The goal of the 3D Elevation Program (3DEP) is to complete nationwide data acquisition in 8 years, by 2023, to provide the first-ever national baseline of consistent high-resolution three-dimensional data—including bare earth elevations and three-dimensional point clouds—collected in a timeframe of less than a decade. Successful implementation of 3DEP depends on partnerships and the development and adoption of a unified Federal approach to acquiring data. The purpose of this document is to outline several best practices to aid the Federal 3DEP community in reaching a higher level of coordinated implementation, maximize Federal data investments, and reduce the number of years it will take to complete national coverage. The best practices are provided to Federal agencies as a checklist to assess the level of their participation and to inspire further adoption of Federal enterprise practices that will advance joint 3DEP coverage goals for the benefit of their missions and the Nation as a whole. It is anticipated that additional best practices will be defined and added as the effort matures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203062","usgsCitation":"Lukas, V., and Baez, V., 2021, 3D Elevation Program—Federal best practices: U.S. Geological Survey Fact Sheet 2020–3062, 2 p., https://doi.org/10.3133/fs20203062.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-118601","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":384879,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3062/fs20203062.pdf","text":"Report","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3062"},{"id":383062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3062/coverthb.jpg"}],"contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 511
Reston, VA 20192
Email: 3DEP@usgs.gov
Water use is a critical and often uncertain component of quantifying any water budget and securing reliable and sustainable water supplies. Recent water-level declines in the Mississippi Alluvial Plain (MAP), especially in the central part of the Mississippi Delta, pose a threat to water sustainability. Aquaculture and Irrigation Water-Use Model (AIWUM) 1.0, one of the first national agricultural water-use models that provides water use at the scale of most groundwater models, was developed and compared to other reported and estimated aquaculture and irrigation water-use values within the MAP study area for 1999 through 2017 to improve water-use estimates needed as input to a hydrologic decision-support system in the MAP. Results indicate annual total water-use estimates from 1999 through 2017 ranged from about 5 to 13 billion gallons per day and, on average, a majority of the water use was applied to rice (about 51 percent), followed by soybeans (about 26 percent), and less than (<) 10 percent each was applied to aquaculture, corn, cotton, and other crops. Comparisons indicated that annual total water-use estimates from AIWUM 1.0 were smaller than or comparable to all other sources of water-use data. Although there is disagreement at the monthly timescale in estimates in the Mississippi Delta within each part of the growing season, the annual total water use is comparable between AIWUM 1.0 and the Mississippi Embayment Regional Aquifer Study groundwater model 2.1. Estimates from AIWUM 1.0 could be used in models at all scales (for example, local, regional, national) and could provide a nationally consistent methodology in estimating water use driven by regional crop-specific withdrawal rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215011","collaboration":"Prepared in cooperation with the Mississippi Department of Environmental Quality, the Yazoo Mississippi Delta Joint Water Management District, and the Arkansas Natural Resources Commission","usgsCitation":"Wilson, J.L., 2021, Aquaculture and Irrigation Water-Use Model (AIWUM) version 1.0—An agricultural water-use model developed for the Mississippi Alluvial Plain, 1999–2017: U.S. Geological Survey Scientific Investigations Report 2021–5011, 36 p., https://doi.org/10.3133/sir20215011.","productDescription":"Report: viii, 36 p.; 3 Data releases; 2 Datasets; 1 Software release","numberOfPages":"47","onlineOnly":"Y","ipdsId":"IP-098146","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":436420,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YDGJ7L","text":"USGS data release","linkHelpText":"Aquaculture and Irrigation Water-Use Model (AIWUM)"},{"id":415513,"rank":8,"type":{"id":35,"text":"Software Release"},"url":"https://code.usgs.gov/map/wu/aiwum_1.1","text":"USGS software release","linkHelpText":"—Mississippi Alluvial Plain / wu / AIWUM 1.1"},{"id":415512,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RGZOBZ","text":"USGS data release","linkHelpText":"Aquaculture and irrigation water-Use model (AIWUM) version 1.1 estimates and related datasets for the Mississippi Alluvial Plain"},{"id":384819,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://www.usgs.gov/core-science-systems/ngp/national-hydrography/access-national-hydrography-products","text":"USGS National Hydrography web page","linkHelpText":"— National Hydrography Dataset"},{"id":384818,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS Water Data for the Nation"},{"id":384817,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JMO9G4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Aquaculture and Irrigation Water-Use Model (AIWUM) version 1.0 estimates and related datasets for the Mississippi Alluvial Plain, 1999–2017"},{"id":384816,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70R9MHS","text":"USGS data release","description":"USGS Data Release","linkHelpText":"National 1-kilometer rasters of selected Census of Agriculture statistics allocated to land use for the time period 1950 to 2012"},{"id":384814,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5011/coverthb.jpg"},{"id":384815,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5011/sir20215011.pdf","text":"Report","size":"16.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5011"}],"country":"United States","state":"Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Mississippi Alluvial Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.9892578125,\n 37.16031654673677\n ],\n [\n -89.296875,\n 37.33522435930639\n ],\n [\n -89.9560546875,\n 37.71859032558816\n ],\n [\n -90.8349609375,\n 36.914764288955936\n ],\n [\n -91.5380859375,\n 35.96022296929667\n ],\n [\n -92.1533203125,\n 34.66935854524543\n ],\n [\n -92.373046875,\n 33.50475906922609\n ],\n [\n -91.0546875,\n 33.100745405144245\n ],\n [\n -89.7802734375,\n 33.50475906922609\n ],\n [\n -88.9453125,\n 35.639441068973944\n ],\n [\n -88.9892578125,\n 37.16031654673677\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The Kansas River provides drinking water to about 800,000 people in northeastern Kansas. Water-treatment facilities that use the Kansas River as a water-supply source use chemical and physical processes during water treatment to remove contaminants before public distribution. Advanced notification of changing water-quality conditions near water-supply intakes allows water-treatment facilities to proactively adjust treatment. