Droughts in dryland regions on all continents are expected to increase in severity and duration under future climate projections. In dryland regions, it is likely that minimum streamflow will decrease with some perennial streams shifting to intermittent flow under climate-driven changes in precipitation and runoff and increases in temperature. Decreasing base flow and shifting flow regimes from perennial to intermittent could have significant implications for stream-dependent biota, including riparian vegetation. In this study, we asked, how do riparian plant communities vary along wet-to-dry hydrologic gradients on small (first–third order) streams? We collected data on geomorphic, hydrologic, and plant community characteristics on 54 stream sites ranging in hydrology from intermittent to perennial flow across the Upper Colorado River Basin (284,898 km2). We found that plant communities varied along hydrologic gradients from high to low elevation between streams, and perennial to intermittent flow. We identified indicator species associated with different hydrologic conditions and suggest how plant communities may shift under warmer, drier conditions. Our results indicate that species richness and cover of total, perennial, wetland, and native plant groups will decrease while annual plants will increase under drying conditions. Understanding how plant communities respond to regional drivers such as hydroclimate requires broad-scale approaches such as sampling across whole river basins. With increasingly arid conditions in many regions of the globe, understanding plant community shifts is key to understanding the future of riparian ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1864","usgsCitation":"Reynolds, L., and Shafroth, P.B., 2017, Riparian plant composition along hydrologic gradients in a dryland river basin and implications for a warming climate: Ecohydrology, v. 10, no. 6, p. 1-13, https://doi.org/10.1002/eco.1864.","productDescription":"e1864; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-073730","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":346153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","volume":"10","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-31","publicationStatus":"PW","scienceBaseUri":"59ce0a25e4b05fe04cc020f3","contributors":{"authors":[{"text":"Reynolds, Lindsay 0000-0001-9973-9312 reynoldsl@usgs.gov","orcid":"https://orcid.org/0000-0001-9973-9312","contributorId":150076,"corporation":false,"usgs":true,"family":"Reynolds","given":"Lindsay","email":"reynoldsl@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":711408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":711407,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191176,"text":"70191176 - 2017 - Burrow dusting or oral vaccination prevents plague-associated prairie dog colony collapse","interactions":[],"lastModifiedDate":"2017-11-10T14:18:08","indexId":"70191176","displayToPublicDate":"2017-09-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1443,"text":"EcoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Burrow dusting or oral vaccination prevents plague-associated prairie dog colony collapse","docAbstract":"Plague impacts prairie dogs (Cynomys spp.), the endangered black-footed ferret (Mustela nigripes) and other sensitive wildlife species. We compared efficacy of prophylactic treatments (burrow dusting with deltamethrin or oral vaccination with recombinant “sylvatic plague vaccine” [RCN-F1/V307]) to placebo treatment in black-tailed prairie dog (C. ludovicianus) colonies. Between 2013 and 2015, we measured prairie dog apparent survival, burrow activity and flea abundance on triplicate plots (“blocks”) receiving dust, vaccine or placebo treatment. Epizootic plague affected all three blocks but emerged asynchronously. Dust plots had fewer fleas per burrow (P < 0.0001), and prairie dogs captured on dust plots had fewer fleas (P < 0.0001) than those on vaccine or placebo plots. Burrow activity and prairie dog density declined sharply in placebo plots when epizootic plague emerged. Patterns in corresponding dust and vaccine plots were less consistent and appeared strongly influenced by timing of treatment applications relative to plague emergence. Deltamethrin or oral vaccination enhanced apparent survival within two blocks. Applying insecticide or vaccine prior to epizootic emergence blunted effects of plague on prairie dog survival and abundance, thereby preventing colony collapse. Successful plague mitigation will likely entail strategic combined uses of burrow dusting and oral vaccination within large colonies or colony complexes.
","language":"English","publisher":"Springer","doi":"10.1007/s10393-017-1236-y","usgsCitation":"Tripp, D.W., Rocke, T.E., Runge, J.P., Abbott, R.C., and Miller, M.W., 2017, Burrow dusting or oral vaccination prevents plague-associated prairie dog colony collapse: EcoHealth, v. 14, no. 3, p. 451-462, https://doi.org/10.1007/s10393-017-1236-y.","productDescription":"12 p.","startPage":"451","endPage":"462","ipdsId":"IP-085018","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":461395,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10393-017-1236-y","text":"Publisher Index Page"},{"id":346158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Larimer County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.10517120361328,\n 40.868872344643655\n ],\n [\n -104.93385314941406,\n 40.868872344643655\n ],\n [\n -104.93385314941406,\n 40.97186275286114\n ],\n [\n -105.10517120361328,\n 40.97186275286114\n ],\n [\n -105.10517120361328,\n 40.868872344643655\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-22","publicationStatus":"PW","scienceBaseUri":"59ce0a24e4b05fe04cc020eb","contributors":{"authors":[{"text":"Tripp, Daniel W.","contributorId":17910,"corporation":false,"usgs":false,"family":"Tripp","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":13449,"text":"Colorado Division of Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":711430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":711429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runge, Jonathan P.","contributorId":196756,"corporation":false,"usgs":false,"family":"Runge","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":711431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abbott, Rachel C. 0000-0003-4820-9295 rabbott@usgs.gov","orcid":"https://orcid.org/0000-0003-4820-9295","contributorId":1183,"corporation":false,"usgs":true,"family":"Abbott","given":"Rachel","email":"rabbott@usgs.gov","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":711432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Michael W.","contributorId":140308,"corporation":false,"usgs":false,"family":"Miller","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":13449,"text":"Colorado Division of Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":711433,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191169,"text":"70191169 - 2017 - Minimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection","interactions":[],"lastModifiedDate":"2017-09-28T11:54:17","indexId":"70191169","displayToPublicDate":"2017-09-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Minimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection","docAbstract":"Evaluating the conditions where a species can persist is an important question in ecology both to understand tolerances of organisms and to predict distributions across landscapes. Presence data combined with background or pseudo-absence locations are commonly used with species distribution modeling to develop these relationships. However, there is not a standard method to generate background or pseudo-absence locations, and method choice affects model outcomes. We evaluated combinations of both model algorithms (simple and complex generalized linear models, multivariate adaptive regression splines, Maxent, boosted regression trees, and random forest) and background methods (random, minimum convex polygon, and continuous and binary kernel density estimator (KDE)) to assess the sensitivity of model outcomes to choices made. We evaluated six questions related to model results, including five beyond the common comparison of model accuracy assessment metrics (biological interpretability of response curves, cross-validation robustness, independent data accuracy and robustness, and prediction consistency). For our case study with cheatgrass in the western US, random forest was least sensitive to background choice and the binary KDE method was least sensitive to model algorithm choice. While this outcome may not hold for other locations or species, the methods we used can be