Hybridization associated with species introductions can accelerate the decline of native species. The main objective of this study was to determine if the decline of a North American liana (American bittersweet, Celastrus scandens) in the eastern portion of its range is related to hybridization with an introduced congener (oriental bittersweet, C. orbiculatus). We used newly characterized microsatellite loci, a maternally-inherited chloroplast DNA marker, and field observation to survey individuals across the USA to determine the prevalence of hybrids, their importance in the invasion of C. orbiculatus, and the predominant direction of hybridization. We found that only 8.4 % of non-native genotypes were hybrids (20 of 239), and these hybrids were geographically widespread. Hybrids showed reduced seed set (decline of >98 %) and small, likely inviable pollen. Genetic analysis of a maternally inherited chloroplast marker showed that all 20 identified hybrids came from C. scandens seed parents. The strong asymmetry in pollen flow that favors fecundity in introduced males has the potential to greatly accelerate the decline of native species by wasting limited female reproductive effort.
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Chicago","active":true,"usgs":false}],"preferred":false,"id":583632,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148555,"text":"sim3333 - 2015 - Geologic and hydrostratigraphic map of the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas","interactions":[],"lastModifiedDate":"2016-08-16T15:52:48","indexId":"sim3333","displayToPublicDate":"2015-07-08T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3333","title":"Geologic and hydrostratigraphic map of the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas","docAbstract":"This report describes the geology and hydrostratigraphy of the Edwards and Trinity Groups in the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas. The hydrostratigraphy was defined based on variations in the amount and type of porosity of each lithostratigraphic unit, which varies depending on the unit’s original depositional environment, lithology, structural history, and diagenesis.
\nRocks exposed in the study area are of the Lower Cretaceous Trinity Group and lower part of the Kainer Formation of the Lower Cretaceous Edwards Group. The mapped outcrops in the study area are the Pearsall Formation and Glen Rose Limestone of the Trinity Group. The Pearsall Formation consists of, in ascending order: the Hammett Shale, Cow Creek Limestone, and Hensell Sand Member. The Glen Rose Limestone is composed of the informal lower and upper members. In the study area the Edwards Group consists only of the informal basal nodular member of the Kainer Formation. The faulting and fracturing in the study area are part of the Miocene-age Balcones fault zone, an extensional system of faults that generally trends southwest to northeast in south-central Texas. An igneous dike, containing aphanitic texture, cuts through part of the Anhalt quadrangle near the confluence of Honey Creek and the Guadalupe River. The dike penetrates the Cow Creek Limestone Member and the lower part of the Hensell Sand Member outcropping at three locations.
\nThe hydrostratigraphic units of the Edwards and Trinity aquifers have been mapped and described herein using a classification system developed by Choquette and Pray (1970), which is based on porosity types being fabric or not-fabric selective. The naming of hydrostratigraphic units is also based on preexisting names and topographic or historical features that occur in outcrop. The only hydrostratigraphic unit of the Edwards aquifer present in the study area is VIII hydrostratigraphic unit. The mapped hydrostratigraphic units of the upper Trinity aquifer are, from top to bottom: the cavernous, Camp Bullis, upper evaporite, fossiliferous, and lower evaporite and they are interval equivalent to the upper member of the Glen Rose Limestone. The middle Trinity aquifer (interval equivalent to the lower member of the Glen Rose Limestone) contains, from top to bottom: the Bulverde, Little Blanco, Twin Sisters, Doeppenschmidt, Rust, and Honey Creek hydrostratigraphic units. The lower part of the middle Trinity aquifer is formed by the Hensell, Cow Creek, and Hammett hydrostratigraphic units which are interval equivalent to the Hensell Sand Member, the Cow Creek Limestone, and the Hammett Shale Member, respectively, of the Pearsall Formation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3333","usgsCitation":"Clark, A.K., and Morris, R.R., 2015, Geologic and hydrostratigraphic map of the Anhalt, Fischer, and Spring Branch 7.5-minute quadrangles, Blanco, Comal, and Kendall Counties, Texas: U.S. Geological Survey Scientific Investigations Map 3333, Pamphlet: iv, 12 p.; Map: 50 x 20 inches; Downloads Directory, https://doi.org/10.3133/sim3333.","productDescription":"Pamphlet: iv, 12 p.; Map: 50 x 20 inches; Downloads Directory","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059768","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":305612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3333.jpg"},{"id":305610,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3333/pdf/sim3333_map.pdf","text":"Map and Summary Table","size":"85.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Map"},{"id":305609,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3333/pdf/sim3333_pamphlet.pdf","text":"Pamphlet","size":"8.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Pamphlet"},{"id":305587,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3333/"},{"id":305611,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3333/downloads/","text":"Downloads Directory","linkHelpText":"Contains: geospatial database. Refer to the Readme and Metadata files for more information."}],"country":"United States","state":"Texas","county":"Blanco County, Comal County, Kendall County","otherGeospatial":"Anhalt, Fischer, Spring Branch quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.37570190429688,\n 29.869228848968312\n ],\n [\n -98.37570190429688,\n 29.983486718474694\n ],\n [\n -98.24798583984375,\n 29.983486718474694\n ],\n [\n -98.24798583984375,\n 29.869228848968312\n ],\n [\n -98.37570190429688,\n 29.869228848968312\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.5089111328125,\n 29.869228848968312\n ],\n [\n -98.5089111328125,\n 29.983486718474694\n ],\n [\n -98.37844848632811,\n 29.983486718474694\n ],\n [\n -98.37844848632811,\n 29.869228848968312\n ],\n [\n -98.5089111328125,\n 29.869228848968312\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.51028442382811,\n 29.756032197482945\n ],\n [\n -98.51028442382811,\n 29.868037972862645\n ],\n [\n -98.37570190429688,\n 29.868037972862645\n ],\n [\n -98.37570190429688,\n 29.756032197482945\n ],\n [\n -98.51028442382811,\n 29.756032197482945\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a5b8bee4b0ebae89b788d3","contributors":{"authors":[{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Robert R.","contributorId":141163,"corporation":false,"usgs":false,"family":"Morris","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":13701,"text":"Volunteer for Science, USGS","active":true,"usgs":false}],"preferred":false,"id":564203,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171042,"text":"70171042 - 2015 - Etheostoma brevirostrum (Holiday Darter)","interactions":[],"lastModifiedDate":"2018-11-20T15:39:57","indexId":"70171042","displayToPublicDate":"2015-07-08T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"displayTitle":"Etheostoma brevirostrum (Holiday Darter)","title":"Etheostoma brevirostrum (Holiday Darter)","docAbstract":"The life history of the Holiday Darter is incompletely known. Only reproductive behavior (Johnston and Shute 1997; Anderson 2009), habitat use, and spawning seasons (Anderson 2009) have been studied. However, based on similarity of life history attributes among snubnose darters (Carney and Burr 1989; Johnston and Haag 1996; Khudamrongsawat et al. 2005), the Holiday darter probably lives 3+ years and matures in the first year. It is likely a benthic omnivore, feeding primarily on chironomid (midge) larvae and other common orders of aquatic insects and occasional microcrustaceans. Spawning occurs from late March to early June, with most activity occurring in April. Based on four females from the Amicalola Creek system, fecundity ranged from 50 to 150 mature eggs, egg sizes ranged from 1.2mm to 1.6mm diameter. The Holiday Darter is an “egg attacher” (sensu Page and Swofford 1984). A spawning female is courted by multiple males, but a dominant (alpha) male aggressively rebuts encroaching males and defends a “roving territory” of the receptive female. The alpha male is the principal spawning partner although satellite males often rush a spawning pair. The receptive female slowly swims along the stream bottom, frequently stopping, apparently to assess substrate attributes, and selects each spawning site where only one or two eggs are spawned. The process is repeated and often covers several meters of stream bottom until the courted female finishes spawning and is abandoned by the alpha male. Water temperatures during spawning in Amicalola Creek and the upper Etowah River ranged 10 to 17° C (Anderson 2009).
","largerWorkTitle":"Freshwater information network: Tennessee Aquarium Conservation Institute","language":"English","publisher":"ICube","usgsCitation":"Burkhead, N.M., 2015, Etheostoma brevirostrum (Holiday Darter), chap. of Freshwater information network: Tennessee Aquarium Conservation Institute, HTML Document.","productDescription":"HTML Document","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030831","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":325096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Amicalola Creek, Etowah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.2544937133789,\n 34.30487507190691\n ],\n [\n -84.2544937133789,\n 34.462126502013184\n ],\n [\n -84.122314453125,\n 34.462126502013184\n ],\n [\n -84.122314453125,\n 34.30487507190691\n ],\n [\n -84.2544937133789,\n 34.30487507190691\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"579dcfade4b0589fa1cbd571","contributors":{"authors":[{"text":"Burkhead, Noel M. nburkhead@usgs.gov","contributorId":3030,"corporation":false,"usgs":true,"family":"Burkhead","given":"Noel","email":"nburkhead@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":629663,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70155218,"text":"70155218 - 2015 - Estimating the abundance of the Southern Hudson Bay polar bear subpopulation with aerial surveys","interactions":[],"lastModifiedDate":"2015-09-10T15:25:28","indexId":"70155218","displayToPublicDate":"2015-07-07T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the abundance of the Southern Hudson Bay polar bear subpopulation with aerial surveys","docAbstract":"The Southern Hudson Bay (SH) polar bear subpopulation occurs at the southern extent of the species’ range. Although capture–recapture studies indicate abundance was likely unchanged between 1986 and 2005, declines in body condition and survival occurred during the period, possibly foreshadowing a future decrease in abundance. To obtain a current estimate of abundance, we conducted a comprehensive line transect aerial survey of SH during 2011–2012. We stratified the study site by anticipated densities and flew coastal contour transects and systematically spaced inland transects in Ontario and on Akimiski Island and large offshore islands in 2011. Data were collected with double-observer and distance sampling protocols. We surveyed small islands in James Bay and eastern Hudson Bay and flew a comprehensive transect along the Québec coastline in 2012. We observed 667 bears in Ontario and on Akimiski Island and nearby islands in 2011, and we sighted 80 bears on offshore islands during 2012. Mark–recapture distance sampling and sight–resight models yielded an estimate of 860 (SE = 174) for the 2011 study area. Our estimate of abundance for the entire SH subpopulation (943; SE = 174) suggests that abundance is unlikely to have changed significantly since 1986. However, this result should be interpreted cautiously because of the methodological differences between historical studies (physical capture–recapture) and this survey. A conservative management approach is warranted given previous increases in duration of the ice-free season, which are predicted to continue in the future, and previously documented declines in body condition and vital rates.
