Inter-individual differences in demographic traits of iteroparous species can arise through learning and maturation, as well as from permanent differences in individual ‘quality’ and sex-specific constraints. As the ability to acquire energy determines the resources an individual can allocate to reproduction and self-maintenance, foraging behavior is a key trait to study to better understand the mechanisms underlying these differences. So far, most seabird studies have focused on the effect of maturation and learning processes on foraging performance, while only a few have included measures of individual quality. Here, we investigated the effects of age, breeding experience, sex, and individual breeding quality on the foraging behavior and location of 83 known-age Adélie penguins at Cape Bird, Ross Sea, Antarctica. Over a 2 yr period, we showed that (1) high-quality birds dived deeper than lower quality ones, apparently catching a higher number of prey per dive and targeting different foraging locations; (2) females performed longer foraging trips and a higher number of dives compared to males; (3) there were no significant age-related differences in foraging behavior; and (4) breeding experience had a weak influence on foraging behavior. We suggest that high-quality individuals have higher physiological ability, enabling them to dive deeper and forage more effectively. Further inquiry should focus on determining the physiological differences among penguins of different quality.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps13208","usgsCitation":"Lescroël, A., Lyver, P., Jongsomjit, D., Veloz, S., Dugger, K., Kappes, P., Karl, B., Whitehead, A., Pech, R., Cole, T.L., and Ballard, G., 2020, Inter-individual differences in the foraging behavior of breeding Adélie penguins are driven by individual quality and sex: MEPS, v. 636, p. 189-205, https://doi.org/10.3354/meps13208.","productDescription":"17 p.","startPage":"189","endPage":"205","ipdsId":"IP-112127","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"636","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lescroël, Amelie","contributorId":276366,"corporation":false,"usgs":false,"family":"Lescroël","given":"Amelie","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyver, Phil O’B.","contributorId":276368,"corporation":false,"usgs":false,"family":"Lyver","given":"Phil O’B.","affiliations":[{"id":12679,"text":"Landcare Research","active":true,"usgs":false}],"preferred":false,"id":834797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jongsomjit, Dennis","contributorId":276370,"corporation":false,"usgs":false,"family":"Jongsomjit","given":"Dennis","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veloz, Sam","contributorId":276372,"corporation":false,"usgs":false,"family":"Veloz","given":"Sam","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kappes, Peter","contributorId":276374,"corporation":false,"usgs":false,"family":"Kappes","given":"Peter","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":834800,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karl, Brian J.","contributorId":276377,"corporation":false,"usgs":false,"family":"Karl","given":"Brian J.","affiliations":[{"id":12679,"text":"Landcare Research","active":true,"usgs":false}],"preferred":false,"id":834801,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Whitehead, Amy L.","contributorId":276379,"corporation":false,"usgs":false,"family":"Whitehead","given":"Amy L.","affiliations":[{"id":25457,"text":"NIWA","active":true,"usgs":false}],"preferred":false,"id":834802,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pech, Roger","contributorId":276381,"corporation":false,"usgs":false,"family":"Pech","given":"Roger","email":"","affiliations":[{"id":12679,"text":"Landcare Research","active":true,"usgs":false}],"preferred":false,"id":834803,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cole, Theresa L.","contributorId":276383,"corporation":false,"usgs":false,"family":"Cole","given":"Theresa","email":"","middleInitial":"L.","affiliations":[{"id":12679,"text":"Landcare Research","active":true,"usgs":false}],"preferred":false,"id":834804,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ballard, Grant","contributorId":276385,"corporation":false,"usgs":false,"family":"Ballard","given":"Grant","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834805,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70220285,"text":"70220285 - 2020 - The next frontier: Making research more reproducible","interactions":[],"lastModifiedDate":"2021-04-30T12:21:02.781787","indexId":"70220285","displayToPublicDate":"2020-12-31T07:20:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2501,"text":"Journal of Water Resources Planning and Management","active":true,"publicationSubtype":{"id":10}},"title":"The next frontier: Making research more reproducible","docAbstract":"Science and engineering rest on the concept of reproducibility. An important question for any study is: are the results reproducible? Can the results be recreated independently by other researchers or professionals? Research results need to be independently reproduced and validated before they are accepted as fact or theory. Across numerous fields like psychology, computer systems, and water resources there are problems to reproduce research results (Aarts et al. 2015; Collberg et al. 2014; Hutton et al. 2016; Stagge et al. 2019; Stodden et al. 2018). This editorial examines the challenges to reproduce research results and suggests community practices to overcome these challenges. Coordination is needed among the authors, journals, funders and institutions that produce, publish, and report research. Making research more reproducible will allow researchers, professionals, and students to more quickly understand and apply research in follow-on efforts and advance the field.","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)WR.1943-5452.0001215","usgsCitation":"Rosenberg, D.E., Filion, Y., Teasley, R., Sandoval-Solis, S., Hecht, J.S., van Zyl, J.E., McMahon, G.F., Horsburgh, J., Kasprzyk, J.R., and Tarboton, D.G., 2020, The next frontier: Making research more reproducible: Journal of Water Resources Planning and Management, v. 146, no. 6, 4 p., https://doi.org/10.1061/(ASCE)WR.1943-5452.0001215.","productDescription":"4 p.","ipdsId":"IP-112233","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":454610,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/(asce)wr.1943-5452.0001215","text":"Publisher Index Page"},{"id":385407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"146","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberg, David E. 0000-0003-2163-2907","orcid":"https://orcid.org/0000-0003-2163-2907","contributorId":257767,"corporation":false,"usgs":false,"family":"Rosenberg","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":815003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Filion, Yves","contributorId":257768,"corporation":false,"usgs":false,"family":"Filion","given":"Yves","email":"","affiliations":[{"id":40753,"text":"Queen's University","active":true,"usgs":false}],"preferred":false,"id":815004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teasley, Rebecca","contributorId":257769,"corporation":false,"usgs":false,"family":"Teasley","given":"Rebecca","email":"","affiliations":[{"id":34699,"text":"University of Minnesota-Duluth","active":true,"usgs":false}],"preferred":false,"id":815005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandoval-Solis, Samuel 0000-0003-0329-3243","orcid":"https://orcid.org/0000-0003-0329-3243","contributorId":257770,"corporation":false,"usgs":false,"family":"Sandoval-Solis","given":"Samuel","email":"","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":815006,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hecht, Jory Seth 0000-0002-9485-3332","orcid":"https://orcid.org/0000-0002-9485-3332","contributorId":257771,"corporation":false,"usgs":true,"family":"Hecht","given":"Jory","email":"","middleInitial":"Seth","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":815007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Zyl, Jakobus E.","contributorId":257774,"corporation":false,"usgs":false,"family":"van Zyl","given":"Jakobus","email":"","middleInitial":"E.","affiliations":[{"id":52116,"text":"Univ. of Auckland","active":true,"usgs":false}],"preferred":false,"id":815008,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McMahon, George F.","contributorId":257776,"corporation":false,"usgs":false,"family":"McMahon","given":"George","email":"","middleInitial":"F.","affiliations":[{"id":36715,"text":"Arcadis","active":true,"usgs":false}],"preferred":false,"id":815009,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Horsburgh, J. S. 0000-0002-0768-3196","orcid":"https://orcid.org/0000-0002-0768-3196","contributorId":248851,"corporation":false,"usgs":false,"family":"Horsburgh","given":"J. S.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":815010,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kasprzyk, Joseph R. 0000-0002-6344-6478","orcid":"https://orcid.org/0000-0002-6344-6478","contributorId":257779,"corporation":false,"usgs":false,"family":"Kasprzyk","given":"Joseph","email":"","middleInitial":"R.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":815011,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tarboton, David G. 0000-0002-1998-3479","orcid":"https://orcid.org/0000-0002-1998-3479","contributorId":257780,"corporation":false,"usgs":false,"family":"Tarboton","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":815012,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70217211,"text":"70217211 - 2020 - Multilocus metabarcoding of terrestrial leech bloodmeal iDNA increases species richness uncovered in surveys of vertebrate host biodiversity","interactions":[],"lastModifiedDate":"2021-01-13T13:15:51.987522","indexId":"70217211","displayToPublicDate":"2020-12-31T07:13:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Multilocus metabarcoding of terrestrial leech bloodmeal iDNA increases species richness uncovered in surveys of vertebrate host biodiversity","docAbstract":"Leech-derived invertebrate DNA (iDNA) has been successfully leveraged to conduct surveys of vertebrate host biodiversity across the Indo Pacific. However, this technique has been limited methodologically, typically only targeting mammalian 16S rDNA, or both 16S and vertebrate 12S rDNA for leech host determination. To improve the taxonomic richness of vertebrate host species in iDNA surveys, we re-analyze datasets from Bangladesh, Cambodia, China, and Madagascar through metabarcoding via next generation sequencing (NGS) of 12S, 16S (2 types, one designed to target mammals and the other, residual eDNA), nicotinamide adenine dinucleotide hydride dehydrogenase 2 (ND2), and cytochrome c oxidase subunit 1 (COI). With our 5 primer sets, we identify 41 unique vertebrate hosts to the species level, among 1,200 leeches analyzed, along with an additional 13 taxa to the family rank. Within our 41 taxa, we note that adding ND2 and COI loci increased species richness detection by 25%. NGS has emerged as more efficient than Sanger sequencing for large scale metabarcoding applications and, with the decline in cost of NGS, our pooled sample multilocus protocol is an attractive option for iDNA biodiversity surveys.
