Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike
Lawrenceville, NJ 08648
Sedimentary deposits in midlatitude continental basins often preserve a paleoclimate record complementary to marine-based records. However, deriving that paleoclimate record depends on having well-exposed deposits and establishing a sufficiently robust geochronology. After decades of research, we have been able to correlate 77 tephra beds exposed in multiple stratigraphic sections in the Death Valley area, California, United States. These correlations identify 25 different tephra beds that erupted from at least five different volcanic centers from older than 3.58 Ma to ca. 32 ka. We have informally named and determined the ages for seven previously unrecognized beds: ca. 3.54 Ma tuff of Curry canyon, ca. 3.45 Ma tuff of Furnace Creek, ca. 3.1 Ma tuff of Kit Fox Hills, ca. 3.1 Ma tuff of Mesquite Flat, ca. 3.15 Ma tuff of Texas Spring, 3.117 ± 0.011 Ma tuff of Echo Canyon, and the ca. 1.3 Ma Amargosa ash bed. Several of these tephra beds are found as far northeast as central Utah and could be important marker beds in western North America.
Our tephrochronologic data, combined with magnetic polarity data and 40Ar/39Ar age determinations, redefine Neogene sedimentary deposits exposed across 175 km2 of the Death Valley area. The alluvial/lacustrine Furnace Creek Formation is a time-transgressive sedimentary sequence ranging from ca. 6.0 to 2.5 Ma in age. The ca. 2.5–1.7 Ma Funeral Formation is typically exposed as a proximal alluvial-fan facies overlying the Furnace Creek Formation. We have correlated deposits in the Kit Fox Hills, Salt Creek, Nova Basin, and southern Death Valley with the informally named ca. 1.3–0.5 Ma Mormon Point formation. In addition, our correlation of the late Pleistocene Wilson Creek ash bed 15 in the Lake Rogers deposits represents the first unambiguous sequences deposited during the Last Glacial Maximum (marine isotope stage [MIS] 2) in Death Valley.
Based on this new stratigraphic framework, we show that the Pliocene and Pleistocene climate in Death Valley is consistent with the well-established marine tropical/subtropical record. Pluvial lakes in Death Valley and Searles Valley began to form ca. 3.5–3.4 Ma in the late Pliocene during MIS MG5. Initiation of lakes in these two hydrologically separated valleys at the same time at the beginning of a cooling trend in the marine climate record suggests a link to a cooler, wetter (glacial) regional climate in North America. The Death Valley lake persisted until ca. 3.30 Ma, at the peak of the M2 glaciation, after which there is no evidence of Pliocene lacustrine deposition, even at the peak of the Northern Hemisphere Glaciation (ca. 2.75 Ma). If pluvial lakes in the Pliocene are an indirect record of glacial climate conditions, as they are for the Pleistocene, then a glacial climate was present in western North America for ∼200,000 yr during the Pliocene, encompassing MIS MG5–M2.
Pleistocene pluvial lakes in Death Valley that formed ca. 1.98–1.78 Ma, 1.3–1.0 Ma, and ca. 0.6 Ma (MIS 16) are consistent with other regional climate records that indicate a regional glacial climate; however, Death Valley was relatively dry at ca. 0.77 Ma (MIS 19), when large lakes existed in other basins. The limited extent of the MIS 2 marsh/shallow lake in the Lake Rogers basin of northern Death Valley reflects the well-known regional glacial climate at that time; however, Death Valley received relatively lower inflow and rainfall in comparison.
Lake trout stocking began in the 1970s as part of a binational effort to restore a self-sustaining population of lake trout in Lake Ontario. Despite 48 years of restoration stocking, lake trout in Lake Ontario have not reestablished a self-sustaining population. Spawning surveys done at Stony Island Reef (SIR) in eastern Lake Ontario in 1987 and 1989 documented lake trout egg deposition and swim-up fry. Bottom trawls in the early 1990s found naturally-reproduced juvenile lake trout in this region of the lake. More recently, naturally-reproduced juveniles have been found in western Lake Ontario, but few have been found near SIR in the eastern basin. In 2017 and 2018, we examined SIR spawning habitat and lake trout egg deposition rates and compared them to historical values. The average interstitial depth observed in 2018 was less than 4 cm, and the maximum depth observed was 15 cm. These interstitial depths are greatly reduced from depths up to 45 cm reported in the 1980s. Only one egg was captured in 95 egg nets deployed during the spawning period, which resulted in a CPUE of 0.00035 eggs/net/day, markedly lower than the egg densities measured at SIR in 1987 and 1989 of (1.27 eggs/net/day and 0.27 eggs/net/day respectively). Observations of the cobble spawning habitat suggested interstitial spaces were more infilled relative to conditions observed in the 1980s. Infill material was heavily comprised of dreissenid mussels shells and shell fragments. These findings indicate that changes in lake trout spawning habitat may be inhibiting lake trout reproduction at SIR.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"NYSDEC Lake Ontario annual report 2018","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"New York State Department of Environmental Conservation (NYSDEC)","usgsCitation":"Furgal, S., Lantry, B.F., Weidel, B., Farrell, J.M., Gorsky, D., and Biesinger, Z., 2018, Lake trout spawning and habitat assessment at Stony Island Reef, chap. 20 of NYSDEC Lake Ontario annual report 2018, p. 20-1-20-6.","productDescription":"6 p.","startPage":"20-1","endPage":"20-6","ipdsId":"IP-106482","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":369862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369861,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.dec.ny.gov/docs/fish_marine_pdf/lourpt18.pdf"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario, Stony Island Reef","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.3065719604492,\n 43.906055713100805\n ],\n [\n -76.27035140991211,\n 43.906055713100805\n ],\n [\n -76.27035140991211,\n 43.92707729641145\n ],\n [\n -76.3065719604492,\n 43.92707729641145\n ],\n [\n -76.3065719604492,\n 43.906055713100805\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Furgal, Stacy 0000-0001-8828-6290","orcid":"https://orcid.org/0000-0001-8828-6290","contributorId":216791,"corporation":false,"usgs":true,"family":"Furgal","given":"Stacy","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farrell, John M.","contributorId":172505,"corporation":false,"usgs":false,"family":"Farrell","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":27058,"text":"State University of New York, College of Environmental Science and Forestry, Department of Environmental and Forest Biology, 250 Illick Hall, 1 Forestry Drive, Syracuse, NY 13210, USA","active":true,"usgs":false}],"preferred":false,"id":765540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gorsky, Dimitry","contributorId":169691,"corporation":false,"usgs":false,"family":"Gorsky","given":"Dimitry","affiliations":[],"preferred":false,"id":765541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Biesinger, Zy","contributorId":197993,"corporation":false,"usgs":false,"family":"Biesinger","given":"Zy","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":765542,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":97670,"text":"ofr20091103 - 2018 - A practical primer on geostatistics","interactions":[],"lastModifiedDate":"2019-11-25T09:59:18","indexId":"ofr20091103","displayToPublicDate":"2019-11-25T11:05:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-1103","displayTitle":"A Practical Primer on Geostatistics","title":"A practical primer on geostatistics","docAbstract":"The Challenge—Most geological phenomena are extraordinarily complex in their interrelationships and vast in their geographical extension. Ordinarily, engineers and geoscientists are faced with corporate or scientific requirements to properly prepare geological models with measurements involving a small fraction of the entire area or volume of interest. Exact description of a system such as an oil reservoir is neither feasible nor economically possible. The results are necessarily uncertain. Note that the uncertainty is not an intrinsic property of the systems; it is the result of incomplete knowledge by the observer.
The Aim of Geostatistics—The main objective of geostatistics is the characterization of spatial systems that are incompletely known, systems that are common in geology. A key difference from classical statistics is that geostatistics uses the sampling location of every measurement. Unless the measurements show spatial correlation, the application of geostatistics is pointless. Ordinarily the need for additional knowledge goes beyond a few points, which explains the display of results graphically as fishnet plots, block diagrams, and maps.
Geostatistical Methods—Geostatistics is a collection of numerical techniques for the characterization of spatial attributes using primarily two tools: probabilistic models, which are used for spatial data in a manner similar to the way in which time-series analysis characterizes temporal data, or pattern recognition techniques. The probabilistic models are used as a way to handle uncertainty in results away from sampling locations, making a radical departure from alternative approaches like inverse distance estimation methods.
Differences with Time Series—On dealing with time-series analysis, users frequently concentrate their attention on extrapolations for making forecasts. Although users of geostatistics may be interested in extrapolation, the methods work at their best interpolating. This simple difference has significant methodological implications.
Historical Remarks—As a discipline, geostatistics was firmly established in the 1960s by the French engineer Georges Matheron, who was interested in the appraisal of ore reserves in mining. Geostatistics did not develop overnight. Like other disciplines, it has built on previous results, many of which were formulated with different objectives in various fields.
