Oligotrophication of Lake Ontario has led to increased water clarity and an increased proportion of zooplankton residing in the metalimnion during the day, which may affect the utilization of different depth regions for planktivorous fish. We investigated day and night distributions of fish using hydroacoustics and suspended vertical gillnets during the summer of 2013 when a deep chlorophyll layer (DCL) was established. We related fish distributions to concurrent measures of temperature and prey (zooplankton) density. Alewife dominated in vertical gill net catches, indicating that most acoustic targets were alewife. Alewife schooled during the day in the bottom of the mixed layer, and at dusk alewife schools broke up and fish moved towards the surface. We hypothesize this movement followed migrating zooplankton to allow feeding at night; alewife sampled from vertical gillnets fed on cyclopoid copepods and cladocerans, prey groups that migrate into the epilimnion at night. Some alewife remained at the bottom of the mixed layer at night and these fish ate deep-water calanoid copepods such as Limnocalanus. Vertical distributions were best predicted by temperature and the interaction between temperature and zooplankton density. We include uplooking acoustics data to complement our downlooking datasets, which provided evidence for potential bias in downlooking acoustic assessments of alewife due to high proportions of alewife found in the surface exclusion zone. Our approach combining several datasets provides a new perspective to understand summer diel distribution of alewife and the factors driving their distribution.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2017.07.007","usgsCitation":"Riha, M., Walsh, M., Connerton, M., Holden, J., Weidel, B., Sullivan, P.J., Holda, T.J., and Rudstam, L.G., 2017, Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use: Journal of Great Lakes Research, v. 43, no. 5, p. 823-837, https://doi.org/10.1016/j.jglr.2017.07.007.","productDescription":"15 p.","startPage":"823","endPage":"837","ipdsId":"IP-079963","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469466,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2017.07.007","text":"Publisher Index Page"},{"id":361464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Ontario ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.98596191406249,\n 43.12905229628564\n ],\n [\n -75.904541015625,\n 43.12905229628564\n ],\n [\n -75.904541015625,\n 44.4377021634654\n ],\n [\n -79.98596191406249,\n 44.4377021634654\n ],\n [\n -79.98596191406249,\n 43.12905229628564\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Riha, Milan","contributorId":213505,"corporation":false,"usgs":false,"family":"Riha","given":"Milan","email":"","affiliations":[{"id":38766,"text":"Institute of Hydrobiology, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":757859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Maureen 0000-0001-7846-5025 mwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-7846-5025","contributorId":3659,"corporation":false,"usgs":true,"family":"Walsh","given":"Maureen","email":"mwalsh@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":757858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connerton, Michael J.","contributorId":168904,"corporation":false,"usgs":false,"family":"Connerton","given":"Michael J.","affiliations":[{"id":25383,"text":"NY State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":757860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holden, Jeremy","contributorId":168905,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":757861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":757862,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Patrick J.","contributorId":213506,"corporation":false,"usgs":false,"family":"Sullivan","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":757863,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Holda, Toby J.","contributorId":213507,"corporation":false,"usgs":false,"family":"Holda","given":"Toby","email":"","middleInitial":"J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":757864,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rudstam, Lars G. 0000-0002-3732-6368","orcid":"https://orcid.org/0000-0002-3732-6368","contributorId":213508,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":757865,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70249340,"text":"70249340 - 2017 - How similar are forest disturbance maps derived from different Landsat time series algorithms?","interactions":[],"lastModifiedDate":"2023-10-05T00:18:45.62362","indexId":"70249340","displayToPublicDate":"2017-10-01T12:47:32","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"How similar are forest disturbance maps derived from different Landsat time series algorithms?","docAbstract":"Disturbance is a critical ecological process in forested systems, and disturbance maps are important for understanding forest dynamics. Landsat data are a key remote sensing dataset for monitoring forest disturbance and there recently has been major growth in the development of disturbance mapping algorithms. Many of these algorithms take advantage of the high temporal data volume to mine subtle signals in Landsat time series, but as those signals become subtler, they are more likely to be mixed with noise in Landsat data. This study examines the similarity among seven different algorithms in their ability to map the full range of magnitudes of forest disturbance over six different Landsat scenes distributed across the conterminous US. The maps agreed very well in terms of the amount of undisturbed forest over time; however, for the ~30% of forest mapped as disturbed in a given year by at least one algorithm, there was little agreement about which pixels were affected. Algorithms that targeted higher-magnitude disturbances exhibited higher omission errors but lower commission errors than those targeting a broader range of disturbance magnitudes. These results suggest that a user of any given forest disturbance map should understand the map’s strengths and weaknesses (in terms of omission and commission error rates), with respect to the disturbance targets of interest.
","language":"English","publisher":"MDPI","doi":"10.3390/f8040098","usgsCitation":"Cohen, W., Healey, S.P., Yang, Z., Stehman, S.V., Brewer, C.K., Brooks, E.B., Gorelick, N., Huang, C., Hughes, M.J., Kennedy, R.E., Loveland, T., Moisen, G.G., Schroeder, T.A., Vogelmann, J., Woodcock, C.E., Yang, L., and Zhu, Z., 2017, How similar are forest disturbance maps derived from different Landsat time series algorithms?: Forests, v. 8, no. 4, 98, 19 p., https://doi.org/10.3390/f8040098.","productDescription":"98, 19 p.","ipdsId":"IP-085817","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":461391,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f8040098","text":"Publisher Index Page"},{"id":421612,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-66.28243,18.51476],[-65.7713,18.42668],[-65.591,18.22803],[-65.84716,17.97591],[-66.59993,17.98182],[-67.18416,17.94655],[-67.24243,18.37446],[-67.10068,18.5206],[-66.28243,18.51476]]],[[[-155.54211,19.08348],[-155.68817,18.91619],[-155.93665,19.05939],[-155.90806,19.33888],[-156.07347,19.70294],[-156.02368,19.81422],[-155.85008,19.97729],[-155.91907,20.17395],[-155.86108,20.26721],[-155.78505,20.2487],[-155.40214,20.07975],[-155.22452,19.99302],[-155.06226,19.8591],[-154.80741,19.50871],[-154.83147,19.45328],[-155.22217,19.23972],[-155.54211,19.08348]]],[[[-156.07926,20.64397],[-156.41445,20.57241],[-156.58673,20.783],[-156.70167,20.8643],[-156.71055,20.92676],[-156.61258,21.01249],[-156.25711,20.91745],[-155.99566,20.76404],[-156.07926,20.64397]]],[[[-156.75824,21.17684],[-156.78933,21.06873],[-157.32521,21.09777],[-157.25027,21.21958],[-156.75824,21.17684]]],[[[-157.65283,21.32217],[-157.70703,21.26442],[-157.7786,21.27729],[-158.12667,21.31244],[-158.2538,21.53919],[-158.29265,21.57912],[-158.0252,21.71696],[-157.94161,21.65272],[-157.65283,21.32217]]],[[[-159.34512,21.982],[-159.46372,21.88299],[-159.80051,22.06533],[-159.74877,22.1382],[-159.5962,22.23618],[-159.36569,22.21494],[-159.34512,21.982]]],[[[-94.81758,49.38905],[-94.64,48.84],[-94.32914,48.67074],[-93.63087,48.60926],[-92.61,48.45],[-91.64,48.14],[-90.83,48.27],[-89.6,48.01],[-89.27292,48.01981],[-88.37811,48.30292],[-87.43979,47.94],[-86.46199,47.55334],[-85.65236,47.22022],[-84.87608,46.90008],[-84.77924,46.6371],[-84.54375,46.53868],[-84.6049,46.4396],[-84.3367,46.40877],[-84.14212,46.51223],[-84.09185,46.27542],[-83.89077,46.11693],[-83.61613,46.11693],[-83.46955,45.99469],[-83.59285,45.81689],[-82.55092,45.34752],[-82.33776,44.44],[-82.13764,43.57109],[-82.43,42.98],[-82.9,42.43],[-83.12,42.08],[-83.142,41.97568],[-83.02981,41.8328],[-82.69009,41.67511],[-82.43928,41.67511],[-81.27775,42.20903],[-80.24745,42.3662],[-78.93936,42.86361],[-78.92,42.965],[-79.01,43.27],[-79.17167,43.46634],[-78.72028,43.62509],[-77.73789,43.62906],[-76.82003,43.62878],[-76.5,44.01846],[-76.375,44.09631],[-75.31821,44.81645],[-74.867,45.00048],[-73.34783,45.00738],[-71.50506,45.0082],[-71.405,45.255],[-71.08482,45.30524],[-70.66,45.46],[-70.305,45.915],[-69.99997,46.69307],[-69.23722,47.44778],[-68.905,47.185],[-68.23444,47.35486],[-67.79046,47.06636],[-67.79134,45.70281],[-67.13741,45.13753],[-66.96466,44.8097],[-68.03252,44.3252],[-69.06,43.98],[-70.11617,43.68405],[-70.64548,43.09024],[-70.81489,42.8653],[-70.825,42.335],[-70.495,41.805],[-70.08,41.78],[-70.185,42.145],[-69.88497,41.92283],[-69.96503,41.63717],[-70.64,41.475],[-71.12039,41.49445],[-71.86,41.32],[-72.295,41.27],[-72.87643,41.22065],[-73.71,40.9311],[-72.24126,41.11948],[-71.945,40.93],[-73.345,40.63],[-73.982,40.628],[-73.95232,40.75075],[-74.25671,40.47351],[-73.96244,40.42763],[-74.17838,39.70926],[-74.90604,38.93954],[-74.98041,39.1964],[-75.20002,39.24845],[-75.52805,39.4985],[-75.32,38.96],[-75.07183,38.78203],[-75.05673,38.40412],[-75.37747,38.01551],[-75.94023,37.21689],[-76.03127,37.2566],[-75.72205,37.93705],[-76.23287,38.31921],[-76.35,39.15],[-76.54272,38.71762],[-76.32933,38.08326],[-76.99,38.23999],[-76.30162,37.91794],[-76.25874,36.9664],[-75.9718,36.89726],[-75.86804,36.55125],[-75.72749,35.55074],[-76.36318,34.80854],[-77.39763,34.51201],[-78.05496,33.92547],[-78.55435,33.86133],[-79.06067,33.49395],[-79.20357,33.15839],[-80.30132,32.50935],[-80.86498,32.0333],[-81.33629,31.44049],[-81.49042,30.72999],[-81.31371,30.03552],[-80.98,29.18],[-80.53558,28.47213],[-80.53,28.04],[-80.05654,26.88],[-80.08801,26.20576],[-80.13156,25.81677],[-80.38103,25.20616],[-80.68,25.08],[-81.17213,25.20126],[-81.33,25.64],[-81.71,25.87],[-82.24,26.73],[-82.70515,27.49504],[-82.85526,27.88624],[-82.65,28.55],[-82.93,29.1],[-83.70959,29.93656],[-84.1,30.09],[-85.10882,29.63615],[-85.28784,29.68612],[-85.7731,30.15261],[-86.4,30.4],[-87.53036,30.27433],[-88.41782,30.3849],[-89.18049,30.31598],[-89.59383,30.15999],[-89.41373,29.89419],[-89.43,29.48864],[-89.21767,29.29108],[-89.40823,29.15961],[-89.77928,29.30714],[-90.15463,29.11743],[-90.88022,29.14854],[-91.62678,29.677],[-92.49906,29.5523],[-93.22637,29.78375],[-93.84842,29.71363],[-94.69,29.48],[-95.60026,28.73863],[-96.59404,28.30748],[-97.14,27.83],[-97.37,27.38],[-97.38,26.69],[-97.33,26.21],[-97.14,25.87],[-97.53,25.84],[-98.24,26.06],[-99.02,26.37],[-99.3,26.84],[-99.52,27.54],[-100.11,28.11],[-100.45584,28.69612],[-100.9576,29.38071],[-101.6624,29.7793],[-102.48,29.76],[-103.11,28.97],[-103.94,29.27],[-104.45697,29.57196],[-104.70575,30.12173],[-105.03737,30.64402],[-105.63159,31.08383],[-106.1429,31.39995],[-106.50759,31.75452],[-108.24,31.75485],[-108.24194,31.34222],[-109.035,31.34194],[-111.02361,31.33472],[-113.30498,32.03914],[-114.815,32.52528],[-114.72139,32.72083],[-115.99135,32.61239],[-117.12776,32.53534],[-117.29594,33.04622],[-117.944,33.62124],[-118.4106,33.74091],[-118.51989,34.02778],[-119.081,34.078],[-119.43884,34.34848],[-120.36778,34.44711],[-120.62286,34.60855],[-120.74433,35.15686],[-121.71457,36.16153],[-122.54747,37.55176],[-122.51201,37.78339],[-122.95319,38.11371],[-123.7272,38.95166],[-123.86517,39.76699],[-124.39807,40.3132],[-124.17886,41.14202],[-124.2137,41.99964],[-124.53284,42.76599],[-124.14214,43.70838],[-124.02053,44.6159],[-123.89893,45.52341],[-124.07963,46.86475],[-124.39567,47.72017],[-124.68721,48.18443],[-124.5661,48.37971],[-123.12,48.04],[-122.58736,47.096],[-122.34,47.36],[-122.5,48.18],[-122.84,49],[-120,49],[-117.03121,49],[-116.04818,49],[-113,49],[-110.05,49],[-107.05,49],[-104.04826,48.99986],[-100.65,49],[-97.22872,49.0007],[-95.15907,49],[-95.15609,49.38425],[-94.81758,49.38905]]],[[[-153.00631,57.11584],[-154.00509,56.73468],[-154.5164,56.99275],[-154.67099,57.4612],[-153.76278,57.81657],[-153.22873,57.96897],[-152.56479,57.90143],[-152.14115,57.59106],[-153.00631,57.11584]]],[[[-165.57916,59.90999],[-166.19277,59.75444],[-166.84834,59.94141],[-167.45528,60.21307],[-166.46779,60.38417],[-165.67443,60.29361],[-165.57916,59.90999]]],[[[-171.73166,63.78252],[-171.11443,63.59219],[-170.49111,63.69498],[-169.68251,63.43112],[-168.68944,63.29751],[-168.77194,63.1886],[-169.52944,62.97693],[-170.29056,63.19444],[-170.67139,63.37582],[-171.55306,63.31779],[-171.79111,63.40585],[-171.73166,63.78252]]],[[[-155.06779,71.14778],[-154.34417,70.69641],[-153.90001,70.88999],[-152.21001,70.82999],[-152.27,70.60001],[-150.73999,70.43002],[-149.72,70.53001],[-147.61336,70.21403],[-145.68999,70.12001],[-144.92001,69.98999],[-143.58945,70.15251],[-142.07251,69.85194],[-140.98599,69.712],[-140.9925,66.00003],[-140.99777,60.3064],[-140.013,60.27684],[-139.039,60.00001],[-138.34089,59.56211],[-137.4525,58.905],[-136.47972,59.46389],[-135.47583,59.78778],[-134.945,59.27056],[-134.27111,58.86111],[-133.35555,58.41029],[-132.73042,57.69289],[-131.70781,56.55212],[-130.00778,55.91583],[-129.97999,55.285],[-130.53611,54.80275],[-131.08582,55.17891],[-131.96721,55.49778],[-132.25001,56.37],[-133.53918,57.17889],[-134.07806,58.12307],[-135.03821,58.18771],[-136.62806,58.21221],[-137.80001,58.5],[-139.86779,59.53776],[-140.82527,59.72752],[-142.57444,60.08445],[-143.95888,59.99918],[-145.92556,60.45861],[-147.11437,60.88466],[-148.22431,60.67299],[-148.01807,59.97833],[-148.57082,59.91417],[-149.72786,59.70566],[-150.60824,59.36821],[-151.71639,59.15582],[-151.85943,59.74498],[-151.40972,60.7258],[-150.34694,61.03359],[-150.62111,61.28442],[-151.89584,60.7272],[-152.57833,60.06166],[-154.01917,59.35028],[-153.28751,58.86473],[-154.23249,58.14637],[-155.30749,57.72779],[-156.30833,57.42277],[-156.5561,56.97998],[-158.11722,56.46361],[-158.43332,55.99415],[-159.60333,55.56669],[-160.28972,55.64358],[-161.22305,55.36473],[-162.23777,55.02419],[-163.06945,54.68974],[-164.78557,54.40417],[-164.94223,54.57222],[-163.84834,55.03943],[-162.87,55.34804],[-161.80417,55.89499],[-160.5636,56.00805],[-160.07056,56.41806],[-158.68444,57.01668],[-158.4611,57.21692],[-157.72277,57.57],[-157.55027,58.32833],[-157.04167,58.91888],[-158.19473,58.6158],[-158.51722,58.78778],[-159.05861,58.42419],[-159.71167,58.93139],[-159.98129,58.57255],[-160.35527,59.07112],[-161.355,58.67084],[-161.96889,58.67166],[-162.05499,59.26693],[-161.87417,59.63362],[-162.51806,59.98972],[-163.81834,59.79806],[-164.66222,60.26748],[-165.34639,60.5075],[-165.35083,61.0739],[-166.12138,61.50002],[-165.73445,62.075],[-164.91918,62.63308],[-164.56251,63.14638],[-163.75333,63.21945],[-163.06722,63.05946],[-162.26056,63.54194],[-161.53445,63.45582],[-160.77251,63.76611],[-160.95834,64.2228],[-161.51807,64.40279],[-160.77778,64.7886],[-161.39193,64.77724],[-162.45305,64.55944],[-162.75779,64.33861],[-163.54639,64.55916],[-164.96083,64.44695],[-166.42529,64.68667],[-166.845,65.0889],[-168.11056,65.67],[-166.70527,66.08832],[-164.47471,66.57666],[-163.65251,66.57666],[-163.7886,66.07721],[-161.67777,66.11612],[-162.48971,66.73557],[-163.71972,67.11639],[-164.43099,67.61634],[-165.39029,68.04277],[-166.76444,68.35888],[-166.20471,68.88303],[-164.43081,68.91554],[-163.16861,69.37111],[-162.93057,69.85806],[-161.9089,70.33333],[-160.9348,70.44769],[-159.03918,70.89164],[-158.11972,70.82472],[-156.58082,71.35776],[-155.06779,71.14778]]]]},\"properties\":{\"name\":\"United States\"}}]}","volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2017-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Cohen, Warren B.","contributorId":330528,"corporation":false,"usgs":false,"family":"Cohen","given":"Warren B.