The Weighted Regressions on Time, Discharge, and Season (WRTDS) model was used to derive estimates of suspended-sediment concentration (SSC) and suspended-sediment load (SSL), their dependence on discharge, and their trends with confidence intervals, for one site each on the lowermost Mississippi and Atchafalaya Rivers. The WRTDS model reduces uncertainty in SSCs related to variable streamflow conditions. Flow-normalized SSCs in each river were similar, and decreased from about 260 mg/L to 130 mg/L from 1980 through 2015; combined annual SSL in the two rivers decreased from about 200 Megatons per year (MT/y) to about 100 MT/y. Declines in SSC and SSL were more gradual from 2005 through 2015 and show signs of stabilizing. Our estimates of SSL in 2015 differ markedly from several recently published estimates of current and projected future Mississippi River SSLs, which were generally around 200 MT/y. However, these values came mostly from a different site upstream on the Mississippi River. The relationship between SSC and streamflow differed in an important way between the two rivers. SSC increased as streamflow increased for the entire range of observed streamflow in the Atchafalaya River. In the Mississippi River, SSC followed the same pattern during low and moderate streamflow but decreased at the highest streamflow that tended to occur between January and July. Since much of the water flowing in the Atchafalaya originates from the Mississippi River, the difference suggests a within-basin source of suspended sediment for the Atchafalaya River that is absent in the lower Mississippi River. These findings have important implications for the restoration of deltaic wetlands in coastal Louisiana. Accurate estimates of the SSL available in each river are crucial for understanding how effective diversions of river water into adjacent estuaries will be in sustaining these wetlands. Our study demonstrates that there might be far less sediment available than previously reported. Further, the difference in the relationship between SSC and streamflow in the two rivers is highly relevant to the ongoing discussion of coastal restoration strategies because the delta building that is occurring at the mouth of the Atchafalaya River is frequently used as a model of what could be expected with controlled diversions in the lower Mississippi River delta. The differences in the SSC behavior with changes in streamflow between the two rivers needs to be considered when results from the Atchafalaya River system are projected to those of the Mississippi River.
The American crocodile Crocodylus acutus is a threatened species that uses relatively deep, open-water habitats with low salinity. Adult female American crocodiles nest on sandy coastal beaches, islands or human-made berms, assist in the hatching process, and can travel long distances to nesting habitat. We satellite-tracked 15 adult female American crocodiles in 2 hydrologically distinct areas in Everglades National Park, Florida, USA, to quantify the home range sizes, test for intraspecific differences in home range and core area size and structure, and identify important crocodile high-use areas. Overall home ranges (95% kernel density estimate; KDE) for adult female crocodiles in South Florida ranged from 30.0 to 141.9 km2 (mean ± SD, 84.4 ± 32.3 km2), and core areas (50% KDE) ranged from 4.7 to 27.4 km2(17.8 ± 7.3 km2). We identified patterns in home range and core area overlap, seasonally shifting patterns in core area use, and the Fox Lake complex as an important crocodile high-use area. As the population of American crocodiles continues to grow and expand into new areas, it is important for conservation managers to understand individual crocodile habitat-use patterns and spatial resource requirements.
","language":"English","publisher":"Inter-research","doi":"10.3354/esr00900","usgsCitation":"Hart, K.M., Beauchamp, J.S., Cherkiss, M.S., and Mazzotti, F., 2018, Variation in home range size and patterns in adult female American crocodiles Crocodylus acutus: Endangered Species Research, v. 36, p. 161-171, https://doi.org/10.3354/esr00900.","productDescription":"11 p.","startPage":"161","endPage":"171","ipdsId":"IP-093882 ","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468654,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00900","text":"Publisher Index Page"},{"id":356576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.83990478515625,\n 25.122905883812052\n ],\n [\n -80.2606201171875,\n 25.122905883812052\n ],\n [\n -80.2606201171875,\n 26.33280692289788\n ],\n [\n -81.83990478515625,\n 26.33280692289788\n ],\n [\n -81.83990478515625,\n 25.122905883812052\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2afe4b0702d0e842fb1","contributors":{"authors":[{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":742931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, Jeffrey S.","contributorId":138880,"corporation":false,"usgs":false,"family":"Beauchamp","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[{"id":12559,"text":"University of Florida, FLEC","active":true,"usgs":false}],"preferred":false,"id":742932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cherkiss, Michael S. 0000-0002-7802-6791 mcherkiss@usgs.gov","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":4571,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","email":"mcherkiss@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":742933,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazzotti, Frank","contributorId":138878,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":742934,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198069,"text":"70198069 - 2018 - DDT and related compounds in pore water of shallow sediments on the Palos Verdes Shelf, California, USA","interactions":[],"lastModifiedDate":"2018-07-16T11:06:02","indexId":"70198069","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2662,"text":"Marine Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"DDT and related compounds in pore water of shallow sediments on the Palos Verdes Shelf, California, USA","docAbstract":"For nearly two and a half decades following World War II, production wastes from the world's largest manufacturer of technical DDT (1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene) were discharged into sewers of Los Angeles County. Following treatment, the wastes were released via a submarine outfall system to nearshore coastal waters where a portion accumulated in shallow sediments of the Palos Verdes Shelf (PVS). An investigation of the pore-water geochemistry of DDT-related compounds (DDX) was undertaken in an effort to understand factors controlling the rate of reductive dechlorination (RDC) of the major DDT degradate, 4,4′-DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene). Equilibrium matrix-solid phase microextraction (matrix-SPMEeq) combined with automated thermal desorption-gas chromatography/mass spectrometry (TDGC/MS) was used to determine freely dissolved concentrations of ten DDX analytes in sediment cores collected from three locations on the PVS (stations 3C, 6C, 8C, which are 7 km, 2 km, and 0 km, respectively, downcurrent from the outfall system). Pore-water concentrations (pM) of the principal DDX compounds involved in RDC were: 3C-DDE: 6.0–24, DDMU (1-chloro-4-[2-chloro-1-(4-chlorophenyl)ethenyl]benzene): 11–160, DDNU (1-chloro-4-[1-(4-chlorophenyl)ethenyl]benzene): 1.8–68; 6C-DDE: 5.6–170, DDMU: 5.6–177, DDNU: 1.7–87; 8CDDE: 27–212, DDMU: 31–403, DDNU: 5.5–89. Variations in the spatial distribution of DDX analytes in pore water reflect several factors including proximity to the outfalls, RDC reaction rates, and natural variability in sedimentation and post-depositional transport processes. A comparison of pore-water data produced using matrix-SPMEeq/TD-GC/MS and whole-core squeezing/solvent extraction/liquid injection-GC/MS indicates that the majority of the DDE in the upper sediment column (≤about 10 cm) is associated with dissolved/colloidal organic matter. Below that depth, freely-dissolved DDE predominates. The principal organic geochemical phase controlling sorption of DDE in PVS sediments are residual hydrocarbons, the vast majority of which originated from petroleum refinery wastes. Organic carbon-normalized sediment-water distribution coefficients (KOC) were calculated from solid-phase and pore-water concentrations of DDX and organic carbon. Log KOC values (L/kg) were relatively invariant across the shelf and with depth in the sediment column. Shelf-wide compound-specific coefficients (log KOC) were: DDE: 7.5 ± 0.11, DDMU: 6.92 ± 0.13, DDNU: 6.37 ± 0.19. The spatial uniformity of KOC means that biological exposure and availability of the DDX compounds can, in principle, be estimated from solid-phase chemical measurements.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marchem.2018.05.003","usgsCitation":"Eganhouse, R.P., DiFilippo, E.L., Pontolillo, J., Orem, W.H., Hackley, P.C., and Edwards, B., 2018, DDT and related compounds in pore water of shallow sediments on the Palos Verdes Shelf, California, USA: Marine Chemistry, v. 203, p. 78-90, https://doi.org/10.1016/j.marchem.2018.05.003.","productDescription":"13 p.","startPage":"78","endPage":"90","ipdsId":"IP-088771","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468657,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marchem.2018.05.003","text":"Publisher Index Page"},{"id":355658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Palos Verdes Shelf","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.35111111111111,33.66777777777777 ], [ -118.35111111111111,33.7175 ], [ -118.28444444444445,33.7175 ], [ -118.28444444444445,33.66777777777777 ], [ -118.35111111111111,33.66777777777777 ] ] ] } } ] }","volume":"203","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc430e4b0f5d57878ea13","contributors":{"authors":[{"text":"Eganhouse, Robert P. 0000-0002-2075-5908 eganhous@usgs.gov","orcid":"https://orcid.org/0000-0002-2075-5908","contributorId":206243,"corporation":false,"usgs":true,"family":"Eganhouse","given":"Robert","email":"eganhous@usgs.gov","middleInitial":"P.