The Water Availability Tool for Environmental Resources (WATER) is a decision support system (DSS) for the nontidal part of the Delaware River Basin (DRB) that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that have been parameterized using three hydrologic response units—forested, agricultural, and developed land cover. It is this integration that enables the regional hydrologic-modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model. The DSS provides a “historical” database, ideal for simulating streamflow for 2001–11, in addition to land-cover forecasts that focus on 2030 and 2060. The WATER Application Utilities are provided with the DSS and apply change factors for precipitation, temperature, and potential evapotranspiration to a 1981–2011 climatic record provided with the DSS. These change factors were derived from a suite of general circulation models (GCMs) and representative concentration pathway (RCP) emission scenarios. These change factors are based on 25-year monthly averages (normals) that are centere on 2030 and 2060. The WATER Application Utilities also can be used to apply a 2010 snapshot of water use for the DRB; a factorial approach enables scenario testing of increased or decreased water use for each simulation. Finally, the WATER Application Utilities can be used to reformat streamflow time series for input to statistical or reservoir management software.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151196","issn":"2331-1258","usgsCitation":"Williamson, T.N., and Lant, J.G., 2015, User manuals for the Delaware River Basin Water Availability Tool for Environmental Resources (DRB–WATER) and associated WATER application utilities: U.S. Geological Survey Open-File Report 2015–1196, 32 p., https://dx.doi.org/10.3133/ofr20151196.","productDescription":"Report: vi, 32 p.; Database","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066506","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":311459,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/sir20155143","text":"Scientific Investigations Report 2015-5143","description":"OFR 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U.S. Geological Survey
1770 Corporate Drive, Ste. 500
Norcross, GA 30093
678-524-1544
http://water.usgs.gov/watercensus/
Mineral extraction and associated industries play an important role in the Afghan economy, particularly in the “transitional era” of declining foreign aid and withdrawal of foreign troops post 2014. In addition to providing a substantial source of government revenue, other potential benefits of natural resource development include boosted exports, employment opportunities, and strengthened industrialization (Joya, 2012). Continued exploration and investment in these industries has resulted in large economic improvements since 2007, when this series of studies was initiated. At that time, the “Preliminary Non-Fuel Mineral Resource Assessment of Afghanistan” was completed by members of the U.S. Geological Survey and Afghanistan Geological Survey (Peters and others, 2007). The assessment published a series of country-wide datasets, including a digital elevation model (DEM), elevation contours, hydrography, transportation routes, geophysics, and cultural datasets (Peters and others, 2007). It also delineated 20 mineralized areas for further study using a geologic-based methodology. A second data product, “Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan,” was released by Peters and others in 2011. This work highlighted geologic, geohydrologic, and hyperspectral studies that were carried out in specific Areas of Interest (AOIs) to assess the location and characteristics of mineral resources. Also included in the 2011 publication is a collection of appendixes and inventories of Geographic Information System (GIS) datasets for each of the 24 identified AOIs. A third data product was released in 2013 (Casey and Chirico, 2013), publishing datasets for five different AOIs, two subareas, and one AOI extension. Each dataset contains vector shapefiles of the AOI boundary, streams, roads, and contours at 25-, 50-, and 100-meter (m) intervals, as well as raster files of the AOI’s DEM and hillshade.
\nThis work represents the fourth installment of the series, and publishes a dataset of eight new AOIs and one subarea within Afghanistan. These areas include Dasht-e-Nawar, Farah, North Ghazni, South Ghazni, Chakhansur, Godzareh East, Godzareh West, and Namaksar-e-Herat AOIs and the Central Bamyan subarea of the South Bamyan AOI (datasets for South Bamyan were published previously in Casey and Chirico, 2013). For each AOI and subarea, this dataset collection consists of the areal extent boundaries, elevation contours at 25-, 50-, and 100-m intervals, and an enhanced DEM. Hydrographic datasets covering the extent of four AOIs and one subarea are also included in the collection. The resulting raster and vector layers are intended for use by government agencies, developmental organizations, and private companies in Afghanistan to support mineral assessments, monitoring, management, and investment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151181","collaboration":"Prepared in cooperation with the Afghanistan Geological Survey under the auspices of the U.S. Department of Defense Task Force for Business and Stability Operations","usgsCitation":"DeWitt, J.D., Chirico, P.G., and Malpeli, K.C., 2015, Topographic and hydrographic GIS datasets for the Afghanistan Geological Survey and U.S. Geological Survey 2014 mineral areas of interest: U.S. Geological Survey Open-File Report 2015−1181, 27 p., https://dx.doi.org/10.3133/ofr20151181.","productDescription":"Report: iii, 23 p.; Metadata","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-058768","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":311065,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1181/metadata","text":"Metadata","size":"429 MB","description":"OFR 2015-1181"},{"id":311064,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1181/ofr20151181.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1181"},{"id":311063,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1181/coverthb.jpg"}],"country":"Afghanistan","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[61.21082,35.65007],[62.23065,35.27066],[62.98466,35.40404],[63.19354,35.85717],[63.9829,36.00796],[64.54648,36.31207],[64.74611,37.11182],[65.58895,37.30522],[65.74563,37.66116],[66.21738,37.39379],[66.51861,37.36278],[67.07578,37.35614],[67.83,37.14499],[68.13556,37.02312],[68.85945,37.34434],[69.19627,37.15114],[69.51879,37.609],[70.11658,37.58822],[70.27057,37.73516],[70.3763,38.1384],[70.80682,38.48628],[71.34813,38.25891],[71.2394,37.95327],[71.54192,37.90577],[71.44869,37.06564],[71.84464,36.73817],[72.19304,36.94829],[72.63689,37.04756],[73.26006,37.49526],[73.9487,37.42157],[74.98,37.41999],[75.15803,37.13303],[74.57589,37.02084],[74.06755,36.83618],[72.92002,36.72001],[71.84629,36.50994],[71.26235,36.07439],[71.49877,35.65056],[71.61308,35.1532],[71.11502,34.73313],[71.15677,34.34891],[70.8818,33.98886],[69.93054,34.02012],[70.32359,33.35853],[69.68715,33.1055],[69.26252,32.50194],[69.31776,31.90141],[68.92668,31.62019],[68.55693,31.71331],[67.79269,31.58293],[67.68339,31.30315],[66.93889,31.30491],[66.38146,30.7389],[66.34647,29.88794],[65.04686,29.47218],[64.35042,29.56003],[64.148,29.34082],[63.55026,29.46833],[62.54986,29.31857],[60.87425,29.82924],[61.78122,30.73585],[61.69931,31.37951],[60.94194,31.54807],[60.86365,32.18292],[60.53608,32.98127],[60.9637,33.52883],[60.52843,33.67645],[60.80319,34.4041],[61.21082,35.65007]]]},\"properties\":{\"name\":\"Afghanistan\"}}]}","contact":"Eastern Geology and Paleoclimate Science Center
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926A National Center
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Reston, VA 20192
http://geology.er.usgs.gov/egpsc/
Or
Jessica D. DeWitt
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Birds can cause extensive crop damage in the United States. In some regions, depredating species comprise a substantial portion of the total avian population, emphasizing their importance both economically and ecologically. We used the National Audubon Society Christmas Bird Count data from the south-central United States and mixed-effects models to identify habitat factors associated with population trend and abundance for 5 species: red-winged blackbird (Agelaius phoeniceus), common grackle (Quiscalus quiscula), rusty blackbird (Euphagus carolinus), Brewer’s blackbird (Euphagus cyanocephalus), and European starling (Sturnus vulgaris). Overall, we found positive associations between bird abundance and agricultural land-cover for all species. Relationships between abundance and other land-cover types were species-specific, often with contrasting relationships among species. Likewise, we found no consistent patterns among abundance and climate. Of the 5 species, only red-winged blackbirds had a significant population trend in our study area, increasing annually by 2.4%. There was marginal evidence to suggest population increases for rusty blackbirds, whereas all other species showed no trend in population size within our study area. Our study provides managers who are interested in limiting crop damage in the south-central United States with novel information on habitat associations in the region that could be used to improve management and control actions.
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Berryman Institute","publisherLocation":"Logan, UT","doi":"10.26077/mej7-v607","usgsCitation":"Strassburg, M., Crimmins, S.M., McKann, P.C., and Thogmartin, W.E., 2015, Winter habitat associations of blackbirds and starlings wintering in the south-central United States: Human-Wildlife Interactions, v. 9, no. 2, p. 171-179, https://doi.org/10.26077/mej7-v607.","productDescription":"9 p.","startPage":"171","endPage":"179","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053796","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":311495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Kansas, Louisiana, Mississippi, Missouri, Oklahoma, Tennessee, Texas","otherGeospatial":"Mississippi Flyway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.0849609375,\n 40.04443758460859\n ],\n [\n -95.2294921875,\n 40.111688665595956\n ],\n [\n -95.80078125,\n 40.613952441166596\n ],\n [\n -91.23046875,\n 40.613952441166596\n ],\n [\n -90.5712890625,\n 39.33429742980725\n ],\n [\n -89.4287109375,\n 37.50972584293751\n ],\n [\n -88.9013671875,\n 36.5978891330702\n ],\n [\n -81.5185546875,\n 36.77409249464195\n ],\n [\n -82.353515625,\n 35.24561909420681\n ],\n [\n -83.4521484375,\n 34.813803317113155\n ],\n [\n -85.60546875,\n 34.88593094075317\n ],\n [\n -85.0341796875,\n 32.509761735919426\n ],\n [\n -84.9462890625,\n 30.86451022625836\n ],\n [\n -87.62695312499999,\n 30.90222470517144\n ],\n [\n -87.3193359375,\n 30.29701788337205\n ],\n [\n -88.1982421875,\n 30.031055426540206\n ],\n [\n -89.07714843749999,\n 29.99300228455108\n ],\n [\n -88.72558593749999,\n 29.726222319395504\n ],\n [\n -88.59374999999999,\n 29.267232865200878\n ],\n [\n -89.82421875,\n 29.036960648558267\n ],\n [\n -91.4501953125,\n 29.036960648558267\n ],\n [\n -92.4169921875,\n 29.38217507514529\n ],\n [\n -93.8232421875,\n 29.34387539941801\n ],\n [\n -95.1416015625,\n 29.036960648558267\n ],\n [\n -96.328125,\n 28.22697003891834\n ],\n [\n -96.8994140625,\n 27.72243591897343\n ],\n [\n -97.0751953125,\n 26.980828590472107\n ],\n [\n -97.119140625,\n 26.352497858154\n ],\n [\n -97.998046875,\n 26.70635985763354\n ],\n [\n -99.49218749999999,\n 28.34306490482549\n ],\n [\n -101.0302734375,\n 31.80289258670676\n ],\n [\n -101.953125,\n 35.42486791930556\n ],\n [\n -102.9638671875,\n 36.949891786813296\n ],\n [\n -102.12890625,\n 37.125286284966776\n ],\n [\n -102.0849609375,\n 40.04443758460859\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564da137e4b0112df6c62dd7","contributors":{"authors":[{"text":"Strassburg, Matthew","contributorId":139647,"corporation":false,"usgs":false,"family":"Strassburg","given":"Matthew","email":"","affiliations":[{"id":12813,"text":"Department of Biological Sciences, North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":542195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crimmins, Shawn M. 0000-0001-6229-5543 scrimmins@usgs.gov","orcid":"https://orcid.org/0000-0001-6229-5543","contributorId":5498,"corporation":false,"usgs":true,"family":"Crimmins","given":"Shawn","email":"scrimmins@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":542193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKann, Patrick C.","contributorId":149776,"corporation":false,"usgs":false,"family":"McKann","given":"Patrick","email":"","middleInitial":"C.","affiliations":[{"id":6733,"text":"former UMESC employee, USGS","active":true,"usgs":false}],"preferred":false,"id":542196,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":542197,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159815,"text":"70159815 - 2015 - Mapping physiological suitability limits for malaria in Africa under climate change","interactions":[],"lastModifiedDate":"2015-12-21T13:42:22","indexId":"70159815","displayToPublicDate":"2015-11-18T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3675,"text":"Vector-Borne and Zoonotic Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Mapping physiological suitability limits for malaria in Africa under climate change","docAbstract":"We mapped current and future temperature suitability for malaria transmission in Africa using a published model that incorporates nonlinear physiological responses to temperature of the mosquito vector Anopheles gambiae and the malaria parasite Plasmodium falciparum. We found that a larger area of Africa currently experiences the ideal temperature for transmission than previously supposed. Under future climate projections, we predicted a modest increase in the overall area suitable for malaria transmission, but a net decrease in the most suitable area. Combined with human population density projections, our maps suggest that areas with temperatures suitable for year-round, highest-risk transmission will shift from coastal West Africa to the Albertine Rift between the Democratic Republic of Congo and Uganda, whereas areas with seasonal transmission suitability will shift toward sub-Saharan coastal areas. Mapping temperature suitability places important bounds on malaria transmissibility and, along with local level demographic, socioeconomic, and ecological factors, can indicate where resources may be best spent on malaria control.
