Numerous hydropower facilities are under construction or planned in tropical and subtropical rivers worldwide. While dams are typically designed considering historic river discharge regimes, climate change may induce large-scale alterations in river hydrology. Here we analyze how future climate change will affect river hydrology, electricity generation, and economic viability of > 350 potential hydropower dams across the Amazon, Earth’s largest river basin and a global hotspot for future hydropower development. Midcentury projections for the RCP 4.5 and 8.5 climate change scenarios show basin-wide reductions of river discharge (means, 13 and 16%, respectively) and hydropower generation (19 and 27%). Declines are sharper for dams in Brazil, which harbors 60% of the proposed projects. Climate change will cause more frequent low-discharge interruption of hydropower generation and less frequent full-capacity operation. Consequently, the minimum electricity sale price for projects to break even more than doubles at many proposed dams, rendering much of future Amazon hydropower less competitive than increasingly lower cost renewable sources such as wind and solar. Climate-smart power systems will be fundamental to support environmentally and financially sustainable energy development in hydropower-dependent regions.
","language":"English","publisher":"Elseiver","doi":"10.1016/j.gloenvcha.2021.102383","usgsCitation":"Almeida, R., Fleischmann, A., Breda, J., Cardoso, D., Angarita, H., Collischonn, W., Forsberg, B.R., García-Villacorta, R., Hamilton, S., Hannam, P., Paiva, R., Poff, N.L., Sethi, S., Shi, Q., Gomes, C.P., and Flecker, A., 2021, Climate change may impair electricity generation and economic viability of future Amazon hydropower: Global Environmental Change, v. 71, 102383, 10 p., https://doi.org/10.1016/j.gloenvcha.2021.102383.","productDescription":"102383, 10 p.","ipdsId":"IP-125313","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467222,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.wur.nl/en/publications/climate-change-may-impair-electricity-generation-and-economic-via","text":"External 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The multidisciplinary characterization of the test hole was a cooperative effort between the Pennsylvania Department of Natural Resources, Bureau of Geological Survey (BGS), and the U.S. Geological Survey (USGS). The study provided information to aid the bedrock mapping of the Laporte 7.5-minute quad-rangle by BGS to help quantify the depth and character of fresh and saline groundwater in an area of shale-gas exploration (described in this report), which could help gas operators protect groundwater resources.
The Laporte test hole was drilled with air-hammer methods in an upland setting in the headwaters of Loyalsock Creek in the Glaciated High Plateau section of the Appalachian Plateaus physiographic province. Bedrock residuum and till were penetrated from land surface to 8.5 ft, the Huntley Mountain Formation of Mississippian and Devonian age was penetrated from 8.5 to 540 ft, and the Catskill Formation of Devonian age was penetrated from 540 to 1,400 ft. Fractures, determined from optical televiewer, acoustic televiewer, and video logs, were commonly encountered to 200 ft bls (below land surface), then decreased exponentially with depth, except at a highly fractured zone from 637 to 644 ft bls. Most fractures were along bedding planes and had a strike of about 243 degrees and dip about 4 degrees to the northwest, consistent with the test-hole location on the north limb of the Muncy Creek anticline. Few fractures were noted below 650 ft.
The depths of fresh and saline water-bearing fracture zones were identified in the test hole by geophysical-log analysis and were verified by pumping samples from zones isolated with packers and by collecting samples in the open hole with a wire-line point sampler. Six water-bearing zones associated with single or multiple fractures were identified at depths of 130–135, 180, 267–275, 425, 637–644, and 1,003 ft bls. Under ambient conditions, fresh water entered the hole from fractures at 130-135 and 180 ft bls, flowed downward and exited at fractures from 267–275, 425, and 637–644 ft. When pumped at 16.2 gal/min, most of the water from the open test hole was contributed from the fracture at 180 ft bls. Transmissivity, estimated from analysis of the specific-capacity data and flowmeter logs, is about 850 ft2/d for the entire open hole, and about 60 percent of the transmissivity is contributed from the fracture zone at 180 ft bls. The hydraulic heads in the deep water-bearing zones at 425 and 637–644 ft were about 100 ft lower than hydraulic heads in shallow water-bearing zones at 180 ft bls and above, indicating a large downward vertical hydraulic gradient.
Water samples pumped from fracture zones isolated by packers at and above the water-bearing zone at 450 ft bls were fresh with dissolved-solids contents of 105 mg/L or less. The sample isolated at 637–644 ft bls was probably affected by leakage around packers, but the specific-conductance samples collected during drilling that were believed to be representa-tive of the fracture zone at 637–644 ft bls indicated slightly saline water. Below the 637–644 ft zone, a flowmeter log in the open hole did not detect any vertical flow, and the temperature log approached the geothermal gradient, indicating little ambient fluid flow and minimal fracture transmissivity below this depth. A petrophysical-log analysis using estimates of formation water resistivity from Archie’s Equation indicated an apparent transition from fresh to saline water in the sandstones occurs between 450 to 900 ft bls, with saline water indicated below 900 ft.
Small seeps of saline water were delineated at 958, 989, and 1,003 ft bls by a time series of specific-conductance logs, and a discrete-point water sample at 990 ft bls with total dissolved-solids concentration of 19,900 mg/L verified that highly saline water was present below 900 ft bls. Occurrence of saline water at a depth of about 900 ft bls is below altitude of streams within 3 to 5 miles of the test hole but is about 930 ft above the altitude at the mouth of Loyalsock Creek where is enters the West Branch Susquehanna River at Montours-ville, Pa. The depth to saline water in this test hole is close to depths estimated at two other deep test holes drilled by the BGS in upland settings in Bradford and Tioga Counties in north-ern Pennsylvania.
The saline water from 990 ft bls had a chemical composition similar to Appalachian Basin brines that had been diluted with fresh water. Predominant ions in the saline water were sodium, chloride, and calcium. Trace constituents of strontium, bromide, barium, lithium, and molybdenum were all more than 5,000 times greater than in freshwater samples from 167 or 270 ft bls. Methane concentration in the saline water sample from 990 ft was 120 mg/L. The concentration ratios of methane to higher-chain hydrocarbon gases and isotopic ratios of 13C/12C and 2H/1H of methane indicate that the gases are likely of thermogenic origin. In the sample from 990 ft bls, the 13C/12C of methane was less negative (-34.81 per mil) than 13C/12C of ethane (-37.1 per mil). Isotopic reversals such as this are generally found in gases from rocks older than the Catskill Formation, so its recognition in a natural upland setting at relatively shallow depth could be important when interpreting isotopic results to identify the origin of stray gas in the area.
","language":"English","publisher":"Pennsylvania Geological Survey","usgsCitation":"Risser, D.W., Williams, J., and Bierly, A.D., 2021, Geohydrologic and water-quality characterization of a fractured-bedrock test hole in an area of Marcellus Shale gas development, Sullivan County, Pennsylvania: Open-File Report OFMI 21-02.0, xii, 56 p.","productDescription":"xii, 56 p.","ipdsId":"IP-107313","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":393593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":393564,"type":{"id":15,"text":"Index Page"},"url":"https://maps.dcnr.pa.gov/publications/Default.aspx?id=995"}],"country":"United States","state":"Pennsylvania","county":"Sullivan County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.61453247070312,\n 41.28967402411714\n ],\n [\n -76.37832641601562,\n 41.28967402411714\n ],\n [\n -76.37832641601562,\n 41.46742831254425\n ],\n [\n -76.61453247070312,\n 41.46742831254425\n ],\n [\n -76.61453247070312,\n 41.28967402411714\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Risser, Dennis W. 0000-0001-9597-5406 dwrisser@usgs.gov","orcid":"https://orcid.org/0000-0001-9597-5406","contributorId":898,"corporation":false,"usgs":true,"family":"Risser","given":"Dennis","email":"dwrisser@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, John 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bierly, Aaron D.","contributorId":270527,"corporation":false,"usgs":false,"family":"Bierly","given":"Aaron","email":"","middleInitial":"D.","affiliations":[{"id":16182,"text":"Pennsylvania Geological Survey","active":true,"usgs":false}],"preferred":false,"id":829530,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229713,"text":"70229713 - 2021 - Complex evolutionary history of felid anelloviruses","interactions":[],"lastModifiedDate":"2022-03-16T16:53:33.668959","indexId":"70229713","displayToPublicDate":"2021-10-29T11:30:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3696,"text":"Virology","active":true,"publicationSubtype":{"id":10}},"title":"Complex evolutionary history of felid anelloviruses","docAbstract":"Anellovirus infections are highly prevalent in mammals, however, prior to this study only a handful of anellovirus genomes had been identified in members of the Felidae family. Here we characterise anelloviruses in pumas (Puma concolor), bobcats (Lynx rufus), Canada lynx (Lynx canadensis), caracals (Caracal caracal) and domestic cats (Felis catus). The complete anellovirus genomes (n = 220) recovered from 149 individuals were diverse. ORF1 protein sequence similarity network analysis coupled with phylogenetic analysis, revealed two distinct clusters that are populated by felid-derived anellovirus sequences, a pattern mirroring that observed for the porcine anelloviruses. Of the two-felid dominant anellovirus groups, one includes sequences from bobcats, pumas, domestic cats and an ocelot, and the other includes sequences from caracals, Canada lynx, domestic cats and pumas. Coinfections of diverse anelloviruses appear to be common among the felids. Evidence of recombination, both within and between felid-specific anellovirus groups, supports a long coevolution history between host and virus.