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":739877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiFilippo, Erica L.","contributorId":90449,"corporation":false,"usgs":true,"family":"DiFilippo","given":"Erica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":739878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pontolillo, James 0000-0002-1075-1313 jpontoli@usgs.gov","orcid":"https://orcid.org/0000-0002-1075-1313","contributorId":206244,"corporation":false,"usgs":true,"family":"Pontolillo","given":"James","email":"jpontoli@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":739879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":739880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":739881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Edwards, Brian 0000-0002-4655-8208 bedwards@usgs.gov","orcid":"https://orcid.org/0000-0002-4655-8208","contributorId":206245,"corporation":false,"usgs":true,"family":"Edwards","given":"Brian","email":"bedwards@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739882,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197656,"text":"70197656 - 2018 - Quantifying anthropogenic contributions to century-scale groundwater salinity changes, San Joaquin Valley, California, USA","interactions":[],"lastModifiedDate":"2018-06-18T11:04:24","indexId":"70197656","displayToPublicDate":"2018-06-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying anthropogenic contributions to century-scale groundwater salinity changes, San Joaquin Valley, California, USA","docAbstract":"Total dissolved solids (TDS) concentrations in groundwater tapped for beneficial uses (drinking water, irrigation, freshwater industrial) have increased on average by about 100 mg/L over the last 100 years in the San Joaquin Valley, California (SJV). During this period land use in the SJV changed from natural vegetation and dryland agriculture to dominantly irrigated agriculture with growing urban areas. Century-scale salinity trends were evaluated by comparing TDS concentrations and major ion compositions of groundwater from wells sampled in 1910 (Historic) to data from wells sampled in 1993-2015 (Modern). TDS concentrations in subregions of the SJV, the southern (SSJV), western (WSJV), northeastern (NESJV), and southeastern (SESJV) were calculated using a cell-declustering method. TDS concentrations increased in all regions, with the greatest increases found in the SSJV and SESJV. Evaluation of the Modern data from the NESJV and SESJV found higher TDS concentrations in recently recharged (post-1950) groundwater from shallow (< 50 m) wells surrounded predominantly by agricultural land uses, while premodern (pre-1950) groundwater from deeper wells, and recently recharged groundwater from wells surrounded by mainly urban, natural, and mixed land uses had lower TDS concentrations, approaching the TDS concentrations in the Historic groundwater. For the NESJV and SESJV, inverse geochemical modeling with PHREEQC indicated that weathering of primary silicate minerals accounted for the majority of the increase in TDS concentrations, contributing more than nitrate from fertilizers and sulfate from soil amendments combined. Bicarbonate showed the greatest increase among major ions, resulting from enhanced silicate weathering due to recharge of irrigation water enriched in CO2 during the growing season. The results of this study demonstrate that large anthropogenic changes to the hydrologic regime, like massive development of irrigated agriculture in semi-arid areas like the SJV, can cause large changes in groundwater quality on a regional scale.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.05.333","usgsCitation":"Hansen, J.A., Jurgens, B., and Fram, M.S., 2018, Quantifying anthropogenic contributions to century-scale groundwater salinity changes, San Joaquin Valley, California, USA: Science of the Total Environment, v. 642, p. 125-136, https://doi.org/10.1016/j.scitotenv.2018.05.333.","productDescription":"12 p.","startPage":"125","endPage":"136","ipdsId":"IP-083514","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":460889,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.05.333","text":"Publisher Index Page"},{"id":437861,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7319T3K","text":"USGS data release","linkHelpText":"Groundwater-quality data and ancillary data for selected wells in the San Joaquin Valley, California, 1900-2015"},{"id":355083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley, San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.71728515624999,\n 40.195659093364654\n ],\n [\n -122.51953124999999,\n 39.791654835253425\n ],\n [\n -122.3876953125,\n 39.487084981687495\n ],\n [\n -122.2119140625,\n 39.198205348894795\n ],\n [\n -122.08007812499999,\n 38.92522904714054\n ],\n [\n -121.92626953124999,\n 38.496593518947584\n ],\n [\n 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0000-0002-2185-1686","orcid":"https://orcid.org/0000-0002-2185-1686","contributorId":205441,"corporation":false,"usgs":true,"family":"Hansen","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738093,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200470,"text":"70200470 - 2018 - Harnessing big data to rethink land heterogeneity in Earth system models","interactions":[],"lastModifiedDate":"2018-10-18T14:26:46","indexId":"70200470","displayToPublicDate":"2018-06-14T14:26:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Harnessing big data to rethink land heterogeneity in Earth system models","docAbstract":"The continual growth in the availability, detail, and wealth of environmental data provides an invaluable asset to improve the characterization of land heterogeneity in Earth system models – a persistent challenge in macroscale models. However, due to the nature of these data (volume and complexity) and computational constraints, these data are underused for global applications. As a proof of concept, this study explores how to effectively and efficiently harness these data in Earth system models over a 1/4° ( ∼ 25km) grid cell in the western foothills of the Sierra Nevada in central California. First, a novel hierarchical multivariate clustering approach (HMC) is introduced that summarizes the high-dimensional environmental data space into hydrologically interconnected representative clusters (i.e., tiles). These tiles and their associated properties are then used to parameterize the sub-grid heterogeneity of the Geophysical Fluid Dynamics Laboratory (GFDL) LM4-HB land model. To assess how this clustering approach impacts the simulated water, energy, and carbon cycles, model experiments are run using a series of different tile configurations assembled using HMC. The results over the test domain show that (1) the observed similarity over the landscape makes it possible to converge on the macroscale response of the fully distributed model with around 300 sub-grid land model tiles; (2) assembling the sub-grid tile configuration from available environmental data can have a large impact on the macroscale states and fluxes of the water, energy, and carbon cycles; for example, the defined subsurface connections between the tiles lead to a dampening of macroscale extremes; (3) connecting the fine-scale grid to the model tiles via HMC enables circumvention of the classic scale discrepancies between the macroscale and field-scale estimates; this has potentially significant implications for the evaluation and application of Earth system models.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-3311-2018","usgsCitation":"Chaney, N.W., Van Huijgevoort, M.H., Shevliakova, E., Malyshev, S., Milly, P.C., Gauthier, P., and Sulman, B.N., 2018, Harnessing big data to rethink land heterogeneity in Earth system models: Hydrology and Earth System Sciences, v. 22, p. 3311-3330, https://doi.org/10.5194/hess-22-3311-2018.","productDescription":"20 p.","startPage":"3311","endPage":"3330","ipdsId":"IP-090830","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-3311-2018","text":"Publisher Index Page"},{"id":358546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-14","publicationStatus":"PW","scienceBaseUri":"5c10a99ae4b034bf6a7e535d","contributors":{"authors":[{"text":"Chaney, Nathaniel W.","contributorId":169242,"corporation":false,"usgs":false,"family":"Chaney","given":"Nathaniel","email":"","middleInitial":"W.","affiliations":[{"id":25453,"text":"Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA","active":true,"usgs":false}],"preferred":false,"id":749025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Huijgevoort, Marjolein H. J.","contributorId":209888,"corporation":false,"usgs":false,"family":"Van Huijgevoort","given":"Marjolein","email":"","middleInitial":"H. J.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shevliakova, Elena","contributorId":201589,"corporation":false,"usgs":false,"family":"Shevliakova","given":"Elena","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":749027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malyshev, Sergey","contributorId":201588,"corporation":false,"usgs":false,"family":"Malyshev","given":"Sergey","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":749028,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":749024,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gauthier, Paul P. G.","contributorId":209889,"corporation":false,"usgs":false,"family":"Gauthier","given":"Paul P. G.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749029,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sulman, Benjamin N. 0000-0002-3265-6691","orcid":"https://orcid.org/0000-0002-3265-6691","contributorId":209890,"corporation":false,"usgs":false,"family":"Sulman","given":"Benjamin","email":"","middleInitial":"N.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749030,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216335,"text":"70216335 - 2018 - Thresholds and hotspots for shrub restoration following a heterogeneous megafire","interactions":[],"lastModifiedDate":"2020-11-12T15:00:59.555625","indexId":"70216335","displayToPublicDate":"2018-06-14T08:54:45","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds and hotspots for shrub restoration following a heterogeneous megafire","docAbstract":"Reestablishing foundational plant species through aerial seeding is an essential yet challenging step for restoring the vast semiarid landscapes impacted by plant invasions and wildfire-regime shifts. A key component of the challenge stems from landscape variability and its effects on plant recovery.