No abstract available.
","language":"English","publisher":"Current Science Association","usgsCitation":"Baruah, S., Dey, C., Sastry, G.N., and Michael, A.J., 2020, Global seismology and tectonics: A report on International Virtual Workshop on Global Seismology and Tectonics (IVWGST-2020): Current Science, v. 119, no. 12, p. 1885-1887.","productDescription":"3 p.","startPage":"1885","endPage":"1887","ipdsId":"IP-124277","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":398907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398902,"type":{"id":15,"text":"Index Page"},"url":"https://www.currentscience.ac.in/Volumes/119/12/1885.pdf"}],"volume":"119","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baruah, Santanu","contributorId":290329,"corporation":false,"usgs":false,"family":"Baruah","given":"Santanu","email":"","affiliations":[{"id":62407,"text":"CSIR-North East Institute of Science & Technology, Jorhat, Assa","active":true,"usgs":false}],"preferred":false,"id":840804,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dey, Chandan","contributorId":290330,"corporation":false,"usgs":false,"family":"Dey","given":"Chandan","email":"","affiliations":[{"id":62407,"text":"CSIR-North East Institute of Science & Technology, Jorhat, Assa","active":true,"usgs":false}],"preferred":false,"id":840805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sastry, G. Narahari","contributorId":290331,"corporation":false,"usgs":false,"family":"Sastry","given":"G.","email":"","middleInitial":"Narahari","affiliations":[{"id":62407,"text":"CSIR-North East Institute of Science & Technology, Jorhat, Assa","active":true,"usgs":false}],"preferred":false,"id":840806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":840807,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216911,"text":"sir20205118 - 2020 - Hydrogeology, numerical simulation of groundwater flow, and effects of future water use and drought for reach 1 of the Washita River alluvial aquifer, Roger Mills and Custer Counties, western Oklahoma, 1980–2015","interactions":[],"lastModifiedDate":"2020-12-30T20:18:58.899472","indexId":"sir20205118","displayToPublicDate":"2020-12-30T13:15:00","publicationYear":"2020","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":"2020-5118","displayTitle":"Hydrogeology, Numerical Simulation of Groundwater Flow, and Effects of Future Water Use and Drought for Reach 1 of the Washita River Alluvial Aquifer, Roger Mills and Custer Counties, Western Oklahoma, 1980–2015","title":"Hydrogeology, numerical simulation of groundwater flow, and effects of future water use and drought for reach 1 of the Washita River alluvial aquifer, Roger Mills and Custer Counties, western Oklahoma, 1980–2015","docAbstract":"The Washita River alluvial aquifer is a valley-fill and terrace alluvial aquifer along the valley of the Washita River in western Oklahoma that provides a productive source of groundwater for agricultural irrigation and water supply. The Oklahoma Water Resources Board (OWRB) has designated the westernmost section of the aquifer in Roger Mills and Custer Counties, Okla., as reach 1 of the Washita River alluvial aquifer; reach 1 is the focus of this report. The OWRB issued an order on November 13, 1990, that established the maximum annual yield (MAY; 120,320 acre-feet per year [acre-ft/yr]) and equal-proportionate-share (EPS) pumping rate (2.0 acre-feet per acre per year [(acre-ft/acre)/yr]) for reach 1 of the Washita River alluvial aquifer. The MAY and EPS were based on hydrologic investigations that evaluated the effects of potential groundwater withdrawals on groundwater availability in the Washita River alluvial aquifer. Every 20 years, the OWRB is statutorily required to update the hydrologic investigation on which the MAY and EPS were based. Because 30 years have elapsed since the last order was issued, the U.S. Geological Survey, in cooperation with the OWRB, conducted a new hydrologic investigation and evaluated the effects of potential groundwater withdrawals on groundwater flow and availability in the Washita River alluvial aquifer.
The Washita River is the primary source of inflow to Foss Reservoir, a Bureau of Reclamation reservoir constructed in 1961 for flood control, water supply, and recreation. Foss Reservoir provides water for Bessie, Clinton, New Cordell, and Hobart, Okla. Nearly 98 percent of the total groundwater use from the Washita River alluvial aquifer during 1967 to 2015 was for irrigation; other uses of groundwater in the study area include public supply, mining, and agriculture.
A hydrogeologic framework was developed for the Washita River alluvial aquifer and included the physical characteristics of the aquifer, the geologic setting, the hydraulic properties of hydrogeologic units, the potentiometric surface (water table), and groundwater-flow directions at a scale that captures the regional controls on groundwater flow. The Washita River alluvial aquifer consists of alluvium and terrace deposits that were transported primarily by water and range from clay to gravel in size. The terrace includes windblown deposits of silt size and, in some cases, contains gravel laid down at several levels along former courses of present-day rivers.
A conceptual flow model is a simplified description of the aquifer system that includes hydrologic boundaries, major inflow and outflow sources of the groundwater-flow system, and a conceptual water budget with the estimated mean flows between those hydrologic boundaries. During the study period 1980–2015, mean annual groundwater withdrawals, predominantly used for agricultural irrigation, totaled 5,502 acre-ft/yr, or 14 percent of aquifer outflows. When applied across the 132-square-mile aquifer area used for modeling purposes (84,366 acres), mean annual recharge of 3.15 inches per year corresponds to a mean annual recharge volume of 22,169 acre-ft/yr, or 56 percent of aquifer inflows. The annual saturated-zone evapotranspiration outflow was 11,828 acre-ft/yr for the Washita River alluvial aquifer, or about 30 percent of aquifer outflows. For the Washita River alluvial aquifer, lateral flow was 17,157 acre-ft/yr, or 44 percent of the aquifer inflows. The conceptual flow model and hydrogeologic framework were used to conceptualize, design, and build the numerical groundwater-flow model.
A numerical groundwater-flow model of the Washita River alluvial aquifer was constructed by using MODFLOW-2005. The Washita River alluvial aquifer groundwater-model grid was spatially discretized into 350-foot (ft) cells and two layers. Layer 1 represented the undifferentiated alluvium and terrace deposits of Quaternary age, and layer 2 represented the bedrock of Permian age, which was given a uniform nominal thickness of 100 ft. The groundwater-simulation period was temporally discretized into 433 monthly transient stress periods, representing January 1980 to December 2015. An initial 365-day steady-state stress period was configured to represent mean annual inflows and outflows from the Washita River alluvial aquifer for the study period. The groundwater-flow model was calibrated manually and by automated adjustment of model inputs by using PEST++. Calibration targets for the Washita River alluvial aquifer model included groundwater-level observations and reservoir-stage observations, as well as base-flow and stream-seepage estimates.
Three groundwater-availability scenarios were used in the calibrated groundwater model to (1) estimate the EPS pumping rate that retains the saturated thickness that meets the minimum 20-year life of the aquifer, (2) quantify the effects of projected pumping rates on groundwater storage over a 50-year period, and (3) evaluate how projected pumping rates extended 50 years into the future and sustained hypothetical drought conditions over a 10-year period affect base flow and groundwater in storage. The results of the groundwater-availability scenarios could be used by the OWRB to reevaluate the established MAY of groundwater from the Washita River alluvial aquifer.
EPS scenarios for the Washita River alluvial aquifer were run for periods of 20, 40, and 50 years. The 20-, 40-, and 50-year EPS pumping rates under normal recharge conditions were 1.7, 1.6, and 1.6 (acre-ft/acre)/yr, respectively. Given the aquifer area used for modeling purposes (84,366 acres), these rates correspond to annual yields of 142,579, 134,986, and 134,986 acre-ft/yr, respectively. Groundwater storage at the end of the 20-year EPS scenario was about 281,000 acre-feet (acre-ft), or about 306,000 acre-ft (52 percent) less than the starting storage. Considering the land-surface area of the Washita River alluvial aquifer and using a specific yield of 0.12, this decrease in storage was equivalent to a mean groundwater-level decline of about 30 ft. The Washita River downstream from Foss Reservoir and most of the streams in the study area were dry at the end of the 20-year EPS scenario. Foss Reservoir stage was below the dead-pool stage of 1,597 ft after about 7 years of pumping in the 20-year EPS scenario.
Four projected 50-year groundwater-use scenarios were used to simulate the effects of selected well withdrawal rates on groundwater storage in the Washita River alluvial aquifer. These four scenarios used (1) no groundwater use, (2) groundwater use at the 2015 pumping rate, (3) mean groundwater use for the simulation period, and (4) increasing groundwater use. Groundwater storage after 50 years with no groundwater use was 545,249 acre-ft, or 693 acre-ft (0.1 percent) greater than the initial groundwater storage; this groundwater storage increase is equivalent to a mean groundwater-level increase of 0.1 ft. Groundwater storage at the end of the 50-year period with 2015 pumping rates was 543,831 acre-ft, or 723 acre-ft (0.1 percent) less than the initial storage; this groundwater storage decrease is equivalent to a mean groundwater-level decrease of 0.1 ft. Groundwater storage after 50 years with the mean pumping rate for the study period was 543,202 acre-ft, or 1,349 acre-ft (0.2 percent) less than the initial groundwater storage; this groundwater storage decrease is equivalent to a mean groundwater-level decrease of 0.1 ft. Groundwater storage at the end of the 50-year period with an increasing demand groundwater-pumping rate, which was 38 percent greater than the 2015 groundwater-pumping rate, was 542,584 acre-ft, or 1,967 acre-ft (0.4 percent) less than the initial storage; this groundwater storage decrease is equivalent to a mean groundwater-level decrease of 0.2 ft.
