The probability distribution of far-field tsunami amplitudes is explained in relation to the distribution of seismic moment at subduction zones. Tsunami amplitude distributions at tide gauge stations follow a similar functional form, well described by a tapered Pareto distribution that is parameterized by a power-law exponent and a corner amplitude. Distribution parameters are first established for eight tide gauge stations in the Pacific, using maximum likelihood estimation. A procedure is then developed to reconstruct the tsunami amplitude distribution that consists of four steps: (1) define the distribution of seismic moment at subduction zones; (2) establish a source-station scaling relation from regression analysis; (3) transform the seismic moment distribution to a tsunami amplitude distribution for each subduction zone; and (4) mix the transformed distribution for all subduction zones to an aggregate tsunami amplitude distribution specific to the tide gauge station. The tsunami amplitude distribution is adequately reconstructed for four tide gauge stations using globally constant seismic moment distribution parameters established in previous studies. In comparisons to empirical tsunami amplitude distributions from maximum likelihood estimation, the reconstructed distributions consistently exhibit higher corner amplitude values, implying that in most cases, the empirical catalogs are too short to include the largest amplitudes. Because the reconstructed distribution is based on a catalog of earthquakes that is much larger than the tsunami catalog, it is less susceptible to the effects of record-breaking events and more indicative of the actual distribution of tsunami amplitudes.
","language":"English","publisher":"Springer","doi":"10.1007/s00024-016-1288-x","usgsCitation":"Geist, E.L., and Parsons, T.E., 2016, Reconstruction of far-field tsunami amplitude distributions from earthquake sources: Pure and Applied Geophysics, v. 173, no. 12, p. 3703-3717, https://doi.org/10.1007/s00024-016-1288-x.","productDescription":"15 p.","startPage":"3703","endPage":"3717","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072794","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan, United States","state":"Hawaii","city":"Crescent City, Hilo, Kahului, Kushimoto, Mera, Nawiliwili, San Diego, San Francisco","volume":"173","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-30","publicationStatus":"PW","scienceBaseUri":"572c609ce4b09acee752ef92","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":628835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":628836,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170799,"text":"70170799 - 2016 - Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture","interactions":[],"lastModifiedDate":"2018-09-12T17:04:25","indexId":"70170799","displayToPublicDate":"2016-05-05T11:45:00","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":"Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture","docAbstract":"Animal waste, stream water, and streambed sediment from 19 small (< 32 km2) watersheds in 12 U.S. states having either no major animal agriculture (control, n = 4), or predominantly beef (n = 4), dairy (n = 3), swine (n = 5), or poultry (n = 3) were tested for: 1) cholesterol, coprostanol, estrone, and fecal indicator bacteria (FIB) concentrations, and 2) shiga-toxin producing and enterotoxigenic Escherichia coli, Salmonella, Campylobacter, and pathogenic and vancomycin-resistant enterococci by polymerase chain reaction (PCR) on enrichments, and/or direct quantitative PCR. Pathogen genes were most frequently detected in dairy wastes, followed by beef, swine and poultry wastes in that order; there was only one detection of an animal-source-specific pathogen gene (stx1) in any water or sediment sample in any control watershed. Post-rainfall pathogen gene numbers in stream water were significantly correlated with FIB, cholesterol and coprostanol concentrations, and were most highly correlated in dairy watershed samples collected from 3 different states. Although collected across multiple states and ecoregions, animal-waste gene profiles were distinctive via discriminant analysis. Stream water gene profiles could also be discriminated by the watershed animal type. Although pathogen genes were not abundant in stream water or streambed samples, PCR on enrichments indicated that many genes were from viable organisms, including several (shiga-toxin producing or enterotoxigenic E. coli, Salmonella, vancomycin-resistant enterococci) that could potentially affect either human or animal health. Pathogen gene numbers and types in stream water samples were influenced most by animal type, by local factors such as whether animals had stream access, and by the amount of local rainfall, and not by studied watershed soil or physical characteristics. Our results indicated that stream water in small agricultural U.S. watersheds was susceptible to pathogen gene inputs under typical agricultural practices and environmental conditions. Pathogen gene profiles may offer the potential to address both source of, and risks associated with, fecal pollution.
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The 3 publications differ in scope, methodology, and resulting estimates. We compare and contrast characteristics of the approaches used in the publications. In addition, we describe decisions made in obtaining the estimates that were produced. Despite variation in the 3 approaches, resulting estimates were reasonably similar; about a quarter- to a half-million birds are killed per year by colliding with wind turbines.
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America\"}}]}","volume":"10","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572dc02fe4b0dae0d5d8f067","contributors":{"authors":[{"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":628843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loss, Scott R.","contributorId":140471,"corporation":false,"usgs":false,"family":"Loss","given":"Scott R.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":628844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smallwood, K. Shawn","contributorId":25899,"corporation":false,"usgs":true,"family":"Smallwood","given":"K.","email":"","middleInitial":"Shawn","affiliations":[],"preferred":false,"id":628845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Wallace P.","contributorId":78627,"corporation":false,"usgs":true,"family":"Erickson","given":"Wallace","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":628846,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170861,"text":"70170861 - 2016 - Modeling suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in North and South America’s coastal waters","interactions":[],"lastModifiedDate":"2016-07-07T10:09:23","indexId":"70170861","displayToPublicDate":"2016-05-05T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Modeling suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in North and South America’s coastal waters","docAbstract":"We used two common correlative species-distribution models to predict suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in the western Atlantic and eastern Pacific Oceans. The Generalized Linear Model (GLM) and the Maximum Entropy (Maxent) model were applied using the Software for Assisted Habitat Modeling. We compared models developed using native occurrences, using non-native occurrences, and using both native and non-native occurrences. Models were trained using occurrence data collected before 2010 and evaluated with occurrence data collected from the invaded range during or after 2010. We considered a total of 22 marine environmental variables. Models built with non-native only or both native and non-native occurrence data outperformed those that used only native occurrences. Evaluation metrics based on the independent test data were highest for models that used both native and non-native occurrences. Bathymetry was the strongest environmental predictor for all models and showed increasing suitability as ocean floor depth decreased, with salinity ranking the second strongest predictor for models that used native and both native and non-native occurrences, indicating low habitat suitability for salinities <30. Our model results also suggest that red lionfish could continue to invade southern latitudes in the western Atlantic Ocean and may establish localized populations in the eastern Pacific Ocean. We reiterate the importance in the choice of the training data source (native, non-native, or native/non-native) used to develop correlative species distribution models for invasive species.
\nLikelihood testing of induced earthquakes in Oklahoma and Kansas has identified the parameters that optimize the forecasting ability of smoothed seismicity models and quantified the recent temporal stability of the spatial seismicity patterns. Use of the most recent 1-year period of earthquake data and use of 10–20-km smoothing distances produced the greatest likelihood. The likelihood that the locations of January–June 2015 earthquakes were consistent with optimized forecasts decayed with increasing elapsed time between the catalogs used for model development and testing. Likelihood tests with two additional sets of earthquakes from 2014 exhibit a strong sensitivity of the rate of decay to the smoothing distance. Marked reductions in likelihood are caused by the nonstationarity of the induced earthquake locations. Our results indicate a multiple-fold benefit from smoothed seismicity models in developing short-term earthquake rate forecasts for induced earthquakes in Oklahoma and Kansas, relative to the use of seismic source zones.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016GL068948","usgsCitation":"Moschetti, M.P., Hoover, S.M., and Mueller, C., 2016, Likelihood testing of seismicity-based rate forecasts of induced earthquakes in Oklahoma and Kansas: Geophysical Research Letters, v. 43, no. 10, p. 4913-4921, https://doi.org/10.1002/2016GL068948.","productDescription":"9 p.","startPage":"4913","endPage":"4921","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075465","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471020,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068948","text":"Publisher Index Page"},{"id":321014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.537109375,\n 33.58716733904656\n ],\n [\n -97.679443359375,\n 33.61461929233378\n ],\n [\n -99.38232421875,\n 36.53612263184686\n ],\n [\n -99.51416015625,\n 37.00255267215955\n ],\n [\n -98.41552734375,\n 37.413800350662875\n ],\n [\n -97.3828125,\n 37.54457732085582\n ],\n [\n -95.592041015625,\n 35.16482750605027\n ],\n [\n -95.537109375,\n 33.58716733904656\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-18","publicationStatus":"PW","scienceBaseUri":"572dc04ee4b0dae0d5d8f207","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":628863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoover, Susan M. 0000-0002-8682-6668 shoover@usgs.gov","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":5715,"corporation":false,"usgs":true,"family":"Hoover","given":"Susan","email":"shoover@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":628864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":628865,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176578,"text":"70176578 - 2016 - Integrating early detection with DNA barcoding: species identification of a non-native monitor lizard (Squamata: Varanidae) carcass in Mississippi, U.S.A. ","interactions":[],"lastModifiedDate":"2016-09-21T16:15:13","indexId":"70176578","displayToPublicDate":"2016-05-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Integrating early detection with DNA barcoding: species identification of a non-native monitor lizard (Squamata: Varanidae) carcass in Mississippi, U.S.A. ","docAbstract":"It is commonly recognized that suspended-sediment concentrations in rivers can change rapidly in time and independently of water discharge during important sediment‑transporting events (for example, during floods); thus, suspended-sediment measurements at closely spaced time intervals are necessary to characterize suspended‑sediment loads. Because the manual collection of sufficient numbers of suspended-sediment samples required to characterize this variability is often time and cost prohibitive, several “surrogate” techniques have been developed for in situ measurements of properties related to suspended-sediment characteristics (for example, turbidity, laser-diffraction, acoustics). Herein, we present a new physically based method for the simultaneous measurement of suspended-silt-and-clay concentration, suspended-sand concentration, and suspended‑sand median grain size in rivers, using multi‑frequency arrays of single-frequency side‑looking acoustic-Doppler profilers. The method is strongly grounded in the extensive scientific literature on the incoherent scattering of sound by random suspensions of small particles. In particular, the method takes advantage of theory that relates acoustic frequency, acoustic attenuation, acoustic backscatter, suspended-sediment concentration, and suspended-sediment grain-size distribution. We develop the theory and methods, and demonstrate the application of the method at six study sites on the Colorado River and Rio Grande, where large numbers of suspended-sediment samples have been collected concurrently with acoustic attenuation and backscatter measurements over many years. The method produces acoustical measurements of suspended-silt-and-clay and suspended-sand concentration (in units of mg/L), and acoustical measurements of suspended-sand median grain size (in units of mm) that are generally in good to excellent agreement with concurrent physical measurements of these quantities in the river cross sections at these sites. In addition, detailed, step-by-step procedures are presented for the general river application of the method.