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":885238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Healey, Sean P.","contributorId":216816,"corporation":false,"usgs":false,"family":"Healey","given":"Sean","email":"","middleInitial":"P.","affiliations":[{"id":39526,"text":"USDA Forest Service, Rocky Mountain Research Station, 507 25th Street, Ogden, UT 84401","active":true,"usgs":false}],"preferred":false,"id":885239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yang, Zhiqiang","contributorId":330529,"corporation":false,"usgs":false,"family":"Yang","given":"Zhiqiang","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":885240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stehman, Stephen V. 0000-0001-5234-2027","orcid":"https://orcid.org/0000-0001-5234-2027","contributorId":216812,"corporation":false,"usgs":false,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[{"id":39524,"text":"College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA","active":true,"usgs":false}],"preferred":false,"id":885241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brewer, C. Kenneth","contributorId":330530,"corporation":false,"usgs":false,"family":"Brewer","given":"C.","email":"","middleInitial":"Kenneth","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":885242,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooks, Evan B.","contributorId":330531,"corporation":false,"usgs":false,"family":"Brooks","given":"Evan","email":"","middleInitial":"B.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":885243,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gorelick, Noel","contributorId":294417,"corporation":false,"usgs":false,"family":"Gorelick","given":"Noel","affiliations":[{"id":12484,"text":"Google","active":true,"usgs":false}],"preferred":false,"id":885244,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Huang, Chengquan 0000-0003-0055-9798","orcid":"https://orcid.org/0000-0003-0055-9798","contributorId":198972,"corporation":false,"usgs":false,"family":"Huang","given":"Chengquan","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":885245,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hughes, M. Joseph","contributorId":330534,"corporation":false,"usgs":false,"family":"Hughes","given":"M.","email":"","middleInitial":"Joseph","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":885246,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kennedy, Robert E.","contributorId":196025,"corporation":false,"usgs":false,"family":"Kennedy","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":885247,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885248,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moisen, Gretchen G.","contributorId":15781,"corporation":false,"usgs":false,"family":"Moisen","given":"Gretchen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":885249,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schroeder, Todd A. taschroeder@fs.fed.us","contributorId":190802,"corporation":false,"usgs":false,"family":"Schroeder","given":"Todd","email":"taschroeder@fs.fed.us","middleInitial":"A.","affiliations":[],"preferred":false,"id":885250,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":885251,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Woodcock, Curtis E.","contributorId":294423,"corporation":false,"usgs":false,"family":"Woodcock","given":"Curtis","email":"","middleInitial":"E.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":885252,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885253,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Zhu, Zhe","contributorId":260473,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhe","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":885254,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70192197,"text":"70192197 - 2017 - A method for quantifying cloud immersion in a tropical mountain forest using time-lapse photography","interactions":[],"lastModifiedDate":"2017-10-23T12:15:45","indexId":"70192197","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"A method for quantifying cloud immersion in a tropical mountain forest using time-lapse photography","docAbstract":"Quantifying the frequency, duration, and elevation range of fog or cloud immersion is essential to estimate cloud water deposition in water budgets and to understand the ecohydrology of cloud forests. The goal of this study was to develop a low-cost and high spatial-coverage method to detect occurrence of cloud immersion within a mountain cloud forest by using time-lapse photography. Trail cameras and temperature/relative humidity sensors were deployed at five sites covering the elevation range from the assumed lifting condensation level to the mountain peaks in the Luquillo Mountains of Puerto Rico. Cloud-sensitive image characteristics (contrast, the coefficient of variation and the entropy of pixel luminance, and image colorfulness) were used with a k-means clustering approach to accurately detect cloud-immersed conditions in a time series of images from March 2014 to May 2016. Images provided hydrologically meaningful cloud-immersion information while temperature-relative humidity data were used to refine the image analysis using dew point information and provided temperature gradients along the elevation transect. Validation of the image processing method with human-judgment based classification generally indicated greater than 90% accuracy. Cloud-immersion frequency averaged 80% at sites above 900 m during nighttime hours and 49% during daytime hours, and was consistent with diurnal patterns of cloud immersion measured in a previous study. Results for the 617 m site demonstrated that cloud immersion in the Luquillo Mountains rarely occurs at the previously-reported cloud base elevation of about 600 m (11% during nighttime hours and 5% during daytime hours). The framework presented in this paper will be used to monitor at a low cost and high spatial resolution the long-term variability of cloud-immersion patterns in the Luquillo Mountains, and can be applied to ecohydrology research at other cloud-forest sites or in coastal ecosystems with advective sea fog.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2017.04.010","usgsCitation":"Bassiouni, M., Scholl, M.A., Torres-Sanchez, A.J., and Murphy, S.F., 2017, A method for quantifying cloud immersion in a tropical mountain forest using time-lapse photography: Agricultural and Forest Meteorology, v. 243, p. 100-112, https://doi.org/10.1016/j.agrformet.2017.04.010.","productDescription":"13 p.","startPage":"100","endPage":"112","ipdsId":"IP-086096","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469543,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2017.04.010","text":"Publisher Index Page"},{"id":438199,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HQ3X52","text":"USGS data release","linkHelpText":"Supplementary Data for Method for Quantifying Cloud Immersion in a Tropical Mountain Forest Using Time-Lapse Photography"},{"id":347111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"El Yunque National Forest, Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.86647033691406,\n 18.242720598398734\n ],\n [\n -65.70270538330078,\n 18.242720598398734\n ],\n [\n -65.70270538330078,\n 18.34866001012719\n ],\n [\n -65.86647033691406,\n 18.34866001012719\n ],\n [\n -65.86647033691406,\n 18.242720598398734\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"243","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59eeffa3e4b0220bbd988f65","contributors":{"authors":[{"text":"Bassiouni, Maoya 0000-0001-5795-9894","orcid":"https://orcid.org/0000-0001-5795-9894","contributorId":197780,"corporation":false,"usgs":true,"family":"Bassiouni","given":"Maoya","affiliations":[],"preferred":false,"id":714696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":714695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Torres-Sanchez, Angel J. 0000-0002-5595-021X ajtorres@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-021X","contributorId":5623,"corporation":false,"usgs":true,"family":"Torres-Sanchez","given":"Angel","email":"ajtorres@usgs.gov","middleInitial":"J.","affiliations":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":714698,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196779,"text":"70196779 - 2017 - Influence of precipitation and crop germination on resource selection by mule deer (Odocoileus hemionus) in southwest Colorado","interactions":[],"lastModifiedDate":"2018-09-10T15:14:47","indexId":"70196779","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Influence of precipitation and crop germination on resource selection by mule deer (Odocoileus hemionus) in southwest Colorado","title":"Influence of precipitation and crop germination on resource selection by mule deer (Odocoileus hemionus) in southwest Colorado","docAbstract":"Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km2, and for two summer seasons that ranged between 5.51 and 6.24 km2. Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-017-15482-7","usgsCitation":"Carrollo, E.M., Johnson, H.E., Fischer, J.W., Hammond, M., Dorsey, P.D., Anderson, C., Vercauteren, K.C., and Walter, W.D., 2017, Influence of precipitation and crop germination on resource selection by mule deer (Odocoileus hemionus) in southwest Colorado: Scientific Reports, v. 7, p. 1-9, https://doi.org/10.1038/s41598-017-15482-7.","productDescription":"Article number: 15234; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-067881","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469480,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-017-15482-7","text":"Publisher Index Page"},{"id":353866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.27001953125,\n 37.48139702942734\n ],\n [\n -108.68362426757812,\n 37.48139702942734\n ],\n [\n -108.68362426757812,\n 37.924701076802094\n ],\n [\n -109.27001953125,\n 37.924701076802094\n ],\n [\n -109.27001953125,\n 37.48139702942734\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-09","publicationStatus":"PW","scienceBaseUri":"5afee7dee4b0da30c1bfc38f","contributors":{"authors":[{"text":"Carrollo, Emily M.","contributorId":204562,"corporation":false,"usgs":false,"family":"Carrollo","given":"Emily","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":734358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":734359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischer, Justin W.","contributorId":171828,"corporation":false,"usgs":false,"family":"Fischer","given":"Justin","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":734360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammond, Matthew","contributorId":204563,"corporation":false,"usgs":false,"family":"Hammond","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":734361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dorsey, Patricia D.","contributorId":204564,"corporation":false,"usgs":false,"family":"Dorsey","given":"Patricia","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":734362,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Charles","contributorId":204565,"corporation":false,"usgs":false,"family":"Anderson","given":"Charles","affiliations":[],"preferred":false,"id":734363,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vercauteren, Kurt C.","contributorId":193057,"corporation":false,"usgs":false,"family":"Vercauteren","given":"Kurt","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":734364,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Walter, W. David 0000-0003-3068-1073 wwalter@usgs.gov","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":5083,"corporation":false,"usgs":true,"family":"Walter","given":"W.","email":"wwalter@usgs.gov","middleInitial":"David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734345,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70192666,"text":"70192666 - 2017 - Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes","interactions":[],"lastModifiedDate":"2017-11-08T15:29:25","indexId":"70192666","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes","docAbstract":"Monitoring animal populations can be difficult. Limited resources often force monitoring programs to rely on unadjusted or smoothed counts as an index of abundance. Smoothing counts is commonly done using a moving-average estimator to dampen sampling variation. These indices are commonly used to inform management decisions, although their reliability is often unknown. We outline a process to evaluate the biological plausibility of annual changes in population counts and indices from a typical monitoring scenario and compare results with a hierarchical Bayesian time series (HBTS) model. We evaluated spring and fall counts, fall indices, and model-based predictions for the Rocky Mountain population (RMP) of Sandhill Cranes (Antigone canadensis) by integrating juvenile recruitment, harvest, and survival into a stochastic stage-based population model. We used simulation to evaluate population indices from the HBTS model and the commonly used 3-yr moving average estimator. We found counts of the RMP to exhibit biologically unrealistic annual change, while the fall population index was largely biologically realistic. HBTS model predictions suggested that the RMP changed little over 31 yr of monitoring, but the pattern depended on assumptions about the observational process. The HBTS model fall population predictions were biologically plausible if observed crane harvest mortality was compensatory up to natural mortality, as empirical evidence suggests. Simulations indicated that the predicted mean of the HBTS model was generally a more reliable estimate of the true population than population indices derived using a moving 3-yr average estimator. Practitioners could gain considerable advantages from modeling population counts using a hierarchical Bayesian autoregressive approach. Advantages would include: (1) obtaining measures of uncertainty; (2) incorporating direct knowledge of the observational and population processes; (3) accommodating missing years of data; and (4) forecasting population size.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-16-137.1","usgsCitation":"Gerber, B.D., and Kendall, W., 2017, Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes: The Condor, v. 119, no. 2, p. 191-206, https://doi.org/10.1650/CONDOR-16-137.1.","productDescription":"16 p.","startPage":"191","endPage":"206","ipdsId":"IP-070023","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469556,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-16-137.1","text":"Publisher Index Page"},{"id":348494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425b3e4b0dc0b45b45321","contributors":{"authors":[{"text":"Gerber, Brian D.","contributorId":187620,"corporation":false,"usgs":false,"family":"Gerber","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":721366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891 wkendall@usgs.gov","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":166709,"corporation":false,"usgs":true,"family":"Kendall","given":"William L.","email":"wkendall@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716678,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196730,"text":"70196730 - 2017 - Using long-term data to predict fish abundance: the case of Prochilodus lineatus (Characiformes, Prochilodontidae) in the intensely regulated upper Paraná River","interactions":[],"lastModifiedDate":"2018-04-27T13:48:58","indexId":"70196730","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2852,"text":"Neotropical Ichthyology","active":true,"publicationSubtype":{"id":10}},"title":"Using long-term data to predict fish abundance: the case of Prochilodus lineatus (Characiformes, Prochilodontidae) in the intensely regulated upper Paraná River","docAbstract":"Populations show spatial-temporal fluctuations in abundance, partly due to random processes and partly due to self-regulatory processes. We evaluated the effects of various external factors on the population numerical abundance of curimba Prochilodus lineatus in the upper Paraná River floodplain, Brazil, over a 19-year period. Panel data analysis was applied to examine the structure of temporal and spatial abundance while controlling auto-regressive processes and spatial non-homogeneity variances that often obscure relationships. As sources of population variation, we considered predation, competition, selected abiotic variables, construction of a dam upstream of the study area, water level and flood intensity during the spawning period. We found that biological interactions (predation and competition) were not significantly related to variations in curimba abundance; specific conductance was a space indicator of abundance, apparently linked to the biology of the species; intensity of floods determined inter-annual variation in abundances; Porto Primavera Dam negatively impacted the abundances at sites in the floodplain directly affected by discharges from the dam. Panel data analysis was a powerful tool that identified the need for intense flooding to maintain high abundances of curimba in the upper Paraná River. We believe our results apply to other species with similar life strategy.