A hypothetical 10-year-drought scenario was used to simulate the effects of a prolonged period of reduced recharge on groundwater storage in the Washita River alluvial aquifer and Foss Reservoir stage and storage. To simulate the hypothetical drought, recharge in the calibrated model was reduced by 50 percent during the simulated drought period (1983–1992). Groundwater storage at the end of the drought period in December 1992 was 562,000 acre-ft, or 36,000 acre-ft (6 percent) less than the groundwater storage of the calibrated groundwater model (598,000 acre-ft). At the end of the hypothetical drought, the largest changes in saturated thickness (as great as 43.5 ft) were in the area upgradient from Foss Reservoir, particularly in the terrace at the model boundary. Substantial decreases in the Foss Reservoir stage began during the fall of 1985 in conjunction with base-flow decreases of up to 100 percent at U.S. Geological Survey streamgage 07324200 Washita River near Hammon, Okla. These lake-stage declines outpaced groundwater-level declines in the surrounding aquifer. The minimum Foss Reservoir storage simulated during the drought period was 77,954 acre-ft, which was a decrease of 46 percent from the nondrought storage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205118","collaboration":"Prepared in cooperation with the Oklahoma Water Resources Board","usgsCitation":"Ellis, J.H., Ryter, D.W., Fuhrig, L.T., Spears, K.W., Mashburn, S.L., and Rogers, I.M.J., 2020, Hydrogeology, numerical simulation of groundwater flow, and effects of future water use and drought for reach 1 of the Washita River alluvial aquifer, Roger Mills and Custer Counties, western Oklahoma, 1980–2015: U.S. Geological Survey Scientific Investigations Report 2020–5118, 81 p., https://doi.org/10.3133/sir20205118.","productDescription":"Report: xi, 81 p.; Data Release","numberOfPages":"98","onlineOnly":"Y","ipdsId":"IP-116035","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":381399,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PKMG6U","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model used in simulation of groundwater flow, and analysis of projected water use for the Washita River alluvial aquifer, western Oklahoma"},{"id":381398,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5118/sir20205118.pdf","text":"Report","size":"18.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5118"},{"id":381397,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5118/coverthb.jpg"}],"country":"United States","state":"Oklahoma","county":"Roger Mills County, Custer County","otherGeospatial":"Washita River alluvial aquifer","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-98.6305,35.812],[-98.6308,35.6387],[-98.6307,35.552],[-98.6199,35.552],[-98.6209,35.4639],[-98.8338,35.4653],[-98.9399,35.4659],[-99.0455,35.4654],[-99.1517,35.4658],[-99.3629,35.4649],[-99.3631,35.508],[-99.5755,35.5085],[-99.576,35.42],[-100.0009,35.4223],[-100.0014,35.4558],[-100.0011,35.6197],[-100.001,35.64],[-100.0015,35.8008],[-100.0015,35.8782],[-99.9742,35.8921],[-99.9566,35.8959],[-99.947,35.9009],[-99.938,35.9037],[-99.9272,35.9074],[-99.9228,35.9115],[-99.9177,35.9175],[-99.9132,35.9234],[-99.911,35.928],[-99.9082,35.9325],[-99.9049,35.9371],[-99.9038,35.9462],[-99.9045,35.9562],[-99.9051,35.9589],[-99.899,35.9698],[-99.894,35.9748],[-99.8522,36.0051],[-99.8398,36.0115],[-99.829,36.0107],[-99.8227,36.0089],[-99.8152,36.0026],[-99.8078,35.9949],[-99.8019,35.9827],[-99.8019,35.9737],[-99.8051,35.9618],[-99.809,35.9518],[-99.8111,35.9364],[-99.8099,35.9287],[-99.8087,35.9246],[-99.8007,35.9174],[-99.7938,35.9102],[-99.788,35.8962],[-99.784,35.8921],[-99.7725,35.8867],[-99.76,35.885],[-99.7521,35.8824],[-99.7372,35.8738],[-99.7258,35.8653],[-99.7189,35.8626],[-99.7149,35.854],[-99.6979,35.855],[-99.6774,35.847],[-99.6615,35.847],[-99.6558,35.8457],[-99.6416,35.8444],[-99.6291,35.84],[-99.6149,35.84],[-99.6042,35.8478],[-99.6002,35.8519],[-99.5929,35.8551],[-99.5855,35.8574],[-99.577,35.8588],[-99.5623,35.8621],[-99.5578,35.8675],[-99.5562,35.8825],[-99.5416,35.903],[-99.532,35.9076],[-99.5241,35.9185],[-99.5156,35.9281],[-99.5067,35.9481],[-99.5061,35.9535],[-99.5085,35.9608],[-99.5085,35.9649],[-99.5045,35.9703],[-99.4995,35.974],[-99.4876,35.9795],[-99.4785,35.9899],[-99.4638,35.9995],[-99.4445,36.01],[-99.4303,36.016],[-99.4144,36.0169],[-99.3928,36.017],[-99.3809,36.017],[-99.3808,35.8991],[-99.374,35.8991],[-99.3736,35.8111],[-99.0571,35.8112],[-98.7366,35.8118],[-98.6305,35.812]]]},\"properties\":{\"name\":\"Custer\",\"state\":\"OK\"}}]}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
Outbursts from impounded water bodies produce large, hazardous, and geomorphically significant floods affecting the Earth as well as other planetary surfaces. Two broad classes of impoundments are: (1) valleys blocked by ice, landslides, constructed dams, and volcanic materials; and (2) closed basins such as tectonic depressions, calderas, meteor craters, and those rimmed by glaciers and moraines. In some environments, floods emanate from subglacial and subterranean sources. Outburst floods are geomorphically important over geologic time because large flows achieve exceptional shear stress and stream power values, thus forming some of the most spectacular landscapes in the solar system.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference Module in Earth Systems and Environmental Sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-818234-5.00007-9","usgsCitation":"O'Connor, J., Clague, J.J., Walder, J.S., Manville, V., and Beebee, R.A., 2020, Outburst floods, chap. of Reference Module in Earth Systems and Environmental Sciences, HTML Document, https://doi.org/10.1016/B978-0-12-818234-5.00007-9.","productDescription":"HTML Document","ipdsId":"IP-120078","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":382557,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":808096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clague, John J.","contributorId":191448,"corporation":false,"usgs":false,"family":"Clague","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":808097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walder, Joseph S. 0000-0003-3523-2998 jswalder@usgs.gov","orcid":"https://orcid.org/0000-0003-3523-2998","contributorId":247681,"corporation":false,"usgs":true,"family":"Walder","given":"Joseph","email":"jswalder@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manville, Vernon","contributorId":247682,"corporation":false,"usgs":false,"family":"Manville","given":"Vernon","affiliations":[{"id":49608,"text":"University of Leeds, Leeds, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":808099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beebee, Robin A. 0000-0002-2976-7294 rbeebee@usgs.gov","orcid":"https://orcid.org/0000-0002-2976-7294","contributorId":5778,"corporation":false,"usgs":true,"family":"Beebee","given":"Robin","email":"rbeebee@usgs.gov","middleInitial":"A.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":808100,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226833,"text":"70226833 - 2020 - Introduction of the Oriental Weatherfish, Misgurnus anguillicaudatus (Cantor, 1842) in the United States","interactions":[],"lastModifiedDate":"2021-12-15T13:17:33.085282","indexId":"70226833","displayToPublicDate":"2020-12-30T07:16:31","publicationYear":"2020","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"title":"Introduction of the Oriental Weatherfish, Misgurnus anguillicaudatus (Cantor, 1842) in the United States","docAbstract":"Although this fish had been present in the then United States (US) territory of Hawaii since the late 19th century, a growing number of collections in the contiguous US over a century later in the 2000s is noteworthy. The Oriental Weatherfish, also often referred to as the weather loach or dojo, is native to eastern Asia from Siberia to Vietnam thus covering a wide climatic range from subtropical to temperate. Primarily a freshwater species, it is typically found in cool, slow-moving streams with silty or muddy substrates. Individuals can reach 28 cm standard length but usually range from 10-20 cm with females generally larger than males. This species has a very slender body shape with a mottled coloration pattern of brown to green markings and a rounded caudal fin. Surrounding its small inferior mouth are 10 barbels and prey consists of small benthic invertebrates including aquatic insects. It is known to bury itself in the substrate to survive periods of drought as well as breathe air using its intestine as an accessory respiratory organ.\nThe occurrence of this species in Hawaii beginning in the late 1800s was likely due to Asian immigrants bringing it with them as a food source. Misgurnus was later used in the state as a baitfish. The introduction of this species in the contiguous US occurred in 1939 when it was imported into the state of Michigan from Japan for the aquarium trade. The first collection made in open waters was from the Shiawassee River, northwest of Detroit, Michigan in 1958 and are believed to have escaped from a nearby aquaculture breeding facility. Based on the linear extent of captures in the Shiawassee River, the fish had likely been present for years prior to its discovery. By 1985, specimens had also been collected from California, Idaho, Oregon, and Washington. Since then, collections have been made in 15 additional states, mostly in the Atlantic (including Gulf of Mexico) and Great Lakes drainages. Collections from the Mississippi River basin have been limited to the upper Illinois River in Illinois, and the upper Ohio drainage in central Ohio and southwest New York. Overall, M. anguillicaudatus has been collected in the following states (with year of first collection): Hawaii (~1870), Michigan (1958), California (1963), Oregon (1977), Washington (1978), Idaho (1985), Illinois (1987), Florida (1988), Tennessee (1995), New York (2001), Indiana (2002), Louisiana (2005), Maryland (2007), Alabama (2009), North Carolina (2009), New Jersey (2007), Pennsylvania (2017), Ohio (2019), and Virginia (2019). An anecdotal report states that it may also be present in Utah. Misgurnus anguillicaudatus has been reported as established with stable populations in most of the locations of these states although some are small in the reported number of individuals or range extent. Exceptions may be Maryland, Tennessee, and Virginia where only a few specimens have been reported. Three areas in particular appear to be undergoing either substantial range expansions or further introductions. These areas include the upper Illinois River and various waters of both western peninsular Florida and southeastern New York. Because of the limited number of reports yet broad fragmented distribution of M. anguillicaudatus in the US, each population is likely the result of a separate introduction as opposed