Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000–2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000–2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990–1999 and 2000–2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974–2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer.
\nMaps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990–1999 and 2000–2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990–1999 and 2000–2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000–2009 than during 1990–1999; and that inland water levels were generally lower during 2000–2009 than during 1990–1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990–1999. Mean October water levels during 2000–2009 were generally higher than during 1990–1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165005","collaboration":"Prepared in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources","usgsCitation":"Prinos, S.T., and Dixon, J.F., 2016, Statistical analysis and mapping of water levels in the Biscayne aquifer, water conservation areas, and Everglades National Park, Miami-Dade County, Florida, 2000–2009: U.S. Geological Survey Scientific Investigations Report 2016–5005, 42 p., https://dx.doi.org/10.3133/sir20165005.","productDescription":"Report: vi, 42 p.; 16 Plates: 23.00 x 30.00 inches or smaller; Appendix; Companion File","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053912","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":318341,"rank":20,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5005/sir20165005_appendix8.pdf","text":"Figure 8-1 - (11x17)","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5005","linkHelpText":"Locations of all sites used to map water levels in the Biscayne aquifer, water conservation areas, and Everglades National Park, in Miami-Dade County, Florida, during the 2000-2009 water years. 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U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 3355
http://fl.water.usgs.gov/
Groundwater represents the terrestrial subsurface component of the hydrologic cycle. As such, groundwater is generally in motion, moving from elevated areas of recharge to lower areas of discharge. Groundwater usually moves in accordance with Darcy’s law (Dalmont, Paris: Les Fontaines Publiques de la Ville de Dijon, 1856). Groundwater residence times can be under a day in small upland catchments to over a million years in subcontinental-sized desert basins. The broadest definition of groundwater includes water in the unsaturated zone, considered briefly here. Water chemically bound to minerals, as in gypsum (CaSO4 • 2H2O) or hydrated clays, cannot flow in response to gradients in total hydraulic head (pressure head plus elevation head); such water is thus usually excluded from consideration as groundwater. In 1940, M. King Hubbert showed Darcy’s law to be a special case of thermodynamically based potential field equations governing fluid motion, thereby establishing groundwater hydraulics as a rigorous engineering science (Journal of Geology 48, pp. 785–944). The development of computer-enabled numerical methods for solving the field equations with real-world approximating geometries and boundary conditions in the mid-1960s ushered in the era of digital groundwater modeling. An estimated 30 percent of global fresh water is groundwater, compared to 0.3 percent that is surface water, 0.04 percent atmospheric water, and 70 percent that exists as ice, including permafrost (Shiklomanov and Rodda 2004, cited under Groundwater Occurrence). Groundwater thus constitutes the vast majority—over 98 percent—of the unfrozen fresh-water resources of the planet, excluding surface-water reservoirs. Environmental dimensions of groundwater are equally large, receiving attention on multiple disciplinary fronts. Riparian, streambed, and spring-pool habitats can be sensitively dependent on the amount and quality of groundwater inputs that modulate temperature and solutes, including nutrients and dissolved oxygen. Groundwater withdrawals can negatively impact riparian habitats by depriving ecosystems of adequate fresh water and fragmenting communities when streams go dry. Biochemical reactions in shallow groundwater can remove anthropogenically elevated nitrogen compounds and reduce—but only to a point—the greening of waterways and shorelines with periphyton and harmful algal blooms. Groundwater extraction for beneficial use is increasingly limited by water-quality constraints imposed by naturally occurring and introduced substances. Overdrafting can cause land-surface subsidence, damaging buildings and roads and disrupting canals, sewers, and other gravity-flow conveyances. Increases in groundwater levels can cause soil salinization in dry regions and erosive sapping and flooding in wet regions. Coastal saltwater intrusion, groundwater flooding, salinization associated with groundwater-irrigated agriculture, induced seismicity from injected wastes, and the detrimental impacts of groundwater depletion are among the major environmental challenges of our time.
","largerWorkTitle":"Oxford Bibliographies in Environmental Science","language":"English","publisher":"Oxford University Press","doi":"10.1093/obo/9780199363445-0053","usgsCitation":"Stonestrom, D.A., 2016, Groundwater, chap. of Oxford Bibliographies in Environmental Science, HTML document, https://doi.org/10.1093/obo/9780199363445-0053.","productDescription":"HTML document","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068189","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":320010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"570e1c32e4b0ef3b7ca24c2d","contributors":{"editors":[{"text":"Wohl, Ellen E.","contributorId":16969,"corporation":false,"usgs":true,"family":"Wohl","given":"Ellen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":626576,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Stonestrom, David A. 0000-0001-7883-3385 dastones@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-3385","contributorId":2280,"corporation":false,"usgs":true,"family":"Stonestrom","given":"David","email":"dastones@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":626222,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70168686,"text":"70168686 - 2016 - A full annual cycle modeling framework for American black ducks","interactions":[],"lastModifiedDate":"2016-02-24T14:30:05","indexId":"70168686","displayToPublicDate":"2016-02-24T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2827,"text":"Natural Resource Modeling","active":true,"publicationSubtype":{"id":10}},"title":"A full annual cycle modeling framework for American black ducks","docAbstract":"American black ducks (Anas rubripes) are a harvested, international migratory waterfowl species in eastern North America. Despite an extended period of restrictive harvest regulations, the black duck population is still below the population goal identified in the North American Waterfowl Management Plan (NAWMP). It has been hypothesized that density-dependent factors restrict population growth in the black duck population and that habitat management (increases, improvements, etc.) may be a key component of growing black duck populations and reaching the prescribed NAWMP population goal. Using banding data from 1951 to 2011 and breeding population survey data from 1990 to 2014, we developed a full annual cycle population model for the American black duck. This model uses the seven management units as set by the Black Duck Joint Venture, allows movement into and out of each unit during each season, and models survival and fecundity for each region separately. We compare model population trajectories with observed population data and abundance estimates from the breeding season counts to show the accuracy of this full annual cycle model. With this model, we then show how to simulate the effects of habitat management on the continental black duck population.
","language":"English","publisher":"Wiley","doi":"10.1111/nrm.12088","usgsCitation":"Robinson, O.J., McGowan, C.P., Devers, P.K., Brook, R.W., Huang, M., Jones, M., McAuley, D.G., and Zimmerman, G.S., 2016, A full annual cycle modeling framework for American black ducks: Natural Resource Modeling, v. 29, no. 1, p. 159-174, https://doi.org/10.1111/nrm.12088.","productDescription":"16 p.","startPage":"159","endPage":"174","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068504","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":318368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-28","publicationStatus":"PW","scienceBaseUri":"56ced42de4b015c306ec2fdc","contributors":{"authors":[{"text":"Robinson, Orin J.","contributorId":167172,"corporation":false,"usgs":false,"family":"Robinson","given":"Orin","email":"","middleInitial":"J.","affiliations":[{"id":33694,"text":"School of Forestry and Wildlife Sciences, Auburn University","active":true,"usgs":false}],"preferred":false,"id":621307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":621264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Devers, Patrick K.","contributorId":167173,"corporation":false,"usgs":false,"family":"Devers","given":"Patrick","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":621308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brook, Rodney W.","contributorId":92083,"corporation":false,"usgs":false,"family":"Brook","given":"Rodney","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":621309,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huang, Min","contributorId":167174,"corporation":false,"usgs":false,"family":"Huang","given":"Min","email":"","affiliations":[],"preferred":false,"id":621310,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Malcom","contributorId":167175,"corporation":false,"usgs":false,"family":"Jones","given":"Malcom","email":"","affiliations":[],"preferred":false,"id":621311,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McAuley, Daniel G. dmcauley@usgs.gov","contributorId":5377,"corporation":false,"usgs":true,"family":"McAuley","given":"Daniel","email":"dmcauley@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":621312,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zimmerman, Guthrie S.","contributorId":42473,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":621313,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70168673,"text":"70168673 - 2016 - Controls on ferromanganese crust composition and reconnaissance resource potential, Ninetyeast Ridge, Indian Ocean","interactions":[],"lastModifiedDate":"2019-12-13T09:14:52","indexId":"70168673","displayToPublicDate":"2016-02-24T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1370,"text":"Deep-Sea Research Part I: Oceanographic Research Papers","active":true,"publicationSubtype":{"id":10}},"title":"Controls on ferromanganese crust composition and reconnaissance resource potential, Ninetyeast Ridge, Indian Ocean","docAbstract":"A reconnaissance survey of Fe-Mn crusts from the 5000 km long (~31°S to 10°N) Ninetyeast Ridge (NER) in the Indian Ocean shows their widespread occurrence along the ridge as well as with water depth on the ridge flanks. The crusts are hydrogenetic based in growth rates and discrimination plots. Twenty samples from 12 crusts from 9 locations along the ridge were analyzed for chemical and mineralogical compositions, growth rates, and statistical relationships (Q-mode factor analysis, correlation coefficients) were calculated. The crusts collected are relatively thin (maximum 40 mm), and those analyzed varied from 4 mm to 32 mm. However, crusts as thick as 80 mm can be expected to occur based on the age of rocks that comprise the NER and the growth rates calculated here. Growth rates of the crusts increase to the north along the NER and with water depth. The increase to the north resulted from an increased supply of Mn from the oxygen minimum zone (OMZ) to depths below the OMZ combined with an increased supply of Fe at depth from the dissolution of biogenic carbonate and from deep-sourced hydrothermal Fe. These increased supplies of Fe increased growth rates of the deeper-water crusts along the entire NER. Because of the huge terrigenous (rivers, eolian, pyroclastic) and hydrothermal (three spreading centers) inputs to the Indian Ocean, and the history of primary productivity, Fe-Mn crust compositions vary from those analyzed from open-ocean locations in the Pacific.