implemented to help determine appropriate methodologies for particular research questions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2017.08.017","usgsCitation":"Jarnevich, C.S., Talbert, M., Morisette, J.T., Aldridge, C.L., Brown, C., Kumar, S., Manier, D.J., Talbert, C., and Holcombe, T.R., 2017, Minimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection: Ecological Modelling, v. 363, p. 48-56, https://doi.org/10.1016/j.ecolmodel.2017.08.017.","productDescription":"9 p.","startPage":"48","endPage":"56","ipdsId":"IP-073503","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":346154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.8486328125,\n 31.615965936476076\n ],\n [\n -101.90917968749999,\n 31.615965936476076\n ],\n [\n -101.90917968749999,\n 49.06666839558117\n ],\n [\n -124.8486328125,\n 49.06666839558117\n ],\n [\n -124.8486328125,\n 31.615965936476076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"363","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ce0a26e4b05fe04cc020f6","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":711394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Talbert, Marian 0000-0003-0588-0265 mtalbert@usgs.gov","orcid":"https://orcid.org/0000-0003-0588-0265","contributorId":196740,"corporation":false,"usgs":true,"family":"Talbert","given":"Marian","email":"mtalbert@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":711395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":711396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":711397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Cynthia 0000-0001-8486-7119","orcid":"https://orcid.org/0000-0001-8486-7119","contributorId":196741,"corporation":false,"usgs":false,"family":"Brown","given":"Cynthia","affiliations":[],"preferred":false,"id":711398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kumar, Sunil","contributorId":195493,"corporation":false,"usgs":false,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":711399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Manier, Daniel J. 0000-0002-1105-1327 manierd@usgs.gov","orcid":"https://orcid.org/0000-0002-1105-1327","contributorId":127553,"corporation":false,"usgs":true,"family":"Manier","given":"Daniel","email":"manierd@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":711400,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Talbert, Colin 0000-0002-9505-1876 talbertc@usgs.gov","orcid":"https://orcid.org/0000-0002-9505-1876","contributorId":181913,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":711401,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Holcombe, Tracy R. holcombet@usgs.gov","contributorId":3694,"corporation":false,"usgs":true,"family":"Holcombe","given":"Tracy","email":"holcombet@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":711402,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70190590,"text":"sir20175098 - 2017 - Hydrogeology and simulated groundwater flow and availability in the North Fork Red River aquifer, southwest Oklahoma, 1980–2013","interactions":[],"lastModifiedDate":"2017-09-28T14:29:06","indexId":"sir20175098","displayToPublicDate":"2017-09-28T00:00:00","publicationYear":"2017","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":"2017-5098","displayTitle":"Hydrogeology and simulated groundwater flow and availability in the North Fork Red River aquifer, southwest Oklahoma,On September 8, 1981, the Oklahoma Water Resources Board established regulatory limits on the maximum annual yield of groundwater (343,042 acre-feet per year) and equal-proportionate-share (EPS) pumping rate (1.0 acre-foot per acre per year) for the North Fork Red River aquifer. The maximum annual yield and EPS were based on a hydrologic investigation that used a numerical groundwater-flow model to evaluate the effects of potential groundwater withdrawals on groundwater availability in the North Fork Red River aquifer. The Oklahoma Water Resources Board is statutorily required (every 20 years) to update the hydrologic investigation on which the maximum annual yield and EPS were based. Because 20 years have elapsed since the final order was issued, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, conducted an updated hydrologic investigation and evaluated the effects of potential groundwater withdrawals on groundwater flow and availability in the North Fork Red River aquifer in Oklahoma. This report describes a hydrologic investigation of the North Fork Red River aquifer that includes an updated summary of the aquifer hydrogeology. As part of this investigation, groundwater flow and availability were simulated by using a numerical groundwater-flow model.
The North Fork Red River aquifer in Beckham, Greer, Jackson, Kiowa, and Roger Mills Counties in Oklahoma is composed of about 777 square miles (497,582 acres) of alluvium and terrace deposits along the North Fork Red River and tributaries, including Sweetwater Creek, Elk Creek, Otter Creek, and Elm Fork Red River. The North Fork Red River is the primary source of surface-water inflow to Lake Altus, which overlies the North Fork Red River aquifer. Lake Altus is a U.S. Bureau of Reclamation reservoir with the primary purpose of supplying irrigation water to the Lugert-Altus Irrigation District.
A hydrogeologic framework was developed for the North Fork Red River aquifer and included a definition of the aquifer extent and potentiometric surface, as well as a description of the textural and hydraulic properties of aquifer materials. The hydrogeologic framework was used in the construction of a numerical groundwater-flow model of the North Fork Red River aquifer described in this report. A conceptual model of aquifer inflows and outflows was developed for the North Fork Red River aquifer to constrain the construction and calibration of a numerical groundwater-flow model that reasonably represented the groundwater-flow system. The conceptual-model water budget estimated mean annual inflows to and outflows from the North Fork Red River aquifer for the period 1980–2013 and included a sub-accounting of mean annual inflows and outflows for the portions of the aquifer that were upgradient and downgradient from Lake Altus. The numerical groundwater-flow model simulated the period 1980–2013 and was calibrated to water-table-altitude observations at selected wells, monthly base flow at selected streamgages, net streambed seepage as estimated for the conceptual model, and Lake Altus stage.
Groundwater-availability scenarios were performed by using the calibrated numerical groundwater-flow model to (1) estimate the EPS pumping rate that guarantees a minimum 20-, 40-, and 50-year life of the aquifer, (2) quantify the potential effects of projected well withdrawals on groundwater storage over a 50-year period, and (3) simulate the potential effects of a hypothetical (10-year) drought on base flow and groundwater storage. The results of the groundwater-availability scenarios could be used by the Oklahoma Water Resources Board to reevaluate the maximum annual yield of groundwater from the North Fork Red River aquifer.
EPS scenarios for the North Fork Red River aquifer were run for periods of 20, 40, and 50 years. The 20-, 40-, and 50-year EPS pumping rates under normal recharge conditions were 0.59, 0.52, and 0.52 acre-foot per acre per year, respectively. Given the 497,582-acre aquifer area, these rates correspond to annual yields of about 294,000, 259,000, and 259,000 acre-feet per year, respectively. Groundwater storage at the end of the 20-year EPS scenario was about 951,000 acre-feet, or about 1,317,000 acre-feet (58 percent) less than the starting EPS scenario storage. This decrease in storage was equivalent to a mean water-level decline of about 22 feet. Most areas of the active alluvium near the North Fork Red River, Elk Creek, and Elm Fork Red River remained partially saturated through the end of the EPS scenario because of streambed seepage. Lake Altus storage was reduced to zero after 6–7 years of EPS pumping in each scenario.
Projected 50-year pumping scenarios were used to simulate the effects of selected well withdrawal rates on groundwater storage of the North Fork Red River aquifer and base flows in the North Fork Red River upstream from Lake Altus. The effects of well withdrawals were evaluated by comparing changes in groundwater storage and base flow between four 50-year scenarios using (1) no groundwater pumping, (2) mean pumping rates for the study period (1980–2013), (3) 2013 pumping rates, and (4) increasing demand pumping rates. The increasing demand pumping rates assumed a 20.4-percent increase in pumping over 50 years based on 2010–60 demand projections for southwest Oklahoma.