","language":"English","publisher":"Springer-Verlag","publisherLocation":"Heidelberg","doi":"10.1007/s00300-015-1737-5","usgsCitation":"Obbard, M.E., Stapleton, S.P., Middel, K.R., Thibault, I., Brodeur, V., and Jutras, C., 2015, Estimating the abundance of the Southern Hudson Bay polar bear subpopulation with aerial surveys: Polar Biology, v. 38, no. 10, p. 1713-1725, https://doi.org/10.1007/s00300-015-1737-5.","productDescription":"13 p.","startPage":"1713","endPage":"1725","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059751","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":306319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-07","publicationStatus":"PW","scienceBaseUri":"55c090ade4b033ef52104296","contributors":{"authors":[{"text":"Obbard, Martyn E.","contributorId":108002,"corporation":false,"usgs":false,"family":"Obbard","given":"Martyn","email":"","middleInitial":"E.","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":566959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stapleton, Seth P. sstapleton@usgs.gov","contributorId":3979,"corporation":false,"usgs":true,"family":"Stapleton","given":"Seth","email":"sstapleton@usgs.gov","middleInitial":"P.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":566960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middel, Kevin R.","contributorId":141065,"corporation":false,"usgs":false,"family":"Middel","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":566961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thibault, Isabelle","contributorId":141066,"corporation":false,"usgs":false,"family":"Thibault","given":"Isabelle","email":"","affiliations":[],"preferred":false,"id":566962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brodeur, Vincent","contributorId":141067,"corporation":false,"usgs":false,"family":"Brodeur","given":"Vincent","email":"","affiliations":[],"preferred":false,"id":566963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jutras, Charles","contributorId":141068,"corporation":false,"usgs":false,"family":"Jutras","given":"Charles","email":"","affiliations":[],"preferred":false,"id":566964,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70155521,"text":"70155521 - 2015 - Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record","interactions":[],"lastModifiedDate":"2015-10-26T14:00:26","indexId":"70155521","displayToPublicDate":"2015-07-07T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record","docAbstract":"Delineating the climate processes governing precipitation variability in drought-prone Texas is critical for predicting and mitigating climate change effects, and requires the reconstruction of past climate beyond the instrumental record. We synthesize existing paleoclimate proxy data and climate simulations to provide an overview of climate variability in Texas during the Holocene. Conditions became progressively warmer and drier transitioning from the early to mid Holocene, culminating between 7 and 3 ka (thousand years ago), and were more variable during the late Holocene. The timing and relative magnitude of Holocene climate variability, however, is poorly constrained owing to considerable variability among the different records. To help address this, we present a new speleothem (NBJ) reconstruction from a central Texas cave that comprises the highest resolution proxy record to date, spanning the mid to late Holocene. NBJ trace-element concentrations indicate variable moisture conditions with no clear temporal trend. There is a decoupling between NBJ growth rate, trace-element concentrations, and δ18O values, which indicate that (i) the often direct relation between speleothem growth rate and moisture availability is likely complicated by changes in the overlying ecosystem that affect subsurface CO2 production, and (ii) speleothem δ18O variations likely reflect changes in moisture source (i.e., proportion of Pacific-vs. Gulf of Mexico-derived moisture) that appear not to be linked to moisture amount.
","language":"English","publisher":"Pergamon Press","publisherLocation":"New York, NY","doi":"10.1016/j.quascirev.2015.06.023","usgsCitation":"Wong, C., Banner, J., and Musgrove, M., 2015, Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record: Quaternary Science Reviews, v. 127, p. 155-173, https://doi.org/10.1016/j.quascirev.2015.06.023.","productDescription":"19 p.","startPage":"155","endPage":"173","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062965","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":306533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.0517578125,\n 36.491973470593685\n ],\n [\n -99.97558593749999,\n 36.50963615733049\n ],\n [\n -99.99755859375,\n 34.66935854524543\n ],\n [\n -99.7119140625,\n 34.415973384481866\n ],\n [\n -99.404296875,\n 34.52466147177172\n ],\n [\n -99.16259765625,\n 34.27083595165\n ],\n [\n -98.525390625,\n 34.10725639663118\n ],\n [\n -98.23974609375,\n 34.21634468843465\n ],\n [\n -96.3720703125,\n 33.96158628979907\n ],\n [\n -95.55908203125,\n 34.052659421375964\n ],\n [\n -94.8779296875,\n 34.03445260967645\n ],\n [\n -94.39453125,\n 33.669496972795535\n ],\n [\n -93.9990234375,\n 33.65120829920497\n ],\n [\n -93.9990234375,\n 31.970803930433096\n ],\n [\n -93.4716796875,\n 31.2221970321032\n ],\n [\n -93.40576171875,\n 30.90222470517144\n ],\n [\n -93.7353515625,\n 30.543338954230222\n ],\n [\n -93.8232421875,\n 29.954934549656144\n ],\n [\n -93.88916015625,\n 29.66896252599253\n ],\n [\n -95.51513671875,\n 28.806173508854776\n ],\n [\n -96.13037109375,\n 28.497660832963472\n ],\n [\n -96.83349609375,\n 28.14950321154457\n ],\n [\n -97.09716796875,\n 27.488781168937997\n ],\n [\n -97.49267578125,\n 27.059125784374068\n ],\n [\n -97.42675781249999,\n 26.509904531413927\n ],\n [\n -97.119140625,\n 25.997549919572112\n ],\n [\n -97.44873046875,\n 25.799891182088334\n ],\n [\n -98.59130859375,\n 26.15543796871355\n ],\n [\n -99.228515625,\n 26.47057302237511\n ],\n [\n -99.84374999999999,\n 27.527758206861886\n ],\n [\n -100.92041015625,\n 29.0945770775118\n ],\n [\n -101.49169921875,\n 29.630771207229\n ],\n [\n -102.3046875,\n 29.783449456820605\n ],\n [\n -102.76611328125,\n 29.516110386062277\n ],\n [\n -103.1396484375,\n 28.844673680771795\n ],\n [\n -104.8974609375,\n 29.726222319395504\n ],\n [\n -104.78759765625,\n 30.088107753367257\n ],\n [\n -105.1171875,\n 30.58117925738696\n ],\n [\n -105.77636718749999,\n 30.996445897426373\n ],\n [\n -106.787109375,\n 31.87755764334002\n ],\n [\n -106.67724609375,\n 32.045332838858506\n ],\n [\n -103.07373046875,\n 31.989441837922904\n ],\n [\n -103.0517578125,\n 36.491973470593685\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55c9cb34e4b08400b1fdb70e","contributors":{"authors":[{"text":"Wong, Corinne I.","contributorId":36018,"corporation":false,"usgs":true,"family":"Wong","given":"Corinne I.","affiliations":[],"preferred":false,"id":565675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banner, Jay L.","contributorId":58200,"corporation":false,"usgs":true,"family":"Banner","given":"Jay L.","affiliations":[],"preferred":false,"id":565676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":1316,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":565674,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70158682,"text":"70158682 - 2015 - Statistical guidelines for assessing marine avian hotspots and coldspots: A case study on wind energy development in the U.S. Atlantic Ocean","interactions":[],"lastModifiedDate":"2017-01-11T16:55:27","indexId":"70158682","displayToPublicDate":"2015-07-07T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Statistical guidelines for assessing marine avian hotspots and coldspots: A case study on wind energy development in the U.S. Atlantic Ocean","docAbstract":"Estimating patterns of habitat use is challenging for marine avian species because seabirds tend to aggregate in large groups and it can be difficult to locate both individuals and groups in vast marine environments. We developed an approach to estimate the statistical power of discrete survey events to identify species-specific hotspots and coldspots of long-term seabird abundance in marine environments. We illustrate our approach using historical seabird data from survey transects in the U.S. Atlantic Ocean Outer Continental Shelf (OCS), an area that has been divided into “lease blocks” for proposed offshore wind energy development. For our power analysis, we examined whether discrete lease blocks within the region could be defined as hotspots (3 × mean abundance in the OCS) or coldspots (1/3 ×) for individual species within a given season. For each of 74 species/season combinations, we determined which of eight candidate statistical distributions (ranging in their degree of skewedness) best fit the count data. We then used the selected distribution and estimates of regional prevalence to calculate and map statistical power to detect hotspots and coldspots, and estimate the p-value from Monte Carlo significance tests that specific lease blocks are in fact hotspots or coldspots relative to regional average abundance. The power to detect species-specific hotspots was higher than that of coldspots for most species because species-specific prevalence was relatively low (mean: 0.111; SD: 0.110). The number of surveys required for adequate power (> 0.6) was large for most species (tens to hundreds) using this hotspot definition. Regulators may need to accept higher proportional effect sizes, combine species into groups, and/or broaden the spatial scale by combining lease blocks in order to determine optimal placement of wind farms. 