Pioneers—Seminal ideas conceptually related to what today we call geostatistics or spatial statistics are found in the work of several pioneers, including: 1940s: A.N. Kolmogorov in turbulent flow and N. Wiener in stochastic processing; 1950s: D. Krige in mining; 1960s: B. Mathern in forestry and L.S. Gandin in meteorology
Calculations—Serious applications of geostatistics require the use of digital computers. Although for most geostatistical techniques rudimentary implementation from scratch is fairly straightforward, coding programs from scratch is recommended only as part of a practice that may help users to gain a better grasp of the formulations.
Software—For professional work, the reader should employ software packages that have been thoroughly tested to handle any sampling scheme, that run as efficiently as possible, and that offer graphic capabilities for the analysis and display of results. This primer employs primarily the package Stanford Geomodeling Software (SGeMS) - recently developed at the Energy Resources Engineering Department at Stanford University - as a way to show how to obtain results practically. This applied side of the primer should not be interpreted as the notes being a manual for the use of SGeMS. The main objective of the primer is to help the reader gain an understanding of the fundamental concepts and tools in geostatistics.
Organization of the Primer—The chapters of greatest importance are those covering kriging and simulation. All other materials are peripheral and are included for better comprehension of these main geostatistical modeling tools. The choice of kriging versus simulation is often a big puzzle to the uninitiated, let alone the different variants of both of them. Chapters 14, 18, and 19 are intended to shed light on those subjects. The critical aspect of assessing and modeling spatial correlation is covered in chapter 7. Chapters 2 and 3 review relevant concepts in classical statistics.
Course Objectives—This course offers stochastic solutions to common problems in the characterization of complex geological systems. At the end of the course, participants should have: an understanding of the theoretical foundations of geostatistics; a good grasp of its possibilities and limitations; and reasonable familiarity with the SGeMS software, thus opening the possibility of practically applying geostatistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20091103","usgsCitation":"Olea, R., 2018, A practical primer on geostatistics (Version 1.0: Originally posted July 6, 2009; Version 1.1: January 2010; Version 1.2: July 2017, Version 1.3: November 2017; Version 1.4: December 2018): U.S. Geological Survey Open-File Report 2009-1103, ii, 346 p., https://doi.org/10.3133/ofr20091103.","productDescription":"ii, 346 p.","numberOfPages":"348","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":344191,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2009/1103/versionHist_1_4.txt","size":"4.74 KB","linkFileType":{"id":2,"text":"txt"}},{"id":344186,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2009/1103/ofr20091103.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2009-1103"},{"id":125462,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2009/1103/coverthb4.jpg"}],"edition":"Version 1.0: Originally posted July 6, 2009; Version 1.1: January 2010; Version 1.2: July 2017, Version 1.3: November 2017; Version 1.4: December 2018","contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Batrachochytrium salamandrivorans (Bsal), a pathogenic chytrid fungus, is nonnative to the United States and poses a disease threat to vulnerable amphibian hosts. The Bsal fungus may lead to increases in threatened, endangered, and sensitive status listings at State, Tribal, and Federal levels, resulting in financial costs associated with implementing the Endangered Species Act of 1973. The United States is a global biodiversity hotspot for salamanders, an order of amphibians that is particularly vulnerable to developing a disease called chytridiomycosis when exposed to Bsal. Published Bsal risk assessments for North America have suggested that salamanders within the Appalachian region of the United States are at a high risk. In May 2017, a workshop was facilitated by the Department of the Interior’s Strategic Sciences Group. During the workshop, a discussion-based incident-response exercise focused on a hypothetical Bsal disease outbreak in Appalachia was led by U.S. Geological Survey staff members. Participants included representatives of the Eastern Band of the Cherokee Indians, U.S. Fish and Wildlife Service, National Park Service, Appalachian Landscape Conservation Cooperative, Tennessee Wildlife Resources Agency, and U.S. Department of Agriculture’s U.S. Forest Service. Scenario building was used to brainstorm cascading consequences (social, economic, and ecological) of a Bsal disease outbreak in the Appalachian region. This report highlights the management and science actions that could be undertaken to ensure an effective, rapid response to a Bsal introduction into the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181150","usgsCitation":"Hopkins, M.C., Adams, M.J., Super, P.E., Olson, D.H., Hickman, C.R., English, P., Sprague, L., Maska, I.B., Pennaz, A.B., and Ludwig, K.A., 2018, Batrachochytrium salamandriovrans (Bsal) in Appalachia—Using scenario building to proactively prepare for a wildlife disease outbreak caused by an invasive amphibian chytrid fungus: U.S. Geological Survey Open-File Report 2018–1150, 31 p., https://doi.org/10.3133/ofr20181150.","productDescription":"Report: v, 9 p.; Appendixes","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092683","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":359122,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1150/coverthb.jpg"},{"id":359123,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1150/ofr20181150.pdf","text":"Report","size":"7.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2018-1150"}],"contact":"Associate Director, Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive, Suite 300
Reston, VA 20192
The use of water in the United States is arguably one of the most important factors determining water availability at any specific place and time. Numerous local, State, and Federal entities develop, compile, and report water-use data, which can lead to confusing or conflicting information. This report was authored jointly by the U.S. Geological Survey (USGS) and Bureau of Reclamation (Reclamation) to compare and contrast the two agencies’ water-use information programs in the Colorado River Basin. The report also describes the legal drivers for each program, clarifies confusing terminology, compares the methods used, and contrasts the information reported by each agency. This detailed comparison demonstrates that these two Federal agencies have different missions, different programmatic drivers, and different user communities, all of which lead to different approaches to water-use data collection, analysis, and reporting. This report highlights those differences and explains why the USGS and Reclamation programs exist and how the data serve different user communities. Even though the two water-use programs are different by design and purpose, the program comparison presented in this report has identified opportunities for closer coordination and sharing of information between the USGS and Reclamation, as well as program components where agency collaboration can improve water-use estimate methodologies. This comparison effort emphasizes that it is incumbent upon each agency to clearly define the meaning of the terms used and the appropriate application of the reported information to avoid confusion or the accidental misuse of the information. An additional benefit of this comparison effort is the formation of a joint USGS/Reclamation water-use team that will continue to investigate opportunities to expand and coordinate future water-use data compilation and reporting.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185021","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Bruce, B.W., Prairie, J.R., Maupin, M.A., Dodds, J.R., Eckhardt, D.W., Ivahnenko, T.I., Matuska, P.J., Evenson, E.J., and Harrison, A.D., 2018, Comparison of U.S. Geological Survey and Bureau of Reclamation water-use reporting in the Colorado River Basin (ver. 1.1, September 2019): U.S. Geological Survey Scientific Investigations Report 2018–5021, 41 p., https://doi.org/10.3133/sir20185021.\n","productDescription":"vi, 41 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-089692","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":353709,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5021/sir20185021.pdf","text":"Report","size":"10.1 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U.S. Geological Survey
988 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Sediment pulses can cause widespread, complex changes to rivers and coastal regions. Quantifying landscape response to sediment-supply changes is a long-standing problem in geomorphology, but the unanticipated nature of most sediment pulses rarely allows for detailed measurement of associated landscape processes and evolution. The intentional removal of two large dams on the Elwha River (Washington, USA) exposed ~30 Mt of impounded sediment to fluvial erosion, presenting a unique opportunity to quantify source-to-sink river and coastal responses to a massive sediment-source perturbation. Here we evaluate geomorphic evolution during and after the sediment pulse, presenting a 5-year sediment budget and morphodynamic analysis of the Elwha River and its delta. Approximately 65% of the sediment was eroded, of which only ~10% was deposited in the fluvial system. This restored fluvial supply of sand, gravel, and wood substantially changed the channel morphology. The remaining ~90% of the released sediment was transported to the coast, causing ~60 ha of delta growth. Although metrics of geomorphic change did not follow simple time-coherent paths, many signals peaked 1–2 years after the start of dam removal, indicating combined impulse and step-change disturbance responses.