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas Water Plan), the Kansas Department of Health and Environment, The Nature Conservancy, the City of Lawrence, the City of Manhattan, the City of Olathe, the City of Topeka, and Johnson County WaterOne, collected water-quality data at the Kansas River at Wamego (USGS site 06887500; hereafter referred to as the “Wamego site”) and De Soto (USGS site 06892350; hereafter referred to as the “De Soto site”) monitoring sites to update previously published regression models relating continuous water-quality sensor measurements, streamflow, and seasonal components to discretely sampled water-quality constituent concentrations or densities. Linear regression analysis was used to update and develop models for total dissolved solids, major ions, hardness as calcium carbonate, nutrients (nitrogen and phosphorus species), chlorophyll a, total suspended solids, suspended sediment, and fecal indicator bacteria at the Wamego and De Soto monitoring sites using data collected during July 2012 through September 2019. The water-quality information documented in this report can be used as guidance for water-treatment processes and to characterize changes in water-quality conditions in the Kansas River over time that would not be otherwise possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211018","collaboration":"Prepared in cooperation with the Kansas Water Office, the Kansas Department of Health and Environment, The Nature Conservancy, the City of Lawrence, the City of Manhattan, the City of Olathe, the City of Topeka, and Johnson County WaterOne","usgsCitation":"Williams, T.J., 2021, Linear regression model documentation and updates for computing water-quality constituent concentrations or densities using continuous real-time water-quality data for the Kansas River, Kansas, July 2012 through September 2019: U.S. Geological Survey Open-File Report 2021–1018, 18 p., https://doi.org/10.3133/ofr20211018.","productDescription":"Report: vii, 18 p.; Appendixes: 1–32; Dataset","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-120556","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":384812,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1018/downloads","text":"Appendixes 1–32","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1018 Appendixes 1–32"},{"id":384811,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1018/ofr20211018.pdf","text":"Report","size":"1.16 MB","description":"OFR 2021–1018"},{"id":384810,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1018/coverthb.jpg"},{"id":384813,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.66845703124999,\n 38.151837403006766\n ],\n [\n -94.5703125,\n 38.151837403006766\n ],\n [\n -94.5703125,\n 39.977120098439634\n ],\n [\n -97.66845703124999,\n 39.977120098439634\n ],\n [\n -97.66845703124999,\n 38.151837403006766\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
Emergent late Pliocene and Pleistocene shoreline deposits, morphologically identifiable Pleistocene shoreline units, and seaward-facing scarps characterize the easternmost Atlantic Coastal Plain (ACP) of the United States of America. In some areas of the ACP, these deposits, units, and scarps have been studied in detail. Within these areas, temporal and spatial data are sufficient for time-depositional frameworks for shoreline-evolution to have been developed and published. For other areas, such as the southeastern Atlantic Coastal Plain (SEACP), available data are conflicting and (or) insufficient to develop such a framework, or to make shoreline correlations. Differential epeirogenic uplift and shoreline deformation, resulting from mantle-flow and climate-induced isostatic adjustments, complicate regional shoreline correlations. In the SEACP, the topographically prominent Orangeburg Scarp (hereafter, the Scarp) rises tens of meters in elevation from southeastern Georgia to southeastern North Carolina. The degree to which the Scarp and shoreline units seaward of the Scarp are deformed continues to be debated, but there is general agreement that the lower Savannah River area (LSRA) of Georgia and South Carolina is the least deformed area of the SEACP.
This paper synthesizes published and previously unpublished numerical age and stratigraphic data for emergent Pliocene and younger shoreline deposits in the LSRA in Georgia. Age data are applied to these shoreline deposits as they are delineated (map units) on the 1976 geologic map of Georgia by Lawton and others. Age assignments are based on stratigraphic position, fossil content, soil and weathering diagnostic properties, and numerical ages as determined by meteoric Beryllium‑10 paleosol residence time (10BePRT), optically stimulated luminescence (OSL), uranium disequilibrium series (U-series), amino acid racemization (AAR), and radiocarbon (14C) analyses. These data provide a preliminary Pliocene-Pleistocene geochronology for the Orangeburg Scarp and shoreline deposits seaward of the Scarp in the LSRA of Georgia. Minimum ages and age ranges indicate the following:
Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
Atmospheric methane is a potent greenhouse gas that plays a major role in controlling the Earth’s climate. The causes of the renewed increase of methane concentration since 2007 are uncertain given the multiple sources and complex biogeochemistry. Here, we present a metadata analysis of methane fluxes from all major natural, impacted and human-made aquatic ecosystems. Our revised bottom-up global aquatic methane emissions combine diffusive, ebullitive and/or plant-mediated fluxes from 15 aquatic ecosystems. We emphasize the high variability of methane fluxes within and between aquatic ecosystems and a positively skewed distribution of empirical data, making global estimates sensitive to statistical assumptions and sampling design. We find aquatic ecosystems contribute (median) 41% or (mean) 53% of total global methane emissions from anthropogenic and natural sources. We show that methane emissions increase from natural to impacted aquatic ecosystems and from coastal to freshwater ecosystems. We argue that aquatic emissions will probably increase due to urbanization, eutrophication and positive climate feedbacks and suggest changes in land-use management as potential mitigation strategies to reduce aquatic methane emissions.