Quantification of errors in sediment-transport measurements made using this acoustical method is essential if the measurements are to be used effectively, for example, to evaluate uncertainty in long-term sediment loads and budgets. Several types of error analyses are presented to evaluate (1) the stability of acoustical calibrations over time, (2) the effect of neglecting backscatter from silt and clay, (3) the bias arising from changes in sand grain size, (4) the time-varying error in the method, and (5) the influence of nonrandom processes on error. Results indicate that (1) acoustical calibrations can be stable for long durations (multiple years), (2) neglecting backscatter from silt and clay can result in unacceptably high bias, (3) two frequencies are likely required to obtain sand-concentration measurements that are unbiased by changes in grain size, depending on site-specific conditions and acoustic frequency, (4) relative errors in silt-and-clay- and sand-concentration measurements decrease substantially as concentration increases, and (5) nonrandom errors may arise from slow changes in the spatial structure of suspended sediment that affect the relations between concentration in the acoustically ensonified part of the cross section and concentration in the entire river cross section. Taken together, the error analyses indicate that the two-frequency method produces unbiased measurements of suspended-silt-and-clay and sand concentration, with errors that are similar to, or larger than, those associated with conventional sampling methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1823","usgsCitation":"Topping, D.J., and Wright, S.A., 2016, Long-term continuous acoustical suspended-sediment measurements in rivers—Theory, application, bias, and error: U.S. Geological Survey Professional Paper 1823, 98 p.,\nhttps://dx.doi.org/10.3133/pp1823.","productDescription":"xii, 97 p.","numberOfPages":"114","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062803","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":320792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1823/coverthb.jpg"},{"id":320827,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1823/pp1823.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1823 Report PDF"}],"country":"United States","state":"Arizona, Texas","otherGeospatial":"Colorado River, Grand Canyon National Park; Rio Grande, Big Bend National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5384521484375,\n 36.01578220325809\n ],\n [\n -112.5384521484375,\n 36.41907231092499\n ],\n [\n -111.86553955078124,\n 36.41907231092499\n ],\n [\n -111.86553955078124,\n 36.01578220325809\n ],\n [\n -112.5384521484375,\n 36.01578220325809\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.76174926757812,\n 28.96489485992114\n ],\n [\n -103.76174926757812,\n 29.410890376109\n ],\n [\n -102.82241821289062,\n 29.410890376109\n ],\n [\n -102.82241821289062,\n 28.96489485992114\n ],\n [\n -103.76174926757812,\n 28.96489485992114\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
http://sbsc.wr.usgs.gov/
","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-05-04","noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f7","contributors":{"authors":[{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":715,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":626542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626543,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169399,"text":"ofr20161054 - 2016 - Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","interactions":[],"lastModifiedDate":"2016-05-04T15:49:10","indexId":"ofr20161054","displayToPublicDate":"2016-05-04T15:15:00","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":"2016-1054","title":"Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","docAbstract":"
The Storm 3 is a browser-based data logger manufactured by WaterLOG/Xylem Incorporated that operates over a temperature range of −40 to 60 degrees Celsius (°C). A Storm logger with no built-in telemetry (Storm3-00) and a logger with built-in cellular modem (Storm3-03) were evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to the manufacturer’s specifications with bench tests, for recording data over the device’s operating temperature range with temperature chamber tests, and for field performance with an outdoor deployment test.
\nThe procedures followed and the results obtained from the testing are described in this publication. The device met most of the manufacturer’s stated specifications. An exception was power consumption, which was about 10 percent above the manufacturer’s specifications. It was also observed that enabling WiFi doubles the Storm 3’s power consumption. In addition, several logging errors were made by two units during deployment testing, but it could not be determined whether these errors were the fault of the Storm or of an attached sensor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161054","usgsCitation":"Kunkle, G.A., 2016, Evaluation of the Storm 3 data logger manufactured by Waterlog/Xylem Incorporated—Results of Bench, Temperature, and Field Deployment Testing: U.S. Geological Survey Open-File Report 2016–1054, 9 p., https://dx.doi.org/10.3133/ofr20161054.","productDescription":"iii, 9 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069059","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":320970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1054/ofr20161054.pdf","text":"Report","size":"373 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1054"},{"id":320969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1054/coverthb.jpg","description":"OFR 2016-1054"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
Although initially viewed as oases within a barren deep ocean, hydrothermal vent and methane seep communities are now recognized to interact with surrounding ecosystems on the sea floor and in the water column, and to affect global geochemical cycles. The importance of understanding these interactions is growing as the potential rises for disturbance from oil and gas extraction, seabed mining and bottom trawling. Here we synthesize current knowledge of the nature, extent and time and space scales of vent and seep interactions with background systems. We document an expanded footprint beyond the site of local venting or seepage with respect to elemental cycling and energy flux, habitat use, trophic interactions, and connectivity. Heat and energy are released, global biogeochemical and elemental cycles are modified, and particulates are transported widely in plumes. Hard and biotic substrates produced at vents and seeps are used by “benthic background” fauna for attachment substrata, shelter, and access to food via grazing or through position in the current, while particulates and fluid fluxes modify planktonic microbial communities. Chemosynthetic production provides nutrition to a host of benthic and planktonic heterotrophic background species through multiple horizontal and vertical transfer pathways assisted by flow, gamete release, animal movements, and succession, but these pathways remain poorly known. Shared species, genera and families indicate that ecological and evolutionary connectivity exists among vents, seeps, organic falls and background communities in the deep sea; the genetic linkages with inactive vents and seeps and background assemblages however, are practically unstudied. The waning of venting or seepage activity generates major transitions in space and time that create links to surrounding ecosystems, often with identifiable ecotones or successional stages. The nature of all these interactions is dependent on water depth, as well as regional oceanography and biodiversity. Many ecosystem services are associated with the interactions and transitions between chemosynthetic and background ecosystems, for example carbon cycling and sequestration, fisheries production, and a host of non-market and cultural services. The quantification of the sphere of influence of vents and seeps could be beneficial to better management of deep-sea environments in the face of growing industrialization.