Unequal sex ratios can reduce the productivity of animal populations and are especially prevalent among endangered species. A cohort of 333 Roseate Tern Sterna dougallii chicks at a site where the adult sex ratio was skewed towards females was sexed at hatching and followed through fledging and return to the breeding area, and subsequently during adulthood. The entire regional metapopulation was sampled for returning birds. Prebreeding survival (from fledging to age 3 years) was lower in males than in females, but only among B-chicks (second in hatching order). Prebreeding survival also declined with hatching date. The proportion of females in this cohort increased from 54.6% at hatching to 56.2% at fledging and to an estimated 58.0% among survivors at age 3 years. This was more than sufficient to explain the degree of skew in the sex ratio of the adult population, but changes in this degree of skew during the study period make it difficult to identify the influence of a single cohort of recruits. Many studies of prebreeding survival in other bird species have identified effects of sex, hatching order or hatching date, but no previous study has tested for effects of all three factors simultaneously.
","language":"English","publisher":"Academic Press","publisherLocation":"London","doi":"10.1111/ibi.12359","collaboration":"Ian Nisbet; David Monticelli; Jeffrey Spendelow; Patricia Szczys","usgsCitation":"Nisbet, I.C., Monticelli, D., Spendelow, J.A., and Szczys, P., 2016, Prebreeding survival of Roseate Terns Sterna dougallii varies with sex, hatching order and hatching date: Ibis, v. 158, no. 2, p. 327-334, https://doi.org/10.1111/ibi.12359.","productDescription":"8 p.","startPage":"327","endPage":"334","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072951","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":319556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"158","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-10","publicationStatus":"PW","scienceBaseUri":"56fa560be4b0a6037df0ab5a","contributors":{"authors":[{"text":"Nisbet, Ian C. T.","contributorId":54866,"corporation":false,"usgs":true,"family":"Nisbet","given":"Ian","email":"","middleInitial":"C. T.","affiliations":[],"preferred":false,"id":625408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monticelli, David","contributorId":168304,"corporation":false,"usgs":false,"family":"Monticelli","given":"David","email":"","affiliations":[{"id":25244,"text":"Marine and Environmental Science Centre, Universidade de Coimbra, Coimbra, Portugal","active":true,"usgs":false}],"preferred":false,"id":625406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spendelow, Jeffrey A. 0000-0001-8167-0898 jspendelow@usgs.gov","orcid":"https://orcid.org/0000-0001-8167-0898","contributorId":4355,"corporation":false,"usgs":true,"family":"Spendelow","given":"Jeffrey","email":"jspendelow@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":625405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Szczys, Patricia","contributorId":35613,"corporation":false,"usgs":true,"family":"Szczys","given":"Patricia","email":"","affiliations":[],"preferred":false,"id":625407,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169085,"text":"70169085 - 2016 - Ecology, distribution, and predictive occurrence modeling of Palmers chipmunk (Tamias palmeri): a high-elevation small mammal endemic to the Spring Mountains in southern Nevada, USA","interactions":[],"lastModifiedDate":"2016-12-16T11:08:53","indexId":"70169085","displayToPublicDate":"2016-03-10T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Ecology, distribution, and predictive occurrence modeling of Palmers chipmunk (Tamias palmeri): a high-elevation small mammal endemic to the Spring Mountains in southern Nevada, USA","docAbstract":"Although montane sky islands surrounded by desert scrub and shrub steppe comprise a large part of the biological diversity of the Basin and Range Province of southwestern North America, comprehensive ecological and population demographic studies for high-elevation small mammals within these areas are rare. Here, we examine the ecology and population parameters of the Palmer’s chipmunk (Tamias palmeri) in the Spring Mountains of southern Nevada, and present a predictive GIS-based distribution and probability of occurrence model at both home range and geographic spatial scales. Logistic regression analyses and Akaike Information Criterion model selection found variables of forest type, slope, and distance to water sources as predictive of chipmunk occurrence at the geographic scale. At the home range scale, increasing population density, decreasing overstory canopy cover, and decreasing understory canopy cover contributed to increased survival rates.
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2016 - Prioritizing avian species for their risk of population-level consequences from wind energy development","interactions":[],"lastModifiedDate":"2016-03-14T13:05:13","indexId":"70169044","displayToPublicDate":"2016-03-10T14:00:00","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}},"title":"Prioritizing avian species for their risk of population-level consequences from wind energy development","docAbstract":"Recent growth in the wind energy industry has increased concerns about its impacts on wildlife populations. Direct impacts of wind energy include bird and bat collisions with turbines whereas indirect impacts include changes in wildlife habitat and behavior. Although many species may withstand these effects, species that are long-lived with low rates of reproduction, have specialized habitat preferences, or are attracted to turbines may be more prone to declines in population abundance. We developed a prioritization system to identify the avian species most likely to experience population declines from wind facilities based on their current conservation status and their expected risk from turbines. We developed 3 metrics of turbine risk that incorporate data on collision fatalities at wind facilities, population size, life history, species’ distributions relative to turbine locations, number of suitable habitat types, and species’ conservation status. We calculated at least 1 measure of turbine risk for 428 avian species that breed in the United States. We then simulated 100,000 random sets of cutoff criteria (i.e., the metric values used to assign species to different priority categories) for each turbine risk metric and for conservation status. For each set of criteria, we assigned each species a priority score and calculated the average priority score across all sets of criteria. Our prioritization system highlights both species that could potentially experience population decline caused by wind energy and species at low risk of population decline. For instance, several birds of prey, such as the long-eared owl, ferruginous hawk, Swainson’s hawk, and golden eagle, were at relatively high risk of population decline across a wide variety of cutoff values, whereas many passerines were at relatively low risk of decline. This prioritization system is a first step that will help researchers, conservationists, managers, and industry target future study and management activity.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS One","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0150813","usgsCitation":"Beston, J.A., Diffendorfer, J., Loss, S., and Johnson, D.H., 2016, Prioritizing avian species for their risk of population-level consequences from wind energy development: PLoS ONE, v. 11, no. 3, https://doi.org/10.1371/journal.pone.0150813.","startPage":"Article e0150813","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057769","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":471160,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0150813","text":"Publisher Index Page"},{"id":318849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-10","publicationStatus":"PW","scienceBaseUri":"56e7e0c0e4b0f59b85d6aabc","contributors":{"authors":[{"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":622671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":622672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loss, Scott","contributorId":131107,"corporation":false,"usgs":false,"family":"Loss","given":"Scott","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":622673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Douglas H. 0000-0002-7778-6641 douglas_h_johnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":1387,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas","email":"douglas_h_johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":622674,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169123,"text":"70169123 - 2016 - Stress in mangrove forests: early detection and preemptive rehabilitation are essential for future successful worldwide mangrove forest management","interactions":[],"lastModifiedDate":"2016-08-25T10:26:16","indexId":"70169123","displayToPublicDate":"2016-03-10T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Stress in mangrove forests: early detection and preemptive rehabilitation are essential for future successful worldwide mangrove forest management","docAbstract":"Mangrove forest rehabilitation should begin much sooner than at the point of catastrophic loss. We describe the need for “mangrove forest heart attack prevention”, and how that might be accomplished in a general sense by embedding plot and remote sensing monitoring within coastal management plans. The major cause of mangrove stress at many sites globally is often linked to reduced tidal flows and exchanges. Blocked water flows can reduce flushing not only from the seaward side, but also result in higher salinity and reduced sediments when flows are blocked landward. Long-term degradation of function leads to acute mortality prompted by acute events, but created by a systematic propensity for long-term neglect of mangroves. Often, mangroves are lost within a few years; however, vulnerability is re-set decades earlier when seemingly innocuous hydrological modifications are made (e.g., road construction, blocked tidal channels), but which remain undetected without reasonable large-scale monitoring.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Pollution Bulletin","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.marpolbul.2016.03.006","usgsCitation":"Lewis, R.R., Milbrandt, E.C., Brown, B., Krauss, K.W., Rovai, A.S., Beever, J.W., and Flynn, L., 2016, Stress in mangrove forests: early detection and preemptive rehabilitation are essential for future successful worldwide mangrove forest management: Marine Pollution Bulletin, v. 109, no. 2, p. 764-771, https://doi.org/10.1016/j.marpolbul.2016.03.006.","productDescription":"8 p.","startPage":"764","endPage":"771","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070524","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":319080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Worldwide","volume":"109","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56f11b70e4b0f59b85ddc517","contributors":{"authors":[{"text":"Lewis, Roy R","contributorId":167668,"corporation":false,"usgs":false,"family":"Lewis","given":"Roy","email":"","middleInitial":"R","affiliations":[{"id":24798,"text":"Coastal Resources Group, Salt Springs, FL","active":true,"usgs":false}],"preferred":false,"id":623077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milbrandt, Eric C","contributorId":167669,"corporation":false,"usgs":false,"family":"Milbrandt","given":"Eric","email":"","middleInitial":"C","affiliations":[{"id":24799,"text":"Sanibel-Captiva Conservation Foundation, Sanibel, FL","active":true,"usgs":false}],"preferred":false,"id":623078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Benjamin","contributorId":167670,"corporation":false,"usgs":false,"family":"Brown","given":"Benjamin","email":"","affiliations":[{"id":24800,"text":"Charles Darwin University, Research Institute for Environment and Livelihoolds, AUS","active":true,"usgs":false}],"preferred":false,"id":623079,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":623076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rovai, Andre S.","contributorId":167671,"corporation":false,"usgs":false,"family":"Rovai","given":"Andre","email":"","middleInitial":"S.","affiliations":[{"id":24801,"text":"Federal University of Santa Catarina, Dept. Ecology and Zoology, Brazil","active":true,"usgs":false}],"preferred":false,"id":623080,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beever, James W.","contributorId":167672,"corporation":false,"usgs":false,"family":"Beever","given":"James","email":"","middleInitial":"W.","affiliations":[{"id":24802,"text":"Southwest