","language":"English","publisher":"Mary Ann Liebert, Inc.","publisherLocation":"New Rochelle, NY","doi":"10.1089/vbz.2015.1822","usgsCitation":"Ryan, S.J., McNally, A., Johnson, L., Mordecai, E., Ben-Horin, T., Paaijmans, K.P., and Lafferty, K.D., 2015, Mapping physiological suitability limits for malaria in Africa under climate change: Vector-Borne and Zoonotic Diseases, v. 15, no. 12, p. 718-725, https://doi.org/10.1089/vbz.2015.1822.","productDescription":"8 p.","startPage":"718","endPage":"725","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068714","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471637,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1089/vbz.2015.1822","text":"Publisher Index Page"},{"id":311744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -14.150390625,\n 33.211116472416855\n ],\n [\n -8.876953125,\n 35.460669951495305\n ],\n [\n -3.779296875,\n 36.4566360115962\n ],\n [\n 5.625,\n 37.85750715625203\n ],\n [\n 11.25,\n 37.78808138412046\n ],\n [\n 13.271484375,\n 35.96022296929667\n ],\n [\n 15.8203125,\n 34.30714385628804\n ],\n [\n 23.203125,\n 34.08906131584996\n ],\n [\n 32.6953125,\n 32.24997445586331\n ],\n [\n 33.92578125,\n 30.14512718337613\n ],\n [\n 44.12109374999999,\n 11.092165893502013\n ],\n [\n 46.845703125,\n 12.12526421833159\n ],\n [\n 51.240234375,\n 13.325484885597936\n ],\n [\n 52.64648437499999,\n 9.882275493429953\n ],\n [\n 51.15234375,\n 1.0546279422758869\n ],\n [\n 51.943359375,\n -7.18810087117902\n ],\n [\n 51.50390625,\n -21.207458730482642\n ],\n [\n 42.890625,\n -28.92163128242129\n ],\n [\n 36.474609375,\n -26.980828590472093\n ],\n [\n 30.585937499999996,\n -33.578014746143985\n ],\n [\n 16.875,\n -35.17380831799957\n ],\n [\n 7.998046875,\n -15.707662769583505\n ],\n [\n 9.404296875,\n -9.622414142924793\n ],\n [\n 5.537109374999999,\n -0.08789059053082422\n ],\n [\n 2.109375,\n 2.811371193331128\n ],\n [\n -4.21875,\n 1.7575368113083254\n ],\n [\n -11.953125,\n 2.28455066023697\n ],\n [\n -17.2265625,\n 7.013667927566642\n ],\n [\n -20.214843749999996,\n 14.093957177836236\n ],\n [\n -20.56640625,\n 21.37124437061832\n ],\n [\n -19.951171875,\n 26.745610382199022\n ],\n [\n -16.787109375,\n 31.728167146023935\n ],\n [\n -14.150390625,\n 33.211116472416855\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"12","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"565d813fe4b071e7ea54347c","contributors":{"authors":[{"text":"Ryan, Sadie J.","contributorId":102738,"corporation":false,"usgs":true,"family":"Ryan","given":"Sadie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":580570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNally, Amy","contributorId":53225,"corporation":false,"usgs":true,"family":"McNally","given":"Amy","affiliations":[],"preferred":false,"id":580571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Leah R.","contributorId":83382,"corporation":false,"usgs":true,"family":"Johnson","given":"Leah R.","affiliations":[],"preferred":false,"id":580572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mordecai, Erin A.","contributorId":9113,"corporation":false,"usgs":true,"family":"Mordecai","given":"Erin A.","affiliations":[],"preferred":false,"id":580573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ben-Horin, Tal","contributorId":58137,"corporation":false,"usgs":false,"family":"Ben-Horin","given":"Tal","email":"","affiliations":[],"preferred":false,"id":580574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paaijmans, Krijn P.","contributorId":62459,"corporation":false,"usgs":true,"family":"Paaijmans","given":"Krijn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":580575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":580569,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70142276,"text":"sir20105090V - 2015 - Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment","interactions":[{"subject":{"id":70142276,"text":"sir20105090V - 2015 - Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment","indexId":"sir20105090V","publicationYear":"2015","noYear":false,"chapter":"V","title":"Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2020-08-18T22:18:50.767782","indexId":"sir20105090V","displayToPublicDate":"2015-11-18T08:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"V","title":"Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment","docAbstract":"A probabilistic mineral resource assessment of undiscovered resources in porphyry copper deposits in the Tethys region of western and southern Asia was carried out as part of a global mineral resource assessment led by the U.S. Geological Survey (USGS). The purpose of the study was to delineate geographic areas as permissive tracts for the occurrence of porphyry copper deposits at a scale of 1:1,000,000 and to provide probabilistic estimates of amounts of copper likely to be contained in undiscovered porphyry copper deposits in those tracts. The team did the assessment using the USGS three-part form of mineral resource assessment, which is based on (1) mineral deposit and grade-tonnage models constructed from known deposits as analogs for undiscovered deposits, (2) delineation of permissive tracts based on geoscientific information, and (3) estimation of numbers of undiscovered deposits.
\nThe assessment area includes the Asian part of Turkey and Georgia, Armenia, Azerbaijan, Iran, western Pakistan, and southwestern Afghanistan. Selected tracts also extend marginally into southwesternmost Russia and northeasternmost Iraq. This region is located in the central part of the larger Tethyan Eurasian Metallogenic Belt, which extends from western Europe to eastern Asia. Mining in this part of the Tethyan Eurasian Metallogenic Belt has occurred for thousands of years; in 2011 the region produced 420,000 metric tons (t) of copper (2.6 percent of global production), 8,300 t of molybdenum (3 percent), and 29,600 kilograms of gold (1 percent).
\nThe assessment team defined 26 tracts permissive for Late Triassic to Holocene porphyry copper-molybdenum and porphyry copper-gold deposits. Permissive tracts range in extent from 2,960 to 194,000 square kilometers (km2) and cover a total area of 924,000 km2. Younger tracts overlap older tracts in several areas. Three permissive tracts include sub-tracts in order to separate tract segments on the basis of geography, data quality, or likelihood of occurrence of undiscovered deposits. About 65 percent of all known porphyry sites occur in only five tracts, which also host most of the identified copper resources. In terms of tectonic setting, 58 percent of the permissive tracts are related to continental arcs; 19 percent to island arcs or back arcs; and 24 percent to postcollisional settings. Of the known porphyry copper deposits, subequal fractions are spread among these three settings.
\nThe spatial distribution of known porphyry deposits and prospects is also related to the level of erosion. Magmatic belts with numerous known porphyry sites exhibit subequal areas of coeval plutonic and volcanic units and lesser amounts of cover rocks. Belts with fewer known porphyry sites display either high or low volcanic-to-plutonic ratios and (or) greater cover, indicating crustal levels that are too shallow or too deep for exposure of porphyry deposits.
\nProbabilistic estimates of numbers of undiscovered porphyry copper deposits were made for 18 of the 26 tracts. The undiscovered porphyry copper endowment for 8 tracts is discussed qualitatively.
\nThe assessment estimates that the Tethys region contains 47 undiscovered deposits within 1 kilometer of the surface. Probabilistic estimates of numbers of undiscovered deposits were combined with grade and tonnage models in a Monte Carlo simulation to estimate probable amounts of contained metal. The 47 undiscovered deposits are estimated to contain a mean of 180 million metric tons (Mt) of copper distributed among the 18 tracts for which probabilistic estimates were made, in addition to the 62 Mt of copper already identified in the 42 known porphyry deposits in the study area. Results of Monte Carlo simulations show that 80 percent of the estimated undiscovered porphyry copper resources in the Tethys region are located in four tracts or sub-tracts.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090V","issn":"2328-0328","collaboration":"Prepared in cooperation with the Natural History Museum, London","usgsCitation":"Zürcher, L., Bookstrom A.A., Hammarstrom, J.M., Mars, J.C., Ludington, S., Zientek, M.L., Dunlap, P., and Wallis, J.C., with contributions from Drew, L.J., Sutphin, D.M., Berger, B.R., Herrington, R.J., Billa, M., Kuşcu, I., Moon, C.J. ,and Richards, J.P., 2015, Porphyry copper assessment of the Tethys region of western and southern Asia: U.S. Geological Survey Scientific Investigations Report 2010–5090–V, 232 p., and spatial data, https://dx.doi.org/10.3133/sir20105090V.","productDescription":"Report: xvii, 232 p.; 7 Figures: 17.0 x 11.0 inches; Appendices A-C; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053054","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":311125,"rank":7,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig07.pdf","text":"Tabloid Figure 7","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 7","linkHelpText":"Eocene to Miocene permissive tracts for porphyry copper deposits in the Tethys region of western and southern Asia."},{"id":311126,"rank":8,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig08.pdf","text":"Tabloid Figure 8","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 8","linkHelpText":"Pliocene to Holocene permissive tract for porphyry copper deposits in the Tethys region of western and southern Asia."},{"id":311127,"rank":9,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig57.pdf","text":"Tabloid Figure 57","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 57","linkHelpText":"Map showing the distribution of permissive intrusive and extrusive rocks used to define tract 142pCu9017, Plio-Quaternary— Afghanistan, Armenia, Azerbaijan, Georgia, Iran, Pakistan, Russian Federation, and Turkey. Sub-tracts: 142pCu9017a, Plio-Quaternary—Konya, Turkey; 142pCu9017b, Plio-Quaternary—Postcollisional, Armenia, Azerbaijan, Georgia, Iran, Russian Federation, and Turkey; and 142pCu9017c, Plio-Quaternary—Bazman, Afghanistan, Iran, Pakistan."},{"id":311122,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig03.pdf","text":"Tabloid Figure 3","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 3","linkHelpText":"Map showing tectono-stratigraphic terranes, accretionary prisms, and metamorphic belts of the Tethys region of western and southern Asia. After Abdullah and Chmyriov (1977b) and Peters and others (2011) for Afghanistan, Kazmi and Rana (1982) for Pakistan, Stöcklin (1968) for Iran, Pollastro and others (1998) for Iraq, Kaymakci and others (2010) and Yigit (2009) for Turkey, and Kekelia and others (2001) for the Caucasus."},{"id":311121,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig02.pdf","text":"Tabloid Figure 2","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 2","linkHelpText":"Map showing major sutures, faults, and geologic and geographic features in the Tethys region of western and southern Asia (assessment area) and vicinity on a digital elevation base."},{"id":311129,"rank":11,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_gis.zip","text":"GIS Data","size":"88.1 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2010-5090V GIS Data"},{"id":311128,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_appendixes_a_c.xlsx","text":"Appendices A–C","size":"516 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2010-5090V Appendixes A–C"},{"id":311124,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig06.pdf","text":"Tabloid Figure 6","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 6","linkHelpText":"Late Cretaceous to late Eocene permissive tracts for porphyry copper deposits in the Tethys region of western and southern Asia."},{"id":311123,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig05.pdf","text":"Tabloid Figure 5","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 5","linkHelpText":"Late Triassic to Early Cretaceous permissive tracts for porphyry copper deposits in the Tethys region of western and southern Asia."},{"id":311120,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v.pdf","text":"Report","size":"28.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V"},{"id":311118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/coverthb.jpg"}],"country":"Afghanistan, Armenia, Azerbaijan, Georgia, Iran, Iraq, Pakistan, Russia, Turkey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 24.609375,\n 39.90973623453719\n ],\n [\n 25.13671875,\n 41.83682786072714\n ],\n [\n 26.630859375,\n 42.87596410238254\n ],\n [\n 27.94921875,\n 43.32517767999296\n ],\n [\n 34.27734375,\n 42.87596410238254\n ],\n [\n 38.759765625,\n 42.22851735620852\n ],\n [\n 40.341796875,\n 42.94033923363181\n ],\n [\n 40.517578125,\n 43.96119063892024\n ],\n [\n 44.12109374999999,\n 43.644025847699496\n ],\n [\n 46.93359375,\n 43.32517767999296\n ],\n [\n 49.39453125,\n 42.68243539838623\n ],\n [\n 50.2734375,\n 41.244772343082076\n ],\n [\n 50.009765625,\n 39.232253141714885\n ],\n [\n 50.88867187499999,\n 38.47939467327645\n ],\n [\n 52.82226562499999,\n 38.272688535980976\n ],\n [\n 55.107421875,\n 38.685509760012\n ],\n [\n 58.447265625,\n 38.89103282648849\n ],\n [\n 61.17187499999999,\n 37.50972584293751\n ],\n [\n 64.6875,\n 36.1733569352216\n ],\n [\n 68.5546875,\n 35.88905007936091\n ],\n [\n 74.00390625,\n 32.91648534731439\n ],\n [\n 74.70703125,\n 32.10118973232094\n ],\n [\n 73.916015625,\n 30.751277776257812\n ],\n [\n 72.24609375,\n 29.22889003019423\n ],\n [\n 69.9609375,\n 27.839076094777816\n ],\n [\n 68.5546875,\n 27.21555620902969\n ],\n [\n 66.181640625,\n 26.43122806450644\n ],\n [\n 62.9296875,\n 25.48295117535531\n ],\n [\n 59.765625,\n 25.3241665257384\n ],\n [\n 56.42578125,\n 25.799891182088334\n ],\n [\n 53.26171875,\n 26.745610382199022\n ],\n [\n 50.009765625,\n 28.76765910569123\n ],\n [\n 47.548828125,\n 29.53522956294847\n ],\n [\n 43.2421875,\n 31.728167146023935\n ],\n [\n 38.408203125,\n 34.30714385628804\n ],\n [\n 33.83789062499999,\n 35.60371874069731\n ],\n [\n 27.773437499999996,\n 35.31736632923788\n ],\n [\n 25.224609375,\n 36.24427318493909\n ],\n [\n 24.169921875,\n 38.685509760012\n ],\n [\n 24.609375,\n 39.90973623453719\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Mineral Resources Program
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12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
http://minerals.usgs.gov/
Population viability analyses provide a quantitative approach that seeks to predict the possible future status of a species of interest under different scenarios and, therefore, can be important components of large-scale species’ conservation programs. We created a model and simulated range-wide population and breeding habitat dynamics for an endangered woodland warbler, the golden-cheeked warbler (Setophaga chrysoparia). Habitat-transition probabilities were estimated across the warbler's breeding range by combining National Land Cover Database imagery with multistate modeling. Using these estimates, along with recently published demographic estimates, we examined if the species can remain viable into the future given the current conditions. Lastly, we evaluated if protecting a greater amount of habitat would increase the number of warblers that can be supported in the future by systematically increasing the amount of protected habitat and comparing the estimated terminal carrying capacity at the end of 50 years of simulated habitat change. The estimated habitat-transition probabilities supported the hypothesis that habitat transitions are unidirectional, whereby habitat is more likely to diminish than regenerate. The model results indicated population viability could be achieved under current conditions, depending on dispersal. However, there is considerable uncertainty associated with the population projections due to parametric uncertainty. Model results suggested that increasing the amount of protected lands would have a substantial impact on terminal carrying capacities at the end of a 50-year simulation. Notably, this study identifies the need for collecting the data required to estimate demographic parameters in relation to changes in habitat metrics and population density in multiple regions, and highlights the importance of establishing a common definition of what constitutes protected habitat, what management goals are suitable within those protected areas, and a standard operating procedure to identify areas of priority for habitat conservation efforts. Therefore, we suggest future efforts focus on these aspects of golden-cheeked warbler conservation and ecology.
