earth sciences.","language":"English","publisher":"BioOne, Coastal education and research foundation","doi":"10.2112/JCOASTRES-D-16-00095.1","collaboration":"Olympic National Park; California Coastal Records Project","usgsCitation":"Warrick, J.A., Ritchie, A., Adelman, G., Adelman, K., and Limber, P.W., 2017, New techniques to measure cliff change from historical oblique aerial photographs and structure-from-motion photogrammetry: Journal of Coastal Research, v. 33, no. 1, p. 39-55, https://doi.org/10.2112/JCOASTRES-D-16-00095.1.","productDescription":"17 p. ","startPage":"39","endPage":"55","ipdsId":"IP-075270","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470181,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2112/jcoastres-d-16-00095.1","text":"Publisher Index Page"},{"id":333423,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5881ded3e4b01192927d9f7b","contributors":{"authors":[{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":658843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ritchie, Andy","contributorId":178426,"corporation":false,"usgs":false,"family":"Ritchie","given":"Andy","email":"","affiliations":[],"preferred":false,"id":658844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adelman, Gabrielle","contributorId":178427,"corporation":false,"usgs":false,"family":"Adelman","given":"Gabrielle","email":"","affiliations":[],"preferred":false,"id":658845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adelman, Ken","contributorId":178428,"corporation":false,"usgs":false,"family":"Adelman","given":"Ken","email":"","affiliations":[],"preferred":false,"id":658846,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Limber, Patrick W. 0000-0002-8207-3750 plimber@usgs.gov","orcid":"https://orcid.org/0000-0002-8207-3750","contributorId":5773,"corporation":false,"usgs":true,"family":"Limber","given":"Patrick","email":"plimber@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":658847,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192594,"text":"70192594 - 2017 - Conservation Reserve Program mitigates grassland loss in the lesser prairie-chicken range of Kansas","interactions":[],"lastModifiedDate":"2017-11-17T11:39:08","indexId":"70192594","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Conservation Reserve Program mitigates grassland loss in the lesser prairie-chicken range of Kansas","docAbstract":"Since the beginning of the 20th century, the overall occupied range of the lesser prairie-chicken (Tympanuchus pallidicinctus) has declined by 84% commensurate with population trends. Much of this decline has been attributed to the loss and fragmentation of native grasslands throughout the lesser prairie-chicken range. However, quantification of changes in land cover in the distribution of the lesser prairie-chicken is lacking. Our objectives were to (1) document changes in the areal extent and connectivity of grasslands in the identified lesser prairie-chicken range in Kansas, USA, (>60% of extant lesser prairie-chicken population) from the 1950s to 2013 using remotely sensed data and (2) assess the potential of the Conservation Reserve Program (U.S. Department of Agriculture Program converting cropland to permanent cover; CRP) to mitigate grassland loss. Digital land cover maps were generated on a decadal time step through spectral classification of LANDSAT images and visual analysis of aerial photographs (1950s and 1960s). Landscape composition and configuration were assessed using FRAGSTATS to compute a variety of landscape metrics measuring changes in the amount of grassland present as well as changes in the size and configuration of grassland patches. With the exception of a single regional portion of the range, nearly all of the grassland converted to cropland in the lesser prairie-chicken range of Kansas occurred prior to the 1950s. Prior to the implementation of CRP, the amount of grassland decreased 3.6% between the 1950s and 1985 from 18,455 km2 to 17,788 km2. Since 1985, the overall amount of grassland in the lesser prairie-chicken range has increased 11.9% to 19,898 km2 due to implementation of CRP, although the area of grassland decreased between 1994 and 2013 as CRP contracts were not renewed by landowners. Since 1986 grassland in Kansas became more connected and less fragmented in response to the CRP. While the CRP has been successful in increasing grassland quantity and connectivity throughout the lesser prairie-chicken range in Kansas, offsetting loss of grassland since the 1950s, abundance and occupied range of lesser prairie-chickens has declined since the 1980s, suggesting that habitat quality is the principal factor influencing population demography of the species. Although the CRP is contributing to conservation actions for lesser prairie-chickens, efforts to improve habitat quality throughout the range of the lesser prairie-chicken are likely necessary to meet management goals. Continuation of the CRP faces an uncertain future in the face of rising commodity prices, energy development, and reduction in program scope, leaving open the possibility that these areas that have created habitat for lesser prairie-chickens could be lost.