to dispersal from the earliest collection location. A majority of the collection locations are clustered in or near large metropolitan areas which reflects probable releases by aquarium hobbyists.","largerWorkType":{"id":25,"text":"Newsletter"},"largerWorkTitle":"Invasive and Introduced Species Section Newsletter","largerWorkSubtype":{"id":30,"text":"Newsletter"},"language":"English","publisher":"American Fisheries Society","usgsCitation":"Benson, A.J., 2020, Introduction of the Oriental Weatherfish, Misgurnus anguillicaudatus (Cantor, 1842) in the United States, v. 23, no. 2, p. 5-6.","productDescription":"2 p.","startPage":"5","endPage":"6","ipdsId":"IP-120881","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":392946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":392932,"type":{"id":15,"text":"Index Page"},"url":"https://introducedfish.fisheries.org/wp-content/uploads/2020/11/IISS_Newletter_September2020.pdf"}],"volume":"23","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Amy J. 0000-0002-4517-1466 abenson@usgs.gov","orcid":"https://orcid.org/0000-0002-4517-1466","contributorId":3836,"corporation":false,"usgs":true,"family":"Benson","given":"Amy","email":"abenson@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":828424,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70217046,"text":"ofr20201142 - 2020 - Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska","interactions":[],"lastModifiedDate":"2020-12-30T12:49:16.90443","indexId":"ofr20201142","displayToPublicDate":"2020-12-29T16:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1142","displayTitle":"Changing Storm Conditions in Response to Projected 21st Century Climate Change and the Potential Impact on an Arctic Barrier Island–Lagoon System—A Pilot Study for Arey Island and Lagoon, Eastern Arctic Alaska","title":"Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska","docAbstract":"Arey Lagoon, located in eastern Arctic Alaska, supports a highly productive ecosystem, where soft substrate and coastal wet sedge fringing the shores are feeding grounds and nurseries for a variety of marine fish and waterfowl. The lagoon is partially protected from the direct onslaught of Arctic Ocean waves by a barrier island chain (Arey Island) which in itself provides important habitat for migratory shorebirds and waterfowl. In this work, numerically modeled waves and water levels are computed under the provision of sea-level rise and changing conditions brought about by 21st century climate variability. Model results, supported by observations, are used to assess the stability of the barrier chain and spatiotemporal changes in flood patterns across fringing coastal wet sedge areas. The results aim to support studies that investigate the possibility of new biological succession trajectories and loss or increase of habitat areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201142","collaboration":"Prepared in cooperation with and funded in part by the Arctic Landscape Conservation Cooperation (ALCC)","usgsCitation":"Erikson, L.H., Gibbs, A.E., Richmond, B.M., Storlazzi, C.D., Jones, B.M., and Ohman, K.A., 2020, Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska: U.S. Geological Survey Open-File Report 2020–1142, 68, p., https://doi.org/10.3133/ofr20201142.","productDescription":"Report: x, 68 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-079323","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":381735,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LGYO2Q","text":"USGS data release","linkHelpText":"Modeled 21st century storm surge, waves, and coastal flood hazards and supporting oceanographic and geological field data (2010 and 2011) for Arey and Barter Islands, Alaska and vicinity"},{"id":381739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1142/coverthb.jpg"},{"id":381740,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1142/ofr20201142.pdf","text":"Report","size":"8.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1142"}],"country":"United States","state":"Alaska","otherGeospatial":"Arey Island and Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -144.09805297851562,\n 70.03559723423488\n ],\n [\n -143.6407470703125,\n 70.03559723423488\n ],\n [\n -143.6407470703125,\n 70.13476515043729\n ],\n [\n -144.09805297851562,\n 70.13476515043729\n ],\n [\n -144.09805297851562,\n 70.03559723423488\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Stewart B. McKinney National Wildlife Refuge in Connecticut. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of two marsh management units within the refuge and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $1,190,000, but that further expenditures may yield diminishing return on investment. Management actions in optimal portfolios at total costs less than $1,190,000 included controlling avian predators in both management units, managing stormwater on lands adjacent to one marsh management unit, and removing a tide gate and breaching a dike to improve tidal flow in the other marsh management unit. The management benefits were derived from expected increases in the numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds, and an expected decrease in the use of herbicides to control invasive vegetation. The prototype presented here provides a framework for decision making at the Stewart B. McKinney National Wildlife Refuge that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201139","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Low, L.E. , Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Vagos, K., and Potvin, R., 2020, Optimization of salt marsh management at the Stewart B. McKinney National Wildlife Refuge, Connecticut, through use of structured decision making: U.S. Geological Survey Open-File Report 2020–1139, 28 p., https://doi.org/10.3133/ofr20201139.","productDescription":"vi, 28 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120812","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":381645,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1139/ofr20201139.pdf","text":"Report","size":"2.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1139"},{"id":381644,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1139/coverthb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Stewart B. McKinney National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.17169189453125,\n 41.15022321163024\n ],\n [\n -73.13186645507812,\n 41.13677892209895\n ],\n [\n -73.10028076171875,\n 41.14867208811923\n ],\n [\n -73.15177917480469,\n 41.18537216794189\n ],\n [\n -73.18113327026366,\n 41.17090135180691\n ],\n [\n -73.17169189453125,\n 41.15022321163024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708–4039
Drought, wildfires, and invasive species are among the many challenges practitioners face in achieving restoration goals in drylands. In this article, we highlight relevant restoration research and programs that pursue actionable information and resource management goals for the Intermountain West. In the context of international restoration targets recently set, we speak to dryland restoration challenges and opportunities related to climate change, social perceptions of drylands, and species selection strategies aimed at restoring healthy native plant communities.
We developed a blended (or hybrid) interactive course—Managing for a Changing Climate—that provides a holistic view of climate change. The course results from communication with university students and natural and cultural resource managers as well as the need for educational efforts aimed at the public, legislators, and decision-makers. Content includes the components of the physical climate system, natural climate variability, anthropogenic drivers of climate change, climate models and projections, climate assessments, energy economics, environmental policy, vulnerabilities to climate hazards, impacts of climate change, and decision-making related to climate adaptation and mitigation efforts. To convey most of the content, the course-development team created over 50 short videos (3–10 min each) in partnership with experts from a variety of academic, government, and industry institutions. The blended course has been offered as an upper-division, undergraduate course in the Department of Geography and Environmental Sustainability and School of Meteorology (four times) and College of International Studies (in Italy, once) at the University of Oklahoma with over 100 total students. The course has also been presented online-only at no cost to the participants in four fall semesters with over 1,000 total registrations. Videos created for this course are freely available on the YouTube page of the South Central Climate Adaptation Science Center. This course and its associated materials comprise high-quality, formal climate training and education that can be adapted to other formal and informal education settings beyond the walls of the university.
Environmental DNA (eDNA) can be used for early detection, population estimations, and assessment of potential spread of invasive species, but questions remain about factors that influence eDNA detection results. Efforts are being made to understand how physical, chemical, and biological factors—settling, resuspension, dispersion, eDNA stability/decay—influence eDNA estimations and potentially population abundance. In a series of field and controlled mesocosm experiments, we examined the detection and accumulation of eDNA in sediment and water and the transport of eDNA in a small stream in the Lake Michigan watershed, using the invasive round goby fish (Neogobius melanostomus) as a DNA source. Experiment 1: caged fish (average n = 44) were placed in a stream devoid of round goby; water was collected over 24 hours along 120-m of stream, including a simultaneous sampling event at 7 distances from DNA source; stream monitoring continued for 24 hours after fish were removed. Experiment 2: round goby were placed in laboratory tanks; water and sediment were collected over 14 days and for another 150 days post-fish removal to calculate eDNA shedding and decay rates for water and sediment. For samples from both experiments, DNA was extracted, and qPCR targeted a cytochrome oxidase I gene (COI) fragment specific to round goby. Results indicated that eDNA accumulated and decayed more slowly in sediment than water. In the stream, DNA shedding was markedly lower than calculated in the laboratory, but models indicate eDNA could potentially travel long distances (up to 50 km) under certain circumstances. Collectively, these findings show that the interactive effects of ambient conditions (e.g., eDNA stability and decay, hydrology, settling-resuspension) are important to consider when developing comprehensive models. Results of this study can help resource managers target representative sites downstream of potential invasion sites, thereby maximizing resource use.