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.virol.2021.07.013","usgsCitation":"Kraberger, S., Serieys, L.E., Richet, C., Fountain-Jones, N.M., Baele, G., Bishop, J.M., Nehring, M., Ivan, J., Newkirk, E.S., Squires, J.R., Lund, M.C., Riley, S.P., Wilmers, C.C., van Helden, P.D., Van Doorslaer, K., Culver, M., VandeWoude, S., Martin, D.P., and Varsani, A., 2021, Complex evolutionary history of felid anelloviruses: Virology, v. 562, p. 176-189, https://doi.org/10.1016/j.virol.2021.07.013.","productDescription":"14 p.","startPage":"176","endPage":"189","ipdsId":"IP-131734","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":450321,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://figshare.com/articles/journal_contribution/Complex_evolutionary_history_of_felid_anelloviruses/23010917","text":"Publisher Index Page"},{"id":397184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"562","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kraberger, Simona","contributorId":288545,"corporation":false,"usgs":false,"family":"Kraberger","given":"Simona","affiliations":[{"id":12431,"text":"ASU","active":true,"usgs":false}],"preferred":false,"id":838069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Serieys, Laurel EK","contributorId":288546,"corporation":false,"usgs":false,"family":"Serieys","given":"Laurel","email":"","middleInitial":"EK","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":false,"id":838070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richet, Cecile","contributorId":288547,"corporation":false,"usgs":false,"family":"Richet","given":"Cecile","email":"","affiliations":[{"id":12431,"text":"ASU","active":true,"usgs":false}],"preferred":false,"id":838071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fountain-Jones, Nicholas M","contributorId":288548,"corporation":false,"usgs":false,"family":"Fountain-Jones","given":"Nicholas","email":"","middleInitial":"M","affiliations":[{"id":61795,"text":"ut","active":true,"usgs":false}],"preferred":false,"id":838072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baele, Guy","contributorId":288550,"corporation":false,"usgs":false,"family":"Baele","given":"Guy","email":"","affiliations":[{"id":61796,"text":"ri","active":true,"usgs":false}],"preferred":false,"id":838073,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bishop, Jacqueline M.","contributorId":288667,"corporation":false,"usgs":false,"family":"Bishop","given":"Jacqueline","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":838186,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nehring, Mary","contributorId":288668,"corporation":false,"usgs":false,"family":"Nehring","given":"Mary","email":"","affiliations":[],"preferred":false,"id":838187,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ivan, Jacob S.","contributorId":200243,"corporation":false,"usgs":false,"family":"Ivan","given":"Jacob S.","affiliations":[],"preferred":false,"id":838188,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Newkirk, Eric S.","contributorId":244981,"corporation":false,"usgs":false,"family":"Newkirk","given":"Eric","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":838189,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Squires, John R.","contributorId":195901,"corporation":false,"usgs":false,"family":"Squires","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":838190,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lund, Michael C.","contributorId":288669,"corporation":false,"usgs":false,"family":"Lund","given":"Michael","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":838191,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Riley, Seth P. 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The 10 study areas were located between Colorado Springs and the terminus of Fountain Creek at the Arkansas River in Pueblo. The purpose of this report is to present elevation maps based on topographic surveys collected in 2020 and to present maps of elevation change that occurred between 2015 and 2020 at all 10 study areas. Elevation and elevation-change maps were developed in Global Mapper, R, and ArcGIS from topographic surveys collected at each study area during the winters of 2015 and 2020. Topographic surveys in 2015 were completed using real-time kinematic Global Navigation Satellite Systems. Topographic surveys in 2020 were completed using both real-time kinematic Global Navigation Satellite Systems and light detection and ranging. Elevation-change maps were created using propagated uncertainties associated with the 95-percent confidence limit. Study areas along Fountain Creek underwent a range of geomorphic responses between 2015 and 2020 that were often related to the dominant channel planform pattern of the study area. The results of this ongoing monitoring effort can be used to assess long-term changes in land-surface elevation and to advance understanding of the geomorphic response to possible changes in flow conditions on Fountain Creek.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sim3481","collaboration":"Prepared in cooperation with Colorado Springs Utilities","usgsCitation":"Hempel, L.A., Creighton, A.L., and Bock, A.R., 2021, Elevation and elevation-change maps of Fountain Creek, southeastern Colorado, 2015–20: U.S. Geological Survey Scientific Investigations Map 3481, 10 sheets, 12-p. pamphlet, https://doi.org/10.3133/sim3481.","productDescription":"Report: vii, 12 p.; 10 Sheets: 12.19 x 13.44 inches or smaller; Data Release; Read Me; Related Work","onlineOnly":"Y","ipdsId":"IP-124273","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":391163,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3456","text":"Elevation and Elevation-Change Maps of Fountain Creek, Southeastern Colorado, 2015–19"},{"id":391154,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3481/sim3481_sheet7.pdf","text":"Elevation (2015, 2020) and Elevation-Change (2015−20) Map—Study Area 07","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3581 Sheet 7","linkHelpText":"Download file and view it in Adobe Acrobat DC or Adobe Reader DC to access interactive layers."},{"id":391153,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3481/sim3481_sheet6.pdf","text":"Elevation (2015, 2020) and Elevation-Change (2015−20) Map—Study Area 06","size":"1.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3581 Sheet 6","linkHelpText":"Download file and view it in Adobe Acrobat DC or Adobe Reader DC to access interactive layers."},{"id":391157,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3481/sim3481_sheet10.pdf","text":"Elevation (2015, 2020) and Elevation-Change (2015−20) Map—Study Area 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Map—Study Area 03","size":"1.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3581 Sheet 3","linkHelpText":"Download file and view it in Adobe Acrobat DC or Adobe Reader DC to access interactive layers."},{"id":391155,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3481/sim3481_sheet8.pdf","text":"Elevation (2015, 2020) and Elevation-Change (2015−20) Map—Study Area 08","size":"1.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3581 Sheet 8","linkHelpText":"Download file and view it in Adobe Acrobat DC or Adobe Reader DC to access interactive layers."},{"id":391156,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3481/sim3481_sheet9.pdf","text":"Elevation (2015, 2020) and Elevation-Change (2015−20) Map—Study Area 09","size":"1.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3581 Sheet 9","linkHelpText":"Download file and view it in Adobe Acrobat DC or Adobe Reader DC to access interactive layers."},{"id":391159,"rank":13,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3481/sim3481_sheets1to10.pdf","text":"Elevation (2015, 2020) and Elevation-Change (2015−20) Map—Study Areas 1- 10","size":"8.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3581 Sheets 1-10","linkHelpText":"Download file and view it in Adobe Acrobat DC or Adobe Reader DC to access interactive layers."},{"id":391162,"rank":15,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98J7DRO","text":"USGS data release","linkHelpText":"Elevation Data from Fountain Creek between Colorado Springs and the Confluence of Fountain Creek at the Arkansas River, Colorado, 2020 (ver 2.0, May 2021)"},{"id":391090,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3481/coverthb.jpg"},{"id":391091,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3481/sim3481_pamphlet.pdf","text":"Report","size":"2.61 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2020) and Elevation-Change (2015−20) Map—Study Area 05","size":"1.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3581 Sheet 5","linkHelpText":"Download file and view it in Adobe Acrobat DC or Adobe Reader DC to access interactive layers."}],"country":"United States","state":"Colorado","otherGeospatial":"Fountain Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.0567626953125,\n 38.09998264736481\n ],\n [\n -104.2108154296875,\n 38.09998264736481\n ],\n [\n -104.2108154296875,\n 38.9807627650163\n ],\n [\n -105.0567626953125,\n 38.9807627650163\n ],\n [\n -105.0567626953125,\n 38.09998264736481\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046
Oxidative weathering of sedimentary rocks plays an important role in the global carbon cycle. Rhenium (Re) has been proposed as a tracer of rock organic carbon (OCpetro) oxidation. However, the sources of Re and its mobilization by hydrological processes remain poorly constrained. Here we examine dissolved Re as a function of water discharge, using samples collected from three alpine catchments that drain sedimentary rocks in Switzerland (Erlenbach, Vogelbach) and Colorado, USA (East River). The Swiss catchments reveal a higher Re flux in the catchment with higher erosion rates, but have similar [Re]/[Na+] and [Re]/[SO42-] ratios, which indicate a dominance of Re from OCpetro. Despite differences in rock type and hydro-climatic setting, the three catchments have a positive correlation between river water [Re]/[Na+] and [Re]/[SO42-] and water discharge. We propose that this reflects preferential routing of Re from a near-surface, oxidative weathering zone. The observations support the use of Re as a proxy to trace rock-organic carbon oxidation, and suggest it may be a hydrological tracer of vadose zone processes. We apply the Re proxy, and estimate CO2 release by OCpetro oxidation of 5.7 +6.6/-2.0 tC km-2 yr-1 for the Erlenbach. The overall weathering intensity was ∼40%, meaning that the corresponding export of un-weathered OCpetro in river sediments is large, and the findings call for more measurements of OCpetro oxidation in mountains and rivers as thet cross floodplains.
This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2 Advanced Wide Field Sensor (AWiFS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2021. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Resourcesat-2 is a medium-resolution satellite launched in 2011 on the Polar Satellite Launch Vehicle-C16. Resourcesat-2 carries the same sensing elements as Resourcesat-1 (launched in October 2003) and provides continuity for the mission. The objectives of the Resourcesat mission are to provide remote sensing data services to global users, focusing on data for integrated land and water resources management.
Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 launch vehicle for continuity of data and improved temporal resolution. The two satellites operating in tandem improved the revisit capability from 5 days to 2–3 days. The Resourcesat-2 platform is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the AWiFS, Linear Imaging Self Scanning-3, and Linear Imaging Self Scanning-4 sensors for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that AWiFS has an interior geometric performance in the range of −16.080 (−0.268 pixel) to 35.520 meters (m; 0.592 pixel) in easting and −25.680 (−0.428 pixel) to 23.400 m (0.390 pixel) in northing in band-to-band registration, an exterior geometric error of −64.262 (−1.071 pixels) to −19.059 m (−0.318 pixel) in easting and −29.028 (−0.484 pixel) to 41.249 m (0.687 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of 2.29–2.36 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.030–0.035.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030G","usgsCitation":"Ramaseri Chandra, S.N., Kim, M., Christopherson, J., Stensaas, G.L., and Anderson, C., 2021, System characterization report on Resourcesat-2 Advanced Wide Field Sensor, chap. G of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors (ver. 1.2, August 2024): U.S. Geological Survey Open-File Report 2021–1030, 17 p., https://doi.org/10.3133/ofr20211030G.","productDescription":"Report: iv, 17 p.; Version History","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-126658","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":392291,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1030/g/versionHist.txt","text":"Version History","size":"1.8 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2021–1030G Version History"},{"id":391064,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/g/images"},{"id":391063,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/g/ofr20211030g.xml","text":"Report","size":"79.7 kB","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2021–1030G xml"},{"id":433255,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/g/ofr20211030g.pdf","text":"Report","size":"2.2 MB","description":"OFR 2021–1030G"},{"id":391061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/g/coverthb3.jpg"}],"edition":"Version 1.0: September 28, 2021; Version 1.1: November 30, 2021; Version 1.2: August 29, 2024","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
A telemetry study was conducted during August–December 2020 to evaluate behavior and movement patterns of adult smallmouth bass (Micropterus dolomieu) in the forebay of Bonneville Dam, Washington. A total of 40 smallmouth bass were collected, tagged, and released during August–September in seven distinct areas of the dam forebay and monitored until mid-December. Movement data from 36 tagged smallmouth bass were used in behavior analyses with an average detection duration (elapsed time from release to last detection) of 53.3 days. Nine smallmouth bass eventually moved upstream out of the array and sixteen smallmouth bass moved downstream out of the array. Smallmouth bass showed high site fidelity, primarily remaining within their zone of release or moving into nearby adjacent zones. Tagged smallmouth bass spent the greatest percentage of time in their zone of release in all zones except the Boat Rock zone; the five smallmouth bass released in the Boat Rock zone moved to the Goose Island zone, where they stayed most of their time. Smallmouth bass movements to zones farthest away from their zone of release were not common and smallmouth bass residence time in those zones was short. A large percentage of tagged smallmouth bass moved among three zones located immediately upstream from the Bonneville Dam spillway, which was not operated during the study. Results from the study provided new insights into smallmouth bass behavior patterns during fall months in the forebay of Bonneville Dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211099","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Kock, T.J., Hansen, G.S., and Evans, S.D., 2021, Behavior and movement of smallmouth bass (Micropterus dolomieu) in the forebay of Bonneville Dam, Columbia River, August–December 2020: U.S. Geological Survey Open-File Report 2021–1099, 13 p., https://doi.org/10.3133/ofr20211099.","productDescription":"vii, 13 p.","onlineOnly":"Y","ipdsId":"IP-127395","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":403444,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211099/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2021-1099"},{"id":391094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1099/coverthb.jpg"},{"id":391095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1099/ofr20211099.pdf","text":"Report","size":"26.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1099"},{"id":397378,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1099/images"},{"id":397379,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1099/ofr20211099.XML"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Bonneville Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.97381973266602,\n 45.624362920967556\n ],\n [\n -121.91717147827148,\n 45.624362920967556\n ],\n [\n -121.91717147827148,\n 45.65736777757339\n ],\n [\n -121.97381973266602,\n 45.65736777757339\n ],\n [\n -121.97381973266602,\n 45.624362920967556\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Northern bobwhite Colinus virginianus populations have been rapidly declining in the eastern, central, and southern United States for decades. Land use change and an incompatibility between northern bobwhite resource needs and human land use practices have driven declines. Here, we applied occupancy analyses on two spatial scales (state level and ecoregion level) to more than 5,000 northern bobwhite surveys conducted over 6 y across the entire state of Arkansas to explore patterns in occupancy and land use variables, and to identify priority areas for management and conservation. At the state level, northern bobwhite occupied 29% of sites and northern bobwhite were most likely to occur in areas with a high percentage of early successional habitat (grassland, pasture, and shrubland). The statewide model predicted that northern bobwhite were likely to occur (≥ 75% predicted occupancy) in < 20% of the state. Arkansas is comprised of five distinct ecoregions, and analyses at the ecoregion spatial scale showed that habitat associations of northern bobwhite could vary between ecoregions. For example, early successional habitat best predicted northern bobwhite occupancy in both the Arkansas River Valley and Ozark Mountains ecoregions, and other habitat associations such as the proportion of herbaceous habitat and hay-pasture habitat, respectively, further refined predictions. Contrastingly, richness of land cover classes alone best predicted northern bobwhite occupancy in the Ouachita Mountains ecoregion. Ecoregion-level models were thus more discerning than the state-level model and should be more helpful to managers in identifying priority conservation areas. However, in two of five ecoregions, surveys too rarely encountered northern bobwhite to accurately predict their occurrence. We found that likely occupied northern bobwhite habitat lay primarily on private properties (95%), but that numerous public entities own and manage land identified as suitable or likely occupied. We conclude that management of northern bobwhite in Arkansas could benefit from cooperation among state, federal, and military partners, as well as surrounding private landowners and that ecoregion-specific models may be more useful in identifying priority areas for management. Our approach incorporates multiple landscape scales when using remote sensing technology in conjunction with monitoring data and could have important application for the management of northern bobwhite and other grassland bird species.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-21-002","usgsCitation":"Lassiter, E.V., Asher, M., Christie, G., Gale, C., Massey, A., Massery, C., MIddaugh, C., Veon, J., and DeGregorio, B.A., 2021, Northern bobwhite occupancy patterns on multiple spatial scales across Arkansas: Journal of Fish and Wildlife Management, v. 12, no. 2, p. 502-512, https://doi.org/10.3996/JFWM-21-002.","productDescription":"11 p.","startPage":"502","endPage":"512","ipdsId":"IP-125981","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450328,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-002","text":"Publisher Index Page"},{"id":396907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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R.","contributorId":288241,"corporation":false,"usgs":false,"family":"MIddaugh","given":"C. R.","affiliations":[{"id":37007,"text":"Arkansas Game and Fish Commission","active":true,"usgs":false}],"preferred":false,"id":837584,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veon, J.","contributorId":288245,"corporation":false,"usgs":false,"family":"Veon","given":"J.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":837585,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837586,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70225682,"text":"70225682 - 2021 - Synergistic interventions to control COVID-19: Mass testing and isolation mitigates reliance on distancing","interactions":[],"lastModifiedDate":"2021-11-03T13:14:26.474395","indexId":"70225682","displayToPublicDate":"2021-10-28T08:13:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5727,"text":"PLOS Computational Biology","active":true,"publicationSubtype":{"id":10}},"title":"Synergistic interventions to control COVID-19: Mass testing and isolation mitigates reliance on distancing","docAbstract":"Stay-at-home orders and shutdowns of non-essential businesses are powerful, but socially costly, tools to control the pandemic spread of SARS-CoV-2. Mass testing strategies, which rely on widely administered frequent and rapid diagnostics to identify and isolate infected individuals, could be a potentially less disruptive management strategy, particularly where vaccine access is limited. In this paper, we assess the extent to which mass testing and isolation strategies can reduce reliance on socially costly non-pharmaceutical interventions, such as distancing and shutdowns. We develop a multi-compartmental model of SARS-CoV-2 transmission incorporating both preventative non-pharmaceutical interventions (NPIs) and testing and isolation to evaluate their combined effect on public health outcomes. Our model is designed to be a policy-guiding tool that captures important realities of the testing system, including constraints on test administration and non-random testing allocation. We show how strategic changes in the characteristics of the testing system, including test administration, test delays, and test sensitivity, can reduce reliance on preventative NPIs without compromising public health outcomes in the future. The lowest NPI levels are possible only when many tests are administered and test delays are short, given limited immunity in the population. Reducing reliance on NPIs is highly dependent on the ability of a testing program to identify and isolate unreported, asymptomatic infections. Changes in NPIs, including the intensity of lockdowns and stay at home orders, should be coordinated with increases in testing to ensure epidemic control; otherwise small additional lifting of these NPIs can lead to dramatic increases in infections, hospitalizations and deaths. Importantly, our results can be used to guide ramp-up of testing capacity in outbreak settings, allow for the flexible design of combined interventions based on social context, and inform future cost-benefit analyses to identify efficient pandemic management strategies.
The gill is one of the most important organs for growth and survival of fishes. Early life stages in coral reef fishes often exhibit extreme physiological and demographic characteristics that are linked to well-established respiratory and ionoregulatory processes. However, gill development and function in coral reef fishes is not well-understood. Therefore, we investigated gill morphology, oxygen uptake, and ionoregulatory systems throughout embryogenesis in two coral reef damselfishes, Acanthochromis polyacanthus and Amphiprion melanopus (Pomacentridae). In both species, we found key gill structures to develop rapidly early in the embryonic phase. Ionoregulatory cells appear on gill filaments 3-4 days post fertilization and increase in density, whilst disappearing or shrinking in cutaneous locations. Primary respiratory tissue (lamellae) appears 5-7 days post fertilization, coinciding with a peak in oxygen uptake rates of the developing embryos. Oxygen uptake was unaffected by phenylhydrazine across all ages (pre-hatch), indicating that haemoglobin is not yet required for oxygen uptake. This suggests that gills have limited contribution to respiratory functions during embryonic development, at least until hatching. Rapid gill development in damselfishes, when compared to most of the previously investigated fishes, may reflect preparations for a high-performance, challenging lifestyle on tropical reefs, but may also make reef fishes more vulnerable to anthropogenic stressors.
