Large volume rhyolitic ignimbrite volcanism is a significant contributor to the evolving crust. The introduction of high-silica material into the upper crust, differentiation within the middle crust, and partial melting in the lower crust contributes to geochemical and isotopic evolution of the crust. Developing accurate models for the genetic evolution of these events is dependent upon geochronology to determine rates of magmatic processes as model constraints. We present new zircon high-precision CA-ID-TIMS U-Pb geochronology and MC-ICPMS Hf isotope geochemistry for four ignimbrites from the nested caldera complex near Socorro, New Mexico (USA), within the Mogollon-Datil volcanic field. In agreement with past 40Ar-39Ar data, interpretations of new U-Pb data indicate eruptions from the Socorro caldera cluster were pulsed. These pulses were intermittently spaced, and a volcanic hiatus following the Hells Mesa Tuff at 33.442 ± 0.015 Ma was interrupted by four successive eruptions, beginning with the La Jencia Tuff at 29.158 ± 0.025 Ma and finishing with the South Canyon Tuff at 28.066 ± 0.021 Ma. Zircon age spectra became more protracted with each eruption, exhibiting age dispersions ranging from 0.347 Myr in the Hells Mesa Tuff to 4.502 Myr in the South Canyon Tuff. The increased dispersion is paralleled by an increase in the proportion of normally discordant grains, indicative of xenocryst incorporation. These protracted age spectra are not necessarily a function of thermal maturation in the middle to upper crust due to long-lived magma chambers. Rather, they are likely the result of increased melting of zircon-bearing lower crust due to deep thermal maturation from repeated juvenile magma injections based on the incorporation of zircon material at the melt source. In contrast, the Hf isotope record is volumetrically dominated by autocrystic zircon domains and becomes more radiogenic through time, recording juvenile replenishment of the lower crust during progressive melting. Together, these data record the protracted evolution of the lower crust sampled by ignimbrites, lend insight into that evolution, and emphasize the need for detailed interpretation of high-precision datasets to advance volcanic models.
Research Highlight: Davis, C. L., Walls, S. C., Barichivich, W. J., Brown, M. E., & Miller, D. A. (2022). Disentangling direct and indirect effects of extreme events on coastal wetland communities. Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.13874. Catastrophic events such as floods, hurricanes, winter storms, droughts and wildfires increasingly touch our lives either directly or indirectly. These events draw our attention to the seriousness of changes in climate not only to human well-being but also to the integrity of ecological systems upon which we depend. Understanding the impacts of extreme events on ecological systems requires the ability to characterize the cascading effects of environmental changes on the environments in which organisms live and the altered biological interactions produced. This scientific ambition represents no small challenge for the study of animal communities, which are typically difficult to census as well as dynamic in time and space. Davis et al. (2022) in a recent study in the Journal of Animal Ecology examined the amphibian and fish communities found in depressional coastal wetlands to better understand how they respond to major rainfall and flooding events. Data from the U.S. Geological Survey's Amphibian Research and Monitoring Initiative provided an 8-year record of observations as well as environmental measurements. For this study, the authors integrated techniques for assessing the dynamics of animal populations with a Bayesian implementation of structural equation modelling. Using their integrated methodological approach permitted the authors to reveal the direct and indirect effects of extreme weather events on co-occurring amphibian and fish communities while accounting for observational uncertainty and temporal variation in population-level processes. Their findings indicate that the most prominent effects of flooding on the amphibian community were caused by changes in the fish community that led to increased predation and resource competition. In their conclusions, the authors emphasize the importance of understanding networks of abiotic and biotic effects if we are to predict and mitigate the influence of extreme weather events.
