The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911–2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 °C per decade before 1981 to 0.334 °C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s−1 before 1994 to 3.74 m s−1 thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3 days per century), decreasing ice cover duration (21.3 days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3 days per century), later fall turnover (14.6 days per century), longer stratification duration (26.8 days per century), and decreasing summer hypolimnetic temperatures (−1.4 °C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911–1980, 1981–1993, and 1994–2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Niño winter of 1997–1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994–2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.
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Resources","active":true,"usgs":false}],"preferred":false,"id":639533,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Chin H","contributorId":172076,"corporation":false,"usgs":false,"family":"Wu","given":"Chin","email":"","middleInitial":"H","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":639534,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magee, Madeline","contributorId":172077,"corporation":false,"usgs":false,"family":"Magee","given":"Madeline","affiliations":[{"id":5083,"text":"University of British Columbia, Department of Zoology, Biodiversity Research Centre and Beaty Biodiversity Museum","active":true,"usgs":false}],"preferred":false,"id":639535,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamilton, David P.","contributorId":166840,"corporation":false,"usgs":false,"family":"Hamilton","given":"David P.","affiliations":[{"id":24543,"text":"Environmental Research Institute, University of Waikato, Private Bag 3015, Hamilton 3240, New Zealand.","active":true,"usgs":false}],"preferred":false,"id":639536,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178255,"text":"70178255 - 2016 - Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data","interactions":[],"lastModifiedDate":"2016-11-09T15:29:43","indexId":"70178255","displayToPublicDate":"2016-05-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2035,"text":"International Journal of Digital Earth","active":true,"publicationSubtype":{"id":10}},"title":"Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data","docAbstract":"The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia, using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season (June–October), followed by a fallow during the rabi season (November–February). These cropland areas are not suitable for growing rabi-season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea (Cicer arietinum L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary (kharif) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left fallow during the second (rabi) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during rabi season. Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.
","language":"English","doi":"10.1080/17538947.2016.1168489","usgsCitation":"Gumma, M., Thenkabail, P.S., Teluguntla, P.G., Rao, M.N., Mohammed, I., and Whitbread, A.M., 2016, Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data: International Journal of Digital Earth, v. 9, no. 10, p. 981-1003, https://doi.org/10.1080/17538947.2016.1168489.","productDescription":"23 p.","startPage":"981","endPage":"1003","ipdsId":"IP-070335","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2016.1168489","text":"Publisher Index Page"},{"id":330906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bangladesh, Bhutan, India, Nepal, Pakistan, Sri Lanka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 83.97949218750001,\n 15.284185114076433\n ],\n [\n 82.3095703125,\n 11.996338401936226\n ],\n [\n 83.32031250000001,\n 7.754537346539373\n ],\n [\n 81.78222656250001,\n 5.266007882805485\n ],\n [\n 79.365234375,\n 5.747174076651375\n ],\n [\n 76.81640625,\n 7.406047717076271\n ],\n [\n 72.59765625,\n 12.382928338487396\n ],\n [\n 66.4013671875,\n 25.64152637306577\n ],\n [\n 80.4638671875,\n 29.11377539511439\n ],\n [\n 95.61523437500003,\n 30.34192736497245\n ],\n [\n 91.62597656250001,\n 20.67390526467282\n ],\n [\n 83.97949218750001,\n 15.284185114076433\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"582443f5e4b09065cdf30528","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":653404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rao, Mahesh N.","contributorId":127588,"corporation":false,"usgs":false,"family":"Rao","given":"Mahesh","email":"","middleInitial":"N.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":653407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohammed, Irshad A.","contributorId":176755,"corporation":false,"usgs":false,"family":"Mohammed","given":"Irshad A.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitbread, Anthony M.","contributorId":176756,"corporation":false,"usgs":false,"family":"Whitbread","given":"Anthony","email":"","middleInitial":"M.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653409,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174051,"text":"70174051 - 2016 - Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca","interactions":[],"lastModifiedDate":"2018-08-07T12:26:29","indexId":"70174051","displayToPublicDate":"2016-05-03T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca","docAbstract":"The authors investigated the chronic toxicity of aqueous Pb to the amphipod Hyalella azteca (Hyalella) in 42-d tests using 2 different diets: 1) the yeastþcereal leafþtrout pellet (YCT) diet, fed at the uniform low ration used in standard methods for sediment toxicity tests; and 2) a new diet of diatomsþTetraMin flakes (DT), fed at increasing rations over time, that has been optimized for use in Hyalella water-only tests. Test endpoints included survival, weight, biomass, fecundity, and total young. Lethal effects of Pb were similar for the DT and YCT tests (20% lethal concentration [LC20]¼13 mg/L and 15mg/L, respectively, as filterable Pb). In contrast, weight and fecundity endpoints were not significantly affected in the DT test at Pb concentrations up to 63 mg/L, but these endpoints were significantly reduced by Pb in the YCT test—and in a 2005 test in the same laboratory with a diet of conditioned Rabbit Chow (RC-2005). The fecundity and total young endpoints from the YCT and RC-2005 tests were considered unreliable because fecundity in controls did not meet test acceptability criteria, but both of these tests still produced lower Pb effect concentrations (for weight or biomass) than the test with the DT diet. The lowest biotic ligand model–normalized effect concentrations for the 3 tests ranged from 3.7mg/L (weight 20% effect concentration [EC20] for the RC-2005 test) to 8.2 mg/L (total young EC20 for the DT test), values that would rank Hyalella as the second or third most sensitive of 13 genera in a species sensitivity distribution for chronic Pb toxicity. These results demonstrate that toxicity tests with Hyalella fed optimal diets can meet more stringent test acceptability criteria for control performance, but suggest that results of these tests may underestimate sublethal toxic effects of Pb to Hyalella under suboptimal feeding regimes.
","language":"English","publisher":"Setac Press","doi":"10.1002/etc.3341","usgsCitation":"Besser, J.M., Ivey, C.D., Brumbaugh, W.G., and Ingersoll, C.G., 2016, Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca: Environmental Toxicology and Chemistry, v. 35, p. 1825-1834, https://doi.org/10.1002/etc.3341.","productDescription":"10 p.","startPage":"1825","endPage":"1834","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063482","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":324365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","edition":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"576e59aee4b07657d1a43c55","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640708,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170845,"text":"70170845 - 2016 - Molecular evidence of undescribed Ceratonova sp. (Cnidaria: Myxosporea) in the freshwater polychaete, Manayunkia speciosa, from western Lake Erie","interactions":[],"lastModifiedDate":"2016-05-12T10:52:39","indexId":"70170845","displayToPublicDate":"2016-05-03T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2361,"text":"Journal of Invertebrate Pathology","active":true,"publicationSubtype":{"id":10}},"title":"Molecular evidence of undescribed Ceratonova sp. (Cnidaria: Myxosporea) in the freshwater polychaete, Manayunkia speciosa, from western Lake Erie","docAbstract":"We used PCR to screen pooled individuals of Manayunkia speciosa from western Lake Erie, Michigan, USA for myxosporean parasites. Amplicons from positive PCRs were sequenced and showed a Ceratonova species in an estimated 1.1% (95% CI = 0.46%, 1.8%) of M. speciosa individuals. We sequenced 18S, ITS1, 5.8S, ITS2 and most of the 28S rDNA regions of this Ceratonova sp., and part of the protein-coding EF2 gene. Phylogenetic analyses of ribosomal and EF2 sequences showed the Lake Erie Ceratonova sp. is most similar to, but genetically distinct from, Ceratonova shasta. Marked interspecific polymorphism in all genes examined, including the ITS barcoding genes, along with geographic location suggests this is an undescribed Ceratonova species. COI sequences showed M. speciosa individuals in Michigan and California are the same species. These findings represent a third parasite in the genus Ceratonovapotentially hosted by M. speciosa.