Groundwater storage after 50 years with no pumping was about 2,606,000 acre-feet, or 137,000 acre-feet (5.5 percent) greater than the initial groundwater storage; this groundwater storage increase is equivalent to a mean water-level increase of 2.3 feet. Groundwater storage after 50 years with the mean pumping rate for the study period (1980–2013) was about 2,476,000 acre-feet, or about 7,000 acre-feet (0.3 percent) greater than the initial groundwater storage; this groundwater storage increase is equivalent to a mean water-level increase of 0.1 foot. Groundwater storage at the end of the 50-year period with 2013 pumping rates was about 2,398,000 acre-feet, or about 70,000 acre-feet (2.8 percent) less than the initial storage; this groundwater storage decrease is equivalent to a mean water-level decline of 1.2 feet. Groundwater storage at the end of the 50-year period with increasing demand pumping rates was about 2,361,000 acre-feet, or about 107,000 acre-feet (4.3 percent) less than the initial storage; this groundwater storage decrease is equivalent to a mean water-level decline of 1.8 feet. Mean annual base flow simulated at the Carter streamgage (07301500) on North Fork Red River increased by about 4,000 acre-feet (10 percent) after 50 years with no pumping and decreased by about 5,400 acre-feet (13 percent) after 50 years with increasing demand pumping rates. Mean annual base flow simulated at the North Fork Red River inflow to Lake Altus increased by about 7,400 acre-feet (15 percent) after 50 years with no pumping and decreased by about 5,800 acre-feet (12 percent) after 50 years with increasing demand pumping rates.
A hypothetical 10-year drought scenario was used to simulate the effects of a prolonged period of reduced recharge on groundwater storage and Lake Altus stage and storage. Drought effects were quantified by comparing the results of the drought scenario to those of the calibrated numerical model (no drought). To simulate the hypothetical drought, recharge in the calibrated numerical model was reduced by 50 percent during the simulated drought period (1984–1993). Groundwater storage at the end of the drought period was about 2,271,000 acre-feet, or about 426,000 acre-feet (15.8 percent) less than the groundwater storage of the calibrated numerical model. This decrease in groundwater storage is equivalent to a mean water-table-altitude decline of 7.1 feet. At the end of the 10-year hypothetical drought period, base flows at the Sweetwater (07301420), Carter (07301500), Headrick (07305000), and Snyder (07307010) streamgages had decreased by about 37, 61, 44, and 45 percent, respectively. The minimum Lake Altus storage simulated during the drought period was 403 acre-feet, which was a decline of 92 percent from the nondrought storage. Reduced base flows in the North Fork Red River were the primary cause of Lake Altus storage declines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175098","collaboration":"Prepared in cooperation with the Oklahoma Water Resources Board","usgsCitation":"Smith, S.J., Ellis, J.H., Wagner, D.L., and Peterson, S.M., 2017, Hydrogeology and simulated groundwater flow and availability in the North Fork Red River aquifer, southwest Oklahoma, 1980–2013: U.S. Geological Survey Scientific Investigations Report 2017–5098, 107 p., https://doi.org/10.3133/sir20175098.","productDescription":"Report: xii, 107 p.; Data Release","numberOfPages":"124","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-071702","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":346139,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5098/sir20175098.pdf","text":"Report","size":"29.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5098"},{"id":346138,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5098/coverthb.jpg"},{"id":346140,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JQ0ZXH","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model used in simulation of groundwater flow and availability in the North Fork Red River aquifer, southwest Oklahoma, 1980–2013"}],"country":"United States","state":"Oklahoma","otherGeospatial":"North Fork Red River Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100,\n 34.5\n ],\n [\n -98.8,\n 34.5\n ],\n [\n -98.8,\n 35.45\n ],\n [\n -100,\n 35.45\n ],\n [\n -100,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma Water Science Center
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202 NW 66th
Oklahoma City, OK 73116
The Alaska Volcano Observatory (AVO) responded to eruptions, volcanic unrest or suspected unrest, and seismic events at 14 volcanic centers in Alaska during 2015. The most notable volcanic activity consisted of continuing intermittent ash eruptions from Cleveland and Shishaldin volcanoes in the Aleutian Islands. Two eruptive episodes, at Veniaminof and Pavlof, on the Alaska Peninsula ended in 2015. During 2015, AVO re-established the seismograph network at Aniakchak, installed six new broadband seismometers throughout the Aleutian Islands, and added a Multiple component Gas Analyzer System (MultiGAS) station on Augustine.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175104","collaboration":"Prepared in collaboration with University of Alaska Fairbanks Geophysical Institute and the Alaska Division of Geological and Geophysical Surveys","usgsCitation":"Dixon, J.P., Cameron, C.E., Iezzi, A.M., and Wallace, Kristi, 2017, 2015 Volcanic activity in Alaska—Summary of events and response of the Alaska Volcano Observatory: U.S. Geological Survey Scientific Investigations Report 2017-5104, 61 p., https://doi.org/10.3133/sir20175104.","productDescription":"vi, 61 p.","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-082299","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":346181,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5104/coverthb.jpg"},{"id":346182,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5104/sir20175104.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5104"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -182.724609375,\n 50.98609893339354\n ],\n [\n -148.798828125,\n 50.98609893339354\n ],\n [\n -148.798828125,\n 61.66902436927201\n ],\n [\n -182.724609375,\n 61.66902436927201\n ],\n [\n -182.724609375,\n 50.98609893339354\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Volcano Science Center
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4230 University Drive
Anchorage, Alaska 99508
Detecting populations of rare or cryptic species is essential for their conservation. For species like giant gartersnakes (Thamnophis gigas), conventional survey methods can be expensive and inefficient. These sampling difficulties might be overcome by modern techniques that detect deoxyribonucleic acid (DNA) shed by organisms into the environment (eDNA). We evaluated the efficacy of detecting giant gartersnake eDNA in water samples from the laboratory and at locations with known giant gartersnake populations in the Sacramento Valley of California, and failed to detect giant gartersnake DNA in most laboratory and all field samples. Aspects of giant gartersnake biology—such as highly keratinized skin and spending extensive time in the terrestrial environment, as well as hot, sunny, and turbid conditions in wetlands and canals of the Sacramento Valley—likely contributed to low detection probabilities. Although detection of eDNA shows promise under many conditions, further development is needed before sampling for eDNA is a viable option for detecting giant gartersnake populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171123","collaboration":"Prepared in cooperation with the Central Valley Project—Bureau of Reclamation and U.S. Fish and Wildlife Service","usgsCitation":"Halstead, B.J., Wood, D.A, Bowen, Lizabeth, Waters, Shannon, Vandergast, A.G., Ersan, J.S.M., Skalos, S.M., and Casazza, M.L., 2017, An evaluation of the efficacy of using environmental DNA (eDNA) to detect giant gartersnakes (Thamnophis gigas): U.S. Geological Survey Open-File Report 2017-1123, 41 p., https://doi.org/10.3133/ofr20171123.","productDescription":"vi, 41 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-086792","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":346165,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1123/ofr20171123.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1123"},{"id":346180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1123/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Colusa National Wildlife Refuge, Natomas Basin","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The U.S. Coal Resources and Reserves Assessment Project, as part of the U.S. Geological Survey (USGS) Energy Resources Program, conducts systematic, geology-based, regional assessments of significant coal beds in major coal basins in the United States. These assessments detail the quantity, quality, location, and economic potential of the Nation’s remaining coal resources and reserves and provide objective scientific information that assists in the formulation of energy strategies, environmental policies, land-use management practices, and economic projections.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173067","usgsCitation":"Shaffer, B.N., 2017, Assessing U.S. coal resources and reserves: U.S. Geological Survey Fact Sheet 2017–3067, 6 p., https://doi.org/10.3133/fs20173067.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-085988","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":346000,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3067/fs20173067.pdf","text":"Report","size":"11.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3067"},{"id":345999,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3067/coverthb.jpg"}],"country":"United 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\"}}]}\n","contact":"Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The U.S. Geological Survey (USGS) recently conducted an assessment of the undiscovered, technically recoverable oil and gas potential of Tertiary strata underlying the onshore areas and State waters of the northern Gulf of Mexico coastal region. The assessment was based on a number of geologic elements including an evaluation of hydrocarbon source rocks, suitable reservoir rocks, and hydrocarbon traps in an Upper Jurassic-Cretaceous-Tertiary Composite Total Petroleum System defined for the region by the USGS. Five conventional assessment units (AUs) were defined for the Midway (Paleocene) and Wilcox (Paleocene-Eocene) Groups, and the Carrizo Sand of the Claiborne Group (Eocene) interval including: (1) the Wilcox Stable Shelf Oil and Gas AU; (2) the Wilcox Expanded Fault Zone Gas and Oil AU; (3) the Wilcox-Lobo Slide Block Gas AU; (4) the Wilcox Slope and Basin Floor Gas AU; and (5) the Wilcox Mississippi Embayment AU (not quantitatively assessed).
