Extraordinary marine inundation scattered clasts southward on the island of Anegada, 120 km south of the Puerto Rico Trench, sometime between 1200 and 1480 calibrated years (cal yr) CE. Many of these clasts were likely derived from a fringing reef and from the sandy flat that separates the reef from the island’s north shore. The scattered clasts include no fewer than 200 coral boulders, mapped herein for the first time and mainly found hundreds of meters inland. Many of these are complete colonies of the brain coral Diploria strigosa. Other coral species represented include Orbicella (formerly Montastraea) annularis, Porites astreoides, and Acropora palmata. Associated bioclastic carbonate sand locally contains articulated cobble-size valves of the lucine Codakia orbicularis and entire conch shells of Strombus gigas, mollusks that still inhabit the sandy shallows between the island’s north shore and a fringing reef beyond. Imbricated limestone slabs are clustered near some of the coral boulders. In addition, fields of scattered limestone boulders and cobbles near sea level extend mainly southward from limestone sources as much as 1 km inland. Radiocarbon ages have been obtained from 27 coral clasts, 8 lucine valves, and 3 conch shells. All these additional ages predate 1500 cal yr CE, all but 2 are in the range 1000–1500 cal yr CE, and 16 of 22 brain coral ages cluster in the range 1200–1480 cal yr CE. The event marked by these coral and mollusk clasts likely occurred in the last centuries before Columbus (before 1492 CE).
The pre-Columbian deposits surpass Anegada’s previously reported evidence for extreme waves in post-Columbian time. The coarsest of the modern storm deposits consist of coral rubble that lines the north shore and sandy fans on the south shore; neither of these storm deposits extends more than 50 m inland. More extensive overwash, perhaps by the 1755 Lisbon tsunami, is marked primarily by a sheet of sand and shells found mainly below sea level beneath the floors of modern salt ponds. This sheet extends more than 1 km southward from the north shore and dates to the interval 1650–1800 cal yr CE. Unlike the pre-Columbian deposits, it lacks coarse clasts from the reef or reef flat; its shell assemblage is instead dominated by cerithid gastropods that were merely stirred up from a marine pond in the island’s interior.
In their inland extent and clustered pre-Columbian ages, the coral clasts and associated deposits suggest extreme waves unrivaled in recent millennia at Anegada. Bioclastic sand coats limestone 4 m above sea level in areas 0.7 and 1.3 km from the north shore. A coral boulder of nearly 1 m3 is 3 km from the north shore by way of an unvegetated path near sea level. As currently understood, the extreme flooding evidenced by these and other clasts represents either an extraordinary storm or a tsunami of nearby origin. The storm would need to have produced tsunami-like bores similar to those of 2013 Typhoon Haiyan in the Philippines. Normal faults and a thrust fault provide nearby tsunami sources along the eastern Puerto Rico Trench.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01356.1","usgsCitation":"Atwater, B.F., ten Brink, U., Cescon, A.L., Feuillet, N., Fuentes, Z., Halley, R.B., Nunez, C., Reinhardt, E.G., Roger, J., Sawai, Y., Spiske, M., Tuttle, M.P., Wei, Y., and Weil-Accardo, J., 2017, Geologic evidence for catastrophic marine inundation in 1200–1480 C.E. near the Puerto Rico Trench at Anegada, British Virgin Islands : Geosphere, v. 13, no. 2, p. 301-368, https://doi.org/10.1130/GES01356.1.","productDescription":"68 p.","startPage":"301","endPage":"368","ipdsId":"IP-066800","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01356.1","text":"Publisher Index Page"},{"id":347745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"British Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.42520141601561,\n 18.684301204932225\n ],\n [\n -64.26727294921875,\n 18.684301204932225\n ],\n [\n -64.26727294921875,\n 18.75518627363531\n ],\n [\n -64.42520141601561,\n 18.75518627363531\n ],\n [\n -64.42520141601561,\n 18.684301204932225\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-17","publicationStatus":"PW","scienceBaseUri":"59f83a37e4b063d5d30980e9","contributors":{"authors":[{"text":"Atwater, Brian F. 0000-0003-1155-2815 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Japan","active":true,"usgs":false}],"preferred":false,"id":717931,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Spiske, Michaela","contributorId":198916,"corporation":false,"usgs":false,"family":"Spiske","given":"Michaela","email":"","affiliations":[],"preferred":false,"id":717617,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tuttle, Martitia P.","contributorId":139388,"corporation":false,"usgs":false,"family":"Tuttle","given":"Martitia","email":"","middleInitial":"P.","affiliations":[{"id":12760,"text":"Tuttle and Associates","active":true,"usgs":false}],"preferred":false,"id":717618,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wei, Yong","contributorId":99691,"corporation":false,"usgs":true,"family":"Wei","given":"Yong","email":"","affiliations":[],"preferred":false,"id":717619,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Weil-Accardo, Jennifer","contributorId":198919,"corporation":false,"usgs":false,"family":"Weil-Accardo","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":717620,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70191872,"text":"70191872 - 2017 - Urbanization may limit impacts of an invasive predator on native mammal diversity","interactions":[],"lastModifiedDate":"2017-10-18T14:45:36","indexId":"70191872","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Urbanization may limit impacts of an invasive predator on native mammal diversity","docAbstract":"Aim
Our understanding of the effects of invasive species on faunal diversity is limited in part because invasions often occur in modified landscapes where other drivers of community diversity can exacerbate or reduce the net impacts of an invader. Furthermore, rigorous assessments of the effects of invasive species on native communities that account for variation in sampling, species-specific detection and occurrence of rare species are lacking. Invasive Burmese pythons (Python molurus bivittatus) may be causing declines in medium- to large-sized mammals throughout the Greater Everglades Ecosystem (GEE); however, other factors such as urbanization, habitat changes and drastic alteration in water flow may also be influential in structuring mammal communities. The aim of this study was to gain an understanding of how mammal communities simultaneously facing invasive predators and intensively human-altered landscapes are influenced by these drivers and their interactions.
Location
Florida, USA.
Methods
We used data from trail cameras and scat searches with a hierarchical community model that accounts for undetected species to determine the relative influence of introduced Burmese pythons, urbanization, local hydrology, habitat types and interactive effects between pythons and urbanization on mammal species occurrence, site-level species richness, and turnover.
Results
Python density had significant negative effects on all species except coyotes. Despite these negative effects, occurrence of some generalist species increased significantly near urban areas. At the community level, pythons had the greatest impact on species richness, while turnover was greatest along the urbanization gradient where communities were increasingly similar as distance to urbanization decreased.