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","language":"English","publisher":"Elsevier Science Ltd.","publisherLocation":"Kidlington, Oxford","doi":"10.1016/j.biocon.2015.06.035","usgsCitation":"Zipkin, E., Kinlan, B.P., Sussman, A., Rypkema, D., Wimer, M., and O’Connell, A.F., 2015, Statistical guidelines for assessing marine avian hotspots and coldspots: A case study on wind energy development in the U.S. Atlantic Ocean: Biological Conservation, v. 191, p. 216-223, https://doi.org/10.1016/j.biocon.2015.06.035.","productDescription":"8 p.","startPage":"216","endPage":"223","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066531","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471948,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2015.06.035","text":"Publisher Index 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aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":576486,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160102,"text":"70160102 - 2015 - Renewed inflation of Long Valley Caldera, California (2011 to 2014)","interactions":[],"lastModifiedDate":"2015-12-14T11:17:50","indexId":"70160102","displayToPublicDate":"2015-07-07T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Renewed inflation of Long Valley Caldera, California (2011 to 2014)","docAbstract":"Slow inflation began at Long Valley Caldera in late 2011, coinciding with renewed swarm seismicity. Ongoing deformation is concentrated within the caldera. We analyze this deformation using a combination of GPS and InSAR (TerraSAR-X) data processed with a persistent scatterer technique. The extension rate of the dome-crossing baseline during this episode (CA99 to KRAC) is 1 cm/yr, similar to past inflation episodes (1990–1995 and 2002–2003), and about a tenth of the peak rate observed during the 1997 unrest. The current deformation is well modeled by the inflation of a prolate spheroidal magma reservoir ∼7 km beneath the resurgent dome, with a volume change of ∼6 × 106 m3/yr from 2011.7 through the end of 2014. The current data cannot resolve a second source, which was required to model the 1997 episode. This source appears to be in the same region as previous inflation episodes, suggesting a persistent reservoir.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, DC","doi":"10.1002/2015GL064338","usgsCitation":"Montgomery-Brown, E., Wicks, C.W., Cervelli, P.F., Langbein, J.O., Svarc, J.L., Shelly, D.R., Hill, D.P., and Lisowski, M., 2015, Renewed inflation of Long Valley Caldera, California (2011 to 2014): Geophysical Research Letters, v. 42, no. 13, p. 5250-5257, https://doi.org/10.1002/2015GL064338.","productDescription":"8 p.","startPage":"5250","endPage":"5257","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064951","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471949,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl064338","text":"Publisher Index Page"},{"id":312244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Long Valley Caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.09454345703125,\n 38.348118547988065\n ],\n [\n -118.9105224609375,\n 38.21660403859855\n ],\n [\n -118.65509033203125,\n 38.0545795282119\n ],\n [\n -118.4381103515625,\n 37.846663684549156\n ],\n [\n -118.3172607421875,\n 37.65338320128765\n ],\n [\n -118.27880859375001,\n 37.35487607348372\n ],\n [\n -118.24859619140626,\n 37.07271048132946\n ],\n [\n -119.05059814453125,\n 37.64903402157866\n ],\n [\n -119.22637939453124,\n 37.844494798834596\n ],\n [\n -119.39117431640625,\n 38.1669547678699\n ],\n [\n -119.36920166015624,\n 38.34165619279593\n ],\n [\n -119.21539306640626,\n 38.429925130409366\n ],\n [\n -119.09454345703125,\n 38.348118547988065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"13","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-07","publicationStatus":"PW","scienceBaseUri":"566ff656e4b09cfe53ca79c2","chorus":{"doi":"10.1002/2015gl064338","url":"http://dx.doi.org/10.1002/2015gl064338","publisher":"Wiley-Blackwell","authors":"Montgomery-Brown E. 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Jr. 0000-0002-0809-1328 cwicks@usgs.gov","orcid":"https://orcid.org/0000-0002-0809-1328","contributorId":127701,"corporation":false,"usgs":true,"family":"Wicks","given":"Charles","suffix":"Jr.","email":"cwicks@usgs.gov","middleInitial":"W.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":581997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cervelli, Peter F. 0000-0001-6765-1009 pcervelli@usgs.gov","orcid":"https://orcid.org/0000-0001-6765-1009","contributorId":1936,"corporation":false,"usgs":true,"family":"Cervelli","given":"Peter","email":"pcervelli@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":581998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langbein, John O. 0000-0002-7821-8101 langbein@usgs.gov","orcid":"https://orcid.org/0000-0002-7821-8101","contributorId":3293,"corporation":false,"usgs":true,"family":"Langbein","given":"John","email":"langbein@usgs.gov","middleInitial":"O.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":581999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Svarc, Jerry L. 0000-0002-2802-4528 jsvarc@usgs.gov","orcid":"https://orcid.org/0000-0002-2802-4528","contributorId":2413,"corporation":false,"usgs":true,"family":"Svarc","given":"Jerry","email":"jsvarc@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":582000,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":582001,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hill, David P. hill@usgs.gov","contributorId":2600,"corporation":false,"usgs":true,"family":"Hill","given":"David","email":"hill@usgs.gov","middleInitial":"P.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":false,"id":582002,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lisowski, Michael 0000-0003-4818-2504 mlisowski@usgs.gov","orcid":"https://orcid.org/0000-0003-4818-2504","contributorId":637,"corporation":false,"usgs":true,"family":"Lisowski","given":"Michael","email":"mlisowski@usgs.gov","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":582003,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70156128,"text":"70156128 - 2015 - Didymosphenia geminata in the Upper Esopus Creek: current status, variability, and controlling factors","interactions":[],"lastModifiedDate":"2015-08-17T11:37:54","indexId":"70156128","displayToPublicDate":"2015-07-06T12:45:00","publicationYear":"2015","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":"Didymosphenia geminata in the Upper Esopus Creek: current status, variability, and controlling factors","docAbstract":"In May of 2009, the bloom-forming diatom Didymosphenia geminata was first identified in the Upper Esopus Creek, a key tributary to the New York City water-supply and a popular recreational stream. The Upper Esopus receives supplemental flows from the Shandaken Portal, an underground aqueduct delivering waters from a nearby basin. The presence of D.geminata is a concern for the local economy, water supply, and aquatic ecosystem because nuisance blooms have been linked to degraded stream condition in other regions. Here we ascertain the extent and severity of the D. geminata invasion, determine the impact of supplemental flows from the Portal on D. geminata, and identify potential factors that may limitD. geminata in the watershed. Stream temperature, discharge, and water quality were characterized at select sites and periphyton samples were collected five times at 6 to 20 study sites between 2009 and 2010 to assess standing crop, diatom community structure, and density of D. geminata and all diatoms. Density of D. geminata ranged from 0–12 cells cm-2 at tributary sites, 0–781 cells cm-2 at sites upstream of the Portal, and 0–2,574 cells cm-2 at sites downstream of the Portal. Survey period and Portal (upstream or downstream) each significantly affected D. geminata cell density. In general, D. geminata was most abundant during the November 2009 and June 2010 surveys and at sites immediately downstream of the Portal. We found that D. geminata did not reach nuisance levels or strongly affect the periphyton community. Similarly, companion studies showed that local macroinvertebrate and fish communities were generally unaffected. A number of abiotic factors including variable flows and moderate levels of phosphorous and suspended sediment may limit blooms of D. geminatain this watershed.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0130558","collaboration":"New York State Dept of Environmental Conservation; USGS","usgsCitation":"George, S.D., and Baldigo, B.P., 2015, Didymosphenia geminata in the Upper Esopus Creek: current status, variability, and controlling factors: PLoS ONE, v. 10, no. 8, p. 1-20, https://doi.org/10.1371/journal.pone.0130558.","productDescription":"20 p.","startPage":"1","endPage":"20","numberOfPages":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043086","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471950,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0130558","text":"Publisher Index Page"},{"id":306799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"8","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-06","publicationStatus":"PW","scienceBaseUri":"55d305a9e4b0518e35468ccc","contributors":{"authors":[{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":567894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":567893,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70154906,"text":"70154906 - 2015 - Potamochoerus porcus (Artiodactyla: Suidae)","interactions":[],"lastModifiedDate":"2015-08-03T10:36:49","indexId":"70154906","displayToPublicDate":"2015-07-06T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2654,"text":"Mammalian Species","active":true,"publicationSubtype":{"id":10}},"title":"Potamochoerus porcus (Artiodactyla: Suidae)","docAbstract":"Potamochoerus porcus (Linnaeus, 1758) is a monotypic suid commonly known as the red river hog. It is 1 of 2 species in the genus Potamochoerus and among the smallest and most plesiomorphic (ancestral) of the 8 African suids. This is the brightest colored wild pig species and is identified by its rufous coat and white dorsal crest; spectacled black-and-white facemask; and elongated, leaf-shaped ears that end in terminally drooping tufts of hair. P. porcus lives in damp forests throughout the rainforest belt of western and central Africa; it never ranges far from thick vegetative cover, soft soils, and water. Although P. porcus is commonly harvested for subsistence and urban bushmeat markets, it is considered of “Least Concern” by the International Union for Conservation of Nature and Natural Resources.