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2016.11.004","usgsCitation":"Haukos, D.A., Spencer, D., Hagen, C.A., Daniels, M.D., and Goodin, D., 2017, Conservation Reserve Program mitigates grassland loss in the lesser prairie-chicken range of Kansas: Global Ecology and Conservation, v. 9, p. 21-38, https://doi.org/10.1016/j.gecco.2016.11.004.","productDescription":"18 p.","startPage":"21","endPage":"38","ipdsId":"IP-078839","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":470169,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2016.11.004","text":"Publisher Index Page"},{"id":349063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.01904296874999,\n 36.96744946416934\n ],\n [\n -97.8662109375,\n 36.96744946416934\n ],\n [\n -97.8662109375,\n 40.027614437486655\n ],\n [\n -102.01904296874999,\n 40.027614437486655\n ],\n [\n -102.01904296874999,\n 36.96744946416934\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc3de4b06e28e9c23c02","contributors":{"authors":[{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":716485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spencer, David","contributorId":200553,"corporation":false,"usgs":false,"family":"Spencer","given":"David","affiliations":[],"preferred":false,"id":722646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagen, Christian A.","contributorId":177795,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":722647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daniels, Melinda D.","contributorId":166701,"corporation":false,"usgs":false,"family":"Daniels","given":"Melinda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":722648,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goodin, Doug","contributorId":200554,"corporation":false,"usgs":false,"family":"Goodin","given":"Doug","email":"","affiliations":[],"preferred":false,"id":722649,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195834,"text":"70195834 - 2017 - A global analysis of traits predicting species sensitivity to habitat fragmentation","interactions":[],"lastModifiedDate":"2018-03-06T11:55:14","indexId":"70195834","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"A global analysis of traits predicting species sensitivity to habitat fragmentation","docAbstract":"Aim
Elucidating patterns in species responses to habitat fragmentation is an important focus of ecology and conservation, but studies are often geographically restricted, taxonomically narrow or use indirect measures of species vulnerability. We investigated predictors of species presence after fragmentation using data from studies around the world that included all four terrestrial vertebrate classes, thus allowing direct inter-taxonomic comparison.
Location
World-wide.
Methods
We used generalized linear mixed-effect models in an information theoretic framework to assess the factors that explained species presence in remnant habitat patches (3342 patches; 1559 species, mostly birds; and 65,695 records of patch-specific presence–absence). We developed a novel metric of fragmentation sensitivity, defined as the maximum rate of change in probability of presence with changing patch size (‘Peak Change’), to distinguish between general rarity on the landscape and sensitivity to fragmentation per se.
Results
Size of remnant habitat patches was the most important driver of species presence. Across all classes, habitat specialists, carnivores and larger species had a lower probability of presence, and those effects were substantially modified by interactions. Sensitivity to fragmentation (measured by Peak Change) was influenced primarily by habitat type and specialization, but also by fecundity, life span and body mass. Reptiles were more sensitive than other classes. Grassland species had a lower probability of presence, though sample size was relatively small, but forest and shrubland species were more sensitive.