Main conclusions
We found evidence for an antagonistic interaction between pythons and urbanization where the impacts of pythons were reduced near urban development. Python-induced changes to mammal communities may be mediated near urban development, but elsewhere in the GEE, pythons are likely causing a fundamental restructuring of the food web, declines in ecosystem function, and creating complex and unpredictable cascading effects.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12531","usgsCitation":"Reichert, B., Sovie, A.R., Udell, B.J., Hart, K.M., Borkhataria, R.R., Bonneau, M., Reed, R., and McCleery, R.A., 2017, Urbanization may limit impacts of an invasive predator on native mammal diversity: Diversity and Distributions, v. 23, no. 4, p. 355-367, https://doi.org/10.1111/ddi.12531.","productDescription":"13 p.","startPage":"355","endPage":"367","ipdsId":"IP-077761","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469970,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12531","text":"Publisher Index Page"},{"id":346891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.529296875,\n 25.085598897064752\n ],\n [\n -80.0189208984375,\n 25.085598897064752\n ],\n [\n -80.0189208984375,\n 27.235094607795503\n ],\n [\n -82.529296875,\n 27.235094607795503\n ],\n [\n -82.529296875,\n 25.085598897064752\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-26","publicationStatus":"PW","scienceBaseUri":"59e86836e4b05fe04cd4d1ff","contributors":{"authors":[{"text":"Reichert, Brian E.","contributorId":197423,"corporation":false,"usgs":false,"family":"Reichert","given":"Brian E.","affiliations":[],"preferred":false,"id":713475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sovie, Adia R.","contributorId":197424,"corporation":false,"usgs":false,"family":"Sovie","given":"Adia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":713477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Udell, Brad J.","contributorId":197490,"corporation":false,"usgs":false,"family":"Udell","given":"Brad","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":713606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":713478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Borkhataria, Rena R.","contributorId":197425,"corporation":false,"usgs":false,"family":"Borkhataria","given":"Rena","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":713479,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bonneau, Mathieu","contributorId":150041,"corporation":false,"usgs":false,"family":"Bonneau","given":"Mathieu","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":713480,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":713474,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCleery, Robert A.","contributorId":139849,"corporation":false,"usgs":false,"family":"McCleery","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":713476,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70188545,"text":"70188545 - 2017 - Evidence for strong lateral seismic velocity variation in the lower crust and upper mantle beneath the California margin","interactions":[],"lastModifiedDate":"2017-06-15T12:15:46","indexId":"70188545","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for strong lateral seismic velocity variation in the lower crust and upper mantle beneath the California margin","docAbstract":"Regional seismograms from earthquakes in Northern California show a systematic difference in arrival times across Southern California where long period (30–50 seconds) SH waves arrive up to 15 seconds earlier at stations near the coast compared with sites towards the east at similar epicentral distances. We attribute this time difference to heterogeneity of the velocity structure at the crust-mantle interface beneath the California margin. To model these observations, we propose a fast seismic layer, with thickness growing westward from the San Andreas along with a thicker and slower continental crust to the east. Synthetics generated from such a model are able to match the observed timing of SH waveforms better than existing 3D models. The presence of a strong upper mantle buttressed against a weaker crust has a major influence in how the boundary between the Pacific plate and North American plate deforms and may explain the observed asymmetric strain rate across the boundary.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2017.02.002","usgsCitation":"Lai, V., Graves, R., Wei, S., and Helmberger, D., 2017, Evidence for strong lateral seismic velocity variation in the lower crust and upper mantle beneath the California margin: Earth and Planetary Science Letters, p. 202-211, https://doi.org/10.1016/j.epsl.2017.02.002.","productDescription":"10 p. ","startPage":"202","endPage":"211","ipdsId":"IP-080254","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":461653,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2017.02.002","text":"Publisher Index Page"},{"id":342548,"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 -119.33349609375,\n 38.41916639395372\n ],\n [\n -122.091064453125,\n 36.55377524336089\n ],\n [\n -122.04711914062499,\n 36.13787471840729\n ],\n [\n -121.73950195312499,\n 35.67514743608467\n ],\n [\n -121.46484375,\n 35.35321610123823\n ],\n [\n -120.9375,\n 34.97600151317588\n ],\n [\n -120.87158203125,\n 34.786739162702524\n ],\n [\n -120.88256835937499,\n 34.49750272138159\n ],\n [\n -120.728759765625,\n 34.30714385628804\n ],\n [\n -120.5419921875,\n 34.23451236236987\n ],\n [\n -120.201416015625,\n 34.225429015241396\n ],\n [\n -119.44335937499999,\n 34.288991865037524\n ],\n [\n -118.05908203124999,\n 35.16482750605027\n ],\n [\n -117.344970703125,\n 35.71975793933433\n ],\n [\n -116.8505859375,\n 36.11125252076156\n ],\n [\n -119.33349609375,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59439c94e4b062508e31a9af","contributors":{"authors":[{"text":"Lai, Voon","contributorId":192952,"corporation":false,"usgs":false,"family":"Lai","given":"Voon","affiliations":[],"preferred":false,"id":698269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":698268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wei, Shengji","contributorId":192953,"corporation":false,"usgs":false,"family":"Wei","given":"Shengji","email":"","affiliations":[],"preferred":false,"id":698270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Helmberger, Don","contributorId":192954,"corporation":false,"usgs":false,"family":"Helmberger","given":"Don","email":"","affiliations":[],"preferred":false,"id":698271,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192860,"text":"70192860 - 2017 - Numerical simulation of large-scale bed load particle tracer advection-dispersion in rivers with free bars","interactions":[],"lastModifiedDate":"2017-11-06T14:05:19","indexId":"70192860","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Numerical simulation of large-scale bed load particle tracer advection-dispersion in rivers with free bars","docAbstract":"Asymptotic characteristics of the transport of bed load tracer particles in rivers have been described by advection-dispersion equations. Here we perform numerical simulations designed to study the role of free bars, and more specifically single-row alternate bars, on streamwise tracer particle dispersion. In treating the conservation of tracer particle mass, we use two alternative formulations for the Exner equation of sediment mass conservation: the flux-based formulation, in which bed elevation varies with the divergence of the bed load transport rate, and the entrainment-based formulation, in which bed elevation changes with the net deposition rate. Under the condition of no net bed aggradation/degradation, a 1-D flux-based deterministic model that does not describe free bars yields no streamwise dispersion. The entrainment-based 1-D formulation, on the other hand, models stochasticity via the probability density function (PDF) of particle step length, and as a result does show tracer dispersion. When the formulation is generalized to 2-D to include free alternate bars, however, both models yield almost identical asymptotic advection-dispersion characteristics, in which streamwise dispersion is dominated by randomness inherent in free bar morphodynamics. This randomness can result in a heavy-tailed PDF of waiting time. In addition, migrating bars may constrain the travel distance through temporary burial, causing a thin-tailed PDF of travel distance. The superdiffusive character of streamwise particle dispersion predicted by the model is attributable to the interaction of these two effects.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016JF003951","usgsCitation":"Iwasaki, T., Nelson, J.M., Shimizu, Y., and Parker, G., 2017, Numerical simulation of large-scale bed load particle tracer advection-dispersion in rivers with free bars: Journal of Geophysical Research F: Earth Surface, v. 122, no. 4, p. 847-874, https://doi.org/10.1002/2016JF003951.","productDescription":"28 p.","startPage":"847","endPage":"874","ipdsId":"IP-075794","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":348286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-12","publicationStatus":"PW","scienceBaseUri":"5a07e90fe4b09af898c8cbed","contributors":{"authors":[{"text":"Iwasaki, Toshiki","contributorId":173795,"corporation":false,"usgs":false,"family":"Iwasaki","given":"Toshiki","email":"","affiliations":[{"id":17685,"text":"University of Illinois, Champagne-Urbana","active":true,"usgs":false}],"preferred":false,"id":717233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":717232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shimizu, Yasuyuki","contributorId":173790,"corporation":false,"usgs":false,"family":"Shimizu","given":"Yasuyuki","email":"","affiliations":[{"id":17805,"text":"Hokkaido University, Sapporo, Japan","active":true,"usgs":false}],"preferred":false,"id":717234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Gary","contributorId":104326,"corporation":false,"usgs":true,"family":"Parker","given":"Gary","email":"","affiliations":[],"preferred":false,"id":720701,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193045,"text":"70193045 - 2017 - Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem","interactions":[],"lastModifiedDate":"2017-11-06T16:31:52","indexId":"70193045","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem","title":"Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem","docAbstract":"Sparse information exists about the ecology of Spiny Softshell Turtles (Apalone spinifera) in large rivers, at the northwestern extent of their natural range, and in Montana, where they are disjunct from downstream populations and a State Species of Concern. We determined spatiotemporal ecology of 47 female and 12 male turtles from 2009 through 2012 and identified fundamental habitats in the Missouri River in east-central Montana. Movement rates of females were greater than those of males and peaked before nesting. Movement rates of males peaked before overwintering, and movement rates of both sexes were minimal in winter. Home range sizes were not different between sexes, varied among individuals and seasons, and were similar to those reported elsewhere in their northern range. Turtles aggregated and showed interannual fidelity to separate and disparate habitats in different seasons. Turtles often chose fine substrates, tributary confluences, and reaches with islands during summer and mainstem outside bends in the winter. They inhabited shallow, slow water velocity areas from May to September. They inhabited deeper, moderate velocity areas from October to April. We did not observe ice jams and associated riverbed scour at hibernacula, but did observe them elsewhere. Ice jams may be spatially predictable and influence the distribution of riverine turtles during autumn and winter. Preservation of dissimilar habitats used during major portions of the life cycle (lateral habitats, islands, and hibernacula) and natural streamflow patterns, which influenced timing of habitat availability and turtle movement, may facilitate continued existence of Spiny Softshell Turtles in the Missouri River in Montana
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Tornabene, B., Bramblett, R.G., Zale, A.V., and Leathe, S.A., 2017, Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem: Herpetological Conservation and Biology, v. 12, no. 1, p. 252-271.","productDescription":"20 p.","startPage":"252","endPage":"271","ipdsId":"IP-071425","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347693,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol12_issue1.html"}],"volume":"12","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e90fe4b09af898c8cbeb","contributors":{"authors":[{"text":"Tornabene, Brian J.","contributorId":200041,"corporation":false,"usgs":false,"family":"Tornabene","given":"Brian J.","affiliations":[],"preferred":false,"id":720774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bramblett, Robert G.","contributorId":169857,"corporation":false,"usgs":false,"family":"Bramblett","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":720775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leathe, Stephen A.","contributorId":200042,"corporation":false,"usgs":false,"family":"Leathe","given":"Stephen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720776,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190700,"text":"70190700 - 2017 - Inter-nesting movements and habitat-use of adult female Kemp’s ridley turtles in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2017-09-12T15:09:37","indexId":"70190700","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Inter-nesting movements and habitat-use of adult female Kemp’s ridley turtles in the Gulf of Mexico","docAbstract":"Species vulnerability is increased when individuals congregate in restricted areas for breeding; yet, breeding habitats are not well defined for many marine species. Identification and quantification of these breeding habitats are essential to effective conservation. Satellite telemetry and switching state-space modeling (SSM) were used to define inter-nesting habitat of endangered Kemp’s ridley turtles (Lepidochelys kempii) in the Gulf of Mexico. Turtles were outfitted with satellite transmitters after nesting at Padre Island National Seashore, Texas, USA, from 1998 through 2013 (n = 60); Rancho Nuevo, Tamaulipas, Mexico, during 2010 and 2011 (n = 11); and Tecolutla, Veracruz, Mexico, during 2012 and 2013 (n = 11). These sites span the range of nearly all nesting by this species. Inter-nesting habitat lies in a narrow band of nearshore western Gulf of Mexico waters in the USA and Mexico, with mean water depth of 14 to 19 m within a mean distance to shore of 6 to 11 km as estimated by 50% kernel density estimate, α-Hull, and minimum convex polygon methodologies. Turtles tracked during the inter-nesting period moved, on average, 17.5 km/day and a mean total distance of 398 km. Mean home ranges occupied were 725 to 2948 km2. Our results indicate that these nearshore western Gulf waters represent critical inter-nesting habitat for this species, where threats such as shrimp trawling and oil and gas platforms also occur. Up to half of all adult female Kemp’s ridleys occupy this habitat for weeks to months during each nesting season. Because inter-nesting habitat for this species is concentrated in nearshore waters of the western Gulf of Mexico in both Mexico and the USA, international collaboration is needed to protect this essential habitat and the turtles occurring within it.
