{"pageNumber":"493","pageRowStart":"12300","pageSize":"25","recordCount":40783,"records":[{"id":70170258,"text":"70170258 - 2016 - Host contact and shedding patterns clarify variation in pathogen exposure and transmission in threatened tortoise <i>Gopherus agassizii</i>: implications for disease modelling and management","interactions":[],"lastModifiedDate":"2016-04-28T13:14:26","indexId":"70170258","displayToPublicDate":"2016-04-14T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Host contact and shedding patterns clarify variation in pathogen exposure and transmission in threatened tortoise <i>Gopherus agassizii</i>: implications for disease modelling and management","docAbstract":"<h1 class=\"article-section__header\">Summary</h1>\n<ol id=\"jane12511-list-0001\" class=\"o-list--numbered o-list--paragraph\">\n<li>Most directly transmitted infections require some form of close contact between infectious and susceptible hosts to spread. Often disease models assume contacts are equal and use mean field estimates of transmission probability for all interactions with infectious hosts.</li>\n<li>Such methods may inaccurately describe transmission when interactions differ substantially in their ability to cause infection. Understanding this variation in transmission risk may be critical to properly model and manage some infectious diseases. In this study, we investigate how varying exposure and transmission may be key to understanding disease dynamics in the threatened desert tortoise&nbsp;<i>Gopherus agassizii</i>.</li>\n<li>We created heterogeneity in&nbsp;<i>Mycoplasma agassizii</i>&nbsp;exposure (the putative bacterial agent of a respiratory disease) by varying the duration of interactions between naturally infected and uninfected captive desert tortoises. Using qPCR, we identified new infections and compared models of transmission probability as a function of contact duration and pathogen load. We then examined the contact patterns of a wild tortoise population using proximity loggers to identify heterogeneity in contact duration.</li>\n<li>The top-ranked model predicting&nbsp;<i>M.&nbsp;agassizii</i>&nbsp;transmission included a dose term defined as the product of the number of days in proximity to an infected host and the infection level of that host. Models predicted low transmission probability for short interactions, unless the infectious host had a high load of&nbsp;<i>M.&nbsp;agassizii</i>: such hosts were predicted to transmit infection at higher rates with any amount of contact. We observed predominantly short-lived interactions in a free-ranging tortoise population and thus, expect transmission patterns in this population to vary considerably with the frequency and duration of high infection levels.</li>\n<li>Mean field models may misrepresent natural transmission patterns in this and other populations depending on the distribution of high-risk contact and shedding events. Rapid outbreaks in generally solitary species may result from changes to their naturally low-risk contact patterns or due to increases in the frequency of severe infections or super-shedding events &ndash; population characteristics that should be further investigated to develop effective management strategies.</li>\n</ol>","language":"English","publisher":"University Press","doi":"10.1111/1365-2656.12511","usgsCitation":"Aiello, C.M., Nussear, K.E., Esque, T., Emblidge, P.G., Sah, P., Bansal, S., and Hudson, P., 2016, Host contact and shedding patterns clarify variation in pathogen exposure and transmission in threatened tortoise <i>Gopherus agassizii</i>: implications for disease modelling and management: Journal of Animal Ecology, v. 85, no. 3, p. 829-842, https://doi.org/10.1111/1365-2656.12511.","productDescription":"14 p.","startPage":"829","endPage":"842","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068200","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471070,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12511","text":"Publisher Index Page"},{"id":438620,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78W3BC8","text":"USGS data release","linkHelpText":"Estimates of pathogen exposure predict varying transmission likelihood: Host contact and shedding patterns may clarify disease dynamics in desert tortoises Gopherus agassizii"},{"id":320044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","city":"Las Vegas","otherGeospatial":"Desert Tortoise Conservation Center","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          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Center","active":true,"usgs":true}],"preferred":false,"id":626654,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Emblidge, Patrick G. pemblidge@usgs.gov","contributorId":5800,"corporation":false,"usgs":true,"family":"Emblidge","given":"Patrick","email":"pemblidge@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":626655,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sah, Pratha","contributorId":127768,"corporation":false,"usgs":false,"family":"Sah","given":"Pratha","email":"","affiliations":[{"id":7145,"text":"Department of Biology, Georgetown University, Washington DC","active":true,"usgs":false}],"preferred":false,"id":626656,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bansal, Shweta","contributorId":168595,"corporation":false,"usgs":false,"family":"Bansal","given":"Shweta","email":"","affiliations":[{"id":25339,"text":"Dep't of Biology, Georgetown U., Washington D.C., NIH, Bethesda, MD","active":true,"usgs":false}],"preferred":false,"id":626657,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hudson, Peter J.","contributorId":85056,"corporation":false,"usgs":true,"family":"Hudson","given":"Peter J.","affiliations":[],"preferred":false,"id":626658,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70174180,"text":"70174180 - 2016 - Using climate, energy, and spatial-based hypotheses to interpret macroecological patterns of North America chelonians","interactions":[],"lastModifiedDate":"2016-06-29T16:43:17","indexId":"70174180","displayToPublicDate":"2016-04-14T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Using climate, energy, and spatial-based hypotheses to interpret macroecological patterns of North America chelonians","docAbstract":"<p>Our study investigates how factors, such as latitude, productivity, and several environmental variables, influence contemporary patterns of the species richness in North American turtles. In particular, we test several hypotheses explaining broad-scale species richness patterns on several species richness data sets: (<i>i</i>) total turtles, (<i>ii</i>) freshwater turtles only, (<i>iii</i>) aquatic turtles, (<i>iv</i>) terrestrial turtles only, (<i>v</i>) Emydidae, and (<i>vi</i>) Kinosternidae. In addition to spatial data, we used a combination of 25 abiotic variables in spatial regression models to predict species richness patterns. Our results provide support for multiple hypotheses related to broad-scale patterns of species richness, and in particular, hypotheses related to climate, productivity, water availability, topography, and latitude. In general, species richness patterns were positively associated with temperature, precipitation, diversity of streams, coefficient of variation of elevation, and net primary productivity. We also found that North America turtles follow the general latitudinal diversity gradient pattern (i.e., increasing species richness towards equator) by exhibiting a negative association with latitude. Because of the incongruent results among our six data sets, our study highlights the importance of considering phylogenetic constraints and guilds when interpreting species richness patterns, especially for taxonomic groups that occupy a myriad of habitats.</p>","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjz-2016-0033","usgsCitation":"Ennen, J.R., Agha, M., Matamoros, W.A., Hazzard, S.C., and Lovich, J.E., 2016, Using climate, energy, and spatial-based hypotheses to interpret macroecological patterns of North America chelonians: Canadian Journal of Zoology, v. 94, p. 453-461, https://doi.org/10.1139/cjz-2016-0033.","productDescription":"9 p.","startPage":"453","endPage":"461","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065530","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471072,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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]\n}","volume":"94","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774f30be4b07dd077c6ae41","contributors":{"authors":[{"text":"Ennen, Joshua R.","contributorId":83858,"corporation":false,"usgs":true,"family":"Ennen","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":641162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false},{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":641165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matamoros, Wilfredo A.","contributorId":172518,"corporation":false,"usgs":false,"family":"Matamoros","given":"Wilfredo","email":"","middleInitial":"A.","affiliations":[{"id":27060,"text":"Facultad de Ciencias Biologicas, Universidad de Cencias y Artes de Chiapas, Museo de Zoologia, Tuxtla Gutiérrez, Chiapas, México Apartado Postal 29000, México","active":true,"usgs":false}],"preferred":false,"id":641163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hazzard, Sarah C.","contributorId":172519,"corporation":false,"usgs":false,"family":"Hazzard","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":27061,"text":"Tennessee Aquarium Conservation Institute, Tennessee Aquarium, 201 Chestnut Street, Chattanooga, TN, 37402 USA","active":true,"usgs":false}],"preferred":false,"id":641164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":641161,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70170243,"text":"70170243 - 2016 - Natural inactivation of <i>Escherichia coli</i> in anoxic and reduced groundwater","interactions":[],"lastModifiedDate":"2016-05-19T10:32:30","indexId":"70170243","displayToPublicDate":"2016-04-13T15:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2169,"text":"Journal of Applied Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Natural inactivation of <i>Escherichia coli</i> in anoxic and reduced groundwater","docAbstract":"<h3>Aims</h3>\n<p>Inactivation rates of&nbsp;<i>E. coli</i>&nbsp;in groundwater have most often been determined in aerobic and oxidized systems. This study examined&nbsp;<i>E. coli</i>&nbsp;inactivation rates in anaerobic and extremely reduced groundwater systems that have been identified as recharge zones.</p>\n<h3>Methods and Results</h3>\n<p>Groundwater from six artesian wells was diverted to above ground, flow through mesocosms that contained laboratory grown&nbsp;<i>E. coli</i>&nbsp;in diffusion chambers. All groundwater was anaerobic and extremely reduced (ORP &lt;&nbsp;<span>-</span>300 mV). Cells were plated onto mTEC agar during 21 day incubation periods. All data fit a bi-phasic inactivation model, with &gt; 95% of the&nbsp;<i>E. coli</i>&nbsp;population being inactivated &lt; 11.0 hrs (mean&nbsp;<i>k</i>&nbsp;= 0.488&plusmn; 0.188 h<span>&minus;1</span>).</p>\n<h3>Conclusions</h3>\n<p>The groundwater geochemical conditions enhanced the inactivation of&nbsp;<i>E. coli</i>&nbsp;to rates approximately 21-fold greater than previously published inactivation rate in groundwater (mean&nbsp;<i>k</i>= 0.023 &plusmn; 0.030 h<span>&minus;1</span>). Also, mTEC agar inhibits&nbsp;<i>E. coli</i>&nbsp;growth following exposure to anaerobic and reduced groundwater.</p>\n<h3>Significance and Impact of the Study</h3>\n<p>Aquifer recharge zones with geochemical characteristics observed in this study complement above ground engineered processes (e.g., filtration, disinfection), while increasing the overall indicator microorganism log-reduction rate of a facility.</p>","language":"English","publisher":"Wiley","doi":"10.1111/jam.13126","usgsCitation":"Lisle, J.T., 2016, Natural inactivation of <i>Escherichia coli</i> in anoxic and reduced groundwater: Journal of Applied Microbiology, v. 120, no. 6, p. 1739-1750, https://doi.org/10.1111/jam.13126.","productDescription":"12 p.","startPage":"1739","endPage":"1750","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066446","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jam.13126","text":"Publisher Index Page"},{"id":320030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"570f5f9ce4b0ef3b7ca3295a","chorus":{"doi":"10.1111/jam.13126","url":"http://dx.doi.org/10.1111/jam.13126","publisher":"Wiley-Blackwell","authors":"Lisle J.T.","journalName":"Journal of Applied Microbiology","publicationDate":"5/13/2016","auditedOn":"11/8/2016"},"contributors":{"authors":[{"text":"Lisle, John T. 0000-0002-5447-2092 jlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-5447-2092","contributorId":2944,"corporation":false,"usgs":true,"family":"Lisle","given":"John","email":"jlisle@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":626594,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70169005,"text":"sir20165029 - 2016 - Flood-inundation maps for a 9.1-mile reach of the Coast Fork Willamette River near Creswell and Goshen, Lane County, Oregon","interactions":[],"lastModifiedDate":"2016-04-13T15:20:35","indexId":"sir20165029","displayToPublicDate":"2016-04-13T12:40:00","publicationYear":"2016","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":"2016-5029","title":"Flood-inundation maps for a 9.1-mile reach of the Coast Fork Willamette River near Creswell and Goshen, Lane County, Oregon","docAbstract":"<p>Digital flood-inundation maps for a 9.1-mile reach of the Coast Fork Willamette River near Creswell and Goshen, Oregon, were developed by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers (USACE). The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation/\" target=\"_blank\" data-mce-href=\"http://water.usgs.gov/osw/flood_inundation/\">http://water.usgs.gov/osw/flood_inundation/</a>, depict estimates of the areal extent and depth of flooding corresponding to selected stages at the USGS streamgage at Coast Fork Willamette River near Goshen, Oregon (14157500), at State Highway 58. Current stage at the streamgage for estimating near-real-time areas of inundation may be obtained at <a href=\"http://waterdata.usgs.gov/or/nwis/uv/?site_no=14157500&amp;PARAmeter_cd=00065,00060\" target=\"_blank\" data-mce-href=\"http://waterdata.usgs.gov/or/nwis/uv/?site_no=14157500&amp;PARAmeter_cd=00065,00060\">http://waterdata.usgs.gov/or/nwis/uv/?site_no=14157500&amp;PARAmeter_cd=00065,00060</a>. In addition, the National Weather Service (NWS) forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.