The composition of clinopyroxene and clinopyroxene-liquid (Cpx-Liq) pairs are frequently used to calculate crystallization/equilibration pressures in igneous systems. While canonical uncertainties are often assigned to calculated pressures based on fits to calibration or test datasets, the sources of these uncertainties (and thus ways to reduce them) have not been rigorously assessed. We show that considerable uncertainties in calculated pressures arise from analytical error associated with Electron Probe Microanalyser (EPMA) measurements of Cpx. Specifically, low X-ray counts during analysis of elements with concentrations <1 wt% resulting from insufficient count times and/or low beam currents yield highly imprecise measurements (1σ errors of 10–40% for Na2O).
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egac126","usgsCitation":"Wieser, P.E., Kent, A.J., Till, C.B., Donovan, J., Neave, D.A., Blatter, D.L., and Krawczynski, M.J., 2023, Barometers behaving badly: Assessing the influence of analytical and experimental uncertainty on clinopyroxene thermobarometry calculations at crustal conditions: Journal of Petrology, v. 64, no. 2, egac126, 27 p., https://doi.org/10.1093/petrology/egac126.","productDescription":"egac126, 27 p.","ipdsId":"IP-147233","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445017,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egac126","text":"Publisher Index Page"},{"id":416850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"64","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Wieser, Penny E. 0000-0002-1070-8323","orcid":"https://orcid.org/0000-0002-1070-8323","contributorId":272601,"corporation":false,"usgs":false,"family":"Wieser","given":"Penny","email":"","middleInitial":"E.","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":872109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kent, Adam J.R.","contributorId":292680,"corporation":false,"usgs":false,"family":"Kent","given":"Adam","email":"","middleInitial":"J.R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":872110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Till, Christy B. 0000-0001-8924-2206","orcid":"https://orcid.org/0000-0001-8924-2206","contributorId":304971,"corporation":false,"usgs":false,"family":"Till","given":"Christy","email":"","middleInitial":"B.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":872111,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donovan, J. 0000-0001-8639-0959","orcid":"https://orcid.org/0000-0001-8639-0959","contributorId":304972,"corporation":false,"usgs":false,"family":"Donovan","given":"J.","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":872112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neave, David A.","contributorId":304973,"corporation":false,"usgs":false,"family":"Neave","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":27871,"text":"University of Manchester","active":true,"usgs":false}],"preferred":false,"id":872113,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blatter, Dawnika L. 0000-0002-7161-6844 dblatter@usgs.gov","orcid":"https://orcid.org/0000-0002-7161-6844","contributorId":4899,"corporation":false,"usgs":true,"family":"Blatter","given":"Dawnika","email":"dblatter@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":872114,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krawczynski, Michael J. 0000-0002-0710-0763","orcid":"https://orcid.org/0000-0002-0710-0763","contributorId":304974,"corporation":false,"usgs":false,"family":"Krawczynski","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":62382,"text":"Washington University St. Louis","active":true,"usgs":false}],"preferred":false,"id":872115,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239117,"text":"70239117 - 2023 - Wild bee exposure to pesticides in conservation grasslands increases along an agricultural gradient: A tale of two sample types","interactions":[],"lastModifiedDate":"2023-01-18T17:29:21.089862","indexId":"70239117","displayToPublicDate":"2022-12-27T07:05:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Wild bee exposure to pesticides in conservation grasslands increases along an agricultural gradient: A tale of two sample types","docAbstract":"Conservation efforts have been implemented in agroecosystems to enhance pollinator diversity by creating grassland habitat, but little is known about the exposure of bees to pesticides while foraging in these grassland fields. Pesticide exposure was assessed in 24 conservation grassland fields along an agricultural gradient at two time points (July and August) using silicone band passive samplers (nonlethal) and bee tissues (lethal). Overall, 46 pesticides were detected including 9 herbicides, 19 insecticides, 17 fungicides, and a plant growth regulator. For the bands, there were more frequent/higher concentrations of herbicides in July (maximum: 1600 ng/band in July; 570 ng/band in August), while insecticides and fungicides had more frequent/higher concentrations in August (maximum: 110 and 65 ng/band in July; 1500 and 1700 ng/band in August). Pesticide concentrations in bands increased 16% with every 10% increase in cultivated crops. The bee tissues showed no difference in detection frequency, and concentrations were similar among months; maximum concentrations of herbicides, insecticides, and fungicides in July and August were 17, 27, and 180 and 19, 120, and 170 ng/g, respectively. Pesticide residues in bands and bee tissues did not always show the same patterns; of the 20 compounds observed in both media, six (primarily fungicides) showed a detection-concentration relationship between the two media. Together, the band and bee residue data can provide a more complete understanding of pesticide exposure and accumulation in conserved grasslands.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.2c07195","usgsCitation":"Hladik, M.L., Kraus, J.M., Smith, C., Vandever, M.W., Kolpin, D., Givens, C.E., and Smalling, K., 2023, Wild bee exposure to pesticides in conservation grasslands increases along an agricultural gradient: A tale of two sample types: Environmental Science and Technology, v. 57, no. 1, p. 321-330, https://doi.org/10.1021/acs.est.2c07195.","productDescription":"10 p.","startPage":"321","endPage":"330","ipdsId":"IP-145884","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":435530,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M3QCVW","text":"USGS data release","linkHelpText":"Pesticide residues in passive samplers and bee tissue from Conservation Reserve Program fields across an agricultural gradient in eastern Iowa, USA, 2019 (ver 2.0, October 2023)"},{"id":411113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.84229194623344,\n 43.40823254194967\n ],\n [\n -93.84229194623344,\n 40.49028000708452\n ],\n [\n -90.2987761617945,\n 40.49028000708452\n ],\n [\n -90.2987761617945,\n 43.40823254194967\n ],\n [\n -93.84229194623344,\n 43.40823254194967\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"57","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":203857,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":860114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Cassandra 0000-0003-1088-1772 cassandrasmith@usgs.gov","orcid":"https://orcid.org/0000-0003-1088-1772","contributorId":193491,"corporation":false,"usgs":true,"family":"Smith","given":"Cassandra","email":"cassandrasmith@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860115,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandever, Mark W. 0000-0003-0247-2629 