","language":"English","publisher":"PLOS ONE","doi":"10.1371/journal.pone.0174248","usgsCitation":"Shaver, D.J., Hart, K.M., Fujisaki, I., Bucklin, D.N., Iverson, A., Rubio, C., Backof, T.F., Burchfield, P.M., Gonzales Diaz Miron, R.D., Dutton, P.H., Frey, A., Peña, J., Gamez, D.G., Martinez, H.J., and Ortiz, J., 2017, Inter-nesting movements and habitat-use of adult female Kemp’s ridley turtles in the Gulf of Mexico: PLoS ONE, v. 12, no. 3, e0174248; 27 p., https://doi.org/10.1371/journal.pone.0174248.","productDescription":"e0174248; 27 p.","ipdsId":"IP-074667","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469969,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0174248","text":"Publisher Index Page"},{"id":345671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.3056640625,\n 18.771115062337024\n ],\n [\n -95.29541015625,\n 18.771115062337024\n ],\n [\n -95.29541015625,\n 28.998531814051795\n ],\n [\n -98.3056640625,\n 28.998531814051795\n ],\n [\n -98.3056640625,\n 18.771115062337024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"3","noUsgsAuthors":false,"publicationDate":"2017-03-20","publicationStatus":"PW","scienceBaseUri":"59b8f21fe4b08b1644e0aee5","contributors":{"authors":[{"text":"Shaver, Donna J.","contributorId":11104,"corporation":false,"usgs":true,"family":"Shaver","given":"Donna","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":710208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Kristen M. 0000-0002-5257-7974 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ariverson@usgs.gov","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":179150,"corporation":false,"usgs":true,"family":"Iverson","given":"Autumn","email":"ariverson@usgs.gov","affiliations":[],"preferred":true,"id":710212,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rubio, Cynthia","contributorId":39277,"corporation":false,"usgs":true,"family":"Rubio","given":"Cynthia","email":"","affiliations":[],"preferred":false,"id":710213,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Backof, Thomas F.","contributorId":196388,"corporation":false,"usgs":false,"family":"Backof","given":"Thomas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":710214,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Burchfield, Patrick M.","contributorId":47676,"corporation":false,"usgs":true,"family":"Burchfield","given":"Patrick","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":710215,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gonzales Diaz Miron, Raul de Jesus","contributorId":168393,"corporation":false,"usgs":false,"family":"Gonzales Diaz Miron","given":"Raul","email":"","middleInitial":"de Jesus","affiliations":[],"preferred":false,"id":710216,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dutton, Peter H.","contributorId":98029,"corporation":false,"usgs":true,"family":"Dutton","given":"Peter","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":710217,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Frey, Amy","contributorId":196390,"corporation":false,"usgs":false,"family":"Frey","given":"Amy","email":"","affiliations":[],"preferred":false,"id":710218,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Peña, Jaime","contributorId":34810,"corporation":false,"usgs":true,"family":"Peña","given":"Jaime","affiliations":[],"preferred":false,"id":710219,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Gamez, Daniel Gomez","contributorId":32065,"corporation":false,"usgs":true,"family":"Gamez","given":"Daniel","email":"","middleInitial":"Gomez","affiliations":[],"preferred":false,"id":710220,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Martinez, Hector J.","contributorId":168394,"corporation":false,"usgs":false,"family":"Martinez","given":"Hector","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":710221,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ortiz, Jaime","contributorId":77447,"corporation":false,"usgs":true,"family":"Ortiz","given":"Jaime","email":"","affiliations":[],"preferred":false,"id":710222,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70192834,"text":"70192834 - 2017 - A 130,000-year-old archaeological site in southern California, USA","interactions":[],"lastModifiedDate":"2019-06-03T11:58:41","indexId":"70192834","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"A 130,000-year-old archaeological site in southern California, USA","docAbstract":"The earliest dispersal of humans into North America is a contentious subject, and proposed early sites are required to meet the following criteria for acceptance: (1) archaeological evidence is found in a clearly defined and undisturbed geologic context; (2) age is determined by reliable radiometric dating; (3) multiple lines of evidence from interdisciplinary studies provide consistent results; and (4) unquestionable artefacts are found in primary context1,2. Here we describe the Cerutti Mastodon (CM) site, an archaeological site from the early late Pleistocene epoch, where in situ hammerstones and stone anvils occur in spatio-temporal association with fragmentary remains of a single mastodon (Mammut americanum). The CM site contains spiral-fractured bone and molar fragments, indicating that breakage occurred while fresh. Several of these fragments also preserve evidence of percussion. The occurrence and distribution of bone, molar and stone refits suggest that breakage occurred at the site of burial. Five large cobbles (hammerstones and anvils) in the CM bone bed display use-wear and impact marks, and are hydraulically anomalous relative to the low-energy context of the enclosing sandy silt stratum. 230Th/U radiometric analysis of multiple bone specimens using diffusion–adsorption–decay dating models indicates a burial date of 130.7 ± 9.4 thousand years ago. These findings confirm the presence of an unidentified species of Homo at the CM site during the last interglacial period (MIS 5e; early late Pleistocene), indicating that humans with manual dexterity and the experiential knowledge to use hammerstones and anvils processed mastodon limb bones for marrow extraction and/or raw material for tool production. Systematic proboscidean bone reduction, evident at the CM site, fits within a broader pattern of Palaeolithic bone percussion technology in Africa3,4,5,6, Eurasia7,8,9 and North America10,11,12. The CM site is, to our knowledge, the oldest in situ, well-documented archaeological site in North America and, as such, substantially revises the timing of arrival of Homo into the Americas.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/nature22065","usgsCitation":"Holen, S., Deméré, T., Fisher, D., Fullagar, R., Paces, J.B., Jefferson, G.T., Beeton, J., Cerutti, R.A., Rountrey, A., Vescera, L., and Holen, K., 2017, A 130,000-year-old archaeological site in southern California, USA: Nature, v. 544, p. 479-483, https://doi.org/10.1038/nature22065.","productDescription":"5 p.","startPage":"479","endPage":"483","ipdsId":"IP-074299","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":438400,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HD7SW7","text":"USGS data release","linkHelpText":"U-series isotope data used to date a 130,000-year-old archaeological site in southern California, U.S.A."},{"id":348703,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cerutti Mastodon site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.29690551757814,\n 32.52249989111295\n ],\n [\n -116.94671630859375,\n 32.52249989111295\n ],\n [\n -116.94671630859375,\n 32.83228893100241\n ],\n [\n -117.29690551757814,\n 32.83228893100241\n ],\n [\n -117.29690551757814,\n 32.52249989111295\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"544","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-27","publicationStatus":"PW","scienceBaseUri":"5a60fbeee4b06e28e9c237aa","contributors":{"authors":[{"text":"Holen, Steven R.","contributorId":198785,"corporation":false,"usgs":false,"family":"Holen","given":"Steven R.","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false},{"id":35320,"text":"Center for American Paleolithic Research","active":true,"usgs":false}],"preferred":false,"id":717121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deméré, Thomas A.","contributorId":198786,"corporation":false,"usgs":false,"family":"Deméré","given":"Thomas A.","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":717122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Daniel C.","contributorId":127409,"corporation":false,"usgs":false,"family":"Fisher","given":"Daniel C.","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":717123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fullagar, Richard","contributorId":198789,"corporation":false,"usgs":false,"family":"Fullagar","given":"Richard","affiliations":[{"id":16754,"text":"University of Wollongong, Australia","active":true,"usgs":false}],"preferred":false,"id":717127,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":717125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jefferson, George T.","contributorId":198787,"corporation":false,"usgs":false,"family":"Jefferson","given":"George","email":"","middleInitial":"T.","affiliations":[{"id":35321,"text":"California Department of Parks and Recreation","active":true,"usgs":false}],"preferred":false,"id":717124,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beeton, Jared M.","contributorId":198788,"corporation":false,"usgs":false,"family":"Beeton","given":"Jared M.","affiliations":[{"id":35737,"text":"Adams State University, Alamosa, Colorado","active":true,"usgs":false}],"preferred":false,"id":717126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cerutti, Richard A.","contributorId":198792,"corporation":false,"usgs":false,"family":"Cerutti","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":717131,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rountrey, Adam N.","contributorId":127421,"corporation":false,"usgs":false,"family":"Rountrey","given":"Adam N.","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":717128,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vescera, Lawrence","contributorId":198790,"corporation":false,"usgs":false,"family":"Vescera","given":"Lawrence","email":"","affiliations":[{"id":35321,"text":"California Department of Parks and Recreation","active":true,"usgs":false}],"preferred":false,"id":717129,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Holen, Kathleen A.","contributorId":198791,"corporation":false,"usgs":false,"family":"Holen","given":"Kathleen A.","affiliations":[{"id":35320,"text":"Center for American Paleolithic Research","active":true,"usgs":false},{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":717130,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70182811,"text":"70182811 - 2017 - Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy","interactions":[],"lastModifiedDate":"2018-07-23T12:49:07","indexId":"70182811","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy","docAbstract":"Hurricane Sandy was one of the most destructive hurricanes in US history, making landfall on the New Jersey coast on Oct 30, 2012. Storm impacts included several barrier island breaches, massive coastal erosion, and flooding. While changes to the subaerial landscape are relatively easily observed, storm-induced changes to the adjacent shoreface and inner continental shelf are more difficult to evaluate. These regions provide a