Florida Regional Planning Council, Fort Myers, FL","active":true,"usgs":false}],"preferred":false,"id":623081,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flynn, Laura L","contributorId":167673,"corporation":false,"usgs":false,"family":"Flynn","given":"Laura L","affiliations":[{"id":24798,"text":"Coastal Resources Group, Salt Springs, FL","active":true,"usgs":false}],"preferred":false,"id":623082,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169007,"text":"70169007 - 2016 - Online induction heating for determination of isotope composition of woody stem water with laser spectrometry: A methods assessment","interactions":[],"lastModifiedDate":"2017-11-22T17:39:15","indexId":"70169007","displayToPublicDate":"2016-03-10T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2114,"text":"Isotopes in Environmental and Health Studies","active":true,"publicationSubtype":{"id":10}},"title":"Online induction heating for determination of isotope composition of woody stem water with laser spectrometry: A methods assessment","docAbstract":"Application of stable isotopes of water to studies of plant–soil interactions often requires a substantial preparatory step of extracting water from samples without fractionating isotopes. Online heating is an emerging approach for this need, but is relatively untested and major questions of how to best deliver standards and assess interference by organics have not been evaluated. We examined these issues in our application of measuring woody stem xylem of sagebrush using a Picarro laser spectrometer with online induction heating. We determined (1) effects of cryogenic compared to induction-heating extraction, (2) effects of delivery of standards on filter media compared to on woody stem sections, and (3) spectral interference from organic compounds for these approaches (and developed a technique to do so). Our results suggest that matching sample and standard media improves accuracy, but that isotopic values differ with the extraction method in ways that are not due to spectral interference from organics.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10256016.2016.1141205","usgsCitation":"Lazarus, B.E., Germino, M., and Vander Veen, J.L., 2016, Online induction heating for determination of isotope composition of woody stem water with laser spectrometry: A methods assessment: Isotopes in Environmental and Health Studies, v. 52, no. 3, p. 309-325, https://doi.org/10.1080/10256016.2016.1141205.","productDescription":"17 p.","startPage":"309","endPage":"325","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063959","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":318824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-10","publicationStatus":"PW","scienceBaseUri":"56e3fa58e4b0f59b85d4946d","contributors":{"authors":[{"text":"Lazarus, Brynne E. 0000-0002-6352-486X blazarus@usgs.gov","orcid":"https://orcid.org/0000-0002-6352-486X","contributorId":4901,"corporation":false,"usgs":true,"family":"Lazarus","given":"Brynne","email":"blazarus@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":622488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":622487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vander Veen, Jessica L.","contributorId":167500,"corporation":false,"usgs":false,"family":"Vander Veen","given":"Jessica","email":"","middleInitial":"L.","affiliations":[{"id":24728,"text":"USGS FRESC","active":true,"usgs":false}],"preferred":false,"id":622489,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168923,"text":"70168923 - 2016 - Does water chemistry limit the distribution of New Zealand mud snails in Redwood National Park?","interactions":[],"lastModifiedDate":"2016-06-02T11:02:21","indexId":"70168923","displayToPublicDate":"2016-03-10T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Does water chemistry limit the distribution of New Zealand mud snails in Redwood National Park?","docAbstract":"New Zealand mud snails (NZMS) are exotic mollusks present in many waterways of the western United States. In 2009, NZMS were detected in Redwood Creek in Redwood National Park, CA. Although NZMS are noted for their ability to rapidly increase in abundance and colonize new areas, after more than 5 years in Redwood Creek, their distribution remains limited to a ca. 300 m reach. Recent literature suggests that low specific conductivity and environmental calcium can limit NZMS distribution. We conducted laboratory experiments, exposing NZMS collected from Redwood Creek to both natural waters and artificial treatment solutions, to determine if low conductivity and calcium concentration limit the distribution of NZMS in Redwood National Park. For natural water exposures, we held NZMS in water from their source location (conductivity 135 μS/cm, calcium 13 mg/L) or water from four other locations in the Redwood Creek watershed encompassing a range of conductivity (77–158 μS/cm) and calcium concentration (<5–13 mg/L). For exposures in treatment solutions, we manipulated both conductivity (range 20–200 μS/cm) and calcium concentration (range <5–17.5 mg/L) in a factorial design. Response variables measured included mortality and reproductive output. Adult NZMS survived for long periods (>4 months) in the lowest conductivity waters from Redwood Creek and all but the lowest-conductivity treatment solutions, regardless of calcium concentration. However, reproductive output was very low in all natural waters and all low-calcium treatment solutions. Our results suggest that water chemistry may inhibit the spread of NZMS in Redwood National Park by reducing their reproductive output.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1098-1","usgsCitation":"Vazquez, R., Ward, D.M., and Sepulveda, A.J., 2016, Does water chemistry limit the distribution of New Zealand mud snails in Redwood National Park?: Biological Invasions, v. 18, no. 6, p. 1523-1531, https://doi.org/10.1007/s10530-016-1098-1.","productDescription":"9 p.","startPage":"1523","endPage":"1531","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070980","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":318785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Redwood Creek, Redwood National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.05349731445312,\n 41.10470834043821\n ],\n [\n -124.05349731445312,\n 41.30411857136123\n ],\n [\n -123.91891479492186,\n 41.30411857136123\n ],\n [\n -123.91891479492186,\n 41.10470834043821\n ],\n [\n -124.05349731445312,\n 41.10470834043821\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-05","publicationStatus":"PW","scienceBaseUri":"56e29aade4b0f59b85d32753","contributors":{"authors":[{"text":"Vazquez, Ryan","contributorId":167388,"corporation":false,"usgs":false,"family":"Vazquez","given":"Ryan","email":"","affiliations":[{"id":24705,"text":"Department of Fisheries Biology, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":622122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, Darren M.","contributorId":167389,"corporation":false,"usgs":false,"family":"Ward","given":"Darren","email":"","middleInitial":"M.","affiliations":[{"id":24705,"text":"Department of Fisheries Biology, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":622123,"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":622121,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168968,"text":"70168968 - 2016 - The differing biogeochemical and microbial signatures of glaciers and rock glaciers","interactions":[],"lastModifiedDate":"2018-02-22T11:30:49","indexId":"70168968","displayToPublicDate":"2016-03-10T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"The differing biogeochemical and microbial signatures of glaciers and rock glaciers","docAbstract":"Glaciers and rock glaciers supply water and bioavailable nutrients to headwater mountain lakes and streams across all regions of the American West. Here we present a comparative study of the metal, nutrient, and microbial characteristics of glacial and rock glacial influence on headwater ecosystems in three mountain ranges of the contiguous U.S.: The Cascade Mountains, Rocky Mountains, and Sierra Nevada. Several meltwater characteristics (water temperature, conductivity, pH, heavy metals, nutrients, complexity of dissolved organic matter (DOM), and bacterial richness and diversity) differed significantly between glacier and rock glacier meltwaters, while other characteristics (Ca2+, Fe3+, SiO2 concentrations, reactive nitrogen, and microbial processing of DOM) showed distinct trends between mountain ranges regardless of meltwater source. Some characteristics were affected both by glacier type and mountain range (e.g. temperature, ammonium (NH4+) and nitrate (NO3- ) concentrations, bacterial diversity). Due to the ubiquity of rock glaciers and the accelerating loss of the low latitude glaciers our results point to the important and changing influence that these frozen features place on headwater ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1002/2015JG003236","usgsCitation":"Fegel, T.S., Baron, J., Fountain, A.G., Johnson, G.F., and Hall, E.K., 2016, The differing biogeochemical and microbial signatures of glaciers and rock glaciers: Journal of Geophysical Research G: Biogeosciences, v. 121, no. 3, p. 919-932, https://doi.org/10.1002/2015JG003236.","productDescription":"14 p.","startPage":"919","endPage":"932","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069738","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471161,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jg003236","text":"Publisher Index Page"},{"id":318781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Oregon, Washington, Wyoming","otherGeospatial":"Cascade Mountains, Sierra Nevada, Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.8046875,\n 34.08906131584996\n ],\n [\n -124.8046875,\n 49.03786794532644\n ],\n [\n -105.46875,\n 49.03786794532644\n ],\n [\n -105.46875,\n 34.08906131584996\n ],\n [\n -124.8046875,\n 34.08906131584996\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-29","publicationStatus":"PW","scienceBaseUri":"56e29aafe4b0f59b85d3275b","contributors":{"authors":[{"text":"Fegel, Timothy S.","contributorId":167462,"corporation":false,"usgs":false,"family":"Fegel","given":"Timothy","email":"","middleInitial":"S.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":622415,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":622414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fountain, Andrew G.","contributorId":10410,"corporation":false,"usgs":false,"family":"Fountain","given":"Andrew","email":"","middleInitial":"G.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":622416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Gunnar F.","contributorId":167464,"corporation":false,"usgs":false,"family":"Johnson","given":"Gunnar","email":"","middleInitial":"F.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":622417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Edward K. ehall@usgs.gov","contributorId":4837,"corporation":false,"usgs":true,"family":"Hall","given":"Edward","email":"ehall@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":622418,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168967,"text":"70168967 - 2016 - Using science-policy integration to improve ecosystem science and inform decision-making: Lessons from U.S. LTERs","interactions":[],"lastModifiedDate":"2018-02-22T11:28:37","indexId":"70168967","displayToPublicDate":"2016-03-10T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1121,"text":"Bulletin of the Ecological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Using science-policy integration to improve ecosystem science and inform decision-making: Lessons from U.S. LTERs","docAbstract":"This Special Session took place on 12 August 2015 at the 100th Meeting of the Ecological Society of America in Baltimore, Maryland, and was conceived of and coordinated by the Science Policy Exchange. The Science Policy Exchange (SPE) is a boundary- spanning organization established to work at the interface of science and policy to confront pressing environmental challenges . SPE was created as a collaborative of six research institutions to increase the impact of science on environmental decisions. This session was organized by Marissa Weiss and co- organized by Pamela Templer, Kathleen Fallon Lambert, Jill Baron, Charles Driscoll, and David Foster. Along the theme of ESA ’ s Centennial meeting, the group of presenters represented collectively more than 100 years of experience in integration of science, policy, and outreach.