The USGS assessment of undiscovered oil and gas resources for the Midway-Wilcox-Carrizo interval resulted in estimated mean values of 110 million barrels of oil (MMBO), 36.9 trillion cubic feet of gas (TCFG), and 639 million barrels of natural gas liquids (MMBNGL) in the four assessed units. The undiscovered oil resources are almost evenly divided between fluvial-deltaic sandstone reservoirs within the Wilcox Stable Shelf (54 MMBO) AU and deltaic sandstone reservoirs of the Wilcox Expanded Fault Zone (52 MMBO) AU. Greater than 70 percent of the undiscovered gas and 66 percent of the natural gas liquids (NGL) are estimated to be in deep (13,000 to 30,000 feet), untested distal deltaic and slope sandstone reservoirs within the Wilcox Slope and Basin Floor Gas AU.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171111","usgsCitation":"Warwick, P.D., 2017, Geologic assessment of undiscovered conventional oil and gas resources in the lower Paleogene Midway and Wilcox Groups, and the Carrizo Sand of the Claiborne Group, of the northern Gulf Coast region: U.S. Geological Survey Open-File Report 2017–1111, 67 p., https://doi.org/10.3133/ofr20171111.","productDescription":"Report: vi, 60 p.; Appendixes 1-4","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063993","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":410834,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20171167","text":"Open-File Report 2017–1167","linkHelpText":"- Geologic Assessment of Undiscovered Gas Resources in Cretaceous–Tertiary Coal Beds of the U.S. Gulf of Mexico Coastal Plain"},{"id":346065,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111_appendix2.pdf","text":"Appendix 2","size":"490 KB","linkHelpText":"- Input Data Form for the Wilcox Expanded Fault Zone Gas and Oil Assessment Unit (50470117)"},{"id":346063,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1111"},{"id":346062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1111/coverthb.jpg"},{"id":346066,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111_appendix3.pdf","text":"Appendix 3","size":"510 KB","linkHelpText":"- Input Data Form for the Wilcox-Lobo Slide Block Gas Assessment Unit (50470119)"},{"id":346067,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111_appendix4.pdf","text":"Appendix 4","size":"396 KB","linkHelpText":"- Input Data Form for the Wilcox Slope and Basin Floor Gas Assessment Unit (50470118)"},{"id":346064,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111_appendix1.pdf","text":"Appendix 1","size":"389 KB","linkHelpText":"- Input Data Form for the Wilcox Stable Shelf Oil and Gas Assessment Unit (50470116)"}],"country":"United States","otherGeospatial":"Gulf of Mexico","contact":"Director, Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956
12201 Sunrise Valley Drive
Reston, VA 20192
http://energy.usgs.gov/
Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Program’s Priority Basin Project assesses the quality of groundwater resources used for drinking water supply and increases public access to groundwater-quality information. In the Yuba River and Bear River Watersheds of the Sierra Nevada, many rural households rely on private wells for their drinking water supplies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171115","collaboration":"Prepared in collaboration with California State Water Resources Control Board","usgsCitation":"Fram, M.S., Jasper, Monica, and Taylor, K.A., 2017, Groundwater Quality in the Yuba River and Bear River watersheds, Sierra Nevada, California: U.S. Geological Survey Open-File Report 2017–1115, 4 p., https://doi.org/10.3133/ofr20171115.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-087403","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":438208,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73F4MS9","text":"USGS data release","linkHelpText":"Groundwater-Quality Data in the Yuba and Bear Watersheds Shallow Aquifer Study Unit, 2015-2016: Results from the California GAMA Priority Basin Project"},{"id":346137,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1115/ofr20171115.pdf","text":"Report","size":"3.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1115"},{"id":346136,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1115/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bear River Watershed, Yuba River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 39\n ],\n [\n -120.4167,\n 39\n ],\n [\n -120.4167,\n 39.75\n ],\n [\n -121.5,\n 39.75\n ],\n [\n -121.5,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"California Water Science Center
California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Many approaches have been developed for measuring or estimating actual evapotranspiration (ETa), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ETa. Several remote sensing methods can be used to estimate ETa at the high spatial resolution of agricultural fields and the large extent of river basins. More complex remote sensing methods apply an analytical approach to ETa estimation using physically based models of varied complexity that require a combination of ground-based and remote sensing data, and are grounded in the theory behind the surface energy balance model. This report, funded through cooperation with the International Joint Commission, provides an overview of selected remote sensing methods used for estimating water consumed through ETa and focuses on Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Operational Simplified Surface Energy Balance (SSEBop), two energy balance models for estimating ETa that are currently applied successfully in the United States. The METRIC model can produce maps of ETa at high spatial resolution (30 meters using Landsat data) for specific areas smaller than several hundred square kilometers in extent, an improvement in practice over methods used more generally at larger scales. Many studies validating METRIC estimates of ETa against measurements from lysimeters have shown model accuracies on daily to seasonal time scales ranging from 85 to 95 percent. The METRIC model is accurate, but the greater complexity of METRIC results in greater data requirements, and the internalized calibration of METRIC leads to greater skill required for implementation. In contrast, SSEBop is a simpler model, having reduced data requirements and greater ease of implementation without a substantial loss of accuracy in estimating ETa. The SSEBop model has been used to produce maps of ETa over very large extents (the conterminous United States) using lower spatial resolution (1 kilometer) Moderate Resolution Imaging Spectroradiometer (MODIS) data. Model accuracies ranging from 80 to 95 percent on daily to annual time scales have been shown in numerous studies that validated ETa estimates from SSEBop against eddy covariance measurements. The METRIC and SSEBop models can incorporate low and high spatial resolution data from MODIS and Landsat, but the high spatiotemporal resolution of ETa estimates using Landsat data over large extents takes immense computing power. Cloud computing is providing an opportunity for processing an increasing amount of geospatial “big data” in a decreasing period of time. For example, Google Earth EngineTM has been used to implement METRIC with automated calibration for regional-scale estimates of ETa using Landsat data. The U.S. Geological Survey also is using Google Earth EngineTM to implement SSEBop for estimating ETa in the United States at a continental scale using Landsat data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175087","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"McShane, R.R., Driscoll, K.P., and Sando, Roy, 2017, A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents: U.S. Geological Survey Scientific Investigations Report 2017–5087, 19 p., https://doi.org/10.3133/sir20175087.","productDescription":"vi, 19 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-083112","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":346073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5087/coverthb.jpg"},{"id":346074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5087/sir20175087.pdf","text":"Report","size":"678 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5087"}],"contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