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-018-30817-8","usgsCitation":"Ritchie, A.C., Warrick, J.A., East, A.E., Magirl, C.S., Stevens, A.W., Bountry, J.A., Randle, T.J., Curran, C.A., Hilldale, R.C., Duda, J.J., Miller, I.M., Pess, G.R., Eidam, E., Foley, M.M., McCoy, R., and Ogston, A.S., 2018, Morphodynamic evolution following sediment release from the world’s largest dam removal: Scientific Reports, v. 8, 13279, 13 p., https://doi.org/10.1038/s41598-018-30817-8.","productDescription":"13279, 13 p.","ipdsId":"IP-093205","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468150,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stevens, Andrew W. 0000-0003-2334-129X astevens@usgs.gov","orcid":"https://orcid.org/0000-0003-2334-129X","contributorId":139313,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bountry, Jennifer A.","contributorId":30114,"corporation":false,"usgs":false,"family":"Bountry","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":769407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Randle, Timothy J.","contributorId":90994,"corporation":false,"usgs":false,"family":"Randle","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":769408,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hilldale, Robert C.","contributorId":139315,"corporation":false,"usgs":false,"family":"Hilldale","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":769410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":772301,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":769412,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pess, George R.","contributorId":13501,"corporation":false,"usgs":false,"family":"Pess","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":769413,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Eidam, Emily","contributorId":139311,"corporation":false,"usgs":false,"family":"Eidam","given":"Emily","email":"","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":769414,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Foley, Melissa M. 0000-0002-5832-6404 mfoley@usgs.gov","orcid":"https://orcid.org/0000-0002-5832-6404","contributorId":4861,"corporation":false,"usgs":true,"family":"Foley","given":"Melissa","email":"mfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769415,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"McCoy, Randall","contributorId":194430,"corporation":false,"usgs":false,"family":"McCoy","given":"Randall","affiliations":[],"preferred":false,"id":769416,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Ogston, Andrea S.","contributorId":12119,"corporation":false,"usgs":true,"family":"Ogston","given":"Andrea","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":769417,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70205455,"text":"70205455 - 2018 - Thresholds of lake and reservoir connectivity in river networks control nitrogen removal","interactions":[],"lastModifiedDate":"2020-09-01T14:05:16.435219","indexId":"70205455","displayToPublicDate":"2019-07-17T18:32:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds of lake and reservoir connectivity in river networks control nitrogen removal","docAbstract":"Lakes, reservoirs, and other ponded waters are ubiquitous features of the aquatic landscape, yet their cumulative role in nitrogen removal in large river basins is often unclear. Here we use predictive modeling, together with comprehensive river water quality, land use, and hydrography datasets, to examine and explain the influences of more than 18,000 ponded waters on nitrogen removal through river networks of the Northeastern United States. Thresholds in pond density where ponded waters become important features to regional nitrogen removal are identified and shown to vary according to a ponded waters’ relative size, network position, and degree of connectivity to the river network, which suggests worldwide importance of these new metrics. Consideration of the interacting physical and biological factors, along with thresholds in connectivity, reveal where, why, and how much ponded waters function differently than streams in removing nitrogen, what regional water quality outcomes may result, and in what capacity management strategies could most effectively achieve desired nitrogen loading reduction.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-018-05156-x","usgsCitation":"Schmadel, N.M., Harvey, J., Alexander, R., Schwarz, G., Moore, R., Eng, K., Gomez-Velez, J., Boyer, E.W., and Scott, D., 2018, Thresholds of lake and reservoir connectivity in river networks control nitrogen removal: Nature Communications, v. 9, 2779, 10 p., https://doi.org/10.1038/s41467-018-05156-x.","productDescription":"2779, 10 p.","ipdsId":"IP-093046","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468151,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-05156-x","text":"Publisher Index Page"},{"id":367536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, District of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode island, Vermont, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.884765625,\n 44.37098696297173\n ],\n [\n -66.884765625,\n 44.99588261816546\n ],\n [\n -67.67578124999999,\n 45.82879925192134\n ],\n [\n -67.8515625,\n 47.368594345213374\n ],\n [\n -69.2138671875,\n 47.517200697839414\n ],\n [\n -71.19140625,\n 45.398449976304086\n ],\n [\n -71.8505859375,\n 44.99588261816546\n ],\n [\n -74.3994140625,\n 45.182036837015886\n ],\n [\n -76.81640625,\n 42.74701217318067\n ],\n [\n -77.6953125,\n 40.81380923056958\n ],\n [\n -79.40917968749999,\n 39.40224434029275\n ],\n [\n -79.27734374999999,\n 37.50972584293751\n ],\n [\n -78.9697265625,\n 36.914764288955936\n ],\n [\n -75.234375,\n 36.38591277287651\n ],\n [\n -73.125,\n 40.111688665595956\n ],\n [\n -69.2578125,\n 41.11246878918088\n ],\n [\n -66.884765625,\n 44.37098696297173\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmadel, Noah M.","contributorId":219098,"corporation":false,"usgs":false,"family":"Schmadel","given":"Noah","email":"","middleInitial":"M.","affiliations":[{"id":39961,"text":"USGS Post-Doc","active":true,"usgs":false}],"preferred":false,"id":771257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harvey, Judson","contributorId":219097,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":436,"text":"National Research Program - 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Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":771261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gomez-Velez, Jesus D.","contributorId":219103,"corporation":false,"usgs":false,"family":"Gomez-Velez","given":"Jesus D.","affiliations":[{"id":39962,"text":"Department of Earth & Environmental Science, New Mexico Institute of Mining and Technology, Socorro, New Mexico, USA","active":true,"usgs":false}],"preferred":false,"id":771262,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":771263,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scott, Durelle","contributorId":219088,"corporation":false,"usgs":false,"family":"Scott","given":"Durelle","affiliations":[{"id":39959,"text":"Virginia Tech.","active":true,"usgs":false}],"preferred":false,"id":771264,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195984,"text":"tm4B5 - 2018 - Guidelines for determining flood flow frequency — Bulletin 17C","interactions":[{"subject":{"id":70275162,"text":"70275162 - 1982 - Guidelines for determining flood flow frequency: Bulletin #17B of the Hydrology Subcommittee","indexId":"70275162","publicationYear":"1982","noYear":false,"title":"Guidelines for determining flood flow frequency: Bulletin #17B of the Hydrology Subcommittee"},"predicate":"SUPERSEDED_BY","object":{"id":70195984,"text":"tm4B5 - 2018 - Guidelines for determining flood flow frequency — Bulletin 17C","indexId":"tm4B5","publicationYear":"2018","noYear":false,"title":"Guidelines for determining flood flow frequency — Bulletin 17C"},"id":1}],"lastModifiedDate":"2024-03-28T13:15:23.826606","indexId":"tm4B5","displayToPublicDate":"2019-07-16T10:55:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-B5","title":"Guidelines for determining flood flow frequency — Bulletin 17C","docAbstract":"Accurate estimates of flood frequency and magnitude are a key component of any effective nationwide flood risk management and flood damage abatement program. In addition to accuracy, methods for estimating flood risk must be uniformly and consistently applied because management of the Nation’s water and related land resources is a collaborative effort involving multiple actors including most levels of government and the private sector.
Flood frequency guidelines have been published in the United States since 1967, and have undergone periodic revisions. In 1967, the U.S. Water Resources Council presented a coherent approach to flood frequency with Bulletin 15, “A Uniform Technique for Determining Flood Flow Frequencies.” The method it recommended involved fitting the log-Pearson Type III distribution to annual peak flow data by the method of moments.
The first extension and update of Bulletin 15 was published in 1976 as Bulletin 17, “Guidelines for Determining Flood Flow Frequency” (Guidelines). It extended the Bulletin 15 procedures by introducing methods for dealing with outliers, historical flood information, and regional skew. Bulletin 17A was published the following year to clarify the computation of weighted skew. The next revision of the Bulletin, the Bulletin 17B, provided a host of improvements and new techniques designed to address situations that often arise in practice, including better methods for estimating and using regional skew, weighting station and regional skew, detection of outliers, and use of the conditional probability adjustment.
The current version of these Guidelines are presented in this document, denoted Bulletin 17C. It incorporates changes motivated by four of the items listed as “Future Work” in Bulletin 17B and 30 years of post-17B research on flood processes and statistical methods. The updates include: adoption of a generalized representation of flood data that allows for interval and censored data types; a new method, called the Expected Moments Algorithm, which extends the method of moments so that it can accommodate interval data; a generalized approach to identification of low outliers in flood data; and an improved method for computing confidence intervals.
Federal agencies are requested to use these Guidelines in all planning activities involving water and related land resources. State, local, and private organizations are encouraged to use these Guidelines to assure uniformity in the flood frequency estimates that all agencies concerned with flood risk should use for Federal planning decisions.
This revision is adopted with the knowledge and understanding that review of these procedures will be ongoing. Updated methods will be adopted when warranted by experience and by examination and testing of new techniques.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: Surface water in Book 4: Hydrologic analysis and interpretation","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4B5","isbn":"978-1-4113-4223-1","usgsCitation":"England, J.F., Jr., Cohn, T.A., Faber, B.A., Stedinger, J.R., Thomas, W.O., Jr., Veilleux, A.G., Kiang, J.E., and Mason, R.R., Jr., 2018, Guidelines for determining flood flow frequency — Bulletin 17C (ver. 1.1, May 2019): U.S. Geological Survey Techniques and Methods, book 4, chap. B5, 148 p., https://doi.org/10.3133/tm4B5.","productDescription":"xiii, 148 p.","numberOfPages":"168","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065340","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":352936,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://acwi.gov/hydrology/Frequency/b17c/","text":"Advisory Committee on Water Information - Bulletin 17C"},{"id":352416,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/b05/tm4b5.pdf","text":"Report","size":"29.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 4-B5"},{"id":352415,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/b05/coverthb2.jpg"},{"id":399694,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107081.htm"},{"id":363942,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/tm/04/b05/versionHist.pdf","size":"153 KB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.5178,\n 33.9703\n ],\n [\n -83.8928,\n 33.9703\n ],\n [\n -83.8928,\n 34.2625\n ],\n [\n -84.5178,\n 34.2625\n ],\n [\n -84.5178,\n 33.9703\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: May 31, 2019","publicComments":"This report is Chapter 5 of Section B: Surface water in Book 4: Hydrologic analysis and interpretation.","contact":"Chief, Analysis and Prediction Branch
Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Mail Stop 415
Reston, VA 20192
Executive Summary
Drainage for agricultural production over the past 150 years has been an integral component of human-driven change to Minnesota’s rural landscapes.