","language":"English","publisher":"Public Library of Science (PLoS)","doi":"10.1371/journal.pone.0244086","usgsCitation":"Nevers, M., Przybyla-Kelly, K., Shively, D., Morris, C.C., Dickey, J., and Byappanahalli, M., 2020, Influence of sediment and stream transport on detecting a source of environmental DNA: PLoS ONE, v. 15, no. 12, e0244086, 21 p., https://doi.org/10.1371/journal.pone.0244086.","productDescription":"e0244086, 21 p.","ipdsId":"IP-120509","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":454617,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0244086","text":"Publisher Index Page"},{"id":436691,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HI425V","text":"USGS data release","linkHelpText":"Environmental DNA detection and survival, influence of sediment, and stream transport in a Lake Michigan watershed, 2018"},{"id":381935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Przybyla-Kelly, Katarzyna 0000-0001-9168-3545 kprzybyla-kelly@usgs.gov","orcid":"https://orcid.org/0000-0001-9168-3545","contributorId":201534,"corporation":false,"usgs":true,"family":"Przybyla-Kelly","given":"Katarzyna","email":"kprzybyla-kelly@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shively, Dawn A.","contributorId":247309,"corporation":false,"usgs":false,"family":"Shively","given":"Dawn A.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":807646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morris, Charles C.","contributorId":201532,"corporation":false,"usgs":false,"family":"Morris","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":807647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickey, Joshua","contributorId":201536,"corporation":false,"usgs":false,"family":"Dickey","given":"Joshua","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":807648,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807649,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217713,"text":"70217713 - 2020 - Effects of fish populations on Pacific Loon (Gavia pacifica) and Yellow-billed Loon (G. adamsii) lake occupancy and chick production in northern Alaska","interactions":[],"lastModifiedDate":"2021-02-01T14:24:20.683608","indexId":"70217713","displayToPublicDate":"2020-12-27T07:50:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":894,"text":"Arctic","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of fish populations on Pacific Loon (Gavia pacifica) and Yellow-billed Loon (G. adamsii) lake occupancy and chick production in northern Alaska","title":"Effects of fish populations on Pacific Loon (Gavia pacifica) and Yellow-billed Loon (G. adamsii) lake occupancy and chick production in northern Alaska","docAbstract":"Predator populations are vulnerable to changes in prey distribution or availability. With warming temperatures, lake ecosystems in the Arctic are predicted to change in terms of hydrologic flow, water levels, and connectivity with other lakes. We surveyed lakes in northern Alaska to understand how shifts in the distribution or availability of fish may affect the occupancy and breeding success of Pacific (Gavia pacifica) and Yellow-billed Loons (G. adamsii). We then modeled the influence of the presence and abundance of five fish species and the physical characteristics of lakes (e.g., hydrologic connectivity) on loon lake occupancy and chick production. The presence of Alaska blackfish (Dallia pectoralis) had a positive influence on Pacific Loon occupancy and chick production, which suggests that small-bodied fish species provide important prey for loon chicks. No characteristics of fish species abundance affected Yellow-billed Loon lake occupancy. Instead, Yellow-billed Loon occupancy was influenced by the physical characteristics of lakes that contribute to persistent fish populations, such as the size of the lake and the proportion of the lake that remained unfrozen over winter. Neither of these variables, however, influenced chick production. The probability of an unoccupied territory becoming occupied in a subsequent year by Yellow-billed Loons was low, and no loon chicks were successfully raised in territories that were previously unoccupied. In contrast, unoccupied territories had a much higher probability of becoming occupied by Pacific Loons, which suggests that Yellow-billed Loons have strict habitat requirements and suitable breeding lakes may be limited. Territories that were occupied had high probabilities of remaining occupied for both loon species.
With the advent of highly precise total stations and modern surveying instrumentation, trigonometric leveling has become a compelling alternative to conventional leveling methods for establishing vertical-control networks and for perpetuating a datum to field sites. Previous studies of trigonometric-leveling measurement uncertainty proclaim that first-, second-, and third-order accuracies may be achieved if strict leveling protocols are rigorously observed. Common field techniques to obtain quality results include averaging zenith angles and slope distances observed in direct and reverse instrument orientation (F1 and F2, respectively), multiple sets of reciprocal observations, quality meteorological observations to correct for the effects of atmospheric refraction, and electronic distance measurements that generally do not exceed 500 feet. In general, third-order specifications are required for differences between F1 and F2 zenith angles and slope distances; differences between redundant instrument-height measurements; section misclosure determined from reciprocal observations; and closure error for closed traverse. For F1 observations such as backsight check and check shots, the construction-grade specification is required for elevation differences between known and observed values.
Recommended specifications for trigonometric-leveling equipment include a total station instrument with an angular uncertainty specification less than or equal to plus or minus 5 arc-seconds equipped with an integrated electronic distance measurement device with an uncertainty specification of less than or equal to plus or minus 3 millimeters plus 3 parts per million. A paired data collector or integrated microprocessor should have the capability to average multiple sets of measurements in direct and reverse instrument orientation. Redundant and independent measurements by the survey crew and automated or manual reduction of slant heights to the vertical equivalent are recommended to obtain quality instrument heights. Horizontal and vertical collimation tests should be conducted daily during trigonometric-leveling surveys, and electronic distance-measurement instruments should be tested annually on calibrated baselines maintained by the National Geodetic Survey. Specifications that were developed by the National Geodetic Survey for geodetic leveling have been adapted by the U.S. Geological Survey (USGS) for the purpose of developing standards for trigonometric leveling, which are identified as USGS Trigonometric Level I (TL I), USGS Trigonometric Level II (TL II), USGS Trigonometric Level III (TL III), and USGS Trigonometric Level IV (TL IV). TL I, TL II, and TL III surveys have a combination of first, second, and third geodetic leveling specifications that have been modified for plane leveling. The TL III category also has specifications that are adapted from construction-grade standards, which are not recognized by the National Geodetic Survey for geodetic leveling. A TL IV survey represents a leveling approach that does not generally meet criteria of a TL I, TL II, or TL III survey.
Site conditions, such as highly variable topography, and the need for cost-effective, rapid, and accurate data collection in response to coastal or inland flooding have emphasized the need for an alternative approach to conventional leveling methods. Trigonometric leveling and the quality-assurance methods described in this manual will accommodate most site and environmental conditions, but measurement uncertainty is potentially variable and dependent on the survey method. Two types of closed traverse surveys have been identified as reliable methods to establish and perpetuate vertical control: the single-run loop traverse and double-run spur traverse. Leveling measurements for a double-run spur traverse are made in the forward direction from the origin to the destination and are then retraced along the same leveling route in the backward direction, from the destination to the origin. Every control point in a double-run spur traverse is occupied twice. Leveling measurements for a single-run loop traverse are made in the forward direction from the origin point to the destination, and then from the destination to the origin point, along a different leveling route. The only point that is redundantly occupied for the single-run loop traverse is the origin. An open traverse method is also considered an acceptable approach to establish and perpetuate vertical control if the foresight prism height is changed between measurement sets to ensure at least two independent observations. A modified version of leap-frog leveling is recommended for all traverse surveys because it reduces measurement uncertainty by forcing the surveying instrumentation into a level and centered condition over the ground point as the instrumentation is advanced to the objective. Sideshots are considered any radial measurement made from the total station that is not part of a traverse survey. F1 and F2 observations are recommended for sideshots measurements for projects that require precise elevations. Quality-assurance measurements made in F1 from the station to network-control points should be considered for surveys that require a high quantity of sideshots.
The accuracy of a trigonometric-leveling survey essentially depends on four components (1) the skill and experience of the surveyor, (2) the environmental or site conditions, (3) the surveying method, and (4) the quality of the surveying instrumentation. Although components one and two can sometimes be difficult to evaluate and be highly variable, the objective of this manual is to disseminate information needed to identify, maintain, and operate quality land-surveying instrumentation, and to document procedures and best practices for preparing and executing precision trigonometric-leveling surveys in the USGS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm11D3","usgsCitation":"Noll, M.L., and Rydlund, P.H., 2020, Procedures and best practices for trigonometric leveling in the U.S. Geological Survey: U.S. Geological Survey Techniques and Methods, book 11, chap. D3, 94 p., https://doi.org/10.3133/tm11D3.","productDescription":"Report: vii, 93 p.; Appendix","numberOfPages":"94","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-108800","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":381587,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/11d3/coverthb.jpg"},{"id":381588,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/11d3/tm11d3.pdf","text":"Report","size":"6.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 11-D3"},{"id":381589,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/11d3/tm11d3_appendix1.pdf","text":"Appendix 1","size":"207 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Standard Field Form for Running Trigonometric Levels"}],"contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Drought and warming increasingly are causing widespread tree die-offs and extreme wildfires. Forest managers are struggling to improve anticipatory forest management practices given more frequent, extensive, and severe wildfire and tree die-off events triggered by “hotter drought”—drought under warmer than historical conditions. Of even greater concern is the increasing probability of multi-year droughts, or “megadroughts”—persistent droughts that span years to decades, and that under a still-warming climate, will also be hotter than historical norms. Megadroughts under warmer temperatures are disconcerting because of their potential to trigger more severe forest die-off, fire cycles, pathogens, and insect outbreaks. In this Perspective, we identify potential anticipatory and/or concurrent options for non-timber forest management actions under megadrought, which by necessity are focused more at finer spatial scales such as the stand level using higher-intensity management. These management actions build on silvicultural practices focused on growth and yield (but not harvest). Current management options that can be focused at finer scales include key silvicultural practices: selective thinning; use of carefully selected forward-thinking seed mixes; site contouring; vegetation and pest management; soil erosion control; and fire management. For the extreme challenges posed by megadroughts, management will necessarily focus even more on finer-scale, higher-intensity actions for priority locations such as fostering stand refugia; assisted stand recovery via soil amendments; enhanced root development; deep soil water retention; and shallow water impoundments. Drought-induced forest die-off from megadrought likely will lead to fundamental changes in the structure, function, and composition of forest stands and the ecosystem services they provide.