vandeverm@usgs.gov","orcid":"https://orcid.org/0000-0003-0247-2629","contributorId":197674,"corporation":false,"usgs":true,"family":"Vandever","given":"Mark","email":"vandeverm@usgs.gov","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":860116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860117,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Givens, Carrie E. 0000-0003-2543-9610","orcid":"https://orcid.org/0000-0003-2543-9610","contributorId":247691,"corporation":false,"usgs":true,"family":"Givens","given":"Carrie","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860118,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860119,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239081,"text":"70239081 - 2023 - Mismatch between conservation status and climate change sensitivity leaves some anurans in the United States unprotected","interactions":[],"lastModifiedDate":"2022-12-26T17:20:39.632092","indexId":"70239081","displayToPublicDate":"2022-12-26T11:10:10","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Mismatch between conservation status and climate change sensitivity leaves some anurans in the United States unprotected","docAbstract":"Species vulnerable to climate change face increased extinction risk, but many sensitive species may be overlooked due to limited data and exclusion from vulnerability assessments. Intrinsic sensitivity, or the inherent risk of species to environmental change due to biological factors, can be assessed with widely available data and may address gaps in multispecies vulnerability assessments. Species that exist in few places (geographically rare) and in fewer climates (smaller realized climate niche breadth) have high intrinsic sensitivity to environmental change. Using point occurrences, we systematically evaluated intrinsic sensitivity based on geographic rarity and realized climate niche breadth for 90 species of frogs and toads native to the United States using over 140 000 occurrence records. To compare sensitivity to perceived extinction risk, we compared intrinsic sensitivity to conservation status at state, federal, and international levels. We found no relationship between intrinsic sensitivity and federal or state conservation status, with some intrinsically sensitive species (i.e., those with small areas of occurrence and narrow climate specificity) not listed as at-risk at any level. Intrinsic sensitivity analysis can serve as an early warning system for species that may be currently at-risk and overlooked.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2022.109866","usgsCitation":"DuBose, T.P., Moore, C.E., Silknetter, S., Benson, A., Alexander, T., O’Malley, G., and Mims, M.C., 2023, Mismatch between conservation status and climate change sensitivity leaves some anurans in the United States unprotected: Biological Conservation, v. 277, 109866, 10 p., https://doi.org/10.1016/j.biocon.2022.109866.","productDescription":"109866, 10 p.","ipdsId":"IP-139716","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":445027,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2022.109866","text":"Publisher Index Page"},{"id":435531,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U56Z7W","text":"USGS data release","linkHelpText":"Rarity and Climate Sensitivity index and components of 90 species of frogs and toads native to the conterminous United States (ver. 2.0, October 2022)"},{"id":411051,"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":"277","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DuBose, Traci P.","contributorId":292582,"corporation":false,"usgs":false,"family":"DuBose","given":"Traci","email":"","middleInitial":"P.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":859979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Chloe E.","contributorId":292583,"corporation":false,"usgs":false,"family":"Moore","given":"Chloe","email":"","middleInitial":"E.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":859980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silknetter, Samuel","contributorId":292585,"corporation":false,"usgs":false,"family":"Silknetter","given":"Samuel","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":859981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benson, Abigail 0000-0002-4391-107X","orcid":"https://orcid.org/0000-0002-4391-107X","contributorId":202078,"corporation":false,"usgs":true,"family":"Benson","given":"Abigail","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":859982,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alexander, Tess","contributorId":292589,"corporation":false,"usgs":false,"family":"Alexander","given":"Tess","email":"","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":859983,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Malley, Grace 0000-0002-7886-8163","orcid":"https://orcid.org/0000-0002-7886-8163","contributorId":300332,"corporation":false,"usgs":false,"family":"O’Malley","given":"Grace","email":"","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":859984,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mims, Meryl C. 0000-0003-0570-988X","orcid":"https://orcid.org/0000-0003-0570-988X","contributorId":209951,"corporation":false,"usgs":false,"family":"Mims","given":"Meryl","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":859985,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256709,"text":"70256709 - 2023 - Multiple dimensions of functional diversity affect stream fish β-diversity","interactions":[],"lastModifiedDate":"2024-09-03T15:19:48.638587","indexId":"70256709","displayToPublicDate":"2022-12-26T10:12:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Multiple dimensions of functional diversity affect stream fish β-diversity","docAbstract":"Increasing water demand and multi-year drought conditions within the Mesilla/Conejos-Médanos Basin near the New Mexico-Texas- Chihuahua border have resulted in diminished surface-water supplies and increased groundwater withdrawals. To better understand recharge to the shallow aquifer, the spatial and temporal groundwater storage changes, and the variability of specific yield (Sy) in the aquifer, seasonal groundwater elevation and repeat microgravity measurements were made during the irrigation release and non-release seasons of 2016, 2017, and 2018 at a network of locations near Las Cruces, New Mexico.
The data collected during this investigation were able to capture seasonal change in groundwater elevations and storage from various sources of recharge at multiple sites in the shallow aquifer. Seasonal recharge in the study area was attributed to streamflow, the application and conveyance of irrigation water, and large or sustained precipitation events. However, increasing groundwater gradients in recent decades between piezometers close to the river and those more than a kilometer from the river suggests that recharge from river seepage has become localized at the seasonal scale. Overall, there was a net increase in storage of almost 8.4 cubic hectometers in the study reach between the start and end of the study, largely following the increased surface-water availability and above average precipitation in 2017. Specific yield, estimated by comparing the groundwater-level changes and storage changes at six sites in the study area, ranged from 0.14 (+/− 0.05) to 0.30 (+/− 0.06), which is slightly greater than previously reported estimates (0.10 to 0.25), but still within the error of the estimates. Most of the variability in the estimated storage change, that was not well-correlated with groundwater elevation change, is thought to be from soil moisture in the unsaturated zone.