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J.","contributorId":149351,"corporation":false,"usgs":false,"family":"Forstner","given":"Michael","email":"","middleInitial":"R. J.","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":578043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Green, M. Clay","contributorId":149352,"corporation":false,"usgs":false,"family":"Green","given":"M.","email":"","middleInitial":"Clay","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":578044,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Floyd W. Weckerly","contributorId":149353,"corporation":false,"usgs":false,"family":"Floyd W. Weckerly","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":578045,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159660,"text":"70159660 - 2015 - Web based visualization of large climate data sets","interactions":[],"lastModifiedDate":"2015-11-17T14:07:35","indexId":"70159660","displayToPublicDate":"2015-11-17T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Web based visualization of large climate data sets","docAbstract":"We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2015.02.016","usgsCitation":"Alder, J.R., and Hostetler, S.W., 2015, Web based visualization of large climate data sets: Environmental Modelling and Software, v. 68, p. 175-180, https://doi.org/10.1016/j.envsoft.2015.02.016.","productDescription":"6 p.","startPage":"175","endPage":"180","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057365","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":311437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"68","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564c4fbee4b0ebfbef0d345f","contributors":{"authors":[{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579956,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159668,"text":"70159668 - 2015 - Experimental infection of snakes with Ophidiomyces ophiodiicola causes pathological changes that typify snake fungal disease","interactions":[],"lastModifiedDate":"2018-02-01T16:58:33","indexId":"70159668","displayToPublicDate":"2015-11-17T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3819,"text":"mBio","active":true,"publicationSubtype":{"id":10}},"title":"Experimental infection of snakes with Ophidiomyces ophiodiicola causes pathological changes that typify snake fungal disease","docAbstract":"Snake fungal disease (SFD) is an emerging skin infection of wild snakes in eastern North America. The fungus Ophidiomyces ophiodiicola is frequently associated with the skin lesions that are characteristic of SFD, but a causal relationship between the fungus and the disease has not been established. We experimentally infected captive-bred corn snakes (Pantherophis guttatus) in the laboratory with pure cultures of O. ophiodiicola. All snakes in the infected group (n = 8) developed gross and microscopic lesions identical to those observed in wild snakes with SFD; snakes in the control group (n = 7) did not develop skin infections. Furthermore, the same strain of O. ophiodiicola used to inoculate snakes was recovered from lesions of all animals in the infected group, but no fungi were isolated from individuals in the control group. Monitoring progression of lesions throughout the experiment captured a range of presentations of SFD that have been described in wild snakes. The host response to the infection included marked recruitment of granulocytes to sites of fungal invasion, increased frequency of molting, and abnormal behaviors, such as anorexia and resting in conspicuous areas of enclosures. While these responses may help snakes to fight infection, they could also impact host fitness and may contribute to mortality in wild snakes with chronic O. ophiodiicola infection. This work provides a basis for understanding the pathogenicity of O. ophiodiicola and the ecology of SFD by using a model system that incorporates a host species that is easy to procure and maintain in the laboratory.
\nIMPORTANCE Skin infections in snakes, referred to as snake fungal disease (SFD), have been reported with increasing frequency in wild snakes in the eastern United States. While most of these infections are associated with the fungusOphidiomyces ophiodiicola, there has been no conclusive evidence to implicate this fungus as a primary pathogen. Furthermore, it is not understood why the infections affect different host populations differently. Our experiment demonstrates that O. ophiodiicola is the causative agent of SFD and can elicit pathological changes that likely impact fitness of wild snakes. This information, and the laboratory model we describe, will be essential in addressing unresolved questions regarding disease ecology and outcomes of O. ophiodiicola infection and helping to conserve snake populations threatened by the disease. The SFD model of infection also offers utility for exploring larger concepts related to comparative fungal virulence, host response, and host-pathogen evolution.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/mBio.01534-15","usgsCitation":"Lorch, J.M., Lankton, J.S., Werner, K., Falendysz, E.A., McCurley, K., and Blehert, D., 2015, Experimental infection of snakes with Ophidiomyces ophiodiicola causes pathological changes that typify snake fungal disease: mBio, v. 6, no. 6, e01534-15; 9 p., https://doi.org/10.1128/mBio.01534-15.","productDescription":"e01534-15; 9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068390","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":471645,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/mbio.01534-15","text":"Publisher Index Page"},{"id":311413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564c4fb9e4b0ebfbef0d3455","contributors":{"authors":[{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":579987,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":579988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Werner, Katrien kwerner@usgs.gov","contributorId":149910,"corporation":false,"usgs":true,"family":"Werner","given":"Katrien","email":"kwerner@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":579989,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falendysz, Elizabeth A. 0000-0003-2895-8918 efalendysz@usgs.gov","orcid":"https://orcid.org/0000-0003-2895-8918","contributorId":127735,"corporation":false,"usgs":true,"family":"Falendysz","given":"Elizabeth","email":"efalendysz@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":579990,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCurley, Kevin","contributorId":149911,"corporation":false,"usgs":false,"family":"McCurley","given":"Kevin","email":"","affiliations":[{"id":17853,"text":"New England Reptile Distributors","active":true,"usgs":false}],"preferred":false,"id":579991,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":1816,"corporation":false,"usgs":true,"family":"Blehert","given":"David S.","email":"dblehert@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":579992,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159610,"text":"ofr20151204 - 2015 - Marshes to mudflats—Effects of sea-level rise on tidal marshes along a latitudinal gradient in the Pacific Northwest","interactions":[],"lastModifiedDate":"2017-07-26T17:12:54","indexId":"ofr20151204","displayToPublicDate":"2015-11-17T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1204","title":"Marshes to mudflats—Effects of sea-level rise on tidal marshes along a latitudinal gradient in the Pacific Northwest","docAbstract":"In the Pacific Northwest, coastal wetlands support a wealth of ecosystem services including habitat provision for wildlife and fisheries and flood protection. The tidal marshes, mudflats, and shallow bays of coastal estuaries link marine, freshwater, and terrestrial habitats, and provide economic and recreational benefits to local communities. Climate change effects such as sea-level rise are altering these habitats, but we know little about how these areas will change over the next 50–100 years. Our study examined the effects of sea-level rise on nine tidal marshes in Washington and Oregon between 2012 and 2015, with the goal of providing scientific data to support future coastal planning and conservation. We compiled physical and biological data, including coastal topography, tidal inundation, vegetation structure, as well as recent and historical sediment accretion rates, to assess and model how sea-level rise may alter these ecosystems in the future. Multiple factors, including initial elevation, marsh productivity, sediment availability, and rates of sea-level rise, affected marsh persistence. Under a low sea-level rise scenario, all marshes remained vegetated with little change in the present configuration of communities of marsh plants or gradually increased proportions of middle-, high-, or transition-elevation zones of marsh vegetation. However, at most sites, mid sea-level rise projections led to loss of habitat of middle and high marshes and a gain of low marshes. Under a high sea-level rise scenario, marshes at most sites eventually converted to intertidal mudflats. Two sites (Grays Harbor and Willapa) seemed to have the most resilience to a high rate of rise in sea-level, persisting as low marsh until at least 2110. Our main model finding is that most tidal marsh study sites are resilient to sea-level rise over the next 50–70 years, but that sea-level rise will eventually outpace marsh accretion and drown most habitats of high and middle marshes by 2110.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151204","collaboration":"Prepared in cooperation with the Northwest Climate Science Center","usgsCitation":"Thorne, K.M., Dugger, B.D., Buffington, K.J., Freeman, C.M., Janousek, C.N., Powelson, K.W., Gutenspergen, G.R., and Takekawa, J.Y., 2015, Marshes to mudflats—Effects of sea-level rise on tidal marshes along a latitudinal gradient in the Pacific Northwest: U.S. Geological Survey Open-File Report 2015-1204, 54 p. plus appendixes, https://dx.doi.org/10.3133/ofr20151204.","productDescription":"Report: vi, 54 p.; Appendixes: A-I","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-01-01","temporalEnd":"2015-12-31","ipdsId":"IP-063198","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":311426,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1204/ofr20151204.pdf","text":"Report","size":"8. MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1204 PDF"},{"id":311427,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1204/ofr20151204_appendixesA-I.pdf","text":"Appendixes A-I","size":"6.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1204 Appendix PDF"},{"id":311425,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1204/coverthb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.4111328125,\n 32.58384932565662\n ],\n [\n -121.53076171875,\n 38.09998264736481\n ],\n [\n -123.28857421875,\n 42.00032514831621\n ],\n [\n -122.03613281249999,\n 49.009050809382046\n ],\n [\n -124.73876953125,\n 48.3416461723746\n ],\n [\n -124.69482421875,\n 42.74701217318067\n ],\n [\n -124.51904296875,\n 40.26276066437183\n ],\n [\n -122.87109375,\n 36.98500309285596\n ],\n [\n -120.80566406250001,\n 34.252676117101515\n ],\n [\n -118.2568359375,\n 33.55970664841198\n ],\n [\n -117.333984375,\n 32.509761735919426\n ],\n [\n -116.4111328125,\n 32.58384932565662\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://www.werc.usgs.gov/
An evaluation was conducted to estimate dam passage survival of juvenile Chinook salmon (Oncorhynchus tshawytscha) at Detroit Dam during a period of spill. To estimate dam passage survival, we used a paired-release recapture study design and released groups of tagged fish upstream (997 fish) and downstream (625 fish) of Detroit Dam. A total of 43 fish (6.8 percent) passed Detroit Dam from the upstream release group and passage occurred through regulating outlets (54.8 percent), spill bays (31.0 percent), and turbines (14.3 percent). We do not present dam passage survival estimates from 2014 because these estimates would have been highly uncertain due to the low number of fish that passed Detroit Dam during the study. Secondary objectives were addressed using data collected from tagged fish that were released at the downstream release site.