framework for the coastal zone, are important for navigation, aggregate resources, marine ecosystems, and coastal evolution. Here we provide unprecedented perspective regarding regional inner continental shelf sediment dynamics based on both observations and numerical modeling over time scales associated with these types of large storm events. Oceanographic conditions and seafloor morphologic changes are evaluated using both a coupled atmospheric-ocean-wave-sediment numerical modeling system and observation analysis from a series of geologic surveys and oceanographic instrument deployments focused on a region offshore of Fire Island, NY. The geologic investigations conducted in 2011 and 2014 revealed lateral movement of sedimentary structures of distances up to 450 m and in water depths up to 30 m, and vertical changes in sediment thickness greater than 1 m in some locations. The modeling investigations utilize a system with grid refinement designed to simulate oceanographic conditions with progressively increasing resolutions for the entire US East Coast (5-km grid), the New York Bight (700-m grid), and offshore of Fire Island, NY (100-m grid), allowing larger scale dynamics to drive smaller scale coastal changes. Model results in the New York Bight identify maximum storm surge of up to 3 m, surface currents on the order of 2 ms-1 along the New Jersey coast, waves up to 8 m in height, and bottom stresses exceeding 10 Pa. Flow down the Hudson Shelf Valley is shown to result in convergent sediment transport and deposition along its axis. Modeled sediment redistribution along Fire Island showed erosion across the crests of inner shelf sand ridges and sedimentation in adjacent troughs, consistent with the geologic observations.","language":"English","publisher":"Elsevier ","doi":"10.1016/j.csr.2017.02.003","usgsCitation":"Warner, J., Schwab, W.C., List, J.H., Safak, I., Liste, M., and Baldwin, W.E., 2017, Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy: Continental Shelf Research, v. 138, p. 1-18, https://doi.org/10.1016/j.csr.2017.02.003.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-072875","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":469976,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.02.003","text":"Publisher Index Page"},{"id":336758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"138","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e60271e4b09da6799ac67f","chorus":{"doi":"10.1016/j.csr.2017.02.003","url":"http://dx.doi.org/10.1016/j.csr.2017.02.003","publisher":"Elsevier BV","authors":"Warner John C., Schwab William C., List Jeffrey H., Safak Ilgar, Liste Maria, Baldwin Wayne","journalName":"Continental Shelf Research","publicationDate":"4/2017"},"contributors":{"authors":[{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"List, Jeffrey H. 0000-0001-8594-2491 jlist@usgs.gov","orcid":"https://orcid.org/0000-0001-8594-2491","contributorId":174581,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Safak, Ilgar 0000-0001-7675-0770 isafak@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-0770","contributorId":5522,"corporation":false,"usgs":true,"family":"Safak","given":"Ilgar","email":"isafak@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liste, Maria","contributorId":190581,"corporation":false,"usgs":false,"family":"Liste","given":"Maria","email":"","affiliations":[],"preferred":false,"id":673851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baldwin, Wayne E. 0000-0001-5886-0917 wbaldwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5886-0917","contributorId":1321,"corporation":false,"usgs":true,"family":"Baldwin","given":"Wayne","email":"wbaldwin@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673852,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192160,"text":"70192160 - 2017 - Automated cropland mapping of continental Africa using Google Earth Engine cloud computing","interactions":[],"lastModifiedDate":"2017-10-23T13:54:01","indexId":"70192160","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Automated cropland mapping of continental Africa using Google Earth Engine cloud computing","docAbstract":"The automation of agricultural mapping using satellite-derived remotely sensed data remains a challenge in Africa because of the heterogeneous and fragmental landscape, complex crop cycles, and limited access to local knowledge. Currently, consistent, continent-wide routine cropland mapping of Africa does not exist, with most studies focused either on certain portions of the continent or at most a one-time effort at mapping the continent at coarse resolution remote sensing. In this research, we addressed these limitations by applying an automated cropland mapping algorithm (ACMA) that captures extensive knowledge on the croplands of Africa available through: (a) ground-based training samples, (b) very high (sub-meter to five-meter) resolution imagery (VHRI), and (c) local knowledge captured during field visits and/or sourced from country reports and literature. The study used 16-day time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) composited data at 250-m resolution for the entire African continent. Based on these data, the study first produced accurate reference cropland layers or RCLs (cropland extent/areas, irrigation versus rainfed, cropping intensities, crop dominance, and croplands versus cropland fallows) for the year 2014 that provided an overall accuracy of around 90% for crop extent in different agro-ecological zones (AEZs). The RCLs for the year 2014 (RCL2014) were then used in the development of the ACMA algorithm to create ACMA-derived cropland layers for 2014 (ACL2014). ACL2014 when compared pixel-by-pixel with the RCL2014 had an overall similarity greater than 95%. Based on the ACL2014, the African continent had 296 Mha of net cropland areas (260 Mha cultivated plus 36 Mha fallows) and 330 Mha of gross cropland areas. Of the 260 Mha of net cropland areas cultivated during 2014, 90.6% (236 Mha) was rainfed and just 9.4% (24 Mha) was irrigated. Africa has about 15% of the world’s population, but only about 6% of world’s irrigation. Net cropland area distribution was 95 Mha during season 1, 117 Mha during season 2, and 84 Mha continuous. About 58% of the rainfed and 39% of the irrigated were single crops (net cropland area without cropland fallows) cropped during either season 1 (January-May) or season 2 (June-September). The ACMA algorithm was deployed on Google Earth Engine (GEE) cloud computing platform and applied on MODIS time-series data from 2003 through 2014 to obtain ACMA-derived cropland layers for these years (ACL2003 to ACL2014). The results indicated that over these twelve years, on average: (a) croplands increased by 1 Mha/yr, and (b) cropland fallows decreased by 1 Mha/year. Cropland areas computed from ACL2014 for the 55 African countries were largely underestimated when compared with an independent source of census-based cropland data, with a root-mean-square error (RMSE) of 3.5 Mha. ACMA demonstrated the ability to hind-cast (past years), now-cast (present year), and forecast (future years) cropland products using MODIS 250-m time-series data rapidly, but currently, insufficient reference data exist to rigorously report trends from these results.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2017.01.019","usgsCitation":"Xiong, J., Thenkabail, P.S., Gumma, M., Teluguntla, P.G., Poehnelt, J., Congalton, R.G., Yadav, K., and Thau, D., 2017, Automated cropland mapping of continental Africa using Google Earth Engine cloud computing: ISPRS Journal of Photogrammetry and Remote Sensing, v. 126, p. 225-244, https://doi.org/10.1016/j.isprsjprs.2017.01.019.","productDescription":"20 p.","startPage":"225","endPage":"244","ipdsId":"IP-081308","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469973,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.isprsjprs.2017.01.019","text":"Publisher Index Page"},{"id":347130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -18.80859375,\n -36.03133177633187\n ],\n [\n 52.03125,\n -36.03133177633187\n ],\n [\n 52.03125,\n 37.579412513438385\n ],\n [\n -18.80859375,\n 37.579412513438385\n ],\n [\n -18.80859375,\n -36.03133177633187\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59eeffa9e4b0220bbd988fa9","contributors":{"authors":[{"text":"Xiong, Jun 0000-0002-2320-0780 jxiong@usgs.gov","orcid":"https://orcid.org/0000-0002-2320-0780","contributorId":5276,"corporation":false,"usgs":true,"family":"Xiong","given":"Jun","email":"jxiong@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":714479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":714480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":714481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":714482,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poehnelt, Justin 0000-0001-5914-4269","orcid":"https://orcid.org/0000-0001-5914-4269","contributorId":192328,"corporation":false,"usgs":false,"family":"Poehnelt","given":"Justin","email":"","affiliations":[],"preferred":false,"id":714483,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Congalton, Russell G.","contributorId":138718,"corporation":false,"usgs":false,"family":"Congalton","given":"Russell","email":"","middleInitial":"G.","affiliations":[{"id":12507,"text":"Department of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA","active":true,"usgs":false}],"preferred":false,"id":714484,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yadav, Kamini","contributorId":138720,"corporation":false,"usgs":false,"family":"Yadav","given":"Kamini","affiliations":[{"id":12507,"text":"Department of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA","active":true,"usgs":false}],"preferred":false,"id":714485,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thau, David","contributorId":103581,"corporation":false,"usgs":true,"family":"Thau","given":"David","email":"","affiliations":[],"preferred":false,"id":714878,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70183250,"text":"sir20175016 - 2017 - Occurrence of cyanobacteria, microcystin, and taste-and-odor compounds in Cheney Reservoir, Kansas, 2001-16","interactions":[],"lastModifiedDate":"2025-07-24T13:03:34.594363","indexId":"sir20175016","displayToPublicDate":"2017-03-31T11:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5016","title":"Occurrence of cyanobacteria, microcystin, and taste-and-odor compounds in Cheney Reservoir, Kansas, 2001-16","docAbstract":"Cheney Reservoir, located in south-central Kansas, is one of the primary drinking-water supplies for the city of Wichita and an important recreational resource. Since 1990, cyanobacterial blooms have been present occasionally in Cheney Reservoir, resulting in increased treatment costs and decreased recreational use. Cyanobacteria, the cyanotoxin microcystin, and the taste-and-odor compounds geosmin and 2-methylisoborneol have been measured in Cheney Reservoir by the U.S. Geological Survey, in cooperation with the city of Wichita, for about 16 years. The purpose of this report is to describe the occurrence of cyanobacteria, microcystin, and taste-and-odor compounds in Cheney Reservoir during May 2001 through June 2016 and to update previously published logistic regression models that used continuous water-quality data to estimate the probability of microcystin and geosmin occurrence above relevant thresholds.