The Northern Goshawk (Accipiter gentilis) is an apex predator occurring across North America and Eurasia. The species has received considerable conservation focus in late-seral conifer forests of western North America, where its habitat has been substantially reduced and altered by timber harvest and is increasingly at risk from high severity fire, drought, and forest pathogens. In the Sierra Nevada range of California, management and conservation of goshawks are hampered by a lack of knowledge of their basic space use and movement ecology. We used global positioning system (GPS) loggers to investigate space use of 20 resident, adult Northern Goshawks over 3 yr (2015–2018) in the Plumas National Forest, California. Median home range sizes of male goshawks were more than twice as large as those of females, and nonbreeding-season home ranges were three times larger than breeding-season home ranges. High resolution GPS data (location interval 1–6 min) allowed quantification of daily transit distances up to 60 km for individual goshawks and revealed long-distance forays into adjacent territories and surrounding areas. Four goshawks (three males, one female) undertook forays >8 km from their nest locations, with forays lasting up to 6 d; these forays occurred during both breeding and nonbreeding seasons for both sexes. Comparing our results to current conservation approaches, we determined that USDA Forest Service goshawk Protected Activity Centers protected <25% of both the roost locations and the area used during the daytime. Conservation efforts for Northern Goshawks in the Sierra Nevada would benefit from consideration of year-round habitat needs at larger scales than previously thought.
Floodplain forest on the upper Mississippi River (UMR), a unique habitat in the Midwest that is important for many bird species, has been reduced and is undergoing continued reduction and changes in structure and species diversity because of river engineering and invasive species. Hydrological changes are causing tree diversity to decline favoring Acer saccharinum (silver maple) and Fraxinus pennsylvanica (green ash). Invasive Phalaris arundinacea (reed canary grass, Phalaris) threatens tree regeneration, and recent Agrilus planipennis (emerald ash borer) arrival threatens to decimate the important ash component of the forest canopy. During the 1990s, virtually no information was available about breeding songbird species and abundances on the UMR floodplain forest from along many river miles and a broad range of forest situations (for example, mainland, island, edge, interior). From 1994 to 1997, we surveyed breeding birds and sampled vegetation at 391 random points on UMR floodplain forest along a latitudinal gradient from Red Wing, Minnesota, to Clinton, Iowa, to characterize bird assemblages and associations with gradients in forest structure at survey points (local scale) and land cover composition within a 200-meter radius of survey points (landscape scale).
Eighty-six bird species were detected during the study, but 28 species comprised 90 percent of all detections. Species that are typically associated with woodland edge or are tolerant of fragmentation were the most common: Setophaga ruticilla (American Redstart), Troglodytes aedon (House Wren), Turdus migratorius (American Robin), Quiscalus quiscula (Common Grackle), and Vireo gilvus (Warbling Vireo). Species typically associated with large forest patches—Setophaga cerulea (Cerulean Warbler), Hylocichla mustelina (Wood Thrush), and Dryocopus pileatus (Pileated Woodpecker)—were rare. Principal components analyses consistently described local habitat gradients related to canopy cover and Phalaris presence and described landscape gradients related to forest area and areas of open land cover types. However, nonmetric multidimensional scaling revealed no pattern in bird assemblages. Canonical correspondence analyses with local habitat variables for each year revealed that bird assemblages were affected by canopy cover, the presence of Phalaris, and the number of tree species. Four bird species were consistently associated with Phalaris presence or negatively with canopy cover, and no species were associated with the number of tree species variable. Although landscape variables were significantly related to the bird assemblage in canonical correspondence analyses, no bird species were consistently related to any landscape variable. These results indicate that there is one assemblage of forest birds on the UMR composed mainly of edge-tolerant species. Species associated with lower canopy cover and Phalaris presence may be favored to increase in abundance as canopy cover opens as trees die and Phalaris becomes more prevalent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205114","usgsCitation":"Kirsch, E.M., 2020, Breeding birds of the upper Mississippi River floodplain forest: One community in a changing forest, 1994 to 1997 (ver. 1.1, February 2021): U.S. Geological Survey Scientific Investigations Report 2020–5114, 22 p., https://doi.org/10.3133/sir20205114.","productDescription":"Report: vi, 22 p.; Data Release; Version History","numberOfPages":"32","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-096746","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":381528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5114/coverthb2.jpg"},{"id":381529,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5114/sir20205114.pdf","text":"Report","size":"4.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5114"},{"id":383313,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2020/5114/versionHist.txt","text":"Version History","size":"667 B","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2020–5114 Version History"},{"id":381530,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z5M7NT","text":"USGS data release","description":"USGS Data Release","linkHelpText":"1990s bird and vegetation data from upper Mississippi River floodplain forest"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Wisconsin","otherGeospatial":"Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.39501953125,\n 44.653024159812\n ],\n [\n -92.548828125,\n 44.59046718130883\n ],\n [\n -92.43896484375,\n 44.32384807250689\n ],\n [\n -92.021484375,\n 44.10336537791152\n ],\n [\n -91.58203125,\n 43.91372326852401\n ],\n [\n -91.40625,\n 43.50075243569041\n ],\n [\n -91.38427734374999,\n 43.02071359427862\n ],\n [\n -91.1865234375,\n 42.633958722673135\n ],\n [\n -90.94482421875,\n 42.32606244456202\n ],\n [\n -90.32958984375,\n 41.918628865183045\n ],\n [\n -90.10986328125,\n 41.918628865183045\n ],\n [\n -89.89013671875,\n 41.95131994679697\n ],\n [\n -89.97802734375,\n 42.261049162113856\n ],\n [\n -90.3955078125,\n 42.601619944327965\n ],\n [\n -90.76904296874999,\n 42.827638636242284\n ],\n [\n -91.03271484375,\n 43.08493742707592\n ],\n [\n -91.16455078125,\n 43.99281450048989\n ],\n [\n -91.7578125,\n 44.35527821160296\n ],\n [\n -92.39501953125,\n 44.653024159812\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 22, 2020; Version 1.1: February 18, 2021","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
The bedrock geology of the 7.5- by 15-minute Springfield quadrangle consists of highly deformed and metamorphosed Mesoproterozoic through Devonian metasedimentary and meta-igneous rocks. In the west, Mesoproterozoic gneisses of the Mount Holly Complex are the oldest rocks and form the eastern side of the Chester dome. The Moretown slice structurally overlies the Chester dome along the Keyes Mountain thrust fault which represents the Ordovician Taconic suture (Red Indian Line) between Laurentian and Ganderian crust. The allochthonous Cambrian through Ordovician Moretown slice includes the Moretown and Cram Hill Formations and the North River Igneous Suite. Silurian and Devonian metasedimentary and metavolcanic rocks of the Connecticut Valley trough (CVT) unconformably overlie the Moretown slice. Ordovician to Silurian and Devonian metasedimentary and meta-igneous rocks of the New Hampshire sequence structurally overlie the CVT along the Devonian, Acadian Monroe thrust fault. The oldest part of the New Hampshire sequence consists of Ordovician metamorphosed volcanic, plutonic, and sedimentary rocks of the Bronson Hill arc including the Ammonoosuc Volcanics, the Partridge Formation, and the Oliverian Plutonic Suite. The Ammonoosuc Volcanics are the base of the exposed arc section in the map area. The Bronson Hill arc rocks are exposed in fault-bounded structural belts, including the Monroe thrust sheet, the Claremont belt, the Sugar River and Unity domes, and the footwall of the Brennan Hill thrust fault. Silurian to Devonian metasedimentary rocks of the Clough Quartzite, and Fitch and Littleton Formations unconformably overlie the Bronson Hill arc rocks. Devonian granitic and pegmatitic dikes and sills of the New Hampshire Plutonic Suite intruded previously deformed rocks.
Devonian, Acadian F1 fold nappes have a sheath fold geometry and are truncated by multiple generations of faults. The Bronson Hill arc structurally overlies the CVT along the Acadian Monroe fault with preserved tectonic mélange in the footwall. Upright dome-stage F2 folds post-date amphibolite facies metamorphism and locally developed into sheath folds in high-strain zones. F3 folds exhibit sinistral rotation associated with Alleghanian lower-greenschist facies faults. Late Paleozoic Alleghanian to Mesozoic shear zones transpose stratigraphy, early structures, and peak metamorphic isograds. 40Ar/39Ar white-mica growth ages (300–250 million years before present [Ma]) indicate that retrograde deformation continued into the latest Paleozoic and earliest Mesozoic. Apatite fission track data show that brittle faults were active prior to about 100 Ma and experienced Late Cretaceous and even Paleocene re-activation.