\nJuvenile salmonids have multiple passage options at the Bennett Dam complex, which includes a series of dams and braided channels. A pair of Passive Integrated Transponder (PIT) monitoring arrays were installed at Upper Bennett Dam and in the Stayton Canal by the U.S. Army Corps of Engineers and the Oregon Department of Fish and Wildlife during 2014. We deployed acoustic telemetry hydrophones near these arrays to detect acoustic-tagged fish from our study and used these detections to quantify proportions of tagged fish passing through the two routes. About one-fourth (0.257) of the tagged fish that were released downstream of Big Cliff Dam were detected on the new PIT tag array while passing the Bennett Dam complex. A total of 402 acoustic-tagged fish were detected at the complex and many (248 fish; 62 percent) eventually entered the Stayton Canal. Median residence time in the canal was 6.5 hours, but 12.7 percent of the fish had extended residence times (7–37 days). Passage also was monitored at the Sullivan Project at Willamette Falls and about 40 percent (0.398) of the tagged fish passing the project were detected on the PIT tag array.
\nA Cormack-Jolly-Seber mark-recapture model was developed to provide reach-specific survival estimates for juvenile Chinook salmon. A portion of the tagged population overwintered in the Willamette River Basin and outmigrated several months after release. As a result, survival estimates from the model would have been negatively biased by factors such as acoustic tag failure and tag loss. Data from laboratory studies were incorporated into the model to provide survival estimates that accounted for these factors. In the North Santiam River between Minto Dam and the Bennett Dam complex, a distance of 37.2 kilometers, survival was estimated to be 0.844 (95-percent confidence interval 0.795–0.893). The survival estimate for the 203.7 kilometer reach between the Bennett Dam complex and Portland, Oregon, was 0.279 (95-percent confidence interval 0.234–0.324), and included portions of the North Santiam, Santiam, and Willamette Rivers. The cumulative survival estimate in the 240.9 kilometer reach from the Minto Dam tailrace to Portland was 0.236 (95-percent confidence interval 0.197–0.275).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151220","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Kock, T.J., Beeman, J.W., Hansen, A.C., Hansel, H.C., Hansen, G.S., Hatton, T.W., Kofoot, E.E., Sholtis, M.D., and Sprando, J.M., 2015, Behavior, passage, and downstream migration of juvenile Chinook salmon from Detroit Reservoir to Portland, Oregon, 2014–15: U.S. Geological Survey Open-File Report 2015-1220, 30 p., https://dx.doi.org/10.3133/ofr20151220.","productDescription":"vi, 30 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2014-08-01","temporalEnd":"2015-06-30","ipdsId":"IP-067565","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":311361,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1220/coverthb.jpg"},{"id":311362,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1220/ofr20151220.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1220 PDF"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Detroit Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.20068359374999,\n 44.65693173288727\n ],\n [\n -123.20068359374999,\n 45.5679096098613\n ],\n [\n -122.07733154296875,\n 45.5679096098613\n ],\n [\n -122.07733154296875,\n 44.65693173288727\n ],\n [\n -123.20068359374999,\n 44.65693173288727\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
The increasing capability of seismic, geodetic, and hydrothermal observation networks allows recognition of volcanic unrest that could previously have gone undetected, creating an imperative to diagnose and interpret unrest episodes. A November 2014 earthquake swarm near Lassen Volcanic National Park, California, which included the largest earthquake in the area in more than 60 years, was accompanied by a rarely observed outburst of hydrothermal fluids. Although the earthquake swarm likely reflects upward migration of endogenous H2O-CO2 fluids in the source region, there is no evidence that such fluids emerged at the surface. Instead, shaking from the modest sized (moment magnitude 3.85) but proximal earthquake caused near-vent permeability increases that triggered increased outflow of hydrothermal fluids already present and equilibrated in a local hydrothermal aquifer. Long-term, multiparametric monitoring at Lassen and other well-instrumented volcanoes enhances interpretation of unrest and can provide a basis for detailed physical modeling.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington D.C.","doi":"10.1002/2015GL065826","usgsCitation":"Ingebritsen, S.E., Shelly, D.R., Hsieh, P.A., Clor, L., Seward, P., and Evans, W.C., 2015, Hydrothermal response to a volcano-tectonic earthquake swarm, Lassen, California: Geophysical Research Letters, v. 42, no. 21, p. 9223-9230, https://doi.org/10.1002/2015GL065826.","productDescription":"8 p.","startPage":"9223","endPage":"9230","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066679","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":312928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.5909423828125,\n 39.38526381099774\n ],\n [\n -122.5909423828125,\n 41.475660200278234\n ],\n [\n -120.02563476562501,\n 41.475660200278234\n ],\n [\n -120.02563476562501,\n 39.38526381099774\n ],\n [\n -122.5909423828125,\n 39.38526381099774\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"21","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-06","publicationStatus":"PW","scienceBaseUri":"56826b42e4b0a04ef4925b55","contributors":{"authors":[{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - 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Western Branch","active":true,"usgs":true}],"preferred":true,"id":583471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clor, Laura 0000-0003-2633-5100 lclor@usgs.gov","orcid":"https://orcid.org/0000-0003-2633-5100","contributorId":150878,"corporation":false,"usgs":false,"family":"Clor","given":"Laura","email":"lclor@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":583472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seward, P.H.","contributorId":150879,"corporation":false,"usgs":false,"family":"Seward","given":"P.H.","email":"","affiliations":[{"id":18130,"text":"White Barn Millworks, Chico, California","active":true,"usgs":false}],"preferred":false,"id":583473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":583474,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159632,"text":"70159632 - 2015 - Rates and patterns of surface deformation from laser scanning following the South Napa earthquake, California","interactions":[],"lastModifiedDate":"2017-02-15T11:07:58","indexId":"70159632","displayToPublicDate":"2015-11-16T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Rates and patterns of surface deformation from laser scanning following the South Napa earthquake, California","docAbstract":"The A.D. 2014 M6.0 South Napa earthquake, despite its moderate magnitude, caused significant damage to the Napa Valley in northern California (USA). Surface rupture occurred along several mapped and unmapped faults. Field observations following the earthquake indicated that the magnitude of postseismic surface slip was likely to approach or exceed the maximum coseismic surface slip and as such presented ongoing hazard to infrastructure. Using a laser scanner, we monitored postseismic deformation in three dimensions through time along 0.5 km of the main surface rupture. A key component of this study is the demonstration of proper alignment of repeat surveys using point cloud–based methods that minimize error imposed by both local survey errors and global navigation satellite system georeferencing errors. Using solid modeling of natural and cultural features, we quantify dextral postseismic displacement at several hundred points near the main fault trace. We also quantify total dextral displacement of initially straight cultural features. Total dextral displacement from both coseismic displacement and the first 2.5 d of postseismic displacement ranges from 0.22 to 0.29 m. This range increased to 0.33–0.42 m at 59 d post-earthquake. Furthermore, we estimate up to 0.15 m of vertical deformation during the first 2.5 d post-earthquake, which then increased by ∼0.02 m at 59 d post-earthquake. This vertical deformation is not expressed as a distinct step or scarp at the fault trace but rather as a broad up-to-the-west zone of increasing elevation change spanning the fault trace over several tens of meters, challenging common notions about fault scarp development in strike-slip systems. Integrating these analyses provides three-dimensional mapping of surface deformation and identifies spatial variability in slip along the main fault trace that we attribute to distributed slip via subtle block rotation. These results indicate the benefits of laser scanner surveys along active faults and demonstrate that fine-scale variability in fault slip has been missed by traditional earthquake response methods.
","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/GES01189.1","usgsCitation":"DeLong, S.B., Lienkaemper, J.J., Pickering, A.J., and Avdievitch, N.N., 2015, Rates and patterns of surface deformation from laser scanning following the South Napa earthquake, California: Geosphere, v. 11, no. 6, p. 2015-2030, https://doi.org/10.1130/GES01189.1.","productDescription":"16 p.","startPage":"2015","endPage":"2030","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063802","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471646,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01189.1","text":"Publisher Index Page"},{"id":438668,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71N7Z89","text":"USGS data release","linkHelpText":"3D point cloud data from laser scanning along the 2014 South Napa Earthquake surface rupture (2016)"},{"id":311373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335479,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F71N7Z89","text":"3D point cloud data from laser scanning along the 2014 South Napa Earthquake surface rupture, California, USA"}],"country":"United States","state":"California","otherGeospatial":"Napa Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.37979888916016,\n 38.2354834596579\n ],\n [\n -122.37979888916016,\n 38.278348508036814\n ],\n [\n -122.30461120605469,\n 38.278348508036814\n ],\n [\n -122.30461120605469,\n 38.2354834596579\n ],\n [\n -122.37979888916016,\n 38.2354834596579\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-10","publicationStatus":"PW","scienceBaseUri":"564afe32e4b0ebfbef0d3118","contributors":{"authors":[{"text":"DeLong, Stephen B. 0000-0002-0945-2172 sdelong@usgs.gov","orcid":"https://orcid.org/0000-0002-0945-2172","contributorId":5240,"corporation":false,"usgs":true,"family":"DeLong","given":"Stephen","email":"sdelong@usgs.gov","middleInitial":"B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":579797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":579798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pickering, Alexandra J. 0000-0002-1281-6117 apickering@usgs.gov","orcid":"https://orcid.org/0000-0002-1281-6117","contributorId":5990,"corporation":false,"usgs":true,"family":"Pickering","given":"Alexandra","email":"apickering@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":579799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Avdievitch, Nikita N.","contributorId":143693,"corporation":false,"usgs":false,"family":"Avdievitch","given":"Nikita","email":"","middleInitial":"N.","affiliations":[{"id":15304,"text":"University of Tubingen, Wilhelmstrasse 56, Tugingen, GER 72076","active":true,"usgs":false}],"preferred":false,"id":579800,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173532,"text":"70173532 - 2015 - Strategic Grassland Bird Conservation throughout the annual cycle: Linking policy alternatives, landowner decisions, and biological population outcomes","interactions":[],"lastModifiedDate":"2016-06-16T10:24:14","indexId":"70173532","displayToPublicDate":"2015-11-16T01:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Strategic Grassland Bird Conservation throughout the annual cycle: Linking policy alternatives, landowner decisions, and biological population outcomes","docAbstract":"Grassland bird habitat has declined substantially in the United States. Remaining grasslands are increasingly fragmented, mostly privately owned, and vary greatly in terms of habitat quality and protection status. A coordinated strategic response for grassland bird conservation is difficult, largely due to the scope and complexity of the problem, further compounded by biological, sociological, and economic uncertainties. We describe the results from a collaborative Structured Decision Making (SDM) workshop focused on linking social and economic drivers of landscape change to grassland bird population outcomes. We identified and evaluated alternative strategies for grassland bird conservation using a series of rapid prototype models. We modeled change in grassland and agriculture cover in hypothetical landscapes resulting from different landowner decisions in response to alternative socio-economic conservation policy decisions. Resulting changes in land cover at all three stages of the annual cycle (breeding, wintering, and migration) were used to estimate changes in grassland bird populations. Our results suggest that successful grassland bird conservation may depend upon linkages with ecosystem services on working agricultural lands and grassland-based marketing campaigns to engage the public. With further development, spatial models that link landowner decisions with biological outcomes can be essential tools for making conservation policy decisions. A coordinated non-traditional partnership will likely be necessary to clearly understand and systematically respond to the many conservation challenges facing grassland birds.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0142525","usgsCitation":"Drum, R.G., Ribic, C., Koch, K., Lonsdorf, E.V., Grant, E.C., Ahlering, M., Barnhill, L.M., Dailey, T., Lor, S., Mueller, C., Pavlacky, D., Rideout, C., and Sample, D.W., 2015, Strategic Grassland Bird Conservation throughout the annual cycle: Linking policy alternatives, landowner decisions, and biological population outcomes: PLoS ONE, v. 10, no. 11, https://doi.org/10.1371/journal.pone.0142525.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057271","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471647,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0142525","text":"Publisher Index Page"},{"id":323729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-16","publicationStatus":"PW","scienceBaseUri":"5763cdb9e4b07657d19ba795","contributors":{"authors":[{"text":"Drum, Ryan G.","contributorId":171941,"corporation":false,"usgs":false,"family":"Drum","given":"Ryan","email":"","middleInitial":"G.