Cyanobacteria, microcystin, and geosmin were detected in about 84, 52, and 31 percent of samples collected in Cheney Reservoir during May 2001 through June 2016, respectively. 2-methylisoborneol was less common, detected in only 3 percent of samples. Microcystin and geosmin concentrations exceeded advisory values of concern more frequently than cyanobacterial abundance; therefore, cyanobacteria are not a good indicator of the presence of these taste-and-odor compounds in Cheney Reservoir. Broad seasonal patterns in cyanobacteria and microcystin were evident, though abundance and concentration varied by orders of magnitude across years. Cyanobacterial abundances generally peaked in late summer or early fall (August through October), and smaller peaks were observed in winter (January through February). In a typical year, microcystin was first detected in June or July, increased to its seasonal maxima in the summer (July through September), and then decreased. Seasonal patterns in geosmin were less consistent than cyanobacteria and microcystin, but geosmin typically had a small peak during winter (January through March) during most years and a large peak during summer (July through September) during some years. Though the relation between cyanobacterial abundance and microcystin and geosmin concentrations was positive, overall correlations were weak, likely because production is strain-specific and cyanobacterial strain composition may vary substantially over time. Microcystin often was present without taste-and-odor compounds. By comparison, where taste-and-odor compounds were present, microcystin frequently was detected. Taste-and-odor compounds, therefore, may be used as indicators that microcystin may be present; however, microcystin was present without taste-and-odor compounds, so taste or odor alone does not provide sufficient warning to ensure human-health protection.
Logistic regression models that estimate the probability of microcystin occurrence at concentrations greater than or equal to 0.1 micrograms per liter and geosmin occurrence at concentrations greater than or equal to 5 nanograms per liter were developed. Models were developed using the complete dataset (January 2003 through June 2016 for microcystin [14-year dataset]; May 2001 through June 2016 for geosmin [16-year dataset]) and an abbreviated 4-year dataset (January 2013 through June 2016 for microcystin and geosmin). Performance of the newly developed models was compared with previously published models that were developed using data collected during May 2001 through December 2009. A seasonal component and chlorophyll fluorescence (a surrogate for algal biomass) were the explanatory variables for microcystin occurrence at concentrations greater than or equal to 0.1 micrograms per liter in all models. All models were relatively robust, though the previously published and 14-year models performed better over time; however, as a tool to estimate microcystin occurrence at concentrations greater than or equal to 0.1 micrograms per liter in a real-time notification system near the Cheney Dam, the 4-year model is most representative of recent (2013 through 2016) conditions. All models for geosmin occurrence at concentrations greater than or equal to 5 nanograms per liter had different explanatory variables and model forms. The previously published and 16-year models were not robust over time, likely because of changing environmental conditions and seasonal patterns in geosmin occurrence. By comparison, the abbreviated 4-year model may be a useful tool to estimate geosmin occurrence at concentrations greater than or equal to 5 nanograms per liter in a real-time notification system near the Cheney Dam. The better performance of the abbreviated 4-year geosmin model during 2013 through 2016 relative to the previously published and 16-year models demonstrates the need for continuous reevaluation of models estimating the probability of occurrence.
Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Since 1996, the U.S. Geological Survey (USGS), in cooperation with the City of Wichita, has done studies in the Cheney Reservoir watershed to understand environmental effects on water-quality conditions. Early studies (1996–2001) determined subwatershed sources of contaminants, nutrient and sediment loading to Cheney Reservoir, changes in reservoir sediment quality over time, and watershed sources of phosphorus. Later studies (2001–present) focused on nutrient and sediment concentrations and mass transport from the watershed; the presence of cyanobacteria, cyanotoxins, and taste-and-odor compounds in the reservoir; and development of regression models for real-time computations of water-quality constituents of interest that may affect drinking-water treatment. This fact sheet summarizes key results from studies done by the USGS during 1996–2016 in the Cheney Reservoir watershed and Cheney Reservoir.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173019","collaboration":"Prepared in cooperation with the City of Wichita, Kansas","usgsCitation":"Graham, J.L., Foster, G.M., and Kramer, A.R., 2017, Twenty years of water-quality studies in the Cheney Reservoir watershed, Kansas, 1996–2016: U.S. Geological Survey Fact Sheet 2017–3019, 4 p., https://doi.org/10.3133/fs20173019.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-080288","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":338840,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3019/fs20173019.pdf","text":"Fact Sheet","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3019"},{"id":338839,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3019/coverthb.jpg"},{"id":338841,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175016","text":"SIR 2017–5016","description":"SIR 2017–5016","linkHelpText":"Occurrence of cyanobacteria, microcystin, and taste-and-odor compounds in Cheney Reservoir, Kansas, 2001-16"}],"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 -97.74,\n 38.1\n ],\n [\n -99.25,\n 38.1\n ],\n [\n -99.25,\n 37.5\n ],\n [\n -97.74,\n 37.5\n ],\n [\n -97.74,\n 38.1\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
This report summarizes the results of three-dimensional (3-D) resistivity inversion simulations that were performed to account for local 3-D distortion of the electric field in the presence of 3-D regional structure, without any a priori information on the actual 3-D distribution of the known subsurface geology. The methodology used a 3-D geologic model to create a 3-D resistivity forward (“known”) model that depicted the subsurface resistivity structure expected for the input geologic configuration. The calculated magnetotelluric response of the modeled resistivity structure was assumed to represent observed magnetotelluric data and was subsequently used as input into a 3-D resistivity inverse model that used an iterative 3-D algorithm to estimate 3-D distortions without any a priori geologic information. A publicly available inversion code, WSINV3DMT, was used for all of the simulated inversions, initially using the default parameters, and subsequently using adjusted inversion parameters. A semiautomatic approach of accounting for the static shift using various selections of the highest frequencies and initial models was also tested. The resulting 3-D resistivity inversion simulation was compared to the “known” model and the results evaluated. The inversion approach that produced the lowest misfit to the various local 3-D distortions was an inversion that employed an initial model volume resistivity that was nearest to the maximum resistivities in the near-surface layer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171007","usgsCitation":"Rodriguez, B.D., 2017, Semiautomatic approaches to account for 3-D distortion of the electric field from local, near-surface structures in 3-D resistivity inversions of 3-D regional magnetotelluric data: U.S. Geological Survey Open-File Report 2017–1007, 25 p., https://doi.org/10.3133/ofr20171007.","productDescription":"iii, 25 p.","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-068212","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":338862,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1007/coverthb.jpg"},{"id":338863,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1007/ofr20171007.pdf","text":"Report","size":"20.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1007"}],"contact":"Director, Crustal Geophysics and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 964
Denver, CO 80225
We present a shoreline change model for coastal hazard assessment and management planning. The model, CoSMoS-COAST (Coastal One-line Assimilated Simulation Tool), is a transect-based, one-line model that predicts short-term and long-term shoreline response to climate change in the 21st century. The proposed model represents a novel, modular synthesis of process-based models of coastline evolution due to longshore and cross-shore transport by waves and sea-level rise. Additionally, the model uses an extended Kalman filter for data assimilation of historical shoreline positions to improve estimates of model parameters and thereby improve confidence in long-term predictions. We apply CoSMoS-COAST to simulate sandy shoreline evolution along 500 km of coastline in Southern California, which hosts complex mixtures of beach settings variably backed by dunes, bluffs, cliffs, estuaries, river mouths, and urban infrastructure, providing applicability of the model to virtually any coastal setting. Aided by data assimilation, the model is able to reproduce the observed signal of seasonal shoreline change for the hindcast period of 1995-2010, showing excellent agreement between modeled and observed beach states. The skill of the model during the hindcast period improves confidence in the model's predictive capability when applied to the forecast period (2010-2100) driven by GCM-projected wave and sea-level conditions. Predictions of shoreline change with limited human intervention indicate that 31% to 67% of Southern California beaches may become completely eroded by 2100 under sea-level rise scenarios of 0.93 to 2.0 m.