We assessed landscape correlates, thresholds, and tipping points for sagebrush presence from fine-scale sampling across a large, heterogeneous area burned the previous year, where we were able to quantify soil surface features that are typically occluded yet can strongly affect recovery patterns.
Hypothesis testing and binary-decision trees were used to evaluate factors affecting initial sagebrush establishment, using 2171 field plots (totaling ~ 2,000,000 m2 sampled) over a 113,000-ha region.
Sagebrush established in 50% of plots where it was seeded, a > 12-fold greater establishment frequency than in unseeded areas. Sagebrush establishment was enhanced in threshold-like ways by elevation (> 1200 m ASL), topographic features that alter heatload and soil water, and by soil-surface features such as “fertile islands” that bore the imprint of pre-fire sagebrush. Sagebrush occupancy had a negative, linear relationship with exotic-annual grass cover and parabolic relationship with perennial bunchgrasses (optimal at 40% cover).
Our approach revealed interactive, ecological relationships such as novel soil-surface effects on first year establishment of sagebrush across the burned landscape, and identified “hot spots” for recovery. The approach could be expanded across sites and years to provide the information needed to explain past seeding successes or failures, and in designing treatments at the landscape scale.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0662-8","usgsCitation":"Germino, M., Barnard, D., Davidson, B., Arkle, R., Pilliod, D., Fisk, M., and Applestein, C., 2018, Thresholds and hotspots for shrub restoration following a heterogeneous megafire: Landscape Ecology, v. 33, p. 1177-1194, https://doi.org/10.1007/s10980-018-0662-8.","productDescription":"18 p.","startPage":"1177","endPage":"1194","ipdsId":"IP-090670","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":380454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.04833984375001,\n 43.197167282501276\n ],\n [\n -116.1474609375,\n 43.197167282501276\n ],\n [\n -116.1474609375,\n 44.008620115415354\n ],\n [\n -117.04833984375001,\n 44.008620115415354\n ],\n [\n -117.04833984375001,\n 43.197167282501276\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","noUsgsAuthors":false,"publicationDate":"2018-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Germino, Matthew 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":218007,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, David 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":218008,"corporation":false,"usgs":true,"family":"Barnard","given":"David","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davidson, Bill 0000-0003-1315-479X","orcid":"https://orcid.org/0000-0003-1315-479X","contributorId":218011,"corporation":false,"usgs":true,"family":"Davidson","given":"Bill","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804735,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arkle, Robert 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":216339,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804737,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisk, Matthew 0000-0002-2250-0116","orcid":"https://orcid.org/0000-0002-2250-0116","contributorId":205749,"corporation":false,"usgs":true,"family":"Fisk","given":"Matthew","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804738,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":205748,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804739,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217156,"text":"70217156 - 2018 - Exposure to human-associated chemical markers of fecal contamination and self-reported illness among swimmers at recreational beaches","interactions":[],"lastModifiedDate":"2021-01-07T13:39:52.424305","indexId":"70217156","displayToPublicDate":"2018-06-14T07:34:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Exposure to human-associated chemical markers of fecal contamination and self-reported illness among swimmers at recreational beaches","docAbstract":"Anthropogenic chemicals have been proposed as potential markers of human fecal contamination in recreational water. However, to date, there are no published studies describing their relationships with illness risks. Using a cohort of swimmers at seven U.S. beaches, we examined potential associations between the presence of chemical markers of human fecal pollution and self-reported gastrointestinal (GI) illness, diarrhea, and respiratory illness. Swimmers were surveyed about their beach activities, water exposure, and baseline symptoms on the day of their beach visit, and about any illness experienced 10–12 days later. Risk differences were estimated using model-based standardization and adjusted for the swimmer’s age, beach site, sand contact, rainfall, and water temperature. Sixty-two chemical markers were analyzed from daily water samples at freshwater and marine beaches. Of those, 20 were found consistently. With the possible exception of bisphenol A and cholesterol, no chemicals were consistently associated with increased risks of illness. These two chemicals were suggestively associated with 2% and 1% increased risks of GI illness and diarrhea in both freshwater and marine beaches. Additional research using the more sensitive analytic methods currently available for a wider suite of analytes is needed to support the use of chemical biomarkers to quantify illness risk and identify fecal pollution sources.