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2016.00072","usgsCitation":"Levin, L.A., Baco, A., Bowden, D., Colaco, A., Cordes, E.E., Cunha, M., Demopoulos, A.W., Gobin, J., Grupe, B., Le, J., Metaxas, A., Netburn, A., Rouse, G., Thurber, A., Tunnicliffe, V., Van Dover, C., Vanreusel, A., and Watling, L., 2016, Hydrothermal vents and methane seeps: Rethinking the sphere of influence: Frontiers in Marine Science, v. 3, art72: 23 p., https://doi.org/10.3389/fmars.2016.00072.","productDescription":"art72: 23 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073011","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471022,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2016.00072","text":"Publisher Index Page"},{"id":320952,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-19","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f4","contributors":{"authors":[{"text":"Levin, Lisa A.","contributorId":12372,"corporation":false,"usgs":true,"family":"Levin","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":628684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baco, Amy","contributorId":120023,"corporation":false,"usgs":true,"family":"Baco","given":"Amy","email":"","affiliations":[],"preferred":false,"id":628685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowden, David","contributorId":10864,"corporation":false,"usgs":true,"family":"Bowden","given":"David","email":"","affiliations":[],"preferred":false,"id":628686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colaco, Ana","contributorId":169152,"corporation":false,"usgs":false,"family":"Colaco","given":"Ana","email":"","affiliations":[{"id":25423,"text":"Univ. of the Azores","active":true,"usgs":false}],"preferred":false,"id":628687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":628688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cunha, Marina","contributorId":169153,"corporation":false,"usgs":false,"family":"Cunha","given":"Marina","email":"","affiliations":[{"id":25424,"text":"Univ. de Aveiro","active":true,"usgs":false}],"preferred":false,"id":628689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":628683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gobin, Judith","contributorId":169154,"corporation":false,"usgs":false,"family":"Gobin","given":"Judith","email":"","affiliations":[{"id":25425,"text":"Univ. West Indies","active":true,"usgs":false}],"preferred":false,"id":628690,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Grupe, Ben","contributorId":169155,"corporation":false,"usgs":false,"family":"Grupe","given":"Ben","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628691,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Le, Jennifer","contributorId":169163,"corporation":false,"usgs":false,"family":"Le","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":628692,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Metaxas, Anna","contributorId":169156,"corporation":false,"usgs":false,"family":"Metaxas","given":"Anna","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":628693,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Netburn, Amanda","contributorId":169157,"corporation":false,"usgs":false,"family":"Netburn","given":"Amanda","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628694,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rouse, Greg","contributorId":169158,"corporation":false,"usgs":false,"family":"Rouse","given":"Greg","email":"","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628695,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thurber, Andrew","contributorId":169159,"corporation":false,"usgs":false,"family":"Thurber","given":"Andrew","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":628696,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tunnicliffe, Verena","contributorId":169160,"corporation":false,"usgs":false,"family":"Tunnicliffe","given":"Verena","email":"","affiliations":[{"id":25427,"text":"Univ. of Victoria","active":true,"usgs":false}],"preferred":false,"id":628697,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Van Dover, Cindy L.","contributorId":95341,"corporation":false,"usgs":true,"family":"Van Dover","given":"Cindy L.","affiliations":[],"preferred":false,"id":628698,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Vanreusel, Ann","contributorId":169161,"corporation":false,"usgs":false,"family":"Vanreusel","given":"Ann","email":"","affiliations":[{"id":25428,"text":"Ghent Univ.","active":true,"usgs":false}],"preferred":false,"id":628699,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Watling, Les","contributorId":54755,"corporation":false,"usgs":false,"family":"Watling","given":"Les","email":"","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":628714,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70170821,"text":"70170821 - 2016 - Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","interactions":[],"lastModifiedDate":"2016-07-28T10:53:13","indexId":"70170821","displayToPublicDate":"2016-05-04T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":904,"text":"Arid Land Research and Management","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","docAbstract":"Dune destabilization and increased mobility is a worldwide issue causing ecological, economic, and health problems for the inhabitants of areas with extensive dune fields. Dunes cover nearly a third of the Navajo Nation within the Colorado Plateau of southwestern USA. There, higher temperatures and prolonged drought beginning in 1996 have produced significant increases in dune mobility. Vegetation plays an important role in dune stabilization, but there are few studies of the plants of the aeolian surfaces of this region. We examined plant species and their attributes within a moderately vegetated dune field of the Navajo Nation to understand the types and characteristics of plants that stabilize rangeland dunes. These dunes supported a low cover of mixed grass-scrubland with fifty-two perennial and annual species including extensive occurrence of non-native annual Salsola spp. Perennial grass richness and shrub cover were positively associated with increased soil sand composition. Taprooted shrubs were more common on sandier substrates. Most dominant grasses had C4 photosynthesis, suggestive of higher water-use efficiencies and growth advantage in warm arid environments. Plant cover was commonly below the threshold of dune stabilization. Increasing sand movement with continued aridity will select for plants adapted to burial, deflation, and abrasion. The study indicates plants tolerant of increased sand mobility and burial but more investigation is needed to identify the plants adapted to establish and regenerate under these conditions. In addition, the role of Salsola spp. in promoting decline of perennial grasses and shrubs needs clarification.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15324982.2016.1138157","usgsCitation":"Thomas, K.A., and Redsteer, M.H., 2016, Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA: Arid Land Research and Management, v. 30, no. 4, p. 400-411, https://doi.org/10.1080/15324982.2016.1138157.","productDescription":"12 p.","startPage":"400","endPage":"411","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063167","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":502595,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":320950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Navajo Nation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.3134765625,\n 34.56085936708387\n ],\n [\n -111.3134765625,\n 38.22091976683121\n ],\n [\n -107.29248046875,\n 38.22091976683121\n ],\n [\n -107.29248046875,\n 34.56085936708387\n ],\n [\n -111.3134765625,\n 34.56085936708387\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"572b0f1ce4b0b13d391a8407","contributors":{"authors":[{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Redsteer, Margaret H.","contributorId":9123,"corporation":false,"usgs":true,"family":"Redsteer","given":"Margaret","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":628555,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170814,"text":"70170814 - 2016 - Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","interactions":[],"lastModifiedDate":"2016-05-04T10:03:24","indexId":"70170814","displayToPublicDate":"2016-05-04T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","docAbstract":"Estuarine navigation channels have long been recognized as conduits for saltwater intrusion into coastal wetlands. Salt flux decomposition and time series measurements of velocity and salinity were used to examine salt flux components and drivers of baroclinic and barotropic exchange in the Houma Navigation Channel, an estuarine channel located in the Mississippi River delta plain that receives substantial freshwater inputs from the Mississippi-Atchafalaya River system at its inland extent. Two modes of vertical current structure were identified from the time series data. The first mode, accounting for 90% of the total flow field variability, strongly resembled a barotropic current structure and was coherent with alongshelf wind stress over the coastal Gulf of Mexico. The second mode was indicative of gravitational circulation and was linked to variability in tidal stirring and the horizontal salinity gradient along the channel’s length. Tidal oscillatory salt flux was more important than gravitational circulation in transporting salt upestuary, except over equatorial phases of the fortnightly tidal cycle during times when river inflows were minimal. During all tidal cycles sampled, the advective flux, driven by a combination of freshwater discharge and wind-driven changes in storage, was the dominant transport term, and net flux of salt was always out of the estuary. These findings indicate that although human-made channels can effectively facilitate inland intrusion of saline water, this intrusion can be minimized or even reversed when they are subject to significant freshwater inputs.