This report addresses system characterization of the BlackSky Global satellites and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
The BlackSky Global satellites are three-band multispectral imagers (red, green, and blue multispectral bands plus a panchromatic band) with a 0.8- to 0.9-meter (m) pixel ground sample distance for the assessed satellites. BlackSky Global satellites 9 and 12–17 were launched in March and December 2021, respectively, into a Sun-synchronous orbit of 430–450 kilometers with an inclination of 42–53 degrees and a swath width of 6 kilometers at nadir. Each Global satellite has an expected lifetime of about 3 years. More information on the BlackSky Global satellites is available in the “Land Remote Sensing Satellites Online Compendium” (https://calval.cr.usgs.gov/apps/compendium) and from BlackSky at Real-Time Space-Based Intelligence (blacksky.com)
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior) and spatial performances. Results of these analyses indicate that the assessed BlackSky Global satellites have an interior geometric performance in the range of −0.011 m (−0.012 pixel) to 0.007 m (0.008 pixel) in easting and −0.018 m (−0.020 pixel) to 0.012 m (0.013 pixel) in northing in band-to-band registration; an exterior geometric performance using ground control points of 8.0-m circular error (95-percent certainty) for orthorectified products and 10.7- to 17.4-m circular error (95-percent certainty) for nonorthorectified products, depending on the geolocation metadata used; and a spatial performance in the range of 1.70 to 2.43 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.032 to 0.084.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030O","usgsCitation":"Vrabel, J.C., Anderson, C., Bresnahan, P.C., Christopherson, J.B., Clauson, J., Kim, M., Ryan, R.E., and Sampath, A., 2023, System characterization report on the BlackSky Global multispectral sensor (ver. 1.1, April 2024), chap. O of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 23 p., https://doi.org/10.3133/ofr20211030O.","productDescription":"Report: v, 23 p., Version History","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-150816","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":428109,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1030/o/versionHist.txt","text":"Version History","size":"1.33 kB","linkFileType":{"id":2,"text":"txt"}},{"id":417822,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/o/ofr20211030o.XML"},{"id":417821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/o/ofr20211030o.pdf","text":"Report","size":"3.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–O"},{"id":417820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/o/coverthb2.jpg"}],"edition":"Version 1.0: June 6, 2023; Version 1.1: April 29, 2024","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The U.S. Geological Survey (USGS) Bee Lab is a collaborative interagency joint venture and international leader for bee (Hymenoptera: Apoidea) identification, survey design, quantification of bee and plant interrelations, and development and maintenance of occurrence databases. Each of these objectives supports native bee conservation by providing critical data and tools for the United States and other countries. The Bee Lab is part of the USGS Eastern Ecological Science Center (EESC) and located in Laurel, Maryland, at the U.S. Fish and Wildlife Service (USFWS) Patuxent Research Refuge. The laboratory houses scientists from the EESC, USGS’s Cooperative Fish and Wildlife Research Units, and the USFWS to develop identification tools and survey design support for State, Federal, Tribal, and nongovernment organization partners. In addition to the development of identification tools, important objectives include developing keys for native and nonnative bee species and making those tools accessible to partners and the public. Among the most visible and reused products produced during the development of the tools are the detailed photographs of the bees themselves. Accurate bee identification allows for better monitoring of bee species and examination of environmental factors that may influence their populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233023","programNote":"Cooperative Research Units Program","usgsCitation":"Droege, S., Irwin, E., Malpass, J., and Mawdsley, J., 2023, The bee lab: U.S. Geological Survey Fact Sheet 2023–3023, 2 p., https://doi.org/10.3133/fs20233023.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-152934","costCenters":[{"id":203,"text":"Cooperative Research Unit Atlanta","active":false,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":417785,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3023/fs20233023.XML"},{"id":417784,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3023/images/"},{"id":417783,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233023/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 20230-3023"},{"id":417782,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3023/fs20233023.pdf","text":"Report","size":"8.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 20230-3023"},{"id":417781,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3023/coverthb.jpg"}],"contact":"Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, Maryland 20708