Benefits of drainage
Historically, poorly drained soils across much of the State would often remain saturated or flooded after spring snowmelt, preventing timely farm operations such as tilling and planting crops (Arneman, 1963). Installation of agricultural drainage, both surface ditches and subsurface drainage, accelerated transport of water off farm fields and imparted producers higher crop yields (Beauchamp, 1987; Stoner and others, 1993). Agricultural drainage offered many other benefits such as preventing crop drown out, aerating the soil profile for improved plant growth, limiting surface runoff and soil erosion, and allowing farmers better access to croplands (Fausey and others, 1987). Without agricultural drainage on much of Minnesota’s croplands, it would have been difficult to realize high enough crop yields to remain economically viable.
Environmental concerns
While drainage of Minnesota croplands provided the benefits mentioned above, several environmental concerns result. These include wetland loss, degradation of downstream water quality, and reduced [potential for] recharge.
Early agricultural drainage efforts (pre-20th century) led to the disappearance of much of Minnesota’s natural wetlands. Increased focus on preventing or mitigating wetland loss over the last 50 years has helped curtail further losses, even as agricultural drainage proceeds. Prior to establishment of Minnesota statehood, wetlands accounted for more than 10 million acres in Minnesota, including prairie wetlands, peatlands, and forest wetlands that comprised approximately 19 percent of the total land area (Palmer, 1915; King, 1980). In 2018, only half of Minnesota’s pre-settlement wetlands remain, mostly in parts of the State that have not experienced widespread drainage, such as northern Minnesota.
Water-quality monitoring has shown that agricultural drainage, in particular the practice of subsurface drainage, provides a direct flow path for nutrient (nitrogen and soluble phosphorus) losses to surface water resources. The negative consequences of agricultural drainage on surface water quality are well documented (for example, Dinnes and others, 2002; Kladivko and others, 2004; Richards and others, 2008; Rozemeijer and others, 2010; Schottler and others, 2013). Agricultural basins with a high percentage of agricultural drainage have been implicated as part of the cause of the Gulf of Mexico hypoxia zone due to excessive nitrogen export (Goolsby and Battaglin, 2001; Randall and Mulla, 2001).
The connection of hydrological effects of agricultural subsurface drainage on groundwater recharge and aquifers, on the other hand, has not been well-established. Agricultural subsurface drainage intercepts infiltrating water below croplands and directly discharges the water to nearby surface waters. However, the size of the water balance shift from drained water that would have evapotranspired or run off the land to drained water that would recharge underlying aquifers has been poorly characterized (Schuh, 2008).
Drain Tiles and Groundwater
Given the poor accounting of subsurface drainage effects on groundwater resources, the Minnesota Ground Water Association (MGWA) deemed it imperative that we document these effects so that groundwater resources in agricultural regions with substantial drainage can be effectively managed. This white paper documents the relations of drain tiles and groundwater resources and discusses the historical significance of agricultural drainage practices, the recognized positive benefits and potential negative consequences of agricultural drainage practices, and the gaps in understanding of the connections between agricultural drainage and groundwater resources.
The major messages emerged from the findings of this white paper are:
In 2015, approximately 8,720 million gallons per day (Mgal/d) of water was withdrawn from groundwater and surface-water sources in Louisiana, a 2.6 percent increase from 2010. Total groundwater withdrawals were about 1,750 Mgal/d, an increase of 12 percent from 2010, and total surface-water withdrawals were about 6,970 Mgal/d, an increase of 0.44 percent from 2010 to 2015.
Total water withdrawals, in Mgal/d, in 2015 for the various categories of use were as follows: public supply—715, industry—2,155, power generation—4,265, rural domestic—39, livestock—6, rice irrigation—825, general irrigation—225, and aquaculture—490. From 2010 to 2015, Louisiana’s total withdrawals for public supply decreased by 3.4 percent, industry increased by 5.7 percent, power generation decreased by 3.9 percent, rural domestic decreased by 4.1 percent, livestock decreased by 21 percent, rice irrigation increased by 20 percent, general irrigation decreased by 6.0 percent, and aquaculture increased by 58 percent.
About 48 percent (approximately 850 Mgal/d) of all groundwater withdrawn was from the Chicot aquifer system and 22 percent (approximately 385 Mgal/d) was withdrawn from the Mississippi River alluvial aquifer. Since 2010, withdrawals from the Chicot aquifer system increased by 30 percent and withdrawals from the Mississippi River alluvial aquifer decreased by 2.9 percent.
About 70 percent (4,905 Mgal/d) of all surface water withdrawn was from the Mississippi River mainstem. This value represents a 1.1-percent decrease in withdrawals from 2010 to 2015.
All water-withdrawal and water-use data presented in this report should be considered estimates. Because of rounding, totals and percentages presented in the tables, figures, and text in the report may differ slightly from totals or percentages calculated individually
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Pierre 0000-0002-3967-9036 psargent@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-9036","contributorId":1228,"corporation":false,"usgs":true,"family":"Sargent","given":"B.","email":"psargent@usgs.gov","middleInitial":"Pierre","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758608,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201558,"text":"sim3402 - 2018 - Surficial materials of Massachusetts—A 1:24,000-scale geologic map database","interactions":[],"lastModifiedDate":"2022-02-03T15:37:52.987287","indexId":"sim3402","displayToPublicDate":"2019-03-01T11:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3402","displayTitle":"Surficial Materials of Massachusetts—A 1:24,000-Scale Geologic Map Database","title":"Surficial materials of Massachusetts—A 1:24,000-scale geologic map database","docAbstract":"The surficial materials geologic map database defines the distribution of nonlithified earth materials at the land surface in the 189 7.5-minute, 1:24,000-scale quadrangles that cover the Commonwealth of Massachusetts (index map). Across the State, these materials range in thickness from a few feet to more than 500 feet (ft). In some places, surficial materials are absent where bedrock is at the land surface. The geologic map database differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. The mapped distribution of surficial materials defines the areas of exposed bedrock and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits at a 1:24,000-scale level of accuracy.
Most of the surficial materials in Massachusetts are deposits of the last two continental ice sheets that covered all of New England in the latter part of the Pleistocene ice age. The glacial deposits are divided into two broad categories, glacial till and moraine deposits, and glacial stratified deposits. Widespread till deposits were laid down directly on bedrock or on semi-consolidated coastal plain strata by glacier ice. Tills in thick-till (>15 ft thick) drumlin landforms are found in all parts of the State. Areas of shallow bedrock contain thin discontinuous till deposits and numerous bedrock outcrops, and are located chiefly in rocky upland areas. Moraine deposits related to glacial ice lobes of the last ice sheet are located mostly in southeastern Massachusetts. Glacial stratified deposits are concentrated in valleys and lowland areas and were laid down by glacial meltwater in streams, lakes, and the sea in front of the retreating ice margin during the last deglaciation. Postglacial deposits, primarily flood-plain alluvium and swamp deposits, make up a lesser proportion of the unconsolidated materials.
The geodatabase included with this report contains MapUnitPolys, MapUnitOverlayPolys, and OverlayPolys, which show the distribution of geologic units that cover the entire map area and are intended for use at quadrangle scale (1:24,000). These data layers can be clipped by quadrangle or by town boundary. Unlike the units in conventional geologic maps, the digitally defined MapUnitOverlayPolys are arranged in order according to superposition. The polygons for till and bedrock are on the bottom and are overlain by the succeeding stratified deposits; these materials are shown everywhere they occur, including beneath postglacial deposits such as swamp deposits, and also beneath water bodies. The postglacial deposits are on top because these materials overlie the other, older deposits. Instructions for using the digital files are included in the README file. A series of map figures in the pamphlet illustrates the stacking of geologic units in a portion of the Mount Toby quadrangle. The BaseMaps folder contains the 1:24,000-scale topographic base map images (1944–1977 editions) used for this compilation.