","language":"English","publisher":"SciELO","doi":"10.1590/1982-0224-20160029","usgsCitation":"Piana, P.A., Cardoso, B.F., Dias, J., Gomes, L., Agostinho, A.A., and Miranda, L.E., 2017, Using long-term data to predict fish abundance: the case of Prochilodus lineatus (Characiformes, Prochilodontidae) in the intensely regulated upper Paraná River: Neotropical Ichthyology, v. 15, no. 3, p. 1-12, https://doi.org/10.1590/1982-0224-20160029.","productDescription":"e160029; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-075860","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469473,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1590/1982-0224-20160029","text":"Publisher Index Page"},{"id":353778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Paraná River","volume":"15","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee7dfe4b0da30c1bfc391","contributors":{"authors":[{"text":"Piana, Pitagoras A.","contributorId":204497,"corporation":false,"usgs":false,"family":"Piana","given":"Pitagoras","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cardoso, Barbara F.","contributorId":204498,"corporation":false,"usgs":false,"family":"Cardoso","given":"Barbara","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":734176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dias, Joilson","contributorId":204499,"corporation":false,"usgs":false,"family":"Dias","given":"Joilson","email":"","affiliations":[],"preferred":false,"id":734177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gomes, Luiz C.","contributorId":204500,"corporation":false,"usgs":false,"family":"Gomes","given":"Luiz C.","affiliations":[],"preferred":false,"id":734178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agostinho, Angelo A.","contributorId":204501,"corporation":false,"usgs":false,"family":"Agostinho","given":"Angelo","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734179,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734150,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193413,"text":"70193413 - 2017 - Are exposure predictions, used for the prioritization of pharmaceuticals in the environment, fit for purpose?","interactions":[],"lastModifiedDate":"2017-11-20T13:35:31","indexId":"70193413","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","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":"Are exposure predictions, used for the prioritization of pharmaceuticals in the environment, fit for purpose?","docAbstract":"Prioritization methodologies are often used for identifying those pharmaceuticals that pose the greatest risk to the natural environment and to focus laboratory testing or environmental monitoring toward pharmaceuticals of greatest concern. Risk-based prioritization approaches, employing models to derive exposure concentrations, are commonly used, but the reliability of these models is unclear. The present study evaluated the accuracy of exposure models commonly used for pharmaceutical prioritization. Targeted monitoring was conducted for 95 pharmaceuticals in the Rivers Foss and Ouse in the City of York (UK). Predicted environmental concentration (PEC) ranges were estimated based on localized prescription, hydrological data, reported metabolism, and wastewater treatment plant (WWTP) removal rates, and were compared with measured environmental concentrations (MECs). For the River Foss, PECs, obtained using highest metabolism and lowest WWTP removal, were similar to MECs. In contrast, this trend was not observed for the River Ouse, possibly because of pharmaceutical inputs unaccounted for by our modeling. Pharmaceuticals were ranked by risk based on either MECs or PECs. With 2 exceptions (dextromethorphan and diphenhydramine), risk ranking based on both MECs and PECs produced similar results in the River Foss. Overall, these findings indicate that PECs may well be appropriate for prioritization of pharmaceuticals in the environment when robust and local data on the system of interest are available and reflective of most source inputs.
","language":"English","publisher":"SETAC Press","doi":"10.1002/etc.3842","usgsCitation":"Burns, E.E., Thomas-Oates, J., Kolpin, D.W., Furlong, E.T., and Boxall, A.B., 2017, Are exposure predictions, used for the prioritization of pharmaceuticals in the environment, fit for purpose?: Environmental Toxicology and Chemistry, v. 36, no. 10, p. 2823-2832, https://doi.org/10.1002/etc.3842.","productDescription":"10 p.","startPage":"2823","endPage":"2832","ipdsId":"IP-084959","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":469564,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://orcid.org/0000-0003-4236-6409>,","text":"External Repository"},{"id":349138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Kingdom","city":"City of York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -1.1940765380859375,\n 53.911619008118656\n ],\n [\n -0.9976959228515625,\n 53.911619008118656\n ],\n [\n -0.9976959228515625,\n 54.05374516606874\n ],\n [\n -1.1940765380859375,\n 54.05374516606874\n ],\n [\n -1.1940765380859375,\n 53.911619008118656\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"10","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-06","publicationStatus":"PW","scienceBaseUri":"5a60fb44e4b06e28e9c22e91","contributors":{"authors":[{"text":"Burns, Emily E.","contributorId":199400,"corporation":false,"usgs":false,"family":"Burns","given":"Emily","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":718961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas-Oates, Jane","contributorId":195997,"corporation":false,"usgs":false,"family":"Thomas-Oates","given":"Jane","email":"","affiliations":[],"preferred":false,"id":718962,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":718959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":718960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boxall, Alistair B.A.","contributorId":187614,"corporation":false,"usgs":false,"family":"Boxall","given":"Alistair","email":"","middleInitial":"B.A.","affiliations":[],"preferred":false,"id":718963,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192801,"text":"70192801 - 2017 - Presentation and analysis of a worldwide database of earthquake-induced landslide inventories","interactions":[],"lastModifiedDate":"2017-11-29T13:40:16","indexId":"70192801","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Presentation and analysis of a worldwide database of earthquake-induced landslide inventories","docAbstract":"Earthquake-induced landslide (EQIL) inventories are essential tools to extend our knowledge of the relationship between earthquakes and the landslides they can trigger. Regrettably, such inventories are difficult to generate and therefore scarce, and the available ones differ in terms of their quality and level of completeness. Moreover, access to existing EQIL inventories is currently difficult because there is no centralized database. To address these issues, we compiled EQIL inventories from around the globe based on an extensive literature study. The database contains information on 363 landslide-triggering earthquakes and includes 66 digital landslide inventories. To make these data openly available, we created a repository to host the digital inventories that we have permission to redistribute through the U.S. Geological Survey ScienceBase platform. It can grow over time as more authors contribute their inventories. We analyze the distribution of EQIL events by time period and location, more specifically breaking down the distribution by continent, country, and mountain region. Additionally, we analyze frequency distributions of EQIL characteristics, such as the approximate area affected by landslides, total number of landslides, maximum distance from fault rupture zone, and distance from epicenter when the fault plane location is unknown. For the available digital EQIL inventories, we examine the underlying characteristics of landslide size, topographic slope, roughness, local relief, distance to streams, peak ground acceleration, peak ground velocity, and Modified Mercalli Intensity. Also, we present an evaluation system to help users assess the suitability of the available inventories for different types of EQIL studies and model development.
","language":"English","publisher":"AGU","doi":"10.1002/2017JF004236","usgsCitation":"Tanyas, H., van Westen, C.J., Allstadt, K.E., Nowicki Jessee, M., Gorum, T., Jibson, R.W., Godt, J.W., Sato, H., Schmitt, R.G., Marc, O., and Hovius, N., 2017, Presentation and analysis of a worldwide database of earthquake-induced landslide inventories: Journal of Geophysical Research F: Earth Surface, v. 122, no. 10, p. 1991-2015, https://doi.org/10.1002/2017JF004236.","productDescription":"25 p.","startPage":"1991","endPage":"2015","ipdsId":"IP-087814","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469483,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jf004236","text":"Publisher Index Page"},{"id":349542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-30","publicationStatus":"PW","scienceBaseUri":"5a60fb44e4b06e28e9c22e9d","contributors":{"authors":[{"text":"Tanyas, Hakan","contributorId":198731,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","affiliations":[],"preferred":false,"id":716989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Westen, Cees J.","contributorId":196188,"corporation":false,"usgs":false,"family":"van Westen","given":"Cees","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":716990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":716991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nowicki Jessee, M. Anna","contributorId":196186,"corporation":false,"usgs":false,"family":"Nowicki Jessee","given":"M. Anna","affiliations":[],"preferred":false,"id":716992,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gorum, Tolga","contributorId":196190,"corporation":false,"usgs":false,"family":"Gorum","given":"Tolga","affiliations":[],"preferred":false,"id":716993,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":716994,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":716995,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sato, Hiroshi P.","contributorId":196189,"corporation":false,"usgs":false,"family":"Sato","given":"Hiroshi P.","affiliations":[],"preferred":false,"id":716996,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schmitt, Robert G. 0000-0001-8060-1954 rschmitt@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-1954","contributorId":5611,"corporation":false,"usgs":true,"family":"Schmitt","given":"Robert","email":"rschmitt@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":716997,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Marc, Odin","contributorId":198732,"corporation":false,"usgs":false,"family":"Marc","given":"Odin","email":"","affiliations":[],"preferred":false,"id":716998,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hovius, Niels","contributorId":198733,"corporation":false,"usgs":false,"family":"Hovius","given":"Niels","email":"","affiliations":[],"preferred":false,"id":716999,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70192823,"text":"70192823 - 2017 - Surveillance for highly pathogenic influenza A viruses in California during 2014–2015 provides insights into viral evolutionary pathways and the spatiotemporal extent of viruses in the Pacific Americas Flyway","interactions":[],"lastModifiedDate":"2017-11-10T10:13:25","indexId":"70192823","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5203,"text":"Emerging Microbes & Infections","active":true,"publicationSubtype":{"id":10}},"title":"Surveillance for highly pathogenic influenza A viruses in California during 2014–2015 provides insights into viral evolutionary pathways and the spatiotemporal extent of viruses in the Pacific Americas Flyway","docAbstract":"We used surveillance data collected in California before, concurrent with, and subsequent to an outbreak of highly pathogenic (HP) clade 2.3.4.4 influenza A viruses (IAVs) in 2014–2015 to (i) evaluate IAV prevalence in waterfowl, (ii) assess the evidence for spill-over infections in marine mammals and (iii) genetically characterize low-pathogenic (LP) and HP IAVs to refine inference on the spatiotemporal extent of HP genome constellations and to evaluate possible evolutionary pathways. We screened samples from 1496 waterfowl and 1142 marine mammals collected from April 2014 to August 2015 and detected IAV RNA in 159 samples collected from birds (n=157) and pinnipeds (n=2). HP IAV RNA was identified in three samples originating from American wigeon (Anas americana). Genetic sequence data were generated for a clade 2.3.4.4 HP IAV-positive diagnostic sample and 57 LP IAV isolates. Phylogenetic analyses revealed that the HP IAV was a reassortant H5N8 virus with gene segments closely related to LP IAVs detected in mallards (Anas platyrhynchos) sampled in California and other IAVs detected in wild birds sampled within the Pacific Americas Flyway. In addition, our analysis provided support for common ancestry between LP IAVs recovered from waterfowl sampled in California and gene segments of reassortant HP H5N1 IAVs detected in British Columbia, Canada and Washington, USA. Our investigation provides evidence that waterfowl are likely to have played a role in the evolution of reassortant HP IAVs in the Pacific Americas Flyway during 2014–2015, whereas we did not find support for spill-over infections in potential pinniped hosts.