Main conclusions
Habitat relationships were more important than life-history characteristics in predicting the effects of fragmentation. Habitat specialization increased sensitivity to fragmentation and interacted with class and habitat type; forest specialists and habitat-specific reptiles were particularly sensitive to fragmentation. Our results suggest that when conservationists are faced with disturbances that could fragment habitat they should pay particular attention to specialists, particularly reptiles. Further, our results highlight that the probability of presence in fragmented landscapes and true sensitivity to fragmentation are predicted by different factors.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.12509","usgsCitation":"Keinath, D., Doak, D.F., Hodges, K.E., Prugh, L.R., Fagan, W., Sekercioglu, C., Buchart, S.H., and Kauffman, M., 2017, A global analysis of traits predicting species sensitivity to habitat fragmentation: Global Ecology and Biogeography, v. 26, no. 1, p. 115-127, https://doi.org/10.1111/geb.12509.","productDescription":"13 p.","startPage":"115","endPage":"127","ipdsId":"IP-065257","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470230,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/geb.12509","text":"Publisher Index Page"},{"id":352265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-23","publicationStatus":"PW","scienceBaseUri":"5afee8ebe4b0da30c1bfc4d6","contributors":{"authors":[{"text":"Keinath, Douglas","contributorId":12747,"corporation":false,"usgs":true,"family":"Keinath","given":"Douglas","affiliations":[],"preferred":false,"id":730340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doak, Daniel F.","contributorId":46811,"corporation":false,"usgs":true,"family":"Doak","given":"Daniel","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":730341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodges, Karen E.","contributorId":202978,"corporation":false,"usgs":false,"family":"Hodges","given":"Karen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":730342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prugh, Laura R. 0000-0001-9045-3107","orcid":"https://orcid.org/0000-0001-9045-3107","contributorId":196572,"corporation":false,"usgs":false,"family":"Prugh","given":"Laura","email":"","middleInitial":"R.","affiliations":[{"id":13194,"text":"School of Environmental and Forest Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":730343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fagan, William F.","contributorId":108239,"corporation":false,"usgs":true,"family":"Fagan","given":"William F.","affiliations":[],"preferred":false,"id":730344,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sekercioglu, Cagan H.","contributorId":202979,"corporation":false,"usgs":false,"family":"Sekercioglu","given":"Cagan H.","affiliations":[],"preferred":false,"id":730345,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Buchart, Stuart H. M.","contributorId":202980,"corporation":false,"usgs":false,"family":"Buchart","given":"Stuart","email":"","middleInitial":"H. M.","affiliations":[],"preferred":false,"id":730346,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":189179,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":730218,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196113,"text":"70196113 - 2017 - Sub-indicator: Prey fish","interactions":[],"lastModifiedDate":"2018-03-21T11:53:43","indexId":"70196113","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Sub-indicator: Prey fish","docAbstract":"Prey fish communities across the Great Lakes continue to change, although the direction and magnitude of those changes are not consistent across the lakes. The metrics used to categorize prey fish status in this and previous periods are based on elements that are common among each of the lake’s Fish Community Objectives and include diversity and the relative role of native species in the prey fish communities. The diversity index categorized three of lakes as ‘fair’, while Superior and Erie were ‘good’ (Table 1). The short term trend, from the previous period (2008-2010) to the current period (2011-2014) found diversity in Erie and Superior to be unchanging, but the other three lakes to be ‘deteriorating’, resulting in an overall trend categorization of ‘undetermined’ (Table 1). The long term diversity trend suggested Lakes Superior and Erie have the most diverse prey communities although the index for those prey fish have been quite variable over time (Figure 1). In Lake Huron, where non-native alewife have substantially declined, the diversity index has also declined. The continued dominance of alewife in Lake Ontario (96% of the prey fish biomass) resulted in the lowest diversity index value (Figure 1). The proportion of native species within the community was judged as ‘good’ in Lakes Superior and Huron, ‘fair’ in Michigan and Erie and ‘poor’ in Ontario (Table 2). The short term trend was improving in in all lakes except