","language":"English","publisher":"MDPI","doi":"10.3390/w8050184","usgsCitation":"Snedden, G., 2016, Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain: Water, v. 8, no. 5, Article 184: 15 p., https://doi.org/10.3390/w8050184.","productDescription":"Article 184: 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069649","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8050184","text":"Publisher Index Page"},{"id":320948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Houma Navigation Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.74844360351562,\n 29.216904948184734\n ],\n [\n -90.74844360351562,\n 29.58898286696141\n ],\n [\n -90.604248046875,\n 29.58898286696141\n ],\n [\n -90.604248046875,\n 29.216904948184734\n ],\n [\n -90.74844360351562,\n 29.216904948184734\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-30","publicationStatus":"PW","scienceBaseUri":"572b0f19e4b0b13d391a83ec","contributors":{"authors":[{"text":"Snedden, Gregg 0000-0001-7821-3709 sneddeng@usgs.gov","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":140235,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","email":"sneddeng@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":628526,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70170954,"text":"70170954 - 2016 - Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California","interactions":[],"lastModifiedDate":"2016-05-13T09:18:39","indexId":"70170954","displayToPublicDate":"2016-05-04T10:15:00","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":"Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California","docAbstract":"Most research on the effects of wildfires on stream water quality has focused on suspended sediment and nutrients in streams and water bodies, and relatively little research has examined the effects of wildfires on trace elements. The purpose of this study was two-fold: 1) to determine the effect of the 2009 Station Fire in the Angeles National Forest northeast of Los Angeles, CA on trace element concentrations in streams, and 2) compare trace elements in post-fire stormflow water quality to criteria for aquatic life to determine if trace elements reached concentrations that can harm aquatic life. Pre-storm and stormflow water-quality samples were collected in streams located inside and outside of the burn area of the Station Fire. Ash and burned soil samples were collected from several locations within the perimeter of the Station Fire. Filtered concentrations of Fe, Mn, and Hg and total concentrations of most trace elements in storm samples were elevated as a result of the Station Fire. In contrast, filtered concentrations of Cu, Pb, Ni, and Se and total concentrations of Cu were elevated primarily due to storms and not the Station Fire. Total concentrations of Se and Zn were elevated as a result of both storms and the Station Fire. Suspended sediment in stormflows following the Station Fire was an important transport mechanism for trace elements. Cu, Pb, and Zn primarily originate from ash in the suspended sediment. Fe primarily originates from burned soil in the suspended sediment. As, Mn, and Ni originate from both ash and burned soil. Filtered concentrations of trace elements in stormwater samples affected by the Station Fire did not reach levels that were greater than criteria established for aquatic life. Total concentrations for Fe, Pb, Ni, and Zn were detected at concentrations above criteria established for aquatic life.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0153372","collaboration":"Amphibian Research and Monitoring Initiative (BRD) Mineral Resources Program (USGS)","usgsCitation":"Burton, C.A., Hoefen, T.M., Plumlee, G.S., Baumberger, K., Backlin, A.R., Gallegos, E., and Fisher, R.N., 2016, Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California: PLoS ONE, v. 11, no. 5, https://doi.org/10.1371/journal.pone.0153372.","productDescription":"26 p.","startPage":"e0153372","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051778","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0153372","text":"Publisher Index Page"},{"id":321203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321176,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1371/journal.pone.0153372."}],"country":"United States","state":"California","otherGeospatial":"Angeles National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.466667,\n 34.625\n ],\n [\n -118.466667,\n 34.125\n ],\n [\n -117.6875,\n 34.125\n ],\n [\n -117.6875,\n 34.625\n ],\n [\n -118.466667,\n 34.625\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"5736fae1e4b0dae0d5e03ebb","contributors":{"authors":[{"text":"Burton, Carmen A. 0000-0002-6381-8833 caburton@usgs.gov","orcid":"https://orcid.org/0000-0002-6381-8833","contributorId":444,"corporation":false,"usgs":true,"family":"Burton","given":"Carmen","email":"caburton@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":629206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plumlee, Geoffrey S. 0000-0002-9607-5626 gplumlee@usgs.gov","orcid":"https://orcid.org/0000-0002-9607-5626","contributorId":960,"corporation":false,"usgs":true,"family":"Plumlee","given":"Geoffrey","email":"gplumlee@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":629207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baumberger, Katherine L. kbaumberger@usgs.gov","contributorId":5870,"corporation":false,"usgs":true,"family":"Baumberger","given":"Katherine L.","email":"kbaumberger@usgs.gov","affiliations":[],"preferred":true,"id":629208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gallegos, Elizabeth 0000-0002-8402-2631 egallegos@usgs.gov","orcid":"https://orcid.org/0000-0002-8402-2631","contributorId":1528,"corporation":false,"usgs":true,"family":"Gallegos","given":"Elizabeth","email":"egallegos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629210,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629211,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70174006,"text":"70174006 - 2016 - Spatially explicit control of invasive species using a reaction-diffusion model","interactions":[],"lastModifiedDate":"2016-09-02T09:35:37","indexId":"70174006","displayToPublicDate":"2016-05-04T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit control of invasive species using a reaction-diffusion model","docAbstract":"Invasive species, which can be responsible for severe economic and environmental damages, must often be managed over a wide area with limited resources, and the optimal allocation of effort in space and time can be challenging. If the spatial range of the invasive species is large, control actions might be applied only on some parcels of land, for example because of property type, accessibility, or limited human resources. Selecting the locations for control is critical and can significantly impact management efficiency. To help make decisions concerning the spatial allocation of control actions, we propose a simulation based approach, where the spatial distribution of the invader is approximated by a reaction–diffusion model. We extend the classic Fisher equation to incorporate the effect of control both in the diffusion and local growth of the invader. The modified reaction–diffusion model that we propose accounts for the effect of control, not only on the controlled locations, but on neighboring locations, which are based on the theoretical speed of the invasion front. Based on simulated examples, we show the superiority of our model compared to the state-of-the-art approach. We illustrate the use of this model for the management of Burmese pythons in the Everglades (Florida, USA). Thanks to the generality of the modified reaction–diffusion model, this framework is potentially suitable for a wide class of management problems and provides a tool for managers to predict the effects of different management strategies.
","language":"English","publisher":"Elsevier : ScienceDirect","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ecolmodel.2016.05.013","usgsCitation":"Bonneau, M., Johnson, F.A., and Romagosa, C., 2016, Spatially explicit control of invasive species using a reaction-diffusion model: Ecological Modelling, v. 337, p. 15-24, https://doi.org/10.1016/j.ecolmodel.2016.05.013.","productDescription":"10 p.","startPage":"15","endPage":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061162","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":324190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"337","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576bb6bce4b07657d1a22959","contributors":{"authors":[{"text":"Bonneau, Mathieu","contributorId":150041,"corporation":false,"usgs":false,"family":"Bonneau","given":"Mathieu","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":640258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":640257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romagosa, Christina M.","contributorId":39661,"corporation":false,"usgs":true,"family":"Romagosa","given":"Christina M.","affiliations":[],"preferred":false,"id":640259,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170139,"text":"sir20165046 - 2016 - Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","interactions":[],"lastModifiedDate":"2021-10-12T17:00:16.258141","indexId":"sir20165046","displayToPublicDate":"2016-05-04T10:00:00","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":"2016-5046","title":"Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","docAbstract":"The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model air2water was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.
The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.
The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165046","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Wood, T.M., Wherry, S.A., Piccolroaz, S., and Girdner, S.F., 2016, Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099: U.S. Geological Survey Scientific Investigations Report 2016–5046, 43 p. https://doi.org/10.3133/sir20165046","productDescription":"vii, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066051","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":320860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5046/sir20165046.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-5046 Report PDF"},{"id":320859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5046/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Crater Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.18616485595703,\n 42.892567248047285\n ],\n [\n -122.18616485595703,\n 42.986065036562955\n ],\n [\n -122.03922271728514,\n 42.986065036562955\n ],\n [\n -122.03922271728514,\n 42.892567248047285\n ],\n [\n -122.18616485595703,\n 42.892567248047285\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: February 2020; Version 1.0: October 2016","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
During July 2015, water samples were collected from 18 wetlands on the Lake Traverse Indian Reservation in northeastern South Dakota and southeastern North Dakota and analyzed for physical properties and 54 pesticides. This study by the U.S. Geological Survey in cooperation with the Sisseton-Wahpeton Oyate was designed to provide an update on pesticide concentrations of the same 18 wetlands that were sampled for a reconnaissance-level assessment during July 2006. The purpose of this report is to present the results of the assessment of pesticide concentrations in selected Lake Traverse Indian Reservation wetlands during July 2015 and provide a comparison of pesticide concentrations between 2006 and 2015.
Of the 54 pesticides that were analyzed for in the samples collected during July 2015, 47 pesticides were not detected in any samples. Seven pesticides—2-chloro-4-isopropylamino-6-amino-s-triazine (CIAT); 2,4–D; acetachlor; atrazine; glyphosate; metolachlor; and prometon—were detected in the 2015 samples with estimated concentrations or concentrations greater than the laboratory reporting level, and most pesticides were detected at low concentrations in only a few samples. Samples from all wetlands contained at least one detected pesticide. The maximum number of pesticides detected in a wetland sample was six, and the median number of pesticides detected was three.
The most commonly detected pesticides in the 2015 samples were atrazine and the atrazine degradate CIAT (also known as deethylatrazine), which were detected in 14 and 13 of the wetlands sampled, respectively. Glyphosate was detected in samples from 11 wetlands, and metolachlor was detected in samples from 10 wetlands. The other detected pesticides were 2,4–D (4 wetlands), acetochlor (3 wetlands), and prometon (1 wetland).
The same pesticides that were detected in the 2006 samples were detected in the 2015 samples, with the exception of simazine, which was detected only in one sample in 2006. Atrazine and CIAT were the most commonly detected pesticides in both sampling years; however, atrazine and CIAT were detected in fewer wetlands in 2015 (14 and 13 wetlands, respectively) than in 2006 (17 wetlands for both pesticides). The pesticides 2,4–D and prometon also were detected in fewer wetlands in 2015 than 2006, and simazine was only detected in 2006. In contrast, acetochlor, glyphosate, and metolachlor were detected in samples from more wetlands in 2015 than in 2006. In samples from individual wetlands, the number of pesticides detected was similar between 2006 and 2015. At least one pesticide was detected in all wetlands in 2015, and all but one wetland had pesticide detections in 2006.