","language":"English","publisher":"Nature","doi":"10.1038/emi.2017.66","usgsCitation":"Ramey, A.M., Hill, N.J., Cline, T., Plancarte, M., De La Cruz, S., Casazza, M.L., Ackerman, J., Fleskes, J.P., Vickers, T.W., Reeves, A.B., Gulland, F., Fontaine, C., Prosser, D.J., Runstadler, J., and Boyce, W.M., 2017, Surveillance for highly pathogenic influenza A viruses in California during 2014–2015 provides insights into viral evolutionary pathways and the spatiotemporal extent of viruses in the Pacific Americas Flyway: Emerging Microbes & Infections, v. 6, p. 1-10, https://doi.org/10.1038/emi.2017.66.","productDescription":"e80; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-086106","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":482057,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/emi.2017.66","text":"Publisher Index Page"},{"id":348062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-15","publicationStatus":"PW","scienceBaseUri":"59fadd20e4b0531197b13c7b","contributors":{"authors":[{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":717066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Nichola J.","contributorId":189563,"corporation":false,"usgs":false,"family":"Hill","given":"Nichola","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":717067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cline, Troy","contributorId":198753,"corporation":false,"usgs":false,"family":"Cline","given":"Troy","affiliations":[],"preferred":false,"id":717068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plancarte, Magdalena","contributorId":198754,"corporation":false,"usgs":false,"family":"Plancarte","given":"Magdalena","email":"","affiliations":[],"preferred":false,"id":717069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De La Cruz, Susan sdelacruz@usgs.gov","contributorId":131159,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"sdelacruz@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":717070,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":717071,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":717072,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":177154,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":717073,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vickers, T. Winston","contributorId":198755,"corporation":false,"usgs":false,"family":"Vickers","given":"T.","email":"","middleInitial":"Winston","affiliations":[],"preferred":false,"id":717074,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":717075,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gulland, Frances","contributorId":198756,"corporation":false,"usgs":false,"family":"Gulland","given":"Frances","affiliations":[],"preferred":false,"id":717076,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Fontaine, Christine","contributorId":198757,"corporation":false,"usgs":false,"family":"Fontaine","given":"Christine","email":"","affiliations":[],"preferred":false,"id":717077,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":717078,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Runstadler, Jonathan","contributorId":198758,"corporation":false,"usgs":false,"family":"Runstadler","given":"Jonathan","affiliations":[],"preferred":false,"id":717079,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Boyce, Walter M.","contributorId":75671,"corporation":false,"usgs":true,"family":"Boyce","given":"Walter","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":717080,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70191902,"text":"70191902 - 2017 - Continuously amplified warming in the Alaskan Arctic: Implications for estimating global warming hiatus","interactions":[],"lastModifiedDate":"2017-10-18T16:12:02","indexId":"70191902","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Continuously amplified warming in the Alaskan Arctic: Implications for estimating global warming hiatus","docAbstract":"Historically, in situ measurements have been notoriously sparse over the Arctic. As a consequence, the existing gridded data of surface air temperature (SAT) may have large biases in estimating the warming trend in this region. Using data from an expanded monitoring network with 31 stations in the Alaskan Arctic, we demonstrate that the SAT has increased by 2.19°C in this region, or at a rate of 0.23°C/decade during 1921–2015. Meanwhile, we found that the SAT warmed at 0.71°C/decade over 1998–2015, which is 2 to 3 times faster than the rate established from the gridded data sets. Focusing on the “hiatus” period 1998–2012 as identified by the Intergovernmental Panel on Climate Change (IPCC) report, the SAT has increased at 0.45°C/decade, which captures more than 90% of the regional trend for 1951–2012. We suggest that sparse in situ measurements are responsible for underestimation of the SAT change in the gridded data sets. It is likely that enhanced climate warming may also have happened in the other regions of the Arctic since the late 1990s but left undetected because of incomplete observational coverage.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL074232","usgsCitation":"Wang, K., Zhang, T., Zhang, X., Clow, G.D., Jafarov, E.E., Overeem, I., Romanovsky, V., Peng, X., and Cao, B., 2017, Continuously amplified warming in the Alaskan Arctic: Implications for estimating global warming hiatus: Geophysical Research Letters, v. 44, no. 17, p. 9029-9038, https://doi.org/10.1002/2017GL074232.","productDescription":"10 p.","startPage":"9029","endPage":"9038","ipdsId":"IP-087891","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469468,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1396127","text":"External Repository"},{"id":346908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.3544921875,\n 67.65938637009882\n ],\n [\n -141.328125,\n 67.65938637009882\n ],\n [\n -141.328125,\n 71.49703690095419\n ],\n [\n -168.3544921875,\n 71.49703690095419\n ],\n [\n -168.3544921875,\n 67.65938637009882\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-13","publicationStatus":"PW","scienceBaseUri":"59e86833e4b05fe04cd4d1d8","contributors":{"authors":[{"text":"Wang, Kang","contributorId":197483,"corporation":false,"usgs":false,"family":"Wang","given":"Kang","email":"","affiliations":[],"preferred":false,"id":713597,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Tingjun","contributorId":197484,"corporation":false,"usgs":false,"family":"Zhang","given":"Tingjun","email":"","affiliations":[],"preferred":false,"id":713598,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Xiangdong","contributorId":197485,"corporation":false,"usgs":false,"family":"Zhang","given":"Xiangdong","email":"","affiliations":[],"preferred":false,"id":713599,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clow, Gary D. 0000-0002-2262-3853 clow@usgs.gov","orcid":"https://orcid.org/0000-0002-2262-3853","contributorId":2066,"corporation":false,"usgs":true,"family":"Clow","given":"Gary","email":"clow@usgs.gov","middleInitial":"D.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":713596,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jafarov, Elchin E.","contributorId":197486,"corporation":false,"usgs":false,"family":"Jafarov","given":"Elchin","email":"","middleInitial":"E.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":713600,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Overeem, Irina","contributorId":197487,"corporation":false,"usgs":false,"family":"Overeem","given":"Irina","email":"","affiliations":[],"preferred":false,"id":713601,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Romanovsky, Vladimir","contributorId":175208,"corporation":false,"usgs":false,"family":"Romanovsky","given":"Vladimir","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":713602,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peng, Xiaoqing","contributorId":197488,"corporation":false,"usgs":false,"family":"Peng","given":"Xiaoqing","email":"","affiliations":[],"preferred":false,"id":713603,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cao, Bin","contributorId":197489,"corporation":false,"usgs":false,"family":"Cao","given":"Bin","email":"","affiliations":[],"preferred":false,"id":713604,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70194203,"text":"70194203 - 2017 - Relative abundance of deformed wing virus, Varroa destructor virus 1, and their recombinants in honey bees (Apis mellifera) assessed by kmer analysis of public RNA-Seq data","interactions":[],"lastModifiedDate":"2017-11-17T14:55:44","indexId":"70194203","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2361,"text":"Journal of Invertebrate Pathology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Relative abundance of deformed wing virus, Varroa destructor virus 1, and their recombinants in honey bees (Apis mellifera) assessed by kmer analysis of public RNA-Seq data","title":"Relative abundance of deformed wing virus, Varroa destructor virus 1, and their recombinants in honey bees (Apis mellifera) assessed by kmer analysis of public RNA-Seq data","docAbstract":"Deformed wing virus (DWV) is a major pathogen of concern to apiculture, and recent reports have indicated the local predominance and potential virulence of recombinants between DWV and a related virus, Varroa destructor virus 1 (VDV). However, little is known about the frequency and titer of VDV and recombinants relative to DWV generally. In this study, I assessed the relative occurrence and titer of DWV and VDV in public RNA-seq accessions of honey bee using a rapid, kmer-based approach. Three recombinant types were detectable graphically and corroborated by de novo assembly. Recombination breakpoints did not disrupt the capsid-encoding region, consistent with previous reports, and both VDV- and DWV-derived capsids were observed in recombinant backgrounds. High abundance of VDV kmers was largely restricted to recombinant forms. Non-metric multidimensional scaling identified genotypic clusters among DWV isolates, which was corroborated by read mapping and consensus generation. The recently described DWV-C lineage was not detected in the searched accessions. The data further highlight the utility of high-throughput sequencing to monitor viral polymorphisms and statistically test biological predictors of titer, and point to the need for consistent methodologies and sampling schemes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jip.2017.07.005","usgsCitation":"Cornman, R.S., 2017, Relative abundance of deformed wing virus, Varroa destructor virus 1, and their recombinants in honey bees (Apis mellifera) assessed by kmer analysis of public RNA-Seq data: Journal of Invertebrate Pathology, v. 149, p. 44-50, https://doi.org/10.1016/j.jip.2017.07.005.","productDescription":"7 p.","startPage":"44","endPage":"50","ipdsId":"IP-085429","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":438200,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BK1B8P","text":"USGS data release","linkHelpText":"Provenance, classification, and abundance of RNA sequence fragments used to assess virus infections in honey bees, Apis mellifera"},{"id":349072,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"149","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb3ae4b06e28e9c22e1a","contributors":{"authors":[{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":722645,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70191363,"text":"70191363 - 2017 - A fault‐based model for crustal deformation in the western United States based on a combined inversion of GPS and geologic inputs","interactions":[],"lastModifiedDate":"2018-03-28T14:55:47","indexId":"70191363","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A fault‐based model for crustal deformation in the western United States based on a combined inversion of GPS and geologic inputs","docAbstract":"We develop a crustal deformation model to determine fault‐slip rates for the western United States (WUS) using the Zeng and Shen (2014) method that is based on a combined inversion of Global Positioning System (GPS) velocities and geological slip‐rate constraints. The model consists of six blocks with boundaries aligned along major faults in California and the Cascadia subduction zone, which are represented as buried dislocations in the Earth. Faults distributed within blocks have their geometrical structure and locking depths specified by the Uniform California Earthquake Rupture Forecast, version 3 (UCERF3) and the 2008 U.S. Geological Survey National Seismic Hazard Map Project model. Faults slip beneath a predefined locking depth, except for a few segments where shallow creep is allowed. The slip rates are estimated using a least‐squares inversion. The model resolution analysis shows that the resulting model is influenced heavily by geologic input, which fits the UCERF3 geologic bounds on California B faults and ±one‐half of the geologic slip rates for most other WUS faults. The modeled slip rates for the WUS faults are consistent with the observed GPS velocity field. Our fit to these velocities is measured in terms of a normalized chi‐square, which is 6.5. This updated model fits the data better than most other geodetic‐based inversion models. Major discrepancies between well‐resolved GPS inversion rates and geologic‐consensus rates occur along some of the northern California A faults, the Mojave to San Bernardino segments of the San Andreas fault, the western Garlock fault, the southern segment of the Wasatch fault, and other faults. Off‐fault strain‐rate distributions are consistent with regional tectonics, with a total off‐fault moment rate of
Responses in lake temperatures to climate warming have primarily been characterized using seasonal metrics of surface-water temperatures such as summertime or stratified period average temperatures. However, climate warming may not affect water temperatures equally across seasons or depths. We analyzed a long-term dataset (1981–2015) of biweekly water temperature data in six temperate lakes in Wisconsin, U.S.A. to understand (1) variability in monthly rates of surface- and deep-water warming, (2) how those rates compared to summertime average trends, and (3) if monthly heterogeneity in water temperature trends can be predicted by heterogeneity in air temperature trends. Monthly surface-water temperature warming rates varied across the open-water season, ranging from 0.013 in August to 0.073°C yr−1 in September (standard deviation [SD]: 0.025°C yr−1). Deep-water trends during summer varied less among months (SD: 0.006°C yr−1), but varied broadly among lakes (–0.056°C yr−1 to 0.035°C yr−1, SD: 0.034°C yr−1). Trends in monthly surface-water temperatures were well correlated with air temperature trends, suggesting monthly air temperature trends, for which data exist at broad scales, may be a proxy for seasonal patterns in surface-water temperature trends during the open water season in lakes similar to those studied here. Seasonally variable warming has broad implications for how ecological processes respond to climate change, because phenological events such as fish spawning and phytoplankton succession respond to specific, seasonal temperature cues.