The Laurentian Great Lakes contain one fifth of the world’s surface freshwater and have been impacted by human activity since the Industrial Revolution. In addition to legacy contaminants, nitrification and invasive species, this aquatic ecosystem is also the recipient of Contaminants of Emerging Concern (CECs) with poorly understood biological consequences. In the current study, we documented the presence, concentrations, and biological effects of CECs across 27 field sites in six Great Lakes tributaries by examining over 2250 resident and caged sunfish (Lepomis ssp.) for a variety of morphological and physiological endpoints and related these results to CEC occurrence. CEC were ubiquitous across studies sites and their presence and concentrations in water and sediment were highest in effluent dominated rivers and downstream of municipal wastewater treatment plant discharges. However, even putative upstream reference sites were not free of CEC presence and fish at these sites exhibited biological effects consistent with CEC exposure. Only the Fox River exhibited consistent adverse biological effects, including increased relative liver size, greater prominence of hepatocyte vacuoles and increased plasma glucose concentrations. Canonical Redundancy Analysis revealed consistent patterns of biological consequences of CEC exposure across all six tributaries. Increasing plasma glucose concentrations, likely as a result of pollutant-induced metabolic stress, were associated with increased relative liver size and greater prominence of hepatocyte vacuoles. These indicators of pollutant exposure were inversely correlated with indicators of reproductive potential including smaller gonad size and less mature gametes. The current study highlights the need for greater integration of chemical and biological studies and suggests that CECs in the Laurentian Great Lakes Basin may adversely affect the reproductive potential of exposed fish populations.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0184725","usgsCitation":"Thomas, L., Jorgenson, Z.G., Brigham, M.E., Choy, S.J., Moore, J.N., Banda, J.A., Gefell, D., Minarik, T.A., and Schoenfuss, H.L., 2017, Contaminants of emerging concern in tributaries to the Laurentian Great Lakes: II. Biological consequences of exposure: PLoS ONE, v. 12, no. 9, Article e0184725; 36 p., https://doi.org/10.1371/journal.pone.0184725.","productDescription":"Article e0184725; 36 p.","ipdsId":"IP-087970","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":469499,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0184725","text":"Publisher Index Page"},{"id":348862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Great Lakes","volume":"12","issue":"9","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-27","publicationStatus":"PW","scienceBaseUri":"5a60fb44e4b06e28e9c22ea3","contributors":{"authors":[{"text":"Thomas, Linnea M.","contributorId":146311,"corporation":false,"usgs":false,"family":"Thomas","given":"Linnea M.","affiliations":[],"preferred":false,"id":721922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgenson, Zachary G.","contributorId":69476,"corporation":false,"usgs":false,"family":"Jorgenson","given":"Zachary","email":"","middleInitial":"G.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":721923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":721921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Choy, Steven J.","contributorId":138668,"corporation":false,"usgs":false,"family":"Choy","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":721924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Jeremy N.","contributorId":138669,"corporation":false,"usgs":false,"family":"Moore","given":"Jeremy","email":"","middleInitial":"N.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":721925,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Banda, Jo A.","contributorId":196761,"corporation":false,"usgs":false,"family":"Banda","given":"Jo","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":721926,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gefell, D.J.","contributorId":200326,"corporation":false,"usgs":false,"family":"Gefell","given":"D.J.","affiliations":[],"preferred":false,"id":721927,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Minarik, Thomas A.","contributorId":139816,"corporation":false,"usgs":false,"family":"Minarik","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":13283,"text":"Metropolitan Water Reclamation District of Greater Chicago","active":true,"usgs":false}],"preferred":false,"id":721928,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":721929,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70190994,"text":"fs20173074 - 2017 - USGS microbiome research","interactions":[],"lastModifiedDate":"2017-10-05T08:15:56","indexId":"fs20173074","displayToPublicDate":"2017-09-26T11:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3074","title":"USGS microbiome research","docAbstract":"Microbiomes are the communities of microorganisms (for example, bacteria, viruses, and fungi) that live on, in, and around people, plants, animals, soil, water, and the atmosphere. Microbiomes are active in the functioning of diverse ecosystems, for instance, by influencing water quality, nutrient acquisition and stress tolerance in plants, and stability of soil and aquatic environments. Microbiome research conducted by the U.S. Geological Survey spans many of our mission areas. Key research areas include water quality, understanding climate effects on soil and permafrost, ecosystem and wildlife health, invasive species, contaminated environments to improve bioremediation, and enhancing energy production. Microbiome research will fundamentally strengthen the ability to address the global challenges of maintaining clean water, ensuring adequate food supply, meeting energy needs, and preserving human and ecosystem health.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20173074","usgsCitation":"Kellogg, C.A., and Hopkins, M.C., 2017, USGS microbiome research: U.S. Geological Survey Fact Sheet 2017–3074, 4 p., https://doi.org/10.3133/fs20173074.","productDescription":"4 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087448","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":346030,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3074/coverthb.jpg"},{"id":346031,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3074/fs20173074l.pdf","text":"Report","size":"2.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3074","linkHelpText":"- Low resolution"},{"id":346032,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3074/fs20173074h.pdf","text":"Report","size":"18.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3074","linkHelpText":"- High resolution"}],"contact":"Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
https://answers.usgs.gov/
Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, during October 2013 through September 2014 (water year 2014) and October 2014 through September 2015 (water year 2015). Major findings for this period include:
Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Dauphin Island is a 26-km-long barrier island located southwest of Mobile Bay, Alabama, in the north-central Gulf of Mexico. The island contains sandy beaches, dunes, maritime forests, freshwater ponds and intertidal wetlands, providing habitat for many endangered and threatened species. Dauphin Island also provides protection for and maintains estuarine conditions within Mississippi Sound, supporting oyster habitat and seagrasses. Wetland marshes along the Alabama mainland are protected by the island from wave-induced erosion during storms approaching from the Gulf of Mexico. Over the years, the island has been eroded by storms, most recently by Hurricane Ivan (2004) and Hurricane Katrina (2005) (Ivan/Katrina), which breached the island along its narrowest extent and caused damage to infrastructure. Along with storms producing significant episodic change, long-term beach erosion has exposed numerous pine tree stumps in the shoreface. The stumps are remnants of past maritime forests and reflect the consistent landward retreat of the island.
Island change has prompted the State of Alabama to evaluate restoration alternatives to increase island resilience and sustainability by protecting and preserving the natural habitat, and by understanding the processes that influence shoreline change. Under a grant from the National Fish and Wildlife Foundation, restoration alternatives are being developed that will allow the State to make decisions on engineering and ecological restoration designs based on scientific analysis of likely outcomes and tradeoffs between impacts to stakeholder interests. Science-based assessment of the coastal zone requires accurate and up-to-date baseline data to provide a valid image of present conditions and to support modeling of coastal processes. Bathymetric elevation measurements are essential to this requirement. In August 2015, the U.S. Army Corps of Engineers and the U.S. Geological Survey conducted single beam and multibeam bathymetric surveys around Dauphin Island using a variety of shallow draft vessels and equipment. More than 95 square kilometers of seafloor was imaged. The data were integrated into a seamless digital elevation model to provide a high-resolution bathymetric map of the seafloor extending 9.5 kilometers seaward from the island’s eastern end and approximately 2 km along the rest of the island on the gulf and sound sides. Water depths range from 0.3 to 15.0 meters (m), with depths greater than 10.0 m constrained to the Mobile ship channel on the extreme eastern flank of the coverage.