","language":"English","publisher":"Wiley","doi":"10.1002/bes2.1206","usgsCitation":"Templer, P.H., Lambert, K.F., Weiss, M., Baron, J., Driscoll, C.T., and Foster, D.R., 2016, Using science-policy integration to improve ecosystem science and inform decision-making: Lessons from U.S. LTERs: Bulletin of the Ecological Society of America, v. 97, no. 1, p. 123-128, https://doi.org/10.1002/bes2.1206.","productDescription":"6 p.","startPage":"123","endPage":"128","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070047","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471164,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/bes2.1206","text":"Publisher Index Page"},{"id":318774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-14","publicationStatus":"PW","scienceBaseUri":"56e29aafe4b0f59b85d3275d","contributors":{"authors":[{"text":"Templer, Pamela H.","contributorId":167457,"corporation":false,"usgs":false,"family":"Templer","given":"Pamela","email":"","middleInitial":"H.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":622409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lambert, Kathleen Fallon","contributorId":167458,"corporation":false,"usgs":false,"family":"Lambert","given":"Kathleen","email":"","middleInitial":"Fallon","affiliations":[{"id":24712,"text":"Harvard Forest","active":true,"usgs":false}],"preferred":false,"id":622410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weiss, Marissa","contributorId":167459,"corporation":false,"usgs":false,"family":"Weiss","given":"Marissa","email":"","affiliations":[{"id":24712,"text":"Harvard Forest","active":true,"usgs":false}],"preferred":false,"id":622411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":622408,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Driscoll, Charles T.","contributorId":35418,"corporation":false,"usgs":true,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":622412,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foster, David R.","contributorId":167461,"corporation":false,"usgs":false,"family":"Foster","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":24712,"text":"Harvard Forest","active":true,"usgs":false}],"preferred":false,"id":622413,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169000,"text":"70169000 - 2016 - Organic contaminants in Great Lakes tributaries: Prevalence and potential aquatic toxicity","interactions":[],"lastModifiedDate":"2016-03-10T09:59:17","indexId":"70169000","displayToPublicDate":"2016-03-10T10:45:00","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":"Organic contaminants in Great Lakes tributaries: Prevalence and potential aquatic toxicity","docAbstract":"Organic compounds used in agriculture, industry, and households make their way into surface waters through runoff, leaking septic-conveyance systems, regulated and unregulated discharges, and combined sewer overflows, among other sources. Concentrations of these organic waste compounds (OWCs) in some Great Lakes tributaries indicate a high potential for adverse impacts on aquatic organisms. During 2010–13, 709 water samples were collected at 57 tributaries, together representing approximately 41% of the total inflow to the lakes. Samples were collected during runoff and low-flow conditions and analyzed for 69 OWCs, including herbicides, insecticides, polycyclic aromatic hydrocarbons, plasticizers, antioxidants, detergent metabolites, fire retardants, non-prescription human drugs, flavors/fragrances, and dyes. Urban-related land cover characteristics were the most important explanatory variables of concentrations of many OWCs. Compared to samples from nonurban watersheds (< 15% urban land cover) samples from urban watersheds (> 15% urban land cover) had nearly four times the number of detected compounds and four times the total sample concentration, on average. Concentration differences between runoff and low-flow conditions were not observed, but seasonal differences were observed in atrazine, metolachlor, DEET, and HHCB concentrations. Water quality benchmarks for individual OWCs were exceeded at 20 sites, and at 7 sites benchmarks were exceeded by a factor of 10 or more. The compounds with the most frequent water quality benchmark exceedances were the PAHs benzo[a]pyrene, pyrene, fluoranthene, and anthracene, the detergent metabolite 4-nonylphenol, and the herbicide atrazine. Computed estradiol equivalency quotients (EEQs) using only nonsteroidal endocrine-active compounds indicated medium to high risk of estrogenic effects (intersex or vitellogenin induction) at 10 sites. EEQs at 3 sites were comparable to values reported in effluent. This multifaceted study is the largest, most comprehensive assessment of the occurrence and potential effects of OWCs in the Great Lakes Basin to date.
","language":"English","doi":"10.1016/j.scitotenv.2016.02.137","usgsCitation":"Baldwin, A.K., Corsi, S., De Cicco, L., Lenaker, P.L., Lutz, M.A., Sullivan, D.J., and Richards, K.D., 2016, Organic contaminants in Great Lakes tributaries: Prevalence and potential aquatic toxicity: Science of the Total Environment, v. 554-555, p. 42-52, https://doi.org/10.1016/j.scitotenv.2016.02.137.","productDescription":"11 p.","startPage":"42","endPage":"52","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073075","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":471162,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.02.137","text":"Publisher Index Page"},{"id":318776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.63671875,\n 41.44272637767212\n ],\n [\n -92.63671875,\n 48.951366470947725\n ],\n [\n -75.76171875,\n 48.951366470947725\n ],\n [\n -75.76171875,\n 41.44272637767212\n ],\n [\n -92.63671875,\n 41.44272637767212\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"554-555","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e29aaee4b0f59b85d32759","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. srcorsi@usgs.gov","contributorId":511,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Cicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":4814,"corporation":false,"usgs":true,"family":"De Cicco","given":"Laura A.","email":"ldecicco@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lenaker, Peter L. 0000-0002-9469-6285 plenaker@usgs.gov","orcid":"https://orcid.org/0000-0002-9469-6285","contributorId":5572,"corporation":false,"usgs":true,"family":"Lenaker","given":"Peter","email":"plenaker@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lutz, Michelle A. malutz@usgs.gov","contributorId":167259,"corporation":false,"usgs":true,"family":"Lutz","given":"Michelle","email":"malutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Daniel J. 0000-0003-2705-3738 djsulliv@usgs.gov","orcid":"https://orcid.org/0000-0003-2705-3738","contributorId":1703,"corporation":false,"usgs":true,"family":"Sullivan","given":"Daniel","email":"djsulliv@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622458,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Richards, Kevin D. krichard@usgs.gov","contributorId":280,"corporation":false,"usgs":true,"family":"Richards","given":"Kevin","email":"krichard@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622459,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169001,"text":"70169001 - 2016 - Application of lime (CaCO3) to promote forest recovery from severe acidification increases potential for earthworm invasion","interactions":[],"lastModifiedDate":"2016-08-17T11:06:43","indexId":"70169001","displayToPublicDate":"2016-03-10T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Application of lime (CaCO3) to promote forest recovery from severe acidification increases potential for earthworm invasion","docAbstract":"The application of lime (calcium carbonate) may be a cost-effective strategy to promote forest ecosystem recovery from acid impairment, under contemporary low levels of acidic deposition. However, liming acidified soils may create more suitable habitat for invasive earthworms that cause significant damage to forest floor communities and may disrupt ecosystem processes. We investigated the potential effects of liming in acidified soils where earthworms are rare in conjunction with a whole-ecosystem liming experiment in the chronically acidified forests of the western Adirondacks (USA). Using a microcosm experiment that replicated the whole-ecosystem treatment, we evaluated effects of soil liming on Lumbricus terrestris survivorship and biomass growth. We found that a moderate lime application (raising pH from 3.1 to 3.7) dramatically increased survival and biomass of L. terrestris, likely via increases in soil pH and associated reductions in inorganic aluminum, a known toxin. Very few L. terrestris individuals survived in unlimed soils, whereas earthworms in limed soils survived, grew, and rapidly consumed leaf litter. We supplemented this experiment with field surveys of extant earthworm communities along a gradient of soil pH in Adirondack hardwood forests, ranging from severely acidified (pH < 3) to well-buffered (pH > 5). In the field, no earthworms were observed where soil pH < 3.6. Abundance and species richness of earthworms was greatest in areas where soil pH > 4.4 and human dispersal vectors, including proximity to roads and public fishing access, were most prevalent. Overall our results suggest that moderate lime additions can be sufficient to increase earthworm invasion risk where dispersal vectors are present.