The bedrock geology was mapped to study the tectonic history of the area and to provide a framework for ongoing characterization of the bedrock of Vermont and New Hampshire. This Scientific Investigations Map of the Springfield 7.5- x 15-minute quadrangle consists of sheets 1 and 2 as well as a geographic information system (GIS) database that includes bedrock geologic units, faults, outcrops, and structural geologic information. Sheet 1 of the report includes a bedrock geologic map, a correlation of map units, and a description of map units. Sheet 2 includes a discussion of the geology, references cited, two cross sections from the geologic map on sheet 1, a tectonic map showing major structural features, and a structural domain map showing the orientation of brittle features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3462","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey; and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Walsh, G.J., Valley, P.M., Armstrong, T.R., Ratcliffe, N.M., Merschat, A.J., and Gentry, B.J., 2020, Bedrock geologic map of the Springfield 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire (ver. 1.1, June 2024): U.S. Geological Survey Scientific Investigations Map 3462, 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3462.","productDescription":"2 Sheets: 62.78 x 40.79 inches and 48.00 x 41.00 inches; Base Map; Metadata; Database; Read Me; Companion File","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091203","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":499273,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_110835.htm","linkFileType":{"id":5,"text":"html"}},{"id":429409,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3462/versionHist.txt","size":"715 B","linkFileType":{"id":2,"text":"txt"}},{"id":381115,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_openaccess.zip","text":"Open Access","size":"5.06 MB","linkFileType":{"id":6,"text":"zip"}},{"id":381114,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_basemap.zip","text":"Base Map","size":"84.1 MB","linkFileType":{"id":6,"text":"zip"}},{"id":381111,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_readme.txt","size":"11.8 KB","linkFileType":{"id":2,"text":"txt"}},{"id":381110,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_sheet2.pdf","text":"Sheet 2","size":"7.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3462"},{"id":381108,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3462/coverthb.jpg"},{"id":381113,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_metadata.zip","size":"445 KB","linkFileType":{"id":6,"text":"zip"}},{"id":381109,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_sheet1.pdf","text":"Sheet 1","size":"23.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3462"},{"id":381112,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3462/sim3462_database.zip","size":"5.38 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New Hampshire, Vermont","county":"Sullivan County, Windsor County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.5,\n 43.25\n ],\n [\n -72.25,\n 43.25\n ],\n [\n -72.25,\n 43.375\n ],\n [\n -72.5,\n 43.375\n ],\n [\n -72.5,\n 43.25\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 22, 2020; Version 1.1: June 4, 2024","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Confined (or buried) aquifers of glacial origin overlain by till confining units provide drinking water to hundreds of thousands of Minnesota residents. The sustainability of these groundwater resources is not well understood because hydraulic properties of till that control vertical groundwater fluxes (leakage) to underlying aquifers are largely unknown. The U.S. Geological Survey, Iowa State University, Minnesota Geological Survey, and Minnesota Department of Health investigated hydraulic properties and groundwater flow through till confining units using field studies and heuristic MODFLOW simulations. Till confining units in the following late-Wisconsinan stratigraphic units (with locations in parentheses) were characterized: Des Moines lobe till of the New Ulm Formation (Litchfield, Minnesota), Superior lobe till of the Cromwell and Aitkin Formations (Cromwell, Minn.), and Wadena lobe till of the Hewitt Formation (hydrogeology field camp [HFC] near Akeley, Minn.). Pre-Illinoian till of the Good Thunder formation (Olivia, Minn.) was also characterized.
Hydraulic and geochemical field data were collected from sediment cores and a series of five piezometer nests. Each nest consisted of five to eight piezometers screened at short vertical intervals in hydrostratigraphic units including (if present) surficial aquifers, till confining units, confined/buried aquifers, and underlying bedrock. Till hydraulic conductivity was estimated from slug tests (horizontal [Kh]) and constant-rate aquifer tests in the confined aquifer (vertical [Kv]). Travel times through the till were evaluated with Darcy’s law and stable isotope concentrations. A series of heuristic MODFLOW simulations were used to evaluate groundwater fluxes through till across the range of till hydraulic properties and pumping rates observed at the field sites.
The field data demonstrated variability in hydraulic properties between and within till stratigraphic units horizontally and vertically. The variability in hydraulic properties within and between sites resulted in substantial differences in groundwater flux through till. A conceptual understanding that emerges from the vertical till profiles is that they are not homogeneous hydrostratigraphic units with uniform properties; rather, each vertical sequence is a heterogeneous mixture of glacial sediment with differing abilities to transmit water.
Till thicknesses varied from 60 to 166 feet, and till textures ranged from a sandy loam (Hewitt Formation, HFC site) to a silt loam/clay loam (Good Thunder formation, Olivia site). Till Kh varied by one to three orders of magnitude within each piezometer nest. Four piezometer nests had downward hydraulic gradients ranging from 0.04 to 0.56, and one nest had a slight upward hydraulic gradient of 0.02. The Cromwell, HFC, and Litchfield 1 sites were examples of “leaky” tills with high Kv (0.001 to 1.1 feet per day [ft/d]) and geometric mean Kh (0.03 to 0.07 ft/d) and extensive vertical hydraulic connectivity between the confined aquifer and the overlying till. Estimated groundwater travel times through these sites ranged from 1 to 81 years, and two of these sites had tritium throughout their till profiles. The tills at the other two sites, Olivia and Litchfield 2, were effective confining units that had low Kv (0.001 to 0.0005 ft/d) and geometric mean Kh (0.0002 to 0.004 ft/d). The till piezometers at these sites had no drawdown response to short-term (up to 10 hours for Olivia and up to 5 days for Litchfield) high-capacity pumping from the confined aquifer. Estimated groundwater travel times through the tills at these sites ranged from 165 to nearly 1,800 years, and tritium was only detected in the upper one-third of these till profiles. Across all sites, the till vertical anisotropy (ratio of Kh to Kv) ranged by four orders of magnitude from 0.05 at the Cromwell nest to 70 at the Litchfield 1 nest. Stable isotopes of oxygen and hydrogen indicate that groundwater throughout all five till profiles is younger than the last glacial advance into Minnesota at about 11,000 years ago.
The heuristic modeling demonstrated that, for understanding sustainability of groundwater pumping from confined aquifers, knowledge of till hydraulic properties is just as important as knowledge of aquifer hydraulic properties. Substantial differences in groundwater fluxes into and through till were observed across hydrogeologic settings representative of the field sites. Over long periods of time (hundreds of years), pumping-induced hydraulic gradients are established in confined aquifer systems and, even in low hydraulic conductivity tills, these pumping-induced hydraulic gradients increase leakage into and through till compared to ambient conditions.
In conclusion, groundwater flowing vertically downward through till confining units (leakage) replenishes water pumped from confined aquifers. Till hydraulic properties, such as those presented in this report, provide important information that can be used to quantify leakage rates through till. Till hydraulic properties are variable over short distances and profoundly affect leakage rates, demonstrating the importance of site-specific till hydraulic data for evaluating the sustainability of groundwater withdrawals from confined aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205127","collaboration":"Prepared in cooperation with the Legislative-Citizen Commission on Minnesota Resources and in collaboration with Iowa State University and the Minnesota Department of Health","usgsCitation":"Trost, J.J., Maher, A., Simpkins, W.W., Witt, A.N., Stark, J.R., Blum, J., and Berg, A.M., 2020, Hydrogeology and groundwater geochemistry of till confining units and confined aquifers in glacial deposits near Litchfield, Cromwell, Akeley, and Olivia, Minnesota, 2014–18: U.S. Geological Survey Scientific Investigations Report 2020–5127, 80 p., https://doi.org/10.3133/sir20205127.","productDescription":"Report: ix, 80 p.; 2 Data Releases; Dataset","numberOfPages":"94","onlineOnly":"Y","ipdsId":"IP-103595","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":381538,"rank":5,"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"},{"id":381534,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5127/coverthb.jpg"},{"id":381535,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5127/sir20205127.pdf","text":"Report","size":"4.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5127"},{"id":381536,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IXC7D3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geochemical data, water-level data, and slug test analysis results from till confining units and confined aquifers in glacial deposits near Akeley, Cromwell, Litchfield, and Olivia, Minnesota, 2015–2018"},{"id":381537,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KOI6T3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Heuristic MODFLOW models used to evaluate the effects of pumping groundwater from confined aquifers overlain by till confining units"}],"country":"United States","state":"Minnesota","city":"Akeley, Cromwell, Litchfield, Olivia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.5758056640625,\n 45.084672408703945\n ],\n [\n -94.48173522949219,\n 45.084672408703945\n ],\n [\n -94.48173522949219,\n 45.16364237397378\n ],\n [\n -94.5758056640625,\n 45.16364237397378\n ],\n [\n -94.5758056640625,\n 45.084672408703945\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.91549682617188,\n 46.65320687122665\n ],\n [\n -92.84614562988281,\n 46.65320687122665\n ],\n [\n -92.84614562988281,\n 46.6965511173143\n ],\n [\n -92.91549682617188,\n 46.6965511173143\n ],\n [\n -92.91549682617188,\n 46.65320687122665\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.74918365478516,\n 46.987044654111116\n ],\n [\n -94.70970153808594,\n 46.987044654111116\n ],\n [\n -94.70970153808594,\n 47.01678007415223\n ],\n [\n -94.74918365478516,\n 47.01678007415223\n ],\n [\n -94.74918365478516,\n 46.987044654111116\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.02418518066406,\n 44.74185630294231\n ],\n [\n -94.95758056640625,\n 44.74185630294231\n ],\n [\n -94.95758056640625,\n 44.79986517347138\n ],\n [\n -95.02418518066406,\n 44.79986517347138\n ],\n [\n -95.02418518066406,\n 44.74185630294231\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
PEST++ Version 5 extends and enhances the functionality of the PEST++ Version 3 software suite, providing environmental modeling practitioners access to updated Version 3 tools as well as new tools to support decision making with environmental models. Version 5 of PEST++ includes tools for global sensitivity analysis (PESTPP-SEN); least-squares parameter estimation with integrated first-order, second-moment parameter and forecast uncertainty estimation (PESTPP-GLM); an iterative, localized ensemble smoother (PESTPP-IES); and a tool for management optimization under uncertainty (PESTPP-OPT). Additionally, all PEST++ Version 5 tools have a built-in fault-tolerant, multithreaded parallel run manager and are model independent, using the same protocol as the widely used PEST software suite.