Concentrations of pesticides detected in samples from wetlands were compared to selected water-quality (human-health and aquatic-life) benchmarks. None of the concentrations in either 2006 or 2015 were greater than water-quality benchmarks, with the exception of atrazine. All detections of atrazine in the 2006 and 2015 samples were greater than the acute benchmark of 0.001 microgram per liter (μg/L) for vascular plants. In addition, some concentrations of 2,4–D and atrazine were within an order of magnitude of a water-quality benchmark. The 2,4–D concentrations in the 2015 samples from three wetlands were within an order of magnitude of the U.S. Environmental Protection Agency’s Maximum Contaminant Level of 70 μg/L (that is, sample concentrations were greater than 7.0 μg/L). The maximum dissolved atrazine concentration of 0.185 μg/L in the 2015 samples along with the concentrations in 2006 samples from two wetlands were within an order of magnitude of the acute benchmark of less than 1 μg/L for nonvascular plants (that is, concentrations were greater than 0.1 μg/L).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds984","collaboration":"Prepared in cooperation with the Sisseton-Wahpeton Oyate","usgsCitation":"Carter, J.M., and Thompson, R.F., 2016, Pesticide concentrations in wetlands on the Lake Traverse Indian Reservation, South and North Dakota, July 2015: U.S. Geological Survey Data Series Report 984, 32 p., https://dx.doi.org/10.3133/ds984.","productDescription":"vi, 32 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072207","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":320926,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0984/coverthb.jpg"},{"id":320927,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0984/ds984.pdf","text":"Report","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 984"}],"country":"United States","state":"North Dakota, South Dakota","otherGeospatial":"Lake Traverse Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.56021118164062,\n 45.93778073466329\n ],\n [\n -97.5146484375,\n 46.02462129598765\n ],\n [\n -97.18505859374999,\n 44.97645666320777\n ],\n [\n -96.85272216796875,\n 45.60058738537025\n ],\n [\n -96.85684204101562,\n 45.622682153628226\n ],\n [\n -96.84173583984374,\n 45.64188792039229\n ],\n [\n -96.78543090820312,\n 45.68123916702059\n ],\n [\n -96.70989990234374,\n 45.71864517367924\n ],\n [\n -96.66320800781249,\n 45.74261022090537\n ],\n [\n -96.61102294921875,\n 45.79625461321962\n ],\n [\n -96.5753173828125,\n 45.84602106744846\n ],\n [\n -96.56021118164062,\n 45.93778073466329\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, South Dakota 57702
The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia, using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season (June–October), followed by a fallow during the rabi season (November–February). These cropland areas are not suitable for growing rabi-season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea (Cicer arietinum L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary (kharif) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left fallow during the second (rabi) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during rabi season. Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.
","language":"English","doi":"10.1080/17538947.2016.1168489","usgsCitation":"Gumma, M., Thenkabail, P.S., Teluguntla, P.G., Rao, M.N., Mohammed, I., and Whitbread, A.M., 2016, Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data: International Journal of Digital Earth, v. 9, no. 10, p. 981-1003, https://doi.org/10.1080/17538947.2016.1168489.","productDescription":"23 p.","startPage":"981","endPage":"1003","ipdsId":"IP-070335","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2016.1168489","text":"Publisher Index Page"},{"id":330906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bangladesh, Bhutan, India, Nepal, Pakistan, Sri Lanka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 83.97949218750001,\n 15.284185114076433\n ],\n [\n 82.3095703125,\n 11.996338401936226\n ],\n [\n 83.32031250000001,\n 7.754537346539373\n ],\n [\n 81.78222656250001,\n 5.266007882805485\n ],\n [\n 79.365234375,\n 5.747174076651375\n ],\n [\n 76.81640625,\n 7.406047717076271\n ],\n [\n 72.59765625,\n 12.382928338487396\n ],\n [\n 66.4013671875,\n 25.64152637306577\n ],\n [\n 80.4638671875,\n 29.11377539511439\n ],\n [\n 95.61523437500003,\n 30.34192736497245\n ],\n [\n 91.62597656250001,\n 20.67390526467282\n ],\n [\n 83.97949218750001,\n 15.284185114076433\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"582443f5e4b09065cdf30528","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":653404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rao, Mahesh N.","contributorId":127588,"corporation":false,"usgs":false,"family":"Rao","given":"Mahesh","email":"","middleInitial":"N.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":653407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohammed, Irshad A.","contributorId":176755,"corporation":false,"usgs":false,"family":"Mohammed","given":"Irshad A.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitbread, Anthony M.","contributorId":176756,"corporation":false,"usgs":false,"family":"Whitbread","given":"Anthony","email":"","middleInitial":"M.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653409,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70173933,"text":"70173933 - 2016 - Long-term trends in a Dimictic Lake","interactions":[],"lastModifiedDate":"2016-06-22T13:17:08","indexId":"70173933","displayToPublicDate":"2016-05-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trends in a Dimictic Lake","docAbstract":"The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911–2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 °C per decade before 1981 to 0.334 °C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s−1 before 1994 to 3.74 m s−1 thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3 days per century), decreasing ice cover duration (21.3 days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3 days per century), later fall turnover (14.6 days per century), longer stratification duration (26.8 days per century), and decreasing summer hypolimnetic temperatures (−1.4 °C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911–1980, 1981–1993, and 1994–2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Niño winter of 1997–1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994–2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.
","language":"English","publisher":"Copernicus Publications","publisherLocation":"Göttingen, Germany","doi":"10.5194/hess-20-1681-2016","usgsCitation":"Robertson, D.M., Hsieh, Y., Lathrop, R.C., Wu, C.H., Magee, M., and Hamilton, D., 2016, Long-term trends in a Dimictic Lake: Hydrology and Earth System Sciences, v. 20, p. 1681-1702, https://doi.org/10.5194/hess-20-1681-2016.","productDescription":"22 p.","startPage":"1681","endPage":"1702","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065196","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":471027,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-1681-2016","text":"Publisher Index Page"},{"id":324224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Dane","otherGeospatial":"Lake 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Resources","active":true,"usgs":false}],"preferred":false,"id":639533,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Chin H","contributorId":172076,"corporation":false,"usgs":false,"family":"Wu","given":"Chin","email":"","middleInitial":"H","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":639534,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magee, Madeline","contributorId":172077,"corporation":false,"usgs":false,"family":"Magee","given":"Madeline","affiliations":[{"id":5083,"text":"University of British Columbia, Department of Zoology, Biodiversity Research Centre and Beaty Biodiversity Museum","active":true,"usgs":false}],"preferred":false,"id":639535,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamilton, David P.","contributorId":166840,"corporation":false,"usgs":false,"family":"Hamilton","given":"David P.","affiliations":[{"id":24543,"text":"Environmental Research Institute, University of Waikato, Private Bag 3015, Hamilton 3240, New Zealand.","active":true,"usgs":false}],"preferred":false,"id":639536,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174051,"text":"70174051 - 2016 - Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca","interactions":[],"lastModifiedDate":"2018-08-07T12:26:29","indexId":"70174051","displayToPublicDate":"2016-05-03T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca","docAbstract":"The authors investigated the chronic toxicity of aqueous Pb to the amphipod Hyalella azteca (Hyalella) in 42-d tests using 2 different diets: 1) the yeastþcereal leafþtrout pellet (YCT) diet, fed at the uniform low ration used in standard methods for sediment toxicity tests; and 2) a new diet of diatomsþTetraMin flakes (DT), fed at increasing rations over time, that has been optimized for use in Hyalella water-only tests. Test endpoints included survival, weight, biomass, fecundity, and total young. Lethal effects of Pb were similar for the DT and YCT tests (20% lethal concentration [LC20]¼13 mg/L and 15mg/L, respectively, as filterable Pb). In contrast, weight and fecundity endpoints were not significantly affected in the DT test at Pb concentrations up to 63 mg/L, but these endpoints were significantly reduced by Pb in the YCT test—and in a 2005 test in the same laboratory with a diet of conditioned Rabbit Chow (RC-2005). The fecundity and total young endpoints from the YCT and RC-2005 tests were considered unreliable because fecundity in controls did not meet test acceptability criteria, but both of these tests still produced lower Pb effect concentrations (for weight or biomass) than the test with the DT diet. The lowest biotic ligand model–normalized effect concentrations for the 3 tests ranged from 3.7mg/L (weight 20% effect concentration [EC20] for the RC-2005 test) to 8.2 mg/L (total young EC20 for the DT test), values that would rank Hyalella as the second or third most sensitive of 13 genera in a species sensitivity distribution for chronic Pb toxicity. These results demonstrate that toxicity tests with Hyalella fed optimal diets can meet more stringent test acceptability criteria for control performance, but suggest that results of these tests may underestimate sublethal toxic effects of Pb to Hyalella under suboptimal feeding regimes.