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2016.03.002","usgsCitation":"Homan, C., Beirer, C.M., McCay, T.S., and Lawrence, G.B., 2016, Application of lime (CaCO3) to promote forest recovery from severe acidification increases potential for earthworm invasion: Forest Ecology and Management, v. 368, p. 39-44, https://doi.org/10.1016/j.foreco.2016.03.002.","productDescription":"6 p.","startPage":"39","endPage":"44","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071766","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2016.03.002","text":"Publisher Index Page"},{"id":318768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.87268447875977,\n 43.50423881694708\n ],\n [\n -74.87268447875977,\n 43.53672718543221\n ],\n [\n -74.79852676391602,\n 43.53672718543221\n ],\n [\n -74.79852676391602,\n 43.50423881694708\n ],\n [\n -74.87268447875977,\n 43.50423881694708\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"368","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e29aaae4b0f59b85d3274d","chorus":{"doi":"10.1016/j.foreco.2016.03.002","url":"http://dx.doi.org/10.1016/j.foreco.2016.03.002","publisher":"Elsevier BV","authors":"Homan Caitlin, Beier Colin, McCay Timothy, Lawrence Gregory","journalName":"Forest Ecology and Management","publicationDate":"5/2016"},"contributors":{"authors":[{"text":"Homan, Caitlin","contributorId":167484,"corporation":false,"usgs":false,"family":"Homan","given":"Caitlin","email":"","affiliations":[{"id":24722,"text":"Graduate Student, SUNY College of Environmental Science & Forestry","active":true,"usgs":false}],"preferred":false,"id":622462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beirer, Colin M","contributorId":167485,"corporation":false,"usgs":false,"family":"Beirer","given":"Colin","email":"","middleInitial":"M","affiliations":[{"id":24723,"text":"Associate Professor, Forest & Natural Resources, SUNY College of ESF","active":true,"usgs":false}],"preferred":false,"id":622463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCay, Timothy S","contributorId":167486,"corporation":false,"usgs":false,"family":"McCay","given":"Timothy","email":"","middleInitial":"S","affiliations":[{"id":24724,"text":"Professor of Biology & Environmental Studies, Colgate University","active":true,"usgs":false}],"preferred":false,"id":622464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622461,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157168,"text":"ds69GG - 2016 - Assessment of undiscovered hydrocarbon resources of sub-Saharan Africa","interactions":[],"lastModifiedDate":"2016-06-08T09:28:17","indexId":"ds69GG","displayToPublicDate":"2016-03-10T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"69","chapter":"GG","title":"Assessment of undiscovered hydrocarbon resources of sub-Saharan Africa","docAbstract":"The main objective of the U.S. Geological Survey’s (USGS) National and Global Petroleum Assessment Project is to assess the potential for undiscovered, technically recoverable oil and natural gas resources of the United States and the world (U.S. Geological Survey World Conventional Resources Assessment Team, 2012). The USGS updated assessments that were completed during the USGS World Petroleum Assessment 2000 (U.S. Geological Survey World Energy Assessment Team, 2000) and conducted new assessments in areas around the world that were not previously examined (U.S. Geological Survey World Conventional Resources Assessment Team, 2012). These assessments used the latest geology-based assessment methodology for conventional oil and gas resources. The new assessments are available at the USGS website, (http://energy.usgs.gov/OilGas/AssessmentsData/WorldPetroleumAssessment.aspx).
\nAs part of this project, the USGS assessed 13 geologic provinces located in sub-Saharan Africa (U.S. Geological Survey World Conventional Resources Assessment Team, 2012). Coastal provinces were extended offshore to water depths ranging from 2,000 to 4,000 meters (m). Within these 13 geologic provinces 18 assessment units (figs. 1, 2) were identified.
\nThe west Africa provinces are (1) the Senegal, containing the passive-margin Senegal Basin of Middle Jurassic to Holocene age; (2) the West African Coastal, characterized by rift, passive-margin, and transform tectonics; (3) the Gulf of Guinea, characterized by transform tectonics; (4) the Niger Delta, containing more than 9,100 m of sedimentary rock and recent sediments; (5) the West-Central Coastal, which contains the Aptian salt basin, is dominated by both rift and sag tectonics, and includes the Congo Basin; and (6) the Orange River Coastal, containing more than 7,000 m of syn-rift and post-rift sedimentary rock. The West African Coastal Province was assessed for the first time, whereas the other five west Africa provinces were reassessed for the 2012 World Oil and Wandrey Gas Resource Assessment (fig. 1 of U.S. Geological Survey World Conventional Resources Assessment Team, 2012). More than 275 new oil and gas fields have been discovered in the six west Africa provinces (IHS Energy, 2008, 2009) since the USGS World Petroleum Assessment in 2000 (U.S. Geological Survey World Energy Assessment Team, 2000). These provinces were assessed because of increased energy exploration activity and new oil and gas discoveries within the provinces.
\nSeven provinces not assessed as part of the World Petroleum Assessment 2000 (U.S. Geological Survey World Energy Assessment Team, 2000) were assessed by the USGS as part of the World Assessment 2012 (U.S. Geological Survey World Conventional Resources Assessment Team, 2012). These provinces are (1) the Chad Province, containing Cretaceous and Cenozoic-age lacustrine, continental, and minor marine rocks; (2) the Sud Province, containing Cretaceous and Paleogene age lacustrine, continental, and minor marine rocks; (3) the South Africa Coastal Province, which contains rift, transform, and passive-margin rocks; (4) the Mozambique Coastal Province, containing rift, drift, and passive-margin rocks; (5) the Morondava Province, which contains failed rift, drift, and passive-margin rocks; (6) the Tanzania Coastal Province, containing rift, drift, and passive-margin rocks; and (7) the Seychelles Province, which contains rift and drift rocks. At the time of this assessment 157 oil and gas fields had been discovered in the seven provinces (IHS Energy, 2009). These provinces were assessed because of increased interest and new oil and gas discoveries within the provinces.
\nThe assessment was geology-based and used the total petroleum system (TPS) concept. The geologic elements of a TPS are hydrocarbon source rocks (source rock maturation and hydrocarbon generation and migration), reservoir rocks (quality and distribution), and traps where hydrocarbon accumulates. Using these geologic criteria, 16 conventional total petroleum systems and 18 assessment units in the 13 provinces were defined. The undiscovered, technically recoverable oil and gas resources were assessed for all assessment units.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69GG","usgsCitation":"Brownfield, M.E., 2016, Assessment of undiscovered hydrocarbon resources of sub-Saharan Africa: U.S. Geological Survey Data Series 69, 16 Chapters, https://doi.org/10.3133/ds69GG.","productDescription":"16 Chapters","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049174","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":318763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds69GG.PNG"},{"id":318758,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-gg/"}],"otherGeospatial":"Africa, Sub-Saharan Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -12.83203125,\n 27.68352808378776\n ],\n [\n -8.4375,\n 27.68352808378776\n ],\n [\n 5.09765625,\n 18.812717856407776\n ],\n [\n 11.25,\n 23.56398712845123\n ],\n [\n 14.765625,\n 22.59372606392931\n ],\n [\n 16.34765625,\n 23.88583769986199\n ],\n [\n 24.2578125,\n 19.31114335506464\n ],\n [\n 25.3125,\n 22.105998799750576\n ],\n [\n 36.38671875,\n 22.26876403907398\n ],\n [\n 38.14453125,\n 17.978733095556183\n ],\n [\n 43.2421875,\n 12.897489183755905\n ],\n [\n 43.9453125,\n 11.178401873711785\n ],\n [\n 48.69140625,\n 12.21118019150401\n ],\n [\n 51.328125,\n 12.554563528593656\n ],\n [\n 50.09765625,\n 7.36246686553575\n ],\n [\n 44.6484375,\n 1.2303741774326145\n ],\n [\n 40.42968749999999,\n -2.986927393334863\n ],\n [\n 39.55078125,\n -6.664607562172573\n ],\n [\n 40.78125,\n -11.005904459659451\n ],\n [\n 40.95703125,\n -14.94478487508836\n ],\n [\n 38.84765625,\n -17.811456088564473\n ],\n [\n 34.98046875,\n -20.13847031245114\n ],\n [\n 35.859375,\n -22.593726063929296\n ],\n [\n 35.15625,\n -25.48295117535531\n ],\n [\n 33.22265625,\n -25.95804467331783\n ],\n [\n 33.046875,\n -28.459033019728043\n ],\n [\n 28.30078125,\n -32.69486597787506\n ],\n [\n 24.08203125,\n -33.87041555094183\n ],\n [\n 19.51171875,\n -34.74161249883172\n ],\n [\n 16.69921875,\n -33.43144133557529\n ],\n [\n 16.875,\n -30.902224705171427\n ],\n [\n 14.94140625,\n -27.059125784374054\n ],\n [\n 13.886718749999998,\n -22.431340156360594\n ],\n [\n 11.25,\n -17.97873309555617\n ],\n [\n 10.8984375,\n -14.264383087562637\n ],\n [\n 13.18359375,\n -11.178401873711785\n ],\n [\n 12.3046875,\n -6.140554782450295\n ],\n [\n 8.4375,\n -1.4061088354351468\n ],\n [\n 8.61328125,\n 1.7575368113083254\n ],\n [\n 8.96484375,\n 4.039617826768437\n ],\n [\n 6.328125,\n 4.039617826768437\n ],\n [\n 3.8671874999999996,\n 6.664607562172585\n ],\n [\n 1.23046875,\n 5.090944175033399\n ],\n [\n -1.9335937499999998,\n 4.390228926463384\n ],\n [\n -4.74609375,\n 5.090944175033399\n ],\n [\n -7.55859375,\n 4.039617826768437\n ],\n [\n -13.18359375,\n 7.536764322084078\n ],\n [\n -14.23828125,\n 9.96885060854611\n ],\n [\n -17.578125,\n 12.897489183755905\n ],\n [\n -17.578125,\n 16.804541076383455\n ],\n [\n -16.875,\n 18.646245142670608\n ],\n [\n -17.578125,\n 22.105998799750576\n ],\n [\n -15.644531250000002,\n 25.958044673317843\n ],\n [\n -12.83203125,\n 27.68352808378776\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e29aace4b0f59b85d32751","contributors":{"authors":[{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":622421,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70169038,"text":"70169038 - 2016 - Impacts of introduced Rangifer on ecosystem processes of maritime tundra on subarctic islands","interactions":[],"lastModifiedDate":"2016-03-14T08:48:54","indexId":"70169038","displayToPublicDate":"2016-03-10T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of introduced Rangifer on ecosystem processes of maritime tundra on subarctic islands","docAbstract":"Introductions of mammalian herbivores to remote islands without predators provide a natural experiment to ask how temporal and spatial variation in herbivory intensity alter feedbacks between plant and soil processes. We investigated ecosystem effects resulting from introductions of Rangifer tarandus (hereafter “Rangifer”) to