This report supersedes U.S. Geological Survey Open-File Reports 2006-1260-A, -B, -C, -D, -E, -F, -G, and -I.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3402","collaboration":"Prepared in cooperation with the Commonwealth of Massachusetts, Massachusetts Geological Survey and Executive Office for Administration and Finance","usgsCitation":"Stone, J.R., Stone, B.D., DiGiacomo-Cohen, M.L., and Mabee, S.B., comps., 2018, Surficial materials of Massachusetts—A 1:24,000-scale geologic map database: U.S. Geological Survey Scientific Investigations Map 3402, 189 sheets, scale 1:24,000; index map, scale 1:250,000; 58-p. pamphlet; and geodatabase files, https://doi.org/10.3133/sim3402.","productDescription":"Pamphlet: iv, 58 p.; Index Map; Quandrangle Map Sheets; Metadata; Read Me; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066389","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":361110,"rank":9,"type":{"id":23,"text":"Spatial 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MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- sim3402_simple.zip contains an automatic translation of most of the contents of SIM3402.gdb into simple flat shapefiles, and contains metadata"},{"id":361232,"rank":10,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_open.zip","text":"Geodatabase","size":"311 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- sim3402_open.zip contains a complete, automatic translation of SIM3402.gdb into shapefiles and other files, and contains metadata"},{"id":361577,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_metadata.xml","text":"SIM 3402 - Metadata","size":"29.6 KB xml"},{"id":361200,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_metadata.txt","text":"SIM 3402 - Metadata","size":"35.1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":361199,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_quadranglespdfs.zip","text":"Maps of Quadrangles 1–189","size":"3.12 GB","linkFileType":{"id":6,"text":"zip"}},{"id":361334,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_quadrangle","text":"Individual Quadrangle Map Sheets","size":"938 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":361201,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_index_map.pdf","text":"Index Map","size":"25.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":361100,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3402/sim3402.pdf","text":"Report Pamphlet","size":"22.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3402"}],"country":"United 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\"}}]}","contact":"Florence Bascom Geoscience Center
(Formerly Eastern Geology and Paleoclimate Science Center)
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Near Moku‘āweoweo, Mauna Loa’s summit caldera, there are three fans of explosive deposits. The fans, located to the west, northwest, and east, are strongly arcuate in map view. Along ‘Āinapō Trail, 2.8–3.5 km southeast of the caldera, there are several small kīpuka that expose a fourth explosive deposit. Although these explosive deposits have been known for some time, no study bearing on the nature of the explosive activity that formed them has been done. By analyzing cosmogenic exposure age data and the physical properties of the debris fans—lithology, size distributions, and clast dispersal—we conclude that the lithic deposits are the result of five separate phreatic events. The lithic ejecta consist of fragments of ponded lavas, pāhoehoe, gabbroic xenoliths, and “bread-crust” fragments. The exposure ages indicate that the explosive deposit on the west caldera rim was erupted 868 ± 57 yr B.P.; for the northwest fan, the age determination is 829 ± 51 yr B.P.; and on the east rim, ejecta deposits are younger, with ages of 150 ± 20 and 220 ± 20 yr B.P. Lavas underlying these deposits have exposure ages of 960–1020 yr B.P., consistent with the stratigraphy. Near ‘Āinapō Trail, the explosive deposit is much older, overlain by flows dated with a pooled mean age of 1507 ± 19 yr B.P. From the cosmogenic dating, we have three reliable and unambiguous dates. At a much earlier time, a fourth explosive eruption created the ‘Āinapō Trail deposit. We conclude there were at least five explosive episodes around the summit caldera. These deposits, along with recent work done on Kīlauea’s explosive activity, further discredit the notion that Hawaiian volcanoes are strictly effusive in nature. The evidence from the summit of Mauna Loa indicates that it, too, has erupted explosively in recent history.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Field volcanology: A tribute to the distinguished career of Don Swanson","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.2538(15)","usgsCitation":"Trusdell, F., Hungerford, J., Stone, J., Fifield, K., McCann, K., Wershow, H., Zaarur, S., and Dimeo Boyd, M., 2018, Explosive eruptions at the summit of Mauna Loa: Lithology, modeling, and dating, chap. of Field volcanology: A tribute to the distinguished career of Don Swanson, v. 538, p. 325-349, https://doi.org/10.1130/2018.2538(15).","productDescription":"25 p.","startPage":"325","endPage":"349","ipdsId":"IP-089763","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":395128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.6297492980957,\n 19.42013505603468\n ],\n [\n -155.55353164672852,\n 19.42013505603468\n ],\n [\n -155.55353164672852,\n 19.502842244396035\n ],\n [\n -155.6297492980957,\n 19.502842244396035\n ],\n [\n -155.6297492980957,\n 19.42013505603468\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"538","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Trusdell, Frank A. 0000-0002-0681-0528 trusdell@usgs.gov","orcid":"https://orcid.org/0000-0002-0681-0528","contributorId":754,"corporation":false,"usgs":true,"family":"Trusdell","given":"Frank A.","email":"trusdell@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":832274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hungerford, Jefferson","contributorId":243584,"corporation":false,"usgs":false,"family":"Hungerford","given":"Jefferson","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":832275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stone, John","contributorId":199224,"corporation":false,"usgs":false,"family":"Stone","given":"John","email":"","affiliations":[],"preferred":false,"id":832276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fifield, Keith","contributorId":272639,"corporation":false,"usgs":false,"family":"Fifield","given":"Keith","email":"","affiliations":[{"id":37791,"text":"Australia National University, Canberra","active":true,"usgs":false}],"preferred":false,"id":832277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCann, Kaitlin","contributorId":272640,"corporation":false,"usgs":false,"family":"McCann","given":"Kaitlin","email":"","affiliations":[{"id":37174,"text":"Volunteer","active":true,"usgs":false}],"preferred":false,"id":832278,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wershow, Harold","contributorId":272641,"corporation":false,"usgs":false,"family":"Wershow","given":"Harold","email":"","affiliations":[{"id":56394,"text":"Everett Community College, Everett, WA","active":true,"usgs":false}],"preferred":false,"id":832279,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zaarur, Shikma","contributorId":272642,"corporation":false,"usgs":false,"family":"Zaarur","given":"Shikma","email":"","affiliations":[{"id":56395,"text":"Hebrew University Insitute of Earh Sciences, Jerusalem","active":true,"usgs":false}],"preferred":false,"id":832280,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dimeo Boyd, Melissa","contributorId":272643,"corporation":false,"usgs":false,"family":"Dimeo Boyd","given":"Melissa","email":"","affiliations":[{"id":56396,"text":"Yeh and Associates, Denver CO","active":true,"usgs":false}],"preferred":false,"id":832281,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202168,"text":"70202168 - 2018 - Potential for negative emissions of greenhouse gases (CO2, CH4 and N2O) through coastal peatland re-establishment: Novel insights from high frequency flux data at meter and kilometer scales","interactions":[],"lastModifiedDate":"2019-02-12T16:26:58","indexId":"70202168","displayToPublicDate":"2019-02-01T16:26:49","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Potential for negative emissions of greenhouse gases (CO2, CH4 and N2O) through coastal peatland re-establishment: Novel insights from high frequency flux data at meter and kilometer scales","title":"Potential for negative emissions of greenhouse gases (CO2, CH4 and N2O) through coastal peatland re-establishment: Novel insights from high frequency flux data at meter and kilometer scales","docAbstract":"High productivity temperate wetlands that accrete peat via belowground biomass (peatlands) may be managed for climate mitigation benefits due to their global distribution and notably negative emissions of atmospheric carbon dioxide (CO2) through rapid storage of carbon (C) in anoxic soils. Net emissions of additional greenhouse gases (GHG)—methane (CH4) and nitrous oxide (N2O)—are more difficult to predict and monitor due to fine-scale temporal and spatial variability, but can potentially reverse the climate mitigation benefits resulting from CO2 uptake. To support management decisions and modeling, we collected continuous 96 hour high frequency GHG flux data for CO2, CH4 and N2O at multiple scales—static chambers (1 Hz) and eddy covariance (10 Hz)—during peak productivity in a well-studied, impounded coastal peatland in California's Sacramento Delta with high annual rates of C fluxes, sequestering 2065 ± 150 g CO2 m−2 y−1 and emitting 64.5 ± 2.4 g CH4 m−2 y−1. Chambers (n = 6) showed strong spatial variability along a hydrologic gradient from inlet to interior plots. Daily (24 hour) net CO2 uptake (NEE) was highest near inlet locations and fell dramatically along the flowpath (−25 to −3.8 to +2.64 g CO2 m−2 d−1). In contrast, daily net CH4 flux increased along the flowpath (0.39 to 0.62 to 0.88 g CH4 m−2d−1), such that sites of high daily CO2 uptake were sites of low CH4 emission. Distributed, continuous chamber data exposed five novel insights, and at least two important datagaps for wetland GHG management, including: (1) increasing dominance of CH4 ebullition fluxes (15%–32% of total) along the flowpath and (2) net negative N2O flux across all sites as measured during a 4 day period of peak biomass (−1.7 mg N2O m−2 d−1; 0.51 g CO2 eq m−2 d−1). The net negative emissions of re-established peat-accreting wetlands are notably high, but may be poorly estimated by models that do not consider within-wetland spatial variability due to water flowpaths.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/aaae74","usgsCitation":"Windham-Myers, L., Bergamaschi, B.A., Anderson, F.A., Knox, S., Miller, R., and Fujii, R., 2018, Potential for negative emissions of greenhouse gases (CO2, CH4 and N2O) through coastal peatland re-establishment: Novel insights from high frequency flux data at meter and kilometer scales: Environmental Research Letters, v. 13, no. 4, p. 1-14, https://doi.org/10.1088/1748-9326/aaae74.","productDescription":"Article 045005; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-091738","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":468152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aaae74","text":"Publisher Index Page"},{"id":361209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","volume":"13","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":757069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Frank A. 0000-0002-1418-4678","orcid":"https://orcid.org/0000-0002-1418-4678","contributorId":203975,"corporation":false,"usgs":true,"family":"Anderson","given":"Frank","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knox, Sarah 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":167493,"corporation":false,"usgs":false,"family":"Knox","given":"Sarah","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":757072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Robin 0000-0002-1875-0390 romiller@usgs.gov","orcid":"https://orcid.org/0000-0002-1875-0390","contributorId":213190,"corporation":false,"usgs":true,"family":"Miller","given":"Robin","email":"romiller@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757073,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fujii, Roger 0000-0002-4616-7231 rfujii@usgs.gov","orcid":"https://orcid.org/0000-0002-4616-7231","contributorId":213191,"corporation":false,"usgs":true,"family":"Fujii","given":"Roger","email":"rfujii@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757074,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201780,"text":"70201780 - 2018 - Landsat benefiting society for fifty years","interactions":[{"subject":{"id":70268821,"text":"70268821 - 2018 - Addressing the water consumption riddle","indexId":"70268821","publicationYear":"2018","noYear":false,"title":"Addressing the water consumption riddle"},"predicate":"IS_PART_OF","object":{"id":70201780,"text":"70201780 - 2018 - Landsat benefiting society for fifty years","indexId":"70201780","publicationYear":"2018","noYear":false,"title":"Landsat benefiting society for fifty years"},"id":1},{"subject":{"id":70268822,"text":"70268822 - 2018 - After the fire: Landsat helps map the way forward","indexId":"70268822","publicationYear":"2018","noYear":false,"title":"After the fire: Landsat helps map the way forward"},"predicate":"IS_PART_OF","object":{"id":70201780,"text":"70201780 - 2018 - Landsat benefiting society for fifty years","indexId":"70201780","publicationYear":"2018","noYear":false,"title":"Landsat benefiting society for fifty years"},"id":2}],"lastModifiedDate":"2025-07-08T14:19:17.321439","indexId":"70201780","displayToPublicDate":"2019-02-01T13:24:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Landsat benefiting society for fifty years","docAbstract":"Since 1972, data acquired by the Landsat series of satellites have become integral to land management for both government and the private sector, providing scientists and decision makers with key information about agricultural productivity, ice sheet dynamics, urban growth, forest monitoring, natural resource management, water quality, and supporting disaster response.