","language":"English","publisher":"Setac Press","doi":"10.1002/etc.3341","usgsCitation":"Besser, J.M., Ivey, C.D., Brumbaugh, W.G., and Ingersoll, C.G., 2016, Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca: Environmental Toxicology and Chemistry, v. 35, p. 1825-1834, https://doi.org/10.1002/etc.3341.","productDescription":"10 p.","startPage":"1825","endPage":"1834","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063482","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":324365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","edition":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"576e59aee4b07657d1a43c55","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640708,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170845,"text":"70170845 - 2016 - Molecular evidence of undescribed Ceratonova sp. (Cnidaria: Myxosporea) in the freshwater polychaete, Manayunkia speciosa, from western Lake Erie","interactions":[],"lastModifiedDate":"2016-05-12T10:52:39","indexId":"70170845","displayToPublicDate":"2016-05-03T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2361,"text":"Journal of Invertebrate Pathology","active":true,"publicationSubtype":{"id":10}},"title":"Molecular evidence of undescribed Ceratonova sp. (Cnidaria: Myxosporea) in the freshwater polychaete, Manayunkia speciosa, from western Lake Erie","docAbstract":"We used PCR to screen pooled individuals of Manayunkia speciosa from western Lake Erie, Michigan, USA for myxosporean parasites. Amplicons from positive PCRs were sequenced and showed a Ceratonova species in an estimated 1.1% (95% CI = 0.46%, 1.8%) of M. speciosa individuals. We sequenced 18S, ITS1, 5.8S, ITS2 and most of the 28S rDNA regions of this Ceratonova sp., and part of the protein-coding EF2 gene. Phylogenetic analyses of ribosomal and EF2 sequences showed the Lake Erie Ceratonova sp. is most similar to, but genetically distinct from, Ceratonova shasta. Marked interspecific polymorphism in all genes examined, including the ITS barcoding genes, along with geographic location suggests this is an undescribed Ceratonova species. COI sequences showed M. speciosa individuals in Michigan and California are the same species. These findings represent a third parasite in the genus Ceratonovapotentially hosted by M. speciosa.
","language":"English","publisher":"Society for Invertebrate Pathology","publisherLocation":"New York, NY","doi":"10.1016/j.jip.2016.05.001","usgsCitation":"Malakauskas, D.M., Snipes, R.B., Thompson, A.M., and Schloesser, D.W., 2016, Molecular evidence of undescribed Ceratonova sp. (Cnidaria: Myxosporea) in the freshwater polychaete, Manayunkia speciosa, from western Lake Erie: Journal of Invertebrate Pathology, v. 137, p. 49-53, https://doi.org/10.1016/j.jip.2016.05.001.","productDescription":"5 p.","startPage":"49","endPage":"53","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075219","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":320962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.1500244140625,\n 42.204107493733176\n ],\n [\n -83.12530517578125,\n 42.12878436246021\n ],\n [\n -83.15277099609375,\n 42.04113400940809\n ],\n [\n -83.10882568359375,\n 41.95540515378059\n ],\n [\n -83.41644287109374,\n 41.734429390721\n ],\n [\n -83.49609375,\n 41.734429390721\n ],\n [\n -83.47686767578125,\n 41.79998325207397\n ],\n [\n -83.44390869140625,\n 41.85115059465234\n ],\n [\n -83.4136962890625,\n 41.89409955811395\n ],\n [\n -83.37799072265624,\n 41.93088998442502\n ],\n [\n -83.35052490234375,\n 41.96357478222518\n ],\n [\n -83.32305908203124,\n 41.99011884096809\n ],\n [\n -83.26812744140625,\n 42.01665183556825\n ],\n [\n -83.22143554687499,\n 42.07987816698549\n ],\n [\n -83.21319580078125,\n 42.14304156290939\n ],\n [\n -83.18572998046875,\n 42.18375873465217\n ],\n [\n -83.1500244140625,\n 42.204107493733176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"137","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572b1d37e4b0b13d391b44c6","contributors":{"authors":[{"text":"Malakauskas, David M.","contributorId":43247,"corporation":false,"usgs":true,"family":"Malakauskas","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":628769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snipes, Robert Benjamin","contributorId":169164,"corporation":false,"usgs":false,"family":"Snipes","given":"Robert","email":"","middleInitial":"Benjamin","affiliations":[{"id":18157,"text":"Francis Marion University","active":true,"usgs":false}],"preferred":false,"id":628770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Ann M.","contributorId":169165,"corporation":false,"usgs":false,"family":"Thompson","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":18157,"text":"Francis Marion University","active":true,"usgs":false}],"preferred":false,"id":628771,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schloesser, Donald W. dschloesser@usgs.gov","contributorId":3579,"corporation":false,"usgs":true,"family":"Schloesser","given":"Donald","email":"dschloesser@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":628772,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209271,"text":"70209271 - 2016 - Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations","interactions":[],"lastModifiedDate":"2020-03-26T11:47:16","indexId":"70209271","displayToPublicDate":"2016-05-03T11:31:24","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations","title":"Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations","docAbstract":"Reliably estimating wildlife abundance is fundamental to effective management. Aerial surveys are one of the only spatially robust tools for estimating large mammal populations, but statistical sampling methods are required to address detection biases that affect accuracy and precision of the estimates. Although various methods for correcting aerial survey bias are employed on large mammal species around the world, these have rarely been rigorously validated. Several populations of feral horses (Equus caballus) in the western United States have been intensively studied, resulting in identification of all unique individuals. This provided a rare opportunity to test aerial survey bias correction on populations of known abundance. We hypothesized that a hybrid method combining simultaneous double-observer and sightability bias correction techniques would accurately estimate abundance. We validated this integrated technique on populations of known size and also on a pair of surveys before and after a known number was removed. Our analysis identified several covariates across the surveys that explained and corrected biases in the estimates. All six tests on known populations produced estimates with deviations from the known value ranging from -8.5% to +13.7% and <0.7 standard errors. Precision varied widely, from 6.1% CV to 25.0% CV. In contrast, the pair of surveys conducted around a known management removal produced an estimated change in population between the surveys that was significantly larger than the known reduction. Although the deviation between was only 9.1%, the precision estimate (CV = 1.6%) may have been artificially low. It was apparent that use of a helicopter in those surveys perturbed the horses, introducing detection error and heterogeneity in a manner that could not be corrected by our statistical models. Our results validate the hybrid method, highlight its potentially broad applicability, identify some limitations, and provide insight and guidance for improving survey designs.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0154902","usgsCitation":"Lubow, B., and Ransom, J.I., 2016, Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations: PLoS ONE, v. 11, no. 5, e0154902, 15 p., https://doi.org/10.1371/journal.pone.0154902.","productDescription":"e0154902, 15 p.","ipdsId":"IP-074372","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471028,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0154902","text":"Publisher Index Page"},{"id":373550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Nevada, Utah, Wyoming","otherGeospatial":"Cedar Mountain Herd Management Area, Little Owyhee Herd Management Area, McCullough Peaks Herd Management Area, Sand Wash Herd Management Area, Snowstorm Mountains Herd Management Area ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.00634765625,\n 44.308126684886126\n ],\n [\n -107.89672851562499,\n 44.308126684886126\n ],\n [\n -107.89672851562499,\n 44.98034238084973\n ],\n [\n -109.00634765625,\n 44.98034238084973\n ],\n [\n -109.00634765625,\n 44.308126684886126\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.984375,\n 40.26276066437183\n ],\n [\n -108.017578125,\n 40.26276066437183\n ],\n [\n -108.017578125,\n 40.896905775860006\n ],\n [\n -108.984375,\n 40.896905775860006\n ],\n [\n -108.984375,\n 40.26276066437183\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.48876953125,\n 39.9434364619742\n ],\n [\n -112.87353515625,\n 39.9434364619742\n ],\n [\n -112.87353515625,\n 40.6306300839918\n ],\n [\n -113.48876953125,\n 40.6306300839918\n ],\n [\n -113.48876953125,\n 39.9434364619742\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.24609374999999,\n 41.393294288784865\n ],\n [\n -116.52099609375,\n 41.393294288784865\n ],\n [\n -116.52099609375,\n 41.95131994679697\n ],\n [\n -117.24609374999999,\n 41.95131994679697\n ],\n [\n -117.24609374999999,\n 41.393294288784865\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-03","publicationStatus":"PW","contributors":{"editors":[{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785658,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Lubow, Bruce C.","contributorId":131076,"corporation":false,"usgs":false,"family":"Lubow","given":"Bruce C.","affiliations":[{"id":7230,"text":"Natural Resource Ecology Laboratory, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":785656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ransom, Jason I.","contributorId":139841,"corporation":false,"usgs":false,"family":"Ransom","given":"Jason","email":"","middleInitial":"I.