native mammalian predator- and herbivore-free islands in the Aleutian archipelago of Alaska. We hypothesized that the maritime tundra of these islands would experience either: (1) accelerated ecosystem processes mediated by positive feedbacks between increased graminoid production and rapid nitrogen cycling; or (2) decelerated processes mediated by herbivory that stimulated shrub domination and lowered soil fertility. We measured summer plant and soil properties across three islands representing a chronosequence of elapsed time post-Rangifer introduction (Atka: ~100 yr; Adak: ~50; Kagalaska: ~0), with distinct stages of irruptive population dynamics of Rangifer nested within each island (Atka: irruption, K-overshoot, decline, K-re-equilibration; Adak: irruption, K-overshoot; Kagalaska: initial introduction). We also measured Rangifer spatial use within islands (indexed by pellet group counts) to determine how ecosystem processes responded to spatial variation in herbivory. Vegetation community response to herbivory varied with temporal and spatial scale. When comparing temporal effects using the island chronosequence, increased time since herbivore introduction led to more graminoids and fewer dwarf-shrubs, lichens, and mosses. Slow-growingCladonia lichens that are highly preferred winter forage were decimated on both long-termRangifer-occupied islands. In addition, linear relations between more concentrated Rangifer spatial use and reductions in graminoid and forb biomass within islands added spatial heterogeneity to long-term patterns identified by the chronosequence. These results support, in part, the hypothesis that Rangifer population persistence on islands is facilitated by successful exploitation of graminoid biomass as winter forage after palatable lichens are decimated. However, the shift from shrubs to graminoids was expected to enhance rates of nitrogen cycling, yet rates of net N-mineralization, NH4+ pools, and soil δ15N declined markedly along the chronosequence and were weakly associated with spatial use within islands. Overall plant and soil patterns were disrupted but responded differently to intermediate (50 yr) and long-term (100 yr) herbivory, and were correlated with distinct stages of irruptive population dynamics.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1002/ecs2.1219","collaboration":"USFWS","usgsCitation":"Ricca, M.A., Miles, A.K., Van Vuren, D., and Eviner, V.T., 2016, Impacts of introduced Rangifer on ecosystem processes of maritime tundra on subarctic islands: Ecosphere, v. 7, no. 3, https://doi.org/10.1002/ecs2.1219.","productDescription":"23 p.","startPage":"Article e01219","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068619","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471166,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1219","text":"Publisher Index Page"},{"id":318832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian archipelago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -177.01171875,\n 51.5429188223739\n ],\n [\n -177.01171875,\n 52.449314140869696\n ],\n [\n -173.924560546875,\n 52.449314140869696\n ],\n [\n -173.924560546875,\n 51.5429188223739\n ],\n [\n -177.01171875,\n 51.5429188223739\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-10","publicationStatus":"PW","scienceBaseUri":"56e7e0b9e4b0f59b85d6aa79","contributors":{"authors":[{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":622653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miles, A. Keith 0000-0002-3108-808X keith_miles@usgs.gov","orcid":"https://orcid.org/0000-0002-3108-808X","contributorId":196,"corporation":false,"usgs":true,"family":"Miles","given":"A.","email":"keith_miles@usgs.gov","middleInitial":"Keith","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":622652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Vuren, Dirk H.","contributorId":89408,"corporation":false,"usgs":true,"family":"Van Vuren","given":"Dirk H.","affiliations":[],"preferred":false,"id":622654,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eviner, Valerie T.","contributorId":167553,"corporation":false,"usgs":false,"family":"Eviner","given":"Valerie","email":"","middleInitial":"T.","affiliations":[{"id":24746,"text":"Department of Plant Sciences, UC Davis, CA","active":true,"usgs":false}],"preferred":false,"id":622655,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169297,"text":"70169297 - 2016 - The role of competition – colonization tradeoffs and spatial heterogeneity in promoting trematode coexistence","interactions":[],"lastModifiedDate":"2016-12-16T11:22:24","indexId":"70169297","displayToPublicDate":"2016-03-10T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The role of competition – colonization tradeoffs and spatial heterogeneity in promoting trematode coexistence","docAbstract":"Competition – colonization tradeoffs occur in many systems, and theory predicts that they can strongly promote species coexistence. However, there is little empirical evidence that observed competition – colonization tradeoffs are strong enough to maintain diversity in natural systems. This is due in part to a mismatch between theoretical assumptions and biological reality in some systems. We tested whether a competition – colonization tradeoff explains how a diverse trematode guild coexists in California horn snail populations, a system that meets the requisite criteria for the tradeoff to promote coexistence. A field experiment showed that subordinate trematode species tended to have higher colonization rates than dominant species. This tradeoff promoted coexistence in parameterized models but did not fully explain trematode diversity and abundance, suggesting a role of additional diversity maintenance mechanisms. Spatial heterogeneity is an alternative way to promote coexistence if it isolates competing species. We used scale transition theory to expand the competition – colonization tradeoff model to include spatial variation. The parameterized model showed that spatial variation in trematode prevalence did not isolate most species sufficiently to explain the overall high diversity, but could benefit some rare species. Together, the results suggest that several mechanisms combine to maintain diversity, even when a competition – colonization tradeoff occurs.
","language":"English","publisher":"The Ecological Society of America","doi":"10.1890/15-0753.1","usgsCitation":"Mordecai, E., Jaramillo, A.G., Ashford, J.E., Hechinger, R., and Lafferty, K.D., 2016, The role of competition – colonization tradeoffs and spatial heterogeneity in promoting trematode coexistence: Ecology, v. 97, no. 6, p. 1484-1496, https://doi.org/10.1890/15-0753.1.","productDescription":"13 p.","startPage":"1484","endPage":"1496","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067090","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":319334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56f50fd3e4b0f59b85e1ebd8","contributors":{"authors":[{"text":"Mordecai, Erin A.","contributorId":9113,"corporation":false,"usgs":true,"family":"Mordecai","given":"Erin A.","affiliations":[],"preferred":false,"id":623479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaramillo, Alejandra G.","contributorId":149800,"corporation":false,"usgs":false,"family":"Jaramillo","given":"Alejandra","email":"","middleInitial":"G.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":623480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ashford, Jacob E.","contributorId":149801,"corporation":false,"usgs":false,"family":"Ashford","given":"Jacob","email":"","middleInitial":"E.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":623481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hechinger, Ryan F.","contributorId":73730,"corporation":false,"usgs":true,"family":"Hechinger","given":"Ryan F.","affiliations":[],"preferred":false,"id":623482,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":623478,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174947,"text":"70174947 - 2016 - Changing regional emissions of airborne pollutants reflected in the chemistry of snowpacks and wetfall in the Rocky Mountain region, USA, 1993–2012","interactions":[],"lastModifiedDate":"2018-02-13T10:27:49","indexId":"70174947","displayToPublicDate":"2016-03-10T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Changing regional emissions of airborne pollutants reflected in the chemistry of snowpacks and wetfall in the Rocky Mountain region, USA, 1993–2012","docAbstract":"Wintertime precipitation sample data from 55 Snowpack sites and 17 National Atmospheric Deposition Program (NADP)/National Trends Network Wetfall sites in the Rocky Mountain region were examined to identify long-term trends in chemical concentration, deposition, and precipitation using Regional and Seasonal Kendall tests. The Natural Resources Conservation Service snow-telemetry (SNOTEL) network provided snow-water-equivalent data from 33 sites located near Snowpack- and NADP Wetfall-sampling sites for further comparisons. Concentration and deposition of ammonium, calcium, nitrate, and sulfate were tested for trends for the period 1993–2012. Precipitation trends were compared between the three monitoring networks for the winter seasons and downward trends were observed for both Snowpack and SNOTEL networks, but not for the NADP Wetfall network. The dry-deposition fraction of total atmospheric deposition, relative to wet deposition, was shown to be considerable in the region. Potential sources of regional airborne pollutant emissions were identified from the U.S. Environmental Protection Agency 2011 National Emissions Inventory, and from long-term emissions data for the period 1996–2013. Changes in the emissions of ammonia, nitrogen oxides, and sulfur dioxide were reflected in significant trends in snowpack and wetfall chemistry. In general, ammonia emissions in the western USA showed a gradual increase over the past decade, while ammonium concentrations and deposition in snowpacks and wetfall showed upward trends. Emissions of nitrogen oxides and sulfur dioxide declined while regional trends in snowpack and wetfall concentrations and deposition of nitrate and sulfate were downward.