","language":"English","publisher":"Wiley","doi":"10.1002/2016JF004065","usgsCitation":"Vitousek, S., Barnard, P., Limber, P.W., Erikson, L.H., and Cole, B., 2017, A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change: Journal of Geophysical Research F: Earth Surface, v. 122, no. 4, p. 782-806, https://doi.org/10.1002/2016JF004065.","productDescription":"25 p.","startPage":"782","endPage":"806","ipdsId":"IP-079262","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":338922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"122","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-06","publicationStatus":"PW","scienceBaseUri":"58df6abfe4b02ff32c6aea27","contributors":{"authors":[{"text":"Vitousek, Sean","contributorId":190192,"corporation":false,"usgs":false,"family":"Vitousek","given":"Sean","affiliations":[],"preferred":false,"id":687761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":687760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":687762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":687763,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, Blake","contributorId":190193,"corporation":false,"usgs":false,"family":"Cole","given":"Blake","email":"","affiliations":[],"preferred":false,"id":687764,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186030,"text":"70186030 - 2017 - Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II","interactions":[],"lastModifiedDate":"2017-03-30T11:53:37","indexId":"70186030","displayToPublicDate":"2017-03-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II","docAbstract":"Browsing ungulates alter forest productivity and vegetation succession through selective foraging on species that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit manner, we developed a Browse Extension that simulates the effects of browsing ungulates on the growth and survival of plant species cohorts within the LANDIS-II spatially dynamic forest landscape simulation model framework. We demonstrate the capabilities of the new extension and explore the spatial effects of ungulates on forest composition and dynamics using two case studies. The first case study examined the long-term effects of persistently high white-tailed deer browsing rates in the northern hardwood forests of the Allegheny National Forest, USA. In the second case study, we incorporated a dynamic ungulate population model to simulate interactions between the moose population and boreal forest landscape of Isle Royale National Park, USA. In both model applications, browsing reduced total aboveground live biomass and caused shifts in forest composition. Simulations that included effects of browsing resulted in successional patterns that were more similar to those observed in the study regions compared to simulations that did not incorporate browsing effects. Further, model estimates of moose population density and available forage biomass were similar to previously published field estimates at Isle Royale and in other moose-boreal forest systems. Our simulations suggest that neglecting effects of browsing when modeling forest succession in ecosystems known to be influenced by ungulates may result in flawed predictions of aboveground biomass and tree species composition.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2017.01.014","usgsCitation":"De Jager, N.R., Drohan, P.J., Miranda, B.M., Sturtevant, B.R., Stout, S.L., Royo, A., Gustafson, E.J., and Romanski, M.C., 2017, Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II: Ecological Modelling, v. 350, p. 11-29, https://doi.org/10.1016/j.ecolmodel.2017.01.014.","productDescription":"19 p.","startPage":"11","endPage":"29","ipdsId":"IP-076795","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":469980,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2017.01.014","text":"Publisher Index Page"},{"id":338815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"350","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194be4b02ff32c699c7f","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drohan, Patrick J.","contributorId":190141,"corporation":false,"usgs":false,"family":"Drohan","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":687395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miranda, Brian M.","contributorId":190142,"corporation":false,"usgs":false,"family":"Miranda","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":687396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sturtevant, Brian R.","contributorId":190143,"corporation":false,"usgs":false,"family":"Sturtevant","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":687397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stout, Susan L.","contributorId":190144,"corporation":false,"usgs":false,"family":"Stout","given":"Susan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":687398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Royo, Alejandro","contributorId":190145,"corporation":false,"usgs":false,"family":"Royo","given":"Alejandro","email":"","affiliations":[],"preferred":false,"id":687399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gustafson, Eric J.","contributorId":190146,"corporation":false,"usgs":false,"family":"Gustafson","given":"Eric","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":687400,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Romanski, Mark C.","contributorId":190147,"corporation":false,"usgs":false,"family":"Romanski","given":"Mark","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":687401,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70186023,"text":"70186023 - 2017 - Lethal and sub-lethal responses of native freshwater mussels exposed to granular Bayluscide®, a sea lamprey larvicide","interactions":[],"lastModifiedDate":"2017-03-30T12:35:48","indexId":"70186023","displayToPublicDate":"2017-03-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Lethal and sub-lethal responses of native freshwater mussels exposed to granular Bayluscide®, a sea lamprey larvicide","docAbstract":"The invasive sea lamprey (Petromyzon marinus) poses a substantial threat to fish communities in the Great Lakes. Efforts to control sea lamprey populations typically involve treating tributary streams with lampricides on a recurring cycle. The presence of a substantial population of larval sea lampreys in the aquatic corridor between Lakes Huron and Erie prompted managers to propose a treatment using the granular formulation of Bayluscide® that targets larval sea lampreys that reside in sediments. However, these treatments could cause adverse effects on native freshwater mussels—imperiled animals that also reside in sediments. We estimated the risk of mortality and sub-lethal effects among eight species of adult and sub-adult mussels exposed to Bayluscide® for durations up to 8 h to mimic field applications. Mortality was appreciable in some species, especially in sub-adults (range, 23–51%). The lethal and sub-lethal effects were positively associated with the duration of exposure in most species and life stage combinations. Estimates of the median time of exposure that resulted in lethal and sub-lethal effects suggest that sub-adults were often affected by Bayluscide® earlier than adults. Siphoning activity and burrowing position of mussels during exposure may have moderated the uptake of Bayluscide® and may have influenced lethal and sub-lethal responses. Given that the various species and life stages were differentially affected, it will be difficult to predict the effects of Bayluscide® treatments on mussels.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2016.12.010","usgsCitation":"Newton, T., Boogaard, M.A., Gray, B.R., Hubert, T.D., and Schloesser, N.A., 2017, Lethal and sub-lethal responses of native freshwater mussels exposed to granular Bayluscide®, a sea lamprey larvicide: Journal of Great Lakes Research, v. 43, no. 2, p. 370-378, https://doi.org/10.1016/j.jglr.2016.12.010.","productDescription":"9 p.","startPage":"370","endPage":"378","ipdsId":"IP-079287","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":338824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194ce4b02ff32c699c85","contributors":{"authors":[{"text":"Newton, Teresa 0000-0001-9351-5852 tnewton@usgs.gov","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":150098,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa","email":"tnewton@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boogaard, Michael A. 0000-0002-5192-8437 mboogaard@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-8437","contributorId":865,"corporation":false,"usgs":true,"family":"Boogaard","given":"Michael","email":"mboogaard@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hubert, Terrance D. 0000-0001-9712-1738 thubert@usgs.gov","orcid":"https://orcid.org/0000-0001-9712-1738","contributorId":3036,"corporation":false,"usgs":true,"family":"Hubert","given":"Terrance","email":"thubert@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schloesser, Nicholas A. 0000-0002-3815-5302 nschloesser@usgs.gov","orcid":"https://orcid.org/0000-0002-3815-5302","contributorId":169551,"corporation":false,"usgs":false,"family":"Schloesser","given":"Nicholas","email":"nschloesser@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687375,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186025,"text":"70186025 - 2017 - Full annual cycle climate change vulnerability assessment for migratory birds","interactions":[],"lastModifiedDate":"2017-03-30T12:19:21","indexId":"70186025","displayToPublicDate":"2017-03-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Full annual cycle climate change vulnerability assessment for migratory birds","docAbstract":"Climate change is a serious challenge faced by all plant and animal species. Climate change vulnerability assessments (CCVAs) are one method to assess risk and are increasingly used as a tool to inform management plans. Migratory animals move across regions and continents during their annual cycles where they are exposed to diverse climatic conditions. Climate change during any period and in any region of the annual cycle could influence survival, reproduction, or the cues used to optimize timing of migration. Therefore, CCVAs for migratory animals best estimate risk when they include climate exposure during the entire annual cycle. We developed a CCVA incorporating the full annual cycle and applied this method to 46 species of migratory birds breeding in the Upper Midwest and Great Lakes (UMGL) region of the United States. Our methodology included background risk, climate change exposure × climate sensitivity, adaptive capacity to climate change, and indirect effects of climate change. We compiled information about migratory connectivity between breeding and stationary non-breeding areas using literature searches and U.S. Geological Survey banding and re-encounter data. Climate change exposure (temperature and moisture) was assessed using UMGL breeding season climate and winter climate from non-breeding regions for each species. Where possible, we focused on non-breeding regions known to be linked through migratory connectivity. We ranked 10 species as highly vulnerable to climate change and two as having low vulnerability. The remaining 34 species were ranked as moderately vulnerable. In general, including non-breeding data provided more robust results that were highly individualistic by species. Two species were found to be highly vulnerable throughout their annual cycle. Projected drying will have the greatest effect during the non-breeding season for species overwintering in Mexico and the Caribbean. Projected temperature increases will have the greatest effect during the breeding season in UMGL as well as during the non-breeding season for species overwintering in South America. We provide a model for adaptive management of migratory animals in the face of projected climate change, including identification of priority species, research needs, and regions within non-breeding ranges for potential conservation partnerships.