","language":"English","publisher":"Society for Invertebrate Pathology","publisherLocation":"New York, NY","doi":"10.1016/j.jip.2016.05.001","usgsCitation":"Malakauskas, D.M., Snipes, R.B., Thompson, A.M., and Schloesser, D.W., 2016, Molecular evidence of undescribed Ceratonova sp. (Cnidaria: Myxosporea) in the freshwater polychaete, Manayunkia speciosa, from western Lake Erie: Journal of Invertebrate Pathology, v. 137, p. 49-53, https://doi.org/10.1016/j.jip.2016.05.001.","productDescription":"5 p.","startPage":"49","endPage":"53","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075219","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":320962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.1500244140625,\n 42.204107493733176\n ],\n [\n -83.12530517578125,\n 42.12878436246021\n ],\n [\n -83.15277099609375,\n 42.04113400940809\n ],\n [\n -83.10882568359375,\n 41.95540515378059\n ],\n [\n -83.41644287109374,\n 41.734429390721\n ],\n [\n -83.49609375,\n 41.734429390721\n ],\n [\n -83.47686767578125,\n 41.79998325207397\n ],\n [\n -83.44390869140625,\n 41.85115059465234\n ],\n [\n -83.4136962890625,\n 41.89409955811395\n ],\n [\n -83.37799072265624,\n 41.93088998442502\n ],\n [\n -83.35052490234375,\n 41.96357478222518\n ],\n [\n -83.32305908203124,\n 41.99011884096809\n ],\n [\n -83.26812744140625,\n 42.01665183556825\n ],\n [\n -83.22143554687499,\n 42.07987816698549\n ],\n [\n -83.21319580078125,\n 42.14304156290939\n ],\n [\n -83.18572998046875,\n 42.18375873465217\n ],\n [\n -83.1500244140625,\n 42.204107493733176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"137","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572b1d37e4b0b13d391b44c6","contributors":{"authors":[{"text":"Malakauskas, David M.","contributorId":43247,"corporation":false,"usgs":true,"family":"Malakauskas","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":628769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snipes, Robert Benjamin","contributorId":169164,"corporation":false,"usgs":false,"family":"Snipes","given":"Robert","email":"","middleInitial":"Benjamin","affiliations":[{"id":18157,"text":"Francis Marion University","active":true,"usgs":false}],"preferred":false,"id":628770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Ann M.","contributorId":169165,"corporation":false,"usgs":false,"family":"Thompson","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":18157,"text":"Francis Marion University","active":true,"usgs":false}],"preferred":false,"id":628771,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schloesser, Donald W. dschloesser@usgs.gov","contributorId":3579,"corporation":false,"usgs":true,"family":"Schloesser","given":"Donald","email":"dschloesser@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":628772,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209271,"text":"70209271 - 2016 - Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations","interactions":[],"lastModifiedDate":"2020-03-26T11:47:16","indexId":"70209271","displayToPublicDate":"2016-05-03T11:31:24","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations","title":"Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations","docAbstract":"Reliably estimating wildlife abundance is fundamental to effective management. Aerial surveys are one of the only spatially robust tools for estimating large mammal populations, but statistical sampling methods are required to address detection biases that affect accuracy and precision of the estimates. Although various methods for correcting aerial survey bias are employed on large mammal species around the world, these have rarely been rigorously validated. Several populations of feral horses (Equus caballus) in the western United States have been intensively studied, resulting in identification of all unique individuals. This provided a rare opportunity to test aerial survey bias correction on populations of known abundance. We hypothesized that a hybrid method combining simultaneous double-observer and sightability bias correction techniques would accurately estimate abundance. We validated this integrated technique on populations of known size and also on a pair of surveys before and after a known number was removed. Our analysis identified several covariates across the surveys that explained and corrected biases in the estimates. All six tests on known populations produced estimates with deviations from the known value ranging from -8.5% to +13.7% and <0.7 standard errors. Precision varied widely, from 6.1% CV to 25.0% CV. In contrast, the pair of surveys conducted around a known management removal produced an estimated change in population between the surveys that was significantly larger than the known reduction. Although the deviation between was only 9.1%, the precision estimate (CV = 1.6%) may have been artificially low. It was apparent that use of a helicopter in those surveys perturbed the horses, introducing detection error and heterogeneity in a manner that could not be corrected by our statistical models. Our results validate the hybrid method, highlight its potentially broad applicability, identify some limitations, and provide insight and guidance for improving survey designs.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0154902","usgsCitation":"Lubow, B., and Ransom, J.I., 2016, Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations: PLoS ONE, v. 11, no. 5, e0154902, 15 p., https://doi.org/10.1371/journal.pone.0154902.","productDescription":"e0154902, 15 p.","ipdsId":"IP-074372","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471028,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0154902","text":"Publisher Index Page"},{"id":373550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Nevada, Utah, Wyoming","otherGeospatial":"Cedar Mountain Herd Management Area, Little Owyhee Herd Management Area, McCullough Peaks Herd Management Area, Sand Wash Herd Management Area, Snowstorm Mountains Herd Management Area ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.00634765625,\n 44.308126684886126\n ],\n [\n -107.89672851562499,\n 44.308126684886126\n ],\n [\n -107.89672851562499,\n 44.98034238084973\n ],\n [\n -109.00634765625,\n 44.98034238084973\n ],\n [\n -109.00634765625,\n 44.308126684886126\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.984375,\n 40.26276066437183\n ],\n [\n -108.017578125,\n 40.26276066437183\n ],\n [\n -108.017578125,\n 40.896905775860006\n ],\n [\n -108.984375,\n 40.896905775860006\n ],\n [\n -108.984375,\n 40.26276066437183\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.48876953125,\n 39.9434364619742\n ],\n [\n -112.87353515625,\n 39.9434364619742\n ],\n [\n -112.87353515625,\n 40.6306300839918\n ],\n [\n -113.48876953125,\n 40.6306300839918\n ],\n [\n -113.48876953125,\n 39.9434364619742\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.24609374999999,\n 41.393294288784865\n ],\n [\n -116.52099609375,\n 41.393294288784865\n ],\n [\n -116.52099609375,\n 41.95131994679697\n ],\n [\n -117.24609374999999,\n 41.95131994679697\n ],\n [\n -117.24609374999999,\n 41.393294288784865\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-03","publicationStatus":"PW","contributors":{"editors":[{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785658,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Lubow, Bruce C.","contributorId":131076,"corporation":false,"usgs":false,"family":"Lubow","given":"Bruce C.","affiliations":[{"id":7230,"text":"Natural Resource Ecology Laboratory, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":785656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ransom, Jason I.","contributorId":139841,"corporation":false,"usgs":false,"family":"Ransom","given":"Jason","email":"","middleInitial":"I.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":785657,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170087,"text":"ofr20161030 - 2016 - Improve wildlife species tracking—Implementing an enhanced global positioning system data management system for California condors","interactions":[],"lastModifiedDate":"2016-05-03T10:16:16","indexId":"ofr20161030","displayToPublicDate":"2016-05-03T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1030","title":"Improve wildlife species tracking—Implementing an enhanced global positioning system data management system for California condors","docAbstract":"U.S. Fish and Wildlife Service (USFWS) staff in the Pacific Southwest Region and at the Hopper Mountain National Wildlife Refuge Complex requested technical assistance to improve their global positioning system (GPS) data acquisition, management, and archive in support of the California Condor Recovery Program. The USFWS deployed and maintained GPS units on individual Gymnogyps californianus (California condor) in support of long-term research and daily operational monitoring and management of California condors. The U.S. Geological Survey (USGS) obtained funding through the Science Support Program to provide coordination among project participants, provide GPS Global System for Mobile Communication (GSM) transmitters for testing, and compare GSM/GPS with existing Argos satellite GPS technology. The USFWS staff worked with private companies to design, develop, and fit condors with GSM/GPS transmitters. The Movebank organization, an online database of animal tracking data, coordinated with each of these companies to automatically stream their GPS data into Movebank servers and coordinated with USFWS to improve Movebank software for managing transmitter data, including proofing/error checking of incoming GPS data. The USGS arranged to pull raw GPS data from Movebank into the USGS California Condor Management and Analysis Portal (CCMAP) (https://my.usgs.gov/ccmap) for production and dissemination of a daily map of condor movements including various automated alerts. Further, the USGS developed an automatic archiving system for pulling raw and proofed Movebank data into USGS ScienceBase to comply with the Federal Information Security Management Act of 2002. This improved data management system requires minimal manual intervention resulting in more efficient data flow from GPS data capture to archive status. As a result of the project’s success, Pinnacles National Park and the Ventana Wildlife Society California condor programs became partners and adopted the same workflow, tracking, and data archive system. This GPS tracking data management model and workflow should be applicable and beneficial to other wildlife tracking programs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161030","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service, Region 8","usgsCitation":"Waltermire, R.G., Emmerich, C.U., Mendenhall, L.C., Bohrer, Gil, Weinzierl, R.P., McGann, A.J., Lineback, P.K., Kern, T.J., and Douglas, D.C., 2016, Improve wildlife species tracking—Implementing an enhanced global positioning system data management system for California condors: U.S. Geological Survey Open-File Report 2016–1030, 46 p., https://dx.doi.org/10.3133/ofr20161030.","productDescription":"vi, 46 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066019","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":320820,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1030/ofr20161030.pdf","text":"Report","size":"5.