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Basins intercepting the main flow and external P sources had highest P and CHL and shallowest SD. Internal loading in shallow, polymictic basins caused P and CHL to increase and SD to decrease as summer progressed. Winter aeration used to eliminate winterkill increased summer internal P loading and decreased water quality, while reductions in upstream beaver impoundments had little effect on water quality. Variations in air temperature and precipitation affected each basin differently. Warmer air temperatures increased productivity throughout the lake and decreased clarity in less eutrophic basins. Increased precipitation increased P in the basins intercepting the main flow but had little effect on the isolated deep West Bay. These relations are used to project effects of future climatic changes on LSG and other temperate lakes.
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earthquake (magnitude 7.8) on 25 April 2015 and later aftershocks struck South Asia, killing ~9000 people and damaging a large region. Supported by a large campaign of responsive satellite data acquisitions over the earthquake disaster zone, our team undertook a satellite image survey of the earthquakes’ induced geohazards in Nepal and China and an assessment of the geomorphic, tectonic, and lithologic controls on quake-induced landslides. Timely analysis and communication aided response and recovery and informed decision-makers. We mapped 4312 coseismic and postseismic landslides. We also surveyed 491 glacier lakes for earthquake damage but found only nine landslide-impacted lakes and no visible satellite evidence of outbursts. Landslide densities correlate with slope, peak ground acceleration, surface downdrop, and specific metamorphic lithologies and large plutonic intrusions.
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Seismic‐hazard analysis usually relies on ground‐motion prediction equations (GMPEs); within this framework site response is modeled statistically with simplified site parameters that include the time‐averaged shear‐wave velocity to 30 m (VS30) and basin depth parameters. Because VS30 is not known in most locations, it must be interpolated or inferred through secondary information such as geology or topography. In this article, we analyze a subset of stations for which VS30 has been measured to address effects of VS30 proxies on the uncertainty in the ground motions as modeled by GMPEs. The stations we analyze also include multiple recordings, which allow us to compute the repeatable site effects (or empirical amplification factors [EAFs]) from the ground motions. Although all methods exhibit similar bias, the proxy methods only reduce the ground‐motion standard deviations at long periods when compared to GMPEs without a site term, whereas measured VS30 values reduce the standard deviations at all periods. The standard deviation of the ground motions are much lower when the EAFs are used, indicating that future refinements of the site term in GMPEs have the potential to substantially reduce the overall uncertainty in the prediction of ground motions by GMPEs.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150214","usgsCitation":"Thompson, E.M., and Wald, D.J., 2016, Uncertainty in Vs30-based site response: Bulletin of the Seismological Society of America, v. 106, no. 2, p. 453-463, https://doi.org/10.1785/0120150214.","productDescription":"11 p.","startPage":"453","endPage":"463","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072079","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":318755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-01","publicationStatus":"PW","scienceBaseUri":"56e1492ce4b00e6e7616095c","contributors":{"authors":[{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":146592,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":622183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":622184,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70162293,"text":"sir20165004 - 2016 - Effects of streamflows on stream-channel morphology in the eastern Niobrara National Scenic River, Nebraska, 1988–2010","interactions":[],"lastModifiedDate":"2016-03-09T15:13:44","indexId":"sir20165004","displayToPublicDate":"2016-03-09T00:00:00","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":"2016-5004","title":"Effects of streamflows on stream-channel morphology in the eastern Niobrara National Scenic River, Nebraska, 1988–2010","docAbstract":"The Niobrara River is an important and valuable economic and ecological resource in northern Nebraska that supports ecotourism, recreational boating, wildlife, fisheries, agriculture, and hydroelectric power. Because of its uniquely rich resources, a 122-kilometer reach of the Niobrara River was designated as a National Scenic River in 1991, which has been jointly managed by the U.S. Fish and Wildlife Service and National Park Service. To assess how the remarkable qualities of the National Scenic River may change if consumptive uses of water are increased above current levels, the U.S. Geological Survey, in cooperation with the National Park Service, initiated an investigation of how stream-channel morphology might be affected by potential decreases in summer streamflows. The study included a 65-kilometer segment in the wide, braided eastern stretch of the Niobrara National Scenic River that provides important nesting habitat for migratory bird species of concern to the Nation.
\nThe study focused on three river segments, separated at the confluences with two tributaries, Plum Creek and Long Pine Creek. With an overall temporal scope of 1988–2010 that includes a short interval preceding and a long interval following the Niobrara National Scenic River Designation Act of 1991, the study analyzed five separate time periods: 1988–93, 1994–99, 2000–3, 2004–6, and 2007–10, each of which ended with a year in which aerial photography coverage was available.
\nStreamflow duration was analyzed for one streamgage upstream from the study area and two streamgages on tributary streams within the study area. Summer streamflows (July, August, and September) were targeted for analysis because median flows of the Niobrara River are lowest during those 3 months. In addition, peak flows during the study period were used to estimate bankfull discharge, which is one determinant of channel dimensions.
\nChanges in channel morphology were examined using aerial photographs from 1993, 1999, 2003, 2006, and 2010 to measure channel width, area of islands, and incipient flood-plain surfaces, and to compute the braided index. Channel metrics were computed for each photography year and summarized by river segment. Additionally, at fixed-location cross sections, photography analysis identified localized geomorphic change to infer processes. Accuracy of geomorphic feature classification was estimated and the root-mean-square difference (RMSD) between aerial photographs was calculated to determine associated errors in channel metric calculations. The horizontal accuracy of boundaries delineated in the classification was estimated as 5 meters (m) for boundaries based on 1993 aerial photography and 4 m for all other aerial photography. The RMSD between aerial photography years ranged from 3.04 m to 4.16 m.
\nThe largest measurable changes in channel metrics were measured between 1993 and 1999 and between 1999 and 2003. Between 1993 and 1999, average total channel width increased by 9 m (3 percent) and 14 m (5 percent) in segments 2 and 3, respectively; average active channel width increased by 13 m (5 percent) in segment 3 and decreased by 6 m (4 percent) in segment 1; and incipient flood-plain-surface area increased by 40, 44, and 33 percent in segments 1, 2, and 3, respectively. Changes in channel metrics between 1999 and 2003 included a decrease in average total channel width of 14 m (5 percent) in segment 2; a decrease in active channel widths of 8 m (3 percent) and 6 m (2 percent) in segments 2 and 3, respectively; and an increase of 5 m (3 percent) in segment 1. Incipient flood-plain areas decreased by 22 and 33 percent in segments 1 and 2, respectively, and increased by 42 percent in segment 3.
\nLarge changes were measured between 1993 and 1999, and between 1999 and 2003, at many of the fixed-location cross sections. Large changes (that is, greater than 25 percent) in total channel width were measured in all three segments between 1993 and 1999 and again between 1999 and 2003; large increases were dominant between 1993 and 1999 and large decreases were dominant between 1999 and 2003. Segment 1 was the most susceptible to localized changes as there was only one period (between 2003 and 2006) in which the active channel width largely changed in fewer than 10 percent of the cross sections.