</p><p>In this study, areas of inundation were provided by USACE. The inundated areas were developed from flood profiles simulated by a one-dimensional unsteady step‑backwater hydraulic model. The profiles were checked by the USACE using documented high-water marks from a January 2006 flood. The model was compared and quality assured using several other methods. The hydraulic model was then used to determine eight water-surface profiles at various flood stages referenced to the streamgage datum and ranging from 11.8 to 19.8 ft, approximately 2.6 ft above the highest recorded stage at the streamgage (17.17 ft) since 1950. The intervals between stages are variable and based on annual exceedance probability discharges, some of which approximate NWS action stages.</p><p>The areas of inundation and water depth grids provided to USGS by USACE were used to create interactive flood‑inundation maps. The availability of these maps with current stage from USGS streamgage and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures as well as for post flood recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165029","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Hess, G.W., and Haluska, T.L., 2016, Flood-inundation maps for a 9.1-mile reach of the Coast Fork Willamette River near Creswell and Goshen, Lane County, Oregon: U.S. Geological Survey Scientific Investigations Report 2016–5029, 8 p., https://dx.doi.org/10.3133/sir20165029.","productDescription":"Report: vi, 8 p.; Metadata","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053101","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":319983,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5029/sir20165029.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5029 Report PDF"},{"id":319984,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2016/5029/sir20165029_metadata.html"},{"id":319982,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5029/coverthb.jpg"}],"country":"United States","state":"Oregon","county":"Lane County","city":"Creswell, Goshen","otherGeospatial":"Willamette River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.98370361328124,\n              44.00318741021592\n            ],\n            [\n              -122.99022674560545,\n              43.9942964557587\n            ],\n            [\n              -122.96688079833984,\n              43.987133329129215\n            ],\n            [\n              -122.99571990966798,\n              43.95649503643676\n            ],\n            [\n              -122.99606323242188,\n              43.914959878503154\n            ],\n            [\n              -122.98542022705078,\n              43.914959878503154\n            ],\n            [\n              -122.97683715820312,\n              43.94339481559037\n            ],\n            [\n              -122.9813003540039,\n              43.95328204198018\n            ],\n            [\n              -122.9541778564453,\n              43.990838502564706\n            ],\n            [\n              -122.97958374023438,\n              43.9965193192732\n            ],\n            [\n              -122.9754638671875,\n              44.00219959217852\n            ],\n            [\n              -122.98370361328124,\n              44.00318741021592\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, Oregon Water Science Center<br>U.S. Geological Survey<br>2130 SW 5th Avenue<br>Portland, Oregon 97201<br><a href=\"http://or.water.usgs.gov\" data-mce-href=\"http://or.water.usgs.gov\">http://or.water.usgs.gov</a><br></p>","tableOfContents":"<ul>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Water-Surface Profiles and Stage‑Discharge Ratings</li>\n<li>Development of Flood-Inundation Maps</li>\n<li>Summary</li>\n<li>Acknowledgments</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-04-13","noUsgsAuthors":false,"publicationDate":"2016-04-13","publicationStatus":"PW","scienceBaseUri":"570f5f9ce4b0ef3b7ca32950","contributors":{"authors":[{"text":"Hess, Glen W.","contributorId":19136,"corporation":false,"usgs":true,"family":"Hess","given":"Glen","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":622472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haluska, Tana 0000-0001-6307-4769 thaluska@usgs.gov","orcid":"https://orcid.org/0000-0001-6307-4769","contributorId":1708,"corporation":false,"usgs":true,"family":"Haluska","given":"Tana","email":"thaluska@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622473,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170212,"text":"70170212 - 2016 - The Chahnaly low sulfidation epithermal gold deposit, western Makran volcanic arc, southeastern Iran","interactions":[],"lastModifiedDate":"2016-04-13T08:48:49","indexId":"70170212","displayToPublicDate":"2016-04-13T08:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"The Chahnaly low sulfidation epithermal gold deposit, western Makran volcanic arc, southeastern Iran","docAbstract":"<p id=\"p-1\">The Chahnaly low-sulfidation epithermal Au deposit and nearby Au prospects are located northwest of the intermittently active Bazman stratovolcano on the western end of the Makran volcanic arc, which formed as the result of subduction of the remnant Neo-Tethyan oceanic crust beneath the Lut block. The arc hosts the Siah Jangal epithermal and Kharestan porphyry prospects, near Taftan volcano, as well as the Saindak Cu-Au porphyry deposit and world-class Reko Diq Cu-Au porphyry deposit, near Koh-i-Sultan volcano to the east-northeast in Pakistan. The host rocks for the Chahnaly deposit include early Miocene andesite and andesitic volcaniclastic rocks that are intruded by younger dacitic domes. Unaltered late Miocene dacitic ignimbrites overlie these rocks. Laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) U-Pb zircon geochronology data yield ages between 21.8 and 9.9 Ma for the acidic-intermediate regional volcanism. The most recent volcanic activity of the Bazman stratovolcano involved extrusion of an olivine basalt during Pliocene to Quaternary times. Interpretation of geochemical data indicate that the volcanic rocks are synsubduction and calc-alkaline to subalkaline. The lack of a significant negative Eu anomaly, a listric-shaped rare earth element pattern, and moderate La/Yb ratios of host suites indicate a high water content of the source magma.</p>\n<p id=\"p-2\">Gold and electrum are temporally and spatially related to a series of structurally controlled, 030&deg;-trending, subvertical hydrothermal breccias with chalcedony-adularia that cut porphyritic andesite and andesitic volcaniclastic rocks. Gold is associated with pyrite, a siliceous matrix of hydrothermal breccia, and previously formed vein clasts, as well as with iron oxides and hydroxides in oxidized zones. Rare silver minerals include Ag-bearing electrum and naumannite, iodargyrite, an unnamed silver diiodide, and hessite. Hydrothermal alteration is generally well developed surrounding the ore-bearing hydrothermal breccia. The main types of alteration in the area include an inner ~0.5- to 20-m-thick gold-bearing hydrothermal breccia composed of quartz-chalcedonyadularia-illite-pyrite, a ~5- to 50-m-thick zone of quartz, chalcedony, pyrite, illitic phengite, phengite, illitic muscovite, illite, illitic paragonite, paragonite, muscovite, montmorillonite and, rarely, siderite, and a 30- to 70-m outer propylitic zone of Fe-Mg chlorite, calcite, ankerite, dolomite, epidote, palygorskite, and pyrite.</p>\n<p id=\"p-3\">The Chahnaly Au deposit formed during the early stages of magmatism. LA-ICP-MS zircon U-Pb geochronology of host andesite and 40Ar/39Ar dating of two samples of gold-associated adularia show that the ore-stage adularia (19.83 &plusmn; 0.10 and 19.2 &plusmn; 0.5 Ma) is younger, by as much as 1.5 million years, than the volcanic host rock (20.32 &plusmn; 0.4 Ma). Therefore, either hydrothermal activity continued well after volcanism or a second magmatic event rejuvenated hydrothermal activity. This second magmatic event may be related to eruption of porphyritic andesite at ~20.32 &plusmn; 0.40 Ma, which is within error of ~19.83 &plusmn; 0.10 Ma adularia. The new LA-ICP-MS zircon U-Pb host rock and vein adularia 40Ar/39Ar ages suggest that early Miocene magmatism and mineralization in the Bazman area is of a similar age to that of the Saindak porphyry and Tanjeel porphyry center of the giant Reko Diq deposit. This confirms the existence of early Miocene arc magmatism and mineralization along the Iranian part of the Makran volcanic arc. Ore, alteration mineralogy, and alteration patterns indicate that the Chahnaly deposit is a typical low-sulfidation epithermal Au deposit, located in a poorly explored part of the Makran volcanic arc in Iran. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</p>","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.3.619","usgsCitation":"Sholeh, A., Rastad, E., Huston, D.L., Gemmell, J.B., and Taylor, R.D., 2016, The Chahnaly low sulfidation epithermal gold deposit, western Makran volcanic arc, southeastern Iran: Economic Geology, v. 111, no. 3, p. 619-639, https://doi.org/10.2113/econgeo.111.3.619.","productDescription":"21 p.","startPage":"619","endPage":"639","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055033","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":320016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran, Pakistan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              60.216064453125,\n              27.98470011861268\n            ],\n            [\n              60.216064453125,\n              29.869228848968312\n            ],\n            [\n              63.4075927734375,\n              29.869228848968312\n            ],\n            [\n              63.4075927734375,\n              27.98470011861268\n            ],\n            [\n              60.216064453125,\n              27.98470011861268\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"111","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-08","publicationStatus":"PW","scienceBaseUri":"570f5f9de4b0ef3b7ca32970","contributors":{"authors":[{"text":"Sholeh, Ali","contributorId":168565,"corporation":false,"usgs":false,"family":"Sholeh","given":"Ali","email":"","affiliations":[{"id":25338,"text":"Tarbiat Modares University","active":true,"usgs":false}],"preferred":false,"id":626483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rastad, Ebrahim","contributorId":119934,"corporation":false,"usgs":true,"family":"Rastad","given":"Ebrahim","email":"","affiliations":[],"preferred":false,"id":626484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huston, David L.","contributorId":67139,"corporation":false,"usgs":true,"family":"Huston","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":626485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gemmell, J. Bruce","contributorId":168566,"corporation":false,"usgs":false,"family":"Gemmell","given":"J.","email":"","middleInitial":"Bruce","affiliations":[{"id":16141,"text":"University of Tasmania","active":true,"usgs":false}],"preferred":false,"id":626486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":626482,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70170469,"text":"70170469 - 2016 - Ecosystem level methane fluxes from tidal freshwater and brackish marshes of the Mississippi River Delta: Implications for coastal wetland carbon projects","interactions":[],"lastModifiedDate":"2016-08-25T08:34:10","indexId":"70170469","displayToPublicDate":"2016-04-12T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem level methane fluxes from tidal freshwater and brackish marshes of the Mississippi River Delta: Implications for coastal wetland carbon projects","docAbstract":"<p><span>Sulfate from seawater inhibits methane production in tidal wetlands, and by extension, salinity has been used as a general predictor of methane emissions. With the need to reduce methane flux uncertainties from tidal wetlands, eddy covariance (EC) techniques provide an integrated methane budget. The goals of this study were to: 1) establish methane emissions from natural, freshwater and brackish wetlands in Louisiana based on EC; and 2) determine if EC estimates conform to a methane-salinity relationship derived from temperate tidal wetlands with chamber sampling. Annual estimates of methane emissions from this study were 62.3&nbsp;g CH</span><sub><span>4</span></sub><span>/m</span><sup><span>2</span></sup><span>/yr and 13.8&nbsp;g CH</span><sub><span>4</span></sub><span>/m</span><sup><span>2</span></sup><span>/yr for the freshwater and brackish (8–10&nbsp;psu) sites, respectively. If it is assumed that long-term, annual soil carbon sequestration rates of natural marshes are ~200&nbsp;g C/m</span><sup><span>2</span></sup><span>/yr (7.3 tCO</span><sub><span>2</span></sub><span>e/ha/yr), healthy brackish marshes could be expected to act as a net radiative sink, equivalent to less than one-half the soil carbon accumulation rate after subtracting methane emissions (4.1 tCO</span><sub><span>2</span></sub><span>e/ha/yr). Carbon sequestration rates would need case-by-case assessment, but the EC methane emissions estimates in this study conformed well to an existing salinity-methane model that should serve as a basis for establishing emission factors for wetland carbon offset projects.