Characterization of rock discontinuities and rock bridges is required to define stability conditions of fractured rock masses in both natural and engineered environments. Although remote sensing methods for mapping discontinuities have improved in recent years, remote detection of intact rock bridges on cliff faces remains challenging, with their existence typically confirmed only after failure. In steep exfoliating cliffs, such as El Capitan in Yosemite Valley (California, USA), rockfalls mainly occur along cliff-parallel exfoliation joints, with rock bridges playing a key role in the stability of partially detached exfoliation sheets. We employed infrared thermal imaging (i.e., thermography) as a new means of detecting intact rock bridges prior to failure. An infrared thermal panorama of El Capitan revealed cold thermal signatures for the surfaces of two granitic exfoliation sheets, consistent with the expectation that air circulation cools the back of the partially detached sheets. However, we also noted small areas of warm thermal anomalies on these same sheets, even during periods of nocturnal rock cooling. Rock attachment via rock bridges is the likely cause for the warm anomalies in the thermal data. 2-D model simulations of the thermal behavior of one of the monitored sheets reproduce the observed anomalies and explain the temperature differences detected in the rock bridge area. Based on combined thermal and ground-based lidar imaging, and using geometric and rock fracture mechanics analysis, we are able to quantify the stability of both sheets. Our analysis demonstrates that thermography can remotely detect intact rock bridges and thereby greatly improve rockfall hazard assessment.
The importance of framing investigations of organism–environment relationships to interpret patterns at relevant spatial scales is increasingly recognized. However, most research related to environmental relationships is single-scaled, implicitly or explicitly assuming that a “species characteristic selection scale” exists. We tested the premise that a single characteristic scale exists to understand species–environment relationships within species by asking (a) what are the characteristic scales of species’ relationships with environmental predictors, and (b) is within-species, cross-predictor consistency in characteristic scales a general phenomenon.
Nebraska, USA.
2016.
Birds.
We used data from 86 species at > 500 locations to build hierarchical N-mixture models relating species abundance to land cover variables. By incorporating Bayesian latent indicator scale selection, we identified the spatial scales that best explain species–environment relationships with each land cover predictor. We quantified the extent of cross-predictor consistency in characteristic scales, and contrasted this to the expectation given a single species’ characteristic scale.
We found no evidence for a characteristic spatial scale explaining all abundance–environment relationships within species, rather we found substantial variation in scale-dependence across multiple environmental attributes. Furthermore, 33% of species displayed evidence of multiple important spatial scales within environmental attributes.
Within species there is little evidence for a single characteristic scale of environmental relationships and considerable variation in species’ scale dependencies. Because species may respond to multiple environmental attributes at different spatial scales, or single environmental attributes at multiple scales, we caution against any unoptimized single-scale studies. Our results demonstrate that until a framework is developed to predict the scales at which species respond to environmental characteristics, multi-scale investigations must be performed to identify and account for multi-scale dependencies. Natural selection acting on species’ response to distinct environmental attributes, rather than natural selection acting on species’ perception of spatial scales per se, may have shaped patterns of scale dependency and is an area ripe for investigation.
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\"}}]}","volume":"28","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Stuber, Erica F.","contributorId":198581,"corporation":false,"usgs":false,"family":"Stuber","given":"Erica","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":832950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832951,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208561,"text":"70208561 - 2019 - Soil and stand structure explain shrub mortality patterns following global change–type drought and extreme precipitation","interactions":[],"lastModifiedDate":"2020-02-18T06:17:13","indexId":"70208561","displayToPublicDate":"2019-09-11T06:46:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Soil and stand structure explain shrub mortality patterns following global change–type drought and extreme precipitation","docAbstract":"(Bradford) The probability of extreme weather events is increasing, with the potential for widespread impacts to plants, plant communities, and ecosystems. Reports of drought-related tree mortality are becoming more frequent along with increasing evidence that drought accompanied by high temperatures is especially detrimental. Simultaneously, extreme large precipitation events have become more frequent over the past century. Water-limited ecosystems may be more vulnerable to these extreme events than other ecosystems, especially when pushed outside of their historical range of variability. However, drought-related mortality of shrubs—an important component of dryland vegetation—remains understudied relative to tree mortality. In 2014, a landscape-scale die-off of the widespread shrub, big sagebrush (Artemisia tridentata Nutt.), was reported in southwest Wyoming, following extreme hot and dry conditions in 2012 and extremely high precipitation in September of 2013. Here, we examined how severe drought, extreme precipitation, soil texture and salinity, and potential competition contributed to this die-off event. At 98 plots within and around the die-off we quantified big sagebrush mortality, characterized soil texture and salinity, and simulated soil water conditions from 1916-2016 using an ecosystem water balance model. We found that the extreme weather conditions alone did not explain patterns of big sagebrush mortality and did not result in extreme (historically unprecedented) soil water conditions during the drought. Instead, plots with chronically dry soil conditions experienced greatest mortality following the global-change type (hot) drought in 2012. Furthermore, mortality was greater in locations with high potential run-on and low potential run-off where saturated soil conditions were simulated in September 2013, suggesting that extreme precipitation also played an important role in the die-off in these locations. In locations where drought alone contributed to mortality, competition negatively impacted big sagebrush. In locations that may have been affected by both drought and saturation, however, mortality was greatest where competition was lowest, suggesting that these locations may have already been less favorable to big sagebrush. Paradoxically, vulnerability to both extreme events (drought and saturation) was associated with finer-textured soils, and our results highlight the importance of soils in determining local variation the vulnerability of dryland plants to extreme events.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2889","usgsCitation":"Renne, R.R., Schlaepfer, D., Palmquist, K.A., Bradford, J.B., Burke, I.C., and Lauenroth, W.K., 2019, Soil and stand structure explain shrub mortality patterns following global change–type drought and extreme precipitation: Ecology, v. 100, no. 12, e02889, 17 p., https://doi.org/10.1002/ecy.2889.","productDescription":"e02889, 17 p.","ipdsId":"IP-107245","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":372376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.67626953125,\n 41.29431726315258\n ],\n [\n -108.67675781249999,\n 41.29431726315258\n ],\n [\n -108.67675781249999,\n 42.74701217318067\n ],\n [\n -110.67626953125,\n 42.74701217318067\n ],\n [\n -110.67626953125,\n 41.29431726315258\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Renne, Rachel R.","contributorId":213935,"corporation":false,"usgs":false,"family":"Renne","given":"Rachel","email":"","middleInitial":"R.","affiliations":[{"id":38934,"text":"School of Forestry and Environmental Studies, Yale University, New Haven, CT 06511, USA","active":true,"usgs":false}],"preferred":false,"id":782495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":782496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":782497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":782498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burke, Ingrid C.","contributorId":127653,"corporation":false,"usgs":false,"family":"Burke","given":"Ingrid","email":"","middleInitial":"C.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":782499,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":782500,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70206135,"text":"70206135 - 2019 - Multivariate models and analyses","interactions":[],"lastModifiedDate":"2020-09-01T20:05:54.143483","indexId":"70206135","displayToPublicDate":"2019-09-10T12:46:42","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Multivariate models and analyses","docAbstract":"No abstract available.