Methane emissions from wetlands are temporally dynamic. Few chamber-based studies have explored diurnal variation in methane flux with high temporal replication. Using an automated sampling system, we measured methane flux every 2.5 to 4 h for 205 diel cycles during three growing seasons (2013–2015) from a seasonal wetland in the Prairie Pothole Region of North America. During ponded conditions, fluxes were generally positive (i.e., methanogenesis dominant, 10.1 ± 0.8 mg m−2 h−1), had extreme range of variation (from −1 to 70 mg m−2 h−1), and were highest during late day. In contrast, during dry conditions fluxes were very low and primarily negative (i.e., oxidation dominant, −0.05 ± 0.002 mg m−2 h−1), with the highest (least negative) fluxes occurring at pre-dawn. During semi-saturated conditions, methane fluxes also were very low, oscillated between positive and negative values (i.e., balanced between methanogenesis and methane oxidation), and exhibited no diel pattern. Methane flux was positively correlated with air temperature during ponded conditions (r = 0.57) and negatively during dry conditions (r = −0.42). Multiple regression analyses showed that temperature, light and water-filled pore space explained 72% of variation in methane flux. Methane fluxes are highly temporally dynamic and follow contrasting diel patterns that are dependent on dominant microbial processes influenced by saturation state.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-018-1042-5","usgsCitation":"Bansal, S., Tangen, B., and Finocchiaro, R., 2018, Diurnal patterns of methane flux from a seasonal wetland: mechanisms and methodology: Wetlands, v. 45, no. 10, p. 4933-4943, https://doi.org/10.1007/s13157-018-1042-5.","productDescription":"11 p.","startPage":"4933","endPage":"4943","ipdsId":"IP-091017","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":437862,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7348JB2","text":"USGS data release","linkHelpText":"Diurnal patterns of methane flux from a depressional, seasonal wetland"},{"id":355062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-22","publicationStatus":"PW","scienceBaseUri":"5b46e567e4b060350a15d119","contributors":{"authors":[{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finocchiaro, Raymond 0000-0002-5514-8729 rfinocchiaro@usgs.gov","orcid":"https://orcid.org/0000-0002-5514-8729","contributorId":167278,"corporation":false,"usgs":true,"family":"Finocchiaro","given":"Raymond","email":"rfinocchiaro@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738042,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197641,"text":"70197641 - 2018 - Dryland photoautotrophic soil surface communities endangered by global change","interactions":[],"lastModifiedDate":"2018-06-15T09:29:38","indexId":"70197641","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Dryland photoautotrophic soil surface communities endangered by global change","docAbstract":"Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth’s terrestrial surface will decrease by about 25–40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41561-018-0072-1","usgsCitation":"Rodriguez-Caballero, E., Belnap, J., Budel, B., Crutzen, P.J., Andreae, M.O., Poschl, U., and Weber, B., 2018, Dryland photoautotrophic soil surface communities endangered by global change: Nature Geoscience, v. 11, p. 185-189, https://doi.org/10.1038/s41561-018-0072-1.","productDescription":"5 p.","startPage":"185","endPage":"189","ipdsId":"IP-078018","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468661,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.obvsg.at/urn:nbn:at:at-ubg:3-14404","text":"External Repository"},{"id":355055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-26","publicationStatus":"PW","scienceBaseUri":"5b46e567e4b060350a15d11d","contributors":{"authors":[{"text":"Rodriguez-Caballero, Emilio 0000-0002-5934-3214","orcid":"https://orcid.org/0000-0002-5934-3214","contributorId":205639,"corporation":false,"usgs":false,"family":"Rodriguez-Caballero","given":"Emilio","email":"","affiliations":[{"id":37132,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":738017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budel, Burkhard","contributorId":172209,"corporation":false,"usgs":false,"family":"Budel","given":"Burkhard","email":"","affiliations":[{"id":26999,"text":"Plant Ecology and Systematics, Institute of Biology, University of Kaiserslautern, Kaiserlautern, Germany","active":true,"usgs":false}],"preferred":false,"id":738019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crutzen, Paul J.","contributorId":205640,"corporation":false,"usgs":false,"family":"Crutzen","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":37133,"text":"Air Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andreae, Meinrat O.","contributorId":205641,"corporation":false,"usgs":false,"family":"Andreae","given":"Meinrat","email":"","middleInitial":"O.","affiliations":[{"id":37134,"text":"Biogeochemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738021,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Poschl, Ulrich","contributorId":205642,"corporation":false,"usgs":false,"family":"Poschl","given":"Ulrich","email":"","affiliations":[{"id":37132,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":738022,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weber, Bettina","contributorId":196800,"corporation":false,"usgs":false,"family":"Weber","given":"Bettina","email":"","affiliations":[],"preferred":false,"id":738023,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70197524,"text":"ofr20181087 - 2018 - Bedrock geologic map of the Littleton and Lower Waterford quadrangles, Essex and Caledonia Counties, Vermont, and Grafton County, New Hampshire","interactions":[],"lastModifiedDate":"2019-02-12T13:58:05","indexId":"ofr20181087","displayToPublicDate":"2018-06-13T14:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1087","title":"Bedrock geologic map of the Littleton and Lower Waterford quadrangles, Essex and Caledonia Counties, Vermont, and Grafton County, New Hampshire","docAbstract":"The bedrock geologic map of the Littleton and Lower Waterford quadrangles covers an area of approximately 107 square miles (277 square kilometers) north and south of the Connecticut River in east-central Vermont and adjacent New Hampshire. This map was created as part of a larger effort to produce a new bedrock geologic map of Vermont through the collection of field data at a scale of 1:24,000. A large part of the map area consists of the Bronson Hill anticlinorium, a post-Early Devonian structure that is cored by metamorphosed Cambrian to Devonian sedimentary, volcanic, and plutonic rocks. The northwestern part of the map is divided by the Monroe fault which separates Early Devonian rocks of the Connecticut Valley-Gaspé trough from rocks of the Bronson Hill anticlinorium.
The Bronson Hill anticlinorium is the apex of the Middle Ordovician to earliest-Silurian Bronson Hill magmatic arc that contains the Ammonoosuc Volcanics, Partridge Formation, and Oliverian Plutonic suite, and extends from Maine, down the eastern side of the Connecticut River in New Hampshire, to Long Island Sound. The deformed and partially eroded arc is locally overlain by a relatively thin Silurian section of metasedimentary rocks (Clough Quartzite and Fitch Formation) that thickens to the east. The Silurian section near Littleton is disconformably overlain by a thicker, Lower Devonian section that includes mostly metasedimentary rocks and minor metavolcanic rocks of the Littleton Formation. The Bronson Hill anticlinorium is bisected by a series of northeast-southwest trending Mesozoic normal faults. Primarily among them is the steeply northwest-dipping Ammonoosuc fault that divides older and younger units (upper and lower sections) of the Ammonoosuc Volcanics. The Ammonoosuc Volcanics are lithologically complex and predominantly include interlayered and interfingered rhyolitic to basaltic volcanic and volcaniclastic rocks, as well as lesser amounts of metamorphic and metasedimentary rocks. The Ammonoosuc Volcanics overlies the Albee Formation that consists of interlayered feldspathic sandstone, siltstone, pelite, and slate.
During the Late Ordovician, a series of arc-related plutons intruded the Ammonoosuc Volcanics, including the Whitefield pluton to the east, the Scrag granite of Billing (1937) in the far southeastern corner of the map, the Highlandcroft Granodiorite just to the west of the Ammonoosuc fault, and the Joslin Turn tonalite (just north of the Connecticut River). To the east of the Monroe fault lies the late Silurian Comerford Intrusive Complex, which consists of metamorphosed gabbro, diorite, tonalite, aplitic tonalite, and crosscutting diabase dikes. Abundant mafic dikes of the Comerford Intrusive Complex intruded the Albee Formation and Ammonoosuc Volcanics well east of the Monroe fault.
This report consists of a single geologic map sheet and an online geographic information systems database that includes contacts of bedrock geologic units, faults, outcrops, and structural geologic information.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181087","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Rankin, D.W., 2018, Bedrock geologic map of the Littleton and Lower Waterford quadrangles, Essex and Caledonia Counties, Vermont, and Grafton County, New Hampshire: U.S. Geological Survey Open-File Report 2018–1087, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20181087.","productDescription":"Sheet: 36.00 x 45.82 inches; Geologic Map: ArcGIS 10.5 zip; Geodatabase; Metadata; Base Map","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081645","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":354879,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1087/metadata/ofr20181087_geologic-map-files.zip","text":"Geologic Map (ArcGIS 10.5)","size":"49.3 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Littleton and Lower Waterford, Vermont, and New Hampshire, Geologic Map"},{"id":354880,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1087/metadata/ofr20181087_basemap-files.zip","text":"Base Map","size":"10.8 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Littleton and Lower Waterford, Vermont, and New Hampshire, Base Map"},{"id":354979,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1087/metadata/ofr20181087_littleton-lowerwaterford-xml.zip","text":"Metadata ","size":"67.1 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Littleton and Lower Waterford, Vermont, and New Hampshire, Metadata"},{"id":354876,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1087/ofr20181087.pdf","text":"Geologic Map","size":"24.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1087"},{"id":354875,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1087/coverthb2.jpg"},{"id":354878,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1087/metadata/ofr20181087_database-files.gdb.zip","text":"Database","size":"1.30 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Littleton and Lower Waterford, Vermont, and New Hampshire, Geodatabase "}],"country":"United States","state":"New Hampshire, Vermont","county":"Caledonia County, Grafton County, Essex County","otherGeospatial":"Littleton Quadrangle, Lower Waterford Quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 44.25\n ],\n [\n -71.75,\n 44.25\n ],\n [\n -71.75,\n 44.375\n ],\n [\n -72,\n 44.375\n ],\n [\n -72,\n 44.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Landscape-scale analyses of biological invasion are needed to understand the relative importance of environmental drivers that vary at larger scales, such as climate, propagule pressure, resource availability, and human disturbance. One poorly understood landscape-scale question is, how does human land-use influence riparian plant invasion? To evaluate the relative importance of land-use, climate, propagule pressure, and water availability in riparian invasion, we examined tamarisk (Tamarix ramosissima, T. chinensis, hybrids), Russian olive (Elaeagnus angustifolia), and Siberian elm (Ulmus pumila) occurrence, abundance, and dominance in 238 riparian sites in developed, cultivated, and undeveloped areas of four western USA river basins (281,946 km2). Temperature and propagule pressure from individuals planted nearby largely drove invasive species occurrence, whereas factors likely to affect resource availability (e.g., land-use, precipitation, streamflow intermittency) were more important to abundance and dominance, supporting the argument that species distribution models based on occurrence alone may fail to identify conditions where invasive species have the greatest impact. The role of land-use varied among taxa: urban and suburban land-use increased Siberian elm occurrence, abundance, and dominance, and urban land-use increased Russian olive occurrence, whereas suburban land-use reduced tamarisk dominance. Surprisingly, Siberian elm, which has received scant prior scientific and management attention, occurred as or more frequently than tamarisk and Russian olive (except in undeveloped areas of the Colorado River headwaters) and had higher density and dominance than tamarisk and Russian olive in developed areas. More research is needed to understand the impacts of this largely unrecognized invader on riparian ecosystem services, particularly in urban and suburban areas.