Landsat 9 continues the mission of unrivaled space-based Earth observation and will lead the Landsat program into its second half century of Earth imagery provided to users, worldwide, at no charge. More than 8 million Landsat scenes held in the USGS archive to date are used in conjunction with advanced geographic information systems, image processing software, and cloud computing capabilities to enable Landsat users to study changes on the Earth’s surface across continental regions and extended time periods.
The Operational Land Imager 2 (OLI-2) and the Thermal Infrared Sensor 2 (TIRS-2) instruments onboard Landsat 9 —which replicate the technologically-advanced instruments introduced onboard Landsat 8—allow for the collection of continuous high-quality data required for advancing Earth applications, including our ability to map surface temperature and surface water quality.
Landsat 9 will build on the Landsat legacy, achieving a half-century record of global Earth observations.
","language":"English","publisher":"NASA","usgsCitation":"Rocchio, L., Connot, P., Young, S., Ramsayer, K., Owen, L., Bouchard, M., and Barnes, C., 2018, Landsat benefiting society for fifty years, 60 p.","productDescription":"60 p.","onlineOnly":"Y","ipdsId":"IP-103742","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":361030,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":399495,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://landsat.gsfc.nasa.gov/wp-content/uploads/2019/02/Case_Studies_Book2018_Landsat_Final_12x9web.pdf","linkFileType":{"id":1,"text":"pdf"}}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rocchio, Laura E. P.","contributorId":212822,"corporation":false,"usgs":false,"family":"Rocchio","given":"Laura E. P.","affiliations":[],"preferred":false,"id":756680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connot, Peggy 0000-0002-8474-8096","orcid":"https://orcid.org/0000-0002-8474-8096","contributorId":212823,"corporation":false,"usgs":true,"family":"Connot","given":"Peggy","email":"","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":756681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Steve 0000-0002-7904-9696","orcid":"https://orcid.org/0000-0002-7904-9696","contributorId":212824,"corporation":false,"usgs":true,"family":"Young","given":"Steve","email":"","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":756682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ramsayer, Kate","contributorId":212825,"corporation":false,"usgs":false,"family":"Ramsayer","given":"Kate","email":"","affiliations":[],"preferred":false,"id":756683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Owen, Linda 0000-0002-1734-5406","orcid":"https://orcid.org/0000-0002-1734-5406","contributorId":212826,"corporation":false,"usgs":true,"family":"Owen","given":"Linda","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":756684,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bouchard, Michelle 0000-0002-6353-3491 mbouchard@usgs.gov","orcid":"https://orcid.org/0000-0002-6353-3491","contributorId":3765,"corporation":false,"usgs":true,"family":"Bouchard","given":"Michelle","email":"mbouchard@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":756685,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barnes, Christopher 0000-0002-4608-4364 christopher.barnes.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-4608-4364","contributorId":198908,"corporation":false,"usgs":true,"family":"Barnes","given":"Christopher","email":"christopher.barnes.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":756686,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202144,"text":"70202144 - 2018 - Secular changes in Cenozoic arc magmatism recorded by trends in forearc-basin sandstone composition, Cook Inlet, southern Alaska","interactions":[],"lastModifiedDate":"2019-10-28T09:41:05","indexId":"70202144","displayToPublicDate":"2019-02-01T11:48:38","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Secular changes in Cenozoic arc magmatism recorded by trends in forearc-basin sandstone composition, Cook Inlet, southern Alaska","docAbstract":"A robust set of modal composition data (238 samples) for Eocene to Pliocene sandstone from the Cook Inlet forearc basin of southern Alaska reveals strong temporal trends in composition, particularly in the abundance of volcanic lithic grains. Field and petrographic point-count data from the northwestern side of the basin indicate that the middle Eocene West Foreland Formation was strongly influenced by nearby volcanic activity. The middle Eocene to lower Miocene Hemlock Conglomerate and Oligocene to middle Miocene Tyonek Formation have a more mature quartzose composition with limited volcanic input. The middle to upper Miocene Beluga Formation includes abundant argillaceous sedimentary lithic grains and records an upward increase in volcanogenic material. The up-section increase in volcanic detritus continues into the upper Miocene to Pliocene Sterling Formation.