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","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Quantitative Analyses in Wildlife Science","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins University Press","isbn":"9781421431086","usgsCitation":"Hooten, M., and Cooch, E.G., 2019, Comparing ecological models, chap. 4 of Quantitative Analyses in Wildlife Science, p. 63-76.","productDescription":"14 p.","startPage":"63","endPage":"76","ipdsId":"IP-086981","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":368668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368667,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://jhupbooks.press.jhu.edu/title/quantitative-analyses-wildlife-science"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":773695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":773991,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70205905,"text":"70205905 - 2019 - κ0 and broadband site spectra in Southern California from source model-constrained inversion","interactions":[],"lastModifiedDate":"2019-10-09T12:39:08","indexId":"70205905","displayToPublicDate":"2019-09-10T12:35:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"κ0 and broadband site spectra in Southern California from source model-constrained inversion","docAbstract":"Ground-motion modeling requires accurate representation of the earthquake source, path, and site. Site amplification is often modeled by VS30, the time-averaged shear-wave velocity of the top 30 meters of the Earth’s surface, though recent studies find that its ability to accurately predict site effects varies. Another measure of the site is κ0, the attenuation of high frequency energy near the site (Anderson & Hough, 1984). We develop a novel application of the Andrews (1986) method to simultaneously invert the spectra of 3,357 earthquakes in Southern California into source and site components. These earthquakes have magnitudes 2.5 to 5.72 and were recorded on 16 stations for a total of 52,297 records. We constrain the inversion with an individual earthquake demonstrating the most Brune-like shape to preserve the site spectra. We then solve for κ0 site amplification at each station in three frequency bands: 1-6 Hz, 6-14 Hz, and 14-35 Hz. The resulting values of κ0 range from 0.017 seconds at ANZA station PFO to 0.059 seconds at ANZA station SND. We compare our results with values of site κ0 from other studies as well as site residuals from GMPEs. We find good agreement between our site κ0 and previous studies in the region. We find that κ0 and high frequency site amplification (14-35 Hz band) correlates well with independent site residuals, making it a good first-order approximation for the effects of site attenuation or amplification on ground motion.","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0120190037","usgsCitation":"Klimasewski, A., Sahakian, V., Baltay Sundstrom, A.S., Boatwright, J., Fletcher, J.P., and Baker, L., 2019, κ0 and broadband site spectra in Southern California from source model-constrained inversion: Bulletin of the Seismological Society of America, v. 109, no. 5, p. 1878-1889, https://doi.org/10.1785/0120190037.","productDescription":"12 p.","startPage":"1878","endPage":"1889","ipdsId":"IP-102984","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":368167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368166,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1785/0120190037"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.5849609375,\n 32.76880048488168\n ],\n [\n -113.4228515625,\n 32.76880048488168\n ],\n [\n -113.4228515625,\n 38.61687046392973\n ],\n [\n -124.5849609375,\n 38.61687046392973\n ],\n [\n -124.5849609375,\n 32.76880048488168\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"109","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Klimasewski, Alexis","contributorId":219664,"corporation":false,"usgs":false,"family":"Klimasewski","given":"Alexis","email":"","affiliations":[{"id":40043,"text":"U. 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Stocking was prioritized at four historically important spawning locations beginning in 1985, and coded wire tags (CWTs) were used to help evaluate performance. We used data from CWT fish captured in fishery-independent surveys from 1998 – 2014 to evaluate relative post-release survival of Lake Trout, estimated by catch-per-unit-effort and corrected for the number of fish stocked (CPUE), across 173 CWT tag lots of the 1994 – 2003 year classes stocked at these four locations. Boosted regression tree (BRT) models were used to assess the relative influence of four variables on Lake Trout CPUE in two age groups (age 4-5 years and 6-10 years) and paired with analyses of variance to test for statistical significance. Genetic strain (29.1%), stocking location (27.8%), mortality at release (23.1%) and predator density (19.9%) had similar influence on the relative survival of younger fish, whereas relative survival of older fish was heavily influenced by stocking location (79.8%). Survival of both age groups was lowest for fish stocked in the Northern Refuge, where the age structure was truncated due to fishery harvest and Sea Lamprey predation. Survival of stocked fish was higher at the Southern Refuge, Clay Banks, and Julian’s Reef, where mortality from sea lamprey and harvest was lower, and where increases in wild Lake Trout have been observed in recent years. Stocked Lake Michigan remnant genetic strains also appeared to survive better than strains from other lakes at these three locations, but strain effects could not be fully disentangled from effects of stocking location, and continued stocking of multiple genetic strains may provide resiliency toward future selection pressures. Continued progress toward rehabilitation will require reducing fishing and lamprey-induced mortality in northern Lake Michigan to build parental stocks of advanced ages as well as balancing efforts among competing management goals.","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10338","usgsCitation":"Kornis, M.S., Bronte, C.R., Holey, M.E., Hanson, S.D., Treska, T.J., Jonas, J.L., Madenjian, C.P., Claramunt, R.M., Robillard, S.R., Breidert, B., Donner, K.C., Lenart, S.J., Martell, A.W., McKee, P.C., and Olson, E., 2019, Factors affecting post-release survival of coded-wire tagged Lake Trout Salvelinus namaycush in Lake Michigan at four historical spawning locations: North American Journal of Fisheries Management, v. 39, no. 5, p. 868-895, https://doi.org/10.1002/nafm.10338.","productDescription":"28 p.","startPage":"868","endPage":"895","ipdsId":"IP-104527","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":367309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.88037109375,\n 46.10370875598026\n ],\n [\n -86.3525390625,\n 46.164614496897094\n ],\n [\n -87.51708984375,\n 45.90529985724799\n ],\n [\n -88.2861328125,\n 44.55916341529182\n ],\n [\n -88.04443359375,\n 43.88205730390537\n ],\n [\n -88.06640625,\n 42.84375132629021\n ],\n [\n -88.06640625,\n 41.86956082699455\n ],\n [\n -87.29736328125,\n 41.541477666790286\n ],\n [\n -86.66015624999999,\n 41.5579215778042\n ],\n [\n -86.0009765625,\n 42.24478535602799\n ],\n [\n -85.869140625,\n 42.87596410238256\n ],\n [\n -86.02294921875,\n 44.166444664458595\n ],\n [\n -85.84716796875,\n 44.449467536006935\n ],\n [\n -85.18798828125,\n 44.762336674810996\n ],\n [\n -84.7705078125,\n 45.166547157856016\n ],\n [\n -84.88037109375,\n 46.10370875598026\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Kornis, Matthew S.","contributorId":201252,"corporation":false,"usgs":false,"family":"Kornis","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":770502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bronte, Charles R.","contributorId":190727,"corporation":false,"usgs":false,"family":"Bronte","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":770503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holey, Mark E.","contributorId":212699,"corporation":false,"usgs":false,"family":"Holey","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":12428,"text":"U. 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Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":770506,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jonas, Jory L.","contributorId":215449,"corporation":false,"usgs":false,"family":"Jonas","given":"Jory","email":"","middleInitial":"L.