Species We Study: Pollinators
Contact Pubs Warehouse
The Delaware River Basin provides drinking water to 13.3 million people and supports endangered species, provides recreational opportunities, and is an essential resource to regional industries. The efforts of Federal and State governments have substantially improved overall water quality in the basin, which had been severely degraded prior to the mid-20th century. Recent trend analyses of water-quality data reveal negative and positive changes: increasing rates of salinization and improvements in nutrient conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233014","issn":"2327-6932","programNote":"Water Availability and Use Science Program","usgsCitation":"Shoda, M., Gain, E.G., and Murphy, J.C., 2023, River water quality in the Delaware River Basin—Concentrations and trends through 2018: U.S. Geological Survey Fact Sheet 2023–3014, 4 p., https://doi.org/10.3133/fs20233014.","productDescription":"Report: 4 p., 2 Data Releases","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-133306","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":417697,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3014/images/"},{"id":417699,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PX8LZO","text":"USGS—Multisource surface-water-quality data and U.S. Geological Survey streamgage match for the Delaware River Basin"},{"id":417695,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3014/fs20233014.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2023-3014 XML"},{"id":417694,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3014/fs20233014.pdf","size":"5.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3014"},{"id":417693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3014/coverthb.jpg"},{"id":417698,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KMWNJ5","text":"USGS—Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, water year 1978–2018"},{"id":417700,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225097","text":"USGS SIR 2022–5097"},{"id":417696,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233014/full","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3014 HTML"},{"id":499664,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114765.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.67732588371656,\n 38.47315961720821\n ],\n [\n -74.18382604899824,\n 38.47315961720821\n ],\n [\n -74.18382604899824,\n 42.626372631803235\n ],\n [\n -75.67732588371656,\n 42.626372631803235\n ],\n [\n -75.67732588371656,\n 38.47315961720821\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"For more information about this publication, contact
Program Coordinator
U.S. Geological Survey
Water Availability and Use Science Program
National Water Quality Program
Email: wausp-info@usgs.gov
For additional information, visit
https://www.usgs.gov/programs/national-water-quality-program
Elevation data are critical for assessments of coastal hazards, including sea-level rise (SLR), flooding, storm surge, tsunami impacts, and wave run-up. Previous research has demonstrated that the quality of data used in elevation-based hazard assessments must be well documented and applied properly to assess potential impacts. Global digital elevation models (DEMs), at 30- to 90-meter resolution, have been used extensively to map and characterize coastal environments and the at-risk resources (population and built structures) contained therein. The inherent absolute vertical accuracy of global DEMs precludes their usefulness for assessing exposure to fine increments (< 1 meter) of coastal inundation at high confidence levels. However, global DEMs are highly suitable for delineation of the global low elevation coastal zone (LECZ) (elevation < 10 meters). An accuracy evaluation of global DEMs over the United States has been conducted to quantify their performance in correctly mapping the LECZ, namely in terms of vertical uncertainty and corresponding confidence levels for several representations of the coastal zone. The evaluation approach includes comparison of the DEMs with an extensive set of high-accuracy geodetic control points as the independent reference data covering a variety of coastal relief settings. The 1-arc-second (30-meter) global DEMs evaluated include ALOS World 3D, ASTER GDEM, Copernicus, FABDEM, and NASADEM, and the 3-arc-second (90-meter) global DEMs include CoastalDEM, Copernicus, MERIT, and TanDEM-X. Additionally, lower resolution (1-kilometer) global DEMs were also assessed, namely the Global Lidar Lowland DTM (derived from ICESat-2) and the GEDI 1-km DEM. The results of the accuracy characterization show that FABDEM performs the best (minimal vertical bias and lowest vertical root mean square error) for high-confidence mapping of the LECZ. Among 90-m DEMs, CoastalDEM performs best, although the differences across datasets are minimal. The results also demonstrate the importance of rigorously accounting for elevation uncertainty when applying global DEMs for coastal mapping applications.