These first-order observations are interpreted to primarily reflect the waxing and waning of nearby arc magmatism. Available U-Pb detrital zircon geochronologic data indicate a dramatic reduction in zircon abundance during the early Eocene, and again during the Oligocene to Miocene, suggesting the arc was nearly dormant during these intervals. The reduced arc flux may record events such as subduction of slab windows or material that resisted subduction. The earlier hiatus in volcanism began ca. 56 Ma and coincided with a widely accepted model of ridge subduction beneath south-central Alaska. The later hiatus (ca. 25–8 Ma) coincided with insertion of the leading edge of the Yakutat terrane beneath the North American continental margin, resulting in an Oligocene to Miocene episode of flat-slab subduction that extended farther to the southwest than the modern seismically imaged flat-slab region. The younger tectonic event coincided with development of some of the best petroleum reservoirs in Cook Inlet.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tectonics, sedimentary basins, and provenance: A celebration of the career of William R. Dickinson","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.2540(26)","usgsCitation":"Helmold, K.P., Wartes, M.A., Gillis, R.J., LePain, D.L., Herriott, T.M., Stanley, R.G., and Wilson, M.D., 2018, Secular changes in Cenozoic arc magmatism recorded by trends in forearc-basin sandstone composition, Cook Inlet, southern Alaska, chap. of Tectonics, sedimentary basins, and provenance: A celebration of the career of William R. Dickinson, p. 591-615, https://doi.org/10.1130/2018.2540(26).","productDescription":"25 p.","startPage":"591","endPage":"615","ipdsId":"IP-092258","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":361172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Cook Inlet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.545654296875,\n 61.60639637138628\n ],\n [\n -154.412841796875,\n 59.10266722885381\n ],\n [\n -152.501220703125,\n 58.49369382056807\n ],\n [\n -151.710205078125,\n 59.19843857520702\n ],\n [\n -150.79833984375,\n 59.772991625706695\n ],\n [\n -150.97412109375,\n 59.89444803635239\n ],\n [\n -151.622314453125,\n 59.75086102411168\n ],\n [\n -151.226806640625,\n 60.673178565817715\n ],\n [\n -150.52368164062497,\n 60.8663124746226\n ],\n [\n -148.831787109375,\n 60.83955785801797\n ],\n [\n -149.43603515625,\n 61.18032911734518\n ],\n [\n -148.787841796875,\n 61.554109444927185\n ],\n [\n -150.545654296875,\n 61.60639637138628\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Ingersoll, Raymond V.","contributorId":213185,"corporation":false,"usgs":false,"family":"Ingersoll","given":"Raymond","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":757056,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lawton, Timothy F.","contributorId":63866,"corporation":false,"usgs":true,"family":"Lawton","given":"Timothy","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":757057,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Graham, Stephan A.","contributorId":45902,"corporation":false,"usgs":true,"family":"Graham","given":"Stephan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":757058,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Helmold, Kenneth P.","contributorId":213171,"corporation":false,"usgs":false,"family":"Helmold","given":"Kenneth","email":"","middleInitial":"P.","affiliations":[{"id":16127,"text":"Alaska Division of Oil and Gas","active":true,"usgs":false}],"preferred":false,"id":757026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wartes, Marwan A.","contributorId":213172,"corporation":false,"usgs":false,"family":"Wartes","given":"Marwan","email":"","middleInitial":"A.","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":757027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gillis, Robert J.","contributorId":213173,"corporation":false,"usgs":false,"family":"Gillis","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":757028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LePain, David L.","contributorId":191714,"corporation":false,"usgs":false,"family":"LePain","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":757029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herriott, Trystan M.","contributorId":213174,"corporation":false,"usgs":false,"family":"Herriott","given":"Trystan","email":"","middleInitial":"M.","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":757030,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stanley, Richard G. 0000-0001-6192-8783 rstanley@usgs.gov","orcid":"https://orcid.org/0000-0001-6192-8783","contributorId":1832,"corporation":false,"usgs":true,"family":"Stanley","given":"Richard","email":"rstanley@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":757025,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Michael D.","contributorId":213175,"corporation":false,"usgs":false,"family":"Wilson","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":12586,"text":"Consultant","active":true,"usgs":false}],"preferred":false,"id":757031,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200801,"text":"70200801 - 2018 - Controls on deep direct-use thermal energy storage (DDU-TES) in the Portland Basin, Oregon, USA","interactions":[],"lastModifiedDate":"2019-12-22T14:18:33","indexId":"70200801","displayToPublicDate":"2019-01-30T09:42:15","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Controls on deep direct-use thermal energy storage (DDU-TES) in the Portland Basin, Oregon, USA","docAbstract":"Aquifer Thermal Energy Storage is being evaluated as a complementary technology to Deep Direct-Use for the Portland Basin, Oregon, USA. Aquifers can be used to efficiently distribute and store heat for seasonal use. The use of injection-extraction well pairs precludes the need to store or dispose of large volumes of pumped groundwater or to obtain a consumptive groundwater right. Injection temperatures vary seasonally, and well pairs can operate in continuous (single direction of flow) or cyclic (seasonal reversal of flow) modes. The target injection aquifers are the lowest Columbia River Basalt Group interflow zones, which are thermally and hydraulically separated from the overlying aquifer system, minimizing heat loss. A new aquifer thermal energy storage design tool allows assessment of thermal storage and recovery using: (1) system design parameters (e.g., well spacing and pumping rate), (2) thermal and hydraulic property values, and (3) regional groundwater flow rates. In continuous mode, extracted water temperature trends towards the flow-weighted average temperature of injected water over time, with the injected signal significantly lagged and damped. By controlling well spacing and temperature of delivered water (possibly using supplemental heating) continuous mode provides steady reliable warm water to end-users year-round. In cyclic mode, there is an advectively and conductively heated zone near the hot well and a cooled zone near the cool well, with temperatures substantially above and below the flow-weighted average injection temperature, respectively. In cyclic mode, during extraction, water temperatures start high or low, depending on the well, and temperatures trend towards the average injection temperature over the season. For the Columbia River Basalt Group in the Portland Basin, the quantity and quality of heat delivered depends most strongly on operational schedule, well spacing, mode of operation, and heterogeneity of the injection horizon.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geothermal's role in today's energy: Geothermal Resources Council Annual Meeting (GRC 2018)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Burns, E.R., Cladouhos, T.T., Williams, C., and Bershaw, 2018, Controls on deep direct-use thermal energy storage (DDU-TES) in the Portland Basin, Oregon, USA, in Geothermal's role in today's energy: Geothermal Resources Council Annual Meeting (GRC 2018), v. 42, p. 132-168.","productDescription":"36 p.","startPage":"132","endPage":"168","ipdsId":"IP-098120","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":365811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365760,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.proceedings.com/42374.html"}],"country":"United States","state":"Oregon","otherGeospatial":"Portland Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.28857421875,\n 44.55133484083592\n ],\n [\n -122.34374999999999,\n 44.55133484083592\n ],\n [\n -122.34374999999999,\n 45.805828539928356\n ],\n [\n -123.28857421875,\n 45.805828539928356\n ],\n [\n -123.28857421875,\n 44.55133484083592\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","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":true,"id":750584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cladouhos, Trenton T.","contributorId":66801,"corporation":false,"usgs":true,"family":"Cladouhos","given":"Trenton","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":766659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, C.F. 0000-0003-2196-5496","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":20401,"corporation":false,"usgs":true,"family":"Williams","given":"C.F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":766660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bershaw","contributorId":217372,"corporation":false,"usgs":false,"family":"Bershaw","email":"","affiliations":[],"preferred":false,"id":766661,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201743,"text":"70201743 - 2018 - Time-dependent pore filling","interactions":[],"lastModifiedDate":"2019-02-11T14:38:39","indexId":"70201743","displayToPublicDate":"2019-01-28T14:39:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Time-dependent pore filling","docAbstract":"Capillarity traps fluids in porous media during immiscible fluid displacement. Most field situations involve relatively long time scales, such as hydrocarbon migration into reservoirs, resource recovery, nonaqueous phase liquid remediation, geological CO2 storage, and sediment‐atmosphere interactions. Yet laboratory studies and numerical simulations of capillary phenomena rarely consider the impact of time on these processes. We use time‐lapse microphotography to record the evolution of saturation in air‐ or hydrocarbon‐filled capillary tubes submerged in water to investigate long‐term pore filling phenomena beyond imbibition. Microphotographic sequences capture a lively pore filling history where various concurrent physical phenomena coexist. Dissolution and diffusion play a central role. Observations indicate preferential transport of the wetting liquid along corners, vapor condensation, capillary flow induced by asymmetrical interfaces, and interface pinning that defines the diffusion length. Other processes include internal snap‐offs, fluid redistribution, and changes in wettability as fluids dissolve into each other. Overall, the rate of pore filling is diffusion‐controlled for a given interfacial configuration; diffusive transport takes place at a constant rate for pinned interfaces and is proportional to the square root of time for free interfaces where the diffusion length increases with time.
","language":"English","publisher":"AGU","doi":"10.1029/2018WR023066","usgsCitation":"Sun, Z., Jang, J., and Santamarina, J.C., 2018, Time-dependent pore filling: Water Resources Research, v. 54, no. 12, p. 10242-10253, https://doi.org/10.1029/2018WR023066.","productDescription":"12 p.","startPage":"10242","endPage":"10253","ipdsId":"IP-087788","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468153,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr023066","text":"Publisher Index Page"},{"id":360762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"12","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-26","publicationStatus":"PW","scienceBaseUri":"5c5022c0e4b0708288f7e7c5","contributors":{"authors":[{"text":"Sun, Zhonghao","contributorId":211899,"corporation":false,"usgs":false,"family":"Sun","given":"Zhonghao","email":"","affiliations":[],"preferred":false,"id":755163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jang, Junbong 0000-0001-5500-7558 jjang@usgs.gov","orcid":"https://orcid.org/0000-0001-5500-7558","contributorId":189400,"corporation":false,"usgs":true,"family":"Jang","given":"Junbong","email":"jjang@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":755164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Santamarina, J. Carlos","contributorId":189401,"corporation":false,"usgs":false,"family":"Santamarina","given":"J.","email":"","middleInitial":"Carlos","affiliations":[],"preferred":false,"id":755165,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201718,"text":"70201718 - 2018 - Ecological changes in the nannoplankton community across a shelf transect during the onset of the Paleocene-Eocene Thermal Maximum","interactions":[],"lastModifiedDate":"2019-01-28T11:30:06","indexId":"70201718","displayToPublicDate":"2019-01-28T11:29:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"Ecological changes in the nannoplankton community across a shelf transect during the onset of the Paleocene-Eocene Thermal Maximum","docAbstract":"Warming and other environmental changes during the Paleocene‐Eocene thermal maximum (PETM) led to profound shifts in the composition and structure of nannoplankton assemblages. Here we analyze the nature of these changes in expanded records from the Cambridge‐Dorchester and Mattawoman Creek‐Billingsley Road cores in Maryland. These cores comprise part of a transect of five paleoshelf cores from Maryland and New Jersey. We integrate multivariate analysis of assemblage data with proxy data to revise understanding of the paleoecological affinities of key species. In particular, Discoasterand Fasciculithus are interpreted as thermophiles without adaptation to particular nutrient levels, while Hornibrookina is considered an opportunist adapted to highly variable nearshore environments. Together the cores show consistent margin‐wide changes across the onset of the PETM, including a pulse of preevent warming, possibly combined with lower salinity, high seasonality, or increased turbidity. The event itself was characterized by continued warming and eutrophication across the paleoshelf. The Maryland sites experienced higher environmental variability as a result of their proximity to large river systems.