","language":"English","publisher":"Wiley","doi":"10.1002/lno.10557","usgsCitation":"Winslow, L., Read, J.S., Hansen, G.J., Rose, K., and Robertson, D.M., 2017, Seasonality of change: Summer warming rates do not fully represent effects of climate change on lake temperatures: Limnology and Oceanography, v. 62, no. 5, p. 2168-2178, https://doi.org/10.1002/lno.10557.","productDescription":"11 p.","startPage":"2168","endPage":"2178","ipdsId":"IP-074340","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":469470,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10557","text":"Publisher Index Page"},{"id":346756,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","volume":"62","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-26","publicationStatus":"PW","scienceBaseUri":"59e71690e4b05fe04cd33188","contributors":{"authors":[{"text":"Winslow, Luke 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":168947,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":713035,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Gretchen J. A.","contributorId":131099,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","email":"","middleInitial":"J. A.","affiliations":[{"id":7242,"text":"Wisconsin Department of Natural Resources, Madison, WI, USA","active":true,"usgs":false}],"preferred":false,"id":713036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rose, Kevin C.","contributorId":64580,"corporation":false,"usgs":true,"family":"Rose","given":"Kevin C.","affiliations":[],"preferred":false,"id":713037,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713038,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194310,"text":"70194310 - 2017 - Harvesting wildlife affected by climate change: a modelling and management approach for polar bears","interactions":[],"lastModifiedDate":"2017-11-22T11:41:08","indexId":"70194310","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Harvesting wildlife affected by climate change: a modelling and management approach for polar bears","docAbstract":"If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double-observer models, distance sampling models and combined double-observer and distance sampling models (known as mark-recapture-distance-sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under-counted, but not over-counted. The estimator combines an MRDS model with an N-mixture model to account for imperfect detection of individuals. The new MRDS-Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS-Nmix model to an MRDS model. Abundance estimates generated by the MRDS-Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re-allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3284","usgsCitation":"Clement, M.J., Converse, S.J., and Royle, J., 2017, Accounting for imperfect detection of groups and individuals when estimating abundance: Ecology and Evolution, v. 7, no. 18, p. 7304-7310, https://doi.org/10.1002/ece3.3284.","productDescription":"7 p.","startPage":"7304","endPage":"7310","ipdsId":"IP-086061","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469478,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3284","text":"Publisher Index Page"},{"id":347004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"18","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-08","publicationStatus":"PW","scienceBaseUri":"59e9b992e4b05fe04cd65c51","contributors":{"authors":[{"text":"Clement, Matthew J. mclement@usgs.gov","contributorId":5278,"corporation":false,"usgs":true,"family":"Clement","given":"Matthew","email":"mclement@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":714185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":714063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":714064,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191365,"text":"70191365 - 2017 - Geothermal implications of a refined composition-age geologic map for the volcanic terrains of southeast Oregon, northeast California, and southwest Idaho, USA","interactions":[],"lastModifiedDate":"2017-10-16T14:49:49","indexId":"70191365","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geothermal implications of a refined composition-age geologic map for the volcanic terrains of southeast Oregon, northeast California, and southwest Idaho, USA","docAbstract":"Sufficient temperatures to generate steam likely exist under most of the dominantly volcanic terrains of southeast Oregon, northeast California, and southeast Idaho, USA, but finding sufficient permeability to allow efficient advective heat exchange is an outstanding challenge. A new thematic interpretation of existing state-level geologic maps provides an updated and refined distribution of the composition and age of geologic units for the purposes of assessing the implications for measurement and development of geothermal resources. This interpretation has been developed to better understand geothermal and hydrologic resources of the region. Comparison of the new geologic categories with available hydrologic data shows that younger volcanogenic terrains tend to have higher primary permeability than older terrains. Decrease in primary permeability with age is attributable to weathering and hydrothermal alteration of volcanogenic deposits to pore-filling clays and deposition of secondary deposits (e.g., zeolites). Spring density as a function of geology and precipitation can be used to infer groundwater flow path length within the upper aquifers. Beneath the upper aquifers, we postulate that, due to accelerated hydrothermal alteration at temperatures ~>30 °C, primary permeability at depths of geothermal interest will be limited, and that secondary permeability is a more viable target for hydrothermal fluid withdrawal. Because open fractures resulting from tensile stresses will affect all geologic layers, regions with a significant amount of groundwater flow through shallow, structurally controlled secondary permeability may overlay zones of deep secondary permeability. Regardless of whether the shallow permeability is connected with the deep permeability, shallow groundwater flow can mask the presence of deep hydrothermal flow, resulting in blind geothermal systems. Ideally, hydraulic connectivity between shallow and deep secondary permeability is limited, so that shallow groundwater does not cool potential geothermal reservoirs.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geothermal Resources Transactions","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Burns, E.R., Gannett, M.W., Sherrod, D.R., Keith, M.K., Curtis, J.A., Bartolino, J.R., Engott, J.A., Scandella, B.P., Stern, M.A., and Flint, A.L., 2017, Geothermal implications of a refined composition-age geologic map for the volcanic terrains of southeast Oregon, northeast California, and southwest Idaho, USA, in Geothermal Resources Transactions, v. 41.","ipdsId":"IP-086602","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":346637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346456,"type":{"id":15,"text":"Index Page"},"url":"https://geothermal.org/transactions.html"}],"volume":"41","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e5c51ce4b05fe04cd1c9de","contributors":{"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gannett, Marshall W. 0000-0003-2498-2427 mgannett@usgs.gov","orcid":"https://orcid.org/0000-0003-2498-2427","contributorId":2942,"corporation":false,"usgs":true,"family":"Gannett","given":"Marshall","email":"mgannett@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherrod, David R. 0000-0001-9460-0434 dsherrod@usgs.gov","orcid":"https://orcid.org/0000-0001-9460-0434","contributorId":527,"corporation":false,"usgs":true,"family":"Sherrod","given":"David","email":"dsherrod@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":712099,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keith, Mackenzie K. 0000-0002-7239-0576 mkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-7239-0576","contributorId":196963,"corporation":false,"usgs":true,"family":"Keith","given":"Mackenzie","email":"mkeith@usgs.gov","middleInitial":"K.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712100,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curtis, Jennifer A. 0000-0001-7766-994X jacurtis@usgs.gov","orcid":"https://orcid.org/0000-0001-7766-994X","contributorId":927,"corporation":false,"usgs":true,"family":"Curtis","given":"Jennifer","email":"jacurtis@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712101,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bartolino, James R. 0000-0002-2166-7803 jrbartol@usgs.gov","orcid":"https://orcid.org/0000-0002-2166-7803","contributorId":2548,"corporation":false,"usgs":true,"family":"Bartolino","given":"James","email":"jrbartol@usgs.gov","middleInitial":"R.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712102,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712103,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Scandella, Benjamin P.","contributorId":169274,"corporation":false,"usgs":false,"family":"Scandella","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":712104,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712105,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":712106,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70193534,"text":"70193534 - 2017 - Estimating Mudpuppy (Necturus maculosus) abundance in the Lamoille River, Vermont, USA","interactions":[],"lastModifiedDate":"2017-11-14T13:37:04","indexId":"70193534","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Estimating Mudpuppy (Necturus maculosus) abundance in the Lamoille River, Vermont, USA","title":"Estimating Mudpuppy (Necturus maculosus) abundance in the Lamoille River, Vermont, USA","docAbstract":"The Mudpuppy (Necturus maculosus) is classified as a Species of Greatest Conservation Need by the state of Vermont. There is concern regarding status of populations in the Lake Champlain basin because of habitat alteration and potential effects of 3-trifluromethyl-4-nitrophenol (TFM), a chemical used to control Sea Lamprey (Petromyzon marinus). The purpose of our research was to assess Mudpuppy capture methods and abundance in the Lamoille River, Vermont, USA. We sampled Mudpuppies under a mark-recapture framework, using modified, baited minnow traps set during two winter-spring periods. We marked each Mudpuppy with a passive integrated transponder (PIT) tag and released individuals after collecting morphological measurements. We collected 80 individuals during 2,581 trap days in 2008–2009 (year 1), and 81 individuals during 3,072 trap days in 2009–2010 (year 2). We estimated abundance from spring trapping periods in 2009 and 2010, during which capture rates were sufficient for analysis. Capture probability was low (< 0.04), but highest following precipitation events in spring, during periods of higher river flow, when water temperatures were approximately 3 to 6° C. During October 2009, management agencies treated the Lamoille River with TFM. Surveyors recovered more than 500 dead Mudpuppies during the post-treatment assessment. Overall, Mudpuppy captures did not change between sampling periods; however, we captured fewer females during year 2 compared to year 1, and the sex ratio changed from 0.79:1 (M:F) during year 1 to 3:1 (M:F) during year 2. Our data may help wildlife managers assess population status of Mudpuppies in conjunction with fisheries management techniques.
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Chellman, I.C., Parrish, D.L., and Donovan, T., 2017, Estimating Mudpuppy (Necturus maculosus) abundance in the Lamoille River, Vermont, USA: Herpetological Conservation and Biology, v. 12, no. 2, p. 422-434.","productDescription":"13 p.","startPage":"422","endPage":"434","ipdsId":"IP-056683","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Lamoille River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.17598342895506,\n 44.630489423286996\n ],\n [\n -73.16044807434082,\n 44.630489423286996\n ],\n [\n -73.16044807434082,\n 44.63983415674708\n ],\n [\n -73.17598342895506,\n 44.63983415674708\n ],\n [\n -73.17598342895506,\n 44.630489423286996\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb44e4b06e28e9c22e8e","contributors":{"authors":[{"text":"Chellman, Isaac C.","contributorId":200358,"corporation":false,"usgs":false,"family":"Chellman","given":"Isaac","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":722045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donovan, Therese M. tdonovan@usgs.gov","contributorId":2653,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese M.","email":"tdonovan@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":722046,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194544,"text":"70194544 - 2017 - Transmission routes maintaining a viral pathogen of steelhead trout within a complex multi-host assemblage","interactions":[],"lastModifiedDate":"2017-12-05T11:03:32","indexId":"70194544","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Transmission routes maintaining a viral pathogen of steelhead trout within a complex multi-host assemblage","docAbstract":"This is the first comprehensive region wide, spatially explicit epidemiologic analysis of surveillance data of the aquatic viral pathogen infectious hematopoietic necrosis virus (IHNV) infecting native salmonid fish. The pathogen has been documented in the freshwater ecosystem of the Pacific Northwest of North America since the 1950s, and the current report describes the disease ecology of IHNV during 2000–2012. Prevalence of IHNV infection in monitored salmonid host cohorts ranged from 8% to 30%, with the highest levels observed in juvenile steelhead trout. The spatial distribution of all IHNV-infected cohorts was concentrated in two sub-regions of the study area, where historic burden of the viral disease has been high. During the study period, prevalence levels fluctuated with a temporal peak in 2002. Virologic and genetic surveillance data were analyzed for evidence of three separate but not mutually exclusive transmission routes hypothesized to be maintaining IHNV in the freshwater ecosystem. Transmission between year classes of juvenile fish at individual sites (route 1) was supported at varying levels of certainty in 10%–55% of candidate cases, transmission between neighboring juvenile cohorts (route 2) was supported in 31%–78% of candidate cases, and transmission from adult fish returning to the same site as an infected juvenile cohort was supported in 26%–74% of candidate cases. The results of this study indicate that multiple specific transmission routes are acting to maintain IHNV in juvenile fish, providing concrete evidence that can be used to improve resource management. Furthermore, these results demonstrate that more sophisticated analysis of available spatio-temporal and genetic data is likely to yield greater insight in future studies.