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":785657,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170087,"text":"ofr20161030 - 2016 - Improve wildlife species tracking—Implementing an enhanced global positioning system data management system for California condors","interactions":[],"lastModifiedDate":"2016-05-03T10:16:16","indexId":"ofr20161030","displayToPublicDate":"2016-05-03T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1030","title":"Improve wildlife species tracking—Implementing an enhanced global positioning system data management system for California condors","docAbstract":"U.S. Fish and Wildlife Service (USFWS) staff in the Pacific Southwest Region and at the Hopper Mountain National Wildlife Refuge Complex requested technical assistance to improve their global positioning system (GPS) data acquisition, management, and archive in support of the California Condor Recovery Program. The USFWS deployed and maintained GPS units on individual Gymnogyps californianus (California condor) in support of long-term research and daily operational monitoring and management of California condors. The U.S. Geological Survey (USGS) obtained funding through the Science Support Program to provide coordination among project participants, provide GPS Global System for Mobile Communication (GSM) transmitters for testing, and compare GSM/GPS with existing Argos satellite GPS technology. The USFWS staff worked with private companies to design, develop, and fit condors with GSM/GPS transmitters. The Movebank organization, an online database of animal tracking data, coordinated with each of these companies to automatically stream their GPS data into Movebank servers and coordinated with USFWS to improve Movebank software for managing transmitter data, including proofing/error checking of incoming GPS data. The USGS arranged to pull raw GPS data from Movebank into the USGS California Condor Management and Analysis Portal (CCMAP) (https://my.usgs.gov/ccmap) for production and dissemination of a daily map of condor movements including various automated alerts. Further, the USGS developed an automatic archiving system for pulling raw and proofed Movebank data into USGS ScienceBase to comply with the Federal Information Security Management Act of 2002. This improved data management system requires minimal manual intervention resulting in more efficient data flow from GPS data capture to archive status. As a result of the project’s success, Pinnacles National Park and the Ventana Wildlife Society California condor programs became partners and adopted the same workflow, tracking, and data archive system. This GPS tracking data management model and workflow should be applicable and beneficial to other wildlife tracking programs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161030","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service, Region 8","usgsCitation":"Waltermire, R.G., Emmerich, C.U., Mendenhall, L.C., Bohrer, Gil, Weinzierl, R.P., McGann, A.J., Lineback, P.K., Kern, T.J., and Douglas, D.C., 2016, Improve wildlife species tracking—Implementing an enhanced global positioning system data management system for California condors: U.S. Geological Survey Open-File Report 2016–1030, 46 p., https://dx.doi.org/10.3133/ofr20161030.","productDescription":"vi, 46 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066019","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":320820,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1030/ofr20161030.pdf","text":"Report","size":"5.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1032"},{"id":320819,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1030/coverthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.29980468749999,\n 37.07271048132946\n ],\n [\n -122.1240234375,\n 36.86204269508728\n ],\n [\n -121.79443359375,\n 36.87962060502676\n ],\n [\n -121.88232421875,\n 36.686041276581925\n ],\n [\n -122.05810546875,\n 36.63316209558658\n ],\n [\n -121.9482421875,\n 36.2265501474709\n ],\n [\n -121.53076171875,\n 35.871246850027966\n ],\n [\n -121.201171875,\n 35.60371874069731\n ],\n [\n -120.9814453125,\n 35.31736632923788\n ],\n [\n -120.95947265624999,\n 35.137879119634185\n ],\n [\n -120.76171875,\n 35.10193405724606\n ],\n [\n -120.65185546875,\n 34.66935854524543\n ],\n [\n -120.80566406250001,\n 34.52466147177172\n ],\n [\n -120.25634765624999,\n 34.34343606848294\n ],\n [\n -119.94873046875,\n 34.379712580462204\n ],\n [\n -119.59716796875,\n 34.34343606848294\n ],\n [\n -119.2236328125,\n 34.21634468843465\n ],\n [\n -118.91601562499999,\n 33.88865750124075\n ],\n [\n -118.5205078125,\n 33.88865750124075\n ],\n [\n -118.19091796875,\n 33.63291573870476\n ],\n [\n -117.83935546874999,\n 33.486435450999885\n ],\n [\n -117.6416015625,\n 33.87041555094183\n ],\n [\n -116.23535156249999,\n 34.03445260967645\n ],\n [\n -116.25732421875,\n 35.7286770448517\n ],\n [\n -116.89453125,\n 35.60371874069731\n ],\n [\n -117.22412109375,\n 36.38591277287651\n ],\n [\n -117.97119140625,\n 37.212831514455964\n ],\n [\n -118.47656249999999,\n 37.35269280367274\n ],\n [\n -118.95996093749999,\n 37.09023980307208\n ],\n [\n -119.77294921874999,\n 37.19533058280065\n ],\n [\n -120.34423828125,\n 37.28279464911045\n ],\n [\n -121.06933593749999,\n 37.23032838760387\n ],\n [\n -121.31103515625,\n 37.45741810262938\n ],\n [\n -121.55273437499999,\n 37.24782120155428\n ],\n [\n -121.9482421875,\n 37.125286284966805\n ],\n [\n -122.29980468749999,\n 37.07271048132946\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The Blackbird cobalt-copper (Co-Cu) district in the Salmon River Mountains of east-central Idaho occupies the central part of the Idaho cobalt belt—a northwest-elongate, 55-km-long belt of Co-Cu occurrences, hosted in grayish siliciclastic metasedimentary strata of the Lemhi subbasin (of the Mesoproterozoic Belt-Purcell Basin). The Blackbird district contains at least eight stratabound ore zones and many discordant lodes, mostly in the upper part of the banded siltite unit of the Apple Creek Formation of Yellow Lake, which generally consists of interbedded siltite and argillite. In the Blackbird mine area, argillite beds in six stratigraphic intervals are altered to biotitite containing over 75 vol% of greenish hydrothermal biotite, which is preferentially mineralized.
Past production and currently estimated resources of the Blackbird district total ~17 Mt of ore, averaging 0.74% Co, 1.4% Cu, and 1.0 ppm Au (not including downdip projections of ore zones that are open downward). A compilation of relative-age relationships and isotopic age determinations indicates that most cobalt mineralization occurred in Mesoproterozoic time, whereas most copper mineralization occurred in Cretaceous time.
Mesoproterozoic cobaltite mineralization accompanied and followed dynamothermal metamorphism and bimodal plutonism during the Middle Mesoproterozoic East Kootenay orogeny (ca. 1379–1325 Ma), and also accompanied Grenvilleage (Late Mesoproterozoic) thermal metamorphism (ca. 1200–1000 Ma). Stratabound cobaltite-biotite ore zones typically contain cobaltite1 in a matrix of biotitite ± tourmaline ± minor xenotime (ca. 1370–1320 Ma) ± minor chalcopyrite ± sparse allanite ± sparse microscopic native gold in cobaltite. Such cobaltite-biotite lodes are locally folded into tight F2 folds with axial-planar S2 cleavage and schistosity. Discordant replacement-style lodes of cobaltite2-biotite ore ± xenotime2 (ca. 1320–1270 Ma) commonly follow S2fractures and fabrics. Discordant quartz-biotite and quartz-tourmaline breccias, and veins contain cobaltite3 ± xenotime3 (ca. 1058–990 Ma).
Mesoproterozoic cobaltite deposition was followed by: (1) within-plate plutonism (530–485 Ma) and emplacement of mafic dikes (which cut cobaltite lodes but are cut by quartz-Fe-Cu-sulfide veins); (2) garnet-grade metamorphism (ca. 151–93 Ma); (3) Fe-Cu-sulfide mineralization (ca. 110–92 Ma); and (4) minor quartz ± Au-Ag ± Bi mineralization (ca. 92–83 Ma).
Cretaceous Fe-Cu-sulfide vein, breccia, and replacement-style deposits contain various combinations of chalcopyrite ± pyrrhotite ± pyrite ± cobaltian arsenopyrite (not cobaltite) ± arsenopyrite ± quartz ± siderite ± monazite (ca. 144–88 Ma but mostly 110–92 Ma) ± xenotime (104–93 Ma). Highly radiogenic Pb (in these sulfides) and Sr (in siderite) indicate that these elements resided in Mesoproterozoic source rocks until they were mobilized after ca. 100 Ma. Fe-Cu-sulfide veins, breccias, and replacement deposits appear relatively undeformed and generally lack metamorphic fabrics.