\nChanges in channel metrics generally corresponded to changes in streamflow conditions, but other than changes in incipient flood-plain area, these changes were small and were not measured in all three segments simultaneously. Increases in total channel width (except in segment 1) and incipient flood-plain area between 1993 and 1999 corresponded to increases in streamflow. Channel narrowing (except in segment 1) between 1999 and 2003 corresponded to lower summer streamflows and extended durations of very low summer streamflow. Although the pattern of low summer streamflow and extended durations of very low summer streamflow continued during the 2004–6 period and at the beginning of the 2007–10 period, no further narrowing was measured. Consistent tributary summer inflows help to explain the resistance of segments 2 and 3 to further narrowing. Because segment 1 is already much narrower than segments 2 and 3, its average current velocity is likely to be swifter and, therefore, competent to offset further effects of the processes that led to its narrowness.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165004","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Schaepe, N.J., Alexander, J.S., and Folz-Donahue, Kiernan, 2016, Effects of streamflows on stream-channel morphology in the eastern Niobrara National Scenic River, Nebraska, 1988–2010: U.S. Geological Survey Scientific Investigations Report 2016–5004, 30 p., https://dx.doi.org/10.3133/sir20165004.","productDescription":"vi, 30 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063713","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":318685,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5004/sir20165004.pdf","text":"Report","size":"2.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5004"},{"id":318684,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5004/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Niobrara National Scenic River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.5523681640625,\n 42.706659563510385\n ],\n [\n -100.5523681640625,\n 42.956422511073335\n ],\n [\n -99.3218994140625,\n 42.956422511073335\n ],\n [\n -99.3218994140625,\n 42.706659563510385\n ],\n [\n -100.5523681640625,\n 42.706659563510385\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, Nebraska 68512
Four commercially available ultraviolet nitrate spectrophotometric sensors were evaluated by the U.S. Geological Survey Hydrologic Instrumentation Facility (HIF) to determine the effects of suspended sediment concentration (SSC) and colored dissolved organic matter (CDOM) on sensor accuracy. The evaluated sensors were: the Hach NITRATAX plus sc (5-millimeters (mm) path length), Hach NITRATAX plus sc (2 mm), S::CAN Spectro::lyser (5 mm), and the Satlantic SUNA V2 (5 mm). A National Institute of Standards and Technology-traceable nitrate-free sediment standard was purchased and used to create the turbid environment, and an easily made filtered tea solution was used for the CDOM test. All four sensors performed well in the test that evaluated the effect of suspended sediment on accuracy. The Hach 5 mm, Hach 2 mm, and the SUNA V2 met their respective manufacturer accuracy specifications up to concentrations of 4,500 milligrams per liter (mg/L) SSC. The S::CAN failed to meet its accuracy specifications when the SSC concentrations exceeded 4,000 mg/L. Test results from the effect of CDOM on accuracy indicated a significant skewing of data from all four sensors and showed an artificial elevation of measured nitrate to varying amounts. Of the four sensors tested, the Satlantic SUNA V2’s accuracy was affected the least in the CDOM test. The nitrate concentration measured by the SUNA V2 was approximately 24 percent higher than the actual concentration when estimated total organic carbon values exceeded 44 mg/L. Measured nitrate concentration falsely increased 49 percent when measured by the Hach 5 mm, and 75 percent when measured by the Hach 2 mm. The S::CAN’s reported nitrate concentration increased 96 percent. Path length plays an important role in the sensor’s ability to compensate measurements for matrix interferences, but does not solely determine how well a sensor can handle all interferences. The sensor’s proprietary algorithms also play a key role in matrix interference compensation. The sensors’ ability to compensate for CDOM varied significantly during the tests, even among the three with 5-mm path lengths. Results of this evaluation suggest that the proprietary algorithms of the nitrate analyzers are more effective compensating for suspended sediment, and less effective compensating for CDOM (color) when sensor path length remains constant.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161014","usgsCitation":"Snazelle, T.T., 2016, The effect of suspended sediment and color on ultraviolet spectrophotometric nitrate sensors: U.S. Geological Survey Open-File Report, 2016−1014, 10 p., https://dx.doi.org/10.3133/ofr20161014.","productDescription":"Report: v,10 p.; Tables: 2-4","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064543","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":318658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1014/ofr20161014.pdf","text":"Report","size":"1.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1014"},{"id":318676,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1014/table/ofr20161014_table4.xlsx","text":"Table 4 - Nitrate measurements by four ultraviolet sensors in water with a 5-mg-NL concentration with varying concentrations ofChief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to quantitatively monitor surface change over time relative to management activities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2015.10.012","usgsCitation":"Gillan, J.K., Karl, J., Barger, N., Elaksher, A., and Duniway, M.C., 2016, Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery: Rangeland Ecology and Management, v. 69, no. 2, p. 95-107, https://doi.org/10.1016/j.rama.2015.10.012.","productDescription":"13 p.","startPage":"95","endPage":"107","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059477","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":318694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Shay Mesa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.6,\n 37.9\n ],\n [\n -109.6,\n 38\n ],\n [\n -109.5,\n 38\n ],\n [\n -109.5,\n 37.9\n ],\n [\n -109.6,\n 37.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"69","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56dff7b3e4b015c306fcda06","contributors":{"authors":[{"text":"Gillan, Jeffrey K.","contributorId":51656,"corporation":false,"usgs":true,"family":"Gillan","given":"Jeffrey","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":622150,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karl, Jason W.","contributorId":22616,"corporation":false,"usgs":true,"family":"Karl","given":"Jason W.","affiliations":[],"preferred":false,"id":622151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barger, Nichole N.","contributorId":102392,"corporation":false,"usgs":true,"family":"Barger","given":"Nichole N.","affiliations":[],"preferred":false,"id":622152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elaksher, Ahmed","contributorId":72305,"corporation":false,"usgs":true,"family":"Elaksher","given":"Ahmed","affiliations":[],"preferred":false,"id":622153,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":622149,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168523,"text":"ofr20161017 - 2016 - Hydrologic conditions, recharge, and baseline water quality of the surficial aquifer system at Jekyll Island, Georgia, 2012-13","interactions":[],"lastModifiedDate":"2021-02-02T16:58:20.689444","indexId":"ofr20161017","displayToPublicDate":"2016-03-08T13:45:00","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":"2016-1017","title":"Hydrologic conditions, recharge, and baseline water quality of the surficial aquifer system at Jekyll Island, Georgia, 2012-13","docAbstract":"An increase of groundwater withdrawals from the surficial aquifer system on Jekyll Island, Georgia, prompted an investigation of hydrologic conditions and water quality by the U.S. Geological Survey during October 2012 through December 2013. The study demonstrated the importance of rainfall as the island’s main source of recharge to maintain freshwater resources by replenishing the water table from the effects of hydrologic stresses, primarily evapotranspiration and pumping. Groundwater-flow directions, recharge, and water quality of the water-table zone on the island were investigated by installing 26 shallow wells and three pond staff gages to monitor groundwater levels and water quality in the water-table zone. Climatic data from Brunswick, Georgia, were used to calculate potential maximum recharge to the water-table zone on Jekyll Island. A weather station located on the island provided only precipitation data. Additional meteorological data from the island would enhance potential evapotranspiration estimates for recharge calculations.
\nGroundwater levels and specific-conductance measurements showed the dependence of freshwater resources on rainfall to recharge the water-table zone of the surficial aquifer system and to influence groundwater flow on Jekyll Island. The unseasonably dry conditions during November 2012 to April 2013 induced saline water infiltration to the water-table zone from the marshland separating the Jekyll River from the island. A strong correlation (R2 = 0.97) of specific conductance to chloride concentration in water samples from wells installed in the water-table zone provided support for the determination of seasonal directions of groundwater flow by confirming salinity changes in the water-table zone. Unseasonably wet conditions during the late spring to August caused groundwater-flow reversals in some areas. The high dependence of the water-table zone in the surficial aquifer system on precipitation to replenish the aquifer with freshwater underscored the importance of monitoring groundwater levels, water quality, and water use to identify aquifer-discharge conditions that have the potential to promote seawater encroachment and degrade freshwater resources on Jekyll Island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161017","collaboration":"Prepared in cooperation with the Jekyll Island Authority","usgsCitation":"Gordon, D.W., and Torak, L.J., 2016, Hydrologic conditions, recharge, and baseline water quality of the surficial aquifer system at Jekyll Island, Georgia, 2012–13: U.S. Geological Survey Open-File Report 2016–1017, 34 p., https://dx.doi.org/10.3133/ofr20161017.","productDescription":"Report: viii, 34 p.; Appendixes: 1-3","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055404","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":318637,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1017/coverthb.jpg"},{"id":318641,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1017/ofr20161017_appendix3.xlsx","text":"Appendix 3. Groundwater-Level Measurements Made onDirector, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
The western United States is vulnerable to socioeconomic disruption due to extreme winter precipitation and floods. Traditionally, forecasts of precipitation and river discharge provide the basis for preparations. Herein we show that earlier event awareness may be possible through use of horizontal water vapor transport (integrated vapor transport (IVT)) forecasts. Applying the potential predictability concept to the National Centers for Environmental Prediction global ensemble reforecasts, across 31 winters, IVT is found to be more predictable than precipitation. IVT ensemble forecasts with the smallest spreads (least forecast uncertainty) are associated with initiation states with anomalously high geopotential heights south of Alaska, a setup conducive for anticyclonic conditions and weak IVT into the western United States. IVT ensemble forecasts with the greatest spreads (most forecast uncertainty) have initiation states with anomalously low geopotential heights south of Alaska and correspond to atmospheric rivers. The greater IVT predictability could provide warnings of impending storminess with additional lead times for hydrometeorological applications.