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":770507,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":770501,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Claramunt, Randall M.","contributorId":190497,"corporation":false,"usgs":false,"family":"Claramunt","given":"Randall","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":770508,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Robillard, Steven R.","contributorId":218845,"corporation":false,"usgs":false,"family":"Robillard","given":"Steven","email":"","middleInitial":"R.","affiliations":[{"id":33955,"text":"Illinois Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":770509,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Breidert, Brian","contributorId":195539,"corporation":false,"usgs":false,"family":"Breidert","given":"Brian","email":"","affiliations":[{"id":34295,"text":"Indiana DNR","active":true,"usgs":false}],"preferred":false,"id":770510,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Donner, Kevin C.","contributorId":218846,"corporation":false,"usgs":false,"family":"Donner","given":"Kevin","email":"","middleInitial":"C.","affiliations":[{"id":39923,"text":"Little Traverse Bay Band of Odawa Indians","active":true,"usgs":false}],"preferred":false,"id":770511,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lenart, Stephen J.","contributorId":218847,"corporation":false,"usgs":false,"family":"Lenart","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":12428,"text":"U. 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Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":770512,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Martell, Archie W.","contributorId":218848,"corporation":false,"usgs":false,"family":"Martell","given":"Archie","email":"","middleInitial":"W.","affiliations":[{"id":34298,"text":"Little River Band of Ottawa Indians","active":true,"usgs":false}],"preferred":false,"id":770513,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McKee, Patrick C.","contributorId":218849,"corporation":false,"usgs":false,"family":"McKee","given":"Patrick","email":"","middleInitial":"C.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":770514,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Olson, Erik J.","contributorId":218850,"corporation":false,"usgs":false,"family":"Olson","given":"Erik J.","affiliations":[{"id":34297,"text":"Grand Traverse Band of Ottawa and Chippewa Indians","active":true,"usgs":false}],"preferred":false,"id":770515,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70210078,"text":"70210078 - 2019 - Hydrothermal fluid migration due to interaction with shallow magma: Insights from gravity changes before and after the 2015 eruption of Cotopaxi volcano, Ecuador","interactions":[],"lastModifiedDate":"2020-05-13T13:51:46.81254","indexId":"70210078","displayToPublicDate":"2019-09-10T08:45:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal fluid migration due to interaction with shallow magma: Insights from gravity changes before and after the 2015 eruption of Cotopaxi volcano, Ecuador","docAbstract":"On August 14, 2015 Cotopaxi Volcano (Ecuador) erupted with several phreatomagmatic explosions after nearly 135 years of quiescence. Unrest began in April 2015 with an increase in the number of daily seismic events and inflation of the flanks of the volcano. Time-lapse gravity measurements started at Cotopaxi volcano in June 2015. Although minor gravity changes were detected prior to eruptive activity, however, the largest gravity variations at Cotopaxi were measured between October 2015 and March 2016, when other geophysical parameters had reached background levels. Inverse modelling of GPS data suggests a deep intrusion prior to the eruptive activity, while inverse modelling of post-eruptive gravity changes suggests variations in the volcano hydrothermal system. Deformation, seismicity, and gravity changes are consistent with the intrusion of a deep magmatic source between April and August 2015. Part of the magma rose from depth and interacted with the hydrothermal system, causing the phreatomagmatic activity and pushing hydrothermal fluids from a deep aquifer into a shallow perched aquifer.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2019.106667","collaboration":"","usgsCitation":"Calahorrano-Di Patre, A., William-Jones, G., Battaglia, M., Mothes, P., Gaunt, E., Zurek, J., Ruiz, M., and Witter, J., 2019, Hydrothermal fluid migration due to interaction with shallow magma: Insights from gravity changes before and after the 2015 eruption of Cotopaxi volcano, Ecuador: Journal of Volcanology and Geothermal Research, v. 387, 106667, 19 p., https://doi.org/10.1016/j.jvolgeores.2019.106667.","productDescription":"106667, 19 p.","ipdsId":"IP-108094","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":374747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-80.30256,-3.40486],[-79.77029,-2.65751],[-79.98656,-2.22079],[-80.36878,-2.68516],[-80.96777,-2.24694],[-80.76481,-1.96505],[-80.93366,-1.05745],[-80.58337,-0.90666],[-80.39932,-0.2837],[-80.0209,0.36034],[-80.09061,0.76843],[-79.54276,0.98294],[-78.85526,1.38092],[-77.85506,0.80993],[-77.66861,0.82589],[-77.42498,0.39569],[-76.57638,0.25694],[-76.29231,0.41605],[-75.80147,0.0848],[-75.37322,-0.15203],[-75.23372,-0.91142],[-75.545,-1.56161],[-76.63539,-2.60868],[-77.8379,-3.00302],[-78.45068,-3.8731],[-78.6399,-4.54778],[-79.20529,-4.95913],[-79.62498,-4.4542],[-80.02891,-4.34609],[-80.44224,-4.42572],[-80.46929,-4.05929],[-80.18401,-3.82116],[-80.30256,-3.40486]]]},\"properties\":{\"name\":\"Ecuador\"}}]}","volume":"387","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Mothes, Patricia","contributorId":178532,"corporation":false,"usgs":false,"family":"Mothes","given":"Patricia","affiliations":[],"preferred":false,"id":789013,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Gaunt, Elizabeth","contributorId":224663,"corporation":false,"usgs":false,"family":"Gaunt","given":"Elizabeth","email":"","affiliations":[{"id":28071,"text":"Instituto Geofisico, Escuela Politecnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":789014,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Zurek, Jeffrey","contributorId":191169,"corporation":false,"usgs":false,"family":"Zurek","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":789015,"contributorType":{"id":2,"text":"Editors"},"rank":6},{"text":"Ruiz, Mario","contributorId":224427,"corporation":false,"usgs":false,"family":"Ruiz","given":"Mario","affiliations":[{"id":40882,"text":"Instituto Geofísico at the Escuela Politécnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":789016,"contributorType":{"id":2,"text":"Editors"},"rank":7},{"text":"Witter, Jeffery","contributorId":224664,"corporation":false,"usgs":false,"family":"Witter","given":"Jeffery","email":"","affiliations":[{"id":40906,"text":"Simon Fraser University, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":789017,"contributorType":{"id":2,"text":"Editors"},"rank":8}],"authors":[{"text":"Calahorrano-Di Patre, Antonina","contributorId":224661,"corporation":false,"usgs":false,"family":"Calahorrano-Di Patre","given":"Antonina","email":"","affiliations":[{"id":40906,"text":"Simon Fraser University, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":789010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"William-Jones, Glyn","contributorId":224662,"corporation":false,"usgs":false,"family":"William-Jones","given":"Glyn","email":"","affiliations":[{"id":40906,"text":"Simon Fraser University, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":789011,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Battaglia, Maurizio 0000-0003-4726-5287 mbattaglia@usgs.gov","orcid":"https://orcid.org/0000-0003-4726-5287","contributorId":204742,"corporation":false,"usgs":true,"family":"Battaglia","given":"Maurizio","email":"mbattaglia@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":789012,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mothes, Patricia","contributorId":178532,"corporation":false,"usgs":false,"family":"Mothes","given":"Patricia","affiliations":[],"preferred":false,"id":789034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaunt, Elizabeth","contributorId":224663,"corporation":false,"usgs":false,"family":"Gaunt","given":"Elizabeth","email":"","affiliations":[{"id":28071,"text":"Instituto Geofisico, Escuela Politecnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":789035,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zurek, Jeffrey","contributorId":191169,"corporation":false,"usgs":false,"family":"Zurek","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":789036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ruiz, Mario","contributorId":224427,"corporation":false,"usgs":false,"family":"Ruiz","given":"Mario","affiliations":[{"id":40882,"text":"Instituto Geofísico at the Escuela Politécnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":789037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Witter, Jeffery","contributorId":224664,"corporation":false,"usgs":false,"family":"Witter","given":"Jeffery","email":"","affiliations":[{"id":40906,"text":"Simon Fraser University, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":789038,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203786,"text":"sir20195058 - 2019 - Controls on spatial and temporal variations of brine discharge to the Dolores River in the Paradox Valley, Colorado, 2016–18","interactions":[],"lastModifiedDate":"2019-09-10T08:04:36","indexId":"sir20195058","displayToPublicDate":"2019-09-09T15:55:00","publicationYear":"2019","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":"2019-5058","displayTitle":"Controls on Spatial and Temporal Variations of Brine Discharge to the Dolores River in the Paradox Valley, Colorado, 2016–18","title":"Controls on spatial and temporal variations of brine discharge to the Dolores River in the Paradox Valley, Colorado, 2016–18","docAbstract":"The Paradox Valley in southwestern Colorado is a collapsed anticline formed by movement of the salt-rich Paradox Formation at the core of the anticline. The salinity of the Dolores River, a tributary of the Colorado River, increases substantially as it crosses the valley because of discharge of brine-rich groundwater derived from the underlying salts. Although the brine is naturally occurring, it increases the salinity of the Colorado River, which is a major concern to downstream agricultural, municipal, and industrial water users. The U.S. Geological Survey in cooperation with the Bureau of Reclamation conducted a study to improve the characterization of processes controlling spatial and temporal variations in brine discharge to the Dolores River. For the study, three geophysical surveys were conducted in March, May, and September 2017, and water levels were monitored in selected ponds and groundwater wells from November 2016 to May 2018. The study also utilized streamflow and specific conductance data from two U.S. Geological Survey streamflow-gaging stations on the Dolores River to estimate salt load to the river.
River-based continuous resistivity profiling and frequency domain electromagnetic induction surveys made during low-flow conditions indicated a zone of brine-rich groundwater close to the riverbed along an approximately 4-kilometer reach of the river. Under high-flow conditions, the brine was depressed as much as 2 meters below the riverbed, and brine discharge to the river was reduced to a minimum. Direct current electrical resistivity surveys show that the freshwater lens overlying the brine is much thicker (up to 10 meters) on the west bank than on the east bank (less than 5 meters). A large low-conductivity anomaly at river distance 6,800 meters was observed in all surveys and may represent a freshwater discharge zone or a losing reach of the river.
Filling and draining of the wildlife ponds on the west side of the river had a negligible effect on salt loads in the river during the study period. Groundwater monitoring showed there was active exchange of water between the river and the adjacent alluvial aquifer. When river stage was low, groundwater flowed towards the river, and brine discharge to the river increased. When the river stage was high, the gradient was reversed, and fresh surface water recharged the alluvial aquifer minimizing brine discharge. Most of the salt load to the river occurred during the winter and appeared to be enhanced by diurnal stage fluctuations.
A conceptual model of brine discharge to the river is presented at three scales. Groundwater at the regional scale drives dissolution of salt in the Paradox Formation and flow of brine into the base of the alluvial aquifer. Surface water–groundwater interactions at the scale of the alluvial aquifer control brine discharge to the river seasonally and interannually. At the finest scale, diurnal fluctuations in river stage drive exchange of freshwater with saltier pore water in the hyporheic zone, which appears to increase brine discharge to the river during winter.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195058","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Mast, M.A., and Terry, N., 2019, Controls on spatial and temporal variations of brine discharge to the Dolores River in the Paradox Valley, Colorado, 2016–18: U.S. Geological Survey Scientific Investigations Report 2019–5058, 25 p., https://doi.org/10.3133/sir20195058.\n","productDescription":"vi, 25 p.","onlineOnly":"Y","ipdsId":"IP-103865","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437347,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77080NB","text":"USGS data release","linkHelpText":"Raw Data from Continuous Resistivity Profiles and Electromagnetic Surveys Collected in and adjacent to the Dolores River in the Paradox Valley, Colorado (2017)"},{"id":367271,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5058/sir20195058.pdf","text":"Report","size":"6.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5058"},{"id":367270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5058/coverthb.jpg"}],"country":"United States","state":"Colorado","county":"Montrose County","otherGeospatial":"Paradox Valley","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-108.3772,38.6678],[-108.1472,38.6675],[-107.965,38.6664],[-107.9279,38.6661],[-107.9084,38.6664],[-107.8589,38.6663],[-107.8206,38.6664],[-107.7782,38.6661],[-107.7658,38.6663],[-107.741,38.6662],[-107.5011,38.6657],[-107.4992,38.6304],[-107.4989,38.6172],[-107.4992,38.5737],[-107.499,38.5356],[-107.4989,38.4717],[-107.4991,38.4531],[-107.4991,38.4504],[-107.4989,38.4445],[-107.4995,38.4404],[-107.4991,38.4246],[-107.4994,38.4096],[-107.4993,38.4033],[-107.4997,38.3656],[-107.4995,38.3248],[-107.4995,38.3008],[-107.5213,38.301],[-107.6333,38.3005],[-107.6358,38.3095],[-107.633,38.3172],[-107.6314,38.3223],[-107.6292,38.3286],[-107.6339,38.3286],[-107.6867,38.3288],[-107.7049,38.329],[-107.7236,38.3287],[-107.7964,38.329],[-107.8146,38.3292],[-107.8522,38.3291],[-107.8715,38.3293],[-107.9079,38.3292],[-107.9449,38.3295],[-107.9631,38.3296],[-108.0007,38.3304],[-108.0206,38.3305],[-108.1127,38.3312],[-108.1274,38.331],[-108.1276,38.3183],[-108.1165,38.3185],[-108.1163,38.3121],[-108.0987,38.312],[-108.0985,38.283],[-108.0815,38.2828],[-108.0807,38.2547],[-108.0085,38.2537],[-108.0084,38.2482],[-107.9814,38.2477],[-107.981,38.2328],[-107.9628,38.2326],[-107.9627,38.2263],[-107.9468,38.2265],[-107.9466,38.2184],[-107.9367,38.2185],[-107.9367,38.1732],[-107.946,38.1731],[-107.946,38.1517],[-107.9654,38.1519],[-108.0549,38.1522],[-108.2235,38.152],[-108.2411,38.1522],[-108.2587,38.1523],[-108.3336,38.1523],[-108.3506,38.1519],[-108.4641,38.1524],[-108.4841,38.1525],[-108.5397,38.1527],[-108.6304,38.153],[-108.6492,38.1531],[-109.041,38.1531],[-109.0409,38.1603],[-109.0607,38.2768],[-109.0608,38.3304],[-109.0608,38.3521],[-109.0607,38.378],[-109.0607,38.4052],[-109.0606,38.4197],[-109.0604,38.4555],[-109.0604,38.4637],[-109.0602,38.4981],[-109.0602,38.4991],[-108.6635,38.4992],[-108.3791,38.4999],[-108.3771,38.6116],[-108.3772,38.6678]]]},\"properties\":{\"name\":\"Montrose\",\"state\":\"CO\"}}]}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
Reduced connectivity created by artificial barriers can influence the genetic integrity of isolated subpopulations by reducing local population sizes and altering patterns of gene flow. We investigated the genetic impacts of one such barrier, the Prairie du Sac dam, Wisconsin, USA, using microsatellite data from six fish species with varying life history traits sampled above and below the dam. Contrary to many past studies in other systems, we did not detect any significant differences in genetic diversity between populations found above and below the Prairie du Sac dam. Our results also revealed low genetic differentiation (FST = 0–0.008) between populations above and below the dam for all species. In fact, we found that more genetic variation was partitioned among sampling years than between above and below dam populations for all but one of the species. Results from coalescent simulations designed to model our study system indicated that the genetic impacts of the dam will likely be detectable approximately 40–60 generations after the dam was constructed, and that it is possible to largely mitigate these impacts with a fish passage strategy that facilitates a migration rate of ≥ 1% between above and below dam populations. In summary, our findings suggest the genetic impacts of dams can be relatively minimal on short time scales, and that fish passage strategies can significantly reduce genetic impacts if designed appropriately.