This investigation demonstrates the value of adding repeat microgravity measurements to conventional groundwater monitoring to better understand the sources and extent of recharge as well as the variability of Sy in the aquifer. Continued monitoring, under a variety of available surface water and meteorological conditions, could provide a more comprehensive understanding of the water budget and reduce the specific yield estimation uncertainty. Evaluating water-levels and storage conditions prior to, and following, local recharge events may help managers identify threshold conditions for aquifer storage depletions and recoveries.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jappgeo.2022.104916","usgsCitation":"Robertson, A.J., Kennedy, J.R., Wildermuth, L.M., Bell, M., Fuchs, E.H., Rinehart, A., and Fernald, I., 2023, Determining seasonal recharge, storage changes, and specific yield using repeat microgravity and water-level measurements in the Mesilla Basin alluvial aquifer, New Mexico, 2016–2018: Journal of Applied Geophysics, v. 209, 104916, 18 p., https://doi.org/10.1016/j.jappgeo.2022.104916.","productDescription":"104916, 18 p.","ipdsId":"IP-126256","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":445042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jappgeo.2022.104916","text":"Publisher Index Page"},{"id":412211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Mesilla Basin alluvial aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.92776690707147,\n 32.36758313268733\n ],\n [\n -106.92776690707147,\n 32.11679945449248\n ],\n [\n -106.55988114871217,\n 32.11679945449248\n ],\n [\n -106.55988114871217,\n 32.36758313268733\n ],\n [\n -106.92776690707147,\n 32.36758313268733\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"209","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Andrew J. 0000-0003-2130-0347 ajrobert@usgs.gov","orcid":"https://orcid.org/0000-0003-2130-0347","contributorId":4129,"corporation":false,"usgs":true,"family":"Robertson","given":"Andrew","email":"ajrobert@usgs.gov","middleInitial":"J.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":176478,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":862099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wildermuth, Libby M. 0000-0001-5333-0968 lwildermuth@usgs.gov","orcid":"https://orcid.org/0000-0001-5333-0968","contributorId":210459,"corporation":false,"usgs":true,"family":"Wildermuth","given":"Libby","email":"lwildermuth@usgs.gov","middleInitial":"M.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862100,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bell, Meghan T. 0000-0003-4993-1642","orcid":"https://orcid.org/0000-0003-4993-1642","contributorId":209712,"corporation":false,"usgs":true,"family":"Bell","given":"Meghan T.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862101,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuchs, Erek H. 0000-0001-9170-9469","orcid":"https://orcid.org/0000-0001-9170-9469","contributorId":270989,"corporation":false,"usgs":false,"family":"Fuchs","given":"Erek","email":"","middleInitial":"H.","affiliations":[{"id":56244,"text":"Elephant Butte Irrigation District","active":true,"usgs":false}],"preferred":false,"id":862102,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rinehart, Alex 0000-0002-9642-1461","orcid":"https://orcid.org/0000-0002-9642-1461","contributorId":301120,"corporation":false,"usgs":false,"family":"Rinehart","given":"Alex","email":"","affiliations":[{"id":34868,"text":"New Mexico Institute of Mining and Technology","active":true,"usgs":false}],"preferred":false,"id":862103,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fernald, Irene 0000-0001-7584-3844","orcid":"https://orcid.org/0000-0001-7584-3844","contributorId":301121,"corporation":false,"usgs":false,"family":"Fernald","given":"Irene","email":"","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":862104,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70240131,"text":"70240131 - 2023 - Borealization of nearshore fishes on an interior Arctic shelf over multiple decades","interactions":[],"lastModifiedDate":"2023-03-15T15:06:22.506747","indexId":"70240131","displayToPublicDate":"2022-12-24T06:37:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Borealization of nearshore fishes on an interior Arctic shelf over multiple decades","docAbstract":"Borealization is a type of community reorganization where Arctic specialists are replaced by species with more boreal distributions in response to climatic warming. The process of borealization is often exemplified by the northward range expansions and subsequent proliferation of boreal species on the Pacific and Atlantic inflow Arctic shelves (i.e., Bering/Chukchi and Barents seas, respectively). But the circumpolar nearshore distribution of Arctic-boreal fishes that predates recent warming suggests borealization is possible beyond inflow shelves. To examine this question, we revisited two nearshore lagoons in the eastern Alaska Beaufort Sea (Kaktovik and Jago lagoons, Arctic National Wildlife Refuge, Alaska, USA), a High Arctic interior shelf. We compared summer fish species assemblage, catch rate, and size distribution among three periods that spanned a 30-year record (baseline conditions, 1988–1991; moderate sea ice decline, 2003–2005; rapid sea ice decline, 2017–2019). Fish assemblages differed among periods in both lagoons, consistent with borealization. Among Arctic specialists, a clear decline in fourhorn sculpin (Myoxocephalus quadricornis, Kanayuq in Iñupiaq) occurred in both lagoons with 86%–90% lower catch rates compared with the baseline period. Among the Arctic-boreal species, a dramatic 18- to 19-fold increase in saffron cod (Eleginus gracilis, Uugaq) occurred in both lagoons. Fish size (length) distributions demonstrated increases in the proportion of larger fish for most species examined, consistent with increasing survival and addition of age-classes. These field data illustrate borealization of an Arctic nearshore fish community during a period of rapid warming. Our results agree with predictions that Arctic-boreal fishes (e.g., saffron cod) are well positioned to exploit the changing Arctic ecosystem. Another Arctic-boreal species, Dolly Varden (Salvelinus malma, Iqalukpik), appear to have already responded to warming by shifting from Arctic nearshore to shelf waters. More broadly, our findings suggest that areas of borealization could be widespread in the circumpolar nearshore.
Watersheds of the Great Lakes Basin (USA/Canada) are highly modified and impacted by human activities including pesticide use. Despite labeling restrictions intended to minimize risks to nontarget organisms, concerns remain that environmental exposures to pesticides may be occurring at levels negatively impacting nontarget organisms. We used a combination of organismal-level toxicity estimates (in vivo aquatic life benchmarks) and data from high-throughput screening (HTS) assays (in vitro benchmarks) to prioritize pesticides and sites of concern in streams at 16 tributaries to the Great Lakes Basin. In vivo or in vitro benchmark values were exceeded at 15 sites, 10 of which had exceedances throughout the year. Pesticides had the greatest potential biological impact at the site with the greatest proportion of agricultural land use in its basin (the Maumee River, Toledo, OH, USA), with 72 parent compounds or transformation products being detected, 47 of which exceeded at least one benchmark value. Our risk-based screening approach identified multiple pesticide parent compounds of concern in tributaries of the Great Lakes; these compounds included: eight herbicides (metolachlor, acetochlor, 2,4-dichlorophenoxyacetic acid, diuron, atrazine, alachlor, triclopyr, and simazine), three fungicides (chlorothalonil, propiconazole, and carbendazim), and four insecticides (diazinon, fipronil, imidacloprid, and clothianidin). We present methods for reducing the volume and complexity of potential biological effects data that result from combining contaminant surveillance with HTS (in vitro) and traditional (in vivo) toxicity estimates. Environ Toxicol Chem 2022;00:1–18. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13093","usgsCitation":"Zwart, J.A., Oliver, S.K., Watkins, W., Sadler, J.M., Appling, A.P., Corson-Dosch, H.R., Jia, X., Kumar, V., and Read, J., 2023, Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions: Journal of the American Water Resources Association, v. 59, no. 2, p. 317-337, https://doi.org/10.1111/1752-1688.13093.","productDescription":"21 p.","startPage":"317","endPage":"337","ipdsId":"IP-135607","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":445061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.13093","text":"Publisher Index Page"},{"id":419302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watkins, William 0000-0002-7544-0700 wwatkins@usgs.gov","orcid":"https://orcid.org/0000-0002-7544-0700","contributorId":178146,"corporation":false,"usgs":true,"family":"Watkins","given":"William","email":"wwatkins@usgs.gov","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":879030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":879032,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corson-Dosch, Hayley R. 0000-0001-8695-1584","orcid":"https://orcid.org/0000-0001-8695-1584","contributorId":244707,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Hayley","middleInitial":"R.