</span></p>","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-016-0746-7","usgsCitation":"Holm, G., Perez, B.C., McWhorter, D.E., Krauss, K.W., Johnson, D., Raynie, R.C., and Killebrew, C.J., 2016, Ecosystem level methane fluxes from tidal freshwater and brackish marshes of the Mississippi River Delta: Implications for coastal wetland carbon projects: Wetlands, v. 36, no. 3, p. 401-413, https://doi.org/10.1007/s13157-016-0746-7.","productDescription":"13 p.","startPage":"401","endPage":"413","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066949","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":320398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.2032470703125,\n              29.940655389125002\n            ],\n            [\n              -90.2911376953125,\n              30.007273923504556\n            ],\n            [\n              -90.4998779296875,\n              30.007273923504556\n            ],\n            [\n              -90.68115234375,\n              29.869228848968312\n            ],\n            [\n              -90.758056640625,\n              29.692824739380754\n            ],\n            [\n              -90.7415771484375,\n              29.511330027309146\n            ],\n            [\n              -90.52734374999999,\n              29.420460341013133\n            ],\n            [\n              -90.19775390625,\n              29.477861195816843\n            ],\n            [\n              -90.1593017578125,\n              29.7453016622136\n            ],\n            [\n              -90.2032470703125,\n              29.940655389125002\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-12","publicationStatus":"PW","scienceBaseUri":"571b4b2de4b071321fe31c63","contributors":{"authors":[{"text":"Holm, Guerry O.","contributorId":79219,"corporation":false,"usgs":true,"family":"Holm","given":"Guerry O.","affiliations":[],"preferred":false,"id":627337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perez, Brian C.","contributorId":42286,"corporation":false,"usgs":true,"family":"Perez","given":"Brian","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":627338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McWhorter, David E.","contributorId":168801,"corporation":false,"usgs":false,"family":"McWhorter","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":18062,"text":"CH2MHILL, Austin, TX","active":true,"usgs":false}],"preferred":false,"id":627339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":627336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Darren J.","contributorId":100291,"corporation":false,"usgs":true,"family":"Johnson","given":"Darren J.","affiliations":[],"preferred":false,"id":627340,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Raynie, Richard C.","contributorId":168802,"corporation":false,"usgs":false,"family":"Raynie","given":"Richard","email":"","middleInitial":"C.","affiliations":[{"id":13608,"text":"Louisiana Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":627341,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Killebrew, Charles J.","contributorId":168803,"corporation":false,"usgs":false,"family":"Killebrew","given":"Charles","email":"","middleInitial":"J.","affiliations":[{"id":13608,"text":"Louisiana Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":627342,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70177031,"text":"70177031 - 2016 - Estimating evapotranspiration and groundwater flow from water-table fluctuations for a general wetland scenario","interactions":[],"lastModifiedDate":"2016-10-17T16:04:56","indexId":"70177031","displayToPublicDate":"2016-04-12T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating evapotranspiration and groundwater flow from water-table fluctuations for a general wetland scenario","docAbstract":"The use of diurnal water-table fluctuation methods to calculate evapotranspiration (ET) and groundwater flow is of increasing interest in ecohydrological studies. Most studies of this type, however, have been located in riparian wetlands of semi-arid regions where groundwater levels are consistently below topographic surface elevations and precipitation events are infrequent. Current methodologies preclude application to a wider variety of wetland systems. In this study, we extended a method for estimating sub-daily ET and groundwater flow rates from water-level fluctuations to fit highly dynamic, non-riparian wetland scenarios. Modifications included (1) varying the specific yield to account for periodic flooded conditions and (2) relating empirically derived ET to estimated potential ET for days when precipitation events masked the diurnal signal. To demonstrate the utility of this method, we estimated ET and groundwater fluxes over two growing seasons (2006–2007) in 15 wetlands within a ridge-and-swale wetland complex of the Laurentian Great Lakes under flooded and non-flooded conditions. Mean daily ET rates for the sites ranged from 4.0 mm d−1 to 6.6 mm d−1. Shallow groundwater discharge rates resulting from evaporative demand ranged from 2.5 mm d−1 to 4.3 mm d−1. This study helps to expand our understanding of the evapotranspirative demand of plants under various hydrologic and climate conditions. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.","language":"English","publisher":"John Wiley & Sons","publisherLocation":"Hoboken, NJ","doi":"10.1002/eco.1356","usgsCitation":"Weber, L.C., Wiley, M.J., and Wilcox, D., 2016, Estimating evapotranspiration and groundwater flow from water-table fluctuations for a general wetland scenario: Ecohydrology, v. 7, no. 2, p. 378-390, https://doi.org/10.1002/eco.1356.","productDescription":"13 p.","startPage":"378","endPage":"390","numberOfPages":"13","ipdsId":"IP-018006","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471080,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/2027.42/106891","text":"External Repository"},{"id":329644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":329620,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/eco.1356/abstract"}],"volume":"7","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2013-01-07","publicationStatus":"PW","scienceBaseUri":"5805e34fe4b0824b2d1c24c2","contributors":{"authors":[{"text":"Weber, Lisa C.","contributorId":124586,"corporation":false,"usgs":true,"family":"Weber","given":"Lisa","email":"","middleInitial":"C.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":651055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiley, Michael J.","contributorId":139111,"corporation":false,"usgs":false,"family":"Wiley","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":651057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilcox, Douglas 0000-0002-2871-4131","orcid":"https://orcid.org/0000-0002-2871-4131","contributorId":175418,"corporation":false,"usgs":false,"family":"Wilcox","given":"Douglas","email":"","affiliations":[{"id":27569,"text":"SUNY – College at Brockport","active":true,"usgs":false}],"preferred":false,"id":651056,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70170199,"text":"70170199 - 2016 - Quaternary alluvial fans of Ciudad Juárez, Chihuahua, northern México: OSL ages and implications for climatic history of the region","interactions":[],"lastModifiedDate":"2020-12-17T19:11:05.395441","indexId":"70170199","displayToPublicDate":"2016-04-11T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5070,"text":"Boletín de la Sociedad Geológica Mexicana","active":true,"publicationSubtype":{"id":10}},"title":"Quaternary alluvial fans of Ciudad Juárez, Chihuahua, northern México: OSL ages and implications for climatic history of the region","docAbstract":"<p><span>Alluvial fans formed from sediments derived from erosion of the Juárez Mountains in northernmost México have a significant flood impact on the Ciudad Juárez, which is built on the fan system. The northern part of Ciudad Juárez is the most active; further south, older parts of the fan, upon which the rest of the city is built, were largely eroded by natural processes prior to human habitation and subsequently modified only recently by human construction. Three aeolian sand samples, collected from the uppermost (youngest) parts of the fan system in the city area, in places where human intervention has not disturbed the sediment, and constrain the latest dates of fan building. Depositional ages of the Quaternary alluvial fans were measured using Optically Stimulated Luminescence (OSL) on aeolian sands that have inter-fingered with alluvial fan material. These dates are: a) sample P1, 31 ka; b) sample P2, 41 ka; c) sample P3, 74 ka, between Oxygen Isotope Stages (OIS) 3 to 5. They demonstrate that fan development, in the area now occupied by the city, terminated in the Late Pleistocene, immediately after what we interpret to have been an extended period of erosion without further deposition, lasting from the Late Pleistocene to Holocene. The three dates broadly correspond to global glacial periods, implying that the cool, dry periods may reflect periods of aeolian transport in northern México in between phases that were wetter to form the alluvial fans. Alluvial fan margins inter-finger with fluvial terrace sediments derived from the Río Bravo, indicating an additional component of fan dissection by Río Bravo lateral erosion, presumed to be active during earlier times than our OSL ages, but these are not yet dated. Further dating is required to ascertain the controls on the fan and fluvial system.</span></p>","language":"English","publisher":"Sociedad Geológica Mexicana","doi":"10.18268/BSGM2016v68n1a13","usgsCitation":"Zuniga de Leon, D., Kershaw, S., and Mahan, S.A., 2016, Quaternary alluvial fans of Ciudad Juárez, Chihuahua, northern México: OSL ages and implications for climatic history of the region: Boletín de la Sociedad Geológica Mexicana, v. 68, no. 1, p. 111-128, https://doi.org/10.18268/BSGM2016v68n1a13.","productDescription":"18 p.","startPage":"111","endPage":"128","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064242","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":471081,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.18268/bsgm2016v68n1a13","text":"Publisher Index Page"},{"id":319967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","city":"Ciudad Juarez","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.5289306640625,\n              31.630290821551032\n            ],\n            [\n              -106.5289306640625,\n              31.753860822284455\n            ],\n            [\n              -106.42353057861327,\n              31.753860822284455\n            ],\n            [\n              -106.42353057861327,\n              31.630290821551032\n            ],\n            [\n              -106.5289306640625,\n              31.630290821551032\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"68","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"570cbc9ae4b0ef3b7ca0dbd6","contributors":{"authors":[{"text":"Zuniga de Leon, David","contributorId":168549,"corporation":false,"usgs":false,"family":"Zuniga de Leon","given":"David","email":"","affiliations":[{"id":25331,"text":"University of Juárez, Chihuahua, México","active":true,"usgs":false}],"preferred":false,"id":626373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kershaw, Stephen","contributorId":168550,"corporation":false,"usgs":false,"family":"Kershaw","given":"Stephen","email":"","affiliations":[{"id":25332,"text":"Institute for the Environment, Brunel University, Uxbridge, UB8 3PH, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":626374,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":626372,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70168417,"text":"ofr20161018 - 2016 - Revisions to the original extent of the Devonian Shale-Middle and Upper Paleozoic Total Petroleum System","interactions":[],"lastModifiedDate":"2018-01-08T13:20:27","indexId":"ofr20161018","displayToPublicDate":"2016-04-11T14:15:00","publicationYear":"2016","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":"2016-1018","title":"Revisions to the original extent of the Devonian Shale-Middle and Upper Paleozoic Total Petroleum System","docAbstract":"<p>Technically recoverable undiscovered hydrocarbon resources in continuous accumulations are present in Upper Devonian and Lower Mississippian strata in the Appalachian Basin Petroleum Province. The province includes parts of New York, Pennsylvania, Ohio, Maryland, West Virginia, Virginia, Kentucky, Tennessee, Georgia, and Alabama. The Upper Devonian and Lower Mississippian strata are part of the previously defined Devonian Shale-Middle and Upper Paleozoic Total Petroleum System (TPS) that extends from New York to Tennessee. This publication presents a revision to the extent of the Devonian Shale-Middle and Upper Paleozoic TPS. The most significant modification to the maximum extent of the Devonian Shale-Middle and Upper Paleozoic TPS is to the south and southwest, adding areas in Tennessee, Georgia, Alabama, and Mississippi where Devonian strata, including potential petroleum source rocks, are present in the subsurface up to the outcrop. The Middle to Upper Devonian Chattanooga Shale extends from southeastern Kentucky to Alabama and eastern Mississippi. Production from Devonian shale has been established in the Appalachian fold and thrust belt of northeastern Alabama. Exploratory drilling has encountered Middle to Upper Devonian strata containing organic-rich shale in west-central Alabama. The areas added to the TPS are located in the Valley and Ridge, Interior Low Plateaus, and Appalachian Plateaus physiographic provinces, including the portion of the Appalachian fold and thrust belt buried beneath Cretaceous and younger sediments that were deposited on the U.S. Gulf Coastal Plain.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161018","usgsCitation":"Enomoto, C.B., Rouse, W.A., Trippi, M.H., and Higley, D.K., 2016, Revisions to the original extent of the Devonian Shale-Middle and Upper Paleozoic Total Petroleum System: U.S. Geological Survey Open-File Report 2016–1018, 6 p., https://dx.doi.org/10.3133/ofr20161018.","productDescription":"Report: iv, 6 p.; Shapefiles; Metadata Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068927","costCenters":[{"id":241,"text":"Eastern Energy Resources Science 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,{"id":70170127,"text":"70170127 - 2016 - Tree-ring-based estimates of long-term seasonal precipitation in the Souris River Region of Saskatchewan, North Dakota and Manitoba","interactions":[],"lastModifiedDate":"2017-10-12T19:56:27","indexId":"70170127","displayToPublicDate":"2016-04-11T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1180,"text":"Canadian Water Resources Journal","active":true,"publicationSubtype":{"id":10}},"title":"Tree-ring-based estimates of long-term seasonal precipitation in the Souris River Region of Saskatchewan, North Dakota and Manitoba","docAbstract":"<p>Historically unprecedented flooding occurred in the Souris River Basin of Saskatchewan, North Dakota and Manitoba in 2011, during a longer term period of wet conditions in the basin. In order to develop a model of future flows, there is a need to evaluate effects of past multidecadal climate variability and/or possible climate change on precipitation. In this study, tree-ring chronologies and historical precipitation data in a four-degree buffer around the Souris River Basin were analyzed to develop regression models that can be used for predicting long-term variations of precipitation. To focus on longer term variability, 12-year moving average precipitation was modeled in five subregions (determined through cluster analysis of measures of precipitation) of the study area over three seasons (November&ndash;February, March&ndash;June and July&ndash;October). The models used multiresolution decomposition (an additive decomposition based on powers of two using a discrete wavelet transform) of tree-ring chronologies from Canada and the US and seasonal 12-year moving average precipitation based on Adjusted and Homogenized Canadian Climate Data and US Historical Climatology Network data. Results show that precipitation varies on long-term (multidecadal) time scales of 16, 32 and 64 years. Past extended pluvial and drought events, which can vary greatly with season and subregion, were highlighted by the models. Results suggest that the recent wet period may be a part of natural variability on a very long time scale.