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geomorphometry 2023 proceedings","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"Geomorphometry 2023","conferenceDate":"July 10-14, 2023","conferenceLocation":"Iasi, Romania","language":"English","publisher":"International Society for Geomorphometry","doi":"10.5281/zenodo.8011577","usgsCitation":"Gesch, D.B., 2023, Assessing global elevation models for mapping the low elevation coastal zone, in Geomorphometry 2023 proceedings, Iasi, Romania, July 10-14, 2023, 4 p., https://doi.org/10.5281/zenodo.8011577.","productDescription":"4 p.","ipdsId":"IP-152258","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":419309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":878927,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70244185,"text":"70244185 - 2023 - Neonicotinoid sunflower seed treatment, while not detected in pollen and nectar, still impacts wild bees and crop yield","interactions":[],"lastModifiedDate":"2023-06-07T14:21:55.839005","indexId":"70244185","displayToPublicDate":"2023-06-06T09:19:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14460,"text":"Agrochemicals","active":true,"publicationSubtype":{"id":10}},"title":"Neonicotinoid sunflower seed treatment, while not detected in pollen and nectar, still impacts wild bees and crop yield","docAbstract":"Neonicotinoid seed treatments are commonly used in agricultural production even though their benefit to crop yield and their impact on pollinators, particularly wild bees, remains unclear. Using an on-farm matched pair design in which half of each field was sown with thiamethoxam treated seed and half without, we assessed honey bee and wild bee exposure to pesticides in sunflower fields by analyzing pesticide residues in field soil, sunflower pollen and nectar, pollen-foraging and nec-tar-foraging honey bees, and a sunflower specialist wild bee (Melissodes agilis). We also quantified the effects of thiamethoxam-treated seed on wild bee biodiversity and crop yield. M. agilis abundance was significantly lower with thiamethoxam treatment and overall wild bee abundance trending lower but was not significantly different. Furthermore, crop yield was significantly lower in plots with thiamethoxam treatment, even though thiamethoxam was only detected at low concentrations in one soil sample (and its primary metabolite, clothianidin, was never detected). Conversely, wild bee richness was significantly higher and diversity was marginally higher with thiamethoxam treatment. Nectar volumes harvested from the nectar-foraging honey bees were also significantly higher with thiamethoxam treatment. Several pesticides that were not used in the sunflower fields were detected in our samples, some of which are known to be deleterious to bee health, highlighting the importance of the landscape scale in the assessment of pesticide exposure for bees. Overall, our results suggest that thiamethoxam seed treatments may negatively impact wild bee pollination services in sunflower. Importantly, this study highlights the advantages of the inclusion of other metrics, such as biodiversity or behavior, in pesticide risk analysis, as pesticide residue analysis, as an independent metric, may erroneously miss the impacts of field realistic pesticide exposure on bees.","language":"English","publisher":"MDPI","doi":"10.3390/agrochemicals2020018","usgsCitation":"Ward, L.T., Hladik, M.L., Guzman, A., Bautista, A., and Mills, N., 2023, Neonicotinoid sunflower seed treatment, while not detected in pollen and nectar, still impacts wild bees and crop yield: Agrochemicals, v. 2, no. 2, p. 279-295, https://doi.org/10.3390/agrochemicals2020018.","productDescription":"17 p.","startPage":"279","endPage":"295","ipdsId":"IP-132034","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":443172,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/agrochemicals2020018","text":"Publisher Index Page"},{"id":435292,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X3SP7F","text":"USGS data release","linkHelpText":"Pesticide concentrations in bees and other matrices collected from sunflower fields (with and without a neonicotinoid seed treatment) near Sacramento, California"},{"id":417913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Sacramento","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.75836841779504,\n 38.795715176727754\n ],\n [\n -121.75836841779504,\n 38.3032820529848\n ],\n [\n -121.16999959773764,\n 38.3032820529848\n ],\n [\n -121.16999959773764,\n 38.795715176727754\n ],\n [\n -121.75836841779504,\n 38.795715176727754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, Laura T.","contributorId":289488,"corporation":false,"usgs":false,"family":"Ward","given":"Laura","email":"","middleInitial":"T.