Soil carbon has been measured for over a century in applications ranging from understanding biogeochemical processes in natural ecosystems to quantifying the productivity and health of managed systems. Consolidating diverse soil carbon datasets is increasingly important to maximize their value, particularly with growing anthropogenic and climate change pressures. In this progress report, we describe recent advances in soil carbon data led by the International Soil Carbon Network and other networks. We highlight priority areas of research requiring soil carbon data, including (a) quantifying boreal, arctic and wetland carbon stocks, (b) understanding the timescales of soil carbon persistence using radiocarbon and chronosequence studies, (c) synthesizing long-term and experimental data to inform carbon stock vulnerability to global change, (d) quantifying root influences on soil carbon and (e) identifying gaps in model–data integration. We also describe the landscape of soil datasets currently available, highlighting their strengths, weaknesses and synergies. Now more than ever, integrated soil data are needed to inform climate mitigation, land management and agricultural practices. This report will aid new data users in navigating various soil databases and encourage scientists to make their measurements publicly available and to join forces to find soil-related solutions.
","language":"English","publisher":"Sage","doi":"10.1177/0309133319873309","usgsCitation":"Avni Malhotra, Katherine Todd-Brown, Luke Nave, Batjes, N., Holmquist, J., Alison Hoyt, Colleen Iversen, Jackson, R.B., Lathja, K., Lawrence, C.R., Olga Vinduśková, Wieder, W., Williams, M., Gustaf Hugelias, and Harden, J., 2019, The landscape of soil carbon data: Emerging questions, synergies and databases: Progress in Physical Geography: Earth and Environment, v. 43, no. 5, p. 707-719, https://doi.org/10.1177/0309133319873309.","productDescription":"13 p.","startPage":"707","endPage":"719","ipdsId":"IP-106672","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":459890,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1564214","text":"External Repository"},{"id":367815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Avni Malhotra","contributorId":219292,"corporation":false,"usgs":false,"family":"Avni Malhotra","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":771920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katherine Todd-Brown","contributorId":219293,"corporation":false,"usgs":false,"family":"Katherine Todd-Brown","affiliations":[{"id":34255,"text":"Wilfred Laurier University","active":true,"usgs":false}],"preferred":false,"id":771921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luke Nave","contributorId":219294,"corporation":false,"usgs":false,"family":"Luke Nave","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":771922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Batjes, Niels","contributorId":219295,"corporation":false,"usgs":false,"family":"Batjes","given":"Niels","email":"","affiliations":[{"id":39988,"text":"ISRIC World Soil Information","active":true,"usgs":false}],"preferred":false,"id":771923,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holmquist, James","contributorId":217021,"corporation":false,"usgs":false,"family":"Holmquist","given":"James","email":"","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":771924,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alison Hoyt","contributorId":219296,"corporation":false,"usgs":false,"family":"Alison Hoyt","affiliations":[{"id":36389,"text":"Max Planck Institute","active":true,"usgs":false}],"preferred":false,"id":771925,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Colleen Iversen","contributorId":219297,"corporation":false,"usgs":false,"family":"Colleen Iversen","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":771926,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jackson, Robert B.","contributorId":177259,"corporation":false,"usgs":false,"family":"Jackson","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":771959,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lathja, Kate","contributorId":219298,"corporation":false,"usgs":false,"family":"Lathja","given":"Kate","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":771927,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lawrence, Corey R. 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202390,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":771919,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Olga Vinduśková","contributorId":219299,"corporation":false,"usgs":false,"family":"Olga Vinduśková","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":771928,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wieder, William","contributorId":202376,"corporation":false,"usgs":false,"family":"Wieder","given":"William","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":771929,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Williams, Matt","contributorId":219300,"corporation":false,"usgs":false,"family":"Williams","given":"Matt","email":"","affiliations":[{"id":25497,"text":"University of Edinburgh","active":true,"usgs":false}],"preferred":false,"id":771930,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gustaf Hugelias","contributorId":219301,"corporation":false,"usgs":false,"family":"Gustaf Hugelias","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":771931,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Harden, Jennifer","contributorId":219302,"corporation":false,"usgs":false,"family":"Harden","given":"Jennifer","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":771932,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70215101,"text":"70215101 - 2019 - Interferometric synthetic aperture radar study of recent eruptive activity at Shrub mud volcano, Alaska","interactions":[],"lastModifiedDate":"2020-10-07T20:05:21.607512","indexId":"70215101","displayToPublicDate":"2019-09-06T14:48:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Interferometric synthetic aperture radar study of recent eruptive activity at Shrub mud volcano, Alaska","docAbstract":"Shrub mud volcano is one of three large mud volcanoes that comprise the Klawasi Group in the Copper River Basin of southcentral Alaska. Except for minor discharges in the mid-1950s when the group was first described, Shrub was dormant prior to its reactivation in summer 1996. From 1997 to 1999, Shrub vigorously erupted more than 5 x 105 cubic meters of saline mud and carbon dioxide-rich gas at temperatures as high as 54 degrees C. Thereafter, activity waned but continued at least through 2015. We analyzed 192 interferograms derived from 106 synthetic aperture radar (SAR) images acquired by the JERS-1 (L-band), ERS-1/2 (C-band), RADARSAT-1 (C-band), and ALOS PALSAR (L-band) satellites to characterize ground deformation at Shrub before, during, and after its reactivation. Collectively, the interferograms span 1992–2000 and 2006–2011. We fit the observations with two deformation sources: a deflating, steeply dipping, pipe-like body under the summit area and an inflating, shallow-dipping, sill-like body under the southwest flank. Both sources are shallow, with centroids less than 1 km beneath the summit. Prior to reactivation, the flank source inflated ~0.35 x 105 cubic meters per year from July 1992 to May 1996. During eruptive activity, the summit source deflated at higher rates that peaked at ~8.71 x 105 cubic meters per year during May–November 1997 and continued at ~0.95 x 105 cubic meters per year during the 2006–2011 observation window. Cumulative source-volume loss is comparable to the volume of mud erupted. We interpret the summit source as the volcano’s feeder conduit that pressurized prior to the first SAR observation in 1992. Also before 1992, the conduit ruptured to feed a lateral intrusion of mud under the southwest flank, perhaps along a bedding plane in underlying glaciolacustrine deposits. The growing sill caused the southwest flank to inflate while it accommodated the mud supply from depth, which explains why we observed pre-eruptive inflation of the flank but not the summit. The summit began deflating when the conduit ruptured to the surface at the onset of eruptive activity. The flank source did not deflate concurrently because the weight of the thin overburden was insufficient to collapse the sill. There is a suggestion in the modern topography that lateral intrusions under Shrub’s southwest flank are a common feature of activity there.