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":639174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":637268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Katie","contributorId":171942,"corporation":false,"usgs":false,"family":"Koch","given":"Katie","email":"","affiliations":[],"preferred":false,"id":639175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lonsdorf, Eric V.","contributorId":149495,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":639176,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grant, Edward C.","contributorId":60957,"corporation":false,"usgs":true,"family":"Grant","given":"Edward","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahlering, Marissa 0000-0002-3913-428X","orcid":"https://orcid.org/0000-0002-3913-428X","contributorId":171943,"corporation":false,"usgs":false,"family":"Ahlering","given":"Marissa","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":639178,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barnhill, Laurel M.","contributorId":171944,"corporation":false,"usgs":false,"family":"Barnhill","given":"Laurel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":639179,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dailey, Thomas","contributorId":171945,"corporation":false,"usgs":false,"family":"Dailey","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":639180,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lor, Socheata","contributorId":48812,"corporation":false,"usgs":true,"family":"Lor","given":"Socheata","email":"","affiliations":[],"preferred":false,"id":639181,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mueller, Connie","contributorId":171946,"corporation":false,"usgs":false,"family":"Mueller","given":"Connie","email":"","affiliations":[],"preferred":false,"id":639182,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pavlacky, D.C. Jr.","contributorId":43540,"corporation":false,"usgs":true,"family":"Pavlacky","given":"D.C.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":639183,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rideout, Catherine","contributorId":79020,"corporation":false,"usgs":true,"family":"Rideout","given":"Catherine","email":"","affiliations":[],"preferred":false,"id":639184,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sample, David W.","contributorId":19484,"corporation":false,"usgs":true,"family":"Sample","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":639185,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70157269,"text":"ofr20151182 - 2015 - The relationship between the ratio of strontium to calcium and sea-surface temperature in a modern Porites astreoides coral: Implications for using P. astreoides as a paleoclimate archive","interactions":[],"lastModifiedDate":"2015-11-13T13:27:24","indexId":"ofr20151182","displayToPublicDate":"2015-11-13T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1182","title":"The relationship between the ratio of strontium to calcium and sea-surface temperature in a modern Porites astreoides coral: Implications for using P. astreoides as a paleoclimate archive","docAbstract":"An inverse relationship has been demonstrated between water temperature and the ratio of strontium to calcium (Sr/Ca) in coral aragonite for a number of Pacific species of the genus Porites. This empirically determined relationship has been used to reconstruct past sea-surface temperature (SST) from modern and Holocene age coral archives. A study was conducted to investigate this relationship for Porites astreoides to determine the potential for using these corals as a paleotemperature archive in the Caribbean and western tropical Atlantic Ocean. Skeletal aragonite from a P. astreoides colony growing offshore of the southeast coast of Florida was subsampled with a mean temporal resolution of 14 samples per year and analyzed for Sr/Ca. The resulting Sr/Ca time series yielded well-defined annual cycles that correspond to annual growth bands in the coral. Sr/Ca was regressed against a monthly SST record from C-MAN buoy station FWYF1 (located at Fowey Rocks, Florida), resulting in the following Sr/Ca-SST relationship: Sr/Ca = –0.040*SST + 10.128 (R = –0.77). A 10-year time series of Sr/Ca-derived SST yields annual cycles with a 10–12 degree Celsius seasonal amplitude, consistent with available local instrumental records. We conclude that Sr/Ca in Porites astreoides from the Caribbean/Atlantic region has high potential for developing subannually resolved modern and recent Holocene SST records.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151182","usgsCitation":"Busch, T.E., Flannery, J.A., Richey, J.N., and Stathakopoulos, Anastasios, 2015, The relationship between the ratio of strontium to calcium and sea-surface temperature in a modern Porites astreoides coral—Implications for using P. astreoides as a paleoclimate archive: U.S. Geological Survey Open-File Report 2015–1182, 10 p., https://dx.doi.org/10.3133/ofr20151182.","productDescription":"iv, 10 p.","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065459","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":311286,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1182/ofr20151182.pdf","text":"Report","size":"2.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1182"},{"id":311285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1182/coverthb.jpg"}],"country":"United States","state":"Florida","city":"Miami","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.99621582031249,\n 24.956180020055925\n ],\n [\n -82.99621582031249,\n 27.756468889550746\n ],\n [\n -79.38720703125,\n 27.756468889550746\n ],\n [\n -79.38720703125,\n 24.956180020055925\n ],\n [\n -82.99621582031249,\n 24.956180020055925\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
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Sources of mercury (Hg) in Great Lakes sediments were assessed with stable Hg isotope ratios using multicollector inductively coupled plasma mass spectrometry. An isotopic mixing model based on mass-dependent (MDF) and mass-independent fractionation (MIF) (δ202Hg and Δ199Hg) identified three primary Hg sources for sediments: atmospheric, industrial, and watershed-derived. Results indicate atmospheric sources dominate in Lakes Huron, Superior, and Michigan sediments while watershed-derived and industrial sources dominate in Lakes Erie and Ontario sediments. Anomalous Δ200Hg signatures, also apparent in sediments, provided independent validation of the model. Comparison of Δ200Hg signatures in predatory fish from three lakes reveals that bioaccumulated Hg is more isotopically similar to atmospherically derived Hg than a lake’s sediment. Previous research suggests Δ200Hg is conserved during biogeochemical processing and odd mass-independent fractionation (MIF) is conserved during metabolic processing, so it is suspected even is similarly conserved. Given these assumptions, our data suggest that in some cases, atmospherically derived Hg may be a more important source of MeHg to higher trophic levels than legacy sediments in the Great Lakes.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Washington, DC","doi":"10.1021/acs.estlett.5b00277","usgsCitation":"Lepak, R.F., Yin, R., Krabbenhoft, D.P., Ogorek, J.M., DeWild, J.F., Holsen, T.M., and Hurley, J., 2015, Use of stable isotope signatures to determine mercury sources in the Great Lakes: Environmental Science & Technology Letters, v. 2, no. 12, https://doi.org/10.1021/acs.estlett.5b00277.","productDescription":"7 p.","endPage":"335","numberOfPages":"341","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070652","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":471650,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.estlett.5b00277","text":"Publisher Index 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rlepak@usgs.gov","contributorId":5784,"corporation":false,"usgs":true,"family":"Lepak","given":"Ryan","email":"rlepak@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":580554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yin, Runsheng","contributorId":150057,"corporation":false,"usgs":false,"family":"Yin","given":"Runsheng","email":"","affiliations":[{"id":17896,"text":"State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, China","active":true,"usgs":false}],"preferred":false,"id":580555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogorek, Jacob M. 0000-0002-6327-0740 jmogorek@usgs.gov","orcid":"https://orcid.org/0000-0002-6327-0740","contributorId":4960,"corporation":false,"usgs":true,"family":"Ogorek","given":"Jacob","email":"jmogorek@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":580557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeWild, John F. 0000-0003-4097-2798 jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holsen, Thomas M.","contributorId":150058,"corporation":false,"usgs":false,"family":"Holsen","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":17897,"text":"Department of Civil and Environmental Engineering, Clarkson University, Potsdam, New York","active":true,"usgs":false}],"preferred":false,"id":580559,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hurley, James P.","contributorId":147931,"corporation":false,"usgs":false,"family":"Hurley","given":"James P.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":580556,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159670,"text":"70159670 - 2015 - Reactive transport modeling of geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN","interactions":[],"lastModifiedDate":"2021-09-01T15:52:59.116597","indexId":"70159670","displayToPublicDate":"2015-11-11T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Reactive transport modeling of geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN","docAbstract":"Anaerobic biodegradation of organic amendments and contaminants in aquifers can trigger secondary water quality impacts that impair groundwater resources. Reactive transport models help elucidate how diverse geochemical reactions control the spatiotemporal evolution of these impacts. Using extensive monitoring data from a crude oil spill site near Bemidji, Minnesota (USA), we implemented a comprehensive model that simulates secondary plumes of depleted dissolved O2 and elevated concentrations of Mn2+, Fe2+, CH4, and Ca2+ over a two-dimensional cross section for 30 years following the spill. The model produces observed changes by representing multiple oil constituents and coupled carbonate and hydroxide chemistry. The model includes reactions with carbonates and Fe and Mn mineral phases, outgassing of CH4 and CO2 gas phases, and sorption of Fe, Mn, and H+. Model results demonstrate that most of the carbon loss from the oil (70%) occurs through direct outgassing from the oil source zone, greatly limiting the amount of CH4 cycled down-gradient. The vast majority of reduced Fe is strongly attenuated on sediments, with most (91%) in the sorbed form in the model. Ferrous carbonates constitute a small fraction of the reduced Fe in simulations, but may be important for furthering the reduction of ferric oxides. The combined effect of concomitant redox reactions, sorption, and dissolved CO2 inputs from source-zone degradation successfully reproduced observed pH. The model demonstrates that secondary water quality impacts may depend strongly on organic carbon properties, and impacts may decrease due to sorption and direct outgassing from the source zone.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015WR016964","usgsCitation":"Ng, G.C., Bekins, B.A., Cozzarelli, I.M., Baedecker, M.J., Bennett, P.C., Amos, R.T., and Herkelrath, W.N., 2015, Reactive transport modeling of geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN: Water Resources Research, v. 51, no. 6, p. 4156-4183, https://doi.org/10.1002/2015WR016964.","productDescription":"28 p.","startPage":"4156","endPage":"4183","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064817","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr016964","text":"Publisher Index Page"},{"id":311418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","county":"Bemidji","otherGeospatial":"Bemindji Oil Spill site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.13130187988281,\n 47.5363264438391\n ],\n [\n -95.0456428527832,\n 47.5363264438391\n ],\n [\n -95.0456428527832,\n 47.57316730158045\n ],\n [\n -95.13130187988281,\n 47.57316730158045\n ],\n [\n -95.13130187988281,\n 47.5363264438391\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-11","publicationStatus":"PW","scienceBaseUri":"564c5de4e4b0ebfbef0d348b","contributors":{"authors":[{"text":"Ng, Gene-Hua Crystal gng@usgs.gov","contributorId":5313,"corporation":false,"usgs":true,"family":"Ng","given":"Gene-Hua","email":"gng@usgs.gov","middleInitial":"Crystal","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":579996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":579997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":579998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baedecker, Mary Jo mjbaedec@usgs.gov","contributorId":3346,"corporation":false,"usgs":true,"family":"Baedecker","given":"Mary","email":"mjbaedec@usgs.gov","middleInitial":"Jo","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":579999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bennett, Philip C.","contributorId":30567,"corporation":false,"usgs":true,"family":"Bennett","given":"Philip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":580000,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Amos, Richard T.","contributorId":69081,"corporation":false,"usgs":true,"family":"Amos","given":"Richard","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":580001,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Herkelrath, William N. 0000-0002-6149-5524 wnherkel@usgs.gov","orcid":"https://orcid.org/0000-0002-6149-5524","contributorId":2612,"corporation":false,"usgs":true,"family":"Herkelrath","given":"William","email":"wnherkel@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":580002,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159594,"text":"70159594 - 2015 - Home range and habitat use of juvenile green turtles (Chelonia mydas) in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2016-07-17T23:15:31","indexId":"70159594","displayToPublicDate":"2015-11-10T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Home range and habitat use of juvenile green turtles (Chelonia mydas) in the northern Gulf of Mexico","docAbstract":"Background: For imperiled marine turtles, use of satellite telemetry has proven to be an effective method in determining long distance movements. However, the large size of the tag, relatively high cost and low spatial resolution of this method make it more difficult to examine fine-scale movements of individuals, particularly at foraging grounds where animals are frequently submerged. Acoustic telemetry offers a more suitable method of assessing fine-scale movement patterns with a smaller tag that provides more precise locations. We used acoustic telemetry to define home ranges and describe habitat use of juvenile green turtles at a temperate foraging ground in the northern Gulf of Mexico.