To measure seafloor change, two periods of historic hydrographic survey data were acquired from the National Oceanic and Atmospheric Administration National Centers for Environmental Information data archive. The two timeframes (1987–1988 and 2005–2007) were selected for their completeness of spatial coverage and because they encompass a period of significant storm impacts to the island. These timeframes were compared to each other and with the 2015 dataset to monitor elevation gain (sediment accretion) and elevation loss (sediment erosion) over time. Sediment dynamics is by far the most significant driver of nearshore elevation change in this area. The Mississippi-Alabama inner shelf is a passive margin, and other influences on elevation change (for example, tectonic adjustment, Holocene subsidence, and eustatic sea-level rise) are neither significant nor variable enough over this time period to have an imprint.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171112","usgsCitation":"Flocks, J.G., DeWitt, N.T., and Stalk, C.A., 2018, Analysis of seafloor change around Dauphin Island, Alabama, 1987–2015 (ver. 1.1, February 2018):St. Petersburg Science Center
U.S. Geological Survey
600 4th Street, South
St Petersburg, FL 33701
In February 2017, the Grand River Dam Authority filed to relicense the Pensacola Hydroelectric Project with the Federal Energy Regulatory Commission. The predominant feature of the Pensacola Hydroelectric Project is Pensacola Dam, which impounds Grand Lake O’ the Cherokees (locally called Grand Lake) in northeastern Oklahoma. Identification of information gaps and assessment of project effects on stakeholders are central aspects of the Federal Energy Regulatory Commission relicensing process. Some upstream stakeholders have expressed concerns about the dynamics of sedimentation and flood flows in the transition zone between major rivers and Grand Lake O’ the Cherokees. To relicense the Pensacola Hydroelectric Project with the Federal Energy Regulatory Commission, the hydraulic models for these rivers require high-resolution bathymetric data along the river channels. In support of the Federal Energy Regulatory Commission relicensing process, the U.S. Geological Survey, in cooperation with the Grand River Dam Authority, performed bathymetric surveys of (1) the Neosho River from the Oklahoma border to the U.S. Highway 60 bridge at Twin Bridges State Park, (2) the Spring River from the Oklahoma border to the U.S. Highway 60 bridge at Twin Bridges State Park, and (3) the Elk River from Noel, Missouri, to the Oklahoma State Highway 10 bridge near Grove, Oklahoma. The Neosho River and Spring River bathymetric surveys were performed from October 26 to December 14, 2016; the Elk River bathymetric survey was performed from February 27 to March 21, 2017. Only areas inundated during those periods were surveyed.
The bathymetric surveys covered a total distance of about 76 river miles and a total area of about 5 square miles. Greater than 1.4 million bathymetric-survey data points were used in the computation and interpolation of bathymetric-survey digital elevation models and derived contours at 1-foot (ft) intervals. The minimum bathymetric-survey elevation of the Neosho River was 709.18 ft above North American Vertical Datum of 1988, which corresponds to a maximum depth of 34.22 ft. The minimum bathymetric-survey elevation of the Spring River was 714.18 ft above North American Vertical Datum of 1988, which corresponds to a maximum depth of 29.22 ft. The minimum bathymetric-survey elevation of the Elk River was 715.62 ft above North American Vertical Datum of 1988, which corresponds to a maximum depth of 27.78 ft.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175101","collaboration":"Prepared in cooperation with the Grand River Dam Authority","usgsCitation":"Hunter, S.L., Ashworth, C.E., and Smith, S.J., 2017, Bathymetric surveys of the Neosho River, Spring River, and Elk River, northeastern Oklahoma and southwestern Missouri, 2016–17 (ver. 1.1, October 2017): U.S. Geological Survey Scientific Investigations Report 2017–5101, 59 p., https://doi.org/10.3133/sir20175101.","productDescription":"Report: 59 p.; Data Release","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087073","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":346091,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71N7ZMS","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Bathymetric surveys of the Neosho River, Spring River, and Elk River, northeastern Oklahoma and southwestern Missouri, 2016–17"},{"id":348038,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5101/coverthb2.jpg"},{"id":348039,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5101/sir20175101_ver1.1.pdf","text":"Report","size":"75.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5101"},{"id":348040,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5101/versionHist.txt","text":"Version History","size":"1.68 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"}],"country":"United States","state":"Missouri, Oklahoma","otherGeospatial":"Neosho River, Spring River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.1,\n 36.8\n ],\n [\n -94.5667,\n 36.8\n ],\n [\n -94.5667,\n 37.0333\n ],\n [\n -95.1,\n 37.0333\n ],\n [\n -95.1,\n 36.8\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.7,\n 36.6667\n ],\n [\n -94.4667,\n 36.6667\n ],\n [\n -94.4667,\n 36.5333\n ],\n [\n -94.7,\n 36.5333\n ],\n [\n -94.7,\n 36.6667\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted September 26, 2017; Version 1.1: October 25, 2017","contact":"Director, Oklahoma Water Science Center
U.S. Geological Survey
202 NW 66th, Bldg 7
Oklahoma City, OK 73116
Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near 13 bridges at 8 highway crossings of the Missouri and Mississippi Rivers in the greater St. Louis, Missouri, area from May 23 to 27, 2016. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches ranging from 1,640 to 1,970 feet longitudinally and extending laterally across the active channel from bank to bank during low to moderate flood flow conditions. These bathymetric surveys indicate the channel conditions at the time of the surveys and provide characteristics of scour holes that may be useful in the development of predictive guidelines or equations for scour holes. These data also may be useful to the Missouri Department of Transportation as a low to moderate flood flow comparison to help assess the bridges for stability and integrity issues with respect to bridge scour during floods.
Bathymetric data were collected around every pier that was in water, except those at the edge of water, and scour holes were observed at most surveyed piers. The observed scour holes at the surveyed bridges were examined with respect to shape and depth.
The frontal slope values determined for scour holes observed in the current (2016) study generally are similar to recommended values in the literature and to values determined for scour holes in previous bathymetric surveys. Several of the structures had piers that were skewed to primary approach flow, as indicated by the scour hole being longer on the side of the pier with impinging flow, and some amount of deposition on the leeward side, as typically has been observed at piers skewed to approach flow; however, at most skewed piers in the current (2016) study, the scour hole was deeper on the leeward side of the pier. At most of these piers, the angled approach flow was the result of a deflection or contraction of flow caused by a spur dike near the pier, which may affect flow differently than for a simple skew. At structure A6500 (site 33), the wide face of the pier footing and seal course would behave as a complex foundation, for which scour is computed differently.