The Permian Basin, in west Texas and southeastern New Mexico is one of the largest conventional oil and gas reservoirs in the United States and is becoming one of the world’s largest continuous oil and gas (COG) reservoirs. Advances in technology have enabled oil and gas to be extracted from reservoirs that historically were developed using conventional, or vertical, well drilling techniques. Conventional oil and gas reservoirs have discrete deposits that are well defined and are typically trapped by an overlying geologic formation or caprock, whereas COG reservoirs contain deposits that are distributed evenly throughout the geologic formation, typically have much lower permeability (the capacity of a porous rock to transmit a fluid) than the conventional deposits, and require specialized horizontal extraction techniques. The methods to extract the oil from the two different reservoirs require differing amounts of water, and the horizontal extraction methods typically require substantially more water. In 2015, the U.S. Geological Survey started a topical study to quantify water used during COG development. The Permian Basin, which contains both types of reservoirs (continuous and conventional), was the second basin in the United States in the U.S. Geological Survey’s topical study to quantify water used during COG development.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213053","usgsCitation":"Houston, N.A., Ball, G.P., Galanter, A.E., Valder, J.F., McShane, R.R., Thamke, J.N., and McDowell, J.S., Estimates of Water Use Associated with Continuous Oil and Gas Development in the Permian Basin, Texas and New Mexico, 2010–2019, with Comparisons to the Williston Basin, North Dakota and Montana: U.S. Geological Survey Fact Sheet 2021–3053, 4 p., https://doi.org/10.3133/fs20213053.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-124923","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":390943,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2021/3053/images"},{"id":390942,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2021/3053/fs20213053.xml","text":"Report","size":"37.7 kB","linkFileType":{"id":8,"text":"xml"},"description":"FS 2021–3053 xml"},{"id":390941,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3053/fs20213053.pdf","text":"Report","size":"4.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021–3053"},{"id":390940,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3053/coverthb.jpg"}],"country":"United States","state":"Montana, New Mexico, North Dakota, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.9296875,\n 48.980216985374994\n ],\n [\n -108.720703125,\n 48.922499263758255\n ],\n [\n -108.017578125,\n 48.28319289548349\n ],\n [\n -107.57812499999999,\n 47.81315451752768\n ],\n [\n -108.369140625,\n 47.45780853075031\n ],\n [\n -108.369140625,\n 47.040182144806664\n ],\n [\n -107.05078125,\n 46.86019101567027\n ],\n [\n -105.556640625,\n 46.07323062540835\n ],\n [\n -103.0078125,\n 45.02695045318546\n ],\n [\n -100.81054687499999,\n 45.089035564831036\n ],\n [\n -99.755859375,\n 47.100044694025215\n ],\n [\n -100.107421875,\n 49.03786794532644\n ],\n [\n -107.9296875,\n 48.980216985374994\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.095703125,\n 34.252676117101515\n ],\n [\n -103.64501953125,\n 33.90689555128866\n ],\n [\n -104.56787109374999,\n 33.578014746143985\n ],\n [\n -105.0732421875,\n 32.879587173066305\n ],\n [\n -105.1171875,\n 32.02670629333614\n ],\n [\n -104.56787109374999,\n 31.42866311735861\n ],\n [\n -104.150390625,\n 30.713503990354965\n ],\n [\n -103.16162109375,\n 30.44867367928756\n ],\n [\n -102.23876953125,\n 30.391830328088137\n ],\n [\n -101.40380859375,\n 30.183121842195515\n ],\n [\n -100.5908203125,\n 29.878755346037977\n ],\n [\n -100.2392578125,\n 29.592565403314087\n ],\n [\n -99.77783203125,\n 29.82158272057499\n ],\n [\n -99.66796875,\n 30.80791068136646\n ],\n [\n -99.73388671874999,\n 31.353636941500987\n ],\n [\n -100.283203125,\n 31.615965936476076\n ],\n [\n -100.34912109375,\n 31.914867503276223\n ],\n [\n -100.61279296875,\n 32.491230287947594\n ],\n [\n -100.32714843749999,\n 32.91648534731439\n ],\n [\n -100.107421875,\n 33.706062655101206\n ],\n [\n -100.45898437499999,\n 34.19817309627726\n ],\n [\n -100.8544921875,\n 34.32529192442733\n ],\n [\n -102.12890625,\n 34.488447837809304\n ],\n [\n -102.72216796875,\n 34.397844946449865\n ],\n [\n -103.095703125,\n 34.252676117101515\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
The U.S. Geological Survey installed 10 rain gages and 12 calibrated H-flumes to measure rainfall and runoff volumes at 10 locations in Ohio Department of Transportation highway median-strip catchments. Data were collected to facilitate comparisons of rainfall and runoff volumes at study sites before and after stormwater best management practices (BMPs) were installed and between sites with different BMPs. The BMP treatments comprised removing the top layer of the existing soil, rototilling the remaining soil to a 6-inch depth, mixing the soils with one of two soil amendments (compost with sand or shale) at one of two thicknesses (4 inches or 6 inches), topping with a compost blanket, seeding, and installing erosion control matting. The overall treatment used at a given study site is referred to as “BMP.” At two locations where soil amendments were installed, a second “control” site was installed to measure runoff from an adjacent catchment in the same median strip where no soil amendment was installed. This no-treatment option (no soil amendment) was considered its own class of BMP.
Rainfall and runoff data were collected during periods when air temperatures were above freezing (including all months except January, February, and parts of December and March) from 2018 to 2020. The data collection period for each study site was divided into “pre-BMP” and “post-BMP” periods. Equipment to measure rainfall and runoff was installed and data were collected from April to December 2018 before installation of soil amendments (the pre-BMP period). The post-BMP period started between April and May of 2019 at the first measured rainfall after soil amendments were installed. Rainfall and runoff monitoring continued through September 2020. For control sites, the post-BMP periods were assigned to start with the first measured rainfall in the 2019 data collection season.
A rainfall-runoff “event” was defined as beginning at the time of the first measured rainfall and ending when rainfall and runoff (if any) ceased and remained ceased for at least 3 hours. A value referred to as “event runoff percentage,” defined as the total volume of runoff during an event expressed as a percentage of the total volume of rainfall falling over the catchment, was computed for each event. The distribution of rainfall totals associated with events was similar between the pre-BMP and post-BMP periods; however, there were appreciable between-site differences in the distribution of event runoff percentages during the pre-BMP and post-BMP periods.
Empirical distribution function (EDF) tests were performed with and without data from events that resulted in no runoff to determine whether the distribution of event runoff percentages changed from the pre-BMP period to the post-BMP period. The null hypothesis that the EDFs of event runoff percentages were equal in the pre-BMP and post-BMP periods was rejected (α=0.05) in at least one of the two tests for four sites (one site with a shale amendment and three sites with sand amendments). Mean event runoff percentages at each of those four sites decreased from the pre-BMP period to the post-BMP period. The null hypothesis that the EDFs of event runoff percentages were equal was not rejected for the other six sites’ draining catchments with soil amendments or the two control sites. EDF tests performed on event rainfall totals indicated no statistically significant changes between the pre-BMP and post-BMP period distributions for any of the sites.
Double-mass analyses of cumulative runoff were performed for two pairs of closely spaced sites (each pair located in a common median strip): one site in each pair drained a catchment where soil amendments were installed, and the other (a control) drained a catchment without soil amendments. Those double-mass analyses indicated a small reduction in runoff from the pre-BMP to post-BMP period at the site whose catchment received the sand and compost amendment, but no perceptible reduction in runoff at the site whose catchment received the shale and compost amendment.
Regression analyses indicated that (a) three rainfall factors (event rainfall totals, total rainfall for the previous 7 days, and a cross product of the factors) and the intercept term were the four most important factors explaining event runoff percentages, (b) the effect of amendment type on event runoff percentage was small in comparison to the rainfall and intercept terms, (c) event runoff percentages tended to be lower for sites with shale amendments than sites with sand amendments; however, event runoff percentages tended to be lower for control sites than for sites with shale or sand amendments, and (d) event runoff percentages increased with increasing amendment thickness. The counterintuitive results that event runoff percentages increased with increasing amendment thickness and that control sites tended to have lower event runoff percentages than sites draining soil-amended catchments likely reflects unmeasured factors that existed at the sites before BMPs were installed rather than the effect of the BMP treatments.
Although not definitive, some support for the conclusion that the sand amendment was generally more effective at reducing runoff than the shale amendment was provided by results from the EDF tests, double-mass analyses, and runoff statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215114","collaboration":"Prepared in cooperation with ms consultants","usgsCitation":"Whitehead, M.T., and Koltun, G.F., 2021, Assessment of runoff volume reduction associated with soil amendments added to portions of highway median-strip catchments in Ohio, 2018–20 (ver. 1.1, December 2021): U.S. Geological Survey Scientific Investigations Report 2021–5114, 27 p., https://doi.org/10.3133/sir20215114.","productDescription":"Report: vii, 27 p.; Data Release; Version History","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-118944","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":390957,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P945PKJ7","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Dataset for analyses in assessment of runoff volume reduction associated with soil amendments added to portions of highway median-strip catchments in Ohio"},{"id":390955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5114/coverthb2.jpg"},{"id":392682,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5114/sir20215114.pdf","text":"Report","size":"5.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5114"},{"id":390958,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5114/sir20215114.XML","text":"Report","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5114 xml"},{"id":392683,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5114/versionHist.txt","text":"Version History","size":"3.07 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"},{"id":390959,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5114/images"}],"country":"United States","state":"Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.6279296875,\n 39.639537564366684\n ],\n [\n -80.947265625,\n 39.639537564366684\n ],\n [\n -80.947265625,\n 41.261291493919884\n ],\n [\n -83.6279296875,\n 41.261291493919884\n ],\n [\n -83.6279296875,\n 39.639537564366684\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: October 2021; Version 1.1: December 2021","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd.
Ste 100
Columbus, OH 43229–1737
Identifying the physical habitat characteristics associated with riverine freshwater mussel assemblages is challenging but crucial for understanding the causes of mussel declines. The occurrence of mussels in multispecies beds suggests that common physical factors influence or limit their occurrence. Fine-scale geomorphic and hydraulic factors (e.g., scour, bed stability) are predictive of mussel-bed occurrence, but they are computationally challenging to represent at intermediate or riverscape scales. We used maximum entropy (MaxEnt) modeling to evaluate associations between riverscape-scale hydrogeomorphic variables and mussel-bed presence along 530 river km of the Meramec River basin, USA, to identify river reaches that are fundamentally suitable for mussels as well as those that are not. We obtained the locations of mussel beds from an existing, multiyear dataset, and we derived river variables from high-resolution, open-source datasets of aerial imagery and topography. Mussel beds occurred almost exclusively in reaches identified by our model as suitable; these were characterized by laterally stable channels, absence of adjacent bluffs, proximity to gravel bars, higher stream power, and larger areas of contiguous water (a proxy for drought vulnerability). We validated our model findings based on model sensitivity using a set of mussel-bed locations not used in model development. These findings can inform how resource managers allocate survey, monitoring, and conservation efforts.