Michigan (‘deteriorating’) and Ontario (‘unchanging’), resulting in an overall short term trend of ‘undetermined’ (Table 2). Over the current period, Lake Superior consistently had the highest proportion native prey fish (87%) while Lake Ontario had the lowest (1%) (Figure 2). Lake Michigan’s percent native has declined as round goby increase and comprises a greater proportion of the community. Native prey fish make up 51% of Lake Erie, although basin-specific values differed (Figure 2). Most notably, native species in Lake Huron comprised less than 10% of the community in 1970, but since alewife have declined, now represent nearly 80% of the community (Figure 2). Prey fish data are most consistent for in-lake populations, which are reported here; data from connecting channels was not consistently available across the basin. Abundance was not used to judge prey fish status since successful, basin-wide management actions, including mineral nutrient input reductions and piscivore restoration, both inherently reduce prey fish abundance. However, recent abundance trends as they relate to predator prey balance are referenced, such as in Lakes Michigan and Huron where piscivore stocking is being reduced to lower predation demand on prey fish populations and maintain sport fisheries.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Sate of the Great Lakes 2017 Technical Report","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"Environment and Climate Change Canada and the U.S. Environmental Protection Agency","usgsCitation":"Weidel, B., and Dunlop, E., 2017, Sub-indicator: Prey fish, 9 p.","productDescription":"9 p.","startPage":"254","endPage":"262","ipdsId":"IP-071538","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":352690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":352660,"type":{"id":15,"text":"Index Page"},"url":"https://binational.net/wp-content/uploads/2017/09/SOGL_2017_Technical_Report-EN.pdf"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8ebe4b0da30c1bfc4ce","contributors":{"authors":[{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":731406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunlop, Erin","contributorId":102377,"corporation":false,"usgs":true,"family":"Dunlop","given":"Erin","affiliations":[],"preferred":false,"id":731407,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189155,"text":"70189155 - 2017 - Drivers of Holocene sea-level change in the Caribbean","interactions":[],"lastModifiedDate":"2017-07-03T09:49:56","indexId":"70189155","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of Holocene sea-level change in the Caribbean","docAbstract":"We present a Holocene relative sea-level (RSL) database for the Caribbean region (5°N to 25°N and 55°W to 90°W) that consists of 499 sea-level index points and 238 limiting dates. The database was compiled from multiple sea-level indicators (mangrove peat, microbial mats, beach rock and acroporid and massive corals). We subdivided the database into 20 regions to investigate the influence of tectonics and glacial isostatic adjustment on RSL. We account for the local-scale processes of sediment compaction and tidal range change using the stratigraphic position (overburden thickness) of index points and paleotidal modeling, respectively. We use a spatio-temporal empirical hierarchical model to estimate RSL position and its rates of change in the Caribbean over 1-ka time slices. Because of meltwater input, the rates of RSL change were highest during the early Holocene, with a maximum of 10.9 ± 0.6 m/ka in Suriname and Guyana and minimum of 7.4 ± 0.7 m/ka in south Florida from 12 to 8 ka. Following complete deglaciation of the Laurentide Ice Sheet (LIS) by ∼7 ka, mid-to late-Holocene rates slowed to < 2.4 ± 0.4 m/ka. The hierarchical model constrains the spatial extent of the mid-Holocene highstand. RSL did not exceed the present height during the Holocene, except on the northern coast of South America, where in Suriname and Guyana, RSL attained a height higher than present by 6.6 ka (82% probability). The highstand reached a maximum elevation of +1.0 ± 1.1 m between 5.3 and 5.2 ka. Regions with a highstand were located furthest away from the former LIS, where the effects from ocean syphoning and hydro-isostasy outweigh the influence of subsidence from forebulge collapse.","language":"English","publisher":"Elesvier","doi":"10.1016/j.quascirev.2016.08.032","usgsCitation":"Khan, N., Ashe, E., Horton, B.P., Dutton, A., Kopp, R.E., Brocard, G., Engelhart, S.E., Hill, D.F., Peltier, W., Vane, C.H., and Scatena, F.N., 2017, Drivers of Holocene sea-level change in the Caribbean: Quaternary Science Reviews, v. 155, p. 13-36, https://doi.org/10.1016/j.quascirev.2016.08.032.","productDescription":"24","startPage":"13","endPage":"36","ipdsId":"IP-076202","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488813,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1320615","text":"External