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1032"},{"id":320819,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1030/coverthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.29980468749999,\n 37.07271048132946\n ],\n [\n -122.1240234375,\n 36.86204269508728\n ],\n [\n -121.79443359375,\n 36.87962060502676\n ],\n [\n -121.88232421875,\n 36.686041276581925\n ],\n [\n -122.05810546875,\n 36.63316209558658\n ],\n [\n -121.9482421875,\n 36.2265501474709\n ],\n [\n -121.53076171875,\n 35.871246850027966\n ],\n [\n -121.201171875,\n 35.60371874069731\n ],\n [\n -120.9814453125,\n 35.31736632923788\n ],\n [\n -120.95947265624999,\n 35.137879119634185\n ],\n [\n -120.76171875,\n 35.10193405724606\n ],\n [\n -120.65185546875,\n 34.66935854524543\n ],\n [\n -120.80566406250001,\n 34.52466147177172\n ],\n [\n -120.25634765624999,\n 34.34343606848294\n ],\n [\n -119.94873046875,\n 34.379712580462204\n ],\n [\n -119.59716796875,\n 34.34343606848294\n ],\n [\n -119.2236328125,\n 34.21634468843465\n ],\n [\n -118.91601562499999,\n 33.88865750124075\n ],\n [\n -118.5205078125,\n 33.88865750124075\n ],\n [\n -118.19091796875,\n 33.63291573870476\n ],\n [\n -117.83935546874999,\n 33.486435450999885\n ],\n [\n -117.6416015625,\n 33.87041555094183\n ],\n [\n -116.23535156249999,\n 34.03445260967645\n ],\n [\n -116.25732421875,\n 35.7286770448517\n ],\n [\n -116.89453125,\n 35.60371874069731\n ],\n [\n -117.22412109375,\n 36.38591277287651\n ],\n [\n -117.97119140625,\n 37.212831514455964\n ],\n [\n -118.47656249999999,\n 37.35269280367274\n ],\n [\n -118.95996093749999,\n 37.09023980307208\n ],\n [\n -119.77294921874999,\n 37.19533058280065\n ],\n [\n -120.34423828125,\n 37.28279464911045\n ],\n [\n -121.06933593749999,\n 37.23032838760387\n ],\n [\n -121.31103515625,\n 37.45741810262938\n ],\n [\n -121.55273437499999,\n 37.24782120155428\n ],\n [\n -121.9482421875,\n 37.125286284966805\n ],\n [\n -122.29980468749999,\n 37.07271048132946\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The Blackbird cobalt-copper (Co-Cu) district in the Salmon River Mountains of east-central Idaho occupies the central part of the Idaho cobalt belt—a northwest-elongate, 55-km-long belt of Co-Cu occurrences, hosted in grayish siliciclastic metasedimentary strata of the Lemhi subbasin (of the Mesoproterozoic Belt-Purcell Basin). The Blackbird district contains at least eight stratabound ore zones and many discordant lodes, mostly in the upper part of the banded siltite unit of the Apple Creek Formation of Yellow Lake, which generally consists of interbedded siltite and argillite. In the Blackbird mine area, argillite beds in six stratigraphic intervals are altered to biotitite containing over 75 vol% of greenish hydrothermal biotite, which is preferentially mineralized.
Past production and currently estimated resources of the Blackbird district total ~17 Mt of ore, averaging 0.74% Co, 1.4% Cu, and 1.0 ppm Au (not including downdip projections of ore zones that are open downward). A compilation of relative-age relationships and isotopic age determinations indicates that most cobalt mineralization occurred in Mesoproterozoic time, whereas most copper mineralization occurred in Cretaceous time.
Mesoproterozoic cobaltite mineralization accompanied and followed dynamothermal metamorphism and bimodal plutonism during the Middle Mesoproterozoic East Kootenay orogeny (ca. 1379–1325 Ma), and also accompanied Grenvilleage (Late Mesoproterozoic) thermal metamorphism (ca. 1200–1000 Ma). Stratabound cobaltite-biotite ore zones typically contain cobaltite1 in a matrix of biotitite ± tourmaline ± minor xenotime (ca. 1370–1320 Ma) ± minor chalcopyrite ± sparse allanite ± sparse microscopic native gold in cobaltite. Such cobaltite-biotite lodes are locally folded into tight F2 folds with axial-planar S2 cleavage and schistosity. Discordant replacement-style lodes of cobaltite2-biotite ore ± xenotime2 (ca. 1320–1270 Ma) commonly follow S2fractures and fabrics. Discordant quartz-biotite and quartz-tourmaline breccias, and veins contain cobaltite3 ± xenotime3 (ca. 1058–990 Ma).
Mesoproterozoic cobaltite deposition was followed by: (1) within-plate plutonism (530–485 Ma) and emplacement of mafic dikes (which cut cobaltite lodes but are cut by quartz-Fe-Cu-sulfide veins); (2) garnet-grade metamorphism (ca. 151–93 Ma); (3) Fe-Cu-sulfide mineralization (ca. 110–92 Ma); and (4) minor quartz ± Au-Ag ± Bi mineralization (ca. 92–83 Ma).
Cretaceous Fe-Cu-sulfide vein, breccia, and replacement-style deposits contain various combinations of chalcopyrite ± pyrrhotite ± pyrite ± cobaltian arsenopyrite (not cobaltite) ± arsenopyrite ± quartz ± siderite ± monazite (ca. 144–88 Ma but mostly 110–92 Ma) ± xenotime (104–93 Ma). Highly radiogenic Pb (in these sulfides) and Sr (in siderite) indicate that these elements resided in Mesoproterozoic source rocks until they were mobilized after ca. 100 Ma. Fe-Cu-sulfide veins, breccias, and replacement deposits appear relatively undeformed and generally lack metamorphic fabrics.
Composite Co-Cu-Au ore contains early cobaltite-biotite lodes, cut by Fe-Cu-sulfide veins and breccias, or overprinted by Fe-Cu-sulfide replacement-style deposits, and locally cut by quartz veinlets ± Au-Ag ± Bi minerals.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2016.2522(08)","usgsCitation":"Bookstrom, A.A., Box, S.E., Cossette, P.M., Frost, T.P., Gillerman, V., King, G., and Zirakparvar, N.A., 2016, Geologic history of the Blackbird Co-Cu district in the Lemhi subbasin of the Belt-Purcell Basin: GSA Special Papers, v. 522, p. 185-219, https://doi.org/10.1130/2016.2522(08).","productDescription":"36 p. 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Igneous and sedimentary rocks in the Greenwater Range, one mountain range east of Death Valley, tell an earlier story that overlaps with the formation of Death Valley proper. This early story has been told by scientists who have studied these rocks for many years and continue to do so. This field guide was prepared for the first Death Valley Natural History Conference and provides an overview of the geology of the Greenwater Range and the early history (10–0 Ma) of Death Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161064","usgsCitation":"Calzia, J.P., Rämö, O.T., Jachens, Robert, Smith, Eugene, and Knott, Jeffrey, 2016, Geology of the Greenwater Range, and the dawn of Death Valley, California—Field guide for the Death Valley Natural History Conference, 2013: U.S. Geological Survey Open-File Report 2016–1064, 32 p., https://dx.doi.org/10.3133/ofr20161064.","productDescription":"iv, 32 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073504","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":320772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1064/ofr20161064.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1064 Report PDF"},{"id":320771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1064/coverthb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Death Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.10052490234375,\n 36.07241230197147\n ],\n [\n -117.10052490234375,\n 36.59127365634205\n ],\n [\n -116.27517700195312,\n 36.59127365634205\n ],\n [\n -116.27517700195312,\n 36.07241230197147\n ],\n [\n -117.10052490234375,\n 36.07241230197147\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center—
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Dams impound the majority of rivers and provide important societal benefits, especially daily water releases that enable on-peak hydroelectricity generation. Such “hydropeaking” is common worldwide, but its downstream impacts remain unclear. We evaluated the response of aquatic insects, a cornerstone of river food webs, to hydropeaking using a life history–hydrodynamic model. Our model predicts that aquatic-insect abundance will depend on a basic life-history trait—adult egg-laying behavior—such that open-water layers will be unaffected by hydropeaking, whereas ecologically important and widespread river-edge layers, such as mayflies, will be extirpated. These predictions are supported by a more-than-2500-sample, citizen-science data set of aquatic insects from the Colorado River in the Grand Canyon and by a survey of insect diversity and hydropeaking intensity across dammed rivers of the Western United States. Our study reveals a hydropeaking-related life history bottleneck that precludes viable populations of many aquatic insects from inhabiting regulated rivers.