","language":"English","publisher":"Nature Research","doi":"10.1038/s41561-021-00715-2","usgsCitation":"Rosentreter, J.A., Borges, A.V., Deemer, B., Holgerson, M.A., Liu, S., Song, C., Melack, J.M., Raymond, P.A., Duarte, C.M., Allen, G., Olefeldt, D., Poulter, B., Batin, T.I., and Eyre, B.D., 2021, Half of global methane emissions come from highly variable aquatic ecosystem sources: Nature Geoscience, v. 14, p. 225-230, https://doi.org/10.1038/s41561-021-00715-2.","productDescription":"6 p.","startPage":"225","endPage":"230","ipdsId":"IP-112683","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":487210,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://infoscience.epfl.ch/record/284804","text":"External 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Shaoda","contributorId":257246,"corporation":false,"usgs":false,"family":"Liu","given":"Shaoda","email":"","affiliations":[{"id":51989,"text":"Yale School of Forestry and Environmental Studies, 195 Prospect Street, New Haven, CT, USA","active":true,"usgs":false}],"preferred":false,"id":813868,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Song, Chunlin","contributorId":257247,"corporation":false,"usgs":false,"family":"Song","given":"Chunlin","email":"","affiliations":[{"id":51990,"text":"Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan, China","active":true,"usgs":false}],"preferred":false,"id":813869,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Melack, John M.","contributorId":167466,"corporation":false,"usgs":false,"family":"Melack","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":24713,"text":"Bren School of Environmental Science and Management, University of California, Santa Barbara, 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","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Technical Memorandum No. ENV-2021-001","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Bureau of Reclamation","collaboration":"U.S. Bureau of Reclamation, U.S. Geological Survey, University of Arizona","usgsCitation":"McGuire, M., Gangopadhyay, S., Martin, J.T., Pederson, G.T., Woodhouse, C.A., and Littell, J., 2021, Water reliability in the west -- SECURE Water Act Section 9503(C), 60 p.","productDescription":"60 p.","ipdsId":"IP-124595","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":384933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":384913,"type":{"id":15,"text":"Index Page"},"url":"https://www.usbr.gov/climate/secure/2021secure.html"}],"country":"United 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gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":813689,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":813690,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":813691,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219301,"text":"ofr20211012 - 2021 - Implementation plan for the southern Pacific Border and Sierra-Cascade Mountains provinces","interactions":[],"lastModifiedDate":"2021-04-06T11:29:46.334003","indexId":"ofr20211012","displayToPublicDate":"2021-04-05T07:36:00","publicationYear":"2021","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":"2021-1012","displayTitle":"Implementation Plan for the Southern Pacific Border and Sierra-Cascade Mountains Provinces","title":"Implementation plan for the southern Pacific Border and Sierra-Cascade Mountains provinces","docAbstract":"The National Cooperative Geologic Mapping Program (NCGMP) is publishing a strategic plan titled Renewing the National Cooperative Geologic Mapping Program as the Nation’s Authoritative Source for Modern Geologic Knowledge (Brock and others, in press). The plan provides a vision, mission, and goals for the program during the years 2020–2030, which are:
In order to achieve the goals outlined in the strategic plan, the NCGMP has developed an implementation plan. This plan will guide the annual review of projects carried out by USGS staff (FEDMAP) described in the plan and the development of the annual FEDMAP prospectus that will ensure the effective application of the NCGMP strategy.
This publication describes the implementation plan of the NCGMP strategy for the southern Pacific Border and Sierra-Cascade Mountains provinces, as defined by Fenneman (1917, 1928, and 1946). This implementation plan focuses on the geology of California and a sliver of Nevada surrounding Lake Tahoe. The southern Pacific Border and Sierra-Cascade Mountains provinces encompass the varied landscapes of the high Sierra Nevada, the Central Valley, and Coast Ranges in northern and central California and the Peninsular Ranges, Continental Borderland, Los Angeles Basin-San Gabriel-San Bernardino valleys, western and central Transverse Ranges, and northernmost Salton Trough in southern California. Societal demands create a need for earth-science data in each of these landscapes. The broader San Francisco Bay area, Central Valley, Los Angeles-San Gabriel-San Bernardino lowlands, and the coastal lowlands that border the Peninsular Ranges are densely populated (about 30 million people) areas at high risk of natural hazards. The mountains of the Sierra Nevada, Peninsular Ranges, and Transverse Ranges, and the coast all provide numerous recreational opportunities that attract visitors from around the world, whereas previously these ranges attracted people to mine their resources. The agricultural capacity of the Central Valley is a critical resource for the Nation that is increasingly water limited.