Repository"},{"id":343272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Caribbean Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.98828124999997,\n 3.0308121226643703\n ],\n [\n -54.79980468749997,\n 3.0308121226643703\n ],\n [\n -54.316406249999986,\n 27.60567082646542\n ],\n [\n -73.69628906249997,\n 27.72243591897343\n ],\n [\n -92.63671874999997,\n 27.332735136859146\n ],\n [\n -92.98828124999997,\n 3.0308121226643703\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"155","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595b5797e4b0d1f9f0536db4","contributors":{"authors":[{"text":"Khan, Nicole 0000-0002-9845-1103 nkhan@usgs.gov","orcid":"https://orcid.org/0000-0002-9845-1103","contributorId":194111,"corporation":false,"usgs":true,"family":"Khan","given":"Nicole","email":"nkhan@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":703244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashe, Erica","contributorId":194112,"corporation":false,"usgs":false,"family":"Ashe","given":"Erica","affiliations":[],"preferred":false,"id":703245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horton, Benjamin P.","contributorId":192807,"corporation":false,"usgs":false,"family":"Horton","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false},{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":703246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dutton, Andrea","contributorId":194113,"corporation":false,"usgs":false,"family":"Dutton","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":703247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kopp, Robert E.","contributorId":194114,"corporation":false,"usgs":false,"family":"Kopp","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":703248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brocard, Gilles","contributorId":194115,"corporation":false,"usgs":false,"family":"Brocard","given":"Gilles","affiliations":[],"preferred":false,"id":703249,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Engelhart, Simon E.","contributorId":60104,"corporation":false,"usgs":false,"family":"Engelhart","given":"Simon","email":"","middleInitial":"E.","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":703250,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hill, David F.","contributorId":194116,"corporation":false,"usgs":false,"family":"Hill","given":"David","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":703251,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Peltier, W.R.","contributorId":194117,"corporation":false,"usgs":false,"family":"Peltier","given":"W.R.","email":"","affiliations":[],"preferred":false,"id":703252,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vane, Christopher H.","contributorId":192893,"corporation":false,"usgs":false,"family":"Vane","given":"Christopher","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":703253,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Scatena, Fred N.","contributorId":194118,"corporation":false,"usgs":false,"family":"Scatena","given":"Fred","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":703254,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70189470,"text":"70189470 - 2017 - Infectious hematopoietic necrosis virus virological and genetic surveillance 2000–2012","interactions":[],"lastModifiedDate":"2017-07-13T13:42:28","indexId":"70189470","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Infectious hematopoietic necrosis virus virological and genetic surveillance 2000–2012","docAbstract":"Surveillance records of the acute RNA pathogen of Pacific salmonid fish infectious hematopoietic necrosis virus are combined for the first time to enable landscape-level ecological analyses and modeling. The study area is the freshwater ecosystems of the large Columbia River watershed in the U.S. states of Washington, Oregon, and Idaho, as well as coastal rivers in Washington and Oregon. The study period is 2000–2012, and records were contributed by all five resource management agencies that operate conservation hatcheries in the study area. Additional records from wild fish were collected from the National Wild Fish Health Survey, operated by the U.S. Fish and Wildlife Survey. After curation and normalization, the data set consists of 6766 records, representing 1146 sample sites and 15 different fish hosts. The virus was found in an average of 12.4% of records, and of these 66.2% also have viral genetic analysis available. This data set is used to conduct univariate ecological and epidemiological analyses and develop a novel hierarchical landscape transmission model for an aquatic pathogen.