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879033,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":879034,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":879035,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879036,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70239217,"text":"70239217 - 2023 - Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs","interactions":[],"lastModifiedDate":"2023-02-02T17:56:41.715738","indexId":"70239217","displayToPublicDate":"2022-12-22T08:57:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs","docAbstract":"Basin analysis and tectonic reconstructions of the Cenozoic history of the Death Valley region, California, USA, are hindered by a lack of volcanic (tuff) age control in many stratigraphic successions exposed in the Grapevine and Funeral Mountains of California, USA. Although maximum depositional ages (MDAs) interpreted from detrital zircon U-Pb data may be a promising alternative to volcanic ages, arguments remain regarding the calculation of MDAs including, but not limited to, the number of “young” grains to consider (i.e., the spectrum of dates used to calculate the MDA); which grains, if any, should be ignored; which approaches yield results that are statistically rigorous; and ultimately, which approaches result in ages that are geologically reasonable. We compare commonly used metrics of detrital zircon MDA for five sandstone samples from the Cenozoic strata exposed on Bat Mountain in the southern Funeral Mountains of California—i.e., the youngest single grain (YSG), the weighted mean of the youngest grain cluster of two or more grains at 1σ uncertainty (YC1σ(2+)) and of three or more grains at 2σ uncertainty (YC2σ(3+)), the youngest graphical peak (YPP), and the maximum likelihood age (MLA). Every sandstone sample yielded abundant Cenozoic zircon U-Pb dates that formed unimodal, near-normal age distributions that were clearly distinguishable from the next-oldest grains in each sample and showed an apparent up-section decrease in peak age. Benchmarked against published K/Ar and 40Ar/39Ar ages and five new zircon U-Pb ages of ash-fall tuffs, our analysis parallels prior studies and demonstrates that many MDA metrics—YSG, YC1σ(2+), YC2σ(3+), and YPP—drift toward unreasonably young or old values. In contrast, the maximum likelihood estimation approach and the resulting MLA metric consistently produce geologically appropriate estimates of MDA without arbitrary omission of any young (or old) zircon dates. Using the MLAs of sandstones and zircon U-Pb ages of interbedded ash-fall tuffs, we develop a new age model for the Oligocene–Miocene Amargosa Valley Formation (deposited ca. 28.5–18.5 Ma) and the Miocene Bat Mountain Formation (deposited ca. 15.5–13.5 Ma) and revise correlations to Cenozoic strata across the eastern Death Valley region.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02543.1","usgsCitation":"Schwartz, T.M., Souders, A., Lundstern, J., Gilmer, A.K., and Thompson, R., 2023, Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs: Geosphere, v. 19, no. 1, p. 235-257, https://doi.org/10.1130/GES02543.1.","productDescription":"23 p.","startPage":"235","endPage":"257","ipdsId":"IP-139248","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":445066,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02543.1","text":"Publisher Index Page"},{"id":435534,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P982KK4D","text":"USGS data release","linkHelpText":"Zircon U-Pb data for ash-fall tuffs and sandstones of the Cenozoic Amargosa Valley and Bat Mountain Formations exposed on Bat Mountain, southern Funeral Mountains, California, USA"},{"id":411342,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bat Mountain, Death Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.12127468750195,\n 37.16000456147583\n ],\n [\n -117.12127468750195,\n 35.551070951522945\n ],\n [\n -115.75746797181529,\n 35.551070951522945\n ],\n [\n -115.75746797181529,\n 37.16000456147583\n ],\n [\n -117.12127468750195,\n 37.16000456147583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwartz, Theresa Maude 0000-0001-6606-4072","orcid":"https://orcid.org/0000-0001-6606-4072","contributorId":245180,"corporation":false,"usgs":true,"family":"Schwartz","given":"Theresa","email":"","middleInitial":"Maude","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Souders, Amanda 0000-0002-1367-8924","orcid":"https://orcid.org/0000-0002-1367-8924","contributorId":296423,"corporation":false,"usgs":true,"family":"Souders","given":"Amanda","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":860788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lundstern, Jens-Erik 0000-0003-0000-8013","orcid":"https://orcid.org/0000-0003-0000-8013","contributorId":264189,"corporation":false,"usgs":true,"family":"Lundstern","given":"Jens-Erik","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860791,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239141,"text":"70239141 - 2023 - Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations","interactions":[],"lastModifiedDate":"2023-04-11T16:56:36.003705","indexId":"70239141","displayToPublicDate":"2022-12-22T07:02:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations","docAbstract":"Meeting food/wood demands with increasing human population and per-capita consumption is a pressing conservation issue, and is often framed as a choice between land sparing and land sharing. Although most empirical studies comparing the efficacy of land sparing and sharing supported land sparing, land sharing may be more efficient if its performance is tested by rigorous experimental design and habitat structures providing crucial resources for various species––keystone structures––are clearly involved. We launched a manipulative experiment to retain naturally regenerated broad-leaved trees when harvesting conifer plantations in central Hokkaido, northern Japan. We surveyed birds in harvested treatments, unharvested plantation controls and natural forest references one-year before the harvest and for three consecutive post-harvest years. We developed a hierarchical community model separating abundance and space-use (territorial proportion overlapping treatment plots) subject to imperfect detection to assess population consequences of retention harvesting. Application of the model to our data showed that retaining some broad-leaved trees increased total abundance of forest birds over the harvest rotation cycle. Specifically, pre-harvest survey showed that the amount of broad-leaved trees increased forest bird abundance in a concave manner (i.e., in a form of diminishing-return). After harvesting, a small amount of retained broad-leaved trees mitigated negative harvesting impacts on abundance though retention harvesting reduced the space-use. Nevertheless, positive retention effects on the post-harvest bird density as the product of abundance and space-use exhibited a concave form. Thus, small profit reductions were shown to yield large increases in forest bird abundance. The difference in bird abundance between clear-cutting and low amounts of broad-leaved tree retention increased slightly from the first to second post-harvesting years. We conclude that retaining a small amount of broad-leaved trees may be a cost-effective on-site conservation approach for the management of conifer plantations. Retention of 20-30 broad-leaved trees per ha may be sufficient to maintain higher forest bird abundance than clear-cutting over the rotation cycle. Retention approaches can be incorporated into management systems using certification schemes and best management practices. Developing an awareness of the roles and values of naturally regenerated trees is needed to diversify plantations.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2802","usgsCitation":"Yamaura, Y., Unno, A., and Royle, A., 2023, Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations: Ecological Applications, v. 33, no. 3, e2802, https://doi.org/10.1002/eap.2802.","productDescription":"e2802","ipdsId":"IP-136595","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445068,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":411174,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Yamaura, Yuichi","contributorId":300495,"corporation":false,"usgs":false,"family":"Yamaura","given":"Yuichi","affiliations":[{"id":65171,"text":"Shikoku Research Center, Forestry and Forest Products Research Institute","active":true,"usgs":false}],"preferred":false,"id":860324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Unno, Akira","contributorId":300496,"corporation":false,"usgs":false,"family":"Unno","given":"Akira","email":"","affiliations":[{"id":65172,"text":"Fores try Research Institute, Hokkaido Research Organization, Koshunai, Bibai,","active":true,"usgs":false}],"preferred":false,"id":860325,"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":146229,"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":true,"id":860326,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242008,"text":"70242008 - 2023 - A genetic warning system for a hierarchically structured wildlife monitoring framework","interactions":[],"lastModifiedDate":"2023-04-04T12:00:53.306947","indexId":"70242008","displayToPublicDate":"2022-12-22T06:53:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"A genetic warning system for a hierarchically structured wildlife monitoring framework","docAbstract":"Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species' conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (Centrocercus urophasianus) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., neighborhood-scale) with low genetic diversity, further facilitating identification of management targets. We developed a genetic warning system utilizing previously developed hierarchical population units to identify management-relevant areas with low genetic diversity within the greater sage-grouse range. Within this warning system we characterized conservation concern thresholds based on values of genetic diversity and developed a statistical model for microsatellite data to robustly estimate these values for hierarchically nested populations. We found that 41 of 224 neighborhood-scale clusters had low genetic diversity, 23 of which were coupled with documented local population trend decline. We also found evidence of cross-scale low genetic diversity in the small and isolated Washington population, unlikely to be reversed through typical local management actions alone. The combination of low genetic diversity and a declining population suggests relatively high conservation concern. Our findings could further facilitate conservation action prioritization in combination with population trend assessments and (or) local information, and act as a base-line of genetic diversity for future comparison. Importantly, the approach we used is broadly applicable across taxa.