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":874806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guzman, Aidee","contributorId":289489,"corporation":false,"usgs":false,"family":"Guzman","given":"Aidee","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":874808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bautista, Ariana","contributorId":289494,"corporation":false,"usgs":false,"family":"Bautista","given":"Ariana","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":874809,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, Nicholas","contributorId":289500,"corporation":false,"usgs":false,"family":"Mills","given":"Nicholas","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":874810,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70244187,"text":"70244187 - 2023 - Combining field observations and high-resolution numerical modeling to demonstrate the effect of coral reef roughness on turbulence and its implications for reef restoration design","interactions":[],"lastModifiedDate":"2023-06-07T14:17:43.502323","indexId":"70244187","displayToPublicDate":"2023-06-06T09:13:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Combining field observations and high-resolution numerical modeling to demonstrate the effect of coral reef roughness on turbulence and its implications for reef restoration design","docAbstract":"Coral reefs are effective natural barriers that protect adjacent coastal communities from hazards such as erosion and storm-induced flooding. However, the degradation of coral reefs compromises their ability to protect against these hazards, making degraded reefs a target for restoration. There have been limited field and numerical modeling studies conducted to understand how an increase in coral reef roughness, as would occur due to restoration, can affect wave energy dissipation for a range of real-world wave and water level conditions. To address this knowledge gap, field measurements were collected over adjacent low-roughness and high-roughness reefs off Molokaʻi, Hawaiʻi, USA, subjected to the same oceanographic forcing. Those field data were then used to calibrate and validate OpenFOAM computational fluid dynamics models of the reef. These calibrated models were then used to explore energy dissipation for a range of wave conditions based on measurements from a suite of existing datasets and values from the literature. In general, wave dissipation scales with incident wave conditions, where greater dissipation occurred for shallow depths and shorter-period waves. This tendency for short-period waves to be more readily attenuated is supported by wave energy dissipation factors in the range of 0.1–5, which decline with increasing wave period. Near-bed turbulent kinetic energy dissipation also scales with incident wave conditions, where the greatest difference in dissipation between low and high relief cases occurs for short wave periods. Turbulence becomes less affected by bottom roughness as the wave period increases. Based on this study, wave attenuation and turbulent energy dissipation could be enhanced by 0.5–1 order of magnitude (45% per across-shore meter) if the seabed roughness at the field site were increased by 13%, an achievable goal in coral reef restoration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2023.104331","usgsCitation":"Norris, B.K., Storlazzi, C.D., Pomeroy, A.W., Rosenberger, K.J., Logan, J.B., and Cheriton, O.M., 2023, Combining field observations and high-resolution numerical modeling to demonstrate the effect of coral reef roughness on turbulence and its implications for reef restoration design: Coastal Engineering, v. 184, 104331, 18 p., https://doi.org/10.1016/j.coastaleng.2023.104331.","productDescription":"104331, 18 p.","ipdsId":"IP-137643","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443176,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2023.104331","text":"Publisher Index Page"},{"id":435295,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P933TO2Q","text":"USGS data release","linkHelpText":"OpenFOAM models of low- and high-relief sites from the coral reef flat off Waiakane, Molokai, Hawaii"},{"id":435294,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HNLI7Y","text":"USGS