","language":"English","publisher":"American Institute of Biological Sciences","publisherLocation":"Washington, D.C.","doi":"10.1093/biosci/biw059","usgsCitation":"Kennedy, T.A., Muehlbauer, J.D., Yackulic, C.B., Lytle, D., Miller, S., Dibble, K.L., Kortenhoeven, E.W., Metcalfe, A.N., and Baxter, C., 2016, Flow management for hydropower extirpates aquatic insects, undermining river food webs: BioScience, v. 66, no. 7, p. 561-575, https://doi.org/10.1093/biosci/biw059.","productDescription":"15 p.","startPage":"561","endPage":"575","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069041","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471029,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biw059","text":"Publisher Index Page"},{"id":438616,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WM1BH4","text":"USGS data release","linkHelpText":"Flow management for hydropower extirpates aquatic insects, undermining river food websData"},{"id":320875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-02","publicationStatus":"PW","scienceBaseUri":"5729cbb2e4b0b13d3919a342","contributors":{"authors":[{"text":"Kennedy, Theodore A. 0000-0003-3477-3629 tkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":167537,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628489,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lytle, D.A.","contributorId":85422,"corporation":false,"usgs":true,"family":"Lytle","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":628491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, S.A.","contributorId":66389,"corporation":false,"usgs":true,"family":"Miller","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":628492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dibble, Kimberly L. 0000-0003-0799-4477 kdibble@usgs.gov","orcid":"https://orcid.org/0000-0003-0799-4477","contributorId":5174,"corporation":false,"usgs":true,"family":"Dibble","given":"Kimberly","email":"kdibble@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628500,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kortenhoeven, Eric W. ekortenhoeven@usgs.gov","contributorId":5046,"corporation":false,"usgs":true,"family":"Kortenhoeven","given":"Eric","email":"ekortenhoeven@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628493,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Metcalfe, Anya N. 0000-0002-6286-4889 ametcalfe@usgs.gov","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":5271,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","email":"ametcalfe@usgs.gov","middleInitial":"N.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628494,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Baxter, Colden V.","contributorId":47334,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden V.","affiliations":[{"id":13656,"text":"Idaho State Univ.","active":true,"usgs":false}],"preferred":false,"id":628501,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70170721,"text":"70170721 - 2016 - Timing and composition of continental volcanism at Harrat Hutaymah, western Saudi Arabia","interactions":[],"lastModifiedDate":"2016-05-04T08:38:28","indexId":"70170721","displayToPublicDate":"2016-05-02T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Timing and composition of continental volcanism at Harrat Hutaymah, western Saudi Arabia","docAbstract":"Harrat Hutaymah is an alkali basalt volcanic field in north-central Saudi Arabia, at the eastern margin of a large Neogene continental, intraplate magmatic province. Lava flow, tephra and spatter cone compositions in the field include alkali olivine basalts and basanites. These compositions contrast with the predominantly tholeiitic, fissure-fed basalts found along the eastern margin of the Red Sea. The Hutaymah lava flows were erupted through Proterozoic arc-associated plutonic and meta-sedimentary rocks of the Arabian shield, and commonly contain a range of sub-continental lithospheric xenoliths, although the lavas themselves show little indication of crustal contamination. Previous radiometric dating of this volcanic field (a single published K–Ar age; 1.8 Ma) is suspiciously old given the field measurement of normal magnetic polarity only (i.e. Brunhes interval, ≤ 780 Ka). We report new age determinations on 14 lava flows by the 40Ar–39Ar laser step heating method, all younger than ~ 850 Ka, to better constrain the time frame of volcanism, and major, trace and rare earth element compositions to describe the chemical variation of volcanic activity at Harrat Hutaymah. Crystal fractionation was dominated by olivine ± clinopyroxene at a range of upper mantle and crustal pressures. Rapid ascent and eruption of magma is indicated by the array of lower crustal and lithospheric xenoliths observed in lava flows and tephra. Modeling suggests 1–7% melting of an enriched asthenospheric mantle source occurred beneath Harrat Hutaymah under a relatively thick lithospheric cap (60–80 km).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2016.01.010","usgsCitation":"Duncan, R.A., Kent, A.J., Thornber, C., Schliedler, T.D., and Al-Amri, A.M., 2016, Timing and composition of continental volcanism at Harrat Hutaymah, western Saudi Arabia: Journal of Volcanology and Geothermal Research, v. 313, p. 1-14, https://doi.org/10.1016/j.jvolgeores.2016.01.010.","productDescription":"14 p.","startPage":"1","endPage":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070061","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2016.01.010","text":"Publisher Index Page"},{"id":320813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Saudi Arabia","otherGeospatial":"Harrat Hutaymah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 30,\n 1\n ],\n [\n 30,\n 40\n ],\n [\n 55,\n 40\n ],\n [\n 55,\n 1\n ],\n [\n 30,\n 1\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"313","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57286c1be4b0b13d3917ce12","contributors":{"authors":[{"text":"Duncan, Robert A.","contributorId":167399,"corporation":false,"usgs":false,"family":"Duncan","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":628172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kent, Adam J R","contributorId":168855,"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":628173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thornber, Carl 0000-0002-6382-4408 cthornber@usgs.gov","orcid":"https://orcid.org/0000-0002-6382-4408","contributorId":167396,"corporation":false,"usgs":true,"family":"Thornber","given":"Carl","email":"cthornber@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":628171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schliedler, Tyler D","contributorId":169027,"corporation":false,"usgs":false,"family":"Schliedler","given":"Tyler","email":"","middleInitial":"D","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":628174,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Al-Amri, Abdullah M","contributorId":169028,"corporation":false,"usgs":false,"family":"Al-Amri","given":"Abdullah","email":"","middleInitial":"M","affiliations":[{"id":24707,"text":"King Saud University, Riyahd, KSA","active":true,"usgs":false}],"preferred":false,"id":628175,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170755,"text":"70170755 - 2016 - Preface: Land subsidence processes","interactions":[],"lastModifiedDate":"2019-09-06T11:12:11","indexId":"70170755","displayToPublicDate":"2016-05-02T11:30:00","publicationYear":"2016","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":"Preface: Land subsidence processes","docAbstract":"No abstract available.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1386-y","usgsCitation":"Galloway, D.L., Erkens, G., Kuniansky, E.L., and Rowland, J.C., 2016, Preface: Land subsidence processes: Hydrogeology Journal, v. 24, no. 3, p. 547-550, https://doi.org/10.1007/s10040-016-1386-y.","productDescription":"3 p.","startPage":"547","endPage":"550","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072759","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":471031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-016-1386-y","text":"Publisher Index Page"},{"id":320814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-04","publicationStatus":"PW","scienceBaseUri":"57286c1be4b0b13d3917ce10","contributors":{"authors":[{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":628277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erkens, Gilles","contributorId":169045,"corporation":false,"usgs":false,"family":"Erkens","given":"Gilles","email":"","affiliations":[{"id":25398,"text":"Deltares Research Institute, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":628278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuniansky, Eve L. 0000-0002-5581-0225 elkunian@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-0225","contributorId":932,"corporation":false,"usgs":true,"family":"Kuniansky","given":"Eve","email":"elkunian@usgs.gov","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":628279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowland, Joel C.","contributorId":169046,"corporation":false,"usgs":false,"family":"Rowland","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":628280,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170759,"text":"70170759 - 2016 - Hydrologic exchanges and baldcypress water use on deltaic hummocks, Louisiana, USA","interactions":[],"lastModifiedDate":"2016-12-09T16:35:39","indexId":"70170759","displayToPublicDate":"2016-05-02T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic exchanges and baldcypress water use on deltaic hummocks, Louisiana, USA","docAbstract":"Coastal forested hummocks support clusters of trees in the saltwater–freshwater transition zone. To examine how hummocks support trees in mesohaline sites that are beyond physiological limits of the trees, we used salinity and stable isotopes (2H and 18O) of water as tracers to understand water fluxes in hummocks and uptake by baldcypress (Taxodium distichum (L.) Rich.), which is the most abundant tree species in coastal freshwater forests of the southeastern U.S. Hummocks were always partially submerged and were completely submerged 1 to 8% of the time during the two studied growing seasons, in association with high water in the estuary. Salinity, δ18O, and δ2H varied more in the shallow open water than in groundwater. Surface water and shallow groundwater were similar to throughfall in isotopic composition, which suggested dominance by rainfall. Salinity of groundwater in hummocks increased with depth, was higher than in swales, and fluctuated little over time. Isotopic composition of xylem water in baldcypress was similar to the vadose zone and unlike other measured sources, indicating that trees preferentially use unsaturated hummock tops as refugia from higher salinity and saturated soil in swales and the lower portions of hummocks. Sustained upward gradients of salinity from groundwater to surface water and vadose water, and low variation in groundwater salinity and isotopic composition, suggested long residence time, limited exchange with surface water, and that the shallow subsurface of hummocks is characterized by episodic salinization and slow dilution.