</p>","language":"English","publisher":"Taylor & Francis Online","doi":"10.1080/07011784.2016.1164627","usgsCitation":"Ryberg, K.R., Vecchia, A.V., Akyuz, F.A., and Lin, W., 2016, Tree-ring-based estimates of long-term seasonal precipitation in the Souris River Region of Saskatchewan, North Dakota and Manitoba: Canadian Water Resources Journal, v. 41, no. 3, p. 412-428, https://doi.org/10.1080/07011784.2016.1164627.","productDescription":"17 p.","startPage":"412","endPage":"428","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061513","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":319955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Manitoba, North Dakota, Saskatchewan","otherGeospatial":"Souris River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.798828125,\n              47.5913464767971\n            ],\n            [\n              -103.798828125,\n              50.45750402042058\n            ],\n            [\n              -98.89892578125,\n              50.45750402042058\n            ],\n            [\n              -98.89892578125,\n              47.5913464767971\n            ],\n            [\n              -103.798828125,\n              47.5913464767971\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"41","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"570cbc9ce4b0ef3b7ca0dbe5","chorus":{"doi":"10.1080/07011784.2016.1164627","url":"http://dx.doi.org/10.1080/07011784.2016.1164627","publisher":"Informa UK Limited","authors":"Ryberg Karen R., Vecchia Aldo V., Akyüz F. Adnan, Lin Wei","journalName":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","publicationDate":"4/5/2016"},"contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401 avecchia@usgs.gov","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":1173,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"avecchia@usgs.gov","middleInitial":"V.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Akyuz, F. 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,{"id":70170406,"text":"70170406 - 2016 - Hg concentrations in fish from coastal waters of California and Western North America","interactions":[],"lastModifiedDate":"2018-08-07T12:23:12","indexId":"70170406","displayToPublicDate":"2016-04-09T13:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Hg concentrations in fish from coastal waters of California and Western North America","docAbstract":"<p><span>The State of California conducted an extensive and systematic survey of mercury (Hg) in fish from the California coast in 2009 and 2010. The California survey sampled 3483 fish representing 46 species at 68 locations, and demonstrated that methylHg in fish presents a widespread exposure risk to fish consumers. Most of the locations sampled (37 of 68) had a species with an average concentration above 0.3&nbsp;&mu;g/g&nbsp;wet weight (ww), and 10 locations an average above 1.0&nbsp;&mu;g/g&nbsp;ww. The recent and robust dataset from California provided a basis for a broader examination of spatial and temporal patterns in fish Hg in coastal waters of Western North America. There is a striking lack of data in publicly accessible databases on Hg and other contaminants in coastal fish. An assessment of the raw data from these databases suggested the presence of relatively high concentrations along the California coast and in Puget Sound, and relatively low concentrations along the coasts of Alaska and Oregon, and the outer coast of Washington. The dataset suggests that Hg concentrations of public health concern can be observed at any location on the coast of Western North America where long-lived predator species are sampled. Output from a linear mixed-effects model resembled the spatial pattern observed for the raw data and suggested, based on the limited dataset, a lack of trend in fish Hg over the nearly 30-year period covered by the dataset. Expanded and continued monitoring, accompanied by rigorous data management procedures, would be of great value in characterizing methylHg exposure, and tracking changes in contamination of coastal fish in response to possible increases in atmospheric Hg emissions in Asia, climate change, and terrestrial Hg control efforts in coastal watersheds.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.093","usgsCitation":"Davis, J., Ross, J., Bezalel, S., Sim, L., Bonnema, A., Ichikawa, G., Heim, W., Schiff, K., Eagles-Smith, C.A., and Ackerman, J., 2016, Hg concentrations in fish from coastal waters of California and Western North America: Science of the Total Environment, v. 568, p. 1146-1156, https://doi.org/10.1016/j.scitotenv.2016.03.093.","productDescription":"11 p.","startPage":"1146","endPage":"1156","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073269","costCenters":[{"id":290,"text":"Forest and Rangeland 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,{"id":70157329,"text":"sir20155137 - 2016 - Hydraulic model and flood-inundation maps developed for the Pee Dee National Wildlife Refuge, North Carolina","interactions":[],"lastModifiedDate":"2017-01-18T13:22:46","indexId":"sir20155137","displayToPublicDate":"2016-04-08T10:45:00","publicationYear":"2016","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":"2015-5137","title":"Hydraulic model and flood-inundation maps developed for the Pee Dee National Wildlife Refuge, North Carolina","docAbstract":"<p>A one-dimensional step-backwater model was developed by the U.S. Geological Survey (USGS) in cooperation with the U.S. Fish and Wildlife Service, Pee Dee National Wildlife Refuge, North Carolina, to provide a means for predicting flood-plain inundation. The model was developed for selected reaches of the Pee Dee River, Brown Creek, and Rocky River, using the U.S. Army Corps of Engineers Hydrologic Engineering Center River Analysis System (HEC-RAS) software. Multiple cross sections were defined on each modeled stream, and hydrologic data were collected between August 2011 and August 2013 at selected locations on the Pee Dee River and on its tributaries Brown Creek, Rocky River, and Thoroughfare Creek. Cross-section, stage, and flow data were used to develop the model and&nbsp;simulate water-surface profiles at 1.0-foot increments at the USGS streamgage Pee Dee River at Pee Dee Refuge near Ansonville, N.C. The profiles were produced for 31 selected water levels that ranged from approximately 193.0 feet to 223.0 feet in elevation at the Pee Dee River at Pee Dee Refuge streamgage.</p>\n<p>A series of digital flood-inundation maps were developed on the basis of the water-surface profiles produced by the model. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation\">http://water.usgs.gov/osw/flood_inundation</a>, depict estimates of the areal extent and depth of flooding corresponding to selected water levels at the USGS streamgage Pee Dee River at Pee Dee Refuge near Ansonville, N.C. These maps, when combined with real-time water-level information from USGS streamgages, provide managers with critical information to help plan flood-response activities and resource protection efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155137","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Smith, D.G., and Wagner, C.R., 2016, Hydraulic model and flood-inundation maps developed for the Pee Dee National Wildlife Refuge, North Carolina: U.S. Geological Survey Scientific Investigations Report 2015–5137, 14 p., https://dx.doi.org/10.3133/sir20155137.","productDescription":"Document: vi, 14 p.; Metadata: 3 downloadable files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069288","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":319758,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137.pdf","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5137"},{"id":319789,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137_peedee.xml","size":"15.6 KB xml","description":"SIR 2015-5137"},{"id":319787,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137_peedee-grids.zip","size":"302 MB grids","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5137"},{"id":319788,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5137/sir20155137_peedee-shapefiles.zip","size":"18.8 MB","linkFileType":{"id":4,"text":"shapefile"},"description":"SIR 2015-5137"},{"id":319757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5137/coverthb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Pee Dee National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.266667,\n              35.233333\n            ],\n            [\n              -80.266667,\n              35\n            ],\n            [\n              -79.85,\n              35\n            ],\n            [\n              -79.85,\n              35.233333\n            ],\n            [\n              -80.266667,\n              35.233333\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, South Atlantic Water Science Center<br> U.S. Geological Survey<br> 720 Gracern Road<br> Columbia, SC 29210<br> <a href=\"http://www.usgs.gov/water/southatlantic/\" data-mce-href=\"http://www.usgs.gov/water/southatlantic/\">http://www.usgs.gov/water/southatlantic/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Constructing Water-Surface Profiles</li><li>Inundation Mapping</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"publishedDate":"2016-04-08","noUsgsAuthors":false,"publicationDate":"2016-04-08","publicationStatus":"PW","scienceBaseUri":"572477a9e4b0b13d3914e097","contributors":{"authors":[{"text":"Smith, Douglas G. dgsmith@usgs.gov","contributorId":1532,"corporation":false,"usgs":true,"family":"Smith","given":"Douglas","email":"dgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572699,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Chad R. 0000-0002-9602-7413 cwagner@usgs.gov","orcid":"https://orcid.org/0000-0002-9602-7413","contributorId":1530,"corporation":false,"usgs":true,"family":"Wagner","given":"Chad R.","email":"cwagner@usgs.gov","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":false,"id":572700,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170185,"text":"70170185 - 2016 - An analysis of water data systems to inform the Open Water Data Initiative","interactions":[],"lastModifiedDate":"2016-08-04T15:36:35","indexId":"70170185","displayToPublicDate":"2016-04-08T09:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"An analysis of water data systems to inform the Open Water Data Initiative","docAbstract":"<p><span>Improving access to data and fostering open exchange of water information is foundational to solving water resources issues. In this vein, the Department of the Interior's Assistant Secretary for Water and Science put forward the charge to undertake an Open Water Data Initiative (OWDI) that would prioritize and accelerate work toward better water data infrastructure. The goal of the OWDI is to build out the Open Water Web (OWW). We therefore considered the OWW in terms of four conceptual functions: water data cataloging, water data as a service, enriching water data, and community for water data. To describe the current state of the OWW and identify areas needing improvement, we conducted an analysis of existing systems using a standard model for describing distributed systems and their business requirements. Our analysis considered three OWDI-focused use cases&mdash;flooding, drought, and contaminant transport&mdash;and then examined the landscape of other existing applications that support the Open Water Web. The analysis, which includes a discussion of observed successful practices of cataloging, serving, enriching, and building community around water resources data, demonstrates that we have made significant progress toward the needed infrastructure, although challenges remain. The further development of the OWW can be greatly informed by the interpretation and findings of our analysis.</span></p>","language":"English","publisher":"American Water Resources Associaton","publisherLocation":"Herndon, VA","doi":"10.1111/1752-1688.12417","usgsCitation":"Blodgett, D.L., Read, E.K., Lucido, J., Slawecki, T., and Young, D., 2016, An analysis of water data systems to inform the Open Water Data Initiative: Journal of the American Water Resources Association, v. 52, no. 4, p. 845-858, https://doi.org/10.1111/1752-1688.12417.","productDescription":"14 p.","startPage":"845","endPage":"858","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071340","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":471083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12417","text":"Publisher Index Page"},{"id":319943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-08","publicationStatus":"PW","scienceBaseUri":"570ccaace4b0ef3b7ca14703","contributors":{"authors":[{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":626327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Read, Emily K. 0000-0002-9617-9433 eread@usgs.gov","orcid":"https://orcid.org/0000-0002-9617-9433","contributorId":5815,"corporation":false,"usgs":true,"family":"Read","given":"Emily","email":"eread@usgs.gov","middleInitial":"K.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":false,"id":626328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucido, Jessica M. jlucido@usgs.gov","contributorId":4695,"corporation":false,"usgs":true,"family":"Lucido","given":"Jessica M.","email":"jlucido@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":626329,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slawecki, Tad","contributorId":168540,"corporation":false,"usgs":false,"family":"Slawecki","given":"Tad","email":"","affiliations":[{"id":25325,"text":"LimnoTech, 501 Avis Drive, Ann Arbor, Michigan, USA 48108","active":true,"usgs":false}],"preferred":false,"id":626330,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, Dwane","contributorId":168541,"corporation":false,"usgs":false,"family":"Young","given":"Dwane","affiliations":[{"id":25326,"text":"U.S. Environmental Protection Agency, 1200 Pennsylvania Ave., NW, Washington, DC, USA  20460","active":true,"usgs":false}],"preferred":false,"id":626331,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70188535,"text":"70188535 - 2016 - Tomographic Rayleigh-wave group velocities in the Central Valley, California centered on the Sacramento/San Joaquin Delta","interactions":[],"lastModifiedDate":"2017-06-14T15:14:42","indexId":"70188535","displayToPublicDate":"2016-04-08T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Tomographic Rayleigh-wave group velocities in the Central Valley, California centered on the Sacramento/San Joaquin Delta","docAbstract":"If shaking from a local or regional earthquake in the San Francisco Bay region were to rupture levees in the Sacramento/San Joaquin Delta then brackish water from San Francisco Bay would contaminate the water in the Delta: the source of fresh water for about half of California. As a prelude to a full shear-wave velocity model that can be used in computer simulations and further seismic hazard analysis, we report on the use of ambient noise tomography to build a fundamental-mode, Rayleigh-wave group velocity model for the region around the Sacramento/San Joaquin Delta in the western Central Valley, California. Recordings from the vertical component of about 31 stations were processed to compute the spatial distribution of Rayleigh wave group velocities. Complex coherency between pairs of stations were stacked over 8 months to more than a year. Dispersion curves were determined from 4 to about 18 seconds. We calculated average group velocities for each period and inverted for deviations from the average for a matrix of cells that covered the study area. Smoothing using the first difference is applied.  