","language":"English","publisher":"Freshwater Mollusk Conservation Society","doi":"10.31931/fmbc-d-20-00002","usgsCitation":"Keymanesh, K., Rosenberger, A.E., Lindner, G., Bouska, K.L., and McMurray, S.E., 2021, Riverscape-scale modeling of fundamentally suitable habitat for mussel assemblages in an Ozark River system, Missouri: Freshwater Mollusk Biology and Conservation, v. 24, no. 2, p. 43-58, https://doi.org/10.31931/fmbc-d-20-00002.","productDescription":"16 p.","startPage":"43","endPage":"58","ipdsId":"IP-113472","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450336,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc-d-20-00002","text":"Publisher Index Page"},{"id":433559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Meramec River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.23145192205784,\n 38.57316922340365\n ],\n [\n -91.80686253958456,\n 38.57316922340365\n ],\n [\n -91.80686253958456,\n 37.62945983446684\n ],\n [\n -90.23145192205784,\n 37.62945983446684\n ],\n [\n -90.23145192205784,\n 38.57316922340365\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keymanesh, K.","contributorId":317234,"corporation":false,"usgs":false,"family":"Keymanesh","given":"K.","email":"","affiliations":[],"preferred":false,"id":908903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":908904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindner, G.","contributorId":341798,"corporation":false,"usgs":false,"family":"Lindner","given":"G.","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":908905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":908906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMurray, Stephen E.","contributorId":206918,"corporation":false,"usgs":false,"family":"McMurray","given":"Stephen","email":"","middleInitial":"E.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":908907,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225582,"text":"sir20215020 - 2021 - Geologic and hydrogeologic characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, northern greater Denver Basin, southeastern Laramie County, Wyoming","interactions":[],"lastModifiedDate":"2022-06-16T19:45:30.631881","indexId":"sir20215020","displayToPublicDate":"2021-10-27T10:00:17","publicationYear":"2021","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":"2021-5020","displayTitle":"Geologic and Hydrogeologic Characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, Northern Greater Denver Basin, Southeastern Laramie County, Wyoming","title":"Geologic and hydrogeologic characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, northern greater Denver Basin, southeastern Laramie County, Wyoming","docAbstract":"In cooperation with the Wyoming State Engineer’s Office, the U.S. Geological Survey studied the geologic and hydrogeologic characteristics of Cenozoic and Upper Cretaceous strata at a location in southeastern Laramie County within the Wyoming part of the Cheyenne Basin, the northern subbasin of the greater Denver Basin. The study aimed to improve understanding of the aquifers/aquifer systems in these strata, motivated in part by declining groundwater levels and interest in exploring future groundwater supplies. Based on detailed geologic characterization using information obtained by drilling and coring a 960-foot-(ft) deep exploratory borehole, and comparisons with previously published descriptions, identified Cenozoic lithostratigraphic units included 40 ft of Quaternary older alluvial fan deposits consisting of an unconsolidated mixture of sand and gravel with lesser quantities of silt and clay in varying proportions and the underlying 407.3-ft-thick White River Formation of late Eocene-Oligocene age consisting largely of mudrocks with sparse thin beds of sandstone, muddy gravel, and conglomeratic mudrocks. Identified Upper Cretaceous lithostratigraphic units included the 351.6-ft-thick Lance Formation, consisting of terrestrial sedimentary rocks including mudrocks (muddy shale and silty and sandy shale, siltstone, claystone, and mudstone) interbedded with much smaller quantities of very fine- to medium-grained muddy and silty sandstone and coal; the 79.6-ft-thick Fox Hills Sandstone, consisting of a transitional marine sequence of muddy or silty sandstone present in five individual beds; and 86.7 ft of the upper transition member of the Pierre Shale, consisting largely of marine sedimentary rocks such as muddy shale. Beds of the upper and lower Fox Hills Sandstone were separated by tongues of the Lance Formation and upper transition member of the Pierre Shale, respectively.
The White River hydrogeologic unit, consisting of the entire White River Formation or Group at the study site, did not contain any substantial secondary permeability features in the mudrocks that composed almost all the unit. A monitoring well (BR–1) was completed in the White River aquifer with the well screen open to the only coarse-grained unit (muddy sandstone) that had sufficient thickness and permeability to be considered as an aquifer. Sampling of the well for a broad suite of constituents indicated groundwater generally was of excellent quality except dissolved arsenic was detected at a concentration greater than the U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level, and dissolved sodium was measured at a concentration greater than several EPA Drinking Water Advisory Levels (DWAs) for the constituent. Well development, well purging for groundwater sampling, and calculated aquifer properties indicated the sandstone aquifer screened by monitoring well BR–1 was not very productive. Analysis of the well water-level responses in BR–1 to atmospheric loading and Earth tides indicated the responses were consistent with a confined-aquifer response with wellbore-storage effects. Hydraulic properties estimated based on these responses yielded values of hydraulic conductivity (K, 0.057 foot per day [ft/d]), specific storage (Ss, 1.6×10−6 per foot [ft−1]) and porosity (n, 0.43). Water levels filtered to remove the effects of atmospheric loading and Earth tides indicated an upward trend (+1.13 foot per year [ft/yr]) during the period analyzed, September 5, 2014, to September 30, 2017.
Lithologic characteristics of the Lance hydrogeologic unit, consisting of the entire Lance Formation at the study site, indicated a potential aquifer in a “sandy” interval in the upper part of the unit. Most of the Lance hydrogeologic unit below the “sandy” interval consisted of various low-permeability lithologies unlikely to yield substantial quantities of water. This lower part of the hydrogeologic unit likely functions as a confining unit separating the underlying Lance-Fox Hills aquifer. A geologic cross section constructed for this study indicated fine-grained sediments composed most of the Lance Formation/hydrogeologic unit not only at the study location, but also throughout southern Laramie County along the line of section and throughout the Wyoming and Colorado parts of the Cheyenne Basin. A monitoring well (LN–1) completed in a sandstone bed in the “sandy” interval of the Lance hydrogeologic unit produced a mean of about 23 gallons per minute (gal/min) during well development, indicating sandstone beds can form moderately productive confined subaquifers in this part of the hydrogeologic unit. Analysis of the well water-level responses in well LN–1 to atmospheric loading and Earth tides indicated the responses were consistent with a confined-aquifer response. Hydraulic properties estimated based on these responses yielded values for a lower bounding K of 0.60 ft/d, Ss of 1.6×10−6 ft−1, and n of 0.38. Water levels filtered to remove the effects of atmospheric loading and Earth tides indicated a downward trend (−0.86 ft/yr) during the period analyzed (November 8, 2014, to September 30, 2017). Analyses for a broad suite of constituents in samples from well LN–1 indicated groundwater quality generally was excellent, although dissolved sodium was measured at a concentration greater than two EPA DWA levels for the constituent.
Because of the absence of any overlying or intertonguing sandstone beds belonging to the lower/basal part of the Lance Formation, the Lance-Fox Hills aquifer at the study site consisted only of the five sandstone beds of the Fox Hills Sandstone. The cross section constructed for this study illustrated how the Fox Hills Sandstone, and thus, most of the Lance-Fox Hills aquifer, consists of a series of sandstone bodies that overlap (shingle) upward to the east across southern Laramie County. These bodies collectively form a fairly continuous body of sandstone, thus potentially forming an areally extensive aquifer across southern Laramie County, and by extension, throughout most of the formation’s extent in the Wyoming part of the Cheyenne Basin, as is the case in the Colorado part of the basin. A monitoring well (FH–1) completed in part of the thickest sandstone bed of the Lance-Fox Hills aquifer was moderately to highly productive and easily produced 25 to 30 gal/min after development. Substantially larger water production rates likely could be obtained by penetrating the full thickness of this bed and by completing a well open to the other overlying and underlying sandstone beds of the aquifer. Analysis of the water-level responses in well FH–1 to atmospheric loading and Earth tides indicated the responses were consistent with a confined-aquifer response. Hydraulic properties computed based on these responses yielded values for a lower bounding estimate for K of 0.26 ft/d, for Ss of 1.0×10−6 ft−1, and for n of 0.41. Water levels filtered to remove the effects of atmospheric loading and Earth tides indicated a downward trend (−1.74 ft/yr) during the period analyzed, December 19, 2014, to September 30, 2017. Sampling of monitoring well FH–1 and two production wells completed in the Fox Hills Sandstone in other parts of Laramie County indicated groundwater quality generally is excellent, although pH exceeded a recommended EPA aesthetic drinking-water standard (Secondary Maximum Contaminant Level) in two of three sampled wells, total dissolved solids concentrations exceeded the Secondary Maximum Contaminant Level in one of the two sampled production wells, and dissolved sodium was measured in all three sampled wells at a concentration greater than two EPA DWA levels for the constituent. The Wyoming Class II agricultural (irrigation) sodium adsorption ratio standard of 8 was exceeded in all three sampled wells, indicating these waters are not suitable for irrigation use.