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1738","usgsCitation":"Hsueh, Y., Chambers, J., Krauss, K.W., Allen, S.T., and Keim, R., 2016, Hydrologic exchanges and baldcypress water use on deltaic hummocks, Louisiana, USA: Ecohydrology, v. 9, no. 8, p. 1452-1463, https://doi.org/10.1002/eco.1738.","productDescription":"12 p.","startPage":"1452","endPage":"1463","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067366","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":320812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Jean Lafitte National Historical Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.14,\n 29.75\n ],\n [\n -90.14,\n 29.76\n ],\n [\n -90.15,\n 29.76\n ],\n [\n -90.15,\n 29.75\n ],\n [\n -90.14,\n 29.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-28","publicationStatus":"PW","scienceBaseUri":"57286c1be4b0b13d3917ce0e","contributors":{"authors":[{"text":"Hsueh, Yu-Hsin","contributorId":169051,"corporation":false,"usgs":false,"family":"Hsueh","given":"Yu-Hsin","email":"","affiliations":[],"preferred":false,"id":628310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chambers, Jim L.","contributorId":16498,"corporation":false,"usgs":true,"family":"Chambers","given":"Jim L.","affiliations":[],"preferred":false,"id":628311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":628298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Scott T.","contributorId":168409,"corporation":false,"usgs":false,"family":"Allen","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":25282,"text":"School of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":628312,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keim, Richard F.","contributorId":21858,"corporation":false,"usgs":true,"family":"Keim","given":"Richard F.","affiliations":[],"preferred":false,"id":628313,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170760,"text":"70170760 - 2016 - Female gonadal hormones and reproductive behaviors as key determinants of successful reproductive output of breeding whooping cranes (Grus americana)","interactions":[],"lastModifiedDate":"2016-05-02T10:19:20","indexId":"70170760","displayToPublicDate":"2016-05-02T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1738,"text":"General and Comparative Endocrinology","active":true,"publicationSubtype":{"id":10}},"title":"Female gonadal hormones and reproductive behaviors as key determinants of successful reproductive output of breeding whooping cranes (Grus americana)","docAbstract":"Reproductive success of endangered whooping cranes (Grus americana) maintained ex situ is poor. As part of an effort to identify potential causes of poor reproductive success in a captive colony, we used non-invasive endocrine monitoring to assess gonadal and adrenal steroids of bird pairs with various reproductive outcomes and evaluated the relationships of hormones and behaviors to reproductive performance. Overall, reproductively successful (i.e., egg laying) females had significantly higher mean estrogen levels but lower mean progestogen concentrations than did unsuccessful females. Other hormones, including glucocorticoids and androgens, were not significantly different between successful and unsuccessful individuals. Observations of specific behaviors such as unison calling, marching, and the number of copulation attempts, along with overall time spent performing reproductive behaviors, were significantly higher in successful pairs. Our findings indicate that overall reproductive performance of whooping crane pairs is linked to female gonadal hormone excretion and reproductive behaviors, but not to altered adrenal hormone production.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ygcen.2016.04.009","usgsCitation":"Brown, M.E., Converse, S.J., Chandler, J.N., Shafer, C., Brown, J.L., Keefer, C., and Songsasen, N., 2016, Female gonadal hormones and reproductive behaviors as key determinants of successful reproductive output of breeding whooping cranes (Grus americana): General and Comparative Endocrinology, v. 230-231, p. 158-165, https://doi.org/10.1016/j.ygcen.2016.04.009.","productDescription":"8 p.","startPage":"158","endPage":"165","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074740","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471032,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ygcen.2016.04.009","text":"Publisher Index Page"},{"id":320811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"230-231","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57286c19e4b0b13d3917ce08","contributors":{"authors":[{"text":"Brown, Megan E.","contributorId":169048,"corporation":false,"usgs":false,"family":"Brown","given":"Megan","email":"","middleInitial":"E.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":628300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":3513,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":628299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, Jane N. 0000-0002-6131-2396 jchandler@usgs.gov","orcid":"https://orcid.org/0000-0002-6131-2396","contributorId":3512,"corporation":false,"usgs":true,"family":"Chandler","given":"Jane","email":"jchandler@usgs.gov","middleInitial":"N.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":628301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shafer, Charles cshafer@usgs.gov","contributorId":3510,"corporation":false,"usgs":true,"family":"Shafer","given":"Charles","email":"cshafer@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":628302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Janine L","contributorId":169049,"corporation":false,"usgs":false,"family":"Brown","given":"Janine","email":"","middleInitial":"L","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":628303,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keefer, Carol L","contributorId":146370,"corporation":false,"usgs":false,"family":"Keefer","given":"Carol L","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":628304,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Songsasen, Nucharin","contributorId":146371,"corporation":false,"usgs":false,"family":"Songsasen","given":"Nucharin","email":"","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":628305,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70162383,"text":"sir20165008 - 2016 - Geology of tight oil and potential tight oil reservoirs in the lower part of the Green River Formation, Uinta, Piceance, and Greater Green River Basins, Utah, Colorado, and Wyoming","interactions":[],"lastModifiedDate":"2016-05-02T10:42:55","indexId":"sir20165008","displayToPublicDate":"2016-05-02T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5008","title":"Geology of tight oil and potential tight oil reservoirs in the lower part of the Green River Formation, Uinta, Piceance, and Greater Green River Basins, Utah, Colorado, and Wyoming","docAbstract":"The recent successful development of a tight oil play in the Eocene-age informal Uteland Butte member of the lacustrine Green River Formation in the Uinta Basin, Utah, using modern horizontal drilling and hydraulic fracturing techniques has spurred a renewed interest in the tight oil potential of lacustrine rocks. The Green River Formation was deposited by two large lakes, Lake Uinta in the Uinta and Piceance Basins and Lake Gosiute in the Greater Green River Basin. These three basins contain the world’s largest in-place oil shale resources with recent estimates of 1.53 trillion, 1.33 trillion, and 1.44 trillion barrels of oil in place in the Piceance, Uinta, and Greater Green River Basins, respectively. The Uteland Butte member was deposited during an early freshwater stage of the lake in the Uinta Basin prior to deposition of the assessed oil shale intervals. This report only presents information on the early freshwater interval and overlying brackish-water interval in all three basins because these intervals are most likely to have tight oil potential. Burial histories of the three basins were reconstructed to study (1) variations in subsidence and lake development, and (2) post deposition burial that led to the development of a petroleum system in only the Uinta Basin. The Uteland Butte member is a successful tight oil play because it is thermally mature for hydrocarbon generation and contains organic-rich shale, brittle carbonate, and porous dolomite. Abnormally high pressure in parts of the Uteland Butte is also important to production. Variations in organic richness of the Uteland Butte were studied using Fischer assay analysis from oil shale assessments, and pressures were studied using drill-stem tests. Freshwater lacustrine intervals in the Piceance and Greater Green River Basins are immature for hydrocarbon generation and contain much less carbonate than the Uteland Butte member. The brackish-water interval in the Uinta Basin is thermally mature for hydrocarbon generation but is clay-rich and contains little carbonate, and thus is a poor prospect for tight oil development.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165008","usgsCitation":"Johnson, R.C., Birdwell, J.E., Mercier, T.J., and Brownfield, M.E., 2016, Geology of tight oil and potential tight oil reservoirs in the lower part of the Green River Formation, Uinta, Piceance, and Greater Green River Basins, Utah, Colorado, and Wyoming: U.S. Geological Survey Scientific Investigations Report 2016–5008, 63 p., https://dx.doi.org/10.3133/sir20165008.","productDescription":"Report: vii, 63 p.; Table 1; Figure 29","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059890","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":320649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5008/coverthb.jpg"},{"id":320650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5008/sir20165008.pdf","text":"Report","size":"53.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5008"},{"id":320651,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2016/5008/sir20165008_fig29.pdf","text":"Figure 29","size":"1.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5008 Figure 29"},{"id":320672,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5008/sir20165008_Table1UtelandFischerassay.xlsx","text":"Table 1","size":"68.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5008 Table 1"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Green River Basin, Piceance River Basin, Uinta River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.566162109375,\n 38.62545397209084\n ],\n [\n -111.566162109375,\n 43.30119623257966\n ],\n [\n -106.336669921875,\n 43.30119623257966\n ],\n [\n -106.336669921875,\n 38.62545397209084\n ],\n [\n -111.566162109375,\n 38.62545397209084\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