\nResults: We outfitted eight juvenile green turtles with acoustic transmitters and tracked them from 14 to 138 days from September 2012 to February 2013 in St. Joseph Bay, Northwest Florida. Mean home range size was relatively small compared to other studies. For four turtles, we observed a moderate inverse relationship between water temperature and water depth which is consistent with the idea that turtles moved to deeper waters when temperatures cooled. On average distance to the channel from turtle locations were different by bottom cover type. These turtles appear to forage in shallow-water seagrass beds that border deep channels. When water temperatures dropped in winter, some of the tracked turtles moved to a deep-water channel on the western side of the study site. Turtles whose foraging sites were farther from the deep-water channel exhibited greater displacement than those with sites that were closer to the channel.
\nConclusions: Green turtles in St. Joseph Bay have relatively small home ranges and many contain multiple activity centers. The frequent use of channels by turtles suggests bathymetry plays a major role in habitat selection of juvenile green turtles, particularly as temperatures drop in winter. The quality and density of seagrass habitat in St. Joseph Bay and its proximity to deep channels appears to provide ideal conditions for juvenile greens. The results of this study help define characteristics of foraging habitat utilized by juvenile greens in the northern Gulf of Mexico that managers can use in creating protected areas such as aquatic preserves.
","language":"English","publisher":"BioMed Central","doi":"10.1186/s40317-015-0089-9","usgsCitation":"Lamont, M.M., Fujisaki, I., Stephens, B.S., and Hackett, C., 2015, Home range and habitat use of juvenile green turtles (Chelonia mydas) in the northern Gulf of Mexico: Animal Biotelemetry, v. 3, no. 53, 12 p., https://doi.org/10.1186/s40317-015-0089-9.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2012-09-01","temporalEnd":"2013-02-28","ipdsId":"IP-062733","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471653,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-015-0089-9","text":"Publisher Index Page"},{"id":311179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.40771484375,\n 29.818008344682042\n ],\n [\n -85.31295776367188,\n 29.821582720575016\n ],\n [\n -85.30746459960938,\n 29.68685971706881\n ],\n [\n -85.35964965820312,\n 29.682087444299334\n ],\n [\n -85.40634155273438,\n 29.785833211631733\n ],\n [\n -85.41458129882812,\n 29.81205076752506\n ],\n [\n -85.40771484375,\n 29.818008344682042\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"53","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-02","publicationStatus":"PW","scienceBaseUri":"56431533e4b0aafbcd017faa","contributors":{"authors":[{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":579612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":579613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stephens, Brail S.","contributorId":105214,"corporation":false,"usgs":true,"family":"Stephens","given":"Brail","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":579614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hackett, Caitlin","contributorId":149797,"corporation":false,"usgs":false,"family":"Hackett","given":"Caitlin","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":579615,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159580,"text":"70159580 - 2015 - Hydrogeochemical effects of a bulkhead in the Dinero mine tunnel, Sugar Loaf mining district, near Leadville, Colorado","interactions":[],"lastModifiedDate":"2018-09-04T15:44:27","indexId":"70159580","displayToPublicDate":"2015-11-10T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeochemical effects of a bulkhead in the Dinero mine tunnel, Sugar Loaf mining district, near Leadville, Colorado","docAbstract":"The Dinero mine drainage tunnel is an abandoned, draining mine adit near Leadville, Colorado, that has an adverse effect on downstream water quality and aquatic life. In 2009, a bulkhead was constructed (creating a mine pool and increasing water-table elevations behind the tunnel) to limit drainage from the tunnel and improve downstream water quality. The goal of this study was to document changes to hydrology and water quality resulting from bulkhead emplacement, and to understand post-bulkhead changes in source water and geochemical processes that control mine-tunnel discharge and water quality. Comparison of pre-and post-bulkhead hydrology and water quality indicated that tunnel discharge and zinc and manganese loads decreased by up to 97 percent at the portal of Dinero tunnel and at two downstream sites (LF-537 and LF-580). However, some water-quality problems persisted at LF-537 and LF-580 during high-flow events and years, indicating the effects of the remaining mine waste in the area. In contrast, post-bulkhead water quality degraded at three upstream stream sites and a draining mine tunnel (Nelson tunnel). Water-quality degradation in the streams likely occurred from increased contributions of mine-pool groundwater to the streams. In contrast, water-quality degradation in the Nelson tunnel was likely from flow of mine-pool water along a vein that connects the Nelson tunnel to mine workings behind the Dinero tunnel bulkhead. Principal components analysis, mixing analysis, and inverse geochemical modeling using PHREEQC indicated that mixing and geochemical reactions (carbonate dissolution during acid weathering, precipitation of goethite and birnessite, and sorption of zinc) between three end-member water types generally explain the pre-and post-bulkhead water composition at the Dinero and Nelson tunnels. The three end members were (1) a relatively dilute groundwater having low sulfate and trace element concentrations; (2) mine pool water, and (3) water that flowed from a structure in front of the bulkhead after bulkhead emplacement. Both (2) and (3) had high sulfate and trace element concentrations. These results indicate how analysis of monitoring information can be used to understand hydrogeochemical changes resulting from bulkhead emplacement. This understanding, in turn, can help inform future decisions on the disposition of the remaining mine waste and water-quality problems in the area.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.03.002","usgsCitation":"Walton-Day, K., and Mills, T.J., 2015, Hydrogeochemical effects of a bulkhead in the Dinero mine tunnel, Sugar Loaf mining district, near Leadville, Colorado: Applied Geochemistry, v. 62, p. 61-74, https://doi.org/10.1016/j.apgeochem.2015.03.002.","productDescription":"14 p.","startPage":"61","endPage":"74","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057803","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":311176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Lake County","otherGeospatial":"Sugar Loaf Mining District","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.3974380493164,\n 39.236109077098135\n ],\n [\n -106.3974380493164,\n 39.26934111143279\n ],\n [\n -106.36722564697266,\n 39.26934111143279\n ],\n [\n -106.36722564697266,\n 39.236109077098135\n ],\n [\n -106.3974380493164,\n 39.236109077098135\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56431534e4b0aafbcd017fb0","contributors":{"authors":[{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":1245,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":579558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mills, Taylor J. 0000-0001-7252-0521 tmills@usgs.gov","orcid":"https://orcid.org/0000-0001-7252-0521","contributorId":4658,"corporation":false,"usgs":true,"family":"Mills","given":"Taylor","email":"tmills@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579559,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159527,"text":"70159527 - 2015 - Hybridization between Yellowstone cutthroat trout and rainbow trout alters the expression of muscle growth-related genes and their relationships with growth patterns","interactions":[],"lastModifiedDate":"2016-04-08T12:45:05","indexId":"70159527","displayToPublicDate":"2015-11-10T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Hybridization between Yellowstone cutthroat trout and rainbow trout alters the expression of muscle growth-related genes and their relationships with growth patterns","docAbstract":"Hybridization creates novel gene combinations that may generate important evolutionary novelty, but may also reduce existing adaptation by interrupting inherent biological processes, such as genotype-environment interactions. Hybridization often causes substantial change in patterns of gene expression, which, in turn, may cause phenotypic change. Rainbow trout (Oncorhynchus mykiss) and cutthroat trout (O. clarkii) produce viable hybrids in the wild, and introgressive hybridization with introduced rainbow trout is a major conservation concern for native cutthroat trout. The two species differ in body shape, which is likely an evolutionary adaptation to their native environments, and their hybrids tend to show intermediate morphology. The characterization of gene expression patterns may provide insights on the genetic basis of hybrid and parental morphologies, as well as on the ecological performance of hybrids in the wild. Here, we evaluated the expression of eight growth-related genes (MSTN-1a, MSTN-1b, MyoD1a, MyoD1b, MRF-4, IGF-1, IGF-2, and CAST-L) and the relationship of these genes with growth traits (length, weight, and condition factor) in six line crosses: both parental species, both reciprocal F1 hybrids, and both first-generation backcrosses (F1 x rainbow trout and F1 x cutthroat trout). Four of these genes were differentially expressed among rainbow, cutthroat, and their hybrids. Transcript abundance was significantly correlated with growth traits across the parent species, but not across hybrids. Our findings suggest that rainbow and cutthroat trout exhibit differences in muscle growth regulation, that transcriptional networks may be modified by hybridization, and that hybridization disrupts intrinsic relationships between gene expression and growth patterns that may be functionally important for phenotypic adaptations.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0141373","usgsCitation":"Ostberg, C.O., Chase, D.M., and Hauser, L., 2015, Hybridization between Yellowstone cutthroat trout and rainbow trout alters the expression of muscle growth-related genes and their relationships with growth patterns: PLoS ONE, v. 10, no. 10, e0141373; 16 p., https://doi.org/10.1371/journal.pone.0141373.","productDescription":"e0141373; 16 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065795","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":471655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0141373","text":"Publisher Index Page"},{"id":311167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-20","publicationStatus":"PW","scienceBaseUri":"56431533e4b0aafbcd017fac","contributors":{"authors":[{"text":"Ostberg, Carl O. 0000-0003-1479-8458 costberg@usgs.gov","orcid":"https://orcid.org/0000-0003-1479-8458","contributorId":3031,"corporation":false,"usgs":true,"family":"Ostberg","given":"Carl","email":"costberg@usgs.gov","middleInitial":"O.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chase, Dorothy M. dchase@usgs.gov","contributorId":4786,"corporation":false,"usgs":true,"family":"Chase","given":"Dorothy","email":"dchase@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":579395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hauser, Lorenz","contributorId":62510,"corporation":false,"usgs":true,"family":"Hauser","given":"Lorenz","email":"","affiliations":[],"preferred":false,"id":579396,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159525,"text":"70159525 - 2015 - Potential estrogenic effects of wastewaters on gene expression in Pimephales promelas and fish assemblages in streams of southeastern New York","interactions":[],"lastModifiedDate":"2018-08-09T12:37:29","indexId":"70159525","displayToPublicDate":"2015-11-10T14:45:00","publicationYear":"2015","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":"Potential estrogenic effects of wastewaters on gene expression in Pimephales promelas and fish assemblages in streams of southeastern New York","docAbstract":"Direct linkages between endocrine-disrupting compounds (EDCs) from municipal and industrial wastewaters and impacts on wild fish assemblages are rare. The levels of plasma vitellogenin (Vtg) and Vtg messenger ribonucleic acid (mRNA) in male fathead minnows (Pimephales promelas) exposed to wastewater effluents and dilutions of 17α-ethinylestradiol (EE2), estrogen activity, and fish assemblages in 10 receiving streams were assessed to improve understanding of important interrelations. Results from 4-d laboratory assays indicate that EE2, plasma Vtg concentration, and Vtg gene expression in fathead minnows, and 17β-estradiol equivalents (E2Eq values) were highly related to each other (R2 = 0.98–1.00). Concentrations of E2Eq in most effluents did not exceed 2.0 ng/L, which was possibly a short-term exposure threshold for Vtg gene expression in male fathead minnows. Plasma Vtg in fathead minnows only increased significantly (up to 1136 μg/mL) in 2 wastewater effluents. Fish assemblages were generally unaffected at 8 of 10 study sites, yet the density and biomass of 79% to 89% of species populations were reduced (63–68% were reduced significantly) in the downstream reach of 1 receiving stream. These results, and moderate to high E2Eq concentrations (up to 16.1 ng/L) observed in effluents during a companion study, suggest that estrogenic wastewaters can potentially affect individual fish, their populations, and entire fish communities in comparable systems across New York, USA.