PEST++ Version 5 is consistent with PEST++ Version 3 conventions and design philosophy. The software’s emphasis continues to target efficient and optimized algorithms that have proven beneficial in decision-support settings and can accommodate large, highly parameterized problems. Expanded and new capabilities are now available to express uncertainty using Monte Carlo and analytical uncertainty approaches and allow evaluation of thousands to millions of parameters. New management optimization capabilities in Version 5 also allow environmental models to be used to answer management questions using multiple societal constraints in a risk-based framework.
The PEST++ Version 5 software suite can be compiled for Microsoft Windows® and Unix-based operating systems such as Apple and Linux®; the source code is available with a Microsoft Visual Studio® 2019 solution; and CMake support for all three operating system is also provided. PEST++ Version 5 continues to build a foundation for an open-source framework capable of producing model-independent, robust, and efficient decision-support tools for large environmental models. The functionality of each of the PEST++ tools are demonstrated on a simple example problem. Implications of decisions used when using the PEST++ suite tools are also discussed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C26","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Great Lakes Restoration Initiative","usgsCitation":"White, J.T., Hunt, R.J., Fienen, M.N., and Doherty, J.E., 2020, Approaches to Highly Parameterized Inversion: PEST++ Version 5, a Software Suite for Parameter Estimation, Uncertainty Analysis, Management Optimization and Sensitivity Analysis: U.S. Geological Survey Techniques and Methods 7C26, 52 p., https://doi.org/10.3133/tm7C26.","productDescription":"Report: viii, 52 p.; Software Release","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-119615","costCenters":[],"links":[{"id":436694,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YTQ5PY","text":"USGS data release","linkHelpText":"PEST++ Version 5.0 source code, pre-compiled binaries and example problem"},{"id":381481,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c26/coverthb.jpg"},{"id":381482,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c26/tm7c26.pdf","text":"Report","size":"2.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 7 C–26"},{"id":381483,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://www.usgs.gov/software/pest-software-suite-parameter-estimation-uncertainty-analysis-management-optimization-and","text":"USGS software release","linkHelpText":"— PEST++, a Software Suite for Parameter Estimation, Uncertainty Analysis, Management Optimization and Sensitivity Analysis"}],"contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
The U.S. Geological Survey (USGS) assessed the potential for undiscovered oil and gas resources of the Yenisey-Khatanga Basin Province as part of the USGS Circum-Arctic Resource Appraisal. The province is situated between the Taimyr-Kara high (Kara block, Central Taimyr fold belt, and South Taimyr fold belt) and the Siberian craton. The two assessment units (AUs) defined for this study—the Khatanga Saddle AU and the Yenisey-Khatanga Basin AU were assessed for undiscovered, technically recoverable, conventional resources. The estimated mean volumes of undiscovered resources for the Yenisey-Khatanga Basin Province are ~5.6 billion barrels of crude oil, ~100 trillion cubic feet of natural gas, and ~2.7 billion barrels of natural-gas liquids, all north of the Arctic Circle.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824R","usgsCitation":"Klett, T.R., and Pitman, J.K., 2018, Geology and assessment of undiscovered oil and gas resources of the Yenisey-Khatanga Basin Province, 2008, chap. R of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 23 p., https://doi.org/10.3133/pp1824R.","productDescription":"Report: vii, 23 p., 2 Appendixes","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-050991","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":381577,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/r/covrthb.jpg"},{"id":381580,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/r/pp1824r_appendix2.xls","text":"Appendix 2","size":"50 KB","linkHelpText":"– Input data for the Yenisey-Khatanga Basin Assessment Unit"},{"id":381579,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/r/pp1824r_appendix1.xls","text":"Appendix 1","size":"50 KB","linkHelpText":"– Input data for the Khatanga Saddle Assessment Unit"},{"id":381578,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/r/pp1824r.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"Russia","otherGeospatial":"Yenisey-Khatanga Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 115.224609375,\n 71.74643171904148\n ],\n [\n 112.32421875,\n 75.02766361549942\n ],\n [\n 109.16015624999999,\n 75.56304125915767\n ],\n [\n 86.748046875,\n 71.46912418989677\n ],\n [\n 78.57421875,\n 70.8446726342528\n ],\n [\n 79.716796875,\n 68.84766505841037\n ],\n [\n 85.69335937499999,\n 67.2720426739952\n ],\n [\n 89.296875,\n 68.87935761076949\n ],\n [\n 95.888671875,\n 68.942606818121\n ],\n [\n 101.953125,\n 70.4367988185464\n ],\n [\n 112.236328125,\n 71.58053179556501\n ],\n [\n 115.224609375,\n 71.74643171904148\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
Hanford, Washington (USA) is the construction site of a multi-billion-dollar high-level nuclear waste treatment facility. This site lies 200 kilometers (km) east of Mount St. Helens (MSH), the most active volcano in the contiguous United States. Tephra from a future MSH eruption could pose a hazard to the air intake and filtration systems at this plant. In this report, we present a probabilistic estimate of the amount of tephra that could fall, and the concentrations of airborne ash that could occur at the Hanford Site during a future eruption. Mount St. Helens has produced four large explosive eruptions in approximately the past 500 years, suggesting that its annual probability of eruption (P1) is roughly 4/500=0.008. Assuming that a large eruption occurs, we calculate the probability (P3|1) of a given fall deposit thickness or airborne concentration at Hanford by running about 10,000 simulations of ash-producing eruptions using the atmospheric transport model Ash3d. In each simulation, we calculate the pattern of tephra dispersal, deposit thickness at Hanford, and airborne ash concentration at ground level. As input for each simulation, we choose meteorological conditions from a randomly chosen time in the historical record between 1980 and 2010, using data from the European Centre for Medium-Range Weather Forecasting (ECMWF) Reanalysis (ERA) Interim model. The volume (dense-rock equivalent) of each simulated eruption is randomly chosen from a uniform probability distribution on a log scale from the range of magma volumes (0.008–2.3 cubic kilometers [km3]) estimated for late Holocene eruptions at MSH. Plume heights and durations of each eruption are chosen using empirical correlations between volume, height, and eruption rate, which account for the fact that larger eruptions have higher plumes and last longer. We construct summary tables of final deposit thickness (T), maximum ground-level airborne concentration (Cmax), and average ground-level airborne concentration (Cavg) during tephra-fall for each run. Each table is sorted and ranked by decreasing value of T, Cmax, or Cavg. Conditional probabilities (P3|1) are derived by dividing rank by n+1, where n is the total number of successful runs. For example, a deposit thickness of 5.10 centimeters (cm) from run 446 is ranked 123 of 9,785 successful runs, yielding P3|1=123/9,786=0.01257. Its annual probability is P=P1·P3|1=0.008×0.01257=0.000101. By interpolation, the deposit thickness (T10k) having an annual probability of 1 in 10,000 (P= 0.0001) is 5.11 cm. Analogous concentration values are Cmax,10k=3,819 and Cavg,10k=1,513 milligrams per cubic meter (mg/m3), respectively. Independent calculations using the known mass accumulation rate of the deposit (=0.001–0.006 kilograms per square meter per second [kg/m2/s]), aggregate fall velocities (u=0.3–0.8 meters per second [m/s]), and the simple formula , yield similar results, although highly variable fall velocities add significant uncertainty. This formula implies that deposit accumulation rates of millimeters (mm) to greater than 1 cm per hour, which are not uncommon during heavy ash fall, are associated with airborne concentrations of 102–103 milligrams per cubic meter (mg/m3). These concentrations are much higher than published measurements (10-3–101 mg/m3), which record only suspended particles sampled in sheltered areas. During heavy ashfall, most fine ash falls as aggregates. Whether such aggregates will be ingested into air ducts will depend on the aggregate size and fall rate, the fragility of the aggregates, the air duct geometry, intake velocity, and other factors.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201133","collaboration":"Prepared in cooperation with the U.S. Department of Energy, Office of River Protection","usgsCitation":"Mastin, L.G., Van Eaton, A., and Schwaiger, H.F., 2020, A probabilistic assessment of tephra-fall hazards at Hanford, Washington, from a future eruption of Mount St. Helens: U.S. Geological Survey Open-File Report 2020–1133, 54 p., https://doi.org/10.3133/ofr20201133.","productDescription":"Report: ix, 54 p.; Data Release","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-112179","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":381546,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1133/covrthb.jpg"},{"id":381547,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1133/ofr20201133.pdf","text":"Report","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381548,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VPFXQR","linkHelpText":"Data Used to Develop A Probabilistic Assessment of Tephra-Fall Hazards at Hanford, Washington"}],"country":"United States","state":"Washington","otherGeospatial":"Hanford","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.88281249999999,\n 46.33175800051563\n ],\n [\n -119.2950439453125,\n 46.33175800051563\n ],\n [\n -119.2950439453125,\n 46.81509864599243\n ],\n [\n -119.88281249999999,\n 46.81509864599243\n ],\n [\n -119.88281249999999,\n 46.33175800051563\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, WA, 98683