The southern. Pacific Border and Sierra-Cascade Mountains provinces, at the edge of the North American continent, were profoundly influenced by subduction zone tectonics during the Mesozoic and early Cenozoic (ongoing in northernmost California) and subsequently by the inception, development, and present activity of the San Andreas transform margin system. Although the geology of this region is the poster child of fundamental conceptual models of subduction zone complexes, forearc basins, ophiolite obductions, magmatic arcs, and suspect terranes, as well as hosting one of Earth’s most notorious continental transform faults—the San Andreas Fault—important questions that have important societal consequences remain to be answered. Most of California’s population reside in these provinces and live within 30 miles of an active fault (according to www.earthquakeauthority.com) yet new faults continue to be discovered, highlighting the importance of deformation off the main San Andreas Fault. Bedrock, surficial, and three-dimensional (3D) geologic maps depicting stratigraphic structure and depth to crystalline basement rocks provide critical context and information for understanding fault rupture, distributed deformation, fault connectivity, and history in addition to providing crucial data that enable forecasting of shaking amplitude and length from hypothetical earthquake scenarios.
The tectonic evolution of California produced not only stunning mountains, with associated hazards from landslides and active volcanoes, but also fertile valleys that make California the top agricultural producer in the country in terms of cash receipts (according to www.ers.usda.gov/faqs). These valleys lie atop large basins that not only store groundwater but, in many cases, host oil and gas fields, contributing to the fourth highest hydrocarbon production by State in the country in 2016 (according to https://www.aei.org/carpe-diem/animated-chart-of-us-oil-production-by-state-1981-2017). Water is a key resource increasingly stressed by growing agricultural, industrial, and residential needs. Warmer and drier conditions have led to an increased reliance on extracting groundwater resources, whose availability and quality are dictated at the first order by the 3D spatial distribution of bedrock and Quaternary surficial deposits. Thus, assessment of this critical resource is inextricably tied to knowledge of the surficial and subsurface geologic structure and material types.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211012","usgsCitation":"Langenheim, V.E., Graymer, R.W., Powell, R.E., Schmidt, K.M., and Sweetkind, D.S., 2021, Implementation plan for the southern Pacific Border and Sierra-Cascade Mountains provinces: U.S. Geological Survey Open-File Report 2021–1012, 11 p., https://doi.org/10.3133/ofr20211012.","productDescription":"iv, 11 p.","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-121693","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":384840,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1012/ofr20211012.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384839,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1012/covrthb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.26855468749999,\n 32.69486597787505\n ],\n [\n -117.20214843749999,\n 34.415973384481866\n ],\n [\n -116.806640625,\n 36.491973470593685\n ],\n [\n -119.35546875000001,\n 38.34165619279595\n ],\n [\n -119.3115234375,\n 39.30029918615029\n ],\n [\n -120.10253906249999,\n 40.212440718286466\n ],\n [\n -121.86035156249999,\n 42.06560675405716\n ],\n [\n -124.3212890625,\n 42.06560675405716\n ],\n [\n -124.541015625,\n 40.51379915504413\n ],\n [\n -123.70605468750001,\n 38.71980474264237\n ],\n [\n -122.607421875,\n 37.19533058280065\n ],\n [\n -121.59667968749999,\n 35.817813158696616\n ],\n [\n -120.58593749999999,\n 34.45221847282654\n ],\n [\n -117.94921874999999,\n 33.54139466898275\n ],\n [\n -117.2900390625,\n 32.54681317351514\n ],\n [\n -115.26855468749999,\n 32.69486597787505\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
Using a before-after study design in a stable, largely undisturbed pond habitat and a dataset spanning 33 years, we document and describe the decline of native Sonora mud turtles (Kinosternon sonoriense) after the introduction of non-native pond sliders (Trachemys scripta). The Sonora mud turtle population in Montezuma Well in central Arizona, USA, declined to less than 25% of previous numbers, from 372 ± 64 in 1983 to 80 ± 21 in 2011. We trapped and removed the non-native turtles between 2007 and 2012 and after removal of the non-natives, the Sonora mud turtle population increased to 139 ± 34 in 2015. The native turtles also significantly increased basking activity after removal of the non-natives, paralleling results of small-scale mesocosm studies showing that pond sliders negatively affect basking rates of native turtle species. Reproductive rates of female Sonora mud turtles (numbers of females with eggs) were lower during the period of peak non-native turtle abundance, and increased after removal of the non-native turtles. We hypothesize that the reduction in effective reproductive rate links interference competition (reflected in reduced basking rates) to the long-term decline of the native mud turtles. Results from the undisturbed natural system of Montezuma Well provide new insights on the overall occurrence, magnitude, and mechanisms of negative effects of introduced pond sliders on native turtle species. Sonora mud turtles are very different in their morphology, behavior, and ecology from pond sliders and from native turtles in other studies, suggesting that impacts of non-native pond sliders are more pervasive than previously thought.