Computed vertical hydraulic gradients indicated a strong potential for downward flow throughout the groundwater system at the study site, including from the low-yielding aquifer in the upper White River Formation/hydrogeologic unit (monitoring well BR–1) to the sandstone subaquifer in the Lance Formation/hydrogeologic unit (monitoring well LN–1), and from the Lance subaquifer (monitoring well LN–1) to the sandstone bed/aquifer that composes much of the Lance-Fox Hills aquifer thickness at the study site (monitoring well FH–1). However, large hydraulic-head differences between wells indicated high resistance to vertical flow attributable to the low vertical hydraulic conductivity of intervening strata, which consisted almost entirely of low-permeability mudrocks. The confined nature of the sandstone aquifers monitored by the various wells coupled with dissimilarities between groundwater-level fluctuations and trends in groundwater levels indicated downward flow through the intervening strata (primarily mudrocks in the various lithostratigraphic/hydrogeologic units) between the examined sets of wells likely was small.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215020","collaboration":"Prepared in cooperation with the Wyoming State Engineer’s Office","usgsCitation":"Bartos, T.T., Galloway, D.L., Hallberg, L.L., Dechesne, M., Diehl, S.F., and Davidson, S.L., 2021, Geologic and hydrogeologic characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, northern greater Denver Basin, southeastern Laramie County, Wyoming: U.S. Geological Survey Scientific Investigations Report 2021–5020, 219 p., 1 pl., https://doi.org/10.3133/sir20215020.","productDescription":"Report: xvii, 219 p.; Appendix Table; Plate: 42.00 x 63.00 inches; Data Release; Dataset","numberOfPages":"242","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-110049","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":390939,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS groundwater data for Wyoming, in USGS water data for the Nation"},{"id":390938,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PPLA74","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Atmospheric-loading frequency response functions and groundwater levels filtered for the effects of atmospheric loading and solid Earth tides for three USGS monitoring wells, southeastern Laramie County, Wyoming, 2014–2017"},{"id":390936,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5020/sir20215020_plate.pdf","text":"Plate","size":"2.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5020 Plate","linkHelpText":"— Construction of monitoring wells BR–1, LN–1, and FH–1, and geophysical logs, generalized lithology, and interpreted lithostratigraphy for exploratory borehole LC–F1, southeastern Laramie County, Wyoming"},{"id":390937,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5020/sir20215020_table1.1.pdf","text":"Table 1.1","size":"500 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5020 Appendix Table","linkHelpText":"— Description of core collected from exploratory borehole LC–F1, southeastern Laramie County, Wyoming"},{"id":390934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5020/coverthb.jpg"},{"id":390935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5020/sir20215020.pdf","text":"Report","size":"26.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5020"}],"country":"United States","state":"Wyoming","county":"Laramie County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.6506,41.651],[-104.6491,41.5656],[-104.0521,41.5654],[-104.052,41.3949],[-104.0526,41.0236],[-104.0528,41.0017],[-104.1399,41.0019],[-104.4725,41.0027],[-104.4875,41.0027],[-104.5606,41.0028],[-104.5679,41.0028],[-104.6087,41.0046],[-104.6134,41.0048],[-104.6337,41.0056],[-104.6648,41.0047],[-104.6837,41.0041],[-104.7013,41.0035],[-104.83,40.9996],[-104.8341,40.9996],[-104.9385,40.9995],[-104.9425,40.9995],[-105.1109,40.9993],[-105.2763,40.9998],[-105.2774,41.6567],[-105.1706,41.6535],[-105.0575,41.6537],[-104.9419,41.6537],[-104.6506,41.651]]]},\"properties\":{\"name\":\"Laramie\",\"state\":\"WY\"}}]}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Black Carp (Mylopharyngodon piceus) has invaded the Mississippi River and is a potential threat to native mollusks. During prior diet research, we discovered that the fluke Aspidogaster conchicola, a mollusk parasite, occurs regularly in the gastrointestinal tract of Black Carp. The fluke remains in fish intestines for extended periods after the fish has consumed its host. Flukes were found in 33% of the wild Black Carp examined, and numbers ranged from 1 to 802, with no pattern evident across seasons of fish capture. Treating the flukes as indicators of prior mollusk consumption, we adjusted the percent occurrence of mollusks from 26.6% to 54.1%, indicating that the previously reported incidences for bivalves (22.8%) and gastropods (16.5%) in the diet of wild Black Carp are likely to be underestimated. Based on percent occurrences in Black Carp, larger fish (>791 mm) had significantly higher fluke occurrence (42.6%) and fish captured from lentic habitats had significantly greater fluke-adjusted mollusk occurrence (87.5%). These diet-occurrence estimates, coupled with the presence of gravid A. conchicola and evidence of their continued viability in Black Carp intestines, indicate that these fish retain evidence of mollusk consumption for extended periods after evacuation of the gastrointestinal tract. Consequently, Black Carp has the potential to disperse this parasite to other mollusks.
","language":"English","publisher":"Freshwater Mollusk Conservation Society","doi":"10.31931/fmbc-d-20-00011","usgsCitation":"Poulton, B.C., Bailey, J., Kroboth, P., George, A.E., and Chapman, D., 2021, Invasive black carp as a reservoir host for the freshwater mollusk parasite Aspidogaster conchicola: Further evidence of mollusk consumption and implications for parasite dispersal: Freshwater Mollusk Biology and Conservation, v. 24, no. 2, p. 114-123, https://doi.org/10.31931/fmbc-d-20-00011.","productDescription":"10 p.","startPage":"114","endPage":"123","ipdsId":"IP-112532","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":450340,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc-d-20-00011","text":"Publisher Index Page"},{"id":391161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Mississippi River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.75830078125,\n 39.99395569397331\n ],\n [\n -89.09912109375,\n 40.68063802521456\n ],\n [\n -89.80224609374999,\n 41.11246878918088\n ],\n [\n -91.16455078125,\n 40.17887331434696\n ],\n [\n -91.5380859375,\n 39.67337039176558\n ],\n [\n -91.7138671875,\n 38.54816542304656\n ],\n [\n -90.4833984375,\n 37.59682400108367\n ],\n [\n -89.7802734375,\n 37.020098201368114\n ],\n [\n -90.2197265625,\n 36.01356058518153\n ],\n [\n -91.34033203125,\n 34.30714385628804\n ],\n [\n -91.64794921875,\n 32.676372772089834\n ],\n [\n -92.08740234375,\n 30.90222470517144\n ],\n [\n -91.42822265625,\n 30.56226095049944\n ],\n [\n -91.318359375,\n 31.052933985705163\n ],\n [\n -90.85693359375,\n 31.93351676190369\n ],\n [\n -90.72509765625,\n 33.19273094190692\n ],\n [\n -90.087890625,\n 34.63320791137959\n ],\n [\n -88.87939453125,\n 36.31512514748051\n ],\n [\n -88.30810546875,\n 36.527294814546245\n ],\n [\n -87.978515625,\n 36.721273880045004\n ],\n [\n -88.154296875,\n 37.24782120155428\n ],\n [\n -88.70361328125,\n 38.89103282648846\n ],\n [\n -89.75830078125,\n 39.99395569397331\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Poulton, Barry C. 0000-0002-7219-4911 bpoulton@usgs.gov","orcid":"https://orcid.org/0000-0002-7219-4911","contributorId":2421,"corporation":false,"usgs":true,"family":"Poulton","given":"Barry","email":"bpoulton@usgs.gov","middleInitial":"C.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":826047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Jennifer","contributorId":212231,"corporation":false,"usgs":false,"family":"Bailey","given":"Jennifer","email":"","affiliations":[{"id":38464,"text":"USFWS, LaCrosse Fish Health Center, Midwest Fisheries Center","active":true,"usgs":false}],"preferred":false,"id":826048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroboth, Patrick 0000-0002-9447-4818","orcid":"https://orcid.org/0000-0002-9447-4818","contributorId":216578,"corporation":false,"usgs":true,"family":"Kroboth","given":"Patrick","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":826049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":826050,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":826051,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225686,"text":"70225686 - 2021 - Telemetry reveals migratory drivers and disparate space use across seasons and age-groups in American horseshoe crabs","interactions":[],"lastModifiedDate":"2021-11-03T13:06:09.653159","indexId":"70225686","displayToPublicDate":"2021-10-27T08:03:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Telemetry reveals migratory drivers and disparate space use across seasons and age-groups in American horseshoe crabs","docAbstract":"Identifying mechanisms that underpin animal migration patterns and examining variability in space use within populations is crucial for understanding population dynamics and management implications. In this study, we quantified the migration rates, seasonal changes in migratory connectivity, and residency across population demographics (age and sex) to understand the proximate cues of migration timing in American horseshoe crabs (Limulus polyphemus). Juvenile (n = 25) and adult (n = 70) horseshoe crabs were tracked with acoustic telemetry techniques for a 3-yr period in Moriches Bay, NY. Connectivity metrics and residency probability were quantified through spatial network analysis and empirically derived Markov Chain models (EDMC), respectively. The migratory probability of adult horseshoe crabs between Moriches Bay and the Atlantic Ocean was estimated to be 41.0% (95% CI: 34.0–59.8); in contrast, only 8% (95% CI: 1.2–31.6) of juveniles migrated into the ocean. Migration timing was influenced by the interaction of photoperiod and temperature, revealing seasonal differences in migration timing and a 50% narrower range of photoperiod and temperature over which fall migrations occurred compared to spring. Sex-specific differences in space use and connectivity within each season were largely absent; however, centralized habitats were important for maintaining connectivity across all seasons. EDMC results revealed that when standardized to the number of horseshoe crab detections on each receiver, the centrally located habitats in Moriches Bay and Inlet accounted for >50% of the total relative residency probability within most seasons, indicating these areas may be preferred by adult horseshoe crabs. Ontogenetic differences in maximum spatial extent, space use, and connectivity were observed in the bay, as juveniles exhibited lower linkages between locations (n = 4) relative to adults (n = 13) during the same temporal period. Our work highlights the application of novel quantitative approaches for addressing the movement dynamics of horseshoe crabs that can be readily applied to other taxa in the context of wildlife conservation.