Quagga mussels (Dreissena rostriformis bugensis) are highly fecund broadcast spawners invasive to freshwaters of North America and western Europe. We hypothesized that environmental cues from phytoplankton can trigger gamete release in quagga mussels. Nutritious algae may stimulate dreissenid spawning, but less palatable food, such as bloom-forming cyanobacteria, could be a hindrance. The objective of our study was to test whether exposure to cyanobacteria can inhibit quagga mussel spawning and fertilization. We assessed spawning in the presence of serotonin, a known spawning inducer, where adult quagga mussels placed in individual vials were exposed to 13 cyanobacteria cultures and purified algal toxin (microcystin-LR) with artificial lake water as the control. Fertilization success was evaluated by combining eggs with sperm in conjunction with cyanobacteria, and enumerating zygote formation marked by cellular cleavage. Several cyanobacterial strains reduced spawning and fertilization success, but microcystin-LR had no effect. Fertilization was more sensitive to cyanobacteria than gamete release. Only 1 culture, Aphanizomenon flos-aquae, inhibited spawning, whereas 6 cultures consisting of Anabaena flos-aquae, Dolichospermum lemmermanii, Gloeotrichia echinulata, Lyngbya wollei, and 2 Microcystis aeruginosa isolates reduced fertilization rates by up to 44%. The effects of cyanobacteria on reproduction in invasive freshwater mussels in the wild have not yet been identified. However, our laboratory studies show that concentrations of cyanobacteria that are possible during bloom conditions probably limit reproduction. Reproductive consequences on wild populations may become more prevalent as cyanobacteria blooms occur earlier in the year, making overlap between blooms and mussel spawning more common. Describing the mechanism by which cyanobacteria inhibit spawning and fertilization could reveal novel control methods to limit reproduction of this invasive species.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/698353","usgsCitation":"Boegehold, A.G., Johnson, N., Ran, J.L., and Kashian, D.R., 2018, Cyanobacteria reduce quagga mussel (Dreissena rostriformis bugensis) spawning and fertilization success: Freshwater Science, v. 37, no. 3, p. 510-518, https://doi.org/10.1086/698353.","productDescription":"9 p.","startPage":"510","endPage":"518","ipdsId":"IP-088358","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":437865,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WQU3P2","text":"USGS data release","linkHelpText":"Sperm motility of quagga mussels exposed to cyanobacteria in a laboratory bioassay, 2016"},{"id":437864,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MG7NFC","text":"USGS data release","linkHelpText":"Cyanobacteria reduce quagga mussel spawning and fertilization success in laboratory bioassays"},{"id":355016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e569e4b060350a15d12b","contributors":{"authors":[{"text":"Boegehold, Anna G.","contributorId":205600,"corporation":false,"usgs":false,"family":"Boegehold","given":"Anna","email":"","middleInitial":"G.","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":737926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":737925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ran, Jeffrey L.","contributorId":205601,"corporation":false,"usgs":false,"family":"Ran","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":737927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kashian, Donna R.","contributorId":205602,"corporation":false,"usgs":false,"family":"Kashian","given":"Donna","email":"","middleInitial":"R.","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":737928,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195591,"text":"sir20185029 - 2018 - Streamflow and selenium loads during synoptic sampling of the Gunnison River and its tributaries near Delta, Colorado, November 2015","interactions":[],"lastModifiedDate":"2018-06-14T10:02:19","indexId":"sir20185029","displayToPublicDate":"2018-06-13T00:00:00","publicationYear":"2018","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":"2018-5029","title":"Streamflow and selenium loads during synoptic sampling of the Gunnison River and its tributaries near Delta, Colorado, November 2015","docAbstract":"In response to the need for more information about selenium (Se) sources and transport, the U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, completed a study that characterized Se loads in a reach of the Gunnison River between Delta and Grand Junction, Colo. This report identifies where possible dissolved Se loading is occurring in a study reach in the Lower Gunnison River Basin between Delta and Grand Junction on November 19, 2015.
The combined Se loads from the Gunnison River at Delta (site 3) and the Uncompahgre River at Delta (site 4) were about 95 percent of the load at the furthest downstream main-stem sample location at the Gunnison River below Roubideau Creek near Delta (site 20) (31.6 and 33.4 pounds per day, respectively), indicating that about 5 percent of the total load (1.8 pounds) was potentially contributed from diffuse groundwater inflow. Main-stem streamflow accounting during November 2015 in a downstream direction was not supportive of substantial net gains or losses in the main-stem water balance.
The cumulative load from measured tributary inflows downstream from the Uncompahgre River confluence only amounted to 1.2 pounds of the main-stem loads (1.8 pounds gain) from site 4 to the end of the synoptic reach at site 20. The remaining 33 percent (about 0.6 pounds) of Se load increase was not accounted for by known tributary inflow. Yet, the small changes in the streamflow mass balance in the same reach does not strongly support a net inflow explanation for the apparent gain in load.