","language":"English","publisher":"SETAC Press","doi":"10.1002/etc.3120","usgsCitation":"Baldigo, B.P., George, S.D., Phillips, P., Hemming, J.D., Denslow, N., and Kroll, K.J., 2015, Potential estrogenic effects of wastewaters on gene expression in Pimephales promelas and fish assemblages in streams of southeastern New York: Environmental Toxicology and Chemistry, v. 34, no. 12, p. 2803-2815, https://doi.org/10.1002/etc.3120.","productDescription":"13 p.","startPage":"2803","endPage":"2815","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043001","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471656,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.3120","text":"Publisher Index Page"},{"id":311165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.8336181640625,\n 41.25406487942273\n ],\n [\n -73.8336181640625,\n 41.53119809844284\n ],\n [\n -73.56170654296875,\n 41.53119809844284\n ],\n [\n -73.56170654296875,\n 41.25406487942273\n ],\n [\n -73.8336181640625,\n 41.25406487942273\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.267333984375,\n 42.037054301883806\n ],\n [\n -75.267333984375,\n 42.42142901536395\n ],\n [\n -74.14398193359375,\n 42.42142901536395\n ],\n [\n -74.14398193359375,\n 42.037054301883806\n ],\n [\n -75.267333984375,\n 42.037054301883806\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"12","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-01","publicationStatus":"PW","scienceBaseUri":"56431535e4b0aafbcd017fb4","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Patrick J. pjphilli@usgs.gov","contributorId":149753,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick J.","email":"pjphilli@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":579383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hemming, Joceyln D. C.","contributorId":149754,"corporation":false,"usgs":false,"family":"Hemming","given":"Joceyln","email":"","middleInitial":"D. C.","affiliations":[{"id":17815,"text":"Wisconsin State Laboratory of Hygiene","active":true,"usgs":false}],"preferred":false,"id":579385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Denslow, Nancy D.","contributorId":72831,"corporation":false,"usgs":true,"family":"Denslow","given":"Nancy D.","affiliations":[],"preferred":false,"id":579386,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kroll, Kevin J.","contributorId":82051,"corporation":false,"usgs":true,"family":"Kroll","given":"Kevin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":579387,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159497,"text":"70159497 - 2015 - Conservation planning for offsetting the impacts of development: a case study of biodiversity and renewable energy in the Mojave Desert","interactions":[],"lastModifiedDate":"2015-11-10T13:07:21","indexId":"70159497","displayToPublicDate":"2015-11-10T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Conservation planning for offsetting the impacts of development: a case study of biodiversity and renewable energy in the Mojave Desert","docAbstract":"Balancing society’s competing needs of development and conservation requires careful consideration of tradeoffs. Renewable energy development and biodiversity conservation are often considered beneficial environmental goals. The direct footprint and disturbance of renewable energy, however, can displace species’ habitat and negatively impact populations and natural communities if sited without ecological consideration. Offsets have emerged as a potentially useful tool to mitigate residual impacts after trying to avoid, minimize, or restore affected sites. Yet the problem of efficiently designing a set of offset sites becomes increasingly complex where many species or many sites are involved. Spatial conservation prioritization tools are designed to handle this problem, but have seen little application to offset siting and analysis. To address this need we designed an offset siting support tool for the Desert Renewable Energy Conservation Plan (DRECP) of California, and present a case study of hypothetical impacts from solar development in the Western Mojave subsection. We compare two offset scenarios designed to mitigate a hypothetical 15,331 ha derived from proposed utility-scale solar energy development (USSED) projects. The first scenario prioritizes offsets based precisely on impacted features, while the second scenario offsets impacts to maximize biodiversity conservation gains in the region. The two methods only agree on 28% of their prioritized sites and differ in meeting species-specific offset goals. Differences between the two scenarios highlight the importance of clearly specifying choices and priorities for offset siting and mitigation in general. Similarly, the effects of background climate and land use change may lessen the durability or effectiveness of offsets if not considered. Our offset siting support tool was designed specifically for the DRECP area, but with minor code modification could work well in other offset analyses, and could provide continuing support for a potentially innovative mitigation solution to environmental impacts.
","language":"English","publisher":"Public Library of Science (PLOS)","doi":"10.1371/journal.pone.0140226","usgsCitation":"Kreitler, J.R., Schloss, C.A., Soong, O., Hannah, L., and Davis, F., 2015, Conservation planning for offsetting the impacts of development: a case study of biodiversity and renewable energy in the Mojave Desert: PLoS ONE, v. 10, no. 11, e0140226; 15 p., https://doi.org/10.1371/journal.pone.0140226.","productDescription":"e0140226; 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058617","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0140226","text":"Publisher Index Page"},{"id":311163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.03759765625,\n 32.62087018318113\n ],\n [\n -116.488037109375,\n 33.26624989076275\n ],\n [\n -115.697021484375,\n 33.8339199536547\n ],\n [\n -117.454833984375,\n 34.31621838080741\n ],\n [\n -118.817138671875,\n 34.8047829195724\n ],\n [\n -117.88330078125,\n 35.69299463209881\n ],\n [\n -118.38867187500001,\n 37.212831514455964\n ],\n [\n -117.960205078125,\n 37.54457732085582\n ],\n [\n -114.63134765625001,\n 35.02099970111467\n ],\n [\n -114.12597656249999,\n 34.32529192442733\n ],\n [\n -114.58740234375,\n 33.44977658311846\n ],\n [\n -114.664306640625,\n 33.03629817885956\n ],\n [\n -114.488525390625,\n 33.02708758002874\n ],\n [\n -114.488525390625,\n 32.79651010951669\n ],\n [\n -114.67529296874999,\n 32.694865977875075\n ],\n [\n -116.03759765625,\n 32.62087018318113\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-03","publicationStatus":"PW","scienceBaseUri":"56431532e4b0aafbcd017f9e","contributors":{"authors":[{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":579234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schloss, Carrie A.","contributorId":149713,"corporation":false,"usgs":false,"family":"Schloss","given":"Carrie","email":"","middleInitial":"A.","affiliations":[{"id":17788,"text":"The Nature Conservancy of California","active":true,"usgs":false}],"preferred":false,"id":579235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soong, Oliver","contributorId":147794,"corporation":false,"usgs":false,"family":"Soong","given":"Oliver","email":"","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":579236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hannah, Lee","contributorId":149715,"corporation":false,"usgs":false,"family":"Hannah","given":"Lee","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":579239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Frank W.","contributorId":36894,"corporation":false,"usgs":true,"family":"Davis","given":"Frank W.","affiliations":[],"preferred":false,"id":579237,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169021,"text":"70169021 - 2015 - Shaping species with ephemeral boundaries: The distribution and genetic structure of desert tortoise (Gopherus morafkai) in the Sonoran Desert region","interactions":[],"lastModifiedDate":"2016-03-21T12:59:44","indexId":"70169021","displayToPublicDate":"2015-11-10T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Shaping species with ephemeral boundaries: The distribution and genetic structure of desert tortoise (Gopherus morafkai) in the Sonoran Desert region","docAbstract":"We examine the role biogeographical features played in the evolution of Morafka's desert tortoise (Gopherus morafkai) and test the hypothesis that G. morafkai maintains genetically distinct lineages associated with different Sonoran Desert biomes. Increased knowledge of the past and present distribution of the Sonoran Desert region's biota provides insight into the forces that drive and maintain its biodiversity.
\nSonoran Desert biogeographical region; Sonora and Sinaloa, Mexico and Arizona, USA.
\nWe examined wild tortoises from Mexico (n = 155) and Arizona (n = 78), spanning their known distribution. We used mtDNA sequences to reconstruct matrilineal relationships and 25 microsatellite (STR) loci for Bayesian analyses of gene flow. We performed clinal analyses on both mtDNA and STR loci to determine the position and amount of introgression where lineages co-occur. We used GIS to assess the association of genetic structuring with ecological features. We used these data in a hypothesis-driven approach to assess different models of how genetic diversity is maintained and distributed in G. morafkai.
\nGopherus morafkai was found to comprise genetically and geographically distinct ‘Sonoran’ and ‘Sinaloan’ lineages. Both lineages occurred in a relatively narrow zone of overlap in Sinaloan thornscrub, where it transitions into Sonoran desertscrub. Limited introgression occurred at the contact zone. The best-fit model suggests that these lineages diverged in parapatry where the distribution of genotypes is environment-dependent and introgression is inhibited by exogenous selection.
\nThe historically shifting ecotone between tropical deciduous forest and Sonoran desertscrub appears to be a boundary that fostered divergence between parapatric lineages of tortoises. The sharp genetic cline between the two lineages suggests that periods of isolation in temporary refugia due to Pleistocene climatic cycling influenced divergence. Despite incomplete reproductive isolation, the Sonoran and Sinaloan lineages of G. morafkai are on separate evolutionary trajectories.
","language":"English","publisher":"John Wiley & Sons Ltd.","doi":"10.1111/jbi.12664","usgsCitation":"Edwards, T., Vaughn, M., Rosen, P.C., Torres, M.C., Karl, A.E., Culver, M., and Murphy, R.W., 2015, Shaping species with ephemeral boundaries: The distribution and genetic structure of desert tortoise (Gopherus morafkai) in the Sonoran Desert region: Journal of Biogeography, v. 43, p. 484-497, https://doi.org/10.1111/jbi.12664.","productDescription":"14 p.","startPage":"484","endPage":"497","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061035","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471659,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.12664","text":"Publisher Index Page"},{"id":319095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, 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The federally threatened Piping Plover (Charadrius melodus; hereafter plovers) is a shorebird that breeds in three habitat types in the Prairie Pothole Region of North Dakota, South Dakota, and Canada: riverine sandbars; reservoir shorelines; and prairie wetlands. Water surface areas of these habitats fluctuate in response to wet-dry periods; decreasing water surface areas expose shorelines that plovers utilize for nesting. Climate varies across the region so when other habitats are unavailable for plover nesting because of flooding, prairie wetlands may periodically provide habitat. Over the last century, many of the wetlands used by plovers in the Prairie Pothole Region have been modified to receive water from consolidation drainage (drainage of smaller wetlands into another wetland), which could eliminate shoreline nesting habitat. We evaluated whether consolidation drainage and fuller wetlands have decreased plover presence in 32 wetlands historically used by plovers. We found that wetlands with more consolidation drainage in their catchment and wetlands that were fuller had a lower probability of plover presence. These results suggest that plovers could have historically used prairie wetlands during the breeding season but consolidation drainage and/or climate change have reduced available shoreline habitat for plovers through increased water levels. Prairie wetlands, outside of some alkali wetlands in the western portion of the region, are less studied as habitat for plovers when compared to river and reservoir shorelines. Our study suggests that these wetlands may have played a larger role in plover ecology than previously thought. Wetland restoration and conservation, through the restoration of natural hydrology, may be required to ensure that adequate habitat exists among the three habitat types in the face of existing or changing climate and to ensure long-term conservation.
","language":"English","publisher":"Scientific Journals","doi":"10.3996/072015-JFWM-068","usgsCitation":"McCauley, L.A., Anteau, M.J., and Post van der Burg, M., 2015, Consolidation drainage and climate change may reduce Piping Plover habitat in the Great Plains: Journal of Fish and Wildlife Management, v. 7, no. 1, 9 p., https://doi.org/10.3996/072015-JFWM-068.","productDescription":"9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060019","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":311113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.029541015625,\n 48.45835188280866\n ],\n [\n -103.33740234375,\n 48.58932584966972\n ],\n [\n -102.7001953125,\n 48.545705491847464\n ],\n [\n -102.0849609375,\n 48.27588152743497\n ],\n [\n -101.414794921875,\n 48.144097934938884\n ],\n [\n -100.634765625,\n 48.16608541901253\n ],\n [\n -100.206298828125,\n 48.011975126709956\n ],\n [\n -99.84374999999999,\n 47.4355191531953\n ],\n [\n -99.68994140625,\n 46.392411189814645\n ],\n [\n -100.579833984375,\n 46.2330529447983\n ],\n [\n -100.6732177734375,\n 46.24824991289166\n ],\n [\n -100.71716308593749,\n 46.51351558059737\n ],\n [\n -100.84899902343749,\n 46.66074749832071\n ],\n [\n -100.975341796875,\n 46.88647742351024\n ],\n [\n -101.0797119140625,\n 47.12621341795227\n ],\n [\n -101.2664794921875,\n 47.18224592701489\n ],\n [\n -101.5521240234375,\n 47.37231462056695\n ],\n [\n -101.7498779296875,\n 47.42065432071321\n ],\n [\n -102.05749511718749,\n 47.43923470537306\n ],\n [\n -102.4530029296875,\n 47.431803338643334\n ],\n [\n -102.579345703125,\n 47.56170075451973\n ],\n [\n -102.557373046875,\n 47.71715357016648\n ],\n [\n -102.7386474609375,\n 47.85003078545827\n ],\n [\n -102.7001953125,\n 48.00094957553023\n ],\n [\n -102.9913330078125,\n 48.06706753191901\n ],\n [\n -103.150634765625,\n 48.0156497866894\n ],\n [\n -103.55712890625,\n 47.923704717745686\n ],\n [\n -103.765869140625,\n 48.103763074117765\n ],\n [\n -103.9251708984375,\n 48.334343174592014\n ],\n [\n -104.029541015625,\n 48.45835188280866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-01","publicationStatus":"PW","scienceBaseUri":"5641c3aae4b0831b7d62e725","contributors":{"authors":[{"text":"McCauley, Lisa A. lmccauley@usgs.gov","contributorId":5048,"corporation":false,"usgs":true,"family":"McCauley","given":"Lisa","email":"lmccauley@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":579519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":579518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":579520,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160098,"text":"70160098 - 2015 - Accounting for time- and space-varying changes in the gravity field to improve the network adjustment of relative-gravity data","interactions":[],"lastModifiedDate":"2015-12-14T11:38:47","indexId":"70160098","displayToPublicDate":"2015-11-09T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for time- and space-varying changes in the gravity field to improve the network adjustment of relative-gravity data","docAbstract":"The relative gravimeter is the primary terrestrial instrument for measuring spatially and temporally varying gravitational fields. The background noise of the instrument—that is, non-linear drift and random tares—typically requires some form of least-squares network adjustment to integrate data collected during a campaign that may take several days to weeks. Here, we present an approach to remove the change in the observed relative-gravity differences caused by hydrologic or other transient processes during a single campaign, so that the adjusted gravity values can be referenced to a single epoch. The conceptual approach is an example of coupled hydrogeophysical inversion, by which a hydrologic model is used to inform and constrain the geophysical forward model. The hydrologic model simulates the spatial variation of the rate of change of gravity as either a linear function of distance from an infiltration source, or using a 3-D numerical groundwater model. The linear function can be included in and solved for as part of the network adjustment. Alternatively, the groundwater model is used to predict the change of gravity at each station through time, from which the accumulated gravity change is calculated and removed from the data prior to the network adjustment. Data from a field experiment conducted at an artificial-recharge facility are used to verify our approach. Maximum gravity change due to hydrology (observed using a superconducting gravimeter) during the relative-gravity field campaigns was up to 2.6 μGal d−1, each campaign was between 4 and 6 d and one month elapsed between campaigns. The maximum absolute difference in the estimated gravity change between two campaigns, two months apart, using the standard network adjustment method and the new approach, was 5.5 μGal. The maximum gravity change between the same two campaigns was 148 μGal, and spatial variation in gravity change revealed zones of preferential infiltration and areas of relatively high groundwater storage. The accommodation for spatially varying gravity change would be most important for long-duration campaigns, campaigns with very rapid changes in gravity and (or) campaigns where especially precise observed relative-gravity differences are used in the network adjustment.