\nThe sources of detrital material in the crusts changed along the NER and reflect, from north to south, the decreasing influence of the Ganga River system and volcanic arcs located to the east, with increasing influence of sediment derived from Australia to the south. In addition, weathering of NER basalt likely contributed to the aluminosilicate fraction of the crusts. The southernmost sample has a relatively large detrital component compared to other southern NER crust samples, which was probably derived predominantly from weathering of local volcanic outcrops.
\nFe-Mn crusts from a dredge haul at 3412 m water depth, 2°S latitude, are pervasively phosphatized along with the substrate rocks (site D7). Phosphatization took place through replacement of carbonate, preferential replacement of Fe oxyhydroxide relative to Mn oxide in the crusts, preferential replacement of silica-rich phases relative to Al-rich phases in the crusts, and precipitation of carbonate fluorapatite in pore space. The preferentially replaced silica may have been Si adsorbed on the Fe oxyhydroxide. The enrichment of Ni, Zn, and Cu in the phosphatized crust reflects preferential adsorption into the tunnel structure of todorokite. The rare earth element plus yttrium (REY) patterns indicate a lower oxidation potential during phosphatization of the NER crusts compared to Pacific phosphatized crusts. NER phosphatization occurred in a deeper-water environment than typical for phosphatization of Pacific crusts, occurred post-middle Miocene, a younger age than phosphatization the Pacific crusts, and had in part a different set of chemical changes produced by the phosphatization than did the Pacific crusts.
\nThe southern third of NER has Fe-Mn crusts with the highest Co (0.91%), Ni (0.43%), ΣREY (0.33%), Cu (0.22%), Te (146 ppm), Pt (1.5 ppm), Ru (52 ppb), and Rh (99 ppb) contents. These are among the highest Pt, Ru, and Rh concentrations measured in marine Fe-Mn deposits. Because of these high metal concentrations, exploration is warranted for the southern sector of the NER, especially at shallower-water sites where the platinum group elements (PGE) and Co are likely to be even more enriched.
","language":"English","publisher":"Permagon Press","doi":"10.1016/j.dsr.2015.11.006","usgsCitation":"Hein, J.R., Conrad, T., Mizell, K., Banakar, V.K., Frey, F.A., and Sager, W.W., 2016, Controls on ferromanganese crust composition and reconnaissance resource potential, Ninetyeast Ridge, Indian Ocean: Deep-Sea Research Part I: Oceanographic Research Papers, v. 110, p. 1-19, https://doi.org/10.1016/j.dsr.2015.11.006.","productDescription":"19 p.","startPage":"1","endPage":"19","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064986","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":318361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Ninetyeast Ridge, Indian Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 86.2646484375,\n -30.48655084258847\n ],\n [\n 112.8515625,\n -30.48655084258847\n ],\n [\n 112.8515625,\n -4.34641127533318\n ],\n [\n 86.2646484375,\n -4.34641127533318\n ],\n [\n 86.2646484375,\n -30.48655084258847\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"110","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56ced431e4b015c306ec2fde","contributors":{"authors":[{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":621234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, Tracey A.","contributorId":52540,"corporation":false,"usgs":true,"family":"Conrad","given":"Tracey A.","affiliations":[],"preferred":false,"id":621235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":621236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banakar, Virupaxa K.","contributorId":167153,"corporation":false,"usgs":false,"family":"Banakar","given":"Virupaxa","email":"","middleInitial":"K.","affiliations":[{"id":24631,"text":"Council for Scientific & Industrial Research, National Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":621237,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frey, Frederick A.","contributorId":167154,"corporation":false,"usgs":false,"family":"Frey","given":"Frederick","email":"","middleInitial":"A.","affiliations":[{"id":24632,"text":"Earth, Atmospheric & Planetary Sciences, MIT","active":true,"usgs":false}],"preferred":false,"id":621238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sager, William W.","contributorId":167155,"corporation":false,"usgs":false,"family":"Sager","given":"William","email":"","middleInitial":"W.","affiliations":[{"id":24633,"text":"Earth & Atmospheric Sciences, University of Houston","active":true,"usgs":false}],"preferred":false,"id":621239,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70161867,"text":"sir20155185 - 2016 - Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow","interactions":[],"lastModifiedDate":"2017-10-12T19:59:21","indexId":"sir20155185","displayToPublicDate":"2016-02-24T13:00:00","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":"2015-5185","title":"Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow","docAbstract":"The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba and the State of North Dakota. In May and June of 2011, record-setting rains were seen in the headwater areas of the basin. Emergency spillways of major reservoirs were discharging at full or nearly full capacity, and extensive flooding was seen in numerous downstream communities. To determine the probability of future extreme floods and droughts, the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, developed a stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural (unregulated) streamflow. Simulations from the model can be used in future studies to simulate regulated streamflow, design levees, and other structures; and to complete economic cost/benefit analyses.
Long-term climatic variability was analyzed using tree-ring chronologies to hindcast precipitation to the early 1700s and compare recent wet and dry conditions to earlier extreme conditions. The extended precipitation record was consistent with findings from the Devils Lake and Red River of the North Basins (southeast of the Souris River Basin), supporting the idea that regional climatic patterns for many centuries have consisted of alternating wet and dry climate states.
A stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration for the Souris River Basin was developed using recorded meteorological data and extended precipitation records provided through tree-ring analysis. A significant climate transition was seen around1970, with 1912–69 representing a dry climate state and 1970–2011 representing a wet climate state. Although there were some distinct subpatterns within the basin, the predominant differences between the two states were higher spring through early fall precipitation and higher spring potential evapotranspiration for the wet compared to the dry state.
A water-balance model was developed for simulating monthly natural (unregulated) mean streamflow based on precipitation, temperature, and potential evapotranspiration at select streamflow-gaging stations. The model was calibrated using streamflow data from the U.S. Geological Survey and Environment Canada, along with natural (unregulated) streamflow data from the U.S. Army Corps of Engineers. Correlation coefficients between simulated and natural (unregulated) flows generally were high (greater than 0.8), and the seasonal means and standard deviations of the simulated flows closely matched the means and standard deviations of the natural (unregulated) flows. After calibrating the model for a monthly time step, monthly streamflow for each subbasin was disaggregated into three values per month, or an approximately 10-day time step, and a separate routing model was developed for simulating 10-day streamflow for downstream gages.
The stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration was combined with the water-balance model to simulate potential future sequences of 10-day mean streamflow for each of the streamflow-gaging station locations. Flood risk, as determined by equilibrium flow-frequency distributions for the dry (1912–69) and wet (1970–2011) climate states, was considerably higher for the wet state compared to the dry state. Future flood risk will remain high until the wet climate state ends, and for several years after that, because there may be a long lag-time between the return of drier conditions and the onset of a lower soil-moisture storage equilibrium.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155185","collaboration":"Prepared in cooperation with the North Dakota State Water Commission","usgsCitation":"Kolars, K.A., Vecchia, A.V., and Ryberg, K.R., 2016, Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow: U.S. Geological Survey Scientific Investigations Report 2015–5185, 55 p., https://dx.doi.org/10.3133/sir20155185.","productDescription":"viii, 55 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068149","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":318270,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5185/sir20155185.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5185"},{"id":318269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5185/coverthb.jpg"}],"country":"Canada, United States","state":"Manitoba, North Dakota, Saskatchewan","otherGeospatial":"Souris River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.04052734375,\n 48.99824008113872\n ],\n [\n -104.74365234375,\n 49.42884000063522\n ],\n [\n -104.7930908203125,\n 50.004208515595614\n ],\n [\n -103.480224609375,\n 50.52041218671901\n ],\n [\n -102.0245361328125,\n 50.604159488561\n ],\n [\n -101.195068359375,\n 50.25071752130677\n ],\n [\n -100.65673828125,\n 49.745781306155735\n ],\n [\n -99.60891723632812,\n 49.648069803718805\n ],\n [\n -99.18594360351562,\n 49.577773933420914\n ],\n [\n -99.2340087890625,\n 49.39131220507362\n ],\n [\n -99.76547241210936,\n 49.413653634531116\n ],\n [\n -99.4482421875,\n 48.100094697973795\n ],\n [\n -101.502685546875,\n 47.99727386804474\n ],\n [\n -103.568115234375,\n 48.52388120259336\n ],\n [\n -104.04052734375,\n 48.99824008113872\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS North Dakota Water Science Center
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Incompatible insect techniques are potential methods for controlling Culex quinquefasciatus and avian disease transmission in Hawai‘i without the use of pesticides or genetically modified organisms. The approach is based on naturally occurring sperm-egg incompatibilities within the Culex pipiens complex that are controlled by different strains of the bacterial endosymbiont Wolbachia pipientis (wPip). Incompatibilities can be unidirectional (crosses between males infected with strain A and females infected with strain B are fertile, while reciprocal crosses are not) or bidirectional (reciprocal crosses between sexes with different wPip strains are infertile). The technique depends on release of sufficient numbers of male mosquitoes infected with an incompatible wPip strain to suppress mosquito populations and reduce transmission of introduced avian malaria (Plasmodium relictum) and Avipoxvirus in native forest bird habitats. Both diseases are difficult to manage using more traditional methods based on removal and treatment of larval habitats and coordination of multiple approaches may be needed to control this vector. We characterized the diversity of Wolbachia strains in C. quinquefasciatus from Hawai‘i, Kaua‘i, Midway Atoll, and American Samoa with a variety of genetic markers to identify compatibility groups and their distribution within and between islands. We confirmed the presence of wPip with multilocus sequence typing, tested for local genetic variability using 16 WO prophage genes, and identified similarities to strains from other parts of the world with a transposable element (tr1). We also tested for genetic differences in ankyrin motifs (ank2 and pk1) which have been used to classify wPip strains into five worldwide groups (wPip1–wPip5) that vary in compatibility with each other based on experimental crosses. We found a mixture of both widely distributed and site specific genotypes based on presence or absence of WO prophage and transposable element markers on Hawai‘i Island (Volcano, Pu‘u Wa‘awa‘a, Laupāhoehoe, Kaumana, Kahuku, Nīnole, and Maulua Gulch), Kaua‘i Island (Kawaikōī, Mōhihi, Kalāheo, Lāwa‘i and Hanapepe) and Midway Atoll. Genotypes from American Samoa were unique and formed their own clade. Based on analysis of ankyrin motifs, wPip strains from Hawai‘i, Kaua‘i, and Midway Atoll were most similar to wPip5 strains of Australasian origin. By contrast, Wolbachia strains from Culex quinquefasciatus collected in American Samoa were most similar to wPip3 strains of American origin. We detected a single Culex mosquito from Pu‘u Wa‘awa‘a on Hawai‘i Island that was infected with a unique wPip3 genotype. This discovery, plus a rarefaction analysis of genotypes from Kaua‘i and Hawai‘i Islands suggests that limited sampling may have underestimated diversity of wPip in our study. Mosquitoes infected with wPip5 and wPip3 are bidirectionally compatible with each other based on prior studies, which would support their ability to coexist within the same population on Hawai‘i Island. Available evidence from prior studies suggests that genotype wPip4 from Africa, the Middle East, Europe, and Asia is bidirectionally incompatible with genotype wPip5 and varies in compatibility with genotype wPip3 depending on geographic origin. Since wPip5 appears to be the most common compatibility group in Hawai‘i based on limited sampling, logical next steps are to 1) expand the current survey to include additional islands and localities, 2) infect a laboratory colony of Hawaiian Culex with wPip4 through tetracycline treatment of Hawaiian mosquitoes and backcross with Culex from Europe, North Africa, and the Middle East that are naturally infected with wPip4, 3) conduct cage trials to confirm bidirectional incompatibilities between Hawaiian Culex infected with wPip4 and wPip5, and 4) conduct field trials to evaluate whether release of incompatible males can be applied at small scales to suppress local populations.
","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, Hi","collaboration":"This product was prepared under Cooperative Agreement G15AC00191 for the Pacific Island Ecosystems Research Center of the U.S. Geological Survey.","usgsCitation":"Atkinson, C.T., Watcher-Weatherwax, W., and Lapointe, D., 2016, Genetic diversity of Wolbachia endosymbionts in Culex quinquefasciatus from Hawai`i, Midway Atoll, and Samoa: Technical Report HCSU-074, Report: iv, 33 p.","productDescription":"Report: iv, 33 p.","startPage":"1","endPage":"33","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073512","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328011,"type":{"id":15,"text":"Index 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Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Are brown trout replacing or displacing bull trout populations in a changing climate?","docAbstract":"Understanding how climate change may facilitate species turnover is an important step in identifying potential conservation strategies. We used data from 33 sites in western Montana to quantify climate associations with native bull trout (Salvelinus confluentus) and non-native brown trout (Salmo trutta) abundance and population growth rates (λ). We estimated λ using exponential growth state space models and delineated study sites based on bull trout use for either Spawning and Rearing (SR) or Foraging, Migrating, and Overwintering (FMO) habitat. Bull trout abundance was negatively associated with mean August stream temperatures within SR habitat (r = -0.75). Brown trout abundance was generally highest at temperatures between 12 and 14°C. We found bull trout λ were generally stable at sites with mean August temperature below 10°C but significantly decreasing, rare, or extirpated at 58% of the sites with temperatures exceeding 10°C. Brown trout λ were highest in SR and sites with temperatures exceeding 12°C. Declining bull trout λs at sites where brown trout were absent suggests brown trout are likely replacing bull trout in a warming climate.