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016GL067765","usgsCitation":"Lavers, D.A., Waliser, D.E., Ralph, F.M., and Dettinger, M.D., 2016, Predictability of horizontal water vapor transport relative to precipitation: Enhancing situational awareness for forecasting western U.S. extreme precipitation and flooding: Geophysical Research Letters, v. 43, no. 5, p. 2275-2282, https://doi.org/10.1002/2016GL067765.","productDescription":"8 p.","startPage":"2275","endPage":"2282","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074402","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl067765","text":"Publisher Index Page"},{"id":319397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-08","publicationStatus":"PW","scienceBaseUri":"56f661ade4b07d796bf770ea","contributors":{"authors":[{"text":"Lavers, David A.","contributorId":167847,"corporation":false,"usgs":false,"family":"Lavers","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":24837,"text":"Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":623809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waliser, Duane E.","contributorId":167848,"corporation":false,"usgs":false,"family":"Waliser","given":"Duane","email":"","middleInitial":"E.","affiliations":[{"id":24837,"text":"Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":623810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ralph, F. Martin","contributorId":150276,"corporation":false,"usgs":false,"family":"Ralph","given":"F.","email":"","middleInitial":"Martin","affiliations":[{"id":17953,"text":"Earth Systems Research Lab, NOAA","active":true,"usgs":false}],"preferred":false,"id":623811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":623808,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168905,"text":"70168905 - 2016 - Slow-moving and far-travelled dense pyroclastic flows during the Peach Spring super-eruption","interactions":[],"lastModifiedDate":"2016-03-08T09:04:46","indexId":"70168905","displayToPublicDate":"2016-03-08T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Slow-moving and far-travelled dense pyroclastic flows during the Peach Spring super-eruption","docAbstract":"Explosive volcanic super-eruptions of several hundred cubic kilometres or more generate long run-out pyroclastic density currents the dynamics of which are poorly understood and controversial. Deposits of one such event in the southwestern USA, the 18.8 Ma Peach Spring Tuff, were formed by pyroclastic flows that travelled >170 km from the eruptive centre and entrained blocks up to ~70–90 cm diameter from the substrates along the flow paths. Here we combine these data with new experimental results to show that the flow’s base had high-particle concentration and relatively modest speeds of ~5–20 m s−1, fed by an eruption discharging magma at rates up to ~107–108 m3 s−1 for a minimum of 2.5–10 h. We conclude that sustained high-eruption discharge and long-lived high-pore pressure in dense granular dispersion can be more important than large initial velocity and turbulent transport with dilute suspension in promoting long pyroclastic flow distance.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/ncomms10890","usgsCitation":"Roche, O., Buesch, D.C., and Valentine, G.A., 2016, Slow-moving and far-travelled dense pyroclastic flows during the Peach Spring super-eruption: Nature Communications, v. 7, p. 1-8, https://doi.org/10.1038/ncomms10890.","productDescription":"Article 10890; 8 p.","startPage":"1","endPage":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064658","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":471171,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/ncomms10890","text":"Publisher Index Page"},{"id":318678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.301025390625,\n 34.15272698011818\n ],\n [\n -117.301025390625,\n 35.6126508187567\n ],\n [\n -113.0712890625,\n 35.6126508187567\n ],\n [\n -113.0712890625,\n 34.15272698011818\n ],\n [\n -117.301025390625,\n 34.15272698011818\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-07","publicationStatus":"PW","scienceBaseUri":"56dff7afe4b015c306fcd9fd","contributors":{"authors":[{"text":"Roche, Olivier","contributorId":167382,"corporation":false,"usgs":false,"family":"Roche","given":"Olivier","email":"","affiliations":[{"id":24702,"text":"Laboratoire Magmas et Volcans, Université Blaise Pascal-CNRS-IRD, OPGC, F-63038 6 Clermont-Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":622108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buesch, David C. 0000-0002-4978-5027 dbuesch@usgs.gov","orcid":"https://orcid.org/0000-0002-4978-5027","contributorId":1154,"corporation":false,"usgs":true,"family":"Buesch","given":"David","email":"dbuesch@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":622106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valentine, Greg A.","contributorId":167383,"corporation":false,"usgs":false,"family":"Valentine","given":"Greg","email":"","middleInitial":"A.","affiliations":[{"id":24703,"text":"Department of Geology and Center for Geohazards Studies, University at Buffalo, Buffalo, 9 NY 14260, USA","active":true,"usgs":false}],"preferred":false,"id":622109,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168921,"text":"70168921 - 2016 - The pace of past climate change vs. potential bird distributions and land use in the United States","interactions":[],"lastModifiedDate":"2016-03-08T08:58:06","indexId":"70168921","displayToPublicDate":"2016-03-08T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"The pace of past climate change vs. potential bird distributions and land use in the United States","docAbstract":"Climate change may drastically alter patterns of species distributions and richness, but predicting future species patterns in occurrence is challenging. Significant shifts in distributions have already been observed, and understanding these recent changes can improve our understanding of potential future changes. We assessed how past climate change affected potential breeding distributions for landbird species in the conterminous United States. We quantified the bioclimatic velocity of potential breeding distributions, that is, the pace and direction of change for each species’ suitable climate space over the past 60 years. We found that potential breeding distributions for landbirds have shifted substantially with an average velocity of 1.27 km yr−1, about double the pace of prior distribution shift estimates across terrestrial systems globally (0.61 km yr−1). The direction of shifts was not uniform. The majority of species’ distributions shifted west, northwest, and north. Multidirectional shifts suggest that changes in climate conditions beyond mean temperature were influencing distributional changes. Indeed, precipitation variables that were proxies for extreme conditions were important variables across all models. There were winners and losers in terms of the area of distributions; many species experienced contractions along west and east distribution edges, and expansions along northern distribution edges. Changes were also reflected in the potential species richness, with some regions potentially gaining species (Midwest, East) and other areas potentially losing species (Southwest). However, the degree to which changes in potential breeding distributions are manifested in actual species richness depends on landcover. Areas that have become increasingly suitable for breeding birds due to changing climate are often those attractive to humans for agriculture and development. This suggests that many areas might have supported more breeding bird species had the landscape not been altered. Our study illustrates that climate change is not only a future threat, but something birds are already experiencing.
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Flooding was caused by record spring precipitation and snowmelt from the third highest cumulative snowfall year on record, which included a warm, saturated late spring snowpack. Flood stage was exceeded for a total of 67 days from April 13 to June 19, 2011. During this flooding, shoreline erosion and lake flood inundation were exacerbated by wind-driven waves associated with local fetch and lake-wide seiche effects. In May 2011, a new water-surface-elevation record was set for Lake Champlain. Peak lake-level water-surface elevations varied at the three U.S. Geological Survey lake-level gages on Lake Champlain in 2011. The May 2011 peak water-surface elevations for Lake Champlain ranged from 103.20 feet above the National Geodetic Vertical Datum of 1929 at the northern end of Lake Champlain (at its outlet into the Richelieu River at Rouses Point, New York) to 103.57 feet above the National Geodetic Vertical Datum of 1929 at the southern end of the Lake in Whitehall, New York. The water-surface elevations for the Richelieu River in Canada are referenced to a different vertical datum than are those in Lake Champlain in the United States, which causes difficulty in assessing real-time flood water-surface elevations and comparing of flood peaks in the Lake Champlain Basin in the United States and Canada.
\nOn March 19, 2012, as a result of the flood event of April and May 2011, the Governments of Canada and the United States asked the International Joint Commission to draft a plan of study to examine the causes and the effects of the spring 2011 flooding on Lake Champlain and the Richelieu River and develop potential mitigation measures. Specific challenges noted by the International Lake Champlain-Richelieu River Technical Working Group (established by the International Joint Commission) included harmonization of vertical datums within the drainage basin. Harmonization of the vertical datum discrepancy is needed for flood assessment and future efforts to model the flow of water through the Lake Champlain Basin in the United States and Canada.
\nIn April 2015, the U.S. Geological Survey and Environment Canada began a joint field effort with the goal of obtaining precise elevations representing a common vertical datum for select reference marks used to determine water-surface elevations throughout Lake Champlain and the Richelieu River. To harmonize the datum difference between the United States and Canada, Global Navigation Satellite System surveys were completed at nine locations in the Lake Champlain Basin to collect simultaneous satellite data. These satellite data were processed to produce elevations for two reference marks associated with dams and seven reference marks associated with active water-level gages (lake gages in Lake Champlain and streamgages in the Richelieu River) to harmonize vertical datums throughout the Lake Champlain Basin. The Global Navigation Satellite System surveys were completed from April 14 to 16, 2015, at locations ranging from southern Lake Champlain near Whitehall, New York, to the northern end of the Richelieu River in Sorel, Quebec, at its confluence with the St. Lawrence River in Canada.
\nLake-gage water-surface elevations determined during the 3 days of surveys were converted to water-surface elevations referenced to the North American Vertical Datum of 1988 by using calculated offsets and historical water-surface elevations. In this report, an “offset” refers to the adjustment that needs to be applied to published data from a particular gage to produce elevation data referenced to the North American Vertical Datum of 1988. Offsets presented in this report can be used in the evaluation of water-surface elevations in a common datum for Lake Champlain and the Richelieu River. In addition, the water-level data referenced to the common datum (as determined from the offsets) may be used to calibrate flow models and support future modeling studies developed for Lake Champlain and the Richelieu River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165009","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Flynn, R.H., Rydlund, P.H., Jr., and Martin, D.J., 2016, Network global navigation satellite system surveys to harmonize American and Canadian datums for the Lake Champlain Basin (ver. 1.1, April 2016): U.S. Geological Survey Scientific Investigations Report 2016–5009, 17 p., https://dx.doi.org/10.3133/sir20165009.","productDescription":"Report: vii, 17 p.; Appendixes: 1-4","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069015","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":319779,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5009/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5009"},{"id":318519,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5009/sir20165009.pdf","text":"Report","size":"3.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5009"},{"id":318520,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5009/downloads/sir20165009_appendix1.zip","text":"Appendix 1","size":"13.1 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5009","linkHelpText":"- Global navigation satellite system data collection information"},{"id":318518,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5009/coverthb2.jpg"},{"id":318521,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5009/downloads/sir20165009_appendix2.txt","text":"Appendix 2","size":"24 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5009","linkHelpText":"- Final coordinates for harmonization of datums"},{"id":318522,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5009/downloads/sir20165009_appendix3.zip","text":"Appendix 3","size":"445 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5009","linkHelpText":"- Surveyor leveling information for sites with benchmarks that could not be surveyed directly with global navigation satellite systems"},{"id":318523,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5009/downloads/sir20165009_appendix4.xlsx","text":"Appendix 4","size":"19 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5009","linkHelpText":"- Elevation offset information for benchmarks surveyed with global navigation satellite systems"}],"country":"Canada, United States","state":"New York, Quebec, Vermont","otherGeospatial":"Lake Champlain Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.278564453125,\n 43.37710501700073\n ],\n [\n -74.278564453125,\n 45.96642454131025\n ],\n [\n -72.432861328125,\n 45.96642454131025\n ],\n [\n -72.432861328125,\n 43.37710501700073\n ],\n [\n -74.278564453125,\n 43.37710501700073\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted March 8, 2016; Version 1.1: April 1, 2016","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at:
http://newengland.water.usgs.gov/
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