Some pathogens sustain transmission in multiple different host species, but how this epidemiologically important feat is achieved remains enigmatic. Sarcoptes scabiei is among the most host generalist and successful of mammalian parasites. We synthesize pathogen and host traits that mediate sustained transmission and present cases illustrating three transmission mechanisms (direct, indirect, and combined). The pathogen traits that explain the success of S. scabiei include immune response modulation, on-host movement capacity, off-host seeking behaviors, and environmental persistence. Sociality and host density appear to be key for hosts in which direct transmission dominates, whereas in solitary hosts, the use of shared environments is important for indirect transmission. In social den-using species, combined direct and indirect transmission appears likely. Empirical research rarely considers the mechanisms enabling S. scabiei to become endemic in host species—more often focusing on outbreaks. Our review may illuminate parasites’ adaptation strategies to sustain transmission through varied mechanisms across host species.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biab106","usgsCitation":"Browne, E., Driessen, M., Cross, P., Escobar, L.E., Foley, J.E., , L., Niedringhaus, K., Rossi, L., and Carver, S., 2021, Sustaining transmission in different host species: The emblematic case of Sarcoptes scabiei: BioScience, biab106, 11 p., https://doi.org/10.1093/biosci/biab106.","productDescription":"biab106, 11 p.","ipdsId":"IP-128884","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":450343,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/biosci/biab106","text":"External Repository"},{"id":391312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Browne, E","contributorId":268241,"corporation":false,"usgs":false,"family":"Browne","given":"E","email":"","affiliations":[{"id":16141,"text":"University of Tasmania","active":true,"usgs":false}],"preferred":false,"id":826258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driessen, MM","contributorId":268242,"corporation":false,"usgs":false,"family":"Driessen","given":"MM","email":"","affiliations":[{"id":55606,"text":"Department of Primary Industries, Parks, Water and Environment, Tasmanian Government.","active":true,"usgs":false}],"preferred":false,"id":826259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":826260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Escobar, L. E. 0000-0001-5735-2750","orcid":"https://orcid.org/0000-0001-5735-2750","contributorId":260844,"corporation":false,"usgs":false,"family":"Escobar","given":"L.","email":"","middleInitial":"E.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":826261,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foley, Janet E.","contributorId":148029,"corporation":false,"usgs":false,"family":"Foley","given":"Janet","email":"","middleInitial":"E.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":826262,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":" Lopez-Olvera","contributorId":268245,"corporation":false,"usgs":false,"given":"Lopez-Olvera","email":"","affiliations":[{"id":55608,"text":"Universitat Autònoma de Barcelona","active":true,"usgs":false}],"preferred":false,"id":826263,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Niedringhaus, KD","contributorId":268246,"corporation":false,"usgs":false,"family":"Niedringhaus","given":"KD","email":"","affiliations":[{"id":39308,"text":"Southeastern Cooperative Wildlife Disease Study","active":true,"usgs":false}],"preferred":false,"id":826264,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rossi, Liza","contributorId":267849,"corporation":false,"usgs":false,"family":"Rossi","given":"Liza","email":"","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":826265,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carver, Scott 0000-0002-3579-7588","orcid":"https://orcid.org/0000-0002-3579-7588","contributorId":197456,"corporation":false,"usgs":false,"family":"Carver","given":"Scott","email":"","affiliations":[],"preferred":false,"id":826266,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70246522,"text":"70246522 - 2021 - Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska","interactions":[],"lastModifiedDate":"2023-07-10T13:20:53.475537","indexId":"70246522","displayToPublicDate":"2021-10-27T06:37:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska","docAbstract":"Mineralogical and geochemical studies of interbedded black and gray mudstones in the Triassic part of the Triassic-Jurassic Otuk Formation (northern Alaska) document locally abundant barite and pyrite plus diverse redox signatures. These strata, deposited in an outer shelf setting at paleolatitudes of ~45 to 60°N, show widespread sedimentological evidence for bioturbation. Barite occurs preferentially in black mudstones (TOC = 0.93–6.46 wt%), forming displacive euhedral crystals with pyrite inclusions and rims, and late albite inclusions or intergrowths. Pyrite also occurs as small (3–20 μm) framboids, discontinuous laminae, euhedral and anhedral crystals, and replacements of barite and fossils (mainly radiolarians). Paragenetically early wurtzite is present as clusters of very small (1–3 μm) aggregates of radiating crystals 0.5 to 1.0 μm long with cores of organic matter that overgrow framboidal pyrite; later wurtzite forms 10- to 30-μm bladed crystals. Equant grains (3–30 μm) and small (20 μm) angular clusters of zinc sulfide that include <1-μm-long, comb-like structures are sphalerite or wurtzite, or both. Minor siderite forms euhedral crystals intergrown with albite that enclose wurtzite and barite. Illite shows intergrowths with sphalerite; rare K-feldspar is intergrown with barite. Formation of these minerals and assemblages is attributed to early diagenetic processes.
Whole-rock geochemical data for 15 samples show large ranges in redox proxies including Post Archean Average Shale (PAAS)-normalized enrichment factors (EFs) for V, U, Mo, and Re, and Al-normalized ratios for V, U, and Mo. Results for most black mudstones, with or without abundant barite and/or pyrite, suggest deposition within an oxygen minimum zone. Cerium anomalies, PAAS-normalized and calculated on a detrital-free basis, range widely from 0.49 to 0.96 and may reflect diagenetic overprinting by Ce-depleted fluids. Considering data for both black and gray mudstones, the overall geochemical pattern together with evidence from pyrite framboid sizes suggest that redox conditions fluctuated greatly from euxinic to oxic, like the redox profiles reported for modern shelf sediments offshore Peru and Namibia. The euxinic redox signatures in some Otuk black mudstones may correlate with widespread Early to Middle Triassic ocean anoxic events proposed for other regions.
Calculations of median EFs for trace elements in Otuk black mudstones reveal both enrichments and depletions. Normalizations to the median composition of the three least-mineralized black mudstones show that barite- and/or pyrite-rich samples display large (>50%) positive changes for Li (+80.4%), V (+75.6%), Sr (+75.9%), Ba (+790%), Cu (+92.1%), Ni (+169%), Ag (+156%), Au (+3091%), As (+109%), Sb (+476%), and Se (+205%); Zn shows a moderate positive change of +42.1%. Moderate negative changes are evident only for Ge (−47.2%) and W (−30.6%). The local enrichments may reflect one or more factors including redox variations in bottom waters and pore fluids, element mobility during diagenesis, and selective fractionation into minerals such as barite, pyrite, and wurtzite. Anomalously low U/Al and UEF values, compared to those for other modern and ancient organic-rich sediments and sedimentary rocks, are attributed to increased solubility and loss of U during bioturbation-related oxygenation in the subsurface.
Physicochemical constraints on barite, pyrite, and wurtzite formation are informed by use of a pH-fO2 plot constructed at 10 °C. Based on paragenetic evidence for multistage deposition of these three minerals, together with the presence of illite intergrown with ZnS and K-feldspar with barite, proposed diagenetic trends involve an increase in pH and fO2 related to the ingress of sulfate-rich pore fluids during bioturbation, followed by a return to lower then higher pH and fO2 conditions linked to carbon, sulfur, barium, and iron cycling during diagenesis. Labile Ba of marine pelagic origin was mobilized from organic-rich sediment upward to the sulfate-methane transition zone where barite precipitated during the interaction of reduced Ba- and CH4-rich fluids with sulfate-bearing pore fluids. The formation of paragenetically early wurtzite (ZnS) crystals, as well as locally high EF values for Cu, Ni, Ag, and Au, is attributed to metal enrichment of pore fluids, with sources being derived in part from water-column deposition from hydrothermal plumes related to coeval Triassic seafloor vent systems including a volcanogenic massive sulfide deposit in British Columbia and the Wrangellia Large Igneous Province in Alaska.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2021.120568","usgsCitation":"Slack, J.F., McAleer, R.J., Shanks, W., and Dumoulin, J.A., 2021, Diagenetic barite-pyrite-wurtzite formation and redox signatures in Triassic mudstone, Brooks Range, northern Alaska: Chemical Geology, v. 585, 120568, 22 p., https://doi.org/10.1016/j.chemgeo.2021.120568.","productDescription":"120568, 22 p.","ipdsId":"IP-130237","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":450344,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2021.120568","text":"Publisher Index Page"},{"id":418739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.604267717169,\n 71.70733094087223\n ],\n [\n -168.604267717169,\n 67.12370451837805\n ],\n [\n -140.49132965188403,\n 67.12370451837805\n ],\n [\n -140.49132965188403,\n 71.70733094087223\n ],\n [\n -168.604267717169,\n 71.70733094087223\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"585","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":877040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":877041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanks, Wayne (Pat)","contributorId":240838,"corporation":false,"usgs":true,"family":"Shanks","given":"Wayne (Pat)","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":877042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":877043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225619,"text":"70225619 - 2021 - Effects of sea ice decline and summer land use on polar bear home range size in the Beaufort Sea","interactions":[],"lastModifiedDate":"2021-10-28T13:48:10.388947","indexId":"70225619","displayToPublicDate":"2021-10-26T08:47:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Effects of sea ice decline and summer land use on polar bear home range size in the Beaufort Sea","docAbstract":"Animals responding to habitat loss and fragmentation may increase their home ranges to offset declines in localized resources or they may decrease their home ranges and switch to alternative resources. In many regions of the Arctic, polar bears (Ursus maritimus) exhibit some of the largest home ranges of any quadrupedal mammal. Polar bears are presently experiencing a rapid decline in Arctic sea ice extent and a change in sea ice composition. For the Southern Beaufort Sea subpopulation of polar bears, this has resulted in a divergent movement pattern where most of the subpopulation remains on the sea ice in the summer melt season while the remainder move to land. We evaluated the effects of summer land use and maternal denning on the annual and seasonal utilization distribution size (i.e., home range) of adult female polar bears in the Southern Beaufort Sea subpopulation over 30 yr (1986–2016) during a period of rapid sea ice decline. For bears that remained on the summer sea ice, model-derived mean annual utilization distributions were 64% larger in 1999–2016 (
In the southwestern United States, non-native grass invasions have increased wildfire occurrence in deserts and the likelihood of fire spread to and from other biomes with disparate fire regimes. The elevational transition between desertscrub and montane grasslands, woodlands, and forests generally occurs at ∼1,200 masl and has experienced fast suburbanization and an expanding wildland-urban interface (WUI). In summer 2020, the Bighorn Fire in the Santa Catalina Mountains burned 486 km2 and prompted alerts and evacuations along a 40-km stretch of WUI below 1,200 masl on the outskirts of Tucson, Arizona, a metropolitan area of >1M people. To better understand the changing nature of the WUI here and elsewhere in the region, we took a multidimensional and timely approach to assess fire dynamics along the Desertscrub-Semi-desert Grassland ecotone in the Catalina foothills, which is in various stages of non-native grass invasion. The Bighorn Fire was principally a forest fire driven by a long-history of fire suppression, accumulation of fine fuels following a wet winter and spring, and two decades of hotter droughts, culminating in the hottest and second driest summer in the 125-yr Tucson weather record. Saguaro (Carnegia gigantea), a giant columnar cactus, experienced high mortality. Resprouting by several desert shrub species may confer some post-fire resiliency in desertscrub. Buffelgrass and other non-native species played a minor role in carrying the fire due to the patchiness of infestation at the upper edge of the Desertscrub biome. Coupled state-and-transition fire-spread simulation models suggest a marked increase in both burned area and fire frequency if buffelgrass patches continue to expand and coalesce at the Desertscrub/Semi-desert Grassland interface. A survey of area residents six months after the fire showed awareness of buffelgrass was significantly higher among residents that were evacuated or lost recreation access, with higher awareness of fire risk, saguaro loss and declining property values, in that order. Sustained and timely efforts to document and assess fast-evolving fire connectivity due to grass invasions, and social awareness and perceptions, are needed to understand and motivate mitigation of an increasingly fire-prone future in the region.