","language":"English","publisher":"American Society of Mammalogists","doi":"10.1093/mspecies/sev002","usgsCitation":"Leslie, D., and Huffman, B.A., 2015, Potamochoerus porcus (Artiodactyla: Suidae): Mammalian Species, v. 47, no. 919, p. 15-31, https://doi.org/10.1093/mspecies/sev002.","productDescription":"17 p.","startPage":"15","endPage":"31","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056332","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":471951,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/mspecies/sev002","text":"Publisher Index Page"},{"id":305856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"919","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-03","publicationStatus":"PW","scienceBaseUri":"55af6d2de4b09a3b01b51aa9","contributors":{"authors":[{"text":"Leslie, David M. Jr. cleslie@usgs.gov","contributorId":145497,"corporation":false,"usgs":true,"family":"Leslie","given":"David M.","suffix":"Jr.","email":"cleslie@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huffman, Brent A.","contributorId":145760,"corporation":false,"usgs":false,"family":"Huffman","given":"Brent","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":565191,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70154748,"text":"ofr20151124 - 2015 - An evaluation of fish behavior upstream of the water temperature control tower at Cougar Dam, Oregon, using acoustic cameras, 2013","interactions":[],"lastModifiedDate":"2016-01-08T14:45:29","indexId":"ofr20151124","displayToPublicDate":"2015-07-06T12:00:00","publicationYear":"2015","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":"2015-1124","title":"An evaluation of fish behavior upstream of the water temperature control tower at Cougar Dam, Oregon, using acoustic cameras, 2013","docAbstract":"This report describes the initial year of a 2-year study to determine the feasibility of using acoustic cameras to monitor fish movements to help inform decisions about fish passage at Cougar Dam near Springfield, Oregon. Specifically, we used acoustic cameras to measure fish presence, travel speed, and direction adjacent to the water temperature control tower in the forebay of Cougar Dam during the spring (May, June, and July) and fall (September, October, and November) of 2013. Cougar Dam is a high-head flood-control dam, and the water temperature control tower enables depth-specific water withdrawals to facilitate adjustment of water temperatures released downstream of the dam. The acoustic cameras were positioned at the upstream entrance of the tower to monitor free-ranging subyearling and yearling-size juvenile Chinook salmon (Oncorhynchus tshawytscha). Because of the large size discrepancy, we could distinguish juvenile Chinook salmon from their predators, which enabled us to measure predators and prey in areas adjacent to the entrance of the tower. We used linear models to quantify and assess operational and environmental factors—such as time of day, discharge, and water temperature—that may influence juvenile Chinook salmon movements within the beam of the acoustic cameras. Although extensive milling behavior of fish near the structure may have masked directed movement of fish and added unpredictability to fish movement models, the acoustic-camera technology enabled us to ascertain the general behavior of discrete size classes of fish. Fish travel speed, direction of travel, and counts of fish moving toward the water temperature control tower primarily were influenced by the amount of water being discharged through the dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151124","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Adams, N.S., Smith, C.D., Plumb, J.M., Hansen, G.S., and Beeman, J.W., 2015, An evaluation of fish behavior upstream of the water temperature control tower at Cougar Dam, Oregon, using acoustic cameras, 2013: U.S. Geological Survey Open-File Report 2015-1124, 62 p., https://dx.doi.org/10.3133/ofr20151124.","productDescription":"x, 62 p.","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063666","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":305440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1124/coverthb.jpg"},{"id":305441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1124/ofr20151124.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Oregon","otherGeospatial":"Cougar Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.25345611572266,\n 44.122345529999656\n ],\n [\n -122.25345611572266,\n 44.132942183139654\n ],\n [\n -122.23114013671875,\n 44.132942183139654\n ],\n [\n -122.23114013671875,\n 44.122345529999656\n ],\n [\n -122.25345611572266,\n 44.122345529999656\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov
The east side of the Uncompahgre River Basin has been a known contributor of dissolved selenium to recipient streams. Discharge of groundwater containing dissolved selenium contributes to surface-water selenium concentrations and loads; however, the groundwater system on the east side of the Uncompahgre River Basin is not well characterized. The U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board and the Bureau of Reclamation, has established a groundwater-monitoring network on the east side of the Uncompahgre River Basin. Ten monitoring wells were installed during October and November 2012. This report presents location data, lithologic logs, well-construction diagrams, and well-development information. Understanding the groundwater system will provide managers with an additional metric for evaluating the effectiveness of salinity and selenium control projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds923","collaboration":"Prepared in cooperation with Colorado Water Conservation Board and the Bureau of Reclamation","usgsCitation":"Thomas, J.C., and Arnold, L.R., 2015, Installation of a groundwater monitoring-well network on the east side of the Uncompahgre River in the Lower Gunnison River Basin, Colorado, 2012: U.S. Geological Survey Data Series 923, 29 p., https://dx.doi.org/10.3133/ds923.","productDescription":"iv, 29 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059394","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":309728,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/ds955","text":"DS 955"},{"id":305498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0923/pdf/ds923.pdf","text":"Report","size":"17.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 923"},{"id":305497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0923/coverthb.jpg"},{"id":305608,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/publication/ds923"}],"country":"United States","state":"Colorado","otherGeospatial":"Uncompahgre River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.6154613494873,\n 37.91705002583544\n ],\n [\n -107.6154613494873,\n 37.928153945306555\n ],\n [\n -107.59949684143065,\n 37.928153945306555\n ],\n [\n -107.59949684143065,\n 37.91705002583544\n ],\n [\n -107.6154613494873,\n 37.91705002583544\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
http://co.water.usgs.gov
Contours and derivative raster files of depth-to-basement, sediment-thickness, and bathymetry data for the area offshore of Washington, Oregon, and California are provided here as GIS-ready shapefiles and GeoTIFF files. The data were used to generate paper maps in 1992 and 1993 from 1984 surveys of the U.S. Exclusive Economic Zone by the U.S. Geological Survey for depth to basement and sediment thickness, and from older data for the bathymetry.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151118","usgsCitation":"Wong, F.L., and Grim, M.S., 2015, Depth-to-basement, sediment-thickness, and bathymetry data for the deep-sea basins offshore of Washington, Oregon, and California: U.S. Geological Survey Open-File Report 2015-1118, Report: iv, 13 p.; Data Catalog, https://doi.org/10.3133/ofr20151118.","productDescription":"Report: iv, 13 p.; Data Catalog","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057812","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":305574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151118.gif"},{"id":305572,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1118/ofr20151118.pdf","text":"Report","size":"5.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":305573,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2015/1118/data_catalog.html","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"description":"Data Catalog"},{"id":305561,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1118/"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.8154296875,\n 47.96050238891509\n ],\n [\n -125.068359375,\n 46.437856895024225\n ],\n [\n -124.892578125,\n 44.96479793033104\n ],\n [\n -125.068359375,\n 43.45291889355465\n ],\n [\n -125.20019531249999,\n 41.80407814427237\n ],\n [\n -125.0244140625,\n 40.51379915504413\n ],\n [\n -124.71679687499999,\n 39.36827914916014\n ],\n [\n -124.3212890625,\n 38.20365531807149\n ],\n [\n -123.79394531249999,\n 36.949891786813296\n ],\n [\n -122.607421875,\n 35.38904996691167\n ],\n [\n -120.80566406250001,\n 33.7243396617476\n ],\n [\n -119.83886718750001,\n 32.694865977875075\n ],\n [\n -120.9814453125,\n 32.02670629333614\n ],\n [\n -122.34374999999999,\n 31.653381399664\n ],\n [\n -123.92578125,\n 32.287132632616355\n ],\n [\n -126.0791015625,\n 34.88593094075317\n ],\n [\n -127.529296875,\n 37.055177106660814\n ],\n [\n -128.32031249999997,\n 39.30029918615029\n ],\n [\n -128.7158203125,\n 41.64007838467894\n ],\n [\n -128.32031249999997,\n 43.67581809328344\n ],\n [\n -127.96875,\n 45.521743896993634\n ],\n [\n -129.6826171875,\n 45.67548217560647\n ],\n [\n -130.078125,\n 47.27922900257082\n ],\n [\n -126.65039062499999,\n 47.60616304386874\n ],\n [\n -125.8154296875,\n 47.96050238891509\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7eef3e4b0bc0bec09ee10","contributors":{"authors":[{"text":"Wong, Florence L. 0000-0002-3918-5896 fwong@usgs.gov","orcid":"https://orcid.org/0000-0002-3918-5896","contributorId":1990,"corporation":false,"usgs":true,"family":"Wong","given":"Florence","email":"fwong@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":564143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grim, Muriel S.","contributorId":85591,"corporation":false,"usgs":true,"family":"Grim","given":"Muriel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":564144,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70142044,"text":"sir20155035 - 2015 - Alteration, slope-classified alteration, and potential lahar inundation maps of volcanoes for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Volcano Archive","interactions":[],"lastModifiedDate":"2015-07-06T11:56:29","indexId":"sir20155035","displayToPublicDate":"2015-07-03T10:15:00","publicationYear":"2015","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":"2015-5035","title":"Alteration, slope-classified alteration, and potential lahar inundation maps of volcanoes for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Volcano Archive","docAbstract":"This study identifies areas prone to lahars from hydrothermally altered volcanic edifices on a global scale, using visible and near infrared (VNIR) and short wavelength infrared (SWIR) reflectance data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and digital elevation data from the ASTER Global Digital Elevation Model (GDEM) dataset. This is the first study to create a global database of hydrothermally altered volcanoes showing quantitatively compiled alteration maps and potentially affected drainages, as well as drainage-specific maps illustrating modeled lahars and their potential inundation zones. We (1) identified and prioritized 720 volcanoes based on population density surrounding the volcanoes using the Smithsonian Institution Global Volcanism Program database (GVP) and LandScan™ digital population dataset; (2) validated ASTER hydrothermal alteration mapping techniques using Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) and ASTER data for Mount Shasta, California, and Pico de Orizaba (Citlaltépetl), Mexico; (3) mapped and slope-classified hydrothermal alteration using ASTER VNIR-SWIR reflectance data on 100 of the most densely populated volcanoes; (4) delineated drainages using ASTER GDEM data that show potential flow paths of possible lahars for the 100 mapped volcanoes; (5) produced potential alteration-related lahar inundation maps using the LAHARZ GIS code for Iztaccíhuatl, Mexico, and Mount Hood and Mount Shasta in the United States that illustrate areas likely to be affected based on DEM-derived volume estimates of hydrothermally altered rocks and the ~2x uncertainty factor inherent within a statistically-based lahar model; and (6) saved all image and vector data for 3D and 2D display in Google Earth™, ArcGIS® and other graphics display programs. In addition, these data are available from the ASTER Volcano Archive (AVA) for distribution (available at http://ava.jpl.nasa.gov/recent_alteration_zones.php).