Cells of the model were about 5.6 km in either dimension. Checkerboard tests of resolution, which is dependent on station density, suggest that the resolving ability of the array is reasonably good within the middle of the array with resolution between 0.2 and 0.4 degrees. Overall, low velocities in the middle of each image reflect the deeper sedimentary syncline in the Central Valley. In detail, the model shows several centers of low velocity that may be associated with gross geologic features such as faulting along the western margin of the Central Valley, oil and gas reservoirs, and large cross cutting features like the Stockton arch. At shorter periods around 5.5s, the model’s western boundary between low and high velocities closely follows regional fault geometry and the edge of a residual isostatic gravity low. In the eastern part of the valley, the boundaries of the low velocity zone and gravity anomaly are better aligned at longer periods (around 10.5s) suggesting that the eastern edge of the gravity low is associated with deeper structure. There is a strong correspondence between a low in gravity near the Kirby Hills fault and low velocities from the ambient noise tomography.  At longer periods, higher velocities creep in from the east and narrow the overall dimension defined by the lower velocities. Overall, there is a strong correspondence between the shape and location of low velocities in the Rayleigh wave velocity images, and geological and geophysical features.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB012376","usgsCitation":"Fletcher, J.P., Erdem, J., Seats, K., and Lawrence, J., 2016, Tomographic Rayleigh-wave group velocities in the Central Valley, California centered on the Sacramento/San Joaquin Delta: Journal of Geophysical Research B: Solid Earth, v. 121, no. 4, p. 2429-2446, https://doi.org/10.1002/2015JB012376.","productDescription":"18 p. ","startPage":"2429","endPage":"2446","ipdsId":"IP-062590","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471084,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012376","text":"Publisher Index Page"},{"id":342506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley, Sacramento/San Joaquin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.7117919921875,\n              39.89709437260048\n            ],\n            [\n              -122.01416015625,\n              38.225235239076824\n            ],\n            [\n              -121.4813232421875,\n              37.63163475580643\n            ],\n            [\n              -121.00341796874999,\n              37.08585785263673\n            ],\n            [\n              -120.67932128906249,\n              36.730079507078415\n            ],\n            [\n              -118.55895996093749,\n              37.53150992479082\n            ],\n            [\n              -118.7017822265625,\n              38.043765107439675\n            ],\n            [\n              -119.08630371093749,\n              38.543869175876154\n            ],\n            [\n              -119.80590820312499,\n              39.317300373271024\n            ],\n            [\n              -120.2838134765625,\n              39.774769485295465\n            ],\n            [\n              -120.948486328125,\n              40.29628651711716\n            ],\n            [\n              -121.31103515625,\n              40.53050177574321\n            ],\n            [\n              -121.97021484374999,\n              40.53050177574321\n            ],\n            [\n              -122.398681640625,\n              40.40094763151963\n            ],\n            [\n              -122.72277832031251,\n              40.225024210604964\n            ],\n            [\n              -122.7117919921875,\n              39.89709437260048\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"121","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-08","publicationStatus":"PW","scienceBaseUri":"59424b39e4b0764e6c65dc30","contributors":{"authors":[{"text":"Fletcher, Jon Peter B. 0000-0001-8885-6177 jfletcher@usgs.gov","orcid":"https://orcid.org/0000-0001-8885-6177","contributorId":1216,"corporation":false,"usgs":true,"family":"Fletcher","given":"Jon","email":"jfletcher@usgs.gov","middleInitial":"Peter B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":698169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erdem, Jemile 0000-0003-2353-9431 jerdem@usgs.gov","orcid":"https://orcid.org/0000-0003-2353-9431","contributorId":127700,"corporation":false,"usgs":true,"family":"Erdem","given":"Jemile","email":"jerdem@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":698172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seats, Kevin","contributorId":192927,"corporation":false,"usgs":false,"family":"Seats","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":698170,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Jesse","contributorId":192928,"corporation":false,"usgs":false,"family":"Lawrence","given":"Jesse","affiliations":[],"preferred":false,"id":698171,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70170099,"text":"70170099 - 2016 - Influence of manatees' diving on their risk of collision with watercraft","interactions":[],"lastModifiedDate":"2016-07-11T15:44:59","indexId":"70170099","displayToPublicDate":"2016-04-07T10:30:00","publicationYear":"2016","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":"Influence of manatees' diving on their risk of collision with watercraft","docAbstract":"<p><span>Watercraft pose a threat to endangered Florida manatees (</span><i>Trichechus manatus latirostris</i><span>). Mortality from watercraft collisions has adversely impacted the manatee population&rsquo;s growth rate, therefore reducing this threat is an important management goal. To assess factors that contribute to the risk of watercraft strikes to manatees, we studied the diving behavior of nine manatees carrying GPS tags and time&ndash;depth recorders in Tampa Bay, Florida, during winters 2002&ndash;2006. We applied a Bayesian formulation of generalized linear mixed models to depth data to model the probability (</span><i>P</i><sub><i>t</i></sub><span>) that manatees would be no deeper than 1.25 m from the water&rsquo;s surface as a function of behavioral and habitat covariates. Manatees above this threshold were considered to be within striking depth of a watercraft. Seventy-eight percent of depth records (individual range 62&ndash;86%) were within striking depth (mean = 1.09 m, max = 16.20 m), illustrating how vulnerable manatees are to strikes. In some circumstances manatees made consecutive dives to the bottom while traveling, even in areas &gt;14 m, possibly to conserve energy. This is the first documentation of potential cost-efficient diving behavior in manatees. Manatees were at higher risk of being within striking depth in shallow water (&lt;0.91 m), over seagrass, at night, and while stationary or moving slowly; they were less likely to be within striking depth when &le;50 m from a charted waterway. In shallow water the probability of a manatee being within striking depth was 0.96 (CI = 0.93&ndash;0.98) and decreased as water depth increased. The probability was greater over seagrass (</span><i>P</i><sub><i>t</i></sub><span><span class=\"Apple-converted-space\">&nbsp;</span></span><i>=</i><span><span class=\"Apple-converted-space\">&nbsp;</span>0.96, CI = 0.93&ndash;0.98) than over other substrates (</span><i>P</i><sub><i>t</i></sub><span><span class=\"Apple-converted-space\">&nbsp;</span>= 0.73, CI = 0.58&ndash;0.84). Quantitative approaches to assessing risk can improve the effectiveness of manatee conservation measures by helping identify areas for protection.</span></p>","language":"English","publisher":"PLos One","doi":"10.1371/journal.pone.0151450","usgsCitation":"Edwards, H.H., Martin, J., Deutsch, C., Muller, R.G., Koslovsky, S.M., Smith, A., and Barlas, M., 2016, Influence of manatees' diving on their risk of collision with watercraft: PLoS ONE, v. 11, no. 4, 15 p., https://doi.org/10.1371/journal.pone.0151450.","productDescription":"15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060636","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0151450","text":"Publisher Index Page"},{"id":319882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.76275634765625,\n              28.13133880763851\n            ],\n            [\n              -82.4139404296875,\n              28.06228599981216\n            ],\n            [\n              -82.3260498046875,\n              27.81357174811185\n            ],\n            [\n              -82.47299194335936,\n              27.410785702577023\n            ],\n            [\n              -82.72018432617188,\n              27.42297612892041\n            ],\n            [\n              -82.84790039062499,\n              27.847576211806295\n            ],\n            [\n              -82.85888671875,\n              28.02592458049937\n            ],\n            [\n              -82.84515380859375,\n              28.13133880763851\n            ],\n            [\n              -82.77374267578125,\n              28.13739395116007\n            ],\n            [\n              -82.76275634765625,\n              28.13133880763851\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-06","publicationStatus":"PW","scienceBaseUri":"5710bf30e4b0ef3b7ca55149","contributors":{"authors":[{"text":"Edwards, Holly H.","contributorId":66419,"corporation":false,"usgs":true,"family":"Edwards","given":"Holly","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":626165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Julien 0000-0002-7375-129X julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":626164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deutsch, Charles J.","contributorId":64135,"corporation":false,"usgs":true,"family":"Deutsch","given":"Charles J.","affiliations":[],"preferred":false,"id":626166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muller, Robert G","contributorId":168507,"corporation":false,"usgs":false,"family":"Muller","given":"Robert","email":"","middleInitial":"G","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":626167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koslovsky, Stacie M.","contributorId":168508,"corporation":false,"usgs":false,"family":"Koslovsky","given":"Stacie","email":"","middleInitial":"M.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":626168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Alexander J.","contributorId":140345,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander J.","affiliations":[{"id":13464,"text":"Environmental Analyst, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":626169,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barlas, Margie E.","contributorId":168510,"corporation":false,"usgs":false,"family":"Barlas","given":"Margie E.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":626170,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70170463,"text":"70170463 - 2016 - Integrated assessment of wastewater treatment plant effluent estrogenicity in the Upper Murray River, Australia, using the native Murray rainbowfish (<i>Melanotaenia fluviatilis</i>)","interactions":[],"lastModifiedDate":"2018-08-09T12:33:24","indexId":"70170463","displayToPublicDate":"2016-04-07T06:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Integrated assessment of wastewater treatment plant effluent estrogenicity in the Upper Murray River, Australia, using the native Murray rainbowfish (<i>Melanotaenia fluviatilis</i>)","docAbstract":"<p><span>The contamination of major continental river systems by endocrine-active chemicals (EACs) derived from the discharge of wastewater treatment plant (WWTP) effluents can affect human and ecosystem health. As part of a long-term effort to develop a native fish model organism for assessment of endocrine disruption in Australia's largest watershed, the Murray-Darling River Basin, the present study evaluated endocrine disruption in adult males of the native Australian Murray rainbowfish (<i>Melanotaenia fluviatilis</i>) exposed to effluent from an activated sludge WWTP and water from the Murray River during a 28-d, continuous-flow, on-site experiment. Analysis of the WWTP effluent and river water detected estrone and 17&beta;-estradiol at concentrations up to approximately 25&thinsp;ng&thinsp;L</span><sup><span>&minus;1</span></sup><span>. Anti-estrogenicity of effluent samples was detected in vitro using yeast-based bioassays (yeast estrogen screen) throughout the experiment, but estrogenicity was limited to the first week of the experiment. Histological evaluation of the testes indicated significant suppression of spermatogenesis by WWTP effluent after 28&thinsp;d of exposure. Plasma vitellogenin concentrations and expression of vitellogenin messenger RNA in liver were not significantly affected by exposure to WWTP effluent. The combination of low contaminant concentrations in the WWTP effluent, limited endocrine disrupting effects in the Murray rainbowfish, and high in-stream dilution factors (&gt;99%) suggest minimal endocrine disruption impacts on native Australian fish in the Murray River downstream from the WWTP outfall.