In active volcanic regions, high-temperature chemical reactions in the hydrothermal system consume CO2 sourced from magma or from the deep crust, whereas reactions with silicates at shallow depths mainly consume atmospheric CO2. Numerous studies have quantified the load of dissolved solids in rivers that drain volcanic regions to determine chemical weathering rates and atmospheric CO2 consumption rates. However, the balance between thermal and non-thermal components to riverine fluxes in these areas remains poorly constrained, hindering accurate estimates of atmospheric CO2 consumption rates. Here we use the Ge/Si ratio and the stable silicon isotopes (δ30Si) as tracers for quantifying non-thermal silicon contributions in rivers draining the Yellowstone Plateau Volcanic Field, USA. The Ge/Si ratio (µmol.mol−1) was determined for seven thermal water samples (183 ± 22), eight rivers (35 ± 23) and six creeks flowing into Yellowstone Lake (5 ± 3) during base flow and during peak water discharge following snowmelt. The δ30Si value (‰) was determined for thermal waters (−0.09 ± 0.04), Yellowstone River at Yellowstone Lake outlet (1.91 ± 0.23) and creek samples (0.82 ± 0.29). The calculated atmospheric CO2 consumption associated with non-thermal waters flowing through Yellowstone's rivers during peak discharge is ∼3.03 ton.km−2.yr−1, which is ∼2% of the annual mean atmospheric CO2 consumption in other volcanic regions. This study highlights the significance of quantifying seasonal variations in chemical weathering rates for improving estimates of atmospheric CO2 consumption rates in active volcanic regions.
The U.S. Geological Survey, in cooperation with the Alabama Department of Transportation, evaluated the role of culvert construction in altering streams and habitats of benthic macroinvertebrate communities at selected study sites in the northern East Gulf Coastal Plain of Alabama during 2011–19. Analysis included examinations of changes in stream channel geometry, suspended sediment, turbidity, and benthic macroinvertebrate communities.
Topographic surveys of stream channel cross sections, upstream and downstream of the culvert, were conducted before and after construction. Changes in channel geometry (cross-sectional area, top width, mean depth, and thalweg slope) were assessed by using paired sample t-tests to compare before- and after-construction channel geometry measurements. Statistically significant changes in stream channel geometry between the before- and after-construction measurements were observed at four of the six study sites. Analysis of the channel geometry data indicates that 1 site had no measured changes, and thalweg reach slopes were inverted at 4 of the 12 study reaches—2 measured in before-construction reaches and 2 measured in after-construction reaches.
Surface-water samples were collected during selected storm events for suspended sediment and turbidity analyses. Samples were simultaneously collected upstream and downstream of the culvert construction reaches during all three phases of construction (before, during, and after). Analysis focused on the parity of upstream to downstream simultaneous samples. The mean upstream to downstream paired ratios of sediment concentrations and turbidity from the after-construction phase indicate that colloidal and noncolloidal sediments were passing through the construction reaches at two of the six sites, noncolloidal sediments were being trapped in the construction reaches at two sites, and colloidal and noncolloidal sediments were being removed from the construction reach at two sites.
Benthic macroinvertebrates were collected and identified at five of the six sites from instream habitats that were available in sampled areas both upstream and downstream of the culvert construction reaches. Differences between upstream and downstream reaches and the Wilcoxon rank sum statistic were used to examine changes in metrics of benthic macroinvertebrate communities between before- and after-construction phases. Benthic macroinvertebrate sampling results did not indicate that culvert construction caused impairment to communities at study sites. No tolerance metrics suggested a major change in the pollution tolerance of the communities. The same upstream to downstream patterns in abundance-weighted tolerance values were observed in the before- and after-construction periods at each site. At one site, the difference between upstream and downstream richness-based tolerance values increased, but the after-construction upstream and downstream richness-based tolerance values were lower (indicating a less pollution-tolerant macroinvertebrate community) than in the before-construction period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215096","collaboration":"Prepared in cooperation with the Alabama Department of Transportation","usgsCitation":"Pugh, A.L., and Gill, A.C., 2021, Effects of culvert construction on streams and macroinvertebrate communities at selected sites in the East Gulf Coastal Plain of Alabama, 2010–19: U.S. Geological Survey Scientific Investigations Report 2021–5096, 52 p., https://doi.org/10.3133/sir20215096.","productDescription":"Report: vii, 52 p.; Data Release; Dataset","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-097029","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":390797,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P906BOVO","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Aerial imagery, benthic macroinvertebrate, topographic survey, and soil survey datasets collected for a study of effects of culverts on the natural conditions of streams in the East Gulf Coastal Plain of Alabama, 2010–2019"},{"id":390796,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5096/sir20215096.pdf","text":"Report","size":"15.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5096"},{"id":390795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5096/coverthb.jpg"},{"id":390798,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Alabama","otherGeospatial":"East Gulf Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.08837890625,\n 34.69646117272349\n ],\n [\n -88.165283203125,\n 34.69646117272349\n ],\n [\n -88.505859375,\n 31.98012335736804\n ],\n [\n -88.363037109375,\n 30.315987718557867\n ],\n [\n -88.121337890625,\n 30.268556249047727\n ],\n [\n -87.747802734375,\n 30.173624550358536\n ],\n [\n -87.418212890625,\n 30.35391637229704\n ],\n [\n -87.264404296875,\n 30.477082932837682\n ],\n [\n -87.4072265625,\n 30.581179257386985\n ],\n [\n -87.451171875,\n 30.741835717889792\n ],\n [\n -87.593994140625,\n 30.86451022625836\n ],\n [\n -87.5390625,\n 31.005862904624205\n ],\n [\n -84.979248046875,\n 30.996445897426373\n ],\n [\n -85.067138671875,\n 31.175209828310845\n ],\n [\n -85.045166015625,\n 31.306715155075167\n ],\n [\n -85.067138671875,\n 31.456782472114313\n ],\n [\n -85.078125,\n 31.71882222408327\n ],\n [\n -85.0341796875,\n 31.970803930433096\n ],\n [\n -84.88037109375,\n 32.25926542645933\n ],\n [\n -84.9462890625,\n 32.35212281198644\n ],\n [\n -85.045166015625,\n 32.46342595776104\n ],\n [\n -85.23193359375,\n 32.48196313217176\n ],\n [\n -85.6494140625,\n 32.54681317351514\n ],\n [\n -86.044921875,\n 32.57459172113418\n ],\n [\n -86.693115234375,\n 32.648625783736726\n ],\n [\n -87.132568359375,\n 32.685619853722\n ],\n [\n -87.4951171875,\n 32.85190345738802\n ],\n [\n -87.73681640625,\n 33.109948297894285\n ],\n [\n -87.82470703125,\n 33.53223722395908\n ],\n [\n -87.91259765625,\n 34.10725639663118\n ],\n [\n -87.95654296875,\n 34.379712580462204\n ],\n [\n -88.08837890625,\n 34.69646117272349\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
The key to Grasshopper Sparrow (Ammodramus savannarum) management is providing large areas of contiguous grassland of intermediate height with moderately deep litter and low shrub density. Grasshopper Sparrows have been reported to use habitats with 8–166 centimeters (cm) average vegetation height, 4–80 cm visual obstruction reading, 12–95 percent grass cover, 4–40 percent forb cover, less than 35 percent shrub cover, less than or equal to (≤) 38 percent bare ground, 5–61 percent litter cover, and ≤9 cm litter depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842GG","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Nenneman, M.P., Wooten, T.L., and Euliss, B.R., 2021, The effects of management practices on grassland birds—Grasshopper Sparrow (Ammodramus savannarum) (ver. 1.1, May 2023), chap. GG of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 59 p., https://doi.org/10.3133/pp1842GG.","productDescription":"v, 59 p.","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-097131","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":416617,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/1842/gg/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":390671,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/gg/pp1842gg.pdf","text":"Report","size":"2.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–GG"},{"id":390670,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/gg/coverthb2.jpg"}],"edition":"Version 1.0: October 25, 2021; Version 1.1: May 2, 2023","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Lahars are one of the greatest hazards at many volcanoes, including Volcán de Fuego (Guatemala). On 1 December 2018 at 8:00pm local Guatemala time (2:00:00 UTC), an hour-long lahar event was detected at Volcán de Fuego by two permanent seismo-acoustic stations along the Las Lajas channel on the southeast side. To establish the timing, duration, and speed of the lahar, infrasound array records were examined to identify both the source direction(s) and the correlated energy fluctuations at the two stations. Co-located seismic and acoustic signals were also examined, which indicated at least 5 distinct energy pulses within the lahar record. We infer that varying sediment load and/or changes in flow velocity is shown by clear fluctuations in the acoustic and seismic power recorded at one of the stations. This particular event studied with infrasound provides insight into how lahars occur around Volcán de Fuego.
","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol.04.02.239256","usgsCitation":"Bosa, A., Johnson, J., DeAngelis, S., Lyons, J.J., Roca, A., Anderson, J., and Pineda, A., 2021, Tracking secondary lahar flow paths and characterizing pulses and surges using infrasound array networks at Volcán de Fuego, Guatemala: Volcanica, v. 4, no. 2, p. 239-256, https://doi.org/10.30909/vol.04.02.239256.","productDescription":"18 p.","startPage":"239","endPage":"256","ipdsId":"IP-130024","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":390965,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":450356,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol.04.02.239256","text":"Publisher Index Page"}],"country":"Guatemala","otherGeospatial":"Volcán de Fuego","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.94242095947266,\n 14.396773712446521\n ],\n [\n -90.81298828125,\n 14.396773712446521\n ],\n [\n -90.81298828125,\n 14.500170089974075\n ],\n [\n -90.94242095947266,\n 14.500170089974075\n ],\n [\n -90.94242095947266,\n 14.396773712446521\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Bosa, Ashley 0000-0002-6981-0306","orcid":"https://orcid.org/0000-0002-6981-0306","contributorId":268013,"corporation":false,"usgs":false,"family":"Bosa","given":"Ashley","email":"","affiliations":[],"preferred":false,"id":825725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Jeffery","contributorId":268014,"corporation":false,"usgs":false,"family":"Johnson","given":"Jeffery","email":"","affiliations":[],"preferred":false,"id":825726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Silvio","contributorId":268015,"corporation":false,"usgs":false,"family":"DeAngelis","given":"Silvio","affiliations":[],"preferred":false,"id":825727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":825728,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roca, Amilcar","contributorId":268016,"corporation":false,"usgs":false,"family":"Roca","given":"Amilcar","email":"","affiliations":[],"preferred":false,"id":825729,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Jacob F. 0000-0001-6447-6778","orcid":"https://orcid.org/0000-0001-6447-6778","contributorId":268017,"corporation":false,"usgs":false,"family":"Anderson","given":"Jacob F.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":825730,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pineda, Armando","contributorId":268018,"corporation":false,"usgs":false,"family":"Pineda","given":"Armando","email":"","affiliations":[],"preferred":false,"id":825731,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}