","language":"English","publisher":"Reabic","doi":"10.3391/ai.2021.16.3.10","usgsCitation":"Drost, C.A., Lovich, J.E., Rosen, P.C., Malone, M., and Garber, S.D., 2021, Non-native Pond Sliders cause long-term decline of native Sonora Mud Turtles: A 33-year before-after study in an undisturbed natural environment: Aquatic Invasions, v. 16, no. 3, p. 542-570, https://doi.org/10.3391/ai.2021.16.3.10.","productDescription":"29 p.","startPage":"542","endPage":"570","ipdsId":"IP-101856","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":452811,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2021.16.3.10","text":"Publisher Index Page"},{"id":436421,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EL65UI","text":"USGS data release","linkHelpText":"Sonora Mud Turtles and non-native turtles, Montezuma Well, Yavapai County, Arizona, 1983 - 2015"},{"id":387893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":821113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":821114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosen, Philip C.","contributorId":70311,"corporation":false,"usgs":true,"family":"Rosen","given":"Philip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":821132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malone, Matthew","contributorId":264216,"corporation":false,"usgs":false,"family":"Malone","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":821133,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garber, Steven D.","contributorId":264217,"corporation":false,"usgs":false,"family":"Garber","given":"Steven","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":821134,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229019,"text":"70229019 - 2021 - Climate change may cause shifts in growth and instantaneous natural mortality of American Shad throughout their native range","interactions":[],"lastModifiedDate":"2022-02-25T13:01:46.692613","indexId":"70229019","displayToPublicDate":"2021-04-05T06:57:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Climate change may cause shifts in growth and instantaneous natural mortality of American Shad throughout their native range","docAbstract":"American Shad Alosa sapidissima is an anadromous species with populations ranging along the U.S. Atlantic coast. Past American Shad stock assessments have been data limited and estimating system-specific growth parameters or instantaneous natural mortality (M) was not possible. This precluded system-specific stock assessment and management due to reliance on these parameters for estimating other population dynamics (such as yield per recruit). Furthermore, climate-informed biological reference points remain a largely unaddressed need in American Shad stock assessment. Population abundance estimates of American Shad and other species often rely heavily on M derived from von Bertalanffy growth function (VBGF) parameters. Therefore, we developed Bayesian hierarchical models to estimate coastwide, regional, and system-specific VBGF parameters and M using data collected from 1982 to 2017. We tested predictive performance of models that included effects of various climate variables on VBGF parameters within these models. System-specific models were better supported than regional or coast-wide models. Mean asymptotic length (L∞) decreased with increasing mean annual sea surface temperature (SST) and degree days (DD) experienced by fish during their lifetime. Although uncertain, K (Brody growth coefficient) decreased over the same range of lifetime SST and DD. Assuming no adaptation, we projected changes in VBGF parameters and M through 2099 using modeled SST from two climate projection scenarios (Representative Concentration Pathways 4.5 and 8.5). We predicted reduced growth under both scenarios, and M was projected to increase by about 0.10. It is unclear how reduced growth and increased mortality may influence population productivity or life history adaptation in the future, but our results may inform stock assessment models to assess those trade-offs.
Groundwater provides nearly 50 percent of the Nation’s drinking water. To help protect this vital resource, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Project assesses groundwater quality in aquifers that are important sources of drinking water. The Colorado Plateaus aquifers constitute one of the important areas being evaluated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213012","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Degnan, J.R., and Musgrove, M., 2021, Groundwater quality in the Colorado Plateaus aquifers, western United States: U.S. Geological Survey Fact Sheet 2021–3012, 4 p., https://doi.org/10.3133/fs20213012.","productDescription":"Report: 4 p.; Data Release","numberOfPages":"4","ipdsId":"IP-117821","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":384828,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XATXV1","linkHelpText":"Datasets of groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January 2017 through December 2019 (ver. 1.1, January 2021)"},{"id":384827,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3012/fs20213012.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384826,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3012/covrthb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.6875,\n 33.063924198120645\n ],\n [\n -105.64453124999999,\n 34.161818161230386\n ],\n [\n -105.16113281249999,\n 36.70365959719456\n ],\n [\n -105.0732421875,\n 37.78808138412046\n ],\n [\n -105.5126953125,\n 38.51378825951165\n ],\n [\n -104.94140625,\n 39.027718840211605\n ],\n [\n -105.205078125,\n 40.38002840251183\n ],\n [\n -106.3916015625,\n 42.71473218539458\n ],\n [\n -107.841796875,\n 43.13306116240612\n ],\n [\n -110.390625,\n 42.61779143282346\n ],\n [\n -110.9619140625,\n 40.94671366508002\n ],\n [\n -109.6875,\n 40.64730356252251\n ],\n [\n -110.9619140625,\n 39.87601941962116\n ],\n [\n -112.763671875,\n 37.23032838760387\n ],\n [\n -113.115234375,\n 36.73888412439431\n ],\n [\n -111.22558593749999,\n 36.4566360115962\n ],\n [\n -111.6650390625,\n 33.211116472416855\n ],\n [\n -109.6875,\n 33.063924198120645\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NAWQA Chief Scientist