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3276","usgsCitation":"Breyta, R., Brito, I.L., Ferguson, P., Kurath, G., Naish, K.A., Purcell, M.K., Wargo, A.R., and LaDeau, S.L., 2017, Transmission routes maintaining a viral pathogen of steelhead trout within a complex multi-host assemblage: Ecology and Evolution, v. 7, no. 20, p. 8187-8200, https://doi.org/10.1002/ece3.3276.","productDescription":"14 p.","startPage":"8187","endPage":"8200","ipdsId":"IP-084983","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":469484,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3276","text":"Publisher Index Page"},{"id":349680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-111.044156,43.020052],[-111.046689,42.001567],[-113.893261,41.988057],[-114.831077,42.002207],[-121.035195,41.993323],[-123.145959,42.009247],[-123.656998,41.995137],[-124.211605,41.99846],[-124.270464,42.045553],[-124.299649,42.051736],[-124.356229,42.114952],[-124.361009,42.180752],[-124.383633,42.22716],[-124.410982,42.250547],[-124.410556,42.307431],[-124.429288,42.331746],[-124.424863,42.395426],[-124.434882,42.434916],[-124.390664,42.566593],[-124.401177,42.627192],[-124.413119,42.657934],[-124.45074,42.675798],[-124.473864,42.732671],[-124.491679,42.741789],[-124.510017,42.734746],[-124.552441,42.840568],[-124.456918,43.000315],[-124.434451,43.115986],[-124.401726,43.184896],[-124.38246,43.270167],[-124.402814,43.305872],[-124.373037,43.338953],[-124.341587,43.351337],[-124.315012,43.388389],[-124.233534,43.55713],[-124.168392,43.808903],[-124.142704,43.958182],[-124.111054,44.235071],[-124.1152,44.286486],[-124.084401,44.415611],[-124.071706,44.423662],[-124.084429,44.486927],[-124.067251,44.60804],[-124.082326,44.608861],[-124.065202,44.622445],[-124.058281,44.658866],[-124.070394,44.683514],[-124.059077,44.737656],[-124.075473,44.771403],[-124.074066,44.798107],[-124.025136,44.928175],[-124.004598,45.044959],[-124.017991,45.049808],[-124.015851,45.064759],[-123.989529,45.094045],[-123.975425,45.145476],[-123.964169,45.317026],[-123.972899,45.33689],[-124.007756,45.336813],[-123.973398,45.354791],[-123.965728,45.386242],[-123.960557,45.430778],[-123.976544,45.489733],[-123.957568,45.510399],[-123.939005,45.661923],[-123.943121,45.727031],[-123.982578,45.761815],[-123.969459,45.782371],[-123.962736,45.869974],[-123.96763,45.907807],[-123.993703,45.946431],[-123.969991,45.969139],[-123.941831,45.97566],[-123.927891,46.009564],[-123.933366,46.071672],[-123.974124,46.168798],[-124.024305,46.229256],[-124.001998,46.237316],[-123.987196,46.211521],[-123.950148,46.204097],[-123.9042,46.169293],[-123.854801,46.157342],[-123.841521,46.169824],[-123.863347,46.18235],[-123.838801,46.192211],[-123.636474,46.214359],[-123.625219,46.233868],[-123.605487,46.2393],[-123.586205,46.228654],[-123.548194,46.248245],[-123.547659,46.259109],[-123.669501,46.266832],[-123.680574,46.296025],[-123.700764,46.305278],[-123.75956,46.275073],[-123.806139,46.283588],[-123.875525,46.239787],[-123.909306,46.245491],[-123.985204,46.309039],[-124.020551,46.315737],[-124.044018,46.275925],[-124.080671,46.267239],[-124.057425,46.409315],[-124.069583,46.630651],[-124.048444,46.645827],[-124.035874,46.630822],[-124.052708,46.622796],[-124.023566,46.582559],[-124.026032,46.462978],[-123.990615,46.463019],[-123.988386,46.497008],[-123.97083,46.47537],[-123.943667,46.477197],[-123.894254,46.537028],[-123.928861,46.588875],[-123.955556,46.60357],[-123.960642,46.636364],[-123.921913,46.650262],[-123.923269,46.672708],[-123.851356,46.70256],[-123.84621,46.716795],[-123.893054,46.750204],[-123.929073,46.725278],[-123.968564,46.736106],[-123.979655,46.724658],[-123.966886,46.705184],[-124.003458,46.702337],[-124.092176,46.741624],[-124.108078,46.836388],[-124.138225,46.905534],[-124.117712,46.91238],[-124.093392,46.901168],[-124.089286,46.867716],[-124.073113,46.861493],[-124.055085,46.870429],[-124.049279,46.891253],[-123.985082,46.921916],[-123.86018,46.948556],[-123.898245,46.971927],[-124.012218,46.985176],[-124.019727,46.991189],[-124.005248,47.003915],[-124.026345,47.030187],[-124.122057,47.04165],[-124.151288,47.021112],[-124.124386,46.94387],[-124.180111,46.926357],[-124.169113,46.994508],[-124.182802,47.134041],[-124.236349,47.287287],[-124.271193,47.305025],[-124.299943,47.34836],[-124.319379,47.355559],[-124.355955,47.545698],[-124.425195,47.738434],[-124.453927,47.765334],[-124.471687,47.766907],[-124.489737,47.816988],[-124.539927,47.836967],[-124.562363,47.866216],[-124.625512,47.887963],[-124.645442,47.935338],[-124.672427,47.964414],[-124.696542,48.069274],[-124.688602,48.092466],[-124.731746,48.169997],[-124.696111,48.198599],[-124.6909,48.212617],[-124.705031,48.238774],[-124.684677,48.255228],[-124.65894,48.331057],[-124.731828,48.381157],[-124.653243,48.390691],[-124.631108,48.376522],[-124.599278,48.381035],[-124.395593,48.288772],[-124.361351,48.287582],[-124.272017,48.25441],[-124.238582,48.262471],[-124.101773,48.216883],[-124.107215,48.200082],[-124.050734,48.177747],[-123.981032,48.164761],[-123.858821,48.154273],[-123.672445,48.162715],[-123.628819,48.139279],[-123.590839,48.134949],[-123.551131,48.151382],[-123.507235,48.131807],[-123.440128,48.142014],[-123.441972,48.124259],[-123.424668,48.118065],[-123.332699,48.11297],[-123.239129,48.118217],[-123.133445,48.177276],[-123.143229,48.156633],[-123.06621,48.120469],[-123.038727,48.081138],[-122.929095,48.096244],[-122.917942,48.091535],[-122.927975,48.06665],[-122.877641,48.047025],[-122.849273,48.053808],[-122.878255,48.076072],[-122.882013,48.100779],[-122.833173,48.134406],[-122.760448,48.14324],[-122.748911,48.117026],[-122.801399,48.087561],[-122.766648,48.04429],[-122.74229,48.049324],[-122.739271,48.069153],[-122.747389,48.070795],[-122.733257,48.091232],[-122.68724,48.101662],[-122.69222,48.087081],[-122.669868,48.017217],[-122.723374,48.008095],[-122.718082,47.987739],[-122.683223,47.972226],[-122.681924,47.936415],[-122.651063,47.920985],[-122.646494,47.894771],[-122.610341,47.887343],[-122.63636,47.866186],[-122.69376,47.868002],[-122.683742,47.838773],[-122.748061,47.800546],[-122.758498,47.746036],[-122.781682,47.70392],[-122.811929,47.679861],[-122.832139,47.695511],[-122.790619,47.792597],[-122.812616,47.840029],[-122.820178,47.835904],[-122.815027,47.807493],[-122.845612,47.777474],[-122.896524,47.674838],[-122.97244,47.6149],[-123.106486,47.45817],[-123.15598,47.355745],[-123.140169,47.347496],[-123.111298,47.362619],[-123.120234,47.39149],[-122.967284,47.585685],[-122.856611,47.649615],[-122.754186,47.671612],[-122.740159,47.736228],[-122.714801,47.768176],[-122.690562,47.778372],[-122.684085,47.798574],[-122.608105,47.856728],[-122.573672,47.857582],[-122.588235,47.912923],[-122.616701,47.925139],[-122.617022,47.938987],[-122.603861,47.940478],[-122.592184,47.922519],[-122.549072,47.919072],[-122.513986,47.880807],[-122.506122,47.831745],[-122.482529,47.815511],[-122.495458,47.786692],[-122.470333,47.757109],[-122.488491,47.743605],[-122.554454,47.745704],[-122.543161,47.710941],[-122.504604,47.699136],[-122.518277,47.65132],[-122.493205,47.635122],[-122.49824,47.598242],[-122.483805,47.586721],[-122.543118,47.556326],[-122.547207,47.528257],[-122.494882,47.510265],[-122.530514,47.469041],[-122.531889,47.428827],[-122.551136,47.394456],[-122.537044,47.375896],[-122.573739,47.318419],[-122.550134,47.290496],[-122.589454,47.227618],[-122.611464,47.2181],[-122.692426,47.280026],[-122.671256,47.343774],[-122.634823,47.370583],[-122.639126,47.377822],[-122.725738,47.33047],[-122.749621,47.276408],[-122.641802,47.205013],[-122.711997,47.127681],[-122.771619,47.167109],[-122.832799,47.243412],[-122.799025,47.289306],[-122.803688,47.355071],[-122.821868,47.363069],[-122.822344,47.319763],[-122.863732,47.270221],[-122.838298,47.208353],[-122.858735,47.167955],[-122.814238,47.179482],[-122.775056,47.123114],[-122.721437,47.103179],[-122.67813,47.103866],[-122.631987,47.140589],[-122.614855,47.169143],[-122.590829,47.178107],[-122.527586,47.291531],[-122.547747,47.316403],[-122.4442,47.266723],[-122.409199,47.288556],[-122.444635,47.300421],[-122.423535,47.319121],[-122.324833,47.348521],[-122.328434,47.400621],[-122.348035,47.415921],[-122.355135,47.441921],[-122.383136,47.450521],[-122.368036,47.459221],[-122.365236,47.48842],[-122.396538,47.51522],[-122.398338,47.55012],[-122.421139,47.57602],[-122.387139,47.59572],[-122.358238,47.58482],[-122.339513,47.599113],[-122.367819,47.624213],[-122.414645,47.639766],[-122.429841,47.658919],[-122.37314,47.729219],[-122.397043,47.779719],[-122.394944,47.803318],[-122.339944,47.846718],[-122.307048,47.949117],[-122.230046,47.970917],[-122.224979,48.016626],[-122.343241,48.097631],[-122.363842,48.12393],[-122.370253,48.164809],[-122.362044,48.187568],[-122.395499,48.228551],[-122.449605,48.232598],[-122.441731,48.211776],[-122.478535,48.188087],[-122.479008,48.175703],[-122.442383,48.130841],[-122.379481,48.087384],[-122.363107,48.054546],[-122.4675,48.130353],[-122.486736,48.12095],[-122.512031,48.133931],[-122.53722,48.183745],[-122.530996,48.249821],[-122.480925,48.251706],[-122.466803,48.269604],[-122.406516,48.25183],[-122.371693,48.287839],[-122.408718,48.326413],[-122.533452,48.383409],[-122.554536,48.40604],[-122.557298,48.444438],[-122.649839,48.408526],[-122.678928,48.439466],[-122.654844,48.454087],[-122.657753,48.47294],[-122.689121,48.476849],[-122.700603,48.457632],[-122.710362,48.461584],[-122.712981,48.47879],[-122.684521,48.509123],[-122.606961,48.522152],[-122.568071,48.50821],[-122.537355,48.466749],[-122.500721,48.460887],[-122.471832,48.470724],[-122.498463,48.556206],[-122.534719,48.574246],[-122.495904,48.575927],[-122.482406,48.559653],[-122.44456,48.570115],[-122.425271,48.599522],[-122.500308,48.656163],[-122.519172,48.713095],[-122.490401,48.751128],[-122.535803,48.776128],[-122.596844,48.771492],[-122.637146,48.735708],[-122.612562,48.714932],[-122.605733,48.701066],[-122.615169,48.693839],[-122.673472,48.733082],[-122.645743,48.781538],[-122.680246,48.80275],[-122.693683,48.804475],[-122.703106,48.786321],[-122.7112,48.79146],[-122.717073,48.84719],[-122.793175,48.892927],[-122.751289,48.911239],[-122.746596,48.930731],[-122.766096,48.941955],[-122.787539,48.931702],[-122.818232,48.939062],[-122.817226,48.95597],[-122.796887,48.975026],[-122.756318,48.996881],[-116.049193,49.000912],[-116.04885,47.977186],[-116.030751,47.973349],[-115.906409,47.846261],[-115.881522,47.849672],[-115.852291,47.827991],[-115.835365,47.760957],[-115.824597,47.752154],[-115.803917,47.75848],[-115.780441,47.743447],[-115.776219,47.719818],[-115.72377,47.696671],[-115.73627,47.654762],[-115.694284,47.62346],[-115.689404,47.595402],[-115.734674,47.567401],[-115.747263,47.543197],[-115.717024,47.532693],[-115.686704,47.485596],[-115.655272,47.477944],[-115.654318,47.468077],[-115.671188,47.45439],[-115.718247,47.45316],[-115.731348,47.433381],[-115.657681,47.400651],[-115.644341,47.381826],[-115.609492,47.380799],[-115.556318,47.353076],[-115.51186,47.295219],[-115.428359,47.278722],[-115.410685,47.264228],[-115.326903,47.255912],[-115.29211,47.209861],[-115.300805,47.19393],[-115.261885,47.181742],[-115.243707,47.150347],[-115.200547,47.139154],[-115.140375,47.093013],[-115.107132,47.049041],[-115.087806,47.045519],[-115.049538,46.970774],[-115.001274,46.971901],[-114.963978,46.932889],[-114.929997,46.919625],[-114.931058,46.882108],[-114.947413,46.859324],[-114.928615,46.854815],[-114.920459,46.827697],[-114.888146,46.808573],[-114.864342,46.813858],[-114.829117,46.782503],[-114.79004,46.778729],[-114.765106,46.758153],[-114.788656,46.714033],[-114.76689,46.696901],[-114.713516,46.715138],[-114.699008,46.740223],[-114.649388,46.73289],[-114.620859,46.707415],[-114.623198,46.691511],[-114.641745,46.679286],[-114.635713,46.659375],[-114.595213,46.633456],[-114.547321,46.644485],[-114.466902,46.631695],[-114.424424,46.660648],[-114.360709,46.669059],[-114.320665,46.646963],[-114.348733,46.533792],[-114.342072,46.519679],[-114.35874,46.505306],[-114.403019,46.498675],[-114.376413,46.442983],[-114.384756,46.411784],[-114.422458,46.387097],[-114.411592,46.366688],[-114.413758,46.335945],[-114.431708,46.310744],[-114.425587,46.287899],[-114.470479,46.26732],[-114.445497,46.220227],[-114.445928,46.173933],[-114.472643,46.162202],[-114.514706,46.167726],[-114.527096,46.146218],[-114.5213,46.125287],[-114.474415,46.112515],[-114.460049,46.097104],[-114.468529,46.062484],[-114.493418,46.03717],[-114.470965,45.995742],[-114.425843,45.984984],[-114.403712,45.967049],[-114.431328,45.938023],[-114.387166,45.889164],[-114.409477,45.85164],[-114.44868,45.858891],[-114.509303,45.845531],[-114.512973,45.828825],[-114.562509,45.779927],[-114.495421,45.703321],[-114.507645,45.658949],[-114.561046,45.639906],[-114.538132,45.606834],[-114.559038,45.565706],[-114.460542,45.561283],[-114.456764,45.543983],[-114.415804,45.509753],[-114.36852,45.492716],[-114.360719,45.474116],[-114.333218,45.459316],[-114.270717,45.486116],[-114.247824,45.524283],[-114.248121,45.545877],[-114.192802,45.536596],[-114.180043,45.551432],[-114.135249,45.557465],[-114.122322,45.58426],[-114.086584,45.59118],[-114.067619,45.627706],[-114.018731,45.648616],[-114.019315,45.692937],[-113.986656,45.704564],[-113.93422,45.682232],[-113.898883,45.644167],[-113.904691,45.622007],[-113.861404,45.62366],[-113.806729,45.602146],[-113.803261,45.584193],[-113.834555,45.520729],[-113.766022,45.520621],[-113.759986,45.480735],[-113.78416,45.454946],[-113.764591,45.431403],[-113.765203,45.410601],[-113.734402,45.392353],[-113.738729,45.329741],[-113.689359,45.28355],[-113.684946,45.253706],[-113.599506,45.191114],[-113.57467,45.128411],[-113.554744,45.112901],[-113.513342,45.115225],[-113.506638,45.107288],[-113.520134,45.093033],[-113.485278,45.063519],[-113.45197,45.059247],[-113.437726,45.006967],[-113.446884,44.998545],[-113.443782,44.95989],[-113.498745,44.942314],[-113.455071,44.865424],[-113.356062,44.819798],[-113.3461,44.800611],[-113.354763,44.795468],[-113.341704,44.784853],[-113.247166,44.82295],[-113.131453,44.772837],[-113.134824,44.752763],[-113.102138,44.729027],[-113.098064,44.697477],[-113.06776,44.679474],[-113.068306,44.656374],[-113.049349,44.62938],[-113.083819,44.60222],[-113.019777,44.528505],[-113.020917,44.493827],[-113.003544,44.450814],[-112.951146,44.416699],[-112.886041,44.395874],[-112.855395,44.359975],[-112.814156,44.377198],[-112.812608,44.392275],[-112.836034,44.422653],[-112.781294,44.484888],[-112.71911,44.504344],[-112.664485,44.48645],[-112.541989,44.483971],[-112.50031,44.463051],[-112.473207,44.480027],[-112.387389,44.448058],[-112.358926,44.48628],[-112.35421,44.535638],[-112.319198,44.53911],[-112.286187,44.568472],[-112.242785,44.568091],[-112.221698,44.543519],[-112.183937,44.533067],[-112.136454,44.539911],[-112.106755,44.520829],[-112.069011,44.537104],[-112.036943,44.530323],[-112.032707,44.546642],[-111.980833,44.536682],[-111.947941,44.556776],[-111.870504,44.564033],[-111.821488,44.509286],[-111.715474,44.543543],[-111.704218,44.560205],[-111.617348,44.549467],[-111.591768,44.561502],[-111.471682,44.540824],[-111.469185,44.552044],[-111.519126,44.582916],[-111.525764,44.604883],[-111.473178,44.665479],[-111.468833,44.679335],[-111.484898,44.687578],[-111.486019,44.707654],[-111.