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.1565","usgsCitation":"Culp, L.A., Cohen, E.B., Scarpignato, A.L., Thogmartin, W.E., and Marra, P.P., 2017, Full annual cycle climate change vulnerability assessment for migratory birds: Ecological Applications, v. 8, no. 3, e01565; 22 p., https://doi.org/10.1002/ecs2.1565.","productDescription":"e01565; 22 p.","ipdsId":"IP-078803","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":461685,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1565","text":"Publisher Index Page"},{"id":338822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"8","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-06","publicationStatus":"PW","scienceBaseUri":"58de194ce4b02ff32c699c83","contributors":{"authors":[{"text":"Culp, Leah A.","contributorId":190138,"corporation":false,"usgs":false,"family":"Culp","given":"Leah","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":687378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohen, Emily B.","contributorId":57774,"corporation":false,"usgs":false,"family":"Cohen","given":"Emily","email":"","middleInitial":"B.","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":687379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scarpignato, Amy L.","contributorId":190139,"corporation":false,"usgs":false,"family":"Scarpignato","given":"Amy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":687380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687377,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marra, Peter P.","contributorId":190140,"corporation":false,"usgs":false,"family":"Marra","given":"Peter","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":687381,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70185601,"text":"ofr20171034 - 2017 - Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production","interactions":[],"lastModifiedDate":"2017-03-30T12:15:26","indexId":"ofr20171034","displayToPublicDate":"2017-03-29T17:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1034","title":"Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production","docAbstract":"The use of Landsat satellite imagery for global agricultural monitoring began almost immediately after the launch of Landsat 1 in 1972, making agricultural monitoring one of the longest-standing operational applications for the Landsat program. More recently, Landsat imagery has been used in domestic agricultural applications as an input for field-level production management. The enactment of the U.S. Geological Survey’s free and open data policy in 2008 and the launch of Landsat 8 in 2013 have both influenced agricultural applications. This report presents two primary sets of case studies on the applications and benefits of Landsat imagery use in agriculture. The first set examines several operational applications within the U.S. Department of Agriculture (USDA) and the second focuses on private sector applications for agronomic management.
Information on the USDA applications is provided in the U.S. Department of Agriculture Uses of Landsat Imagery for Global and Domestic Agricultural Monitoring section of the report in the following subsections:
Private sector applications using Landsat imagery for agricultural management are discussed in the Landsat Imagery Use and Benefits in Field-Level Agricultural Production Management section of the report in the following subsections:
Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The endangered manatee Trichechus manatus is one of few large grazers in seagrass systems. To assess the long-term impacts of repeated grazing on seagrasses, we selected a study site within Kennedy Space Center in the northern Banana River, Brevard County, Florida, that was typically grazed by large numbers of manatees in spring. Two 13x13 m manatee exclosures and 2 paired open plots of equal size were established at the study site in October 1990. Shoot counts, biomass, and species composition of the co-dominant seagrass species, Syringodium filiforme and Halodule wrightii, were sampled 3 times per year in all 4 plots between October 1990 and October 1994. We used a Bayesian modelling approach, accounting for the influence of depth, to detect treatment (exclosed vs. open) effects. S. filiforme shoot counts, total biomass, and frequency of occurrence significantly increased in the exclosures. By July 1993, mean biomass values in the exclosures (167 g dry wt m-2) greatly exceeded those in the open plots (28 g dry wt m-2). H. wrightii decreased in the exclosures by 1994. Initially, both S. filiforme and H. wrightii responded positively to release from manatee grazing pressure. As S. filiforme continued to become denser in the exclosures, it gradually replaced H. wrightii. Our findings may be helpful to biologists and managers interested in predicting seagrass recovery and manatee carrying capacity of repeatedly grazed seagrass beds in areas of special significance to manatees and seagrass conservation.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps11986","collaboration":"InoMedic Health Applications, Inc;National Oceanic and Atmospheric Administrationmahon","usgsCitation":"Lefebvre, L.W., Provancha, J.A., Slone, D., and Kenworthy, W.J., 2017, Manatee grazing impacts on a mixed species seagrass bed: Marine Ecology Progress Series, v. 564, p. 29-45, https://doi.org/10.3354/meps11986.","productDescription":"17 p.","startPage":"29","endPage":"45","ipdsId":"IP-072284","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":338694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"564","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58dcc7d1e4b02ff32c68565d","contributors":{"authors":[{"text":"Lefebvre, Lynn W. 0000-0002-4464-6263 llefebvre@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6263","contributorId":1614,"corporation":false,"usgs":true,"family":"Lefebvre","given":"Lynn","email":"llefebvre@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":686787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Provancha, Jane A.","contributorId":190011,"corporation":false,"usgs":false,"family":"Provancha","given":"Jane","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":686788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slone, Daniel H. 0000-0002-9903-9727 dslone@usgs.gov","orcid":"https://orcid.org/0000-0002-9903-9727","contributorId":1749,"corporation":false,"usgs":true,"family":"Slone","given":"Daniel H.","email":"dslone@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":686786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kenworthy, W. Judson","contributorId":190012,"corporation":false,"usgs":false,"family":"Kenworthy","given":"W.","email":"","middleInitial":"Judson","affiliations":[],"preferred":false,"id":686789,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70185740,"text":"70185740 - 2017 - Weather radar data correlate to hail-induced mortality in grassland birds","interactions":[],"lastModifiedDate":"2017-07-03T09:44:29","indexId":"70185740","displayToPublicDate":"2017-03-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Weather radar data correlate to hail-induced mortality in grassland birds","docAbstract":"Small-bodied terrestrial animals such as songbirds (Order Passeriformes) are especially vulnerable to hail-induced mortality; yet, hail events are challenging to predict, and they often occur in locations where populations are not being studied. Focusing on nesting grassland songbirds, we demonstrate a novel approach to estimate hail-induced mortality. We quantify the relationship between the probability of nests destroyed by hail and measured Level-III Next Generation Radar (NEXRAD) data, including atmospheric base reflectivity, maximum estimated size of hail and maximum estimated azimuthal wind shear. On 22 June 2014, a hailstorm in northern Colorado destroyed 102 out of 203 known nests within our research site. Lark bunting (Calamospiza melanocorys) nests comprised most of the sample (n = 186). Destroyed nests were more likely to be found in areas of higher storm intensity, and distributions of NEXRAD variables differed between failed and surviving nests. For 133 ground nests where nest-site vegetation was measured, we examined the ameliorative influence of woody vegetation, nest cover and vegetation density by comparing results for 13 different logistic regression models incorporating the independent and additive effects of weather and vegetation variables. The most parsimonious model used only the interactive effect of hail size and wind shear to predict the probability of nest survival, and the data provided no support for any of the models without this predictor. We conclude that vegetation structure may not mitigate mortality from severe hailstorms and that weather radar products can be used remotely to estimate potential for hail mortality of nesting grassland birds. These insights will improve the efficacy of grassland bird population models under predicted climate change scenarios.