Based on the results of the loading and streamflow analysis, when errors in the loading estimates are considered, there is no conclusive evidence of an appreciable amount of Se load that is unaccounted for in the study reach of the Gunnison River as was originally hypothesized. Differences determined from comparisons of cumulative tributary loads and Gunnison River main-stem loads for this study are within error estimates of the main-stem loads.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185029","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board","usgsCitation":"Stevens, M.R., Leib, K.J., Thomas, J.C., Bauch, N.J., and Richards, R.J., 2018, Streamflow and selenium loads during synoptic sampling of the Gunnison River and its tributaries near Delta, Colorado, November 2015: U.S. GeologicalSurvey Scientific Investigations Report 2018–5029, 17 p., https://doi.org/10.3133/sir20185029.","productDescription":"v, 17 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-087865","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":354762,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5029/coverthb.jpg"},{"id":354763,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5029/sir20185029.pdf","text":"Report","size":"3.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5029"}],"country":"United States","state":"Colorado","otherGeospatial":"Gunnison River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109,\n 37.5\n ],\n [\n -106.25,\n 37.5\n ],\n [\n -106.25,\n 39.5\n ],\n [\n -109,\n 39.5\n ],\n [\n -109,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Within the U.S. portion of the Central Flyway, the U.S. Fish and Wildlife Service manages waterfowl on numerous individual units (i.e., Refuges) within the National Wildlife Refuge System. Presently, the extent of waterfowl use that Refuges receive and the contribution of Refuges to waterfowl populations (i.e., the proportion of the Central Flyway population registered at each Refuge) remain unassessed. Such an evaluation would help determine to what extent Refuges support waterfowl relative to stated targets, aid in identifying species requiring management attention, inform management targets, and improve fiscal efficiencies. Using historic monitoring data (1954–2008), we performed this assessment for 23 Refuges in Texas, New Mexico, Oklahoma, Kansas, and Nebraska during migration and wintering months (October–March). We examined six dabbling ducks and two diving ducks, plus all dabbling ducks and all diving ducks across two periods (long-term [all data] and short-term [last 10 October–March periods]). Individual Refuge use was represented by the sum of monthly duck count averages for October–March. We used two indices of Refuge contribution: peak contribution and January contribution. Peak contribution was the highest monthly count average for each October–March period divided by the indexed population total for the Central Flyway in the corresponding year; January contribution used the January count average divided by the corresponding population index. Generally, Refuges in Kansas, Nebraska, and New Mexico recorded most use and contribution for mallards Anas platyrhynchos. Refuges along the Texas Gulf Coast recorded most use and contribution for other dabbling ducks, with Laguna Atascosa and Aransas (including Matagorda Island) recording most use for diving ducks. The long-term total January contribution of the assessed Refuges to ducks wintering in the Central Flyway was greatest for green-winged teal Anas creccawith 35%; 12–15% for American wigeon Mareca americana, gadwall Mareca strepera, and northern pintail Anas acuta; and 7–8% for mallard and mottled duck Anas fulvigula. Results indicated that the reliance on the National Wildlife Refuge System decreased for these ducks, with evidence suggesting that, for several species, the assessed Refuges may be operating at carrying capacity. Future analyses could be more detailed and informative were Refuges to implement a single consistent survey methodology that incorporated estimations of detection bias in the survey process, while concomitantly recording habitat metrics on and neighboring each Refuge.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/042017-JFWM-033","usgsCitation":"Andersson, K., Davis, C.A., Harris, G., and Haukos, D.A., 2018, Nonbreeding duck use at Central Flyway National Wildlife Refuges: Journal of Fish and Wildlife Management, v. 9, no. 1, p. 45-64, https://doi.org/10.3996/042017-JFWM-033.","productDescription":"20 p.","startPage":"45","endPage":"64","ipdsId":"IP-079449","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468665,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/042017-jfwm-033","text":"Publisher Index Page"},{"id":355021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.67773437499999,\n 26.667095801104814\n ],\n [\n -92.98828125,\n 26.667095801104814\n ],\n [\n -92.98828125,\n 43.644025847699496\n ],\n [\n -104.67773437499999,\n 43.644025847699496\n ],\n [\n -104.67773437499999,\n 26.667095801104814\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-04","publicationStatus":"PW","scienceBaseUri":"5b46e568e4b060350a15d127","contributors":{"authors":[{"text":"Andersson, Kent","contributorId":205605,"corporation":false,"usgs":false,"family":"Andersson","given":"Kent","affiliations":[],"preferred":false,"id":737939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Craig A.","contributorId":171490,"corporation":false,"usgs":false,"family":"Davis","given":"Craig","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":737940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harris, Grant","contributorId":172342,"corporation":false,"usgs":false,"family":"Harris","given":"Grant","affiliations":[],"preferred":false,"id":737941,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":737936,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197560,"text":"70197560 - 2018 - Spatial patterns of development drive water use","interactions":[],"lastModifiedDate":"2018-06-12T09:43:27","indexId":"70197560","displayToPublicDate":"2018-06-12T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Spatial patterns of development drive water use","docAbstract":"Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non‐spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio‐economic and environmental variables and two water use variables: a) domestic water use, and b) total development‐related water use (a combination of public supply, domestic self‐supply and industrial self‐supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio‐economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water‐efficient land use planning.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017WR021730","usgsCitation":"Sanchez, G., Smith, J., Terando, A.J., Sun, G., and Meentemeyer, R., 2018, Spatial patterns of development drive water use: Water Resources Research, v. 54, no. 3, p. 1633-1649, https://doi.org/10.1002/2017WR021730.","productDescription":"14 p.","startPage":"1633","endPage":"1649","ipdsId":"IP-089850","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":354927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, South 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,{"id":70196111,"text":"fs20183021 - 2018 - Hydrographic surveys of rivers and lakes using a multibeam echosounder mapping system","interactions":[],"lastModifiedDate":"2018-09-25T06:27:51","indexId":"fs20183021","displayToPublicDate":"2018-06-12T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3021","title":"Hydrographic surveys of rivers and lakes using a multibeam echosounder mapping system","docAbstract":"A multibeam echosounder is a type of sound navigation and ranging device that uses sound waves to “see” through even murky waters. Unlike a single beam echosounder (also known as a depth sounder or fathometer) that releases a single sound pulse in a single, narrow beam and “listens” for the return echo, a multibeam system emits a multidirectional radial beam to obtain information within a fan-shaped swath. The timing and direction of the returning sound waves provide detailed information on the depth of water and the shape of the river channel, lake bottom, or any underwater features of interest. This information has been used by the U.S. Geological Survey to efficiently generate high-resolution maps of river and lake bottoms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183021","usgsCitation":"Huizinga, R.J., and Heimann, D.C., 2018, Hydrographic surveys of rivers and lakes using a multibeam echosounder mapping system: U.S. Geological Survey Fact Sheet 2018–3021, 6 p., https://doi.org/10.3133/fs20183021.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-094385","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":354917,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3021/fs20183021.pdf","text":"Report","size":"4.80 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3021"},{"id":354916,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3021/coverthb2.jpg"}],"country":"United 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\"}}]}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Geometry strongly controls the dynamic behavior of marine‐terminating (tidewater) glaciers, significantly influencing advance and retreat cycles independent of climate. Yet the recent, nearly ubiquitous retreat of tidewater glaciers suggests that changes in atmospheric and oceanic forcing may also drive dynamic change. To isolate the influence of geometry on tidewater glacier dynamics, we analyzed detailed observational time series from 2012 to 2016 for two tidewater glaciers with shared dynamic histories and environmental forcing: Columbia Glacier and its former tributary (Post Glacier) in southcentral Alaska. We find that although terminus retreat has driven decadal‐scale changes in dynamics of the Columbia‐Post system, environmental factors contribute to short‐term (i.e., seasonal) dynamic variability. In particular, analysis of force balance time series indicates that observed variations in speed result from seasonal changes to the subglacial hydrologic system and associated changes in basal drag. Variations in terminus position only drive noticeable speed change when the terminus retreats from regions of relatively high basal drag. In agreement with long‐term analyses of Columbia Glacier, we find that terminus geometry can perturb the timing of seasonal ice flow patterns. Specifically, our data support the idea that retreat of a glacier terminus into deeper water is accompanied by a shift in the primary control on frontal ablation. Although our analysis focuses on two Alaskan glaciers, our data suggest that changes in the relative importance of surface meltwater and buoyancy effects on submarine melting and/or calving may manifest as a shift in terminus change seasonality and offer a mechanism to identify frontal ablation controls.
In many coastal areas, high water tables are present, complicating installation of some stormwater best management practices (BMPs) that rely on infiltration. Regional estimates of the seasonal high water table (SHWT) often rely on sources such as soil surveys taken over a decade ago; these data are static and do not account for groundwater withdrawals or other anthropogenic impacts. To improve estimates of the SHWT, we developed a GIS-based methodology relying on surface water elevations. Data sources included a 1.5-m (5.0 ft) resolution Lidar-derived digital elevation model (DEM), aerial imagery, and publicly available shapefiles of water boundaries. Twenty-six groundwater monitoring wells were screened to eliminate well locations influenced by pumping, yielding 22 wells. In coastal Virginia, tidal water bodies and ditches form terminal boundaries for discharge from the water-table aquifers and permit water table elevations to be fixed at the landward boundaries of surface water bodies. Water table elevations interpolated from well data and boundary elevations were used to create a triangulated irregular network representing the water table elevations for November 2012, which was the date of the DEM. An adjustment factor, calculated from the highest recorded April water table depth from long-term groundwater monitoring data, was added to estimate the SHWT elevation. SHWT elevations were subtracted from the DEM to yield SHWT depth, which was compared with long-term monitoring well data, yielding an R2 value of 0.91. Residual errors were random, although the method underpredicted the highest expected SHWT and overpredicted the median SHWT. The SHWT depth map was validated by using water table depths from 57 soil borings at 10 different sites, and consistently matched observations better than available soil survey estimates. The SHWT depth map could be useful for BMP siting and feasibility studies in similar hydrogeological settings.