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0293","usgsCitation":"Al-Chokhachy, R.K., Schmetterling, D.A., Clancy, C., Saffel, P., Kovach, R., Nyce, L., Liermann, B., Fredenberg, W.A., and Pierce, R., 2016, Are brown trout replacing or displacing bull trout populations in a changing climate?: Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 9, p. 1395-1404, https://doi.org/10.1139/cjfas-2015-0293.","productDescription":"10 p.","startPage":"1395","endPage":"1404","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070449","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":326148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.1474609375,\n 47.60616304386874\n ],\n [\n -109.2919921875,\n 47.45780853075031\n ],\n [\n -109.599609375,\n 45.521743896993634\n ],\n [\n -116.19140625,\n 45.30580259943578\n ],\n [\n -116.23535156249999,\n 47.30903424774781\n ],\n [\n -116.1474609375,\n 47.60616304386874\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"73","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a5b8b4e4b0ebae89b7884e","contributors":{"authors":[{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmetterling, David A.","contributorId":20223,"corporation":false,"usgs":true,"family":"Schmetterling","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":644796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clancy, Chris","contributorId":173465,"corporation":false,"usgs":false,"family":"Clancy","given":"Chris","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saffel, Pat","contributorId":173466,"corporation":false,"usgs":false,"family":"Saffel","given":"Pat","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kovach, Ryan 0000-0001-5402-2123 rkovach@usgs.gov","orcid":"https://orcid.org/0000-0001-5402-2123","contributorId":145914,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nyce, Leslie","contributorId":173467,"corporation":false,"usgs":false,"family":"Nyce","given":"Leslie","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644800,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liermann, Brad","contributorId":173468,"corporation":false,"usgs":false,"family":"Liermann","given":"Brad","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644801,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fredenberg, Wade A.","contributorId":78860,"corporation":false,"usgs":true,"family":"Fredenberg","given":"Wade","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":644802,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pierce, Ron","contributorId":171578,"corporation":false,"usgs":false,"family":"Pierce","given":"Ron","email":"","affiliations":[{"id":6581,"text":"Montana Fish, Wildlife and Parks, Kalispell, Montana 59901, USA","active":true,"usgs":false}],"preferred":false,"id":644803,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70161955,"text":"sir20155163 - 2016 - Groundwater ages from the freshwater zone of the Edwards aquifer, Uvalde County, Texas—Insights into groundwater flow and recharge","interactions":[],"lastModifiedDate":"2016-02-24T09:17:23","indexId":"sir20155163","displayToPublicDate":"2016-02-23T13:00:00","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":"2015-5163","title":"Groundwater ages from the freshwater zone of the Edwards aquifer, Uvalde County, Texas—Insights into groundwater flow and recharge","docAbstract":"Tritium–helium-3 groundwater ages of the Edwards aquifer in south-central Texas were determined as part of a long-term study of groundwater flow and recharge in the Edwards and Trinity aquifers. These ages help to define groundwater residence times and to provide constraints for calibration of groundwater flow models. A suite of 17 samples from public and private supply wells within Uvalde County were collected for active and noble gases, and for tritium–helium-3 analyses from the confined and unconfined parts of the Edwards aquifer. Samples were collected from monitoring wells at discrete depths in open boreholes as well as from integrated pumped well-head samples. The data indicate a fairly uniform groundwater flow system within an otherwise structurally complex geologic environment comprised of regionally and locally faulted rock units, igneous intrusions, and karst features within carbonate rocks. Apparent ages show moderate, downward average, linear velocities in the Uvalde area with increasing age to the east along a regional groundwater flow path. Though the apparent age data show a fairly consistent distribution across the study area, many apparent ages indicate mixing of both modern (less than 60 years) and premodern (greater than 60 years) waters. This mixing is most evident along the “bad water” line, an arbitrary delineation of 1,000 milligrams per liter dissolved solids that separates the freshwater zone of the Edwards aquifer from the downdip saline water zone. Mixing of modern and premodern waters also is indicated within the unconfined zone of the aquifer by high excess helium concentrations in young waters. Excess helium anomalies in the unconfined aquifer are consistent with possible subsurface discharge of premodern groundwater from the underlying Trinity aquifer into the younger groundwater of the Edwards aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155163","usgsCitation":"Hunt, A.G., Landis, G.P., and Faith, J.R., 2016, Groundwater ages from the freshwater zone of the Edwards Aquifer, Uvalde County, Texas—Insights into groundwater flow and recharge: U.S. Geological Survey Scientific Investigations Report 2015–5163, 28 p., https://dx.doi.org/10.3133/sir20155163.","productDescription":"viii, 28 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065915","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":318180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5163/coverthb.jpg"},{"id":318181,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5163/sir20155163.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5163"}],"country":"United States","state":"Texas","county":"Uvalde County","otherGeospatial":"Edwards Aquifer","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.4132,29.6253],[-99.4107,29.087],[-99.6813,29.0872],[-100.1119,29.0844],[-100.1112,29.3486],[-100.111,29.6236],[-100.0145,29.6237],[-99.6173,29.6257],[-99.6033,29.6257],[-99.4132,29.6253]]]},\"properties\":{\"name\":\"Uvalde\",\"state\":\"TX\"}}]}","contact":"Center Director, USGS Crustal Geophysics and Geochemistry Science Center
Box 25046, Mail Stop 964
Denver, CO 80225
Arsenic concentrations were measured in samples from 168 domestic wells in Licking County, Ohio, to document arsenic concentrations in a wide variety of wells and to identify hydrogeologic factors associated with arsenic concentrations in groundwater. Elevated concentrations of arsenic (greater than 10.0 micrograms per liter [µg/L]) were detected in 12 percent of the wells (about 1 in 8). The maximum arsenic concentration of about 44 µg/L was detected in two wells in the same township.
A subset of 102 wells was also sampled for iron, sulfate, manganese, and nitrate, which were used to estimate redox conditions of the groundwater. Elevated arsenic concentrations were detected only in strongly reducing groundwater. Almost 20 percent of the samples with iron concentrations high enough to produce iron staining (greater than 300 µg/L) also had elevated concentrations of arsenic.
In groundwater, arsenic primarily occurs as two inorganic species—arsenite and arsenate. Arsenic speciation was determined for a subset of nine samples, and arsenite was the predominant species. Of the two species, arsenite is more difficult to remove from water, and is generally considered to be more toxic to humans.
Aquifer and well-construction characteristics were compiled from 99 well logs. Elevated concentrations of arsenic (and iron) were detected in glacial and bedrock aquifers but were more prevalent in glacial aquifers. The reason may be that the glacial deposits typically contain more organic carbon than the Paleozoic bedrock. Organic carbon plays a role in the redox reactions that cause arsenic (and iron) to be released from the aquifer matrix. Arsenic concentrations were not significantly different for different types of bedrock (sandstone, shale, sandstone/shale, or other). However, arsenic concentrations in bedrock wells were correlated with two well-construction characteristics; higher arsenic concentrations in bedrock wells were associated with (1) shorter open intervals and (2) deeper open intervals, relative to the water level.
The spatial distribution of arsenic concentrations was compared to hydrogeologic characteristics of Licking County. Elevated concentrations of arsenic (and iron) were associated with areas of flat topography and thick (greater than 100 feet),clay-rich glacial deposits. These characteristics are conducive to development of strongly reducing redox conditions, which can cause arsenic associated with iron oxyhydroxides in the aquifer matrix to be released to the groundwater.
Hydrogeologic characteristics conducive to the development of strongly reducing groundwater are relatively wide-spread in the western part of Licking County, which is part of the Central Lowland physiographic province. In this area, a thick layer of clay-rich glacial deposits obscures the bedrock surface and creates flat to gently rolling landscape with poorly developed drainage networks. In the eastern part of the county, which is part of the Appalachian Plateaus physiographic province, the landscape includes steep-sided valleys and bedrock uplands. In this area, elevated arsenic concentrations were detected in buried valleys but not in the bedrock uplands, where glacial deposits are thin or absent. The observation that elevated concentrations of arsenic (and iron) were more prevalent in the western part of Licking County is true for both glacial and bedrock aquifers.
In Licking County, thick, clay-rich glacial deposits (and elevated concentrations of arsenic) are associated with two hydrogeologic settings—buried valley and complex thick drift. Most wells in the buried-valley setting had low arsenic concentrations, but a few samples had very high concentrations (30–44 µg/L) and very reducing redox conditions (methanogenic and near-methanogenic). For wells in the complex-thick-drift setting, elevated arsenic concentrations are more prevalent, but the maximum concentration was lower (about 21 µg/L). Similar observations were made about arsenic concentrations in parts of southwestern Ohio.