National Water-Quality Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 413
Reston, VA 20192-0002
Groundwater provides nearly 50 percent of the Nation’s drinking water. To help protect this vital resource, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Project assesses groundwater quality in aquifers that are important sources of drinking water. The Stream Valley aquifers constitute one of the important aquifer systems being evaluated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213011","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Kingsbury, J.A., 2021, Groundwater quality in selected Stream Valley aquifers, western United States: U.S. Geological Survey Fact Sheet 2021–3011, 4 p., https://doi.org/10.3133/fs20213011.","productDescription":"Report: 4 p.; Data Release","numberOfPages":"4","ipdsId":"IP-117820","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":384825,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XATXV1","linkHelpText":"Datasets of groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January 2017 through December 2019 (ver. 1.1, January 2021)"},{"id":384824,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3011/fs20213011.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384823,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3011/covrthb.jpg"}],"country":"United States","state":"Colorado, Kansas, Missouri, Nebraska, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.615234375,\n 38.993572058209466\n ],\n [\n -92.98828125,\n 39.774769485295465\n ],\n [\n -94.5703125,\n 39.639537564366684\n ],\n [\n -95.49316406249999,\n 40.3130432088809\n ],\n [\n -97.0751953125,\n 42.97250158602597\n ],\n [\n -104.0625,\n 43.068887774169625\n ],\n [\n -104.1064453125,\n 40.94671366508002\n ],\n [\n -106.435546875,\n 39.470125122358176\n ],\n [\n -106.12792968749999,\n 38.09998264736481\n ],\n [\n -104.67773437499999,\n 37.020098201368114\n ],\n [\n -102.87597656249999,\n 36.94989178681327\n ],\n [\n -99.755859375,\n 36.73888412439431\n ],\n [\n -99.8876953125,\n 35.31736632923788\n ],\n [\n -96.5478515625,\n 33.94335994657882\n ],\n [\n -94.6142578125,\n 36.94989178681327\n ],\n [\n -94.52636718749999,\n 38.30718056188316\n ],\n [\n -91.2744140625,\n 38.54816542304656\n ],\n [\n -90.4833984375,\n 38.61687046392973\n ],\n [\n -90.615234375,\n 38.993572058209466\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NAWQA Chief Scientist
National Water-Quality Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 413
Reston, VA 20192-0002
Groundwater provides nearly 50 percent of the Nation’s drinking water. To help protect this vital resource, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Project assesses groundwater quality in aquifers that are important sources of drinking water. The Edwards-Trinity aquifer system constitutes one of the important aquifers being evaluated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213010","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Musgrove, M., 2021, Groundwater quality in the Edwards-Trinity aquifer system: U.S. Geological Survey Fact Sheet 2021–3010, 4 p., https://doi.org/10.3133/fs20213010.","productDescription":"Report: 4 p.; Data Release","numberOfPages":"4","ipdsId":"IP-117819","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":384821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3010/fs20213010.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3010/covrthb.jpg"},{"id":384822,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XATXV1","linkHelpText":"Datasets of groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January 2017 through December 2019 (ver. 1.1, January 2021)"}],"country":"United States","state":"Arkansas, Oklahoma, Texas","otherGeospatial":"Edwards-Trinity Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.546875,\n 28.93124697186731\n ],\n [\n -98.052978515625,\n 29.31514119318728\n ],\n [\n -97.086181640625,\n 30.467614102257855\n ],\n [\n -96.04248046875,\n 31.644028945047822\n ],\n [\n -95.328369140625,\n 32.90726224488304\n ],\n [\n -94.031982421875,\n 33.687781758439364\n ],\n [\n -93.14208984375,\n 33.779147331286474\n ],\n [\n -92.515869140625,\n 34.08906131584994\n ],\n [\n -93.878173828125,\n 34.65128519895413\n ],\n [\n -95.9326171875,\n 34.397844946449865\n ],\n [\n -97.283935546875,\n 34.252676117101515\n ],\n [\n -98.69018554687499,\n 33.137551192346145\n ],\n [\n -99.51416015625,\n 32.37068286611427\n ],\n [\n -101.348876953125,\n 32.045332838858506\n ],\n [\n -104.578857421875,\n 31.644028945047822\n ],\n [\n -103.216552734375,\n 30.401306519203583\n ],\n [\n -101.326904296875,\n 29.878755346037977\n ],\n [\n -100.546875,\n 28.93124697186731\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NAWQA Chief Scientist
National Water-Quality Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 413
Reston, VA 20192-0002
In the face of global change, understanding causes of range limits are one of the most pressing needs in biogeography and ecology. A prevailing hypothesis is that abiotic stress forms cold (upper latitude/altitude) limits, whereas biotic interactions create warm (lower) limits. A new framework – Interactive Range-Limit Theory (iRLT) – asserts that positive biotic factors such as food availability can ameliorate abiotic stress along cold edges, whereas abiotic stress can have a positive effect and mediate biotic interactions (e.g., competition) along warm limits.
Northeastern United States
Carnivora
We evaluated two hypotheses of iRLT using occupancy and structural equation modeling (SEM) frameworks based on data collected over a 6-year period (2014–2019) of six carnivore species across a broad latitudinal (42.8–45.3°N) and altitudinal (3–1451 m) gradient.
We found that snow directly limits populations, but prey or habitat availability can influence range dynamics along cold edges. For example, bobcats (Lynx rufus) and coyotes (Canis latrans) were limited by deep snow and long winters, but the availability of prey had a strong positive effect. Conversely, snow had a strong positive effect on the warm limits of Canada lynx (Lynx canadensis), countering the negative effect of competition with the phylogenetically similar bobcat and with coyotes, highlighting how climate mediates competition between species.