A Bayesian hierarchical modeling approach is introduced to pool data properly from multiple flow-through wetlands to estimate wetland-specific long-term phosphorus retention capacity. By pooling data from multiple wetlands, we overcome the difficulties in estimating the effectiveness of using constructed and natural wetlands for nutrient reduction. The Bayesian hierarchical modeling approach reduces estimation uncertainty by shrinking wetland-specific estimates towards the overall average of the same quantity from multiple wetlands, facilitating information sharing across sites, thereby reducing the demand on sample sizes from individual wetlands and avoiding several common pitfalls of using large data (i.e., from multiple systems) induced by Simpson's paradox. In this paper, we develop a sequential updating framework to alleviate the computational burden of compiling and modeling data from multiple wetlands. We then demonstrate the sequential updating process to estimate retention capacity of a suite of wetlands in Ohio, USA. A total of four wetlands, representing both natural and constructed wetlands, were used. The estimated total phosphorus retention capacities range less than 0.01 to well over 1 ton per year per system. As wetland restoration initiatives expand around the Laurentian Great Lakes and nationally, this model serves as an important initial step in developing tools to meet nutrient reduction goals and standards. Extending this work, we have developed a publicly accessible on-line open computation platform that can help natural resource specialists better plan for wetland efficacy in the future.
Accurate estimates of earthquake ground shaking rely on uncertain ground-motion models derived from limited instrumental recordings of historical earthquakes. A critical issue is that there is currently no method to empirically validate the resultant ground-motion estimates of these models at the timescale of rare, large earthquakes; this lack of validation causes great uncertainty in ground-motion estimates. Here, we address this issue and validate ground-motion estimates for southern California utilizing the unexceeded ground motions recorded by 20 precariously balanced rocks. We used cosmogenic 10Be exposure dating to model the age of the precariously balanced rocks, which ranged from ca. 1 ka to ca. 50 ka, and calculated their probability of toppling at different ground-motion levels. With this rock data, we then validated the earthquake ground motions estimated by the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3) seismic-source characterization and the Next Generation Attenuation (NGA)-West2 ground-motion models. We found that no ground-motion model estimated levels of earthquake ground shaking consistent with the observed continued existence of all 20 precariously balanced rocks. The ground-motion model I14 estimated ground-motion levels that were inconsistent with the most rocks; therefore, I14 was invalidated and removed. At a 2475 year mean return period, the removal of this invalid ground-motion model resulted in a 2–7% reduction in the mean and a 10–36% reduction in the 5th–95th fractile uncertainty of the ground-motion estimates. Our findings demonstrate the value of empirical data from precariously balanced rocks as a validation tool for removing invalid ground-motion models and, in turn, reducing the uncertainty in earthquake ground-motion estimates.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36484.1","usgsCitation":"Rood, A.H., Rood, D., Balco, G., Stafford, P.J., Grant Ludwig, L., Kendrick, K.J., and Wilcken, K., 2023, Validation of earthquake ground-motion models in southern California, USA, using precariously balanced rocks: GSA Bulletin, v. 135, no. 9-10, p. 2179-2199, https://doi.org/10.1130/B36484.1.","productDescription":"21 p.","startPage":"2179","endPage":"2199","ipdsId":"IP-143199","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118,\n 34.6\n ],\n [\n -118,\n 33.6\n ],\n [\n -116,\n 33.6\n ],\n [\n -116,\n 34.6\n ],\n [\n -118,\n 34.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"135","issue":"9-10","noUsgsAuthors":false,"publicationDate":"2022-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Rood, Anna H.","contributorId":245478,"corporation":false,"usgs":false,"family":"Rood","given":"Anna","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":928942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rood, Dylan","contributorId":167067,"corporation":false,"usgs":false,"family":"Rood","given":"Dylan","email":"","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":928943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balco, Greg","contributorId":347027,"corporation":false,"usgs":false,"family":"Balco","given":"Greg","email":"","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":928944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stafford, Peter J.","contributorId":261918,"corporation":false,"usgs":false,"family":"Stafford","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":928945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grant Ludwig, Lisa","contributorId":245422,"corporation":false,"usgs":false,"family":"Grant Ludwig","given":"Lisa","email":"","affiliations":[{"id":34134,"text":"UC Irvine","active":true,"usgs":false}],"preferred":false,"id":928946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kendrick, Katherine J. 0000-0002-9839-6861","orcid":"https://orcid.org/0000-0002-9839-6861","contributorId":207907,"corporation":false,"usgs":true,"family":"Kendrick","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928947,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilcken, Klaus","contributorId":351569,"corporation":false,"usgs":false,"family":"Wilcken","given":"Klaus","affiliations":[{"id":84009,"text":"Australian Nuclear Science and Technology Organisation","active":true,"usgs":false}],"preferred":false,"id":928948,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239050,"text":"70239050 - 2023 - Cryptic declines of small, cold-water specialists highlight potential vulnerabilities of headwater streams as climate refugia","interactions":[],"lastModifiedDate":"2022-12-22T12:48:14.551596","indexId":"70239050","displayToPublicDate":"2022-12-20T06:45:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic declines of small, cold-water specialists highlight potential vulnerabilities of headwater streams as climate refugia","docAbstract":"Increasing temperatures and climate-driven disturbances like wildfire are a growing threat to many species, including cold-water specialists. Montane areas and cold streams are often considered climate refugia that buffer communities against change. However, climate refugia are often species-specific, and despite growing awareness that life histories and habitat requirements shape responses to change, small or non-game species are often under-represented in monitoring and planning programs. A recent study in Montana, USA, revealed much larger warming-related declines in occupancy for small, non-game slimy sculpin (Cottus cognatus) between 1993 and 1995 and 2011–2013 than for two socially valued salmonid fishes that shape regional conservation efforts. To broaden insight into climate change vulnerabilities of headwater stream communities, we analyzed data for Rocky Mountain tailed frogs (Ascaphus montanus) that were collected during those same electrofishing surveys for fishes from 241 stream reaches. Tailed frogs occupy small, cold streams and have several life-history traits that make them sensitive to environmental change. We used a Bayesian framework to estimate occupancy, colonization, and extinction dynamics relative to forest canopy, estimated stream temperature, and wildfire effects. Tailed frog occupancy decreased by 19 % from 1993 to 1995 to 2011–2013. Changes in occupancy were linked with increased extinction and reduced colonization where there were fire-driven reductions in canopy cover, and reduced colonization of stream reaches that warmed on average 0.8 °C during the study. Our results highlight extensive extirpations for oft-overlooked species and emphasize the importance of including species with diverse habitat requirements and life histories in conservation planning.