Taiyangshan is a poorly studied copper–molybdenum deposit located in the Triassic Western Qinling collisional belt of northwest China. The intrusions exposed in the vicinity of the Taiyangshan deposit record episodic magmatism over 20–30 million years. Pre-mineralization quartz diorite porphyries, which host some of the deposit, were emplaced at 226.6 ± 6.2 Ma. Syn-collisional monzonite and quartz monzonite porphyries, which also host mineralization, were emplaced at 218.0 ± 6.1 Ma and 215.0 ± 5.8 Ma, respectively. Mineralization occurred during the transition from a syn-collisional to a post-collisional setting at ca. 208 Ma. A barren post-mineralization granite porphyry marked the end of post-collisional magmatism at 200.7 ± 5.1 Ma. The ore-bearing monzonite and quartz monzonite porphyries have a εHf(t) range from − 2.0 to + 12.5, which is much more variable than that of the slightly older quartz diorite porphyries, with TDM2 of 1.15–1.23 Ga corresponding to the positive εHf(t) values and TDM1 of 0.62–0.90 Ga corresponding to the negative εHf(t) values. Molybdenite in the Taiyangshan deposit with 27.70 to 38.43 ppm Re suggests metal sourced from a mantle–crust mixture or from mafic and ultramafic rocks in the lower crust. The δ34S values obtained for pyrite, chalcopyrite, and molybdenite from the deposit range from + 1.3‰ to + 4.0‰, + 0.2‰ to + 1.1‰, and + 5.3‰ to + 5.9‰, respectively, suggesting a magmatic source for the sulfur. Calculated δ18Ofluid values for magmatic K-feldspar from porphyries (+ 13.3‰), hydrothermal K-feldspar from stockwork veins related to potassic alteration (+ 11.6‰), and hydrothermal sericite from quartz–pyrite veins (+ 8.6 to + 10.6‰) indicate the Taiyangshan deposit formed dominantly from magmatic water. Hydrogen isotope values for hydrothermal sericite ranging from − 85 to − 50‰ may indicate that magma degassing progressively depleted residual liquid in deuterium during the life of the magmatic–hydrothermal system. Alternatively, δD variability may have been caused by a minor amount of mixing with meteoric waters. We propose that the ore-related magma was derived from partial melting of the ancient Mesoproterozoic to Neoproterozoic middle to lower continental crust. This crust was likely metasomatized during earlier subduction, and the crustal magmas may have been contaminated with lithospheric mantle derived magma triggered by MASH (e.g., melting, assimilation, storage, and homogenization) processes during collisional orogeny. In addition, a significant proportion of the metals and sulfur supplied from mafic magma were simultaneously incorporated into the resultant hybrid magmas.
","language":"English","publisher":"International Association for Gondwana Research","doi":"10.1016/j.gr.2016.03.014","usgsCitation":"Kun-Feng Qiu, Taylor, R.D., Song, Y., Yu, H., Kai-Rui Song, and Li, N., 2016, Geologic and geochemical insights into the formation of the Taiyangshan porphyry copper–molybdenum deposit, Western Qinling Orogenic Belt, China: Gondwana Research, v. 35, p. 40-58, https://doi.org/10.1016/j.gr.2016.03.014.","productDescription":"19 p.","startPage":"40","endPage":"58","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072464","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":322044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 102,\n 32\n ],\n [\n 102,\n 36\n ],\n [\n 107,\n 36\n ],\n [\n 107,\n 32\n ],\n [\n 102,\n 32\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57500763e4b0ee97d51bb609","contributors":{"authors":[{"text":"Kun-Feng Qiu","contributorId":169784,"corporation":false,"usgs":false,"family":"Kun-Feng Qiu","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":631054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Song, Yao-Hui","contributorId":169785,"corporation":false,"usgs":false,"family":"Song","given":"Yao-Hui","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yu, Hao-Cheng","contributorId":169788,"corporation":false,"usgs":false,"family":"Yu","given":"Hao-Cheng","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631059,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kai-Rui Song","contributorId":169786,"corporation":false,"usgs":false,"family":"Kai-Rui Song","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631057,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Nan","contributorId":169787,"corporation":false,"usgs":false,"family":"Li","given":"Nan","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631058,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174339,"text":"70174339 - 2016 - A millennial-scale record of Pb and Hg contamination in peatlands of the Sacramento-San Joaquin Delta of California, USA","interactions":[],"lastModifiedDate":"2016-07-08T13:22:05","indexId":"70174339","displayToPublicDate":"2016-05-01T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A millennial-scale record of Pb and Hg contamination in peatlands of the Sacramento-San Joaquin Delta of California, USA","docAbstract":"In this paper, we provide the first record of millennial patterns of Pb and Hg concentrations on the west coast of the United States. Peat cores were collected from two micro-tidal marshes in the Sacramento-San Joaquin Delta of California. Core samples were analyzed for Pb, Hg, and Ti concentrations and dated using radiocarbon, 210Pb, and 137Cs. Pre-anthropogenic concentrations of Pb and Hg in peat ranged from 0.60 to 13.0 µg g-1and from 6.9 to 71 ng g-1, respectively. For much of the past 6000+ years, the Delta was free from anthropogenic pollution, however, beginning in ~1425 CE, Hg and Pb concentrations, Pb/Ti ratios, Pb enrichment factors (EFs), and HgEFs all increased. Pb isotope compositions of the peat suggest that this uptick was likely caused by smelting activities originating in Asia. The next increases in Pb and Hg contamination occurred during the California Gold Rush (beginning ~1850 CE), when concentrations reached their highest levels (74 µg g-1 Pb, 990 ng g-1 Hg; PbEF = 12 and HgEF = 28). Lead concentrations increased again beginning in the ~1920s with the incorporation of Pb additives in gasoline. The phase-out of lead additives in the late 1980s was reflected in Pb isotope ratios and reductions in Pb concentrations in the surface layers of the peat. The rise and fall of Hg contamination was also tracked by the peat archive, with the highest Hg concentrations occurring just before 1963 CE and then decreasing during the post-1963 period. Overall, the results show that the Delta was a pristine region for most of its ~6700-year existence; however, since ~1425 CE, it has received Pb and Hg contamination from both global and regional sources.
","language":"English","publisher":"Elsevier B.V.","doi":"10.1016/j.scitotenv.2016.01.201","collaboration":"(REPEAT II project)","usgsCitation":"Drexler, J.Z., Alpers, C.N., Neymark, L., Paces, J.B., Taylor, H.E., and Fuller, C.C., 2016, A millennial-scale record of Pb and Hg contamination in peatlands of the Sacramento-San Joaquin Delta of California, USA: Science of the Total Environment, v. 551-552, p. 738-751, https://doi.org/10.1016/j.scitotenv.2016.01.201.","productDescription":"13 p.","startPage":"738","endPage":"751","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071457","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":324937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta of California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.25537109375,\n 41.94314874732696\n ],\n [\n -124.3212890625,\n 41.73852846935917\n ],\n [\n -124.20043945312499,\n 41.65649719441145\n ],\n [\n -124.178466796875,\n 41.36856413680967\n ],\n [\n -124.31030273437499,\n 41.16211393939692\n ],\n [\n -124.222412109375,\n 40.95501133048621\n ],\n [\n -124.53002929687499,\n 40.463666324587685\n ],\n [\n -124.45312499999999,\n 40.245991504199026\n ],\n [\n -123.90380859374999,\n 39.69873414348139\n ],\n [\n -123.914794921875,\n 39.317300373271024\n ],\n [\n -123.85986328124999,\n 38.89103282648846\n ],\n [\n -123.6181640625,\n 38.7283759182398\n ],\n [\n -123.11279296875001,\n 38.08268954483802\n ],\n [\n -123.07983398437499,\n 37.94419750075404\n ],\n [\n -122.84912109375,\n 37.90953361677018\n ],\n [\n -122.78320312499999,\n 37.57070524233116\n ],\n [\n -122.56347656249999,\n 37.59682400108367\n ],\n [\n -121.10229492187501,\n 37.75334401310656\n ],\n [\n -121.322021484375,\n 38.59970036588819\n ],\n [\n -121.79443359375,\n 39.78321267821705\n ],\n [\n -121.728515625,\n 40.830436877649255\n ],\n [\n -121.89331054687499,\n 41.623655390686395\n ],\n [\n -121.92626953124999,\n 41.97582726102573\n ],\n [\n -124.25537109375,\n 41.94314874732696\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"551-552","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5780ceaee4b0811616822296","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":5044,"text":"National Research Program - 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Understanding the spatial variability of nutrient concentrations in flowing waters and the apparent contributions that human and nonhuman factors have on different sizes of streams and rivers is critical to the development of effective water quality assessment and management plans. This semi-quantitative analysis is also intended to identify areas within which more detailed quantitative work can be conducted to determine specific regional factors associated with variations in stream N concentrations.