&nbsp;</span></p>","language":"English","publisher":"Elsevier Science","doi":"10.1002/etc.2895","usgsCitation":"Vajda, A.M., Kumar, A., Woods, M., Williams, M., Doan, H., Tolsher, P., Kookana, R.S., and Barber, L.B., 2016, Integrated assessment of wastewater treatment plant effluent estrogenicity in the Upper Murray River, Australia, using the native Murray rainbowfish (<i>Melanotaenia fluviatilis</i>): Environmental Toxicology and Chemistry, v. 34, no. 5, p. 1078-1087, https://doi.org/10.1002/etc.2895.","productDescription":"10 p.","startPage":"1078","endPage":"1087","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062599","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":320526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Upper Murray River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              145.5908203125,\n              -27.215556209029675\n            ],\n            [\n              145.5908203125,\n              -28.265682390146466\n            ],\n            [\n              145.4150390625,\n              -29.228890030194215\n            ],\n            [\n              144.7119140625,\n              -30.486550842588485\n            ],\n            [\n              143.4375,\n              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CO","active":true,"usgs":false}],"preferred":false,"id":627312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kumar, Anupama","contributorId":168793,"corporation":false,"usgs":false,"family":"Kumar","given":"Anupama","email":"","affiliations":[{"id":25361,"text":"CSIRO Land and Water, Adelaide, South Australia","active":true,"usgs":false}],"preferred":false,"id":627313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woods, Marianne","contributorId":168794,"corporation":false,"usgs":false,"family":"Woods","given":"Marianne","email":"","affiliations":[{"id":25361,"text":"CSIRO Land and Water, Adelaide, South Australia","active":true,"usgs":false}],"preferred":false,"id":627314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Mike","contributorId":168795,"corporation":false,"usgs":false,"family":"Williams","given":"Mike","email":"","affiliations":[{"id":25361,"text":"CSIRO Land and Water, Adelaide, South Australia","active":true,"usgs":false}],"preferred":false,"id":627315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doan, Hai","contributorId":168796,"corporation":false,"usgs":false,"family":"Doan","given":"Hai","email":"","affiliations":[{"id":25361,"text":"CSIRO Land and Water, Adelaide, South Australia","active":true,"usgs":false}],"preferred":false,"id":627316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tolsher, Peter","contributorId":168797,"corporation":false,"usgs":false,"family":"Tolsher","given":"Peter","email":"","affiliations":[{"id":25362,"text":"EGL Management Services, Victoria, Australia","active":true,"usgs":false}],"preferred":false,"id":627317,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kookana, Rai S.","contributorId":168798,"corporation":false,"usgs":false,"family":"Kookana","given":"Rai","email":"","middleInitial":"S.","affiliations":[{"id":25361,"text":"CSIRO Land and Water, Adelaide, South Australia","active":true,"usgs":false}],"preferred":false,"id":627318,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":627311,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70170096,"text":"70170096 - 2016 - Radar and optical mapping of surge persistence and marsh dieback along the New Jersey Mid-Atlantic coast after Hurricane Sandy","interactions":[],"lastModifiedDate":"2016-07-17T23:31:33","indexId":"70170096","displayToPublicDate":"2016-04-06T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Radar and optical mapping of surge persistence and marsh dieback along the New Jersey Mid-Atlantic coast after Hurricane Sandy","docAbstract":"<p><span>This study combined a radar-based time series of Hurricane Sandy surge and estimated persistence with optical sensor-based marsh condition change to assess potential causal linkages of surge persistence and marsh condition change along the New Jersey Atlantic Ocean coast. Results based on processed TerraSAR-X and COSMO-SkyMed synthetic aperture radar (SAR) images indicated that surge flooding persisted for 12&nbsp;h past landfall in marshes from Great Bay to Great Egg Harbor Bay and up to 59&nbsp;h after landfall in many back-barrier lagoon marshes. Marsh condition change (i.e. loss of green marsh vegetation) was assessed from optical satellite images (Satellite Pour l&rsquo;Observation de la Terre and Moderate Resolution Imaging Spectroradiometer) collected before and after Hurricane Sandy. High change in condition often showed spatial correspondence, with high surge persistence in marsh surrounding the lagoon portion of Great Bay, while in contrast, low change and high persistence spatial correspondence dominated the interior marshes of the Great Bay and Great Egg Harbor Bay estuaries. Salinity measurements suggest that these areas were influenced by freshwater discharges after landfall possibly mitigating damage. Back-barrier marshes outside these regions exhibited mixed correspondences. In some cases, topographic features supporting longer surge persistence suggested that non-correspondence between radar and optical data-based results may be due to differential resilience; however, in many cases, reference information was lacking to determine a reason for non-correspondence.</span></p>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/01431161.2016.1163748","usgsCitation":"Rangoonwala, A., Enwright, N.M., Ramsey, E.W., and Spruce, J.P., 2016, Radar and optical mapping of surge persistence and marsh dieback along the New Jersey Mid-Atlantic coast after Hurricane Sandy: International Journal of Remote Sensing, v. 37, no. 7, p. 1692-1713, https://doi.org/10.1080/01431161.2016.1163748.","productDescription":"22 p.","startPage":"1692","endPage":"1713","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064429","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471086,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/01431161.2016.1163748","text":"Publisher Index Page"},{"id":438621,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OEFCOR","text":"USGS data release","linkHelpText":"Radar and optical mapping of surge persistence and marsh dieback along the New Jersey Mid-Atlantic coast after Hurricane Sandy"},{"id":319878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75,\n              39\n            ],\n            [\n              -75,\n              40.5\n            ],\n            [\n              -74,\n              40.5\n            ],\n            [\n              -74,\n              39\n            ],\n            [\n              -75,\n              39\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"37","issue":"7","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-04","publicationStatus":"PW","scienceBaseUri":"572477b0e4b0b13d3914e11a","contributors":{"authors":[{"text":"Rangoonwala, Amina 0000-0002-0556-0598 rangoonwalaa@usgs.gov","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":3455,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"Amina","email":"rangoonwalaa@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":626153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Enwright, Nicholas M. 0000-0002-7887-3261 enwrightn@usgs.gov","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":4880,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","email":"enwrightn@usgs.gov","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":626154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsey, Elijah W. III 0000-0002-4518-5796 ramseye@usgs.gov","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":2883,"corporation":false,"usgs":true,"family":"Ramsey","given":"Elijah","suffix":"III","email":"ramseye@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":626155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spruce, Joseph P.","contributorId":168501,"corporation":false,"usgs":false,"family":"Spruce","given":"Joseph","email":"","middleInitial":"P.","affiliations":[{"id":25312,"text":"Computer Sciences Corporation, John C. Stennis Space Centre, MS","active":true,"usgs":false}],"preferred":false,"id":626156,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70170071,"text":"70170071 - 2016 - The high cost of motherhood: End-lactation syndrome in southern sea otters (<i>Enhydra lutris nereis</i>) on the central California, USA, coast","interactions":[],"lastModifiedDate":"2016-05-17T16:18:45","indexId":"70170071","displayToPublicDate":"2016-04-06T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"The high cost of motherhood: End-lactation syndrome in southern sea otters (<i>Enhydra lutris nereis</i>) on the central California, USA, coast","docAbstract":"<p><span>Sea otters (</span><i><i>Enhydra lutris</i></i><span>) have exceptionally high energetic requirements, which nearly double during lactation and pup care. Thus, females are extremely vulnerable to caloric insufficiency. Despite a number of compensatory strategies, the metabolic challenge of reproduction culminates in numerous maternal deaths annually. Massive depletion of energy reserves results in a case presentation that we define as end-lactation syndrome (ELS), characterized by moderate to severe emaciation not attributable to a concurrent, independent disease process in females dying during late pup care or postweaning. We compiled detailed data for 108 adult female southern sea otters (</span><i><i>Enhydra lutris</i>&nbsp;nereis</i><span>) examined postmortem that stranded in California, US, 2005&ndash;12, and assessed pathology, reproductive status, and the location and timing of stranding. We introduce simple, grossly apparent, standardized physical criteria to assess reproductive stage for female sea otters. We also describe ELS, examine associated risk factors, and highlight female life history strategies that likely optimize reproduction and survival. Our data suggest that females can reset both the timing and energetic demands of reproduction through fetal loss, pup abandonment, or early weaning as part of specific physiologic checkpoints during each reproductive cycle. Females appear to preload nutritionally during delayed implantation and gestation to increase fitness and reproductive success. We found that ELS was a major cause of death, affecting 56% of enrolled adult females. Peak ELS prevalence occurred in late spring, possibly reflecting the population trend toward fall/winter pupping. Increasing age and number of pregnancies were associated with a higher risk of ELS. Although the proportion of ELS females was highest in areas with dense sea otter populations, cases were recovered throughout the range, suggesting that death from ELS is associated with, but not solely caused by, population resource limitation.</span></p>","language":"English","publisher":"Wildlife Diseases Association","doi":"10.7589/2015-06-158","usgsCitation":"Chinn, S.S., Miller, M.A., Tinker, M.T., Staedler, M., Batac, F.I., Dodd, E.M., and Henkel, L.A., 2016, The high cost of motherhood: End-lactation syndrome in southern sea otters (<i>Enhydra lutris nereis</i>) on the central California, USA, coast: Journal of Wildlife Diseases, v. 52, no. 2, p. 307-318, https://doi.org/10.7589/2015-06-158.","productDescription":"12 p.","startPage":"307","endPage":"318","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070046","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":319824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"52","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572477b3e4b0b13d3914e15d","contributors":{"authors":[{"text":"Chinn, Sarah S","contributorId":168466,"corporation":false,"usgs":false,"family":"Chinn","given":"Sarah","email":"","middleInitial":"S","affiliations":[{"id":25299,"text":"CA DFW","active":true,"usgs":false}],"preferred":false,"id":626018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Melissa A.","contributorId":57701,"corporation":false,"usgs":false,"family":"Miller","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":39007,"text":"CA Dept of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":626019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":626017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staedler, Michelle M.","contributorId":40087,"corporation":false,"usgs":true,"family":"Staedler","given":"Michelle M.","affiliations":[],"preferred":false,"id":626020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Batac, Francesca I.","contributorId":168467,"corporation":false,"usgs":false,"family":"Batac","given":"Francesca","email":"","middleInitial":"I.","affiliations":[{"id":13632,"text":"CDFW, Bishop, CA","active":true,"usgs":false}],"preferred":false,"id":626021,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dodd, Erin M.","contributorId":168468,"corporation":false,"usgs":false,"family":"Dodd","given":"Erin","email":"","middleInitial":"M.","affiliations":[{"id":13632,"text":"CDFW, Bishop, CA","active":true,"usgs":false}],"preferred":false,"id":626022,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Henkel, Laird A.","contributorId":84288,"corporation":false,"usgs":true,"family":"Henkel","given":"Laird","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":626023,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70170085,"text":"70170085 - 2016 - Semi-arid vegetation response to antecedent climate and water balance windows","interactions":[],"lastModifiedDate":"2016-06-15T16:24:21","indexId":"70170085","displayToPublicDate":"2016-04-06T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Semi-arid vegetation response to antecedent climate and water balance windows","docAbstract":"<div id=\"avsc12232-sec-0001\" class=\"section\">\n<h4>Questions</h4>\n<div class=\"para\">\n<p>Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation?</p>\n</div>\n</div>\n<div id=\"avsc12232-sec-0002\" class=\"section\">\n<h4>Location</h4>\n<div class=\"para\">\n<p>Semi-arid grasslands in Capitol Reef National Park, Utah, USA.</p>\n</div>\n</div>\n<div id=\"avsc12232-sec-0003\" class=\"section\">\n<h4>Methods</h4>\n<div class=\"para\">\n<p>We built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar&ndash;Nov 2000&ndash;2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years.</p>\n</div>\n</div>\n<div id=\"avsc12232-sec-0004\" class=\"section\">\n<h4>Results</h4>\n<div class=\"para\">\n<p>Water balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1&nbsp;mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3&nbsp;mo early in the growing season to 1&nbsp;yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a na&iuml;ve NDVI climatology.</p>\n</div>\n</div>\n<div id=\"avsc12232-sec-0005\" class=\"section\">\n<h4>Conclusions</h4>\n<div class=\"para\">\n<p>We determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation response with short lead times. This understanding was obtained through high-frequency vegetation monitoring using remote sensing, which reduces the costs and time necessary for field measurements and can lead to more rapid detection of vegetation changes that could help managers take appropriate actions.