Bottled water (BW) consumption in the United States and globally has increased amidst heightened concern about environmental contaminant exposures and health risks in drinking water supplies, despite a paucity of directly comparable, environmentally-relevant contaminant exposure data for BW. This study provides insight into exposures and cumulative risks to human health from inorganic/organic/microbial contaminants in BW.
BW from 30 total domestic US (23) and imported (7) sources, including purified tapwater (7) and spring water (23), were analyzed for 3 field parameters, 53 inorganics, 465 organics, 14 microbial metrics, and in vitro estrogen receptor (ER) bioactivity. Health-benchmark-weighted cumulative hazard indices and ratios of organic-contaminant in vitro exposure-activity cutoffs were assessed for detected regulated and unregulated inorganic and organic contaminants.
48 inorganics and 45 organics were detected in sampled BW. No enforceable chemical quality standards were exceeded, but several inorganic and organic contaminants with maximum contaminant level goal(s) (MCLG) of zero (no known safe level of exposure to vulnerable sub-populations) were detected. Among these, arsenic, lead, and uranium were detected in 67 %, 17 %, and 57 % of BW, respectively, almost exclusively in spring-sourced samples not treated by advanced filtration. Organic MCLG exceedances included frequent detections of disinfection byproducts (DBP) in tapwater-sourced BW and sporadic detections of DBP and volatile organic chemicals in BW sourced from tapwater and springs. Precautionary health-based screening levels were exceeded frequently and attributed primarily to DBP in tapwater-sourced BW and co-occurring inorganic and organic contaminants in spring-sourced BW.
The results indicate that simultaneous exposures to multiple drinking-water contaminants of potential human-health concern are common in BW. Improved understandings of human exposures based on more environmentally realistic and directly comparable point-of-use exposure characterizations, like this BW study, are essential to public health because drinking water is a biological necessity and, consequently, a high-vulnerability vector for human contaminant exposures.
Sinuous ridges are an important yet understudied component of Mars' hydrologic history. We have produced a map of sinuous ridges, valleys and channels, and tectonic ridges across southeastern Terra Sabaea and into northern Hellas Planitia (10°-45° S, 35°-80° E) using a CTX mosaic. Although we mapped different types of ridges and negative relief features, the focus of this paper are the sinuous ridges. We present here a new dataset of sinuous ridges that includes basic morphometry (e.g., length, width, sinuosity), morphology, and the types of terrains they are located on. We chose our region of interest because it includes surface ages spanning Mars' geologic history, with emphasis on Noachian and Hesperian terrains. The shift from either a warm and wet or a cold and icy environment to our modern cold and dry climate occurred towards the end of the Noachian and into the Hesperian, a critical temporal window to characterize fluvial landforms.
Our CTX-based mapping significantly improved the documentation of fluvial landforms within the study region, with over an order of magnitude increase in the number of valley networks and channels, and nearly 1700 sinuous ridges. Sinuous ridges are found in concentrated settings, with the majority (∼80%) located within impact craters and relatively few (∼20%) on the intercrater plains. Fluvial features are prevalent on Early and Middle Noachian-aged terrain but are relatively rare in the Late Noachian, signifying a shift in fluvial activity that likely led to a decrease in channel incision and subsequent inversion of relief. A subset of sinuous ridges—radial ridges in high-elevation, degraded craters— are possible records of ancient proglacial lakes. The youngest sinuous ridges are associated with intracrater alluvial fans in a narrow zone (∼12°S to 30°S and ∼ 62°E to 77°E). These formed in the Late Hesperian into the Amazonian, reflecting a later epoch of punctuated fluvial events driven by pre-existing topography and solar insolation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2022.115399","usgsCitation":"Gullikson, A.L., Anderson, R.B., and Williams, R.M., 2023, Spatial and temporal distribution of sinuous ridges in southeastern Terra Sabaea and the northern region of Hellas Planitia, Mars: Icarus, v. 394, 115399, 14 p., https://doi.org/10.1016/j.icarus.2022.115399.","productDescription":"115399, 14 p.","ipdsId":"IP-129949","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":445100,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2022.115399","text":"Publisher Index Page"},{"id":412941,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Hellas Plantia, Mars, Terra Sabaea","volume":"394","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gullikson, Amber L. 0000-0002-1505-3151","orcid":"https://orcid.org/0000-0002-1505-3151","contributorId":208679,"corporation":false,"usgs":true,"family":"Gullikson","given":"Amber","email":"","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":864024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Ryan B. 0000-0003-4465-2871 rbanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-4465-2871","contributorId":170054,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan","email":"rbanderson@usgs.gov","middleInitial":"B.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":864025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Rebecca M.E.","contributorId":302332,"corporation":false,"usgs":false,"family":"Williams","given":"Rebecca","email":"","middleInitial":"M.E.","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":864026,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238945,"text":"70238945 - 2023 - Effects of structure and volcanic stratigraphy on groundwater and surface water flow: Hat Creek basin, California, USA","interactions":[],"lastModifiedDate":"2023-03-31T15:02:55.092427","indexId":"70238945","displayToPublicDate":"2022-12-16T06:57:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Effects of structure and volcanic stratigraphy on groundwater and surface water flow: Hat Creek basin, California, USA","docAbstract":"Hydrogeologic systems in the southern Cascade Range in California (USA) develop in volcanic rocks where morphology, stratigraphy, extensional structures, and attendant basin geometry play a central role in groundwater flow paths, groundwater/surface-water interactions, and spring discharge locations. High-volume springs (greater than 3 m3/s) flow from basin-filling (<800 ka) volcanic rocks in the Hat Creek and Fall River tributaries and contribute approximately half of the average annual flow of the Pit River, the largest tributary to Shasta Lake. A hydrogeologic conceptual framework is constructed for the Hat Creek basin combining new geologic mapping, water-well lithologic logs, a database of active faults, LiDAR mapping of faults and volcanic landforms, streamflow measurements and airborne thermal infrared remote sensing of stream temperature. These data are used to integrate the geologic structure and the volcanic and volcaniclastic stratigraphy to create a three-dimensional interpretation of the hydrogeology in the basin. Two large streamflow gains from focused groundwater discharge near Big Spring and north of Sugarloaf Peak result from geologic barriers that restrict lateral groundwater flow and force water into Hat Creek. The inferred groundwater-flow barriers divide the aquifer system into at least three leaky compartments. The two downstream compartments lose streamflow in the upstream reaches (immediately downstream of the groundwater-flow barriers) and gain in downstream reaches with the greatest inflows immediately upstream of the barriers.