\nUsing the GVP and the LandScan™ digital population dataset, 350 of the most densely populated stratovolcanoes were assessed for study. Of the 350 volcanoes, 250 volcanoes were not mapped due to excessive snow, ice, and (or) vegetation. Results from mapping the remaining 100 stratovolcanoes show that 87 contain slopes with hydrothermal alteration, and 49 have hydrothermally altered rocks on steep slopes situated above areas with populations >100 people per km2. Of these, 17 stratovolcanoes exhibit laterally extensive hydrothermal alteration on slopes >35° and cover an area >0.25 km2, which may pose a significant possibility of generating debris flows.
\nThis study was undertaken during 2012–2013 in cooperation with the National Aeronautics and Space Administration (NASA). Since completion of this study, a new lahar modeling program (LAHAR_pz) has been released, which may produce slightly different modeling results from the LAHARZ model used in this study. The maps and data from this study should not be used in place of existing volcano hazard maps published by local authorities. For volcanoes without hazard maps and (or) published lahar-related hazard studies, this work will provide a starting point from which more accurate hazard maps can be produced. This is the first dataset to provide digital maps of altered volcanoes and adjacent watersheds that can be used for assessing volcanic hazards, hydrothermal alteration, and other volcanic processes in future studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155035","usgsCitation":"Mars, J., Hubbard, B.E., Pieri, D., and Linick, J., 2015, Alteration, slope-classified alteration, and potential lahar inundation maps of volcanoes for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Volcano Archive: U.S. Geological Survey Scientific Investigations Report 2015-5035, https://doi.org/10.3133/sir20155035.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054579","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":305571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155035.gif"},{"id":305570,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5035/pdf/sir2015-5035.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":305557,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5035/"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7eef3e4b0bc0bec09ee12","contributors":{"authors":[{"text":"Mars, John C. jmars@usgs.gov","contributorId":127493,"corporation":false,"usgs":true,"family":"Mars","given":"John C.","email":"jmars@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":564125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubbard, Bernard E. 0000-0002-9315-2032 bhubbard@usgs.gov","orcid":"https://orcid.org/0000-0002-9315-2032","contributorId":2342,"corporation":false,"usgs":true,"family":"Hubbard","given":"Bernard","email":"bhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":564126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pieri, David","contributorId":139492,"corporation":false,"usgs":false,"family":"Pieri","given":"David","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":564127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Linick, Justin","contributorId":139493,"corporation":false,"usgs":false,"family":"Linick","given":"Justin","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":564128,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70143962,"text":"sir20155032 - 2015 - Groundwater quality in Geauga County, Ohio: status, including detection frequency of methane in water wells, 2009, and changes during 1978-2009","interactions":[],"lastModifiedDate":"2015-07-03T11:05:27","indexId":"sir20155032","displayToPublicDate":"2015-07-03T10:00:00","publicationYear":"2015","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":"2015-5032","title":"Groundwater quality in Geauga County, Ohio: status, including detection frequency of methane in water wells, 2009, and changes during 1978-2009","docAbstract":"Domestic wells that are not safeguarded by regular water-quality testing provide drinking water for 79 percent of the residents of Geauga County, in northeastern Ohio. Since 1978, the U.S. Geological Survey (USGS) has worked cooperatively with the Board of Commissioners and Geauga County Planning Commission to monitor the quality of groundwater in four commonly used aquifers in county—the glacial deposits, the Pottsville Formation, the Cuyahoga Group, and the Berea Sandstone. A 33-percent growth in population from 1980 to 2009 increased the potential for humans to influence groundwater resources by withdrawing more groundwater, disposing of more human waste near the land surface, treating an expanded network of township roads with deicing salt, and likely using more solvents, pesticides, and other chemicals on the land surface than were used in preceding decades.
\nTo describe the status of groundwater quality in 2009 and its suitability for drinking, USGS personnel collected samples of water prior to treatment from 16 wells (mostly domestic) during June 9–19. The samples were analyzed for 92 properties and constituents, 41 of which had human-health benchmarks to which analytical results could be compared to evaluate suitability for drinking. Four of these benchmarks were exceeded at the following frequencies: arsenic (2 of 16 wells, 12.5 percent), total coliform bacteria (2 of 16 wells, 12.5 percent), fecal coliform bacteria (1 of 14 wells, 7 percent), and sodium (6 of 16 wells, 38 percent). No domestic wells sampled in 2009 exceeded the health-based benchmark of 300 micrograms per liter (µg/L) for manganese, although 5 of 65 wells (8 percent) sampled since 1978 have. Analyses from domestic wells were augmented with water-quality data from seven public-supply well fields that were obtained from the Ohio Environmental Protection Agency. These public-supply data were typically collected between 2000 and 2010 and represent water samples that were collected prior to treatment or that were treated by a method that does not effectively remove the constituents of interest. Similar to the domestic-well data, these data indicated that some samples from public-supply wells have also exceeded health-based benchmarks for arsenic and sodium, along with occasional exceedances of health-based benchmarks for cadmium and lead. Concentrations of nitrate, pesticides, and volatile organic compounds in ground-water samples from domestic and (or) public-supply wells were either considerably less than the human-health benchmarks for these constituents or were not detected.
\nWater-quality data collected in 2009 were also compared to aesthetically based benchmarks developed by the U.S. Environmental Protection Agency, called Secondary Maximum Contaminant Levels (SMCLs). Iron and manganese most frequently exceeded SMCLs (in samples from 10 of 16 domestic wells and in untreated water from 3 of 4 public-supply well fields).
\nTo evaluate the frequency of methane detection in water wells in the county, the USGS sampled 16 wells across the county and screened the samples for combustible gas within the headspace (the air above the water in a closed container). Water from three (19 percent) of the wells contained detectable combustible gas (0.10 to 0.40 percent by volume). All three detections were from wells tapping the Cuyahoga Group or the Berea Sandstone, and all detections were less than the lower explosive limit of 5 percent by volume—the concentration at which methane in air can be flammable if an ignition source is present. Analyses of dissolved gas composition in water from these three wells showed methane concentrations ranging from 0.007 to 1.8 milligrams per liter (mg/L).
\nThe primary effect of human activities on groundwater quality found during this study is the input of salinity, or chloride, near land surface. On the basis of ratios of chloride to bromide, the main sources of chloride are road salt and septic leachate rather than oil-field brines (either spilled at land surface or sprayed on roads for dust control). The correlation of chloride concentration to distance of well from road for 31 wells in the county sampled by the U.S. Geological Survey in 1999 suggests that road salt is the dominant source of chloride.
\nThe majority of constituents exceeding health-based and aesthetically based benchmarks in groundwater were those that are naturally present in aquifer rocks and sediments rather than constituents introduced by human activities. Concentrations of such natural contaminants are controlled by geochemical processes in the subsurface, particularly by oxidation-reduction (redox) reactions. The categorization of redox conditions based on the water quality of 116 samples collected from 65 wells in Geauga County during 1978 through 2009 indicates that most groundwater samples were strongly reducing (60 percent) or oxic (18 percent). Oxic waters were found only in the Pottsville Formation and Berea Sandstone and were generally associated with nitrate at concentrations of 0.38 to 6.0 mg/L. Strongly reducing waters occurred in all four commonly used aquifers and were associated with the following naturally occurring contaminants: (1) arsenic and manganese at concentrations exceeding the health-based benchmarks (10 µg/L and 300 µg/L, respectively) in some samples, (2) iron and manganese at concentrations exceeding the aesthetically based standards (300 µg/L and 50 µg/L, respectively) in most samples, and (3) total sulfides (consisting of hydrogen sulfide gas with its characteristic rotten-egg odor and [or] iron sulfide minerals that appear as finely disseminated particulates in water).