We used an integrated dataset that included competitors and prey species collected at the same spatial and temporal scale. As such, this design, along with a causal modeling framework (SEM), allowed us to evaluate community-wide hypotheses at macroecological scales and identify coarse-scale drivers of species' range limits. Our study supports iRLT and underscores the need to consider direct and indirect mechanisms for studying range dynamics and species' responses to global change.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.14112","usgsCitation":"Siren, A., Sutherland, C., Bernier, C., Royar, K., Kilborn, J.R., Callahan, C., Cliche, R., Prout, L.S., and Morelli, T.L., 2021, Abiotic stress and biotic factors mediate range dynamics on opposing edges: Journal of Biogeography, v. 48, no. 7, p. 1758-1772, https://doi.org/10.1111/jbi.14112.","productDescription":"15 p.","startPage":"1758","endPage":"1772","ipdsId":"IP-125344","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":452813,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.14112","text":"Publisher Index Page"},{"id":410693,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.47563781677009,\n 45.75938677061683\n ],\n [\n -74.47563781677009,\n 42.221428132868596\n ],\n [\n -69.90726541446244,\n 42.221428132868596\n ],\n [\n -69.90726541446244,\n 45.75938677061683\n ],\n [\n -74.47563781677009,\n 45.75938677061683\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Siren, Alexej P. 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Tamarisk thrives in today’s human-altered streamside (riparian) habitats and can be found along wetlands, rivers, lakes, and streams across the western U.S. In 2001, a biological control agent, Diorhabda spp. (tamarisk leaf beetle), was released in six states, and has since spread throughout the southwestern U.S. and northern Mexico. Beetle defoliation of tamarisk has altered tamarisk’s water use and effectiveness as erosion control, as well as dynamics of native and nonnative plant and wildlife species. The full effects of the tamarisk leaf beetle on ecosystem function remain unknown. The U.S. Geological Survey collaborates with Tribal, State, Federal agencies, and other institutions to provide current, fact-based information on the effects of tamarisk and the tamarisk leaf beetle on managed resources, and provides sound science for conservation and restoration of riparian habitats in the southwestern U.S.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203061","usgsCitation":"Nagler, P.L., Hull, J.B., van Riper, C., Shafroth, P.B., and Yackulic, C.B., 2021, The Transformation of dryland rivers: The future of introduced tamarisk in the U.S.: U.S. Geological Survey Fact Sheet 2020–3061, 6 p., https://doi.org/10.3133/fs20203061.","productDescription":"6 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-122043","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":384841,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3061/covrthb.jpg"},{"id":384842,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3061/fs20203061.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United 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Intrusion whole-rock geochemistry and phenocryst and/or mineral trace element compositions coupled with new zircon U-Pb geo-chronology and zircon in situ Lu-Hf isotopes document distinct pulses of magma from beneath the caldera complex. Fourteen intrusions, the Chiquito Peak Tuff, and the dacite of Fisher Gulch were dated, showing intrusive magmatism began after the 28.8 Ma eruption of the Chiquito Peak Tuff and continued to 24 Ma. Additionally, magmatic-hydrothermal mineralization is associated with the intrusive magmatism within and around the margins of the Platoro caldera complex.
After caldera collapse, three plutons were emplaced within the subsided block between ca. 28.8 and 28.6 Ma. These have broadly similar modal miner-alogy and whole-rock geochemistry. Despite close temporal relations between the tuff and the intrusions, mineral textures and compositions indicate that the larger two intracaldera intrusions are discrete later pulses of magma. Intrusions outside the caldera are younger, ca. 28–26.3 Ma, and smaller in exposed area. They contain abundant glomerocrysts and show evidence of open-system processes such as magma mixing and crystal entrainment. The protracted magmatic history at the Platoro caldera complex documents the diversity of the multiple discrete magma pulses needed to generate large composite volcanic fields.
Pollination of crops and naturally-occurring flowering plants is a critical ecosystem service provided by managed and unmanaged animal pollinators. Insects are the most studied pollinators, particularly managed honey bees, unmanaged wild bees, and butterflies. Bees and butterflies thrive in early-successional habitat featuring grasses, exposed soil, wildflowers, and shrubs, which is consistently found within transportation and utility rights-of-way (ROW). However, intensive management of ROW can reduce the amount of high-quality pollinator habitat; such practices include frequent mowing, broadcast herbicide use, and planting non- native cool season grasses. Here, we review peer-reviewed academic and non-peer reviewed gray literature describing ROW management practices and their effects on pollinator populations, focusing on applications of these practices in landscapes similar to those found in Maine and the northeast United States; that is, landscapes that are heavily forested and interspersed with agriculture, developed areas, and wetlands. The literature consistently recommends these management practices to provide pollinator habitat in ROW and promote plant and pollinator diversity and abundance:
1) Reduce mowing frequency and time mowing to pollinator activity.
2) Target herbicide applications to undesirable plant species using backpack sprayers.
3) Plant native seeds, seedlings, or shrubs, leaving some exposed soil for nesting.
We considered threats to plants and pollinators associated with ROW, including traffic volume and mortality, noise, light, and air pollution, and habitat fragmentation. The literature suggests that these threats vary widely across road sizes, types, and landscape context, and the overall negative impacts do not outweigh the potential benefits of promoting pollinator habitat in ROW. Landscape context also influences the composition of ROW plant and pollinator communities. In Maine, agriculture and grassland in the surrounding generally reduced bumble bee and butterfly abundance in Priority 1 ROW sites. Many state Departments of Transportation have incorporated integrative vegetation management (IVM) principles into ROW management, and we summarize a number of case studies here. Restoration projects in high-visibility areas are common; further, these can lead to public support for additional pollinator habitat enhancement. Implementing new management practices can be difficult, therefore we discuss strategies to aid in successful adoption, including gathering public support, collaborations between public and private agencies, and innovative funding opportunities. While assessing vegetation management impacts on bee and butterfly communities in ROW is a rapidly expanding area of research, there are still many gaps in current knowledge. We conclude this report by addressing these gaps and provide suggestions for further study.