</p>\n</div>\n</div>","language":"English","publisher":"Wiley","doi":"10.1111/avsc.12232","usgsCitation":"Thoma, D.P., Munson, S.M., Irvine, K.M., Witwicki, D.L., and Bunting, E., 2016, Semi-arid vegetation response to antecedent climate and water balance windows: Applied Vegetation Science, v. 19, no. 3, p. 413-429, https://doi.org/10.1111/avsc.12232.","productDescription":"17 p.","startPage":"413","endPage":"429","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068856","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":319819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-30","publicationStatus":"PW","scienceBaseUri":"572477b1e4b0b13d3914e14e","contributors":{"authors":[{"text":"Thoma, David P.","contributorId":45975,"corporation":false,"usgs":true,"family":"Thoma","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":626080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":626079,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":626081,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witwicki, Dana L.","contributorId":72473,"corporation":false,"usgs":true,"family":"Witwicki","given":"Dana","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":626082,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bunting, Erin 0000-0001-9103-6065 ebunting@usgs.gov","orcid":"https://orcid.org/0000-0001-9103-6065","contributorId":168488,"corporation":false,"usgs":true,"family":"Bunting","given":"Erin","email":"ebunting@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":626083,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70170088,"text":"70170088 - 2016 - Angler harvest, hatchery return, and tributary stray rates of recycled adult summer steelhead <i>Oncorhynchus mykiss</i> in the Cowlitz River, Washington","interactions":[],"lastModifiedDate":"2016-10-11T16:12:42","indexId":"70170088","displayToPublicDate":"2016-04-06T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Angler harvest, hatchery return, and tributary stray rates of recycled adult summer steelhead <i>Oncorhynchus mykiss</i> in the Cowlitz River, Washington","docAbstract":"<p><span>Hatchery &lsquo;recycling&rsquo; programs have been used to increase angling opportunities by re-releasing fish into a river after they returned to a hatchery or fish trap. Recycling is intended to increase opportunities for fishermen, but this strategy could affect wild fish populations if some recycled fish remain in the river and interact with wild fish populations. To quantify hatchery return and angler harvest rates of recycled steelhead, we conducted a 2-year study on the Cowlitz River, Washington. A total of 1051 steelhead were recycled, including 218 fish that were radio-tagged. Fates of recycled steelhead were similar between years: 48.4% returned to the hatchery, 19.2% were reported captured by anglers, and 32.4% remained in the river. A multistate model quantified the effects of covariates on hatchery return and angler harvest rates, which were positively affected by river discharge and negatively affected by time since release. However, hatchery return rates increased and angler harvest rates decreased during periods of increasing discharge. A total of 21.1% (46 fish) of the radio-tagged steelhead failed to return to the hatchery or be reported by anglers, but nearly half of those fish (20 fish) appeared to be harvested and not reported. The remaining tagged fish (11.9% of the radio-tagged population) were monitored into the spawning period, but only five fish (2.3% of the radio-tagged population) entered tributaries where wild steelhead spawning occurs. Future research focused on straying behaviour, and spawning success of recycled steelhead may further advance the understanding of the effects of recycling as a management strategy.</span></p>","language":"English","publisher":"John Wiley & Sons, Ltd.","doi":"10.1002/rra.3023","usgsCitation":"Kock, T.J., Perry, R.W., Gleizes, C., Dammers, W., and Liedtke, T.L., 2016, Angler harvest, hatchery return, and tributary stray rates of recycled adult summer steelhead <i>Oncorhynchus mykiss</i> in the Cowlitz River, Washington: River Research and Applications, v. 32, no. 8, p. 1790-1799, https://doi.org/10.1002/rra.3023.","productDescription":"10 p.","startPage":"1790","endPage":"1799","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070184","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":319817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Cowlitz River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.13751220703125,\n              46.07132518308108\n            ],\n            [\n              -123.13751220703125,\n              46.645665192584936\n            ],\n            [\n              -122.54150390625,\n              46.645665192584936\n            ],\n            [\n              -122.54150390625,\n              46.07132518308108\n            ],\n            [\n              -123.13751220703125,\n              46.07132518308108\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"32","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-23","publicationStatus":"PW","scienceBaseUri":"572477a0e4b0b13d3914dfec","contributors":{"authors":[{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":626097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":626098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gleizes, Chris","contributorId":37233,"corporation":false,"usgs":true,"family":"Gleizes","given":"Chris","email":"","affiliations":[],"preferred":false,"id":626099,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dammers, Wolf","contributorId":79385,"corporation":false,"usgs":true,"family":"Dammers","given":"Wolf","email":"","affiliations":[],"preferred":false,"id":626100,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":626101,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70169105,"text":"ofr20161040 - 2016 - Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015","interactions":[],"lastModifiedDate":"2016-04-07T09:02:24","indexId":"ofr20161040","displayToPublicDate":"2016-04-06T00:00:00","publicationYear":"2016","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":"2016-1040","title":"Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015","docAbstract":"<p>The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Source-water supplies are treated by a combination of chemical and physical processes to remove contaminants before distribution. Advanced notification of changing water-quality conditions and cyanobacteria and associated toxin and taste-and-odor compounds provides drinking-water treatment facilities time to develop and implement adequate treatment strategies. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas State Water Plan Fund), and the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One, began a study in July 2012 to develop statistical models at two Kansas River sites located upstream from drinking-water intakes. Continuous water-quality monitors have been operated and discrete-water quality samples have been collected on the Kansas River at Wamego (USGS site number 06887500) and De Soto (USGS site number 06892350) since July 2012. Continuous and discrete water-quality data collected during July 2012 through June 2015 were used to develop statistical models for constituents of interest at the Wamego and De Soto sites. Logistic models to continuously estimate the probability of occurrence above selected thresholds were developed for cyanobacteria, microcystin, and geosmin. Linear regression models to continuously estimate constituent concentrations were developed for major ions, dissolved solids, alkalinity, nutrients (nitrogen and phosphorus species), suspended sediment, indicator bacteria (<i>Escherichia coli</i>, fecal coliform, and enterococci), and actinomycetes bacteria. These models will be used to provide real-time estimates of the probability that cyanobacteria and associated compounds exceed thresholds and of the concentrations of other water-quality constituents in the Kansas River. The models documented in this report are useful for characterizing changes in water-quality conditions through time, characterizing potentially harmful cyanobacterial events, and indicating changes in water-quality conditions that may affect drinking-water treatment processes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161040","collaboration":"Prepared in cooperation with the Kansas Water Office, the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One","usgsCitation":"Foster, G.M., and Graham, J.L., 2016, Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015: U.S. Geological Survey Open-File Report 2016–1040, 27 p., https://dx.doi.org/10.3133/ofr20161040. ","productDescription":"Report: iv, 27 p.; 31 Appendixes","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071163","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":319781,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1040/coverthb.jpg"},{"id":319791,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1040/downloads/","text":"Appendixes 1 through 31","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1040 Appendixes"},{"id":319782,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1040/ofr20161040.pdf","text":"Report","size":"830 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1040"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.6142578125,\n              38.81403111409755\n            ],\n            [\n              -94.921875,\n              39.14710270770074\n            ],\n            [\n              -95.185546875,\n              39.45316112807394\n            ],\n            [\n              -95.5810546875,\n              39.90130858574735\n            ],\n            [\n              -95.635986328125,\n              39.95185892663005\n            ],\n            [\n              -95.82275390625,\n              39.707186656826565\n            ],\n            [\n              -96.207275390625,\n              39.690280594818034\n            ],\n            [\n              -96.39404296875,\n              39.487084981687495\n            ],\n            [\n              -96.50390625,\n              39.18117526158749\n            ],\n            [\n              -96.866455078125,\n              39.26628442213066\n            ],\n            [\n              -96.88842773437499,\n              38.976492485539424\n            ],\n            [\n              -96.910400390625,\n              38.60828592850559\n            ],\n            [\n              -96.94335937499999,\n              38.42777351132905\n            ],\n            [\n              -96.624755859375,\n              38.53097889440026\n            ],\n            [\n              -96.075439453125,\n              38.61687046392973\n            ],\n            [\n              -95.020751953125,\n              38.65119833229951\n            ],\n            [\n              -94.68017578125,\n              38.659777730712534\n            ],\n            [\n              -94.6142578125,\n              38.81403111409755\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Kansas Water Science Center<br>U.S. Geological Survey<br> 4821 Quail Crest Place<br> Lawrence, KS 66049<br></p><p><a href=\"http://ks.water.usgs.gov\" data-mce-href=\"http://ks.water.usgs.gov\">http://ks.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Description of Study Area</li><li>Methods</li><li>Results of Logistic Regression Analysis for Cyanobacteria and Associated Compounds</li><li>Results of Linear Regression Analysis for Selected Constituents</li><li>Summary</li><li>References Cited</li><li>Tables</li><li>Appendixes 1–31</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-06","noUsgsAuthors":false,"publicationDate":"2016-04-06","publicationStatus":"PW","scienceBaseUri":"572477aae4b0b13d3914e0a1","contributors":{"authors":[{"text":"Foster, Guy M. gfoster@usgs.gov","contributorId":3437,"corporation":false,"usgs":true,"family":"Foster","given":"Guy M.","email":"gfoster@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":622947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622948,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70168640,"text":"sir20165025 - 2016 - Effect of a levee setback on aquatic resources using two-dimensional flow and bioenergetics models","interactions":[],"lastModifiedDate":"2016-04-06T08:25:40","indexId":"sir20165025","displayToPublicDate":"2016-04-05T18:00:00","publicationYear":"2016","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":"2016-5025","title":"Effect of a levee setback on aquatic resources using two-dimensional flow and bioenergetics models","docAbstract":"<p class=\"p1\">Watershed restoration is the focus of many resource managers and can include a multitude of restoration actions each with specific restoration objectives. For the White River flowing through the cities of Pacific and Sumner, Washington, a levee setback has been proposed to reconnect the river with its historical floodplain to help reduce flood risks, as well as provide increased habitat for federally listed species of salmonids. The study presented here documents the use of a modeling framework that integrates two-dimensional hydraulic modeling with process-based bioenergetics modeling for predicting how changes in flow from reconnecting the river with its floodplain affects invertebrate drift density and the net rate of energy intake of juvenile salmonids. Modeling results were calculated for flows of 25.9 and 49.3 cubic meters per second during the spring, summer, and fall. Predicted hypothetical future mean velocities and depths were significantly lower and more variable when compared to current conditions. The abundance of low energetic cost and positive growth locations for salmonids were predicted to increase significantly in the study reach following floodplain reconnection, particularly during the summer. This modeling framework presents a viable approach for evaluating the potential fisheries benefits of reconnecting a river to its historical floodplain that integrates our understanding of hydraulic, geomorphology, and organismal biology.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165025","collaboration":"Prepared in cooperation with the King County Water and Land Resources Division","usgsCitation":"Black, R.W., Czuba, C.R., Magirl, C.S., McCarthy, Sarah, Berge, Hans, and Comanor, Kyle, 2016, Effect of a levee setback on aquatic resources using two-dimensional flow and bioenergetics models: U.S. Geological Survey Scientific Investigations Report 2016–5025, 26 p., https://dx.doi.org/10.3133/sir20165025.","productDescription":"v, 26 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066982","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":319584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5025/coverthb.jpg"},{"id":319585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5025/sir20165025.