","language":"English","publisher":"ASCE","doi":"10.1061/(ASCE)IR.1943-4774.0001313","usgsCitation":"Johnson, R., Sample, D., and McCoy, K.J., 2018, GIS-based method for estimating surficial groundwater levels in coastal Virginia using limited information: Journal of Irrigation and Drainage Engineering, v. 144, no. 7, p. 1-14, https://doi.org/10.1061/(ASCE)IR.1943-4774.0001313.","productDescription":"Article 05018004; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-075767","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true},{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":468670,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1061/(asce)ir.1943-4774.0001313","text":"External Repository"},{"id":355518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","volume":"144","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e56de4b060350a15d13f","contributors":{"authors":[{"text":"Johnson, R.D.","contributorId":62360,"corporation":false,"usgs":true,"family":"Johnson","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":739631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sample, David J.","contributorId":204837,"corporation":false,"usgs":false,"family":"Sample","given":"David J.","affiliations":[{"id":36990,"text":"Virginia Tech Biological Systems Engineering Department","active":true,"usgs":false}],"preferred":false,"id":739630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Kurt J. 0000-0002-9756-8238 kjmccoy@usgs.gov","orcid":"https://orcid.org/0000-0002-9756-8238","contributorId":1391,"corporation":false,"usgs":true,"family":"McCoy","given":"Kurt","email":"kjmccoy@usgs.gov","middleInitial":"J.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":739632,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197732,"text":"70197732 - 2018 - A history of trade routes and water-level regulation on waterways in Voyageurs National Park, Minnesota, USA","interactions":[],"lastModifiedDate":"2018-06-19T17:00:09","indexId":"70197732","displayToPublicDate":"2018-06-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A history of trade routes and water-level regulation on waterways in Voyageurs National Park, Minnesota, USA","docAbstract":"Unlike most national parks, main access to Voyageurs National Park is by boat. This remote system of interconnected waterways along the USA-Canada border was an important transportation route for thousands of years of American Indian occupation, leading up to and including the trade route of the voyageurs, or French-Canadian fur traders from around 1680 to 1870. The Ojibwe people collaborated with the voyageurs and the two cultures developed a trade network that continued to rely on these waterways. By the mid-1800s, European fashion changed, and the fur trade dwindled while the Ojibwe remained tied to the land and waters. The complexity of the waterways increased with the installation of dams on two of the natural lakes in the early 1900s. Modern water levels have affected—and in some cases destabilized—vulnerable landforms within the past century. The knowledge of these effects can be used by resource managers to weigh the consequences of hydrologic manipulation in Voyageurs National Park.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World Environmental and Water Resources Congress 2018","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Environmental and Water Resources Congress 2018","conferenceDate":"June 3-7, 2018","conferenceLocation":"Minneapolis, MN","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/9780784481394.014","usgsCitation":"Christensen, V.G., and LaBounty, A.E., 2018, A history of trade routes and water-level regulation on waterways in Voyageurs National Park, Minnesota, USA, in World Environmental and Water Resources Congress 2018, Minneapolis, MN, June 3-7, 2018, 12 p., https://doi.org/10.1061/9780784481394.014.","productDescription":"12 p.","ipdsId":"IP-092923","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":355182,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Voyageurs National Park","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-31","publicationStatus":"PW","scienceBaseUri":"5b46e56de4b060350a15d143","contributors":{"authors":[{"text":"Christensen, Victoria G. 0000-0003-4166-7461 vglenn@usgs.gov","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":2354,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","email":"vglenn@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaBounty, Andrew E.","contributorId":205738,"corporation":false,"usgs":false,"family":"LaBounty","given":"Andrew","email":"","middleInitial":"E.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":738320,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197552,"text":"70197552 - 2018 - Real-time water quality monitoring at a Great Lakes National Park","interactions":[],"lastModifiedDate":"2018-06-12T10:23:52","indexId":"70197552","displayToPublicDate":"2018-06-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Real-time water quality monitoring at a Great Lakes National Park","docAbstract":"Quantitative polymerase chain reaction (qPCR) was used by the USEPA to establish new recreational water quality criteria in 2012 using the indicator bacteria enterococci. The application of this method has been limited, but resource managers are interested in more timely monitoring results. In this study, we evaluated the efficacy of qPCR as a rapid, alternative method to the time-consuming membrane filtration (MF) method for monitoring water at select beaches and rivers of Sleeping Bear Dunes National Lakeshore in Empire, MI. Water samples were collected from four locations (Esch Road Beach, Otter Creek, Platte Point Bay, and Platte River outlet) in 2014 and analyzed for culture-based (MF) and non-culture-based (i.e., qPCR) endpoints using Escherichia coli and enterococci bacteria. The MF and qPCR enterococci results were significantly, positively correlated overall (r = 0.686, p < 0.0001, n = 98) and at individual locations as well, except at the Platte River outlet location: Esch Road Beach (r = 0.441, p = 0.031, n = 24), Otter Creek (r = 0.592, p = 0.002, n = 24), and Platte Point Bay (r = 0.571, p = 0.004, n = 24). Similarly, E. coli MF and qPCR results were significantly, positively correlated (r = 0.469, p < 0.0001, n = 95), overall but not at individual locations. Water quality standard exceedances based on enterococci levels by qPCR were lower than by MF method: 3 and 16, respectively. Based on our findings, we conclude that qPCR may be a viable alternative to the culture-based method for monitoring water quality on public lands. Rapid, same-day results are achievable by the qPCR method, which greatly improves protection of the public from water-related illnesses.","language":"English","publisher":"ASA, CSSA, and SSSA","doi":"10.2134/jeq2017.11.0462","usgsCitation":"Byappanahalli, M., Nevers, M., Shively, D., Spoljaric, A., and Otto, C., 2018, Real-time water quality monitoring at a Great Lakes National Park: Journal of Environmental Quality, 8 p., https://doi.org/10.2134/jeq2017.11.0462.","productDescription":"8 p.","ipdsId":"IP-091163","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":437867,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77P8XND","text":"USGS data release","linkHelpText":"Quantitative polymerase chain reaction (qPCR): An alternative, rapid water quality monitoring tool at a National Park on Lake Michigan."},{"id":354921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Special Section: Microbial Water Quality—Monitoring and Modeling","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e56de4b060350a15d145","contributors":{"authors":[{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":737638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":737639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shively, Dawn 0000-0002-6119-924X dshively@usgs.gov","orcid":"https://orcid.org/0000-0002-6119-924X","contributorId":201533,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":737640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spoljaric, Ashley 0000-0001-6262-030X aspoljaric@usgs.gov","orcid":"https://orcid.org/0000-0001-6262-030X","contributorId":139464,"corporation":false,"usgs":true,"family":"Spoljaric","given":"Ashley","email":"aspoljaric@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":737656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Otto, Christopher","contributorId":205045,"corporation":false,"usgs":false,"family":"Otto","given":"Christopher","email":"","affiliations":[{"id":37025,"text":"Sleeping Bear Dunes National Lakeshore","active":true,"usgs":false}],"preferred":false,"id":737641,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197734,"text":"70197734 - 2018 - Voyageurs National Park: Water-level regulation and effects on water quality and aquatic biology","interactions":[],"lastModifiedDate":"2018-06-19T17:03:05","indexId":"70197734","displayToPublicDate":"2018-06-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Voyageurs National Park: Water-level regulation and effects on water quality and aquatic biology","docAbstract":"Following dam installations in the remote Rainy Lake Basin during the early 1900s, water-level fluctuations were considered extreme (1914–1949) compared to more natural conditions. In 1949, the International Joint Commission (IJC), which sets rules governing dam operation on waters shared by the United States and Canada, established the first rule curves to regulate water levels on these waterbodies. However, rule curves established prior to 2000 were determined to be detrimental to the ecosystem. Therefore, the IJC implemented an order in 2000 to change rule curves and to restore a more natural water regime. After 2000, measured chlorophyll-a concentrations in the two most eutrophic water bodies decreased whereas concentrations in oligotrophic lakes did not show significant water-quality differences. Fish mercury data were inconclusive, due to the variation in water levels and fish mercury concentrations, but can be used by the IJC as part of a long term data set.