Composite Co-Cu-Au ore contains early cobaltite-biotite lodes, cut by Fe-Cu-sulfide veins and breccias, or overprinted by Fe-Cu-sulfide replacement-style deposits, and locally cut by quartz veinlets ± Au-Ag ± Bi minerals.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2016.2522(08)","usgsCitation":"Bookstrom, A.A., Box, S.E., Cossette, P.M., Frost, T.P., Gillerman, V., King, G., and Zirakparvar, N.A., 2016, Geologic history of the Blackbird Co-Cu district in the Lemhi subbasin of the Belt-Purcell Basin: GSA Special Papers, v. 522, p. 185-219, https://doi.org/10.1130/2016.2522(08).","productDescription":"36 p. 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Igneous and sedimentary rocks in the Greenwater Range, one mountain range east of Death Valley, tell an earlier story that overlaps with the formation of Death Valley proper. This early story has been told by scientists who have studied these rocks for many years and continue to do so. This field guide was prepared for the first Death Valley Natural History Conference and provides an overview of the geology of the Greenwater Range and the early history (10–0 Ma) of Death Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161064","usgsCitation":"Calzia, J.P., Rämö, O.T., Jachens, Robert, Smith, Eugene, and Knott, Jeffrey, 2016, Geology of the Greenwater Range, and the dawn of Death Valley, California—Field guide for the Death Valley Natural History Conference, 2013: U.S. Geological Survey Open-File Report 2016–1064, 32 p., https://dx.doi.org/10.3133/ofr20161064.","productDescription":"iv, 32 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073504","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":320772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1064/ofr20161064.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1064 Report PDF"},{"id":320771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1064/coverthb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Death Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.10052490234375,\n 36.07241230197147\n ],\n [\n -117.10052490234375,\n 36.59127365634205\n ],\n [\n -116.27517700195312,\n 36.59127365634205\n ],\n [\n -116.27517700195312,\n 36.07241230197147\n ],\n [\n -117.10052490234375,\n 36.07241230197147\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center—
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Dams impound the majority of rivers and provide important societal benefits, especially daily water releases that enable on-peak hydroelectricity generation. Such “hydropeaking” is common worldwide, but its downstream impacts remain unclear. We evaluated the response of aquatic insects, a cornerstone of river food webs, to hydropeaking using a life history–hydrodynamic model. Our model predicts that aquatic-insect abundance will depend on a basic life-history trait—adult egg-laying behavior—such that open-water layers will be unaffected by hydropeaking, whereas ecologically important and widespread river-edge layers, such as mayflies, will be extirpated. These predictions are supported by a more-than-2500-sample, citizen-science data set of aquatic insects from the Colorado River in the Grand Canyon and by a survey of insect diversity and hydropeaking intensity across dammed rivers of the Western United States. Our study reveals a hydropeaking-related life history bottleneck that precludes viable populations of many aquatic insects from inhabiting regulated rivers.
","language":"English","publisher":"American Institute of Biological Sciences","publisherLocation":"Washington, D.C.","doi":"10.1093/biosci/biw059","usgsCitation":"Kennedy, T.A., Muehlbauer, J.D., Yackulic, C.B., Lytle, D., Miller, S., Dibble, K.L., Kortenhoeven, E.W., Metcalfe, A.N., and Baxter, C., 2016, Flow management for hydropower extirpates aquatic insects, undermining river food webs: BioScience, v. 66, no. 7, p. 561-575, https://doi.org/10.1093/biosci/biw059.","productDescription":"15 p.","startPage":"561","endPage":"575","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069041","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471029,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biw059","text":"Publisher Index Page"},{"id":438616,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WM1BH4","text":"USGS data release","linkHelpText":"Flow management for hydropower extirpates aquatic insects, undermining river food websData"},{"id":320875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-02","publicationStatus":"PW","scienceBaseUri":"5729cbb2e4b0b13d3919a342","contributors":{"authors":[{"text":"Kennedy, Theodore A. 0000-0003-3477-3629 tkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":167537,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628489,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lytle, D.A.","contributorId":85422,"corporation":false,"usgs":true,"family":"Lytle","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":628491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, S.A.","contributorId":66389,"corporation":false,"usgs":true,"family":"Miller","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":628492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dibble, Kimberly L. 0000-0003-0799-4477 kdibble@usgs.gov","orcid":"https://orcid.org/0000-0003-0799-4477","contributorId":5174,"corporation":false,"usgs":true,"family":"Dibble","given":"Kimberly","email":"kdibble@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628500,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kortenhoeven, Eric W. ekortenhoeven@usgs.gov","contributorId":5046,"corporation":false,"usgs":true,"family":"Kortenhoeven","given":"Eric","email":"ekortenhoeven@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628493,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Metcalfe, Anya N. 0000-0002-6286-4889 ametcalfe@usgs.gov","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":5271,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","email":"ametcalfe@usgs.gov","middleInitial":"N.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628494,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Baxter, Colden V.","contributorId":47334,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden V.","affiliations":[{"id":13656,"text":"Idaho State Univ.","active":true,"usgs":false}],"preferred":false,"id":628501,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70170721,"text":"70170721 - 2016 - Timing and composition of continental volcanism at Harrat Hutaymah, western Saudi Arabia","interactions":[],"lastModifiedDate":"2016-05-04T08:38:28","indexId":"70170721","displayToPublicDate":"2016-05-02T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Timing and composition of continental volcanism at Harrat Hutaymah, western Saudi Arabia","docAbstract":"Harrat Hutaymah is an alkali basalt volcanic field in north-central Saudi Arabia, at the eastern margin of a large Neogene continental, intraplate magmatic province. Lava flow, tephra and spatter cone compositions in the field include alkali olivine basalts and basanites. These compositions contrast with the predominantly tholeiitic, fissure-fed basalts found along the eastern margin of the Red Sea. The Hutaymah lava flows were erupted through Proterozoic arc-associated plutonic and meta-sedimentary rocks of the Arabian shield, and commonly contain a range of sub-continental lithospheric xenoliths, although the lavas themselves show little indication of crustal contamination. Previous radiometric dating of this volcanic field (a single published K–Ar age; 1.8 Ma) is suspiciously old given the field measurement of normal magnetic polarity only (i.e. Brunhes interval, ≤ 780 Ka). We report new age determinations on 14 lava flows by the 40Ar–39Ar laser step heating method, all younger than ~ 850 Ka, to better constrain the time frame of volcanism, and major, trace and rare earth element compositions to describe the chemical variation of volcanic activity at Harrat Hutaymah. Crystal fractionation was dominated by olivine ± clinopyroxene at a range of upper mantle and crustal pressures. Rapid ascent and eruption of magma is indicated by the array of lower crustal and lithospheric xenoliths observed in lava flows and tephra. Modeling suggests 1–7% melting of an enriched asthenospheric mantle source occurred beneath Harrat Hutaymah under a relatively thick lithospheric cap (60–80 km).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2016.01.010","usgsCitation":"Duncan, R.A., Kent, A.J., Thornber, C., Schliedler, T.D., and Al-Amri, A.M., 2016, Timing and composition of continental volcanism at Harrat Hutaymah, western Saudi Arabia: Journal of Volcanology and Geothermal Research, v. 313, p. 1-14, https://doi.org/10.1016/j.jvolgeores.2016.01.010.","productDescription":"14 p.","startPage":"1","endPage":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070061","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2016.01.010","text":"Publisher Index Page"},{"id":320813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Saudi Arabia","otherGeospatial":"Harrat Hutaymah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 30,\n 1\n ],\n [\n 30,\n 40\n ],\n [\n 55,\n 40\n ],\n [\n 55,\n 1\n ],\n [\n 30,\n 1\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"313","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57286c1be4b0b13d3917ce12","contributors":{"authors":[{"text":"Duncan, Robert A.","contributorId":167399,"corporation":false,"usgs":false,"family":"Duncan","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":628172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kent, Adam J R","contributorId":168855,"corporation":false,"usgs":false,"family":"Kent","given":"Adam","email":"","middleInitial":"J R","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":628173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thornber, Carl 0000-0002-6382-4408 cthornber@usgs.gov","orcid":"https://orcid.org/0000-0002-6382-4408","contributorId":167396,"corporation":false,"usgs":true,"family":"Thornber","given":"Carl","email":"cthornber@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":628171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schliedler, Tyler D","contributorId":169027,"corporation":false,"usgs":false,"family":"Schliedler","given":"Tyler","email":"","middleInitial":"D","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":628174,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Al-Amri, Abdullah M","contributorId":169028,"corporation":false,"usgs":false,"family":"Al-Amri","given":"Abdullah","email":"","middleInitial":"M","affiliations":[{"id":24707,"text":"King Saud University, Riyahd, KSA","active":true,"usgs":false}],"preferred":false,"id":628175,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}