The hydrogeologic settings and characteristics associated with arsenic in Licking County also exist in other parts of Ohio. The statewide extent of these characteristics roughly corresponds to areas where elevated concentrations of arsenic are known to exist. This preliminary conceptual model can be tested and revised as additional wells are sampled for arsenic.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155148","isbn":"978-1-4113-4008-4","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Thomas, M.A., 2016, Arsenic in groundwater of Licking County, Ohio, 2012—Occurrence and relation to hydrogeology:\nU.S. Geological Survey Scientific Investigations Report 2015–5148, 38 p., https://dx.doi.org/10.3133/sir20155148.","productDescription":"Report: vii, 38 p.; Table","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065867","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":318250,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5148/sir20155148_table2.xlsx","text":"Table 2. Water-quality and hydrogeologic data for 168 domestic wells in Licking County, Ohio, 2012.","size":"108 kb","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5148 Table 2."},{"id":318247,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5148/coverthb.jpg"},{"id":318248,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5148/sir20155148.pdf","text":"Report","size":"9.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5148"}],"country":"United States","state":"Ohio","county":"Licking County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.96875,\n 39.95185892663003\n ],\n [\n -82.96875,\n 40.50544628405211\n ],\n [\n -81.89208984375,\n 40.50544628405211\n ],\n [\n -81.89208984375,\n 39.95185892663003\n ],\n [\n -82.96875,\n 39.95185892663003\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Ohio Water Science Center
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This study analyzes the active tectonics within the northwestern and southeastern extensions of the Pambak-Sevan-Syunik fault (PSSF), a major right-lateral strike-slip fault cutting through Armenia. Quantifying the deformations in terms of geometry, kinematics, slip rates and earthquake activity, using cosmogenic 3He, OSL/IRSL and radiocarbon dating techniques, reveal different behaviors between the two regions. Within the northwestern extension, in the region of Amasia, the PSSF bends to the west and splits into two main WNW–ESE trending reverse faults defining a compressional pop-up structure. We estimate an uplift rate and a shortening rate of 0.5 ± 0.1 mm/y and 1.4 ± 0.6 mm/y, respectively. This suggests that most of the ∼2 mm/y right lateral movement of the PSSF seems to be absorbed within the Amasia pop-structure. Within the southeastern extension, the PSSF shows signs of dying out within the Tsghuk Volcano region at the southernmost tip of the Syunik graben. There, the tectonic activity is characterized by a very slow NS trending normal faulting associated with a slight right-lateral movement. Slip rates analyses (i.e. vertical slip rate, EW stretching rate at 90° to the fault, and right-lateral slip rate of ∼0.2 mm/y, ∼0.1 mm/y and ∼0.05 mm/y, respectively) lead to the conclusion that the right lateral movement observed further north along the PSSF is mainly transferred within other active faults further west within the Karabagh (Hagari fault or other structures further northwestwards). Comparing our slip rates with those estimated from GPS data suggests that most of the deformation is localized and seismic, at least within the Tsghuk region. The geometrical and kinematic pattern observed within the two terminations of the PSSF suggests that the fault and its surrounding crustal blocks are presently rotating anticlockwise, as also observed within the GPS velocity field. This is consistent with the recent kinematic models proposed for the Caucasus-Kura-South Caspian region and brings a new insight into the present geodynamics of Armenia.
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Sediment accumulation threatens the viability and hydrologic functioning of many naturally formed depressional wetlands across the interior regions of North America. These wetlands provide many ecosystem services and vital habitats for diverse plant and animal communities. Climate change may further impact sediment accumulation rates in the context of current land use patterns. We estimated sediment accretion in wetlands within a region renowned for its large populations of breeding waterfowl and migrant shorebirds and examined the relative roles of precipitation and land use context in the sedimentation process. We modeled rates of sediment accumulation from 1971 through 2100 using the Revised Universal Soil Loss Equation (RUSLE) with a sediment delivery ratio and the Unit Stream Power Erosion Deposition model (USPED). These models predicted that by 2100, 21–33 % of wetlands filled completely with sediment and 27–46 % filled by half with sediments; estimates are consistent with measured sediment accumulation rates in the region reported by empirical studies. Sediment accumulation rates were strongly influenced by size of the catchment, greater coverage of tilled landscape within the catchment, and steeper slopes. Conservation efforts that incorporate the relative risk of infilling of wetlands with sediments, thus emphasizing areas of high topographic relief and large watersheds, may benefit wetland-dependent biota.
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rainfall occurred across South Carolina during October 1–5, 2015, as a result of an upper atmospheric low-pressure system that funneled tropical moisture from Hurricane Joaquin into the State. The storm caused major flooding in the central and coastal parts of South Carolina. Almost 27 inches of rain fell near Mount Pleasant in Charleston County during this period. U.S. Geological Survey (USGS) streamgages recorded peaks of record at 17 locations, and 15 other locations had peaks that ranked in the top 5 for the period of record. During the October 2015 flood event, USGS personnel made about 140 streamflow measurements at 86 locations to verify, update, or extend existing rating curves (which are used to compute streamflow from monitored river stage). Immediately after the storm event, USGS personnel documented 602 high-water marks, noting the location and height of the water above land surface. Later in October, 50 additional high-water marks were documented near bridges for South Carolina Department of Transportation. Using a subset of these high-water marks, 20 flood-inundation maps of 12 communities were created. Digital datasets of the inundation area, modeling boundary, and water depth rasters are all available for download.
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720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Portable antennas have become an increasingly common technique for tracking fish marked with passive integrated transponder (PIT) tags. We used logistic regression to evaluate how species, fish length, and physical habitat characteristics influence portable antenna detection efficiency in stream-dwelling brown trout (Salmo trutta), bull trout (Salvelinus confluentus), and redband trout (Oncorhynchus mykiss newberrii) marked with 12-mm PIT tags. We redetected 56% (20/36) of brown trout, 34% (68/202) of bull trout, and 33% (20/61) of redband trout after a recovery period of 21 to 46 hours. Models indicate support for length and species and minor support for percent boulder, large woody debris, and percent cobble as parameters important for describing variation in detection efficiency, although 95% confidence intervals for estimates were large. The odds of detecting brown trout (1.5 ± 2.2 [mean ± SE]) are approximately four times as high as bull trout (0.4 ± 1.6) or redband trout (0.3 ± 1.8) and species-specific differences may be related to length. Our reported detection efficiency for brown trout falls within the range of other studies, but is the first reported for bull trout and redband trout. Portable antennas may be a relatively unbiased way of redetecting varying sizes of all three salmonid species.