","language":"English","publisher":"Wiley","doi":"10.1002/rse2.41","usgsCitation":"Carver, A., Ross, J.D., Augustine, D., Skagen, S.K., Dwyer, A.M., Tomback, D.F., and Wunder, M., 2017, Weather radar data correlate to hail-induced mortality in grassland birds: Remote Sensing in Ecology and Conservation, v. 3, no. 2, p. 90-101, https://doi.org/10.1002/rse2.41.","productDescription":"12 p.","startPage":"90","endPage":"101","ipdsId":"IP-073446","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469986,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.41","text":"Publisher Index Page"},{"id":338545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-24","publicationStatus":"PW","scienceBaseUri":"58dcc7d3e4b02ff32c685665","contributors":{"authors":[{"text":"Carver, Amber","contributorId":189956,"corporation":false,"usgs":false,"family":"Carver","given":"Amber","email":"","affiliations":[],"preferred":false,"id":686605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Jeremy D.","contributorId":189958,"corporation":false,"usgs":false,"family":"Ross","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":686608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Augustine, David J.","contributorId":36849,"corporation":false,"usgs":true,"family":"Augustine","given":"David J.","affiliations":[],"preferred":false,"id":686606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skagen, Susan K. 0000-0002-6744-1244 skagens@usgs.gov","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":2009,"corporation":false,"usgs":true,"family":"Skagen","given":"Susan","email":"skagens@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":686604,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dwyer, Angela M.","contributorId":189959,"corporation":false,"usgs":false,"family":"Dwyer","given":"Angela","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":686609,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tomback, Diana F.","contributorId":189960,"corporation":false,"usgs":false,"family":"Tomback","given":"Diana","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":686610,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wunder, Michael B.","contributorId":80599,"corporation":false,"usgs":false,"family":"Wunder","given":"Michael B.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":686607,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70181024,"text":"ofr20171016 - 2017 - Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City","interactions":[],"lastModifiedDate":"2017-03-29T15:19:26","indexId":"ofr20171016","displayToPublicDate":"2017-03-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1016","title":"Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City","docAbstract":"The salt marshes of Jamaica Bay, managed by the New York City Department of Parks & Recreation and the Gateway National Recreation Area of the National Park Service, serve as a recreational outlet for New York City residents, mitigate flooding, and provide habitat for critical wildlife species. Hurricanes and extra-tropical storms have been recognized as one of the critical drivers of coastal wetland morphology due to their effects on hydrodynamics and sediment transport, deposition, and erosion processes. However, the magnitude and mechanisms of hurricane effects on sediment dynamics and associated coastal wetland morphology in the northeastern United States are poorly understood. In this study, the depth-averaged version of the Delft3D modeling suite, integrated with field measurements, was utilized to examine the effects of Hurricane Sandy and future potential hurricanes on salt marsh morphology in Jamaica Bay, New York City. Hurricane Sandy-induced wind, waves, storm surge, water circulation, sediment transport, deposition, and erosion were simulated by using the modeling system in which vegetation effects on flow resistance, surge reduction, wave attenuation, and sedimentation were also incorporated. Observed marsh elevation change and accretion from a rod surface elevation table and feldspar marker horizons and cesium-137- and lead-210-derived long-term accretion rates were used to calibrate and validate the wind-waves-surge-sediment transport-morphology coupled model.
The model results (storm surge, waves, and marsh deposition and erosion) agreed well with field measurements. The validated modeling system was then used to detect salt marsh morphological change due to Hurricane Sandy across the entire Jamaica Bay over the short-term (for example, 4 days and 1 year) and long-term (for example, 5 and 10 years). Because Hurricanes Sandy (2012) and Irene (2011) were two large and destructive tropical cyclones which hit the northeast coast, the validated coupled model was run to predict the effects of Sandy-like and Irene-like hurricanes with different storm tracks and wind intensities on wetland morphology in Jamaica Bay. Model results indicate that, in Jamaica Bay salt marshes, the morphological changes (greater than 5 millimeters [mm] determined by the long-term marsh accretion rate) caused by Hurricane Sandy were complex and spatially heterogeneous. Most of the erosion (5–40 mm) and deposition (5–30 mm) were mainly characterized by fine sand for channels and bay bottoms and by mud for marsh areas. Hurricane Sandy-generated deposition and erosion were generated locally. The storm-induced net sediment input through Rockaway Inlet was only about 1 percent of the total amount of the sediment reworked by the hurricane. Salt marshes inside the western part of the bay showed erosion overall while marshes inside the eastern part showed deposition from Hurricane Sandy. Model results indicated that most of the marshes could recover from Hurricane Sandy-induced erosion after 1 year and demonstrated continued marsh accretion after the hurricane over the course of long simulation periods although the effect (accretion) was diminished. Local waves and currents generated by Hurricane Sandy appeared to play a critical role in sediment transport and associated wetland morphological change in Jamaica Bay. Hypothetical hurricanes, depending on their track and intensity, cause variable responses in spatial patterns of sediment deposition and erosion compared to simulations without the hurricane. In general, hurricanes passing west of the Jamaica Bay estuary appear to be more destructive to the salt marshes than those passing the east. Consequently, marshes inside the western part of the bay were likely to be more vulnerable to hurricanes than marshes inside the eastern part of the bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171016","usgsCitation":"Wang, H., Chen, Q., Hu, K., Snedden, G.A., Hartig, E.K., Couvillion, B.R., Johnson, C.L., and Orton, P.M., 2017, Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City: U.S. Geological Survey Open-File Report 2017–1016, 43 p., https://doi.org/10.3133/ofr20171016.","productDescription":"vii, 43 p.","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-079827","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":338515,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1016/coverthb.jpg"},{"id":338516,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1016/ofr20171016.pdf","text":"Report","size":"30.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1016"}],"country":"United States","state":"New York","city":"New York City","otherGeospatial":"Jamaica Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.95687103271484,\n 40.539112438263516\n ],\n [\n -73.72684478759766,\n 40.539112438263516\n ],\n [\n -73.72684478759766,\n 40.658503716866974\n ],\n [\n -73.95687103271484,\n 40.658503716866974\n ],\n [\n -73.95687103271484,\n 40.539112438263516\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
","tableOfContents":"Borehole geophysical logs and thermal imaging data were collected by the U.S. Geological Survey near the Hemphill Road TCE (trichloroethylene) National Priorities List Superfund site near Gastonia, North Carolina, during August 2014 through February 2015. In an effort to assist the U.S. Environmental Protection Agency in the development of a conceptual groundwater model for the assessment of current contaminant distribution and future migration of contaminants, surface geological mapping and borehole geophysical log and thermal imaging data collection, which included the delineation of more than 600 subsurface features (primarily fracture orientations), was completed in five open borehole wells and two private supply bedrock wells. In addition, areas of possible groundwater discharge within a nearby creek downgradient of the study site were determined based on temperature differences between the stream and bank seepage using thermal imagery.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171017","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Region 4 Superfund Section","usgsCitation":"Antolino, D.J., and Chapman, M.J., 2017, Geophysical logging and thermal imaging near the Hemphill Road TCE National Priorities List Superfund site near Gastonia, North Carolina (ver. 1.1, March 2017): U.S. Geological Survey Open-File Report 2017–1017, 47 p., https://doi.org/10.3133/ofr20171017.","productDescription":"Report: v, 47 p.; Data Release","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079978","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":337458,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1017/coverthb2.jpg"},{"id":337459,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1017/ofr20171017.pdf","text":"Report","size":"19.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1017"},{"id":337460,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6NPM","text":"USGS data release ","description":"USGS data release","linkHelpText":"Geophysical logging and thermal imaging at the Hemphill Road TCE NPL Superfund site near Gastonia, North Carolina"},{"id":338827,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1017/versionHist.txt","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"North Carolina","county":"Gaston County","city":"Gastonia","otherGeospatial":"Hemphill Road trichloroethylene National Priorities List Superfund site","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-81.4535,35.4201],[-81.2581,35.4132],[-81.0069,35.4038],[-80.9549,35.4006],[-80.9554,35.3925],[-80.9632,35.3901],[-80.9761,35.3828],[-80.9806,35.3823],[-80.9846,35.3822],[-80.9868,35.38],[-80.9844,35.3695],[-80.9776,35.3646],[-80.9742,35.3642],[-80.9697,35.3669],[-80.9669,35.3688],[-80.9647,35.3738],[-80.9625,35.3756],[-80.9597,35.3756],[-80.9563,35.3738],[-80.9505,35.3675],[-80.9432,35.3658],[-80.9296,35.3636],[-80.9268,35.3627],[-80.9285,35.3614],[-80.9374,35.3572],[-80.9442,35.3521],[-80.9537,35.3521],[-80.9593,35.3489],[-80.9656,35.3506],[-80.9706,35.3501],[-80.9818,35.3446],[-80.984,35.3373],[-80.9823,35.3341],[-80.9805,35.3287],[-80.9844,35.3237],[-80.9894,35.3205],[-80.9938,35.3132],[-80.9961,35.3113],[-81.0022,35.3045],[-81.0033,35.3017],[-81.0105,35.2944],[-81.0133,35.293],[-81.0143,35.2876],[-81.0152,35.2685],[-81.0139,35.2585],[-81.0082,35.2509],[-81.012,35.2349],[-81.0113,35.2309],[-81.0129,35.2231],[-81.0071,35.2109],[-81.0054,35.2055],[-81.0064,35.1973],[-81.0063,35.1923],[-81.0046,35.1864],[-81.0045,35.1814],[-81.0049,35.1728],[-81.0088,35.165],[-81.0076,35.1569],[-81.0109,35.1532],[-81.0176,35.1536],[-81.0238,35.1486],[-81.0448,35.1494],[-81.0682,35.1507],[-81.1814,35.1568],[-81.2141,35.1586],[-81.3277,35.1637],[-81.3163,35.1906],[-81.3209,35.2609],[-81.355,35.2796],[-81.3548,35.2946],[-81.3594,35.3022],[-81.3675,35.314],[-81.3659,35.3181],[-81.3565,35.3309],[-81.3986,35.3531],[-81.4535,35.4201]]]},\"properties\":{\"name\":\"Gaston\",\"state\":\"NC\"}}]}","edition":"Version 1.0: Originally posted March 27, 2017; Version 1.1: March 30, 2017","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
https://www2.usgs.gov/water/southatlantic/