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Maine","active":true,"usgs":false}],"preferred":false,"id":923636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923633,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240861,"text":"70240861 - 2021 - Middle Holocene hydrologic changes catalyzed by river avulsion in Big Soda Lake, Nevada, USA","interactions":[],"lastModifiedDate":"2023-02-27T20:12:21.152859","indexId":"70240861","displayToPublicDate":"2021-04-01T13:56:48","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Middle Holocene hydrologic changes catalyzed by river avulsion in Big Soda Lake, Nevada, USA","docAbstract":"Big Soda Lake is a 63 m deep, 1.6 km2 maar lake in the Great Basin of Nevada, USA. Water level in the lake is controlled by groundwater inputs from the surrounding aquifer and the only surface water input is rainfall, which is negligible. A core taken in 2010 records an 8.75 m depositional history of the lake. A radiocarbon date on fossil pollen from 8.4 m below the sediment water interface (BSWI) of 14,740 (+1120/−825) cal yr BP suggests that the core may cover the latest Pleistocene and Holocene depositional history of the lake. Stable isotope values of oxygen and carbon (δ18O and δ13C) on authigenic calcite, diatom assemblages, and sedimentary structures all show consistent hydrological change from initially saline water at the bottom of the core to fresh/brackish water at about 6 m BWSI, back to saline water at 4.3 m. At 4.3 m depth, the bedding and color of the core change abruptly, and the stable- isotope and diatom assemblages indicate a consistently hypersaline lake until near the top of the core, when fresh water entered the lake due to irrigation and canal building in the twentieth century. The stable isotopes of the calcite abruptly change from inversely varying isotopic compositions below 4.3 m depth to covarying above. This break between relatively fresh and saline conditions in the lake occurs during the middle Holocene, although the exact timing of the transition is unknown due to variability in the 14C age determinations. The cause for such an abrupt change is difficult to explain through climate shifts, as evidence suggests climate in the Great Basin was different from what the Big Soda Lake record indicates in the Early Holocene. It is hypothesized that the Walker River flowed to the Carson River basin before 5600 cal yr BP, with water either flowing directly into the lake or raising the groundwater table sufficiently to freshen Big Soda Lake. The initial increase in salinity likely was caused by decreased flow of the Walker River due to Middle Holocene aridity. The lake level lowered slowly, and more saline conditions prevailed until 4.3 m depth when water from the Walker River stopped flowing into the Carson River basin. Above 4.3 m depth, diatom and isotopic evidence indicates that the lake became consistently saline. The isotopic and diatom assemblage transitions observed in Big Soda Lake sediment are not consistent with climate reconstructions and demonstrate that hydrologic shifts in a basin can be an important driver of change regardless of climatic conditions. However, climate shifts may also play a role in the hydrologic changes by supplying more or less water to river courses that may induce river avulsion.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Limnogeology: Progress, challenges and opportunities: A tribute to Elizabeth Gierlowski-Kordesch","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-66576-0_10","usgsCitation":"Rosen, M., Reidy, L.M., Starratt, S.W., and Zimmerman, S., 2021, Middle Holocene hydrologic changes catalyzed by river avulsion in Big Soda Lake, Nevada, USA, chap. of Limnogeology: Progress, challenges and opportunities: A tribute to Elizabeth Gierlowski-Kordesch, p. 295-328, https://doi.org/10.1007/978-3-030-66576-0_10.","productDescription":"34 p.","startPage":"295","endPage":"328","ipdsId":"IP-109894","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":436422,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9INH1ID","text":"USGS data release","linkHelpText":"Mineralogic, grain-size, biologic, and stable isotopic analyses of core TOPGUN-SODA10 2A-K from Big Soda Lake, Nevada, USA"},{"id":413426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Big Soda Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.87892835971928,\n 39.51788809213036\n ],\n [\n -118.8770297198971,\n 39.51835411876252\n ],\n [\n -118.87495847645494,\n 39.520218194026086\n ],\n [\n -118.87098859319025,\n 39.521849218843585\n ],\n [\n -118.86969406603852,\n 39.52288107190569\n ],\n [\n -118.86891734974776,\n 39.52690848070142\n ],\n [\n -118.86960776422836,\n 39.529504537764296\n ],\n [\n -118.87465642011955,\n 39.532200340442046\n ],\n [\n -118.87780643618821,\n 39.532200340442046\n ],\n [\n -118.87996398144054,\n 39.53123518854974\n ],\n [\n -118.88039549049098,\n 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This poses a challenge on determining when and where we should deploy measuring instruments (e.g., in-situ sensors) to collect labeled data efficiently. This problem differs from traditional pool-based active learning settings in that the labeling decisions have to be made immediately after we observe the input data that come in a time series. In this paper, we develop a real-time active learning method that uses the spatial and temporal contextual information to select representative query samples in a reinforcement learning framework. To reduce the need for large training data, we further propose to transfer the policy learned from simulation data which is generated by existing physics-based models. We demonstrate the effectiveness of the proposed method by predicting streamflow and water temperature in the Delaware River Basin given a limited budget for collecting labeled data. 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