438793,44.720546],[-111.414271,44.710741],[-111.385005,44.755128],[-111.355768,44.727602],[-111.323669,44.724474],[-111.26875,44.668279],[-111.276956,44.655626],[-111.25268,44.651092],[-111.224161,44.623402],[-111.225208,44.581006],[-111.189617,44.571062],[-111.143557,44.535732],[-111.122654,44.493659],[-111.048974,44.474072],[-111.044156,43.020052]]],[[[-122.519535,48.288314],[-122.551793,48.281512],[-122.584086,48.297987],[-122.618466,48.294159],[-122.623779,48.269431],[-122.652639,48.265081],[-122.668385,48.223967],[-122.63126,48.220686],[-122.588138,48.18594],[-122.558205,48.119579],[-122.571615,48.105113],[-122.54512,48.05255],[-122.516314,48.057181],[-122.511081,48.075301],[-122.525422,48.096537],[-122.513276,48.097538],[-122.491104,48.094242],[-122.431266,48.045001],[-122.376259,48.034457],[-122.373263,48.000791],[-122.353611,47.981433],[-122.349597,47.958796],[-122.380497,47.904023],[-122.431035,47.914732],[-122.445519,47.930226],[-122.446682,47.963155],[-122.47266,47.988449],[-122.546824,47.967215],[-122.542924,47.996404],[-122.607342,48.030992],[-122.593621,48.0472],[-122.614028,48.072788],[-122.598301,48.110616],[-122.609568,48.15186],[-122.633167,48.163281],[-122.679556,48.155113],[-122.693084,48.181509],[-122.770045,48.224395],[-122.72259,48.304268],[-122.673731,48.354683],[-122.664659,48.401508],[-122.634991,48.404244],[-122.637892,48.395681],[-122.60198,48.409907],[-122.585038,48.395166],[-122.585162,48.353304],[-122.506568,48.310041],[-122.519535,48.288314]]],[[[-122.474684,47.511068],[-122.452399,47.503471],[-122.460442,47.493764],[-122.433385,47.46643],[-122.437656,47.407424],[-122.373628,47.388718],[-122.437809,47.365606],[-122.453997,47.343337],[-122.51885,47.33332],[-122.528128,47.345542],[-122.517797,47.368678],[-122.526733,47.398581],[-122.514703,47.414048],[-122.513328,47.449106],[-122.482739,47.483133],[-122.474684,47.511068]]],[[[-122.695907,48.737273],[-122.663259,48.697077],[-122.618225,48.670721],[-122.609576,48.645018],[-122.673538,48.680809],[-122.691795,48.711498],[-122.718833,48.716818],[-122.715709,48.748672],[-122.695907,48.737273]]],[[[-123.035393,49.002154],[-123.021459,48.977299],[-123.083834,48.976139],[-123.090546,49.001976],[-123.035393,49.002154]]],[[[-122.800217,48.60169],[-122.801096,48.585425],[-122.771206,48.562426],[-122.788503,48.530393],[-122.779124,48.508911],[-122.816332,48.487841],[-122.81973,48.458843],[-122.802509,48.433098],[-122.812208,48.422326],[-122.874135,48.418196],[-122.893646,48.422655],[-122.889016,48.435947],[-122.928004,48.439966],[-122.91646,48.453263],[-122.926901,48.460874],[-122.962009,48.451161],[-123.039156,48.460003],[-123.119451,48.492576],[-123.163234,48.529544],[-123.173061,48.579086],[-123.203026,48.596178],[-123.178425,48.622115],[-123.107362,48.622451],[-123.102074,48.604035],[-123.048403,48.569216],[-122.987296,48.561895],[-122.995026,48.578162],[-123.034101,48.591767],[-123.024902,48.594484],[-123.048652,48.621002],[-122.941316,48.702904],[-122.894599,48.71503],[-122.743049,48.661991],[-122.809622,48.619035],[-122.800217,48.60169]]],[[[-123.197953,48.68466],[-123.14799,48.668001],[-123.106165,48.633473],[-123.237148,48.683466],[-123.197953,48.68466]]],[[[-123.025486,48.717966],[-123.009787,48.722291],[-123.005086,48.694342],[-123.021215,48.681416],[-123.042337,48.675663],[-123.035672,48.68535],[-123.047058,48.695772],[-123.070427,48.699971],[-123.025486,48.717966]]],[[[-122.649405,48.588457],[-122.583985,48.551534],[-122.572967,48.529028],[-122.599948,48.536904],[-122.649256,48.528769],[-122.649405,48.588457]]],[[[-122.714512,48.60878],[-122.670638,48.568812],[-122.68944,48.543903],[-122.717278,48.539739],[-122.73944,48.573893],[-122.714512,48.60878]]],[[[-122.699266,48.621115],[-122.674173,48.629944],[-122.657016,48.609891],[-122.699266,48.621115]]]]},\"properties\":{\"name\":\"Idaho\",\"nation\":\"USA \"}}]}","volume":"7","issue":"20","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-06","publicationStatus":"PW","scienceBaseUri":"5a60fb39e4b06e28e9c22e0b","contributors":{"authors":[{"text":"Breyta, Rachel","contributorId":150355,"corporation":false,"usgs":false,"family":"Breyta","given":"Rachel","affiliations":[],"preferred":false,"id":724406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brito, Ilana L.","contributorId":177102,"corporation":false,"usgs":false,"family":"Brito","given":"Ilana","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":724407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferguson, Paige","contributorId":201135,"corporation":false,"usgs":false,"family":"Ferguson","given":"Paige","affiliations":[],"preferred":false,"id":724408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":724405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Naish, Kerry A. 0000-0002-3275-8778","orcid":"https://orcid.org/0000-0002-3275-8778","contributorId":201136,"corporation":false,"usgs":false,"family":"Naish","given":"Kerry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724409,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":724410,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wargo, Andrew R.","contributorId":201137,"corporation":false,"usgs":false,"family":"Wargo","given":"Andrew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":724411,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LaDeau, Shannon L.","contributorId":172640,"corporation":false,"usgs":false,"family":"LaDeau","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":724412,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70191679,"text":"70191679 - 2017 - Large-scale modeled contemporary and future water temperature estimates for 10774 Midwestern U.S. Lakes","interactions":[],"lastModifiedDate":"2017-10-17T16:24:36","indexId":"70191679","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale modeled contemporary and future water temperature estimates for 10774 Midwestern U.S. Lakes","docAbstract":"Climate change has already influenced lake temperatures globally, but understanding future change is challenging. The response of lakes to changing climate drivers is complex due to the nature of lake-atmosphere coupling, ice cover, and stratification. To better understand the diversity of lake responses to climate change and give managers insight on individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota, and Wisconsin for contemporary (1979–2015) and future (2020–2040 and 2080–2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. In addition to lake-specific daily simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We include all supporting lake-specific model parameters, meteorological drivers, and archived code for the model and derived metric calculations. This unique dataset offers landscape-level insight into the impact of climate change on lakes.
","language":"English","publisher":"Nature","doi":"10.1038/sdata.2017.53","usgsCitation":"Winslow, L.A., Hansen, G.J., Read, J.S., and Notaro, M., 2017, Large-scale modeled contemporary and future water temperature estimates for 10774 Midwestern U.S. Lakes: Scientific Data, v. 4, p. 1-11, https://doi.org/10.1038/sdata.2017.53.","productDescription":"Article number: 170053; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-079867","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":482062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/sdata.2017.53","text":"Publisher Index Page"},{"id":346755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-83.880387,41.720089],[-86.824828,41.76024],[-86.24971,42.480212],[-86.226305,42.988284],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.110884,45.526285],[-84.94565,45.708621],[-85.011433,45.757962],[-84.204218,45.627116],[-84.095905,45.497298],[-83.488826,45.355872],[-83.316118,45.141958],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.915976,44.070503],[-82.617955,43.768596],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.431103,41.757457],[-83.880387,41.720089]]],[[[-90.418136,46.566094],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192],[-90.614589,42.508053],[-91.078097,42.806526],[-91.177728,43.118733],[-91.062562,43.243165],[-91.217706,43.50055],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.974286,49.367738],[-94.555835,48.716207],[-93.741843,48.517347],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.735927,47.624343],[-92.058888,46.809938],[-92.025789,46.710839],[-91.781928,46.697604],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.418136,46.566094]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Michigan\",\"nation\":\"USA \"}}]}","volume":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-25","publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd33182","contributors":{"authors":[{"text":"Winslow, Luke A. 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":5919,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":713042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Gretchen J. A.","contributorId":131099,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","email":"","middleInitial":"J. A.","affiliations":[{"id":7242,"text":"Wisconsin Department of Natural Resources, Madison, WI, USA","active":true,"usgs":false}],"preferred":false,"id":713043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":713044,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Notaro, Michael","contributorId":197249,"corporation":false,"usgs":false,"family":"Notaro","given":"Michael","email":"","affiliations":[],"preferred":false,"id":713045,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192157,"text":"70192157 - 2017 - Evaluating a kinematic method for generating broadband ground motions for great subduction zone earthquakes: Application to the 2003 Mw 8.3 Tokachi‐Oki earthquake","interactions":[],"lastModifiedDate":"2017-10-23T14:06:59","indexId":"70192157","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluating a kinematic method for generating broadband ground motions for great subduction zone earthquakes: Application to the 2003 Mw 8.3 Tokachi‐Oki earthquake","title":"Evaluating a kinematic method for generating broadband ground motions for great subduction zone earthquakes: Application to the 2003 Mw 8.3 Tokachi‐Oki earthquake","docAbstract":"We compare broadband synthetic seismograms with recordings of the 2003
Multibeam acoustic backscatter has considerable utility for remote characterization of spatially heterogeneous bed sediment composition over vegetated and unvegetated riverbeds of mixed sand and gravel. However, the use of high-frequency, decimeter-resolution acoustic backscatter for sediment classification in shallow water is hampered by significant topographic contamination of the signal. In mixed sand-gravel riverbeds, changes in the abiotic composition of sediment (such as homogeneous sand to homogeneous gravel) tend to occur over larger spatial scales than is characteristic of small-scale bedform topography (ripples, dunes, and bars) or biota (such as vascular plants and periphyton). A two-stage method is proposed to filter out the morphological contributions to acoustic backscatter. First, the residual supragrain-scale topographic effects in acoustic backscatter with small instantaneous insonified areas, caused by ambiguity in the local (beam-to-beam) bed-sonar geometry, are removed. Then, coherent scales between high-resolution topography and backscatter are identified using cospectra, which are used to design a frequency domain filter that decomposes backscatter into the (unwanted) high-pass component associated with bedform topography (ripples, dunes, and sand waves) and vegetation, and the (desired) low-frequency component associated with the composition of sediment patches superimposed on the topography. This process strengthens relationships between backscatter and sediment composition. A probabilistic framework is presented for classifying vegetated and unvegetated substrates based on acoustic backscatter at decimeter resolution. This capability is demonstrated using data collected from diverse settings within a 386 km reach of a canyon river whose bed varies among sand, gravel, cobbles, boulders, and submerged vegetation.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JF004302","usgsCitation":"Buscombe, D.D., Grams, P.E., and Kaplinski, M.A., 2017, Compositional signatures in acoustic backscatter over vegetated and unvegetated mixed sand-gravel riverbeds: Journal of Geophysical Research F: Earth Surface, v. 122, no. 10, p. 1771-1793, https://doi.org/10.1002/2017JF004302.","productDescription":"23 p.","startPage":"1771","endPage":"1793","ipdsId":"IP-085837","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":482058,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eartharxiv.org/a4q6m/","text":"External Repository"},{"id":438198,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7B56HM0","text":"USGS data release","linkHelpText":"Acoustic backscatter - Data and Python Code"},{"id":349234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado River, Grand Canyon, Glen Canyon, Marble Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.32922363281249,\n 35.60818490437746\n ],\n [\n -111.2640380859375,\n 35.60818490437746\n ],\n [\n -111.2640380859375,\n 37.081475648860525\n ],\n [\n -114.32922363281249,\n 37.081475648860525\n ],\n [\n -114.32922363281249,\n 35.60818490437746\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-13","publicationStatus":"PW","scienceBaseUri":"5a60fb44e4b06e28e9c22e97","contributors":{"authors":[{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":717192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":717191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaplinski, Matthew A.","contributorId":139210,"corporation":false,"usgs":false,"family":"Kaplinski","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":717193,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190030,"text":"70190030 - 2017 - Methane in aquifers used for public supply in the United States","interactions":[],"lastModifiedDate":"2018-03-15T14:54:36","indexId":"70190030","displayToPublicDate":"2017-09-30T00:00:00","publicationYear":"2017","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":"Methane in aquifers used for public supply in the United States","docAbstract":"In 2013 to 2015, 833 public supply wells in 15 Principal aquifers in the U.S. were sampled to identify which aquifers contained high methane concentrations (>1 mg/L) and determine the geologic, hydrologic, and geochemical conditions associated with high concentrations. This study represents the first national assessment of methane in aquifers used for public supply in the U.S. and, as such, advances the understanding of the occurrence and distribution of methane in groundwater nationally. Methane concentrations >1 and > 10 mg/L occurred in 6.7 and 1.1% of the samples, respectively. Most high concentrations occurred in aquifers in the Atlantic and Gulf Coastal Plain regions and upper Midwest. High methane concentrations were most commonly associated with Tertiary and younger aquifer sediments, old groundwater (>60 years), and concentrations of oxygen, nitrate-N, and sulfate <0.5 mg/L. Concentrations of methane were also positively correlated (p < 0.05) with dissolved organic carbon and ammonium. Case studies in Florida, Texas, and Iowa were used to explore how regional context from this data set could aid our understanding of local occurrences of methane in groundwater. Regional data for methane, Br/Cl ratios, sulfate, and other parameters helped identify mixing processes involving end members such as wastewater effluent-impacted groundwater, saline formation water, and pore water in glacial till that contributed methane to groundwater in some cases and supported methane oxidation in others.