","language":"English","publisher":"Published for the Royal Astronomical Society, the Deutsche Geophysikalische Gesellschaft, and the European Geophysical Society by Blackwell Scientific Publications","publisherLocation":"Oxford, UK","doi":"10.1093/gji/ggv493","usgsCitation":"Kennedy, J.R., and Ferre, T.P., 2015, Accounting for time- and space-varying changes in the gravity field to improve the network adjustment of relative-gravity data: Geophysical Journal International, v. 2, no. 204, p. 892-906, https://doi.org/10.1093/gji/ggv493.","productDescription":"15 p.","startPage":"892","endPage":"906","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067380","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471661,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggv493","text":"Publisher Index Page"},{"id":312246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"204","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-10","publicationStatus":"PW","scienceBaseUri":"566ff63be4b09cfe53ca7965","contributors":{"authors":[{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferre, Ty P.A.","contributorId":102167,"corporation":false,"usgs":true,"family":"Ferre","given":"Ty","email":"","middleInitial":"P.A.","affiliations":[],"preferred":false,"id":581890,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159443,"text":"sir20155120 - 2015 - Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14","interactions":[],"lastModifiedDate":"2015-11-10T13:25:43","indexId":"sir20155120","displayToPublicDate":"2015-11-06T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5120","title":"Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14","docAbstract":"Harmful cyanobacterial “algal” blooms (cyanoHABs) and associated toxins, such as microcystin, are a major water-quality issue for Lake Erie and inland lakes in Ohio. Predicting when and where a bloom may occur is important to protect the public that uses and consumes a water resource; however, predictions are complicated and likely site specific because of the many factors affecting toxin production. Monitoring for a variety of environmental and water-quality factors, for concentrations of cyanobacteria by molecular methods, and for algal pigments such as chlorophyll and phycocyanin by using optical sensors may provide data that can be used to predict the occurrence of cyanoHABs.
\nTo test these monitoring approaches, water-quality samples were collected at Ohio recreational sites during May–November in 2013 and 2014. In 2013, samples were collected monthly at eight sites at eight lakes to facilitate an initial assessment and select sites for more intensive sampling during 2014. In 2014, samples were collected approximately weekly at five sites at three lakes. Physical water-quality parameters were measured at the time of sampling. Composite samples were preserved and analyzed for dissolved and total nutrients, toxins, phytoplankton abundance and biovolume, and cyanobacterial genes by molecular methods. Molecular assays were done to enumerate (1) general cyanobacteria, (2) general Microcystis and Dolichospermum (Anabaena), (3) mcyE genes forMicrocystis, Dolichospermum (Anabaena), and Planktothrix targeting deoxyribonucleic acid (DNA), and (4) mcyE transcripts for Microcystis, Dolichospermum (Anabaena), and Planktothrix targeting ribonucleic acid (RNA).The DNA assays for the mcyE gene provide data on cyanobacteria that have the potential to produce microcystin, whereas the RNA assays provide data on cyanobacteria that are actively transcribing the toxin gene. Environmental data were obtained from available online sources. Quality-control (QC) samples were collected and analyzed for all constituents to characterize bias and variability; however, QC data for molecular assays were examined in more detail than for the other constituents. The QC data for molecular assays suggested that sampling variability and qPCR variability were small in comparison with the combined variability associated with sample filtering, extraction and purification, and the matrix itself.
\nA total of 46 water-quality samples were collected during 2013 at 8 beach sites—Buck Creek, Buckeye Crystal, Deer Creek, Harsha Main, Maumee Bay State Park (MBSP) Inland (negative control site), MBSP Lake Erie, Port Clinton, and Sandusky Bay. Microcystin was detected in 67–100 percent of samples at all sites except for MBSP Inland, where microcystin was detected in only 20 percent of samples. Microcystin concentrations ranged from <0.10 to 48 micrograms per liter (µ/L), with the widest range found at MBSP Lake Erie and the highest concentrations found at Buckeye Crystal. Saxitoxin was detected in five samples, and cylindrospermopsin was not detected in any samples.
\nA total of 65 water-quality samples were collected during 2014 at 5 sites on 3 lakes—Buckeye Fairfield and Onion Island, Harsha Main and Campers, and MBSP Lake Erie beach. Four of the sites were bathing beaches and one site, Onion Island, was an offshore boater swim area. Concentrations of microcystin ranged from <0.10 to 240 µ/L and, as in 2013, the widest range was found at MBSP Lake Erie. At Buckeye Lake, microcystin concentrations were consistently high (greater than 20 µ/L), ranging from 23 to 81 µ/L. At Harsha Main and Campers, microcystin concentrations ranged from <0.10 to 15 µ/L. Saxitoxin was detected in four samples collected at MBSP Lake Erie. Throughout the 2014 season, the cyanobacterial community, as determined by molecular and microscopy methods, and the dominance associated with the highest microcystin concentrations were unique to individual lakes. At Buckeye Lake, Planktothrix dominated the cyanobacterial community throughout the season and Planktothrix DNA and RNA were found in 100 percent of samples; Microcystis mcyE DNA was found in low concentrations. At Harsha Lake, Dolichospermum and Microcystis were a substantial percentage of the community from late May through August, and the highest microcystin concentrations occurred in June and July. At MBSP Lake Erie, Microcystis generally dominated from mid-July through early November, and the highest microcystin concentrations occurred in August.
\nSpearman’s correlation coefficient (rho) was computed to determine the relations between environmental and water-quality factors and microcystin concentrations at four sites—Buckeye Fairfield, Buckeye Onion Island, Harsha Main, and MBSP Lake Erie. Factors were evaluated for use as potential independent variables in two types of predictive models—daily and long-term models. Easily or continuously measured water-quality factors and available environmental data are used for daily predictions that do not require a site visit. Data from factors used in daily predictions and results from samples collected and analyzed in a laboratory are used for long-term predictions (a few days to several weeks). A few statistically significant correlations (p ≤ 0.05) between microcystin concentrations and factors for both daily and long-term predictions were found at Buckeye Onion Island, and many were found at Harsha Main and MBSP Lake Erie. There were only a few statistically significant factors for daily predictions at Buckeye Fairfield, likely because of the lack of variability in microcystin concentrations. Among factors for daily predictions, phycocyanin had the highest Spearman’s correlation to microcystin concentrations (rho = 0.79 to 0.93) at all sites except for Buckeye Fairfield. Turbidity, pH, algae category, and Secchi depth were significantly correlated to microcystin concentrations at Harsha Main and MBSP Lake Erie. Algae categories were observational categories from 0 (none) to 4 (extreme). Several discharge variables (Maumee River at Waterville, river mouth is approximately 3.5 miles from the beach) at MBSP Lake Erie were promising environmental factors for daily predictions. In addition to discrete water-quality measurements recorded at Harsha Main at the time of sampling, many manipulated measurements (factors derived from mathematical manipulation of time-series data) available from a nearby continuous monitor were strongly correlated to microcystin concentrations; the highest correlation was found for the relation between microcystin concentrations and the antecedent 7-day average phycocyanin (rho = 0.98). For long-term predictions, the most highly correlated molecular assays were Planktothrix mcyE DNA at Buckeye Onion Island and Microcystis mcyE DNA at Harsha Main and MBSP Lake Erie. Concentrations of several nutrient constituents were significantly correlated to microcystin concentrations including total nitrogen at Buckeye Onion Island, ammonia and nitrate plus nitrite (both negatively correlated) at Harsha Main and MBSP Lake Erie, and total phosphorus at MBSP Lake Erie.
\nThe results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155120","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Francy, D.S., Graham, J.L., Stelzer, E.A., Ecker, C.D., Brady, A.M.G., Struffolino, Pamela, and Loftin, K.A., 2015, Water quality, cyanobacteria, and environmental factors and their relations to microcystin concentrations for use in predictive models at Ohio Lake Erie and inland lake recreational sites, 2013–14: U.S. Geological Survey Scientific Investigations Report 2015–5120, 58 p., https://dx.doi.org/10.3133/sir20155120.","productDescription":"Report: vii, 58 p.; Appendix","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2013-05-01","temporalEnd":"2014-11-01","ipdsId":"IP-064699","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":310974,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5120/sir20155120.pdf","text":"Report","size":"9.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":310973,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5120/coverthb.jpg"},{"id":310975,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5120/sir20155120_appendix2_phytoplanktondata.xlsx","text":"Appendix 2","size":"181 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2","linkHelpText":"Phytoplankton abundance and community composition at Ohio recreational lake sites, 2013–14."}],"country":"United States","state":"Ohio","otherGeospatial":"Buck Creek State Park, Buckeye Lake State Park, Deer Creek State Park, East Fork State Park, Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.638916015625,\n 41.413895564677304\n ],\n [\n -83.638916015625,\n 41.7672146942102\n ],\n [\n -82.6556396484375,\n 41.7672146942102\n ],\n [\n -82.6556396484375,\n 41.413895564677304\n ],\n [\n -83.638916015625,\n 41.413895564677304\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.54440307617188,\n 39.89498716884207\n ],\n [\n -82.54440307617188,\n 39.94712141785606\n ],\n [\n -82.40432739257812,\n 39.94712141785606\n ],\n [\n -82.40432739257812,\n 39.89498716884207\n ],\n [\n -82.54440307617188,\n 39.89498716884207\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.17449951171875,\n 38.983965305617666\n ],\n [\n -84.17449951171875,\n 39.0533181067413\n ],\n [\n -84.05982971191406,\n 39.0533181067413\n ],\n [\n -84.05982971191406,\n 38.983965305617666\n ],\n [\n -84.17449951171875,\n 38.983965305617666\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.7546157836914,\n 39.94212035820183\n ],\n [\n -83.7546157836914,\n 39.99369266969988\n ],\n [\n -83.70586395263672,\n 39.99369266969988\n ],\n [\n -83.70586395263672,\n 39.94212035820183\n ],\n [\n -83.7546157836914,\n 39.94212035820183\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.27104568481445,\n 39.59748778978444\n ],\n [\n -83.27104568481445,\n 39.64535376010791\n ],\n [\n -83.21285247802734,\n 39.64535376010791\n ],\n [\n -83.21285247802734,\n 39.59748778978444\n ],\n [\n -83.27104568481445,\n 39.59748778978444\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio Water Science Center
U.S. Geological Survey
6480 Doubletree Ave
Columbus, OH 43229-1111
http://oh.water.usgs.gov/