Although there have been few attempts to systematically analyze information on the use of deterrents on polar bears (Ursus maritimus), understanding their effectiveness in mitigating human-polar bear conflicts is critical to ensuring both human safety and polar bear conservation. To fill this knowledge gap, we analyzed 19 incidents involving the use of bear spray on free-ranging polar bears from 1986 to 2019 in Canada, Russia, and the United States to evaluate the effectiveness of bear spray as a polar bear deterrent. We found that bear spray was an effective deterrent in close-range encounters with polar bears, stopping undesirable behavior in 18 of 19 incidents. Bear spray effectively deterred both curious and aggressive polar bears, including polar bears attempting to attack people. The mean distance between user and bear at the time of spraying was 2 m (min–max = 0.2–10.0 m, mode = 1 m), though bears were usually first seen at greater distances. Bear spray was successfully deployed against polar bears in all 4 seasons. Wind affected spray performance in 1 of 19 of incidents. In 8 of 14 bear spray incidents, other deterrents were used without success before bear spray was used effectively to deter polar bears. No humans or polar bears were killed or injured in any of the incidents in which bear spray was used. We also analyzed 54 polar bear attacks and attempted attacks on humans where bear spray was not carried. The data suggest that in 93% of those incidents, the use of bear spray might have saved the lives of both the people and bears involved if it had been available and used. Our analysis improves our understanding of the effectiveness of bear spray for polar bear conflict mitigation.
The movement of plant species across the globe exposes native communities to new species introductions. While introductions are pervasive, two aspects of variability underlie patterns and processes of biological invasions at macroecological scales. First, only a portion of introduced species become invaders capable of substantially impacting ecosystems. Second, species that do become invasive at one location may not be invasive in others; impacts depend on invader abundance and recipient species and conditions. Accounting for these phenomena is essential to accurately understand the patterns of plant invasion and explain the idiosyncratic results reflected in the literature on biological invasions. The lack of community-level richness and the abundance of data spanning broad scales and environmental conditions have until now hindered our understanding of invasions at a macroecological scale. To address this limitation, we leveraged quantitative surveys of plant communities in the USA and integrated and harmonized nine datasets into the Standardized Plant Community with Introduced Status (SPCIS) database. The database contains 14,056 unique taxa identified within 83,391 sampling units, of which 52.6% have at least one introduced species. The SPCIS database includes comparable information on plant species occurrence, abundance, and native status across the 50 U.S. States and Puerto Rico. SPCIS can be used to answer macro-scale questions about native plant communities and interactions with invasive plants. There are no copyright restrictions on the data, and we ask the users of this dataset to cite this paper, the respective paper(s) corresponding to the dataset sampling design (all references are provided in Data S1: Metadata S1: Class II-B-2), and the references described in Data S1: Metadata S1: Class III-B-4 as applicable to the dataset being utilized.
The lone star tick, Amblyomma americanum L., is a three-host hard tick notorious for aggressive feeding behavior. In the early to mid-20th century, this species’ range was mostly limited to the southern USA. Since the 1950s, A. americanum has been detected in many new localities in the western, northcentral, and northeastern regions of the country. To examine the influence of climate on this apparent expansion, we used historical (1748–1950) lone star locations from the literature and museum records to model areas suitable for this species based on past environmental conditions in the late 1800s – early 1900s. We then projected this model forward using present (2011–2020) climatic conditions and compared the two for evidence of climate-associated distributional shifts. A maximum entropy distribution or Maxent model was generated by using a priori selected climatic variables including temperature, precipitation, and vapor pressure deficit. Temperature and vapor pressure deficit were selected as the most important factors in creating a sensitive and specific model (success rate = 82.6 ± 6.1%) that had a good fit to the existing data and was significantly better than a random model [partial ROC (receiver operating characteristic) to AUC (area under the ROC curve) ratio = 1.97 ± 0.07, P < 0.001]. The present projected model was tested with an independent dataset of curated museum records (1952–2020) and found to be 95.6% accurate. Comparison of past and present models revealed > 98% A. americanum niche overlap. The model suggests that some areas along the western fringe are becoming less suitable for A. americanum, whereas areas in some Great Lakes and coastal northeastern regions are becoming more suitable, results that are compatible with possible effects of climate change. However, these changes are minor, and overall climate in North America does not appear to have changed in ways significant to A. americanum’s distribution. These findings are consistent with an alternative hypothesis that recent changes in A. americanum’s distribution are a result of this species re-occupying its historical range, driven predominantly by factors other than climate, such as shifts in land use and population densities of major hosts.