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World Environmental and Water Resources Congress 2018","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Environmental and Water Resources Congress 2018","conferenceDate":"June 3-7, 2018","conferenceLocation":"Minneapolis, MN","language":"English","publisher":"ASCE","doi":"10.1061/9780784481394.017","usgsCitation":"Christensen, V.G., Maki, R., and LeDuc, J.F., 2018, Voyageurs National Park: Water-level regulation and effects on water quality and aquatic biology, in World Environmental and Water Resources Congress 2018, Minneapolis, MN, June 3-7, 2018, https://doi.org/10.1061/9780784481394.017.","ipdsId":"IP-093049","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":355183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Voyageurs","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-31","publicationStatus":"PW","scienceBaseUri":"5b46e56de4b060350a15d141","contributors":{"authors":[{"text":"Christensen, Victoria G. 0000-0003-4166-7461 vglenn@usgs.gov","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":2354,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","email":"vglenn@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maki, Ryan P.","contributorId":100111,"corporation":false,"usgs":true,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":738324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LeDuc, Jaime F.","contributorId":190132,"corporation":false,"usgs":false,"family":"LeDuc","given":"Jaime","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":738325,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221334,"text":"70221334 - 2018 - Ground-nesting great horned owl in Suisun Marsh, California","interactions":[],"lastModifiedDate":"2021-06-10T12:28:18.88242","indexId":"70221334","displayToPublicDate":"2018-06-10T07:24:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1153,"text":"California Fish and Game","active":true,"publicationSubtype":{"id":10}},"title":"Ground-nesting great horned owl in Suisun Marsh, California","docAbstract":"Great horned owls (Bubo virginianus) are widespread throughout North, Central, and parts of South America (Artuso et al. 2013). Across this range, great horned owls are generalists, occupying a diverse range of habitats including deciduous and coniferous forests, wetlands, and agricultural landscapes. Within these habitats, great horned owls are generally found near upland or short-vegetation habitat suitable for locating prey (Artuso et al. 2013). In Suisun Marsh, California, great horned owls primarily occupy stands of non-native eucalyptus (Eucalyptus spp.), as well as man-made structures like waterfowl-nesting platforms (Figure 1) and on dock pilings over water (Figure 2), and they forage in nearby upland fields and seasonally flooded, diked wetlands managed primarily for waterfowl (USGS unpublished data).","language":"English","publisher":"California Department of Fish and Wildlife","usgsCitation":"Skalos, S., Falcon, M.J., Wang, O., Mott, A.L., Hunt, M., Rocha, O., Ackerman, J.T., Casazza, M.L., and Hull, J.M., 2018, Ground-nesting great horned owl in Suisun Marsh, California: California Fish and Game, v. 104, no. 4, p. 164-172.","productDescription":"9 p.","startPage":"164","endPage":"172","ipdsId":"IP-101149","costCenters":[{"id":651,"text":"Western Ecological Research 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sskalos@usgs.gov","orcid":"https://orcid.org/0000-0003-1229-8580","contributorId":167191,"corporation":false,"usgs":true,"family":"Skalos","given":"Shannon","email":"sskalos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falcon, Matthew J.","contributorId":260146,"corporation":false,"usgs":false,"family":"Falcon","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":39913,"text":"former WERC","active":true,"usgs":false}],"preferred":false,"id":817353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Olivia","contributorId":260147,"corporation":false,"usgs":false,"family":"Wang","given":"Olivia","email":"","affiliations":[{"id":52524,"text":"University of California, Davis, Department of Animal Science, 1 Shields Avenue, Davis, CA 95616, USA (SS, OW, 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Wildlife, Grizzly Island Wildlife Area, 2548 Grizzly Island Road, Suisun City, CA 94585, USA (OR)","active":true,"usgs":false}],"preferred":false,"id":817357,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817358,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research 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The drill site of the prospective case study is the “Range Resources MCC Partners L.P. Units 1-5H” location (also referred to as the “RR–MCC” drill site), located in Washington County, southwestern Pennsylvania. Specifically, the USGS was approached to provide a geologic framework that would (1) provide geologic parameters for the proposed area of a localized groundwater circulation model, and (2) provide potential information for the siting of both shallow and deep groundwater monitoring wells located near the drill pad and the deviated drill legs.
The lead organization of the prospective case study of the RR–MCC drill site was the Groundwater and Ecosystems Restoration Division (GWERD) of the U.S. Environmental Protection Agency. Aside from the USGS, additional partners/participants were to include the Department of Energy, the Pennsylvania Geological Survey, the Pennsylvania Department of Environmental Protection, and the developer Range Resources LLC. During the initial cooperative phase, GWERD, with input from the participating agencies, drafted a Quality Assurance Project Plan (QAPP) that proposed much of the objectives, tasks, sampling and analytical procedures, and documentation of results.
Later in 2012, the proposed cooperative agreement between the aforementioned partners and the associated land owners for a monitoring program at the drill site was not executed. Therefore, the prospective case study of the RR–MCC site was terminated and no installation of groundwater monitoring wells nor the collection of nearby soil, stream sediment, and surface-water samples were made.
Prior to the completion of the QAPP and termination of the perspective case study the geologic framework was rapidly conducted and nearly completed. This was done for three principal reasons. First, there was an immediate need to know the distribution of the relatively undisturbed surface to near-surface bedrock geology and unconsolidated materials for the collection of baseline surface data prior to drill site development (drill pad access road, drill pad leveling) and later during monitoring associated with well drilling, well development, and well production. Second, it was necessary to know the bedrock geology to support the siting of: (1) multiple shallow groundwater monitoring wells (possibly as many as four) surrounding and located immediately adjacent to the drill pad, and (2) deep groundwater monitoring wells (possibly two) located at distance from the drill pad with one possibly being sited along one of the deviated production drill legs. Lastly, the framework geology would provide the lateral extent, thickness, lithology, and expected discontinuities of geologic units (to be parsed or grouped as hydrostratigraphic units) and regional structure trends as inputs into the groundwater model.
This report provides the methodology of geologic data accumulation and aggregation, and its integration into a geographic information system (GIS) based program. The GIS program will allow multiple data to be exported in various formats (shapefiles [.shp], database files [.dbf], and Keyhole Markup Language files [.KML]) for use in surface and subsurface geologic site characterization, for sampling strategies, and for inputs for groundwater modeling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181057","usgsCitation":"Stamm, R.G., 2018, Preliminary geologic framework developed for a proposed environmental monitoring study of a deep, unconventional Marcellus Shale drill site, Washington County, Pennsylvania: U.S. Geological Survey Open-File Report 2018–1057, 49 p., https://doi.org/10.3133/ofr20181057.","productDescription":"vi, 49 p.","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069591","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":354769,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1057/ofr20181057.pdf","text":"Report","size":"129 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1057"},{"id":354768,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1057/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Washington County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.4833,\n 40.3\n ],\n [\n -80.3833,\n 40.3\n ],\n [\n -80.3833,\n 40.3833\n ],\n [\n -80.4833,\n 40.3833\n ],\n [\n -80.4833,\n 40.3\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
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926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192