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1634","usgsCitation":"Breyta, R., Brito, I.L., Kurath, G., and LaDeau, S.L., 2017, Infectious hematopoietic necrosis virus virological and genetic surveillance 2000–2012: Ecology, v. 98, no. 1, p. 283-283, https://doi.org/10.1002/ecy.1634.","productDescription":"1 p.","startPage":"283","endPage":"283","ipdsId":"IP-079462","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":470235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.1634","text":"Publisher Index Page"},{"id":343805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"1","noUsgsAuthors":false,"publicationDate":"2017-01-03","publicationStatus":"PW","scienceBaseUri":"596886a0e4b0d1f9f05f5998","contributors":{"authors":[{"text":"Breyta, Rachel","contributorId":150355,"corporation":false,"usgs":false,"family":"Breyta","given":"Rachel","affiliations":[],"preferred":false,"id":704803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brito, Ilana L.","contributorId":177102,"corporation":false,"usgs":false,"family":"Brito","given":"Ilana","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":704804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":704805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaDeau, Shannon L.","contributorId":172640,"corporation":false,"usgs":false,"family":"LaDeau","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":704806,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193167,"text":"70193167 - 2017 - Validation of daily increments periodicity in otoliths of spotted gar","interactions":[],"lastModifiedDate":"2017-11-20T15:37:49","indexId":"70193167","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3909,"text":"Journal of the Southeastern Association of Fish and Wildlife Agencies","active":true,"publicationSubtype":{"id":10}},"title":"Validation of daily increments periodicity in otoliths of spotted gar","docAbstract":"Accurate age and growth information is essential in successful management of fish populations and for understanding early life history. We validated daily increment deposition, including the timing of first ring formation, for spotted gar (Lepisosteus oculatus) through 127 days post hatch. Fry were produced from hatchery-spawned specimens, and up to 10 individuals per week were sacrificed and their otoliths (sagitta, lapillus, and asteriscus) removed for daily age estimation. Daily age estimates for all three otolith pairs were significantly related to known age. The strongest relationships existed for measurements from the sagitta (r2 = 0.98) and the lapillus (r2 = 0.99) with asteriscus (r2 = 0.95) the lowest. All age prediction models resulted in a slope near unity, indicating that ring deposition occurred approximately daily. Initiation of ring formation varied among otolith types, with deposition beginning 3, 7, and 9 days for the sagitta, lapillus, and asteriscus, respectively. Results of this study suggested that otoliths are useful to estimate daily age of spotted gar juveniles; these data may be used to back calculate hatch dates, estimate early growth rates, and correlate with environmental factor that influence spawning in wild populations. is early life history information will be valuable in better understanding the ecology of this species.
","language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","usgsCitation":"Snow, R.A., Long, J.M., and Frenette, B.D., 2017, Validation of daily increments periodicity in otoliths of spotted gar: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 4, p. 60-65.","productDescription":"6 p.","startPage":"60","endPage":"65","ipdsId":"IP-077724","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349157,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.seafwa.org/publications/journal/?id=402080"}],"volume":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc3de4b06e28e9c23bf9","contributors":{"authors":[{"text":"Snow, Richard A.","contributorId":176213,"corporation":false,"usgs":false,"family":"Snow","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":722924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frenette, Bryan D.","contributorId":200628,"corporation":false,"usgs":false,"family":"Frenette","given":"Bryan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":722925,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187204,"text":"70187204 - 2017 - Accurate aging of juvenile salmonids using fork lengths","interactions":[],"lastModifiedDate":"2017-04-26T12:54:27","indexId":"70187204","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Accurate aging of juvenile salmonids using fork lengths","docAbstract":"Juvenile salmon life history strategies, survival, and habitat interactions may vary by age cohort. However, aging individual juvenile fish using scale reading is time consuming and can be error prone. Fork length data are routinely measured while sampling juvenile salmonids. We explore the performance of aging juvenile fish based solely on fork length data, using finite Gaussian mixture models to describe multimodal size distributions and estimate optimal age-discriminating length thresholds. Fork length-based ages are compared against a validation set of juvenile coho salmon, Oncorynchus kisutch, aged by scales. Results for juvenile coho salmon indicate greater than 95% accuracy can be achieved by aging fish using length thresholds estimated from mixture models. Highest accuracy is achieved when aged fish are compared to length thresholds generated from samples from the same drainage, time of year, and habitat type (lentic versus lotic), although relatively high aging accuracy can still be achieved when thresholds are extrapolated to fish from populations in different years or drainages. Fork length-based aging thresholds are applicable for taxa for which multiple age cohorts coexist sympatrically. Where applicable, the method of aging individual fish is relatively quick to implement and can avoid ager interpretation bias common in scale-based aging.