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0149898","usgsCitation":"Banish, N.P., Burdick, S.M., and Moyer, K.R., 2016, Efficiency of portable antennas for detecting passive integrated transponder tags in stream-dwelling salmonids: PLoS ONE, v. 11, no. 2, e0149898, 10 p., https://doi.org/10.1371/journal.pone.0149898.","productDescription":"e0149898, 10 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052642","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":471214,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0149898","text":"Publisher Index Page"},{"id":319877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","county":"Klamath County, Lake County","otherGeospatial":"Boulder Creek, Brownsworth Creek, Klamath River basin, Leonard Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.9,\n 42.45\n ],\n [\n -120.9,\n 42.55\n ],\n [\n -120.8,\n 42.55\n ],\n [\n -120.8,\n 42.45\n ],\n [\n -120.9,\n 42.45\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-22","publicationStatus":"PW","scienceBaseUri":"572485fde4b0b13d39159452","contributors":{"authors":[{"text":"Banish, Nolan P.","contributorId":168511,"corporation":false,"usgs":false,"family":"Banish","given":"Nolan","email":"","middleInitial":"P.","affiliations":[{"id":25313,"text":"U.S. Fish and Wildlife Service, Klamath Falls Fish and Wildlife Office, 1936 California Avenue, Klamath Falls, Oregon, 97601, USA","active":true,"usgs":false}],"preferred":false,"id":626212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burdick, Summer M. 0000-0002-3480-5793 sburdick@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-5793","contributorId":3448,"corporation":false,"usgs":true,"family":"Burdick","given":"Summer","email":"sburdick@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":626211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moyer, Katherine R.","contributorId":168512,"corporation":false,"usgs":false,"family":"Moyer","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":25314,"text":"Conservation and Land Management Internship Program, Chicago Botanic Garden, 1000 Lake Cook Road, Glencoe, Illinois, 60022, USA","active":true,"usgs":false}],"preferred":false,"id":626213,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70177889,"text":"70177889 - 2016 - Toward a quantitative and empirical dissolved organic carbon budget for the Gulf of Maine, a semienclosed shelf sea","interactions":[],"lastModifiedDate":"2016-10-26T14:12:02","indexId":"70177889","displayToPublicDate":"2016-02-20T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Toward a quantitative and empirical dissolved organic carbon budget for the Gulf of Maine, a semienclosed shelf sea","docAbstract":"A time series of organic carbon export from Gulf of Maine (GoM) watersheds was compared to a time series of biological, chemical, bio-optical, and hydrographic properties, measured across the GoM between Yarmouth, NS, Canada, and Portland, ME, U.S. Optical proxies were used to quantify the dissolved organic carbon (DOC) and particulate organic carbon in the GoM. The Load Estimator regression model applied to river discharge data demonstrated that riverine DOC export (and its decadal variance) has increased over the last 80 years. Several extraordinarily wet years (2006–2010) resulted in a massive pulse of chromophoric dissolved organic matter (CDOM; proxy for DOC) into the western GoM along with unidentified optically scattering material (<0.2 μm diameter). A survey of DOC in the GoM and Scotian Shelf showed the strong influence of the Gulf of Saint Lawrence on the DOC that enters the GoM. A deep plume of CDOM-rich water was observed near the coast of Maine which decreased in concentration eastward. The Forel-Ule color scale was derived and compared to the same measurements made in 1912–1913 by Henry Bigelow. Results show that the GoM has yellowed in the last century, particularly in the region of the extension of the Eastern Maine Coastal Current. Time lags between DOC discharge and its appearance in the GoM increased with distance from the river mouths. Algae were also a significant source of DOC but not CDOM. Gulf-wide algal primary production has decreased. 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600 4th Street South
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(727) 502-8000
http://coastal.er.usgs.gov/
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The coupled effect of bivalve grazing at the sediment-water interface and sinking of phytoplankton cells to that bottom filtration zone could influence the relative biomass of sinking (diatoms) and non-sinking phytoplankton. Simulations with a pseudo-2D numerical model showed that benthic filter feeding can interact with sinking to alter diatom:non-diatom ratios. Cases with the smallest proportion of diatom biomass were those with the fastest sinking speeds and strongest bivalve grazing rates. Hydrodynamics modulated the coupled sinking-grazing influence on phytoplankton communities. For example, in simulations with persistent stratification, the non-sinking forms accumulated in the surface layer away from bottom grazers while the sinking forms dropped out of the surface layer toward bottom grazers. Tidal-scale stratification also influenced vertical gradients of the two groups in opposite ways. 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future climate conditions. Current and hypothetical operations and structures at Detroit Dam were imposed on boundary conditions derived from downscaled General Circulation Models in base (1990–1999) and future (2059–2068) periods. Compared with the base period, future air temperatures were about 2 °C warmer year-round. Higher air temperature and lower precipitation under the future period resulted in a 23% reduction in mean annual PRMS-simulated discharge and a 1 °C increase in mean annual estimated stream temperatures flowing into the lake compared to the base period. Simulations incorporating current operational rules and minimum release rates at Detroit Dam to support downstream habitat, irrigation, and water supply during key times of year resulted in lower future lake levels. That scenario results in a lake level that is above the dam’s spillway crest only about half as many days in the future compared to historical frequencies. Managing temperature downstream of Detroit Dam depends on the ability to blend warmer water from the lake’s surface with cooler water from deep in the lake, and the spillway is an important release point near the lake’s surface. Annual average in-lake and release temperatures from Detroit Lake warmed 1.1 °C and 1.5 °C from base to future periods under present-day dam operational rules and fill schedules. Simulated dam operations such as beginning refill of the lake 30 days earlier or reducing minimum release rates (to keep more water in the lake to retain the use of the spillway) mitigated future warming to 0.4 and 0.9 °C below existing operational scenarios during the critical autumn spawning period for endangered salmonids. A hypothetical floating surface withdrawal at Detroit Dam improved temperature control in summer and autumn (0.6 °C warmer in summer, 0.6 °C cooler in autumn compared to existing structures) without altering release rates or lake level management rules.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"New York","doi":"10.1016/j.jhydrol.2016.01.062","collaboration":"USACE","usgsCitation":"Buccola, N.L., Risley, J.C., and Rounds, S.A., 2016, Simulating future water temperatures in the North Santiam River, Oregon: Journal of Hydrology, v. 535, p. 318-330, https://doi.org/10.1016/j.jhydrol.2016.01.062.","productDescription":"13 p.","startPage":"318","endPage":"330","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066718","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":471223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2016.01.062","text":"Publisher Index Page"},{"id":318165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.178955078125,\n 44.79158175909386\n ],\n [\n -122.21603393554688,\n 44.775986224030376\n ],\n [\n -122.30255126953126,\n 44.775986224030376\n ],\n [\n -122.31491088867186,\n 44.73795445686983\n ],\n [\n -122.32177734375,\n 44.692088041727814\n ],\n [\n -122.31353759765624,\n 44.66962952692013\n ],\n [\n -122.2723388671875,\n 44.65009330721101\n ],\n [\n -122.22427368164064,\n 44.63934558051711\n ],\n [\n -122.14187622070311,\n 44.623708968901205\n ],\n [\n -122.08694458007812,\n 44.58068656459206\n ],\n [\n -122.09793090820311,\n 44.524905626703834\n ],\n [\n -122.02926635742188,\n 44.4867089169177\n ],\n [\n -121.91940307617188,\n 44.473971118440275\n ],\n [\n -121.79718017578124,\n 44.4808302785626\n ],\n [\n -121.76971435546874,\n 44.56601255400719\n ],\n [\n -121.74087524414064,\n 44.67548910920999\n ],\n [\n -121.74911499023438,\n 44.73600343509071\n ],\n [\n -121.74911499023438,\n 44.790607161582656\n ],\n [\n -121.79580688476562,\n 44.811070253260006\n ],\n [\n -121.90292358398438,\n 44.82860426955568\n ],\n [\n -121.95785522460936,\n 44.8500274926005\n ],\n [\n -121.99905395507812,\n 44.87046950217272\n ],\n [\n -122.06909179687501,\n 44.84808025602074\n ],\n [\n -122.1240234375,\n 44.824708282300236\n ],\n [\n -122.178955078125,\n 44.79158175909386\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"535","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56c84acce4b0b3c9ae3810a3","contributors":{"authors":[{"text":"Buccola, Norman L. 0000-0002-9590-2458 nbuccola@usgs.gov","orcid":"https://orcid.org/0000-0002-9590-2458","contributorId":139096,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman","email":"nbuccola@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Risley, John C. 0000-0002-8206-5443 jrisley@usgs.gov","orcid":"https://orcid.org/0000-0002-8206-5443","contributorId":2698,"corporation":false,"usgs":true,"family":"Risley","given":"John","email":"jrisley@usgs.gov","middleInitial":"C.