\nBecause of the association of redox conditions with specific contaminants, attempts were made to further document spatially where oxic and strongly reducing conditions occur so that contaminant occurrence can be better anticipated by planners and well owners. Within the Pottsville Formation, wells tapping strongly reducing groundwater tended to have a greater thickness of overlying low-permeability (recharge-inhibiting) material such as clay and shale than other wells tapping oxic or nitrate-reducing groundwater. In the Berea Sandstone, oxic conditions were found at well locations where either depth to groundwater was shallow (less than 45 feet [ft] below land surface) or the measured water level was within the open interval (uncased portion) of the well, whereas strongly reducing groundwater was found at well locations where depths to water were greater than 60 ft below land surface and measured water levels were 15 ft or more above the open interval of the well.
\nTo evaluate whether constituent concentrations consistently increased or decreased over time, the strength of the association between sampling year (time) and constituent concentration was statistically evaluated for 116 water-quality samples collected by the USGS in 1978, 1980, 1986, 1999, and 2009 from a total of 65 wells across the county (generally domestic wells or wells serving small businesses or churches). Results indicate that many of the constituents that have been analyzed for decades exhibited no consistent temporal trends at a statistically significant level (p-value less than 0.05); fluctuations in concentrations of these constituents represent natural variation in groundwater quality. Dissolved oxygen, calcium, and sulfate concentrations and chloride:bromide ratios increased over time in one or more aquifers, while pH and concentrations of bromide and dissolved organic carbon decreased over time. Detections of total coliform bacteria and nitrate did not become more frequent from 1986 to 2009, even though potential sources of these constituents, such as number of septic systems (linked to population) and percent developed land in the county, increased during this period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155032","collaboration":"Geauga County Planning Commission; Geauga County Board of County Commissioners","usgsCitation":"Jagucki, M.L., Kula, S.P., and Mailot, B.E., 2015, Groundwater quality in Geauga County, Ohio: status, including detection frequency of methane in water wells, 2009, and changes during 1978-2009: U.S. Geological Survey Scientific Investigations Report 2015-5032, Report: x, 116 p.; Appendix, https://doi.org/10.3133/sir20155032.","productDescription":"Report: x, 116 p.; Appendix","numberOfPages":"130","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"1978-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-048863","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":305569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155032.jpg"},{"id":305553,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5032/"},{"id":305567,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5032/pdf/sir20155032.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":305568,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5032/table/sir20155032_table4-1.xls","text":"Appendix Table 4-1","size":"411 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix Table 4-1","linkHelpText":"Selected chemical characteristics of water samples collected by the U.S. Geological Survey in Geauga County, Ohio, 1978–2009."}],"country":"United States","county":"Geauga County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.41693115234375,\n 41.34588656996289\n ],\n [\n -81.41693115234375,\n 41.71085461169185\n ],\n [\n -80.9967041015625,\n 41.71085461169185\n ],\n [\n -80.9967041015625,\n 41.34588656996289\n ],\n [\n -81.41693115234375,\n 41.34588656996289\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7eef3e4b0bc0bec09ee14","contributors":{"authors":[{"text":"Jagucki, Martha L. 0000-0003-3798-8393 mjagucki@usgs.gov","orcid":"https://orcid.org/0000-0003-3798-8393","contributorId":1794,"corporation":false,"usgs":true,"family":"Jagucki","given":"Martha","email":"mjagucki@usgs.gov","middleInitial":"L.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kula, Stephanie P. spkula@usgs.gov","contributorId":4666,"corporation":false,"usgs":true,"family":"Kula","given":"Stephanie","email":"spkula@usgs.gov","middleInitial":"P.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mailot, Brian E. bemailot@usgs.gov","contributorId":2569,"corporation":false,"usgs":true,"family":"Mailot","given":"Brian","email":"bemailot@usgs.gov","middleInitial":"E.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":564108,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227709,"text":"70227709 - 2015 - Human harvest, climate change and their synergistic effects drove the Chinese Crested Tern to the brink of extinction","interactions":[],"lastModifiedDate":"2022-01-27T15:32:29.717459","indexId":"70227709","displayToPublicDate":"2015-07-03T09:11:12","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Human harvest, climate change and their synergistic effects drove the Chinese Crested Tern to the brink of extinction","docAbstract":"Synergistic effect refers to simultaneous actions of separate factors which have a greater total effect than the sum of the individual factor effects. However, there has been a limited knowledge on how synergistic effects occur and individual roles of different drivers are not often considered. Therefore, it becomes quite challenging to manage multiple threatening processes simultaneously in order to mitigate biodiversity loss. In this regard, our hypothesis is, if the traits actually play different roles in the synergistic interaction, conservation efforts could be made more effectively. To understand the synergistic effect and test our hypothesis, we examined the processes associated with the endangerment of critically endangered Chinese Crested Tern (Thalasseus bernsteini), whose total population number was estimated no more than 50. Through monitoring of breeding colonies and investigations into causative factors, combined with other data on human activities, we found that widespread human harvest of seabird eggs and increasing frequency of typhoons are the major factors that threatened the Chinese Crested Tern. Furthermore, 28 percent of breeding failures were due to the synergistic effects in which egg harvest-induced renestings suffered the higher frequent typhoons. In such combined interactions, the egg harvest has clearly served as a proximal factor for the population decline, and the superimposition of enhanced typhoon activity further accelerated the species toward imminent extinction. Our findings suggest that species endangerment, on one hand, should be treated as a synergistic process, while conservation efforts, on the other hand, should focus principally on combatting the threat that triggers synergistic effects.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2015.06.006","usgsCitation":"Chen, S., Fan, Z., Roby, D., Lu, Y., Chen, G., Huang, Q., Cheng, L., and Zhu, J., 2015, Human harvest, climate change and their synergistic effects drove the Chinese Crested Tern to the brink of extinction: Global Ecology and Conservation, v. 4, p. 137-145, https://doi.org/10.1016/j.gecco.2015.06.006.","productDescription":"9 p.","startPage":"137","endPage":"145","ipdsId":"IP-077723","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471953,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2015.06.006","text":"Publisher Index Page"},{"id":394970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 118.91601562499999,\n 26.82407078047018\n ],\n [\n 124.01367187499999,\n 26.82407078047018\n ],\n [\n 124.01367187499999,\n 34.161818161230386\n ],\n [\n 118.91601562499999,\n 34.161818161230386\n ],\n [\n 118.91601562499999,\n 26.82407078047018\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Shuihua","contributorId":272348,"corporation":false,"usgs":false,"family":"Chen","given":"Shuihua","email":"","affiliations":[],"preferred":false,"id":831968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fan, Zhongyong","contributorId":272349,"corporation":false,"usgs":false,"family":"Fan","given":"Zhongyong","email":"","affiliations":[],"preferred":false,"id":831969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roby, Daniel D. 0000-0001-9844-0992","orcid":"https://orcid.org/0000-0001-9844-0992","contributorId":272249,"corporation":false,"usgs":true,"family":"Roby","given":"Daniel D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":831857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Yiwei","contributorId":272354,"corporation":false,"usgs":false,"family":"Lu","given":"Yiwei","email":"","affiliations":[],"preferred":false,"id":831970,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Gangsong","contributorId":272355,"corporation":false,"usgs":false,"family":"Chen","given":"Gangsong","email":"","affiliations":[],"preferred":false,"id":831971,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huang, Qin","contributorId":272356,"corporation":false,"usgs":false,"family":"Huang","given":"Qin","email":"","affiliations":[],"preferred":false,"id":831972,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cheng, Lijing","contributorId":272357,"corporation":false,"usgs":false,"family":"Cheng","given":"Lijing","email":"","affiliations":[],"preferred":false,"id":831973,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhu, Jiang","contributorId":170401,"corporation":false,"usgs":false,"family":"Zhu","given":"Jiang","email":"","affiliations":[],"preferred":false,"id":831974,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70115013,"text":"70115013 - 2015 - Primative components, crustal assimilation, and magmatic degassing of the 2008 Kilauea summit eruption","interactions":[],"lastModifiedDate":"2015-11-16T16:11:12","indexId":"70115013","displayToPublicDate":"2015-07-02T14:09:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Primative components, crustal assimilation, and magmatic degassing of the 2008 Kilauea summit eruption","docAbstract":"Simultaneous summit and rift zone eruptions at Kīlauea starting in 2008 reflect a shallow eruptive plumbing system inundated by a bourgeoning supply of new magma from depth. Olivine-hosted melt inclusions, host glass, and bulk lava compositions of magma erupted at both the summit and east rift zone demonstrate chemical continuity at both ends of a well-worn summit-to-rift pipeline. Analysis of glass within dense-cored lapilli erupted from the summit in March – August 2008 show these are not samplings of compositionally distinct magmas stored in the shallow summit magma reservoir, but instead result from remelting and assimilation of fragments from conduit wall and vent blocks. Summit pyroclasts show the predominant and most primitive component erupted to be a homogenous, relatively trace-element-depleted melt that is a compositionally indistinguishable from east rift lava. Based on a “top-down” model for the geochemical variation in east rift zone lava over the past 30 years, we suggest that the apparent absence of a 1982 enriched component in melt inclusions, as well as the proposed summit-rift zone connectivity based on sulfur and mineral chemistry, indicate that the last of the pre-1983 magma has been flushed out of the summit reservoir during the surge of mantle-derived magma from 2003-2007.