Previous bathymetric surveys exist for all the sites examined in this study. A previous survey in October 2010 at most of the sites had similar flow conditions and similar results to the 2016 surveys. A survey during flood conditions in August 2011 at the sites on the Missouri River and in May 2009 at structures A4936 and A1850 (site 35) on the Mississippi River did not always indicate more substantial scour during flood conditions. At structure A6500 (site 33) on the Mississippi River, a previous survey in 2009 was part of a habitat assessment before construction of the bridge and provides unique insight into the effects of the construction of that bridge on the channel in this reach. Substantial scour was observed near the right pier, and the riprap blanket surrounding the left pier seems to limit scour near that pier. Multiple additional surveys have been completed at structures A4936 and A1850 (site 35) on the Mississippi River, and the results of these surveys also are presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175076","collaboration":"Prepared in cooperation with the Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2017, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri and Mississippi Rivers near St. Louis, Missouri, May 23–27, 2016: U.S. Geological Survey Scientific Investigations Report 2017–5076, 102 p., https://doi.org/10.3133/sir20175076.","productDescription":"Report: x, 102 p.; Data Release","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-086447","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":346078,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71C1VCC","text":"USGS Data Release","linkHelpText":"Bathymetry and Velocity Data from Surveys at Highway Bridges crossing the Missouri and Mississippi Rivers near St. Louis, Missouri, October 2008 through May 2016"},{"id":346076,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5076/coverthb.jpg"},{"id":346077,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5076/sir20175076.pdf","text":"Report","size":"17.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5076"}],"country":"United States","state":"Missouri","city":"St. Louis","otherGeospatial":"Mississippi River, Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.69419860839844,\n 38.42293213401053\n ],\n [\n -90.06935119628906,\n 38.42293213401053\n ],\n [\n -90.06935119628906,\n 38.92843409820933\n ],\n [\n -90.69419860839844,\n 38.92843409820933\n ],\n [\n -90.69419860839844,\n 38.42293213401053\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
The maps and graphs in this summary describe national streamflow conditions for water year 2016 (October 1, 2015, to September 30, 2016) in the context of streamflow ranks relative to the 87-year period of 1930–2016, unless otherwise noted. The illustrations are based on observed data from the U.S. Geological Survey’s (USGS) National Streamflow Network. The period of 1930–2016 was used because the number of streamgages before 1930 was too small to provide representative data for computing statistics for most regions of the country.
In the summary, reference is made to the term “runoff,” which is the depth to which a river basin, State, or other geographic area would be covered with water if all the streamflow within the area during a specified period was uniformly distributed on it. Runoff quantifies the magnitude of water flowing through the Nation’s rivers and streams in measurement units that can be compared from one area to another.
In all the graphics, a rank of 1 indicates the highest flow of all years analyzed and 87 indicates the lowest flow of all years. Rankings of streamflow are grouped into much below normal, below normal, normal, above normal, and much above normal based on percentiles of flow (less than 10 percent, 10–24 percent, 25–75 percent, 76–90 percent, and greater than 90 percent, respectively). Some of the data used to produce the maps and graphs are provisional and subject to change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173063","usgsCitation":"Jian, Xiaodong, Wolock, D.M., Lins, H.F., and Brady, S.J., 2017, Streamflow of 2016—Water year summary: U.S. Geological Survey Fact Sheet 2017–3063, 6 p., https://doi.org/10.3133/fs20173063.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-088111","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":346071,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3063/coverthb.jpg"},{"id":346072,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3063/fs20173063.pdf","text":"Fact Sheet","size":"524 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3063"}],"country":"United 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States\"}}]}","contact":"Office of Surface Water
U.S. Geological Survey
415 National Center
Reston, VA 20192
This field manual provides general guidance for identifying and collecting high-water marks and is meant to be used by field personnel as a quick reference. The field manual describes purposes for collecting and documenting high-water marks along with the most common types of high-water marks. The manual provides a list of suggested field equipment, describes rules of thumb and best practices for finding high-water marks, and describes the importance of evaluating each high-water mark and assigning a numeric uncertainty value as part of the flagging process. The manual also includes an appendix of photographs of a variety of high-water marks obtained from various U.S. Geological Survey field investigations along with general comments about the logic for the assigned uncertainty values.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171105","collaboration":"Prepared in cooperation with the South Carolina Department of Transportation","usgsCitation":"Feaster, T.D., and Koenig, T.A, 2017, Field manual for identifying and preserving high-water mark data: U.S. Geological Survey Open-File Report 2017–1105, 67 p., https://doi.org/10.3133/ofr20171105.","productDescription":"x, 67 p.","numberOfPages":"80","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-087515","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":346094,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1105/ofr20171105.pdf","text":"Report","size":"4.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1105"},{"id":346095,"rank":3,"type":{"id":21,"text":"Referenced Work"},"url":"https://doi.org/10.3133/tm3A24","text":"T & M 3–A24","description":"T & M 3–A24"},{"id":346093,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1105/coverthb2.jpg"}],"contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Introduced American Bullfrogs (Lithobates catesbeianus) have been present in Grand Teton National Park since approximately the 1950s, but little is known about their distribution and potential impacts. In this study, we surveyed the current bullfrog distribution and spatial overlap with sympatric native amphibians in the park, and characterized post-metamorphic bullfrog diets from July – September 2015. Despite surveys in multiple large rivers and floodplain habitats, we only documented bullfrogs in a geothermal pond and 5 km of stream channel immediately downstream of this pond. In these waters, bullfrogs overlapped with native amphibians at the downstream end of their distribution, and we did not document native amphibians in bullfrog stomach contents. Larger bullfrogs (SVL ≥ 96 mm) primarily consumed native rodents (especially meadow voles, Microtus pennsylvanicus), while smaller bullfrogs frequently consumed native invertebrates and less frequently consumed non-native invertebrates and fish. Taken together, these data indicate that the distribution and implications of the bullfrog invasion in Grand Teton National Park are currently localized to a small area, so these bullfrogs should therefore be vulnerable to eradication.
","language":"English","publisher":"Northwest Science Association","doi":"10.3955/046.091.0305","collaboration":"Grand Teton National Park; Greater Yellowstone Inventory & Monitoring Network","usgsCitation":"Flynn, L.M., Kreofsky, T.M., and Sepulveda, A.J., 2017, Introduced American Bullfrog distribution and diets in Grand Teton National Park: Northwest Science, v. 3, no. 91, p. 244-256, https://doi.org/10.3955/046.091.0305.","productDescription":"13 p.","startPage":"244","endPage":"256","ipdsId":"IP-074245","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":346086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Grand Teton National 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\"}}]}","volume":"3","issue":"91","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59cb672be4b017cf3141c671","contributors":{"authors":[{"text":"Flynn, Lauren M","contributorId":196692,"corporation":false,"usgs":false,"family":"Flynn","given":"Lauren","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":711144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kreofsky, Tess Marie","contributorId":196693,"corporation":false,"usgs":false,"family":"Kreofsky","given":"Tess","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":711145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":711143,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191035,"text":"70191035 - 2017 - Camera traps reveal an apparent mutualism between a common mesocarnivore and an endangered ungulate","interactions":[],"lastModifiedDate":"2017-09-25T12:07:37","indexId":"70191035","displayToPublicDate":"2017-09-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2653,"text":"Mammalian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Camera traps reveal an apparent mutualism between a common mesocarnivore and an endangered ungulate","docAbstract":"Camera traps are commonly used to study mammal ecology and they occasionally capture previously undocumented species interactions. The key deer (Odocoileus virginianus clavium) is an endangered endemic subspecies of the Florida Keys, where it exists with few predators. We obtained a camera trap sequence of 80 photos in which a key deer interacted with two northern raccoons (Procyon lotor). One of the raccoons groomed the deer’s face for ∼1 min. This interaction is peculiar and appears mutualistic because the deer was not concerned and willingly remained still throughout the physical contact. Although mutualistic relationships between deer and birds are common, we are unaware of any previously documented mesocarnivore-deer mutualisms. Key deer have evolved in the absence of mammalian predators and we hypothesize that they exhibit reduced vigilance or concern when encountering other species because of predator naivety. Key deer and raccoons are commonly associated with humans and urbanization and an alternative hypothesis is that the interactions are a consequence of heightened deer density, causing a greater probability of sustained interactions with the common mesocarnivores.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.mambio.2017.08.007","usgsCitation":"Cove, M., Maurer, A.S., and O’Connell, A.F., 2017, Camera traps reveal an apparent mutualism between a common mesocarnivore and an endangered ungulate: Mammalian Biology, v. 87, p. 143-145, https://doi.org/10.1016/j.mambio.2017.08.007.","productDescription":"3 p.","startPage":"143","endPage":"145","ipdsId":"IP-090449","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":346052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ca15ace4b017cf314041bd","contributors":{"authors":[{"text":"Cove, Michael V.","contributorId":176507,"corporation":false,"usgs":false,"family":"Cove","given":"Michael V.","affiliations":[],"preferred":false,"id":711034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maurer, Andrew S.","contributorId":176508,"corporation":false,"usgs":false,"family":"Maurer","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":711035,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":711033,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191064,"text":"70191064 - 2017 - Coming to terms about describing Golden Eagle reproduction","interactions":[],"lastModifiedDate":"2017-11-22T16:43:46","indexId":"70191064","displayToPublicDate":"2017-09-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Coming to terms about describing Golden Eagle reproduction","docAbstract":"Clearly defined terms are essential for reporting and understanding research findings, and inconsistent terminology can complicate efforts to compare findings from different studies. In this article, we reiterate and clarify recommended terms for describing Golden Eagle (Aquila chrysaetos) territory occupancy and reproduction. Several authors have provided recommendations for reporting data on raptor reproduction, but our literature review showed that authors continue to use different, often ambiguous and undefined, terms. The inconsistent use of terminology by researchers has been continued and expanded by lawmakers, regulators, and managers, perpetuating confusion. We recommend that authors clearly define and reference all terminology that they use, and we caution against use of the term “active” to describe a nest or nesting territory, because it is tainted with a history of inconsistent use. We provide a glossary of recommended terms for Golden Eagles and other large, long-lived raptors.