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2019.106671","usgsCitation":"Niu, Y., Dzurisin, D., and Lu, Z., 2019, Interferometric synthetic aperture radar study of recent eruptive activity at Shrub mud volcano, Alaska: Journal of Volcanology and Geothermal Research, v. 387, 106671 12p., https://doi.org/10.1016/j.jvolgeores.2019.106671.","productDescription":"106671 12p.","ipdsId":"IP-109278","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":379173,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2019.106671"},{"id":379196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Shrub Mud Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -145.2886962890625,\n 61.87169117378061\n ],\n [\n -144.5306396484375,\n 61.87169117378061\n ],\n [\n -144.5306396484375,\n 62.37509086856917\n ],\n [\n -145.2886962890625,\n 62.37509086856917\n ],\n [\n -145.2886962890625,\n 61.87169117378061\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"387","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Niu, Yufen","contributorId":242811,"corporation":false,"usgs":false,"family":"Niu","given":"Yufen","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":800868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dzurisin, Daniel 0000-0002-0138-5067 dzurisin@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-5067","contributorId":538,"corporation":false,"usgs":true,"family":"Dzurisin","given":"Daniel","email":"dzurisin@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":800869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, Zhong","contributorId":199794,"corporation":false,"usgs":false,"family":"Lu","given":"Zhong","affiliations":[],"preferred":false,"id":800870,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203995,"text":"pp1842H - 2019 - The effects of management practices on grassland birds—Marbled Godwit (Limosa fedoa)","interactions":[{"subject":{"id":70203995,"text":"pp1842H - 2019 - The effects of management practices on grassland birds—Marbled Godwit (Limosa fedoa)","indexId":"pp1842H","publicationYear":"2019","noYear":false,"chapter":"H","displayTitle":"The Effects of Management Practices on Grassland Birds—Marbled Godwit (Limosa fedoa)","title":"The effects of management practices on grassland birds—Marbled Godwit (Limosa fedoa)"},"predicate":"IS_PART_OF","object":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"id":1}],"isPartOf":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"lastModifiedDate":"2023-12-20T21:07:12.547889","indexId":"pp1842H","displayToPublicDate":"2019-09-06T10:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1842","chapter":"H","displayTitle":"The Effects of Management Practices on Grassland Birds—Marbled Godwit (Limosa fedoa)","title":"The effects of management practices on grassland birds—Marbled Godwit (Limosa fedoa)","docAbstract":"Keys to Marbled Godwit (Limosa fedoa) management include providing large expanses of short, sparsely to moderately vegetated landscapes that include native grasslands and wetland complexes. Optimal wetland complexes should contain a diversity of wetland classes and sizes, such as ephemeral, temporary, seasonal, semipermanent, permanent, and alkali wetlands, as well as intermittent streams. Marbled Godwits use wetlands of various salinities. The species has been reported to use habitats with less than or equal to 70 centimeters (cm) average vegetation height, 4–23 cm visual obstruction reading, and 1–9 cm litter depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842H","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Nenneman, M.P., and Euliss, B.R., 2019, The effects of management practices on grassland birds—Marbled Godwit (Limosa fedoa), chap. H of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 9 p., https://doi.org/10.3133/pp1842H.","productDescription":"iv, 9 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095156","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":366525,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/h/coverthb.jpg"},{"id":366526,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/h/pp1842h.pdf","text":"Report","size":"1.10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–H"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
The National Park Service (NPS) and the Bureau of Land Management (BLM) are concerned about cumulative effects of groundwater development on groundwater-dependent resources managed by, and other groundwater resources of interest to, these agencies in Snake Valley and adjacent areas, Utah and Nevada. Of particular concern to the NPS and BLM are withdrawals from all existing approved, perfected, certified, permitted, and vested groundwater rights in Snake Valley totaling about 55,272 acre-feet per year (acre-ft/yr), and from several senior water-right applications filed by the Southern Nevada Water Authority (SNWA) totaling 50,680 acre-ft/yr.
An existing groundwater-flow model of the eastern Great Basin was used to investigate where potential drawdown and capture of natural discharge is likely to result from potential groundwater withdrawals from existing groundwater rights in Snake Valley, and from groundwater withdrawals proposed in several applications filed by the SNWA. To evaluate the potential effects of the existing and proposed SNWA groundwater withdrawals, 11 withdrawal scenarios were simulated. All scenarios were run as steady state to estimate the ultimate long-term effects of the simulated withdrawals. This assessment provides a general understanding of the relative susceptibility of the groundwater resources of interest to the NPS and BLM, and the groundwater system in general, to existing and future groundwater development in the study area.
At the NPS and BLM groundwater resource sites of interest, simulated drawdown resulting from withdrawals based on existing approved, perfected, certified, permitted, and vested groundwater rights within Snake Valley ranged between 0 and 159 feet (ft) without accounting for irrigation return flow, and between 0 and 123 ft with accounting for irrigation return flow. With the addition of proposed SNWA withdrawals of 35,000 acre-ft/yr (equal to the Unallocated Groundwater portion allotted to Nevada in a draft interstate agreement), simulated drawdowns at the NPS and BLM sites of interest increased to range between 0 and 2,074 ft without irrigation return flow, and between 0 and 2,002 ft with irrigation return flow. With the addition of the proposed SNWA withdrawals of an amount equal to the full application amounts (50,680 acre-ft/yr), simulated drawdowns at the NPS and BLM sites of interest increased to range between 1 and 3,119 ft without irrigation return flow, and between 1 and 3,044 ft with irrigation return flow.