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2016.09.012","usgsCitation":"Sethi, S., Gerken, J., and Ashline, J., 2017, Accurate aging of juvenile salmonids using fork lengths: Fisheries Research, v. 185, p. 161-168, https://doi.org/10.1016/j.fishres.2016.09.012.","productDescription":"8 p.","startPage":"161","endPage":"168","ipdsId":"IP-077073","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470171,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2016.09.012","text":"Publisher Index Page"},{"id":340459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5901b1bae4b0c2e071a99b92","contributors":{"authors":[{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerken, Jonathon","contributorId":191437,"corporation":false,"usgs":false,"family":"Gerken","given":"Jonathon","email":"","affiliations":[],"preferred":false,"id":693046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ashline, Joshua","contributorId":191438,"corporation":false,"usgs":false,"family":"Ashline","given":"Joshua","email":"","affiliations":[],"preferred":false,"id":693047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192516,"text":"70192516 - 2017 - Impacts of mesquite distribution on seasonal space use of lesser prairie-chickens","interactions":[],"lastModifiedDate":"2017-10-26T13:45:42","indexId":"70192516","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of mesquite distribution on seasonal space use of lesser prairie-chickens","docAbstract":"Loss of native grasslands by anthropogenic disturbances has reduced availability and connectivity of habitat for many grassland species. A primary threat to contiguous grasslands is the encroachment of woody vegetation, which is spurred by disturbances that take on many forms from energy development, fire suppression, and grazing. These disturbances are exacerbated by natural- and human-driven cycles of changes in climate punctuated by drought and desertification conditions. Encroachment of honey mesquite (Prosopis glandulosa) into the prairies of southeastern New Mexico has potentially limited habitat for numerous grassland species, including lesser prairie-chickens (Tympanuchus pallidicinctus). To determine the magnitude of impacts of distribution of mesquite and how lesser prairie-chickens respond to mesquite presence on the landscape in southeastern New Mexico, we evaluated seasonal space use of lesser prairie-chickens in the breeding and nonbreeding seasons. We derived several remotely sensed spatial metrics to characterize the distribution of mesquite. We then used these data to create population-level resource utilization functions and predict intensity of use of lesser prairie-chickens across our study area. Home ranges were smaller in the breeding season compared with the nonbreeding season; however, habitat use was similar across seasons. During both seasons, lesser prairie-chickens used areas closer to leks and largely avoided areas with mesquite. Relative to the breeding season, during the nonbreeding season habitat use suggested a marginal increase in mesquite within areas of low intensity of use, yet aversion to mesquite was strong in areas of medium to high intensity of use. To our knowledge, our study is the first to demonstrate a negative behavioral response by lesser prairie-chickens to woody encroachment in native grasslands. To mitigate one of the possible limiting factors for lesser prairie-chickens, we suggest future conservation strategies be employed by land managersto reduce mesquite abundance in the southern portion of their current range.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2016.09.006","usgsCitation":"Boggie, M.A., Strong, C.R., Lusk, D., Carleton, S.A., Gould, W., Howard, R.L., Nichols, C.T., Falkowski, M.J., and Hagen, C.A., 2017, Impacts of mesquite distribution on seasonal space use of lesser prairie-chickens: Rangeland Ecology and Management, v. 70, no. 1, p. 68-77, https://doi.org/10.1016/j.rama.2016.09.006.","productDescription":"10 p.","startPage":"68","endPage":"77","ipdsId":"IP-073814","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470250,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2016.09.006","text":"Publisher Index Page"},{"id":347478,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","county":"Chaves County, Lea 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