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5025"}],"country":"United States","state":"Washington","city":"Pacific","otherGeospatial":"White River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.25688934326172,\n              47.22866141531796\n            ],\n            [\n              -122.25688934326172,\n              47.28633255817871\n            ],\n            [\n              -122.18358993530273,\n              47.28633255817871\n            ],\n            [\n              -122.18358993530273,\n              47.22866141531796\n            ],\n            [\n              -122.25688934326172,\n              47.22866141531796\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_wa@usgs.gov\">Director</a>, Washington Water Science Center<br /> U.S. Geological Survey<br /> 934 Broadway, Suite 300<br /> Tacoma, Washington 98402<br /> <a href=\"http://wa.water.usgs.gov\" target=\"blank\">http://wa.water.usgs.gov</a></p>","tableOfContents":"<ul>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Methods</li>\n<li>Results</li>\n<li>Discussion</li>\n<li>Conclusions</li>\n<li>Acknowledgments</li>\n<li>References Cited</li>\n<li>Appendix A. Initial Drift Densities Used in Invertebrate Drift Model</li>\n<li>Appendix B. Invertebrate Attributes Used in Invertebrate Drift Model</li>\n</ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477a5e4b0b13d3914e066","contributors":{"authors":[{"text":"Black, Robert W. 0000-0002-4748-8213 rwblack@usgs.gov","orcid":"https://orcid.org/0000-0002-4748-8213","contributorId":1820,"corporation":false,"usgs":true,"family":"Black","given":"Robert","email":"rwblack@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":621096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Czuba, Christiana R. cczuba@usgs.gov","contributorId":4555,"corporation":false,"usgs":true,"family":"Czuba","given":"Christiana","email":"cczuba@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":621097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":621098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCarthy, Sarah","contributorId":13097,"corporation":false,"usgs":true,"family":"McCarthy","given":"Sarah","affiliations":[],"preferred":false,"id":621099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berge, Hans","contributorId":167120,"corporation":false,"usgs":false,"family":"Berge","given":"Hans","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":621100,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Comanor, Kyle","contributorId":168354,"corporation":false,"usgs":true,"family":"Comanor","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":625553,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70168519,"text":"ofr20161011 - 2016 - Simulation of hypothetical Asian carp egg and larvae development and transport in the Lockport, Brandon Road, Dresden Island, and Marseilles Pools of the Illinois Waterway by use of the Fluvial Egg Drift Simulator (FluEgg) model","interactions":[],"lastModifiedDate":"2016-04-06T08:18:57","indexId":"ofr20161011","displayToPublicDate":"2016-04-05T11:30:00","publicationYear":"2016","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":"2016-1011","title":"Simulation of hypothetical Asian carp egg and larvae development and transport in the Lockport, Brandon Road, Dresden Island, and Marseilles Pools of the Illinois Waterway by use of the Fluvial Egg Drift Simulator (FluEgg) model","docAbstract":"<p>As part of the Great Lakes and Mississippi River Interbasin Study, the U.S. Army Corps of Engineers (USACE) is conducting an assessment of the vulnerability of the Chicago Area Waterway System and Des Plaines River to Asian carp (specifically, <i>Hypophthalmichthys nobilis</i> (bighead carp) and <i>Hypophthalmichthys molitrix</i> (silver carp)) spawning and recruitment. As part of this assessment, the USACE requested the help of the U.S. Geological Survey in predicting the fate and transport of Asian carp eggs hypothetically spawned at the electric dispersal barrier on the Chicago Sanitary and Ship Canal and downstream of the Brandon Road Lock and Dam on the Des Plaines River under dry weather flow and high water temperature conditions. The Fluvial Egg Drift Simulator (FluEgg) model predicted that approximately 80 percent of silver carp eggs spawned near the electric dispersal barrier would hatch within the Lockport and Brandon Road pools (as close as 3.6 miles downstream of the barrier) and approximately 82 percent of the silver carp eggs spawned near the Brandon Road Dam would hatch in the Des Plaines River (as close as 1.6 miles downstream from the gates of Brandon Road Lock). Extension of the FluEgg model to include the fate and transport of larvae until gas bladder inflation&mdash;the point at which the larvae begin to leave the drift&mdash;suggests that eggs spawned at the electric dispersal barrier would reach the gas bladder inflation stage primarily within the Dresden Island Pool, and those spawned at the Brandon Road Dam would reach this stage primarily within the Marseilles and Starved Rock Pools.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161011","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Great Lakes Restoration Initiative","usgsCitation":"Murphy, E.A., Garcia, Tatiana, Jackson, P.R., and Duncker J.J., 2016, Simulation of hypothetical Asian carp egg and larvae development and transport in the Lockport, Brandon Road, Dresden Island, and Marseilles Pools of the Illinois Waterway by use of the fluvial egg drift simulator (FluEgg) model: U.S. Geological Survey Open File Report 2016–1011, 19 p., https://dx.doi.org/10.3133/ofr20161011.","productDescription":"vii, 19 p.","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070545","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":319192,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1011/ofr20161011.pdf","size":"2.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1011"},{"id":319191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1011/coverthb.jpg"}],"country":"United States","state":"Illinois","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.96728515624999,\n              40.95501133048621\n            ],\n            [\n              -88.96728515624999,\n              41.85319643776675\n            ],\n            [\n              -87.9345703125,\n              41.85319643776675\n            ],\n            [\n              -87.9345703125,\n              40.95501133048621\n            ],\n            [\n              -88.96728515624999,\n              40.95501133048621\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Illinois Water Science Center<br> U.S. Geological Survey<br> 405 N Goodwin<br> Urbana, IL 61801<br> <a href=\"http://il.water.usgs.gov/\" data-mce-href=\"http://il.water.usgs.gov/\">http://il.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>FluEgg Model Overview</li><li>Hydraulic Data</li><li>FluEgg Simulation Scenarios</li><li>Results</li><li>Limitations</li><li>Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477b1e4b0b13d3914e151","contributors":{"authors":[{"text":"Murphy, Elizabeth A. emurphy@usgs.gov","contributorId":140328,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","email":"emurphy@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Tatiana 0000-0002-1979-7246 tgarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-1979-7246","contributorId":140327,"corporation":false,"usgs":true,"family":"Garcia","given":"Tatiana","email":"tgarcia@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. Ryan pjackson@usgs.gov","contributorId":2960,"corporation":false,"usgs":true,"family":"Jackson","given":"P. Ryan","email":"pjackson@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":620773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620774,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70163218,"text":"sir20155019E - 2016 - Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in <i>Montana StreamStats</i>","interactions":[{"subject":{"id":70163218,"text":"sir20155019E - 2016 - Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in <i>Montana StreamStats</i>","indexId":"sir20155019E","publicationYear":"2016","noYear":false,"chapter":"E","title":"Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in <i>Montana StreamStats</i>"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2018-02-28T16:38:48","indexId":"sir20155019E","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","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":"2015-5019","chapter":"E","title":"Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in <i>Montana StreamStats</i>","docAbstract":"<p>Chapter E of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Environmental Quality and the Montana Department of Natural Resources and Conservation, to provide an update of statewide streamflow characteristics based on data through water year 2009 for streamflow-gaging stations in or near Montana. Streamflow characteristics are presented for 408 streamflow-gaging stations in Montana and adjacent areas having 10 or more years of record. Data include the magnitude and probability of annual low and high streamflow, the magnitude and probability of low streamflow for three seasons (March&ndash;June, July&ndash;October, and November&ndash;February), streamflow duration statistics for monthly and annual periods, and mean streamflows for monthly and annual periods. Streamflow is considered to be regulated at streamflow-gaging stations where dams or other large-scale human modifications affect 20 percent or more of the contributing drainage basin. Separate streamflow characteristics are presented for the unregulated and regulated periods of record for streamflow-gaging stations with sufficient data.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019E","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality and Montana Department of Natural Resources and Conservation","usgsCitation":"McCarthy, P.M., 2016, Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: U.S. Geological Survey Scientific Investigations Report 2015–5019–E, 10 p., https://dx.doi.org/10.3133/sir20155019E.","productDescription":"Report: v, 10 p.; 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 \"}}]}","contact":"<p>Director, Wyoming-Montana Water Science Center<br />U.S. Geological Survey<br />3162 Bozeman Ave<br />Helena, MT 59601</p>\n<p><a href=\"http://wy-mt.water.usgs.gov/\">http://wy-mt.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Streamflow Characteristics Analyses and Results.</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Information and Streamflow Characteristics for Streamflow-Gaging Stations</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-04-05","noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"572477b1e4b0b13d3914e155","contributors":{"authors":[{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620700,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70170050,"text":"70170050 - 2016 - Developing recreational harvest regulations for an unexploited lake trout population","interactions":[],"lastModifiedDate":"2016-06-01T11:44:58","indexId":"70170050","displayToPublicDate":"2016-04-04T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Developing recreational harvest regulations for an unexploited lake trout population","docAbstract":"<p><span>Developing fishing regulations for previously unexploited populations presents numerous challenges, many of which stem from a scarcity of baseline information about abundance, population productivity, and expected angling pressure. We used simulation models to test the effect of six management strategies (catch and release; trophy, minimum, and maximum length limits; and protected and exploited slot length limits) on an unexploited population of Lake Trout&nbsp;</span><i>Salvelinus namaycush</i><span>&nbsp;in Follensby Pond, a 393-ha lake located in New York State&rsquo;s Adirondack Park. We combined field and literature data and mark&ndash;recapture abundance estimates to parameterize an age-structured population model and used the model to assess the effects of each management strategy on abundance, catch per unit effort (CPUE), and harvest over a range of angler effort (0&ndash;2,000 angler-days/year). Lake Trout density (3.5 fish/ha for fish &ge; age 13, the estimated age at maturity) was similar to densities observed in other unexploited systems, but growth rate was relatively slow. Maximum harvest occurred at levels of effort &le; 1,000 angler-days/year in all the scenarios considered. Regulations that permitted harvest of large postmaturation fish, such as New York&rsquo;s standard Lake Trout minimum size limit or a trophy size limit, resulted in low harvest and high angler CPUE. Regulations that permitted harvest of small and sometimes immature fish, such as a protected slot or maximum size limit, allowed high harvest but resulted in low angler CPUE and produced rapid declines in harvest with increases in effort beyond the effort consistent with maximum yield. Management agencies can use these results to match regulations to management goals and to assess the risks of different management options for unexploited Lake Trout populations and other fish species with similar life history traits.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2015.1131780","usgsCitation":"Lenker, M.A., Weidel, B., Jensen, O.P., and Solomon, C.T., 2016, Developing recreational harvest regulations for an unexploited lake trout population: North American Journal of Fisheries Management, v. 36, no. 2, p. 385-397, https://doi.org/10.1080/02755947.2015.1131780.","productDescription":"13 p.","startPage":"385","endPage":"397","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065857","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":319754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","county":"Franklin County","city":"Harrietstown","otherGeospatial":"Adirondack Park, Follensby Pond","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.3,\n              44.2\n            ],\n            [\n              -74.3,\n              44.1\n            ],\n            [\n              -74.4,\n              44.1\n            ],\n            [\n              -74.4,\n              44.2\n            ],\n            [\n              -74.3,\n              44.2\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-31","publicationStatus":"PW","scienceBaseUri":"5703821ee4b0328dcb81b361","contributors":{"authors":[{"text":"Lenker, Melissa A","contributorId":168438,"corporation":false,"usgs":false,"family":"Lenker","given":"Melissa","email":"","middleInitial":"A","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":625938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":625937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jensen, Olaf P.","contributorId":92159,"corporation":false,"usgs":false,"family":"Jensen","given":"Olaf","email":"","middleInitial":"P.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":625939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":625940,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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