At the NPS and BLM groundwater resource sites of interest, simulated capture of natural discharge resulting from withdrawals based on existing groundwater rights in Snake Valley, both with and without irrigation return flow, ranged between 0 and 100 percent; simulated capture of 100 percent occurred at four sites. With the addition of proposed SNWA withdrawals of an amount equal to the Unallocated Groundwater portion allotted to Nevada in the draft interstate agreement, simulated capture of 100 percent occurred at nine additional sites without irrigation return flow, and at eight additional sites with irrigation return flow. With the addition of the proposed SNWA withdrawals of an amount equal to the full application amounts, simulated capture of 100 percent occurred at 11 additional sites without irrigation return flow, and at 9 additional sites with irrigation return flow.
The large simulated drawdowns produced in the scenarios that include large portions or all of the proposed SNWA withdrawals indicate that the groundwater system may not be able to support the amount of withdrawals from the proposed points of diversion (PODs) in the current SNWA water-right applications. Therefore, four additional scenarios were simulated where the withdrawal rates at the SNWA PODs were constrained by not allowing drawdowns to be deeper than the assumed depth of the PODs (about 2,000 ft). In the constrained scenarios, total withdrawals at the SNWA PODs were reduced to about 48 percent of the Unallocated Groundwater portion allotted to Nevada (35,000 acre-ft/yr reduced to 16,817 acre-ft/yr or 16,914 acre-ft/yr, without or with irrigation return flow, respectively), and about 44 percent of the full application amounts (50,680 acre-ft/yr reduced to 22,048 acre-ft/yr or 22,165 acre-ft/yr, without or with irrigation return flow, respectively). This indicates that the SNWA may need to add more PODs, or PODs in different locations, in order to withdraw large portions or all of the groundwater that has been applied for.
At the NPS and BLM groundwater resource sites of interest, simulated drawdown resulting from the addition of the constrained SNWA withdrawals applied to the Unallocated Groundwater amount ranged between 0 and 290 ft without irrigation return flow, and between 0 and 252 ft with irrigation return flow. With the addition of the constrained SNWA withdrawals applied to the full application amounts, simulated drawdowns at the NPS and BLM sites of interest ranged between 0 and 358 ft without irrigation return flow, and between 0 and 313 ft with irrigation return flow.
At the NPS and BLM groundwater resource sites of interest, with the addition of the constrained SNWA withdrawals applied to the Unallocated Groundwater amount, simulated capture of 100 percent of the natural discharge occurred at five additional sites without irrigation return flow, and at two additional sites with irrigation return flow (in addition to the four captured from existing water rights both with and without irrigation return flow). With the addition of the constrained SNWA withdrawals applied to the full application amounts, simulated capture of 100 percent occurred at six additional sites both with and without irrigation return flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191083","collaboration":"Prepared in cooperation with the National Park Service and the Bureau of Land Management","usgsCitation":"Masbruch, M.D., 2019, Numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada: U.S. Geological Survey Open-File Report 2019–1083, 49 p., https://doi.org/10.3133/ofr20191083.","productDescription":"Report: vi, 49 p.; Data Release","numberOfPages":"49","onlineOnly":"Y","ipdsId":"IP-103457","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":367115,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1083/coverthb_.jpg"},{"id":367116,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1083/ofr20191083.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1083"},{"id":367119,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LQDQGM","text":"Data Release","linkHelpText":"MODFLOW-2005 files for numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.48828125000001,\n 35.53222622770337\n ],\n [\n -110.302734375,\n 39.36827914916014\n ],\n [\n -110.12695312499999,\n 40.97989806962013\n ],\n [\n -111.005859375,\n 42.68243539838623\n ],\n [\n -114.78515624999999,\n 41.244772343082076\n ],\n [\n -117.59765625,\n 37.64903402157866\n ],\n [\n -115.48828125000001,\n 35.53222622770337\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
801-908-5000
Volcanism in Saudi Arabia includes a historic eruption close to the holy city of Al Madinah. As part of a volcanic hazard assessment of this area, magnetotelluric (MT) data were collected to investigate the structural setting, the distribution of melt within the crust, and the mantle source of volcanism. Interpretation of a new 3‐D resistivity model includes a shallow graben beneath thin lava fields (Harrats), a melt‐free upper crust, and decompression melting in the asthenosphere below thin lithosphere. Within the lower crust the model images elongate conductivity anomalies, one of which was attributed in a previous MT study to melt. The regional MT data, combined with perspective from geology and geophysical modeling, suggest the lower crust is anisotropic with no interconnected melt zones. These divergent interpretations have distinct hazard implications and highlight the importance of large survey aperture and anisotropic modeling to MT studies of volcanic regions. Lower‐crustal anisotropy extends beyond the Harrat, with the most conductive direction oriented N10°E and a factor of 3–5, determined from 2‐D anisotropic inversion, between the most and least conductive directions. The enhanced conductivity is likely due to interconnected grain boundary graphite, while the anisotropy direction reflects either frozen‐in fabric from Neoproterozoic stabilization of the Arabian Shield or modern ductile deformation driven by channelized asthenospheric flow coupled through a thin rigid mantle lid. Asthenospheric melt is interpreted to transect the crust primarily through diking, with limited melt storage and short residence times in the crust.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB017903","collaboration":"","usgsCitation":"Bedrosian, P.A., Peacock, J., Al-Dhahry, M.K., Shareef, A., Feucht, D., and Zahran, H.M., 2019, Crustal magmatism and anisotropy beneath the Arabian Shield - A cautionary tale: Journal of Geophysical Research B: Solid Earth, v. 124, no. 10, p. 10153-10179, https://doi.org/10.1029/2019JB017903.","productDescription":"27 p.","startPage":"10153","endPage":"10179","ipdsId":"IP-104561","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":374162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Saudi Arabia","otherGeospatial":"Arabian Shield","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 35.68359375,\n 27.605670826465445\n ],\n [\n 37.3095703125,\n 24.5271348225978\n ],\n [\n 39.15527343749999,\n 21.3303150734318\n ],\n [\n 41.3525390625,\n 18.145851771694467\n ],\n [\n 42.7587890625,\n 16.341225619207496\n ],\n [\n 42.978515625,\n 16.551961721972525\n ],\n [\n 44.1650390625,\n 18.521283325496277\n ],\n [\n 45.2197265625,\n 20.756113874762082\n ],\n [\n 43.3740234375,\n 23.40276490540795\n ],\n [\n 40.5615234375,\n 27.01998400798257\n ],\n [\n 35.68359375,\n 27.605670826465445\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"10","noUsgsAuthors":false,"publicationDate":"2019-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":787526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":787527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Dhahry, Maher K.","contributorId":224237,"corporation":false,"usgs":false,"family":"Al-Dhahry","given":"Maher","email":"","middleInitial":"K.","affiliations":[{"id":36695,"text":"Saudi Geological Survey","active":true,"usgs":false}],"preferred":true,"id":787528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shareef, Adel","contributorId":216214,"corporation":false,"usgs":false,"family":"Shareef","given":"Adel","email":"","affiliations":[{"id":36695,"text":"Saudi Geological Survey","active":true,"usgs":false}],"preferred":false,"id":787529,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feucht, D. W. 0000-0002-3672-4719","orcid":"https://orcid.org/0000-0002-3672-4719","contributorId":224277,"corporation":false,"usgs":false,"family":"Feucht","given":"D. W.","affiliations":[],"preferred":false,"id":787530,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zahran, Hani M. 0000-0002-0029-3822","orcid":"https://orcid.org/0000-0002-0029-3822","contributorId":203711,"corporation":false,"usgs":false,"family":"Zahran","given":"Hani","email":"","middleInitial":"M.","affiliations":[{"id":36695,"text":"Saudi Geological Survey","active":true,"usgs":false}],"preferred":true,"id":787531,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70204915,"text":"sir20195090 - 2019 - Tritium as an indicator of modern, mixed, and premodern groundwater age","interactions":[],"lastModifiedDate":"2019-09-05T09:14:28","indexId":"sir20195090","displayToPublicDate":"2019-09-05T10:00:00","publicationYear":"2019","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":"2019-5090","title":"Tritium as an indicator of modern, mixed, and premodern groundwater age","docAbstract":"Categorical classification of groundwater age is often used for the assessment and understanding of groundwater resources. This report presents a tritium-based age classification system for the conterminous United States based on tritium (3H) thresholds that vary in space and time: modern (recharged in 1953 or later), if the measured value is larger than an upper threshold; premodern (recharged prior to 1953) if the measured value is smaller than a lower threshold; or mixed if the measured value is between the two thresholds. Inclusion of spatially varying thresholds, rather than a single threshold, accounts for the observed systematic variation in 3H deposition across the United States. Inclusion of time-varying thresholds, rather than a single threshold, accounts for the date of sampling given the radioactive decay of 3H.