","largerWorkTitle":"Hawaiian volcanoes, from source to surface","language":"English","publisher":"American Geophysical Union","usgsCitation":"Rowe, M.C., Thornber, C.R., and Orr, T., 2015, Primative components, crustal assimilation, and magmatic degassing of the 2008 Kilauea summit eruption, chap. of Hawaiian volcanoes, from source to surface, p. 439-457.","productDescription":"18 p.","startPage":"439","endPage":"457","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057405","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":311401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.2756118774414,\n 19.43162918399349\n ],\n [\n -155.25157928466797,\n 19.425153718960157\n ],\n [\n -155.23990631103513,\n 19.413821034154534\n ],\n [\n -155.2639389038086,\n 19.40443049681278\n ],\n [\n -155.2910614013672,\n 19.399896939902558\n ],\n [\n -155.29483795166016,\n 19.409935360334085\n ],\n [\n -155.28350830078125,\n 19.427743935948932\n ],\n [\n -155.2756118774414,\n 19.43162918399349\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564b0c57e4b0ebfbef0d3179","contributors":{"authors":[{"text":"Rowe, Michael C.","contributorId":79191,"corporation":false,"usgs":true,"family":"Rowe","given":"Michael","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":519011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thornber, Carl R. cthornber@usgs.gov","contributorId":2016,"corporation":false,"usgs":true,"family":"Thornber","given":"Carl","email":"cthornber@usgs.gov","middleInitial":"R.","affiliations":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":519009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orr, Tim R. torr@usgs.gov","contributorId":3766,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","email":"torr@usgs.gov","affiliations":[],"preferred":false,"id":519010,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70154794,"text":"70154794 - 2015 - A collision risk model to predict avian fatalities at wind facilities: an example using golden eagles, Aquila chrysaetos","interactions":[],"lastModifiedDate":"2015-07-06T11:41:25","indexId":"70154794","displayToPublicDate":"2015-07-02T12:45:00","publicationYear":"2015","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":"A collision risk model to predict avian fatalities at wind facilities: an example using golden eagles, Aquila chrysaetos","docAbstract":"Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is considerable uncertainty surrounding avian collision risk at wind facilities. This uncertainty is not reflected in many models currently used to predict the avian fatalities that would result from proposed wind developments. We introduce a method to predict fatalities at wind facilities, based on pre-construction monitoring. Our method can directly incorporate uncertainty into the estimates of avian fatalities and can be updated if information on the true number of fatalities becomes available from post-construction carcass monitoring. Our model considers only three parameters: hazardous footprint, bird exposure to turbines and collision probability. By using a Bayesian analytical framework we account for uncertainties in these values, which are then reflected in our predictions and can be reduced through subsequent data collection. The simplicity of our approach makes it accessible to ecologists concerned with the impact of wind development, as well as to managers, policy makers and industry interested in its implementation in real-world decision contexts. We demonstrate the utility of our method by predicting golden eagle (Aquila chrysaetos) fatalities at a wind installation in the United States. Using pre-construction data, we predicted 7.48 eagle fatalities year-1 (95% CI: (1.1, 19.81)). The U.S. Fish and Wildlife Service uses the 80th quantile (11.0 eagle fatalities year-1) in their permitting process to ensure there is only a 20% chance a wind facility exceeds the authorized fatalities. Once data were available from two-years of post-construction monitoring, we updated the fatality estimate to 4.8 eagle fatalities year-1 (95% CI: (1.76, 9.4); 80th quantile, 6.3). In this case, the increased precision in the fatality prediction lowered the level of authorized take, and thus lowered the required amount of compensatory mitigation.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0130978","usgsCitation":"New, L., Bjerre, E., Millsap, B.A., Otto, M.C., and Runge, M.C., 2015, A collision risk model to predict avian fatalities at wind facilities: an example using golden eagles, Aquila chrysaetos: PLoS ONE, v. 10, no. 7, p. 1-12, https://doi.org/10.1371/journal.pone.0130978.","productDescription":"12 p.","startPage":"1","endPage":"12","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049300","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471954,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0130978","text":"Publisher Index Page"},{"id":305581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-02","publicationStatus":"PW","scienceBaseUri":"559ba6a8e4b0b94a640170c5","contributors":{"authors":[{"text":"New, Leslie lnew@usgs.gov","contributorId":145484,"corporation":false,"usgs":true,"family":"New","given":"Leslie","email":"lnew@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":564175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bjerre, Emily","contributorId":44451,"corporation":false,"usgs":true,"family":"Bjerre","given":"Emily","affiliations":[],"preferred":false,"id":564176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Millsap, Brian A.","contributorId":75841,"corporation":false,"usgs":true,"family":"Millsap","given":"Brian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":564177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Otto, Mark C.","contributorId":6307,"corporation":false,"usgs":true,"family":"Otto","given":"Mark","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":564178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":564174,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70154807,"text":"70154807 - 2015 - Testing the thermal-niche oxygen-squeeze hypothesis for estuarine striped bass","interactions":[],"lastModifiedDate":"2015-09-10T15:17:54","indexId":"70154807","displayToPublicDate":"2015-07-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Testing the thermal-niche oxygen-squeeze hypothesis for estuarine striped bass","docAbstract":"In many stratified coastal ecosystems, conceptual and bioenergetics models predict seasonal reduction in quality and quantity of fish habitat due to high temperatures and hypoxia. We tested these predictions using acoustic telemetry of 2 to 4 kg striped bass (Morone saxatilis Walbaum) and high-resolution spatial water quality sampling in the Patuxent River, a sub-estuary of the Chesapeake Bay, during 2008 and 2009. Striped bass avoided hypoxic (dissolved oxygen ≤2 mg·l−1) subpycnocline waters, but frequently occupied habitats with high temperatures (>25 °C) in the summer months, as cooler habitats were typically not available. Using traditional concepts of the seasonal thermal-niche oxygen-squeeze, most of the Patuxent estuary would beconsidered unsuitable habitat for adult striped bass during summer. Application of a bioenergetics model revealed that habitats selected by striped bass during summer would support positive growth rates assuming fish could feed at one-half ofmaximum consumption. Occupancy of the estuary during summer by striped bass in this study was likely facilitated by sufficient prey and innate tolerance of high temperatures by sub-adult fish of the size range that we tagged. Our results help extend the thermalniche oxygen-squeeze hypothesis to native populations of striped bass in semi-enclosed coastal systems. Tolerance of for supraoptimal temperatures in our study supports recent suggestions by others that the thermal-niche concept for striped bass should be revised to include warmer temperatures.
","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10641-015-0431-3","usgsCitation":"Kraus, R.T., Secor, D., and Wingate, R.L., 2015, Testing the thermal-niche oxygen-squeeze hypothesis for estuarine striped bass: Environmental Biology of Fishes, v. 98, no. 10, p. 2083-2092, https://doi.org/10.1007/s10641-015-0431-3.","productDescription":"10 p.","startPage":"2083","endPage":"2092","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049336","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":305673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"10","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-02","publicationStatus":"PW","scienceBaseUri":"55a4e143e4b0183d66e453a8","contributors":{"authors":[{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":564215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Secor, D.H.","contributorId":99495,"corporation":false,"usgs":true,"family":"Secor","given":"D.H.","email":"","affiliations":[],"preferred":false,"id":564699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wingate, Rebecca L.","contributorId":145585,"corporation":false,"usgs":false,"family":"Wingate","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":564700,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70154789,"text":"70154789 - 2015 - Sea otter health: challenging a pet hypothesis","interactions":[],"lastModifiedDate":"2015-07-06T12:49:53","indexId":"70154789","displayToPublicDate":"2015-07-01T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2025,"text":"International Journal for Parasitology: Parasites and Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"Sea otter health: challenging a pet hypothesis","docAbstract":"A recent series of studies on tagged sea otters (Enhydra lutris nereis) challenges the hypothesis that sea otters are sentinels of a dirty ocean, in particular, that pet cats are the main source of exposure to Toxoplasma gondii in central California. Counter to expectations, sea otters from unpopulated stretches of coastline are less healthy and more exposed to parasites than city-associated otters. Ironically, now it seems that spillover from wildlife, not pets, dominates spatial patterns of disease transmission.
","language":"English","publisher":"Australian Society for Parasitology","publisherLocation":"Oxford","doi":"10.1016/j.ijppaw.2015.05.005","usgsCitation":"Lafferty, K.D., 2015, Sea otter health: challenging a pet hypothesis: International Journal for Parasitology: Parasites and Wildlife, v. 4, no. 3, p. 291-294, https://doi.org/10.1016/j.ijppaw.2015.05.005.","productDescription":"4 p.","startPage":"291","endPage":"294","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065768","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471956,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijppaw.2015.05.005","text":"Publisher Index Page"},{"id":305585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"559ba6b1e4b0b94a640170cf","contributors":{"authors":[{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":564165,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70154742,"text":"70154742 - 2015 - Southern San Andreas Fault seismicity is consistent with the Gutenberg-Richter magnitude-frequency distribution","interactions":[],"lastModifiedDate":"2015-08-03T10:26:16","indexId":"70154742","displayToPublicDate":"2015-07-01T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Southern San Andreas Fault seismicity is consistent with the Gutenberg-Richter magnitude-frequency distribution","docAbstract":"The magnitudes of any collection of earthquakes nucleating in a region are generally observed to follow the Gutenberg-Richter (G-R) distribution. On some major faults, however, paleoseismic rates are higher than a G-R extrapolation from the modern rate of small earthquakes would predict. This, along with other observations, led to formulation of the characteristic earthquake hypothesis, which holds that the rate of small to moderate earthquakes is permanently low on large faults relative to the large-earthquake rate (Wesnousky et al., 1983; Schwartz and Coppersmith, 1984). We examine the rate difference between recent small to moderate earthquakes on the southern San Andreas fault (SSAF) and the paleoseismic record, hypothesizing that the discrepancy can be explained as a rate change in time rather than a deviation from G-R statistics. We find that with reasonable assumptions, the rate changes necessary to bring the small and large earthquake rates into alignment agree with the size of rate changes seen in epidemic-type aftershock sequence (ETAS) modeling, where aftershock triggering of large earthquakes drives strong fluctuations in the seismicity rates for earthquakes of all magnitudes. The necessary rate changes are also comparable to rate changes observed for other faults worldwide. These results are consistent with paleoseismic observations of temporally clustered bursts of large earthquakes on the SSAF and the absence of M greater than or equal to 7 earthquakes on the SSAF since 1857.