","language":"English","publisher":"Springer","doi":"10.1007/s10493-022-00765-0","usgsCitation":"Rochlin, I., Egizi, A., and Ginsberg, H., 2023, Modeling of historical and current distributions of lone star tick, Amblyomma americanum (Acari: Ixodidae), is consistent with ancestral range recovery: Experimental and Applied Acarology, v. 89, p. 85-103, https://doi.org/10.1007/s10493-022-00765-0.","productDescription":"19 p.","startPage":"85","endPage":"103","ipdsId":"IP-134334","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":498447,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/132","text":"External Repository"},{"id":410279,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","noUsgsAuthors":false,"publicationDate":"2022-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Rochlin, Ilia","contributorId":299797,"corporation":false,"usgs":false,"family":"Rochlin","given":"Ilia","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":858696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Egizi, Andrea","contributorId":299798,"corporation":false,"usgs":false,"family":"Egizi","given":"Andrea","email":"","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":858697,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ginsberg, Howard 0000-0002-4933-2466","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":15473,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":858698,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238795,"text":"70238795 - 2023 - Extent, patterns, and drivers of hypoxia in the world's streams and rivers","interactions":[],"lastModifiedDate":"2023-05-25T15:32:33.866612","indexId":"70238795","displayToPublicDate":"2022-12-08T07:12:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12978,"text":"Limnology and Oceanography - Letters","active":true,"publicationSubtype":{"id":10}},"title":"Extent, patterns, and drivers of hypoxia in the world's streams and rivers","docAbstract":"Hypoxia in coastal waters and lakes is widely recognized as a detrimental environmental issue, yet we lack a comparable understanding of hypoxia in rivers. We investigated controls on hypoxia using 118 million paired observations of dissolved oxygen (DO) concentration and water temperature in over 125,000 locations in rivers from 93 countries. We found hypoxia (DO < 2 mg L−1) in 12.6% of all river sites across 53 countries, but no consistent trend in prevalence since 1950. High-frequency data reveal a 3-h median duration of hypoxic events which are most likely to initiate at night. River attributes were better predictors of riverine hypoxia occurrence than watershed land cover, topography, and climate characteristics. Hypoxia was more likely to occur in warmer, smaller, and lower-gradient rivers, particularly those draining urban or wetland land cover. Our findings suggest that riverine hypoxia and the resulting impacts on ecosystems may be more pervasive than previously assumed.
An essential goal in conservation biology is delineating population units that maximize the probability of species persisting into the future and adapting to future environmental change. However, future-facing conservation concerns are often addressed using retrospective patterns that could be irrelevant. We recommend a novel landscape genomics framework for delineating future “Geminate Evolutionary Units” (GEUs) in a focal species: (1) identify loci under environmental selection, (2) model and map adaptive conservation units that may spawn future lineages, (3) forecast relative selection pressures on each future lineage, and (4) estimate their fitness and likelihood of persistence using geo-genomic simulations. Using this process, we delineated conservation units for the Yosemite toad (Anaxyrus canorus), a U.S. federally threatened species that is highly vulnerable to climate change. We used a genome-wide dataset, redundancy analysis, and Bayesian association methods to identify 24 candidate loci responding to climatic selection (R2 ranging from 0.09 to 0.52), after controlling for demographic structure. Candidate loci included genes such as MAP3K5, involved in cellular response to environmental change. We then forecasted future genomic response to climate change using the multivariate machine learning algorithm Gradient Forests. Based on all available evidence, we found three GEUs in Yosemite National Park, reflecting contrasting adaptive optima: YF-North (high winter snowpack with moderate summer rainfall), YF-East (low to moderate snowpack with high summer rainfall), and YF-Low-Elevation (low snowpack and rainfall). Simulations under the RCP 8.5 climate change scenario suggest that the species will decline by 29% over 90 years, but the highly diverse YF-East lineage will be least impacted for two reasons: (1) geographically it will be sheltered from the largest climatic selection pressures, and (2) its standing genetic diversity will promote a faster adaptive response. Our approach provides a comprehensive strategy for protecting imperiled non-model species with genomic data alone and has wide applicability to other declining species.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.13511","usgsCitation":"Maier, P., Vandergast, A.G., and Bohonak, A.J., 2023, Using landscape genomics to delineate future adaptive potential for climate change in the Yosemite toad (Anaxyrus canorus): Evolutionary Applications, v. 16, p. 74-97, https://doi.org/10.1111/eva.13511.","productDescription":"24 p.","startPage":"74","endPage":"97","ipdsId":"IP-147179","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.13511","text":"Publisher Index Page"},{"id":414614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Kings Canyon National Park, Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.85061210634456,\n 36.52123522076397\n ],\n [\n -118.13910750098108,\n 36.616475004823215\n ],\n [\n -118.44742616330538,\n 37.41654854711554\n ],\n [\n -119.44353261081429,\n 38.35710042889701\n ],\n [\n -120.2024708565354,\n 38.166222753255624\n ],\n [\n -120.45742667345743,\n 37.99820964775573\n ],\n [\n -119.61547955711029,\n 37.360016749403826\n ],\n [\n -118.85061210634456,\n 36.52123522076397\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2022-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Maier, Paul A. 0000-0003-0851-8827","orcid":"https://orcid.org/0000-0003-0851-8827","contributorId":221033,"corporation":false,"usgs":false,"family":"Maier","given":"Paul A.","affiliations":[{"id":40313,"text":"Department of Biology, San Diego State","active":true,"usgs":false}],"preferred":false,"id":867267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bohonak, Andrew J.","contributorId":195156,"corporation":false,"usgs":false,"family":"Bohonak","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":867269,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238766,"text":"70238766 - 2023 - Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis","interactions":[],"lastModifiedDate":"2022-12-08T12:51:26.352949","indexId":"70238766","displayToPublicDate":"2022-12-07T06:46:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis","docAbstract":"Precisely measuring the Earth’s changing surface on decadal to centennial time scales is critical for many science and engineering applications, yet long-term records of quantitative landscape change are often temporally and geographically sparse. Archives of scanned historical aerial photographs provide an opportunity to augment these records with accurate elevation measurements that capture the historical state of the Earth surface. Structure from Motion (SfM) photogrammetry workflows produce high-quality digital elevation models (DEMs) and orthoimage mosaics from these historical images, but time-intensive tasks like manual image preprocessing (e.g., fiducial marker identification) and ground control point (GCP) selection impede processing at scale. We developed an automated method to process historical images and generate self-consistent time series of high-resolution (0.5–2 m) DEMs and orthomosaics, without manual GCP selection. The method relies on SfM to correct camera interior and exterior orientation and a robust multi-stage co-registration approach using modern reference terrain datasets for geolocation refinement. We demonstrate the method using scanned images from the North American Glacier Aerial Photography (NAGAP) archive collected between 1967 and 1997. We present results for two sites with variable photo acquisition geometry and overlap — Mount Baker and South Cascade Glacier in Washington State, USA. The automated method corrects initial camera position errors of several kilometers and produces accurately georeferenced, high-resolution DEMs and orthoimages, regardless of camera configuration, acquisition geometry, terrain characteristics, and reference DEM properties. The average RMS reprojection error following bundle adjustment optimization was 0.67 px (0.15 m) for the 261 images contributing to 10 final DEM mosaics between 1970 and 1992 at Mount Baker, and 0.65 px (0.13 m) for the 243 images contributing to 18 individual DEMs between 1967 and 1997 at South Cascade Glacier. The relative accuracy of elevation values in the historical time series stacks was 0.68 m at Mount Baker and 0.37 m at South Cascade Glacier. Our products have reduced systematic error and improved accuracy compared to DEM products generated using SfM with manual GCP selection. Final elevation change measurement precision was