The efficacy of the tritium-based age classification system was evaluated at national and regional scales. The system was evaluated at a national scale by classifying samples from 1,788 public-supply wells distributed across 19 principal aquifers and comparing those results with expectations based on hydrogeologic principles. The regional-scale data are from five paired networks of shallow and deep wells (287 wells). As expected, modern groundwater is more prevalent in shallow wells than in deeper wells, in fractured-rock and carbonate aquifers as compared to clastic aquifers, in unconfined areas as compared to confined areas, and in humid climates as compared to arid climates. The results from a tritium-based age classification system compared favorably with the results of 14 previous studies of groundwater ages that used different age tracers and analytical methods. The wells and samples from the Cambrian-Ordovician aquifer that had been analyzed using a more complex multi-tracer analysis were also analyzed using the tritium-based age classification system, and there was a close match between the two methods. The results from these various studies suggest that the tritium-based age classification system may be informative as a screening tool prior to selecting more expensive and complex age-dating tracers and methods, or to provide an explanatory variable for other water-quality data where more complex methods or tracers are not available.
This work improves on previous groundwater age classification using 3H by developing methods that (1) determine 3H thresholds for groundwater recharged in 1953 or later that minimize the misclassification of modern samples as mixed; (2) determine a pre-1953 threshold to estimate premodern background concentrations; and (3) add a mixed category to classify samples that are clearly neither entirely modern nor entirely premodern. As with any tritium-based approach, it can fail when the 3H record in precipitation does not accurately reflect the record of 3H in recharge
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195090","usgsCitation":"Lindsey, B.D., Jurgens, B.C., and Belitz, K., 2019, Tritium as an indicator of modern, mixed, and premodern groundwater age: U.S. Geological Survey Scientific Investigations Report 2019–5090, 18 p., https://doi.org/10.3133/sir20195090.","productDescription":"vii, 18 p.","onlineOnly":"Y","ipdsId":"IP-097386","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes 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U.S. Geological Survey
2201 Sunrise Valley Drive, MS 413
Reston, VA 20192-0002
Species distributions are determined by the interaction of multiple biotic and abiotic factors, which produces complex spatial and temporal patterns of occurrence. As habitats and climate change due to anthropogenic activities, there is a need to develop species distribution models that can quantify these complex range dynamics. In this paper, we develop a dynamic occupancy model that uses a spatial generalized additive model to estimate non-linear spatial variation in occupancy not accounted for by environmental covariates. The model is flexible and can accommodate data from a range of sampling designs that provide information about both occupancy and detection probability. Output from the model can be used to create distribution maps and to estimate indices of temporal range dynamics. We demonstrate the utility of this approach by modeling long-term range dynamics of 10 eastern North American birds using data from the North American Breeding Bird Survey. We anticipate this framework will be particularly useful for modeling species’ distributions over large spatial scales and for quantifying range dynamics over long temporal scales.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-48851-5","usgsCitation":"Rushing, C.S., Royle, J.A., Ziolkowski, D., and Pardieck, K.L., 2019, Modeling spatially and temporally complex range dynamics when detection is imperfect: Scientific Reports, v. 9, 12805, 9 p., https://doi.org/10.1038/s41598-019-48851-5.","productDescription":"12805, 9 p.","ipdsId":"IP-098777","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":459911,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-48851-5","text":"Publisher Index Page"},{"id":367307,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Rushing, Clark S. 0000-0002-9283-6563","orcid":"https://orcid.org/0000-0002-9283-6563","contributorId":218851,"corporation":false,"usgs":true,"family":"Rushing","given":"Clark","email":"","middleInitial":"S.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":true,"id":770529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":770530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziolkowski, David 0000-0002-2500-4417 dziolkowski@usgs.gov","orcid":"https://orcid.org/0000-0002-2500-4417","contributorId":195409,"corporation":false,"usgs":true,"family":"Ziolkowski","given":"David","email":"dziolkowski@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":770531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":770532,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204783,"text":"ofr20191091 - 2019 - Evaluation of groundwater-flow models for estimating drawdown from proposed groundwater development in Tule Desert, Nevada","interactions":[],"lastModifiedDate":"2019-09-17T18:18:38","indexId":"ofr20191091","displayToPublicDate":"2019-09-05T09:37:47","publicationYear":"2019","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":"2019-1091","displayTitle":"Evaluation of Groundwater-Flow Models for Estimating Drawdown from Proposed Groundwater Development in Tule Desert, Nevada","title":"Evaluation of groundwater-flow models for estimating drawdown from proposed groundwater development in Tule Desert, Nevada","docAbstract":"At the request of the Bureau of Land Management (BLM), the U.S. Geological Survey (USGS) is releasing with this open-file report (OFR) a previously unpublished review and comparison of two numerical models for Tule Desert, Nevada. The original review was performed in spring 2013, and only minor editorial revisions were made in the current (2019) OFR for clarity and to reformat the original interagency correspondence to the USGS OFR template. No revisions have been made to the technical content of the original review for this OFR release. Report content presented in the purpose and scope statement, and all subsequent sections of the OFR, are original content submitted to BLM in May 2013. Model review and comparisons described in the following paragraphs are based on, in part, results of a long-term (more than 2 years) aquifer test mandated by Nevada State Engineer Order 1169. Additional information on Order 1169 and associated aquifer test results can be found at the State of Nevada Division of Water Resources website (State of Nevada, 2019).
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819