","language":"English","publisher":"Seismological Society of Amercia","doi":"10.1785/0120140340","usgsCitation":"Page, M.T., and Felzer, K., 2015, Southern San Andreas Fault seismicity is consistent with the Gutenberg-Richter magnitude-frequency distribution: Bulletin of the Seismological Society of America, v. 105, no. 4, p. 2070-2080, https://doi.org/10.1785/0120140340.","productDescription":"11 p.","startPage":"2070","endPage":"2080","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060995","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":305534,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Southern San Andreas Fault","volume":"105","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-16","publicationStatus":"PW","scienceBaseUri":"55950123e4b0b6d21dd6cbc0","contributors":{"authors":[{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":563889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Felzer, Karen 0000-0003-0828-5525 kfelzer@usgs.gov","orcid":"https://orcid.org/0000-0003-0828-5525","contributorId":145408,"corporation":false,"usgs":true,"family":"Felzer","given":"Karen","email":"kfelzer@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":563890,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155220,"text":"70155220 - 2015 - Social living mitigates the costs of a chronic illness in a cooperative carnivore","interactions":[],"lastModifiedDate":"2018-08-09T12:52:14","indexId":"70155220","displayToPublicDate":"2015-07-01T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Social living mitigates the costs of a chronic illness in a cooperative carnivore","docAbstract":"Infection risk is assumed to increase with social group size, and thus be a cost of group living. We assess infection risk and costs with respect to group size using data from an epidemic of sarcoptic mange (Sarcoptes scabiei) among grey wolves (Canis lupus). We demonstrate that group size does not predict infection risk and that individual costs of infection, in terms of reduced survival, can be entirely offset by having sufficient numbers of pack-mates. Infected individuals experience increased mortality hazards with increasing proportions of infected pack-mates, but healthy individuals remain unaffected. The social support of group hunting and territory defence are two possible mechanisms mediating infection costs. This is likely a common phenomenon among other social species and chronic infections, but difficult to detect in systems where infection status cannot be measured continuously over time.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford","doi":"10.1111/ele.12444","usgsCitation":"Almberg, E., Cross, P.C., Dobson, A.P., Smith, D.W., Metz, M., Stahler, D.R., and Hudson, P., 2015, Social living mitigates the costs of a chronic illness in a cooperative carnivore: Ecology Letters, v. 18, no. 7, p. 660-667, https://doi.org/10.1111/ele.12444.","productDescription":"8 p.","startPage":"660","endPage":"667","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062430","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.12444","text":"Publisher Index Page"},{"id":306321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-18","publicationStatus":"PW","scienceBaseUri":"55c090b5e4b033ef521042b7","chorus":{"doi":"10.1111/ele.12444","url":"http://dx.doi.org/10.1111/ele.12444","publisher":"Wiley-Blackwell","authors":"Almberg E. 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Although there are advantages and disadvantages to each approach, we suggest that there is no unique best way to analyze data. Further, we argue that, although multimodel inference can be useful in natural resource management, the importance of considering causality and accurately estimating effect sizes is greater than simply considering a variety of models. Determining causation is far more valuable than simply indicating how the response variable and explanatory variables covaried within a data set, especially when the data set did not arise from a controlled experiment. Understanding the causal mechanism will provide much better predictions beyond the range of data observed. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Washington, D.C.","doi":"10.1002/jwmg.894","usgsCitation":"Fieberg, J., and Johnson, D.H., 2015, MMI: Multimodel inference or models with management implications?: Journal of Wildlife Management, v. 79, no. 5, p. 708-718, https://doi.org/10.1002/jwmg.894.","productDescription":"11 p.","startPage":"708","endPage":"718","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059993","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471958,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.894","text":"Publisher Index Page"},{"id":308443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-25","publicationStatus":"PW","scienceBaseUri":"5603cd4ee4b03bc34f544b25","contributors":{"authors":[{"text":"Fieberg, J.","contributorId":106070,"corporation":false,"usgs":true,"family":"Fieberg","given":"J.","affiliations":[],"preferred":false,"id":572697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Douglas H. 0000-0002-7778-6641 douglas_h_johnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":1387,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas","email":"douglas_h_johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":572696,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70154750,"text":"70154750 - 2015 - Training conservation practitioners to be better decision makers","interactions":[],"lastModifiedDate":"2015-07-01T11:31:29","indexId":"70154750","displayToPublicDate":"2015-07-01T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Training conservation practitioners to be better decision makers","docAbstract":"Traditional conservation curricula and training typically emphasizes only one part of systematic decision making (i.e., the science), at the expense of preparing conservation practitioners with critical skills in values-setting, working with decision makers and stakeholders, and effective problem framing. In this article we describe how the application of decision science is relevant to conservation problems and suggest how current and future conservation practitioners can be trained to be better decision makers. Though decision-analytic approaches vary considerably, they all involve: (1) properly formulating the decision problem; (2) specifying feasible alternative actions; and (3) selecting criteria for evaluating potential outcomes. Two approaches are available for providing training in decision science, with each serving different needs. Formal education is useful for providing simple, well-defined problems that allow demonstrations of the structure, axioms and general characteristics of a decision-analytic approach. In contrast, practical training can offer complex, realistic decision problems requiring more careful structuring and analysis than those used for formal training purposes. Ultimately, the kinds and degree of training necessary depend on the role conservation practitioners play in a decision-making process. Those attempting to facilitate decision-making processes will need advanced training in both technical aspects of decision science and in facilitation techniques, as well as opportunities to apprentice under decision analysts/consultants. Our primary goal should be an attempt to ingrain a discipline for applying clarity of thought to all decisions.
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Sea otters are well known for structuring nearshore ecosystems and causing community-level changes such as increases in kelp abundance and changes in the size and number of other consumers. Monitoring population status of sea otters in Glacier Bay will help park researchers and managers understand and interpret sea otter-induced ecosystem changes relative to other sources of variation, including potential human-induced impacts such as ocean acidification, vessel disturbance, and oil spills. This report was prepared for the National Park Service (NPS), Southeast Alaska Inventory and Monitoring Network following a request for evaluation of options for monitoring sea otter population status in Glacier Bay National Park and Preserve. To meet this request, we provide a detailed consideration of the primary method of assessment of abundance and distribution, aerial surveys, including analyses of power to detect interannual trends and designs to reduce variation around annual abundance estimates. We also describe two alternate techniques for evaluating sea otter population status—(1) quantifying sea otter diets and energy intake rates, and (2) detecting change in ages at death. In addition, we provide a brief section on directed research to identify studies that would further our understanding of sea otter population dynamics and effects on the Glacier Bay ecosystem, and provide context for interpreting results of monitoring activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151119","collaboration":"National Park Service, Southeast Alaska Inventory and Monitoring Network","usgsCitation":"Esslinger, G.G., Esler, D., Howlin, S., and Starcevich, L.A., 2015, Monitoring population status of sea otters (Enhydra lutris) in Glacier Bay National Park and Preserve, Alaska—Options and considerations: U.S. Geological Survey Open-File Report 2015-1119, 42 p., https://dx.doi.org/10.3133/ofr20151119.","productDescription":"iv, 42 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066127","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":305530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151119.jpg"},{"id":305529,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1119/"},{"id":302337,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1119/pdf/ofr20151119.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1119"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay National Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -136.67404174804688,\n 58.84146431191663\n ],\n [\n -135.90911865234375,\n 58.84643781578906\n ],\n [\n -135.80474853515622,\n 58.39091676201985\n ],\n [\n -136.05880737304688,\n 58.37507825384993\n ],\n [\n -136.37741088867188,\n 58.58686725348443\n ],\n [\n -136.56005859375,\n 58.58400407034718\n ],\n [\n -136.67404174804688,\n 58.84146431191663\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
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Anchorage, Alaska 99508-4560
http://alaska.usgs.gov
Polar bears (Ursus maritimus) summer on the sea ice or, where it melts, on shore. Although the physiology of “ice” bears in summer is unknown, “shore” bears purportedly minimize energy losses by entering a hibernation-like state when deprived of food. Such a strategy could partially compensate for the loss of on-ice foraging opportunities caused by climate change. However, here we report gradual, moderate declines in activity and body temperature of both shore and ice bears in summer, resembling energy expenditures typical of fasting, nonhibernating mammals. Also, we found that to avoid unsustainable heat loss while swimming, bears employed unusual heterothermy of the body core. Thus, although well adapted to seasonal ice melt, polar bears appear susceptible to deleterious declines in body condition during the lengthening period of summer food deprivation.
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