","language":"English","publisher":"Soil and Water Conservation Society","doi":"10.2489/jswc.71.3.167","usgsCitation":"Omernik, J.M., Paulsen, S.G., Griffith, G.E., and Weber, M.H., 2016, Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment: Journal of Soil and Water Conservation, v. 71, no. 3, p. 167-181, https://doi.org/10.2489/jswc.71.3.167.","productDescription":"15 p.","startPage":"167","endPage":"181","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057215","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":322053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"71","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"57500771e4b0ee97d51bb70e","contributors":{"authors":[{"text":"Omernik, James M.","contributorId":169740,"corporation":false,"usgs":false,"family":"Omernik","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":25578,"text":"USGS -Volunteer","active":true,"usgs":false}],"preferred":false,"id":630982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paulsen, Steven G.","contributorId":169741,"corporation":false,"usgs":false,"family":"Paulsen","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":630983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griffith, Glenn E. 0000-0001-7966-4720 ggriffith@usgs.gov","orcid":"https://orcid.org/0000-0001-7966-4720","contributorId":4053,"corporation":false,"usgs":true,"family":"Griffith","given":"Glenn","email":"ggriffith@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":630981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, Marc H.","contributorId":169742,"corporation":false,"usgs":false,"family":"Weber","given":"Marc","email":"","middleInitial":"H.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":630984,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171382,"text":"70171382 - 2016 - Federal interagency nature‐like fishway passage design guidelines for Atlantic coast diadromous fishes","interactions":[],"lastModifiedDate":"2022-11-03T16:08:51.655969","indexId":"70171382","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Federal interagency nature‐like fishway passage design guidelines for Atlantic coast diadromous fishes","docAbstract":"The National Marine Fisheries Service (NMFS), the U.S. Geological Survey (USGS) and the U.S. Fish and Wildlife Service (USFWS) have collaborated to develop passage design guidance for use by engineers and other restoration practitioners considering and designing nature‐like fishways (NLFs). The primary purpose of these guidelines is to provide a summary of existing fish swimming and leaping performance data and the best available scientific information on safe, timely and effective passage for 14 diadromous fish species using Atlantic Coast rivers and streams. These guidelines apply to passage sites where complete barrier removal is not possible. This technical memorandum presents seven key physical design parameters based on the biometrics and swimming mode and performance of each target fishes for application in the design of NLFs addressing passage of a species or an assemblage of these species. The passage parameters include six dimensional guidelines recommended for minimum weir opening width and depth, minimum pool length, width and depth, and maximum channel slope, along with a maximum flow velocity guideline for each species. While\r\nthese guidelines are targeted for the design of step‐pool NLFs, the information may also have application in the design of other NLF types being considered at passage restoration sites and grade control necessary for infrastructure protection upstream of some dam removals, and in considering passage performance at sites such as natural bedrock features.","language":"English","publisher":"NOAA National Marine Fisheries Service","usgsCitation":"Turek, J., Haro, A.J., and Towler, B., 2016, Federal interagency nature‐like fishway passage design guidelines for Atlantic coast diadromous fishes, iii., 48 p.","productDescription":"iii., 48 p.","ipdsId":"IP-064934","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":336275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321862,"type":{"id":15,"text":"Index Page"},"url":"https://repository.library.noaa.gov/view/noaa/28919"}],"country":"United States","otherGeospatial":"Atlantic Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.53543042272173,\n 25.604386278077925\n ],\n [\n -78.9738695738202,\n 26.2643242769976\n ],\n [\n -77.65563187117027,\n 27.236312736346505\n ],\n [\n -77.71124176588978,\n 30.200566890880694\n ],\n [\n -75.63764563171657,\n 31.546671317157745\n ],\n [\n -72.88778473754125,\n 34.107153920647505\n ],\n [\n -71.80667946744646,\n 38.30485849898287\n ],\n [\n -68.12544832929673,\n 40.622781401735494\n ],\n [\n -66.51825275575436,\n 43.557615229438966\n ],\n [\n -66.93056853663478,\n 44.9924864367367\n ],\n [\n -70.50837479109403,\n 44.130583189469974\n ],\n [\n -71.56583190151437,\n 42.4531846455987\n ],\n [\n -71.04268393869013,\n 41.91302433499763\n ],\n [\n -73.12852497871336,\n 41.628116403040906\n ],\n [\n -74.47837257632011,\n 40.75996139502365\n ],\n [\n -74.85717819557229,\n 39.49615977300374\n ],\n [\n -75.36275241829512,\n 40.14818872121907\n ],\n [\n -76.70262042023853,\n 39.66328529391899\n ],\n [\n -77.26910128913559,\n 38.52431672198591\n ],\n [\n -76.80124506434308,\n 36.52548541174258\n ],\n [\n -77.48886662326828,\n 34.86340904706914\n ],\n [\n -78.19352283187868,\n 34.321846961811204\n ],\n [\n -79.02627770062944,\n 34.25764313694468\n ],\n [\n -79.67952029102847,\n 33.43439936645508\n ],\n [\n -81.32614282245044,\n 32.564707556457805\n ],\n [\n -82.03773749487134,\n 30.379248385899615\n ],\n [\n -80.44494631692717,\n 26.744769560981013\n ],\n [\n -80.53543042272173,\n 25.604386278077925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b548c1e4b01ccd54fddfb8","contributors":{"authors":[{"text":"Turek, James","contributorId":169721,"corporation":false,"usgs":false,"family":"Turek","given":"James","email":"","affiliations":[{"id":25574,"text":"NOAA/NMFS Restoration Center","active":true,"usgs":false}],"preferred":false,"id":630824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haro, Alexander J. 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":2917,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":630823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Towler, Brett","contributorId":141164,"corporation":false,"usgs":false,"family":"Towler","given":"Brett","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":630825,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192507,"text":"70192507 - 2016 - Trends in pesticide use on soybean, corn and cotton since the introduction of major genetically modified crops in the United States","interactions":[],"lastModifiedDate":"2017-10-26T10:27:36","indexId":"70192507","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Trends in pesticide use on soybean, corn and cotton since the introduction of major genetically modified crops in the United States","docAbstract":"BACKGROUND
Genetically modified (GM) varieties of soybean, corn and cotton have largely replaced conventional varieties in the United States. The most widely used applications of GM technology have been the development of crops that are resistant to a specific broad-spectrum herbicide (primarily glyphosate) or that produce insecticidal compounds within the plant itself. With the widespread adoption of GM crops, a decline in the use of conventional pesticides was expected.
RESULTS
There has been a reduction in the annual herbicide application rate to corn since the advent of GM crops, but the herbicide application rate is mostly unchanged for cotton. Herbicide use on soybean has increased. There has been a substantial reduction in the amount of insecticides used on both corn and cotton since the introduction of GM crops.
CONCLUSIONS
The observed changes in pesticide use are likely to be the result of many factors, including the introduction of GM crops, regulatory restrictions on some conventional pesticides, introduction of new pesticide technologies and changes in farming practices. In order to help protect human and environmental health and to help agriculture plan for the future, more detailed and complete documentation on pesticide use is needed on a frequent and ongoing basis.