","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-16-46.1","usgsCitation":"Steenhof, K., Kochert, M.N., McIntyre, C.L., and Brown, J.L., 2017, Coming to terms about describing Golden Eagle reproduction: Journal of Raptor Research, v. 51, no. 3, p. 378-390, https://doi.org/10.3356/JRR-16-46.1.","productDescription":"13 p.","startPage":"378","endPage":"390","ipdsId":"IP-073063","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469501,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-16-46.1","text":"Publisher Index Page"},{"id":346046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ca15a9e4b017cf314041ac","contributors":{"authors":[{"text":"Steenhof, Karen karen_steenhof@usgs.gov","contributorId":30585,"corporation":false,"usgs":true,"family":"Steenhof","given":"Karen","email":"karen_steenhof@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":711079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kochert, Michael N. 0000-0002-4380-3298 mkochert@usgs.gov","orcid":"https://orcid.org/0000-0002-4380-3298","contributorId":3037,"corporation":false,"usgs":true,"family":"Kochert","given":"Michael","email":"mkochert@usgs.gov","middleInitial":"N.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":711078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McIntyre, Carol L.","contributorId":196673,"corporation":false,"usgs":false,"family":"McIntyre","given":"Carol","email":"","middleInitial":"L.","affiliations":[{"id":20307,"text":"US National Park Service","active":true,"usgs":false}],"preferred":false,"id":711080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Jessi L.","contributorId":44817,"corporation":false,"usgs":false,"family":"Brown","given":"Jessi","email":"","middleInitial":"L.","affiliations":[{"id":13184,"text":"Program in Ecology, Evolution and Conservation Biology, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":711081,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191087,"text":"70191087 - 2017 - Semipermanent GPS (SPGPS) as a volcano monitoring tool: Rationale, method, and applications","interactions":[],"lastModifiedDate":"2017-09-25T13:35:49","indexId":"70191087","displayToPublicDate":"2017-09-25T00:00:00","publicationYear":"2017","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":"Semipermanent GPS (SPGPS) as a volcano monitoring tool: Rationale, method, and applications","docAbstract":"Semipermanent GPS (SPGPS) is an alternative to conventional campaign or survey-mode GPS (SGPS) and to continuous GPS (CGPS) that offers several advantages for monitoring ground deformation. Unlike CGPS installations, SPGPS stations can be deployed quickly in response to changing volcanic conditions or earthquake activity such as a swarm or aftershock sequence. SPGPS networks can be more focused or more extensive than CGPS installations, because SPGPS equipment can be moved from station to station quickly to increase the total number of stations observed in a given time period. SPGPS networks are less intrusive on the landscape than CGPS installations, which makes it easier to satisfy land-use restrictions in ecologically sensitive areas. SPGPS observations are preferred over SGPS measurements because they provide better precision with only a modest increase in the amount of time, equipment, and personnel required in the field. We describe three applications of the SPGPS method that demonstrate its utility and flexibility. At the Yellowstone caldera, Wyoming, a 9-station SPGPS network serves to densify larger preexisting networks of CGPS and SGPS stations. At the Three Sisters volcanic center, Oregon, a 14-station SPGPS network complements an SGPS network and extends the geographic coverage provided by 3 CGPS stations permitted under wilderness land-use restrictions. In the Basin and Range province in northwest Nevada, a 6-station SPGPS network has been established in response to a prolonged earthquake swarm in an area with only sparse preexisting geodetic coverage. At Three Sisters, the estimated precision of station velocities based on annual ~ 3 month summertime SPGPS occupations from 2009 to 2015 is approximately half that for nearby CGPS stations. Conversely, SPGPS-derived station velocities are about twice as precise as those based on annual ~ 1 week SGPS measurements. After 5 years of SPGPS observations at Three Sisters, the precision of velocity determinations is estimated to be 0.5 mm/yr in longitude, 0.6 mm/yr in latitude, and 0.8 mm/yr in height. We conclude that an optimal approach to monitoring volcano deformation includes complementary CGPS and SPGPS networks, periodic InSAR observations, and measurements from in situ borehole sensors such as tiltmeters or strainmeters. This comprehensive approach provides the spatial and temporal detail necessary to adequately characterize a complex and evolving deformation pattern. Such information is essential to multi-parameter models of magmatic or tectonic processes that can help to guide research efforts, and also to inform hazards assessments and land-use planning decisions.
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","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2017.09.014","usgsCitation":"Thompson, M., Beston, J.A., Etterson, M.A., Diffendorfer, J., and Loss, S., 2017, Factors associated with bat mortality at wind energy facilities in the United States: Biological Conservation, v. 215, p. 241-245, https://doi.org/10.1016/j.biocon.2017.09.014.","productDescription":"5 p.","startPage":"241","endPage":"245","ipdsId":"IP-084171","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469502,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6490962","text":"Publisher Index Page"},{"id":346041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"215","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ca15a6e4b017cf3140419f","contributors":{"authors":[{"text":"Thompson, Maureen","contributorId":196680,"corporation":false,"usgs":false,"family":"Thompson","given":"Maureen","email":"","affiliations":[],"preferred":false,"id":711099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beston, Julie A. jbeston@usgs.gov","contributorId":5673,"corporation":false,"usgs":true,"family":"Beston","given":"Julie","email":"jbeston@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":711100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Etterson, Matthew A.","contributorId":108012,"corporation":false,"usgs":false,"family":"Etterson","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":711101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":711098,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loss, Scott R.","contributorId":140471,"corporation":false,"usgs":false,"family":"Loss","given":"Scott R.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":711102,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}