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":620890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168510,"text":"70168510 - 2016 - Fishing diseased abalone to promote yield and conservation","interactions":[],"lastModifiedDate":"2016-02-18T09:29:57","indexId":"70168510","displayToPublicDate":"2016-02-18T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3048,"text":"Philosophical Transactions of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Fishing diseased abalone to promote yield and conservation","docAbstract":"Past theoretical models suggest fishing disease-impacted stocks can reduce parasite transmission, but this is a good management strategy only when the exploitation required to reduce transmission does not overfish the stock. We applied this concept to a red abalone fishery so impacted by an infectious disease (withering syndrome) that stock densities plummeted and managers closed the fishery. In addition to the non-selective fishing strategy considered by past disease-fishing models, we modelled targeting (culling) infected individuals, which is plausible in red abalone because modern diagnostic tools can determine infection without harming landed abalone and the diagnostic cost is minor relative to the catch value. The non-selective abalone fishing required to eradicate parasites exceeded thresholds for abalone sustainability, but targeting infected abalone allowed the fishery to generate yield and reduce parasite prevalence while maintaining stock densities at or above the densities attainable if the population was closed to fishing. The effect was strong enough that stock and yield increased even when the catch was one-third uninfected abalone. These results could apply to other fisheries as the diagnostic costs decline relative to catch value.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2015.0211","usgsCitation":"Ben-Horin, T., Lafferty, K.D., Bidegain, G., and Lenihan, H.S., 2016, Fishing diseased abalone to promote yield and conservation: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 371, no. 1689, art20150211, https://doi.org/10.1098/rstb.2015.0211.","productDescription":"art20150211","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071571","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471224,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2015.0211","text":"Publisher Index Page"},{"id":318125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"371","issue":"1689","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-05","publicationStatus":"PW","scienceBaseUri":"56c6eb28e4b0946c6523b0c5","contributors":{"authors":[{"text":"Ben-Horin, Tal","contributorId":58137,"corporation":false,"usgs":false,"family":"Ben-Horin","given":"Tal","email":"","affiliations":[],"preferred":false,"id":620737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":620736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bidegain, Gorka","contributorId":167008,"corporation":false,"usgs":false,"family":"Bidegain","given":"Gorka","email":"","affiliations":[{"id":13403,"text":"University of Southern Mississippi, Department of Biological Sciences, Hattiesburg, Mississippi, USA","active":true,"usgs":false}],"preferred":false,"id":620738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lenihan, Hunter S.","contributorId":94227,"corporation":false,"usgs":true,"family":"Lenihan","given":"Hunter","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":620739,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168659,"text":"70168659 - 2016 - Testing the suitability of geologic frameworks for extrapolating hydraulic properties across regional scales","interactions":[],"lastModifiedDate":"2016-12-16T10:51:16","indexId":"70168659","displayToPublicDate":"2016-02-18T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Testing the suitability of geologic frameworks for extrapolating hydraulic properties across regional scales","docAbstract":"The suitability of geologic frameworks for extrapolating hydraulic conductivity (K) to length scales commensurate with hydraulic data is difficult to assess. A novel method is presented for evaluating assumed relations between K and geologic interpretations for regional-scale groundwater modeling. The approach relies on simultaneous interpretation of multiple aquifer tests using alternative geologic frameworks of variable complexity, where each framework is incorporated as prior information that assumes homogeneous K within each model unit. This approach is tested at Pahute Mesa within the Nevada National Security Site (USA), where observed drawdowns from eight aquifer tests in complex, highly faulted volcanic rocks provide the necessary hydraulic constraints. The investigated volume encompasses 40 mi3 (167 km3) where drawdowns traversed major fault structures and were detected more than 2 mi (3.2 km) from pumping wells. Complexity of the five frameworks assessed ranges from an undifferentiated mass of rock with a single unit to 14 distinct geologic units. Results show that only four geologic units can be justified as hydraulically unique for this location. The approach qualitatively evaluates the consistency of hydraulic property estimates within extents of investigation and effects of geologic frameworks on extrapolation. Distributions of transmissivity are similar within the investigated extents irrespective of the geologic framework. In contrast, the extrapolation of hydraulic properties beyond the volume investigated with interfering aquifer tests is strongly affected by the complexity of a given framework. Testing at Pahute Mesa illustrates how this method can be employed to determine the appropriate level of geologic complexity for large-scale groundwater modeling.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1375-1","usgsCitation":"Mirus, B.B., Halford, K.J., Sweetkind, D.S., and Fenelon, J.M., 2016, Testing the suitability of geologic frameworks for extrapolating hydraulic properties across regional scales: Hydrogeology Journal, v. 24, no. 5, p. 1133-1146, https://doi.org/10.1007/s10040-016-1375-1.","productDescription":"14 p.","startPage":"1133","endPage":"1146","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033309","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":490008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-016-1375-1","text":"Publisher Index Page"},{"id":318311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Pahute Mesa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.7,\n 37.3\n ],\n [\n -116.7,\n 37\n ],\n [\n -116.3,\n 37\n ],\n [\n -116.3,\n 37.3\n ],\n [\n -116.7,\n 37.3\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-18","publicationStatus":"PW","scienceBaseUri":"56cc4007e4b059daa47e46e5","contributors":{"authors":[{"text":"Mirus, Benjamin B.","contributorId":12348,"corporation":false,"usgs":false,"family":"Mirus","given":"Benjamin","email":"","middleInitial":"B.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":621173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halford, Keith J. 0000-0002-7322-1846 khalford@usgs.gov","orcid":"https://orcid.org/0000-0002-7322-1846","contributorId":1374,"corporation":false,"usgs":true,"family":"Halford","given":"Keith","email":"khalford@usgs.gov","middleInitial":"J.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":621176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweetkind, Donald S. 0000-0003-0892-4796 dsweetkind@usgs.gov","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":139913,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald","email":"dsweetkind@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":621174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fenelon, Joseph M. 0000-0003-4449-245X jfenelon@usgs.gov","orcid":"https://orcid.org/0000-0003-4449-245X","contributorId":2355,"corporation":false,"usgs":true,"family":"Fenelon","given":"Joseph","email":"jfenelon@usgs.gov","middleInitial":"M.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":621175,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168509,"text":"70168509 - 2016 - Cumulative drought and land-use impacts on perennial vegetation across a North American dryland region","interactions":[],"lastModifiedDate":"2016-06-15T16:18:08","indexId":"70168509","displayToPublicDate":"2016-02-17T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Cumulative drought and land-use impacts on perennial vegetation across a North American dryland region","docAbstract":"The decline and loss of perennial vegetation in dryland ecosystems due to global change pressures can alter ecosystem properties and initiate land degradation processes. We tracked changes of perennial vegetation using remote sensing to address the question of how prolonged drought and land-use intensification have affected perennial vegetation cover across a desert region in the early 21st century?
\nMojave Desert, southeastern California, southern Nevada, southwestern Utah and northwestern Arizona, USA.
\nWe coupled the Moderate-Resolution Imaging Spectroradiometer Enhanced Vegetation Index (MODIS-EVI) with ground-based measurements of perennial vegetation cover taken in about 2000 and about 2010. Using the difference between these years, we determined perennial vegetation changes in the early 21st century and related these shifts to climate, soil and landscape properties, and patterns of land use.
\nWe found a good fit between MODIS-EVI and perennial vegetation cover (2000: R2 = 0.83 and 2010: R2 = 0.74). The southwestern, far southeastern and central Mojave Desert had large declines in perennial vegetation cover in the early 21st century, while the northeastern and southeastern portions of the desert had increases. These changes were explained by 10-yr precipitation anomalies, particularly in the cool season and during extreme dry or wet years. Areas heavily impacted by visitor use or wildfire lost perennial vegetation cover, and vegetation in protected areas increased to a greater degree than in unprotected areas.
\nWe find that we can extrapolate previously documented declines of perennial plant cover to an entire desert, and demonstrate that prolonged water shortages coupled with land-use intensification create identifiable patterns of vegetation change in dryland regions.
\nReconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.