","language":"English","publisher":"AGU","doi":"10.1029/2018PA003383","usgsCitation":"Leon y Leon, I.A., Bralower, T.J., and Self-Trail, J., 2018, Ecological changes in the nannoplankton community across a shelf transect during the onset of the Paleocene-Eocene Thermal Maximum: Paleoceanography and Paleoclimatology, v. 33, no. 12, p. 1396-1407, https://doi.org/10.1029/2018PA003383.","productDescription":"12 p.","startPage":"1396","endPage":"1407","ipdsId":"IP-096927","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":468154,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018pa003383","text":"Publisher Index Page"},{"id":360724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-21","publicationStatus":"PW","scienceBaseUri":"5c5022c4e4b0708288f7e810","contributors":{"authors":[{"text":"Leon y Leon, Isabel A.","contributorId":211831,"corporation":false,"usgs":false,"family":"Leon y Leon","given":"Isabel","email":"","middleInitial":"A.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":754990,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bralower, Timothy J.","contributorId":211832,"corporation":false,"usgs":false,"family":"Bralower","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":754991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Self-Trail, Jean 0000-0002-3018-4985 jstrail@usgs.gov","orcid":"https://orcid.org/0000-0002-3018-4985","contributorId":147370,"corporation":false,"usgs":true,"family":"Self-Trail","given":"Jean","email":"jstrail@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":754989,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202690,"text":"70202690 - 2018 - Improving ecological restoration to curb biotic invasion - A practical guide","interactions":[],"lastModifiedDate":"2019-03-18T16:19:44","indexId":"70202690","displayToPublicDate":"2019-01-04T16:19:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2100,"text":"Invasive Plant Science and Management","active":true,"publicationSubtype":{"id":10}},"title":"Improving ecological restoration to curb biotic invasion - A practical guide","docAbstract":"Common practices for invasive species control and management include physical, chemical, and biological approaches. The first two approaches have clear limitations and may lead to unintended (negative) consequences, unless carefully planned and implemented. For example, physical removal rarely completely eradicates the targeted invasive species and can cause disturbances that facilitate new invasions by nonnative species from nearby habitats. Chemical treatments can harm native, and especially rare, species through unanticipated side effects. Biological methods may be classified as biocontrol and the ecological approach. Similar to physical and chemical methods, biocontrol also has limitations and sometimes leads to unintended consequences. Therefore, a relatively safer and more practical choice may be the ecological approach, which has two major components: (1) restoration of native species and (2) biomass manipulation of the restored community, such as selective grazing or prescribed burning (to achieve and maintain viable population sizes). Restoration requires well-planned and implemented planting designs that consider alpha-, beta-, and gamma-diversity and the abundance of native and invasive component species at local, landscape, and regional levels. Given the extensive destruction or degradation of natural habitats around the world, restoration could be most effective for enhancing ecosystem resilience and resistance to biotic invasions. At the same time, ecosystems in human-dominated landscapes, especially those newly restored, require close monitoring and careful intervention (e.g., through biomass manipulation), especially when successional trajectories are not moving as intended. Biomass management frequently uses prescribed burning, grazing, harvesting, and thinning to maintain overall ecosystem health and sustainability. Thus, the resulting optimal, balanced, and relatively stable ecological conditions could more effectively limit the spread and establishment of invasive species. Here we review the literature (especially within the last decade) on ecological approaches that involve biodiversity, biomass, and productivity, three key community/ecosystem variables that reciprocally influence one another. We focus on the common and most feasible ecological practices that can aid in resisting new invasions and/or suppressing the dominance of existing invasive species. We contend that, because of the strong influences from neighboring areas (i.e., as exotic species pools), local restoration and management efforts in the future need to consider the regional context and projected climate changes.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/inp.2018.29","usgsCitation":"Guo, Q., Brockway, D.G., Larson, D.L., Wang, D., and Ren, H., 2018, Improving ecological restoration to curb biotic invasion - A practical guide: Invasive Plant Science and Management, v. 11, no. 4, p. 163-174, https://doi.org/10.1017/inp.2018.29.","productDescription":"12 p.","startPage":"163","endPage":"174","ipdsId":"IP-097426","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468155,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/inp.2018.29","text":"Publisher Index Page"},{"id":362157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Guo, Qinfeng","contributorId":214263,"corporation":false,"usgs":false,"family":"Guo","given":"Qinfeng","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":759492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brockway, Dale G.","contributorId":214264,"corporation":false,"usgs":false,"family":"Brockway","given":"Dale","email":"","middleInitial":"G.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":759493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":759491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Deli","contributorId":214265,"corporation":false,"usgs":false,"family":"Wang","given":"Deli","email":"","affiliations":[{"id":39004,"text":"Northeast Normal University","active":true,"usgs":false}],"preferred":false,"id":759494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ren, Hai","contributorId":214266,"corporation":false,"usgs":false,"family":"Ren","given":"Hai","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":759495,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202182,"text":"70202182 - 2018 - Clarification of the term “normal material” used for standard atomic weights (IUPAC Technical Report)","interactions":[],"lastModifiedDate":"2019-02-12T16:51:07","indexId":"70202182","displayToPublicDate":"2019-01-01T16:51:02","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3207,"text":"Pure and Applied Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Clarification of the term “normal material” used for standard atomic weights (IUPAC Technical Report)","docAbstract":"The standard atomic weights of the elements apply to normal materials. Since 1984, the Commission on Isotopic Abundances and Atomic Weights (Commission) has defined a normal material as:
“The material is a reasonably possible source for this element or its compounds in commerce, for industry or science; the material is not itself studied for some extraordinary anomaly and its isotopic composition has not been modified significantly in a geologically brief period.”
The term “a geologically brief period” in this definition is confusing, and confusion can be reduced by revising this definition to the following, which was accepted by the Commission on Isotopic Abundances and Atomic Weights at its meeting in Groningen, Netherlands in September 2017:
“Normal materials include all substances, except (1) those subjected to substantial deliberate, undisclosed, or inadvertent artificial isotopic modification, (2) extraterrestrial materials, and (3) isotopically anomalous specimens, such as natural nuclear reactor products from Oklo (Gabon) or other unique occurrences.”
Rationale
Despite a long history and growing interest in isotopic analyses of N2O, there is a lack of isotopically characterized N2O isotopic reference materials (standards) to enable normalization and reporting of isotope‐delta values. Here we report the isotopic characterization of two pure N2O gas reference materials, USGS51 and USGS52, which are now available for laboratory calibration (https://isotopes.usgs.gov/lab/referencematerials.html).
Methods
A total of 400 sealed borosilicate glass tubes of each N2O reference gas were prepared from a single gas filling of a high vacuum line. We demonstrated isotopic homogeneity via dual‐inlet isotope‐ratio mass spectrometry. Isotopic analyses of these reference materials were obtained from eight laboratories to evaluate interlaboratory variation and provide preliminary isotopic characterization of their δ15N, δ18O, δ15Nα, δ15Nβ and site preference (SP) values.
Results
The isotopic homogeneity of both USGS51 and USGS52 was demonstrated by one‐sigma standard deviations associated with the determinations of their δ15N, δ18O, δ15Nα, δ15Nβand SP values of 0.12 mUr or better. The one‐sigma standard deviations of SPmeasurements of USGS51 and USGS52 reported by eight laboratories participating in the interlaboratory comparison were 1.27 and 1.78 mUr, respectively.
Conclusions
The agreement of isotope‐delta values obtained in the interlaboratory comparison was not sufficient to provide reliable accurate isotope measurement values for USGS51 and USGS52. We propose that provisional values for the isotopic composition of USGS51 and USGS52 determined at the Tokyo Institute of Technology can be adopted for normalizing and reporting sample data until further refinements are achieved through additional calibration efforts.
Chronic exposure to arsenic (As) via drinking groundwater is a human health concern worldwide. Probabilities of elevated geogenic As concentrations in groundwater were predicted in complex, glacial aquifers in Minnesota, north‐central USA, a region that commonly has elevated As concentrations in well water. Maps of elevated As hazard were created for depths typical of drinking water supply and with well construction attributes common for domestic wells. Conventional variables describing aquifer properties and materials, position on the hydrologic landscape, and soil geochemistry were among the most influential for predicting the probability of elevated As. We also found that certain well construction attributes were influential in predicting As hazard. Smaller distances between the top of the well screen and overlying aquitard (proximity) and shorter well screen lengths were each associated with higher probabilities of elevated As. Influential predictor variables, which are either mapped across the region or are well construction attributes, are proxies in the model for measurable physical or geochemical causes of elevated As (e.g., redox condition, till or aquifer sediment chemistry, and water chemistry), which are not mapped across the region. Our setting shares some important characteristics with deltaic and other high‐As aquifers in Southeast Asia: late Quaternary age, complex layering of coarse‐ and fine‐grained materials, low‐As sediment concentrations, and geochemical controls on As mobilization. Translating three‐dimensional geologic and geochemical understanding of As mobility to quantifiable variables for modeling with powerful, flexible statistical tools could improve predictions and help identify safer groundwater supply options in the USA, Southeast Asia, and elsewhere.
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