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2017.07.014","usgsCitation":"McMahon, P.B., Belitz, K., Barlow, J.R., and Jurgens, B.C., 2017, Methane in aquifers used for public supply in the United States: Applied Geochemistry, v. 84, p. 337-347, https://doi.org/10.1016/j.apgeochem.2017.07.014.","productDescription":"11 p.","startPage":"337","endPage":"347","ipdsId":"IP-078350","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":438204,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7377766","text":"USGS data release","linkHelpText":"Data from Methane in Aquifers Used for Public Supply in the United States"},{"id":352578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"84","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee7eae4b0da30c1bfc3b1","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":707250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":707251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Jeannie R. B. 0000-0002-0799-4656 jbarlow@usgs.gov","orcid":"https://orcid.org/0000-0002-0799-4656","contributorId":3701,"corporation":false,"usgs":true,"family":"Barlow","given":"Jeannie","email":"jbarlow@usgs.gov","middleInitial":"R. B.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":707252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":707253,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191338,"text":"70191338 - 2017 - Food-web dynamics and isotopic niches in deep-sea communities residing in a submarine canyon and on the adjacent open slopes","interactions":[],"lastModifiedDate":"2017-10-05T14:04:43","indexId":"70191338","displayToPublicDate":"2017-09-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Food-web dynamics and isotopic niches in deep-sea communities residing in a submarine canyon and on the adjacent open slopes","docAbstract":"Examination of food webs and trophic niches provide insights into organisms' functional ecology, yet few studies have examined trophodynamics within submarine canyons, where the interaction of canyon morphology and oceanography influences habitat provision and food deposition. Using stable isotope analysis and Bayesian ellipses, we documented deep-sea food-web structure and trophic niches in Baltimore Canyon and the adjacent open slopes in the US Mid-Atlantic Region. Results revealed isotopically diverse feeding groups, comprising approximately 5 trophic levels. Regression analysis indicated that consumer isotope data are structured by habitat (canyon vs. slope), feeding group, and depth. Benthic feeders were enriched in 13C and 15N relative to suspension feeders, consistent with consuming older, more refractory organic matter. In contrast, canyon suspension feeders had the largest and more distinct isotopic niche, indicating they consume an isotopically discrete food source, possibly fresher organic material. The wider isotopic niche observed for canyon consumers indicated the presence of feeding specialists and generalists. High dispersion in δ13C values for canyon consumers suggests that the isotopic composition of particulate organic matter changes, which is linked to depositional dynamics, resulting in discrete zones of organic matter accumulation or resuspension. Heterogeneity in habitat and food availability likely enhances trophic diversity in canyons. Given their abundance in the world's oceans, our results from Baltimore Canyon suggest that submarine canyons may represent important havens for trophic diversity.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps12231","usgsCitation":"Demopoulos, A.W., McClain-Counts, J., Ross, S.W., Brooke, S., and Mienis, F., 2017, Food-web dynamics and isotopic niches in deep-sea communities residing in a submarine canyon and on the adjacent open slopes: Marine Ecology Progress Series, v. 578, p. 19-33, https://doi.org/10.3354/meps12231.","productDescription":"15 p.","startPage":"19","endPage":"33","ipdsId":"IP-082908","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469493,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://imis.nioz.nl/imis.php?module=ref&refid=289810","text":"External Repository"},{"id":438203,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71N7Z9R","text":"USGS data release","linkHelpText":"Food-web dynamics and isotopic niches in deep-sea communities residing in a submarine canyon and on the adjacent open slopes"},{"id":346430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Baltimore Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.49853515625,\n 39.18117526158749\n ],\n [\n -74.94873046875,\n 36.66841891894786\n ],\n [\n -73.6083984375,\n 35.88905007936091\n ],\n [\n -72.13623046875,\n 36.686041276581925\n ],\n [\n -71.54296874999999,\n 38.61687046392973\n ],\n [\n -73.49853515625,\n 39.18117526158749\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"578","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d7449de4b05fe04cc7e306","contributors":{"authors":[{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":196216,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":711996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McClain-Counts, Jennifer 0000-0002-3383-5472 jmcclaincounts@usgs.gov","orcid":"https://orcid.org/0000-0002-3383-5472","contributorId":196217,"corporation":false,"usgs":true,"family":"McClain-Counts","given":"Jennifer","email":"jmcclaincounts@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":711997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ross, Steve W.","contributorId":72543,"corporation":false,"usgs":false,"family":"Ross","given":"Steve","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":711998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brooke, Sandra","contributorId":150169,"corporation":false,"usgs":false,"family":"Brooke","given":"Sandra","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":711999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mienis, Furu","contributorId":20255,"corporation":false,"usgs":true,"family":"Mienis","given":"Furu","affiliations":[],"preferred":false,"id":712000,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191213,"text":"70191213 - 2017 - Importance of scale, land cover, and weather on the abundance of bird species in a managed forest","interactions":[],"lastModifiedDate":"2018-03-15T11:05:20","indexId":"70191213","displayToPublicDate":"2017-09-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Importance of scale, land cover, and weather on the abundance of bird species in a managed forest","docAbstract":"Climate change and habitat loss are projected to be the two greatest drivers of biodiversity loss over the coming century. While public lands have the potential to increase regional resilience of bird populations to these threats, long-term data are necessary to document species responses to changes in climate and habitat to better understand population vulnerabilities. We used generalized linear mixed models to determine the importance of stand-level characteristics, multi-scale land cover, and annual weather factors to the abundance of 61 bird species over a 20-year time frame in Chippewa National Forest, Minnesota, USA. Of the 61 species modeled, we were able to build final models with R-squared values that ranged from 26% to 69% for 37 species; the remaining 24 species models had issues with convergence or low explanatory power (R-squared < 20%). Models for the 37 species show that stand-level characteristics, land cover factors, and annual weather effects on species abundance were species-specific and varied within guilds. Forty-one percent of the final species models included stand-level characteristics, 92% included land cover variables at the 200 m scale, 51% included land cover variables at the 500 m scale, 46% included land cover variables at the 1000 m scale, and 38% included weather variables in best models. Three species models (8%) included significant weather and land cover interaction terms. Overall, models indicated that aboveground tree biomass and land cover variables drove changes in the majority of species. Of those species models including weather variables, more included annual variation in precipitation or drought than temperature. Annual weather variability was significantly more likely to impact abundance of species associated with deciduous forests and bird species that are considered climate sensitive. The long-term data and models we developed are particularly suited to informing science-based adaptive forest management plans that incorporate climate sensitivity, aim to conserve large areas of forest habitat, and maintain an historical mosaic of cover types for conserving a diverse and abundant avian assemblage.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2017.09.057","usgsCitation":"Grinde, A.R., Hiemi, G.J., Sturtevant, B.R., Panci, H., Thogmartin, W.E., and Wolter, P., 2017, Importance of scale, land cover, and weather on the abundance of bird species in a managed forest: Forest Ecology and Management, v. 405, p. 295-308, https://doi.org/10.1016/j.foreco.2017.09.057.","productDescription":"14 p.","startPage":"295","endPage":"308","ipdsId":"IP-083833","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":469494,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/239","text":"Publisher Index Page"},{"id":352524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Chippewa National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.71588134765625,\n 46.80193957664001\n ],\n [\n -93.22998046875,\n 46.80193957664001\n ],\n [\n -93.22998046875,\n 47.8666165573186\n ],\n [\n -94.71588134765625,\n 47.8666165573186\n ],\n [\n -94.71588134765625,\n 46.80193957664001\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"405","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee7ebe4b0da30c1bfc3b3","contributors":{"authors":[{"text":"Grinde, Alexis R.","contributorId":196778,"corporation":false,"usgs":false,"family":"Grinde","given":"Alexis","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hiemi, Gerald J.","contributorId":196780,"corporation":false,"usgs":false,"family":"Hiemi","given":"Gerald","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sturtevant, Brian R.","contributorId":190143,"corporation":false,"usgs":false,"family":"Sturtevant","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Panci, Hannah","contributorId":196779,"corporation":false,"usgs":false,"family":"Panci","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":711558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":711556,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wolter, Peter","contributorId":196781,"corporation":false,"usgs":false,"family":"Wolter","given":"Peter","affiliations":[],"preferred":false,"id":711561,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191227,"text":"ds1065 - 2017 - Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) on the Middle San Luis Rey River, San Diego, southern California—2016 data summary","interactions":[],"lastModifiedDate":"2017-10-02T10:57:32","indexId":"ds1065","displayToPublicDate":"2017-09-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1065","displayTitle":"Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) on the Middle San Luis Rey River, San Diego, southern California—2016 data summary","title":"Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) on the Middle San Luis Rey River, San Diego, southern California—2016 data summary","docAbstract":"We surveyed for Least Bell’s Vireos (LBVI) (Vireo bellii pusillus) and Southwestern Willow Flycatchers (SWFL) (Empidonax traillii extimus) along the San Luis Rey River, between College Boulevard in Oceanside and Interstate 15 in Fallbrook, California (middle San Luis Rey River), in 2016. Surveys were done from March 30 to July 11 (LBVI) and from May 18 to July 30 (SWFL). We found 142 LBVI territories, at least 106 of which were occupied by pairs. Six additional transient LBVIs were detected. Of 20 banded LBVIs detected in the survey area, 9 had been given full color-band combinations prior to 2016, although we were unable to determine the exact color combination of 1 female LBVI. Seven other LBVIs with single (natal) federal bands were recaptured and banded in 2016. Four vireos with single dark blue federal bands indicating that they were banded as nestlings on the lower San Luis Rey River could not be recaptured for identification.
Three SFWL territories were observed in the survey area in 2016. Two territories were occupied by pairs and one by a male of unknown breeding status. Both pairs attempted to nest at least once, and both pairs were successful, fledging three young each. Nesting began in early June and continued into July. Brown-Headed Cowbird (Molothrus ater) eggs were not observed in either nest. An additional 12 transient Willow Flycatchers of unknown subspecies were detected in 2016.
Two of the five resident SWFLs were originally banded as nestlings on Marine Corps Base Camp Pendleton. One male and one female were banded as nestlings on Camp Pendleton in 2009 and 2011, respectively. One natal male of unknown breeding status, originally banded as a nestling on the middle San Luis Rey River in 2015, was recaptured and given a unique color combination in 2016. This male was later detected on Marine Corps Base Camp Pendleton.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1065","usgsCitation":"Allen, L.D., Howell, S.L., and Kus, B.E., 2017, Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) on the Middle San Luis Rey River, San Diego, southern California—2016 data summary: U.S. Geological Survey Data Series 1065, 11 p., https://doi.org/10.3133/ds1065.","productDescription":"iv, 11 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-087469","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":346297,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1065/coverthb.jpg"},{"id":346298,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1065/ds1065.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1065"}],"country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Middle San Luis Rey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.3020553588867,\n 33.244430403478276\n ],\n [\n -117.158203125,\n 33.244430403478276\n ],\n [\n -117.158203125,\n 33.324504165325195\n ],\n [\n -117.3020553588867,\n 33.324504165325195\n ],\n [\n -117.3020553588867,\n 33.244430403478276\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819