","language":"English","publisher":"International Environmetrics Society","doi":"10.1002/env.2368","usgsCitation":"Tipton, J., Hooten, M., Pederson, N., Tingley, M., and Bishop, D., 2016, Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models: Environmetrics, v. 27, no. 1, p. 42-54, https://doi.org/10.1002/env.2368.","productDescription":"13 p.","startPage":"42","endPage":"54","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065402","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":498967,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/env.2368","text":"Publisher Index Page"},{"id":318106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-29","publicationStatus":"PW","scienceBaseUri":"56c599abe4b0946c6521edf1","contributors":{"authors":[{"text":"Tipton, John","contributorId":166999,"corporation":false,"usgs":false,"family":"Tipton","given":"John","affiliations":[],"preferred":false,"id":620683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":619800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pederson, Neil","contributorId":149422,"corporation":false,"usgs":false,"family":"Pederson","given":"Neil","email":"","affiliations":[{"id":17731,"text":"Research Scientist, Tree Ring Laboratory, Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":620684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tingley, Martin","contributorId":167000,"corporation":false,"usgs":false,"family":"Tingley","given":"Martin","email":"","affiliations":[],"preferred":false,"id":620685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bishop, Daniel","contributorId":141104,"corporation":false,"usgs":false,"family":"Bishop","given":"Daniel","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":620686,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70164455,"text":"70164455 - 2016 - Wetting and drying of soil in response to precipitation: Data analysis, modeling, and forecasting","interactions":[],"lastModifiedDate":"2016-12-20T11:32:48","indexId":"70164455","displayToPublicDate":"2016-02-17T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Wetting and drying of soil in response to precipitation: Data analysis, modeling, and forecasting","docAbstract":"This paper investigates methods to analyze and forecast soil moisture time series. We extend an existing Antecedent Water Index (AWI) model, which expresses soil moisture as a function of time and rainfall. Unfortunately, the existing AWI model does not forecast effectively for time periods beyond a few hours. To overcome this limitation, we develop a novel AWI-based model. Our model accumulates rainfall over a time interval and can fit a diverse range of wetting and drying curves. In addition, parameters in our model reflect hydrologic redistribution processes of gravity and suction.We validate our models using experimental soil moisture and rainfall time series data collected from steep gradient post-wildfire sites in Southern California, where rapid landscape change was observed in response to small to moderate rain storms. We found that our novel model fits the data for three distinct soil textures, occurring at different depths below the ground surface (5, 15, and 30 cm). Our model also successfully forecasts soil moisture trends, such as drying and wetting rate.","conferenceTitle":"13th Conference of the Association for the Advancement of Artificial Intelligence","conferenceDate":"February 12–17, 2016","conferenceLocation":" Phoenix, Arizona ","language":"English","publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","collaboration":"Carnegie Mellon University","usgsCitation":"Basak, A., Kulkarni, C., Schmidt, K.M., and Mengshoel, O., 2016, Wetting and drying of soil in response to precipitation: Data analysis, modeling, and forecasting, 13th Conference of the Association for the Advancement of Artificial Intelligence, Phoenix, Arizona , February 12–17, 2016.","ipdsId":"IP-068964","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":332337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":316604,"type":{"id":15,"text":"Index Page"},"url":"https://www.aaai.org/Conferences/AAAI/aaai16.php"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585a51bfe4b01224f329b5ed","contributors":{"authors":[{"text":"Basak, Aniruddha","contributorId":156329,"corporation":false,"usgs":false,"family":"Basak","given":"Aniruddha","email":"","affiliations":[{"id":20319,"text":"Carnegie Mellon University, Silicon Valley","active":true,"usgs":false}],"preferred":false,"id":597456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulkarni, Chinmay","contributorId":156330,"corporation":false,"usgs":false,"family":"Kulkarni","given":"Chinmay","email":"","affiliations":[{"id":20319,"text":"Carnegie Mellon University, Silicon Valley","active":true,"usgs":false}],"preferred":false,"id":597457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":597455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mengshoel, Ole","contributorId":156331,"corporation":false,"usgs":false,"family":"Mengshoel","given":"Ole","email":"","affiliations":[{"id":20319,"text":"Carnegie Mellon University, Silicon Valley","active":true,"usgs":false}],"preferred":false,"id":597458,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168559,"text":"70168559 - 2016 - Demographic response of northern spotted owls to barred owl removal","interactions":[],"lastModifiedDate":"2018-02-23T16:07:04","indexId":"70168559","displayToPublicDate":"2016-02-17T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Demographic response of northern spotted owls to barred owl removal","docAbstract":"Federally listed as threatened in 1990 primarily because of habitat loss, the northern spotted owl (Strix occidentalis caurina) has continued to decline despite conservation efforts resulting in forested habitat being reserved throughout its range. Recently, there is growing evidence the congeneric invasive barred owl (Strix varia) may be responsible for the continued decline primarily by excluding spotted owls from their preferred habitat. We used a long-term demographic study for spotted owls in coastal northern California as the basis for a pilot barred owl removal experiment. Our demography study used capture–recapture, reproductive output, and territory occupancy data collected from 1990 to 2013 to evaluate trends in vital rates and populations. We used a classic before-after-control-impact (BACI) experimental design to investigate the demographic response of northern spotted owls to the lethal removal of barred owls. According to the best 2-species dynamic occupancy model, there was no evidence of differences in barred or northern spotted owl occupancy prior to the initiation of the treatment (barred owl removal). After treatment, barred owl occupancy was lower in the treated relative to the untreated areas and spotted owl occupancy was higher relative to the untreated areas. Barred owl removal decreased spotted owl territory extinction rates but did not affect territory colonization rates. As a result, spotted owl occupancy increased in the treated area and continued to decline in the untreated areas. Prior to and after barred owl removal, there was no evidence that average fecundity differed on the 2 study areas. However, the greater number of occupied spotted owl sites on the treated areas resulted in greater productivity in the treated areas based on empirical counts of fledged young. Prior to removal, survival was declining at a rate of approximately 0.2% per year for treated and untreated areas. Following treatment, estimated survival was 0.859 for the treated areas and 0.822 for the untreated areas. Derived estimates of population change on both study areas showed the same general decline before removal with an estimated slope of –0.0036 per year. Following removal, the rate of population change on the treated areas increased to an average of 1.029 but decreased to an average of 0.870 on the untreated areas. The results from this first experiment demonstrated that lethal removal of barred owls allowed the recovery of northern spotted owl populations in the treated portions of our study area. If additional federally funded barred owl removal experiments provide similar results, this could be the foundation for development of a long-term conservation strategy for northern spotted owls.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Washington, D.C.","doi":"10.1002/jwmg.1046","usgsCitation":"Diller, V.L., Hamm, K.A., Early, D.A., Lamphear, D., Dugger, K.M., Yackulic, C.B., Schwarz, C.J., Carlson, P., and McDonald, T.L., 2016, Demographic response of northern spotted owls to barred owl removal: Journal of Wildlife Management, v. 80, no. 4, p. 691-707, https://doi.org/10.1002/jwmg.1046.","productDescription":"17 p.","startPage":"691","endPage":"707","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065237","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":318296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Humboldt county, Del Norte county","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.4091796875,\n 40.204050425113294\n ],\n [\n -124.4091796875,\n 42.00032514831621\n ],\n [\n -123.321533203125,\n 42.00032514831621\n ],\n [\n -123.321533203125,\n 40.204050425113294\n ],\n [\n -124.4091796875,\n 40.204050425113294\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-17","publicationStatus":"PW","scienceBaseUri":"56cc3f4ae4b059daa47e43b0","contributors":{"authors":[{"text":"Diller, V. 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This study parameterized a bioenergetics model for the Threespine Stickleback using laboratory measurements to determine mass- and temperature-dependent functions for maximum consumption and routine respiration costs. Maximum consumption experiments were conducted across a range of temperatures from 7.5°C to 23.0°C and a range of fish weights from 0.5 to 4.5 g. Respiration experiments were conducted across a range of temperatures from 8°C to 28°C. Model sensitivity was consistent with other comparable models in that the mass-dependent parameters for maximum consumption were the most sensitive. Growth estimates based on the Threespine Stickleback bioenergetics model suggested that 22°C is the optimal temperature for growth when food is not limiting. The bioenergetics model performed well when used to predict independent, paired measures of consumption and growth observed from a separate wild population of Threespine Sticklebacks. Predicted values for consumption and growth (expressed as percent body weight per day) only deviated from observed values by 2.0%. Our model should provide insight into the physiological performance of this species across a range of environmental conditions and be useful for quantifying the trophic impact of this species in food webs containing other ecologically or economically important species.
","language":"English","publisher":"CrossMark","doi":"10.1080/00028487.2015.1079554","usgsCitation":"Hovel, R.A., Beauchamp, D.A., Hansen, A., and Sorel, M.H., 2016, Development of a bioenergetics model for the threespine stickleback Gasterosteus aculeatus: Transactions of the American Fisheries Society, v. 144, no. 6, p. 1311-1321, https://doi.org/10.1080/00028487.2015.1079554.","productDescription":"10 p.","startPage":"1311","endPage":"1321","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058066","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"144","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-03","publicationStatus":"PW","scienceBaseUri":"575be4abe4b04f417c27f51b","contributors":{"authors":[{"text":"Hovel, Rachel A.","contributorId":171740,"corporation":false,"usgs":false,"family":"Hovel","given":"Rachel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":638463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":638464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Adam G.","contributorId":103947,"corporation":false,"usgs":true,"family":"Hansen","given":"Adam G.","affiliations":[],"preferred":false,"id":638465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sorel, Mark H.","contributorId":171739,"corporation":false,"usgs":false,"family":"Sorel","given":"Mark","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":638466,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}