","language":"English","publisher":"Wiley","doi":"10.1002/ps.4082","usgsCitation":"Coupe, R.H., and Capel, P.D., 2016, Trends in pesticide use on soybean, corn and cotton since the introduction of major genetically modified crops in the United States: Pest Management Science, v. 72, no. 5, p. 1013-1022, https://doi.org/10.1002/ps.4082.","productDescription":"10 p.","startPage":"1013","endPage":"1022","ipdsId":"IP-066541","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":347436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"72","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-10","publicationStatus":"PW","scienceBaseUri":"5a07ea42e4b09af898c8cc70","contributors":{"authors":[{"text":"Coupe, Richard H. 0000-0001-8679-1015 rhcoupe@usgs.gov","orcid":"https://orcid.org/0000-0001-8679-1015","contributorId":551,"corporation":false,"usgs":true,"family":"Coupe","given":"Richard","email":"rhcoupe@usgs.gov","middleInitial":"H.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":716095,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70161743,"text":"70161743 - 2016 - Summary of the GK15 ground‐motion prediction equation for horizontal PGA and 5% damped PSA from shallow crustal continental earthquakes","interactions":[],"lastModifiedDate":"2016-06-28T16:09:00","indexId":"70161743","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Summary of the GK15 ground‐motion prediction equation for horizontal PGA and 5% damped PSA from shallow crustal continental earthquakes","docAbstract":"We present a revised ground‐motion prediction equation (GMPE) for computing medians and standard deviations of peak ground acceleration (PGA) and 5% damped pseudospectral acceleration (PSA) response ordinates of the horizontal component of randomly oriented ground motions to be used for seismic‐hazard analyses and engineering applications. This GMPE is derived from the expanded Next Generation Attenuation (NGA)‐West 1 database (see Data and Resources; Chiou et al., 2008). The revised model includes an anelastic attenuation term as a function of quality factor (Q0) to capture regional differences in far‐source (beyond 150 km) attenuation, and a new frequency‐dependent sedimentary‐basin scaling term as a function of depth to the 1.5 km/s shear‐wave velocity isosurface to improve ground‐motion predictions at sites located on deep sedimentary basins. The new Graizer–Kalkan 2015 (GK15) model, developed to be simple, is applicable for the western United States and other similar shallow crustal continental regions in active tectonic environments for earthquakes with moment magnitudes (M) 5.0–8.0, distances 0–250 km, average shear‐wave velocities in the upper 30 m (VS30) 200–1300 m/s, and spectral periods (T) 0.01–5 s. Our aleatory variability model captures interevent (between‐event) variability, which decreases with magnitude and increases with distance. The mixed‐effect residuals analysis reveals that the GK15 has no trend with respect to the independent predictor parameters. Compared to our 2007–2009 GMPE, the PGA values are very similar, whereas spectral ordinates predicted are larger at T<0.2 s and they are smaller at longer periods.
","language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerito, CA","doi":"10.1785/0120150194","usgsCitation":"Graizer, V., and Kalkan, E., 2016, Summary of the GK15 ground‐motion prediction equation for horizontal PGA and 5% damped PSA from shallow crustal continental earthquakes: Bulletin of the Seismological Society of America, v. 106, no. 2, p. 687-707, https://doi.org/10.1785/0120150194.","productDescription":"21 p.","startPage":"687","endPage":"707","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065326","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":324563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Armenia, Georgia, Italy, Taiwan, Turkey, United States, Uzbekistan","state":"Alaska, California, Nevada","volume":"106","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-06","publicationStatus":"PW","scienceBaseUri":"57739fb7e4b07657d1a90d78","contributors":{"authors":[{"text":"Graizer, Vladimir;","contributorId":152040,"corporation":false,"usgs":false,"family":"Graizer","given":"Vladimir;","affiliations":[{"id":12536,"text":"U.S. Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":587625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":587624,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70184218,"text":"70184218 - 2016 - Megafloods and Clovis cache at Wenatchee, Washington","interactions":[],"lastModifiedDate":"2017-03-06T11:23:52","indexId":"70184218","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Megafloods and Clovis cache at Wenatchee, Washington","docAbstract":"Immense late Wisconsin floods from glacial Lake Missoula drowned the Wenatchee reach of Washington's Columbia valley by different routes. The earliest debacles, nearly 19,000 cal yr BP, raged 335 m deep down the Columbia and built high Pangborn bar at Wenatchee. As advancing ice blocked the northwest of Columbia valley, several giant floods descended Moses Coulee and backflooded up the Columbia past Wenatchee. Ice then blocked Moses Coulee, and Grand Coulee to Quincy basin became the westmost floodway. From Quincy basin many Missoula floods backflowed 50 km upvalley to Wenatchee 18,000 to 15,500 years ago. Receding ice dammed glacial Lake Columbia centuries more—till it burst about 15,000 years ago. After Glacier Peak ashfall about 13,600 years ago, smaller great flood(s) swept down the Columbia from glacial Lake Kootenay in British Columbia. The East Wenatchee cache of huge fluted Clovis points had been laid atop Pangborn bar after the Glacier Peak ashfall, then buried by loess. Clovis people came five and a half millennia after the early gigantic Missoula floods, two and a half millennia after the last small Missoula flood, and two millennia after the glacial Lake Columbia flood. People likely saw outburst flood(s) from glacial Lake Kootenay.
","language":"English","publisher":"Cambridge University Press","doi":"10.1016/j.yqres.2016.02.007","usgsCitation":"Waitt, R.B., 2016, Megafloods and Clovis cache at Wenatchee, Washington: Quaternary Research, v. 85, no. 3, p. 430-444, https://doi.org/10.1016/j.yqres.2016.02.007.","productDescription":"15 p.","startPage":"430","endPage":"444","ipdsId":"IP-022694","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":336869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","volume":"85","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-20","publicationStatus":"PW","scienceBaseUri":"58be8338e4b014cc3a3a99e1","contributors":{"authors":[{"text":"Waitt, Richard B. 0000-0002-6392-5604 waitt@usgs.gov","orcid":"https://orcid.org/0000-0002-6392-5604","contributorId":2343,"corporation":false,"usgs":true,"family":"Waitt","given":"Richard","email":"waitt@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":680593,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70178545,"text":"70178545 - 2016 - Assessing the role of seabirds in the ecology of influenza A viruses","interactions":[],"lastModifiedDate":"2018-07-15T18:33:20","indexId":"70178545","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":948,"text":"Avian Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the role of seabirds in the ecology of influenza A viruses","docAbstract":"Wild waterbirds, specifically waterfowl, gulls, and shorebirds, are recognized as the primordial reservoir of influenza A viruses (IAVs). However, the role of seabirds, an abundant, diverse, and globally distributed group of birds, in the perpetuation and transmission of IAVs is less clear. Here we summarize published and publicly available data for influenza viruses in seabirds, which for the purposes of this study are defined as birds that exhibit a largely or exclusively pelagic lifestyle and exclude waterfowl, gulls, and shorebirds, and we review this collective dataset to assess the role of seabirds in the influenza A ecology. Since 1961, more than 40,000 samples have been collected worldwide from the seabirds considered here and screened, using a variety of techniques, for evidence of active or past IAV infection. From these data, the overall prevalence of active infection has been estimated to be very low; however, serological data provide evidence that some seabird species are more frequently exposed to IAVs. Sequence data for viruses from seabirds are limited, except for murres (common murre, Uria aalge, and thick-billed murre, Uria lomvia; family Alcidae) for which there are full or partial genome sequences available for more than 80 viruses. Characterization of these viruses suggests that murres are infected with Group 1 hemagglutinin subtype viruses more frequently as compared to Group 2 and also indicates that these northern, circumpolar birds are frequently infected by intercontinental reassortant viruses. Greater temporal and spatial sampling and characterization of additional viruses are required to better understand the role of seabirds in global IAV dynamics.
","language":"English","publisher":"American Association of Avian Pathologists","doi":"10.1637/11135-050815-RegR","usgsCitation":"Lang, A.S., Lebarbenchon, C., Robertson, G.J., Ramey, A.M., Waldenstrom, J., and Wille, M., 2016, Assessing the role of seabirds in the ecology of influenza A viruses: Avian Diseases, v. 60, no. 1s, p. 378-386, https://doi.org/10.1637/11135-050815-RegR.","productDescription":"9 p.","startPage":"378","endPage":"386","ipdsId":"IP-065494","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":331238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1s","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"583d5034e4b0d9329c80c59f","contributors":{"authors":[{"text":"Lang, Andrew S.","contributorId":177028,"corporation":false,"usgs":false,"family":"Lang","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":654331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lebarbenchon, Camille","contributorId":140670,"corporation":false,"usgs":false,"family":"Lebarbenchon","given":"Camille","email":"","affiliations":[],"preferred":false,"id":654332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":654336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robertson, Gregory J.","contributorId":173883,"corporation":false,"usgs":false,"family":"Robertson","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":27311,"text":"Wildlife Research Division, Science and Technology Branch, Environment and Climate","active":true,"usgs":false}],"preferred":false,"id":654333,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waldenstrom, Jonas","contributorId":42891,"corporation":false,"usgs":true,"family":"Waldenstrom","given":"Jonas","email":"","affiliations":[],"preferred":false,"id":654334,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wille, Michelle","contributorId":173881,"corporation":false,"usgs":false,"family":"Wille","given":"Michelle","email":"","affiliations":[{"id":27309,"text":"Memorial University of Newfoundland, St. John’s, NL A1B 3X9, Canada","active":true,"usgs":false}],"preferred":false,"id":654335,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}