data release","linkHelpText":"3D bathymetric surfaces of low- and high-relief sites from the coral reef flat off Waiakane, Molokai"},{"id":435293,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XZT1FK","text":"USGS data release","linkHelpText":"Aerial imagery and structure-from-motion-derived shallow water bathymetry from a UAS survey of the coral reef off Waiakane, Molokai, Hawaii, June 2018"},{"id":417912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Norris, Benjamin K 0000-0002-9133-5935","orcid":"https://orcid.org/0000-0002-9133-5935","contributorId":306089,"corporation":false,"usgs":true,"family":"Norris","given":"Benjamin","email":"","middleInitial":"K","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pomeroy, Andrew W. M.","contributorId":304433,"corporation":false,"usgs":false,"family":"Pomeroy","given":"Andrew","email":"","middleInitial":"W. M.","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":874820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","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":874821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874823,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70247384,"text":"70247384 - 2023 - Wave runup and inundation dynamics on a perched beach","interactions":[],"lastModifiedDate":"2023-08-01T14:43:36.324122","indexId":"70247384","displayToPublicDate":"2023-06-06T09:13:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Wave runup and inundation dynamics on a perched beach","docAbstract":"Sandy beaches perched over rocky shore platforms are common globally, yet their mixed sand and rocky morphology present challenges for quantifying and predicting wave runup and inundation. For typical linear beach profiles, simple relationships can be made between vertical runup and horizontal inundation based on beach slope. However, as topographic irregularities increase, substantial deviations from these relationships can occur. Shore platforms often experience a range of beach states, from full sand coverage (accreted) to complete shore platform erosion (exposed). As a result, existing methods for quantifying runup and inundation on purely sandy beaches are generally not directly applicable to these coastlines. To advance our understanding of runup and inundation on perched beaches, the aim of this work is three-fold: (1) to provide a method for quantifying beach slope and runup across a range of perched beach profiles, (2) to assess the relationship between vertical runup and horizontal inundation observations, and (3) to understand how different hydrodynamic mechanisms (i.e., setup, swash) contribute to runup during different beach states. To achieve this, we conducted an 8-month field study along a perched beach in southwestern Australia that experiences large seasonal variations in beach state and wave climate. A method was developed to measure runup and beach slope when only the topography shoreward of the shore platform edge was known. Using this method, an approximately linear relationship between inundation and runup was identified by incorporating beach slope. Our observations suggest that the components that dominate runup on perched beaches were primarily dependent on beach state (i.e., accreted versus exposed). Runup was dominated by swash in the infragravity band when in an accreted beach state, and setup when in an exposed beach state. These results aid our understanding of coastal processes on perched beaches, while providing new methods applicable to a range of perched beach profiles.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2023.108751","usgsCitation":"Portch, C., Cuttler, M., Buckley, M.L., Hansen, J., and Lowe, R., 2023, Wave runup and inundation dynamics on a perched beach: Geomorphology, v. 435, 108751, 17 p., https://doi.org/10.1016/j.geomorph.2023.108751.","productDescription":"108751, 17 p.","ipdsId":"IP-140579","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443178,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://research-repository.uwa.edu.au/en/publications/34488bfe-0539-470d-b6b2-b1172a214a86","text":"Publisher Index Page"},{"id":419473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 114.05497489313888,\n -30.071042453727458\n ],\n [\n 114.05497489313888,\n -36.351098064417805\n ],\n [\n 124.80921873141176,\n -36.351098064417805\n ],\n [\n 124.80921873141176,\n -30.071042453727458\n ],\n [\n 114.05497489313888,\n -30.071042453727458\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"435","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Portch, Carly","contributorId":317832,"corporation":false,"usgs":false,"family":"Portch","given":"Carly","email":"","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":879394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cuttler, Michael","contributorId":317833,"corporation":false,"usgs":false,"family":"Cuttler","given":"Michael","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":879395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":879396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Jeff","contributorId":317834,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":879397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowe, Ryan","contributorId":317835,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":879398,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248836,"text":"70248836 - 2023 - Progress in reducing nutrient and sediment loads to Chesapeake Bay: Three decades of monitoring data and implications for restoring complex ecosystems","interactions":[],"lastModifiedDate":"2023-09-22T12:09:23.21022","indexId":"70248836","displayToPublicDate":"2023-06-06T07:06:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5067,"text":"WIREs Water","active":true,"publicationSubtype":{"id":10}},"title":"Progress in reducing nutrient and sediment loads to Chesapeake Bay: Three decades of monitoring data and implications for restoring complex ecosystems","docAbstract":"For over three decades, Chesapeake Bay (USA) has been the focal point of a coordinated restoration strategy implemented through a partnership of governmental and nongovernmental entities, which has been a classical model for coastal restoration worldwide. This synthesis aims to provide resource managers and estuarine scientists with a clearer perspective of the magnitude of changes in water quality within the Bay watershed, including nitrogen (N), phosphorus (P), and sediment for the River Input Monitoring (RIM) watershed and the unmonitored below-RIM watershed. The flow-normalized N load from the RIM watershed has declined in the period of 1985–2017, but P and sediment loads have lacked progress. Reductions of riverine N are largely driven by reductions of point sources and atmospheric deposition. Future reductions will require significant progress in managing agricultural nonpoint sources. The below-RIM watershed, which comprises a disproportionately high fraction of inputs to the Bay, has shown long-term declines in major sources, including point sources (N and P), atmospheric deposition (N), manure (N and P) and fertilizer (P), based on a combination of monitoring and modeling assessments. To date, the Bay cleanup efforts have achieved some progress toward reducing nutrients from the watershed, which have resulted in improving water quality in the estuary. However, further reductions are critical to achieve the Chesapeake Bay Total Maximum Daily Load goals, and emerging challenges due to Conowingo Reservoir, legacy nutrients, climate change, and population growth should be considered. Continued monitoring, modeling, and assessment are critically important for informing the restoration of this complex ecosystem.
","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1671","usgsCitation":"Zhang, Q., Blomquist, J.D., Fanelli, R., Keisman, J.L., Moyer, D.L., and Langland, M.J., 2023, Progress in reducing nutrient and sediment loads to Chesapeake Bay: Three decades of monitoring data and implications for restoring complex ecosystems: WIREs Water, v. 15, no. 5, e1671, 20 p., https://doi.org/10.1002/wat2.1671.","productDescription":"e1671, 20 p.","ipdsId":"IP-134733","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":443182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wat2.1671","text":"Publisher Index Page"},{"id":421065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1904296875,\n 38.41916639395372\n ],\n [\n -75.223388671875,\n 38.64261790634527\n ],\n [\n -75.35522460937499,\n 38.79690830348427\n ],\n [\n -75.498046875,\n 38.87392853923629\n ],\n [\n -75.5419921875,\n 39.0533181067413\n ],\n [\n -75.662841796875,\n 39.30029918615029\n ],\n [\n -75.750732421875,\n 39.70718665682654\n ],\n [\n -75.6298828125,\n 40.052847601823984\n ],\n [\n -75.69580078125,\n 40.07807142745009\n ],\n [\n -75.95947265625,\n 40.052847601823984\n ],\n [\n -76.0693359375,\n 40.069664523297774\n ],\n [\n -76.058349609375,\n 40.18726672309203\n ],\n [\n -75.9375,\n 40.29628651711716\n ],\n [\n -75.91552734375,\n 40.3549167507906\n ],\n [\n -75.89355468749999,\n 40.47202439692057\n ],\n [\n -76.09130859375,\n 40.56389453066509\n ],\n [\n -76.190185546875,\n 40.64730356252251\n ],\n [\n -76.0693359375,\n 40.75557964275589\n ],\n [\n -75.83862304687499,\n 40.871987756697415\n ],\n [\n -75.76171875,\n 40.91351257612758\n ],\n [\n -75.706787109375,\n 40.95501133048621\n ],\n [\n -75.7177734375,\n 41.071069130806414\n ],\n [\n -75.662841796875,\n 41.1455697310095\n ],\n [\n -75.5419921875,\n 41.13729606112276\n ],\n [\n -75.322265625,\n 41.104190944576466\n ],\n [\n -75.377197265625,\n 41.22824901518529\n ],\n [\n -75.377197265625,\n 41.28606238749825\n ],\n [\n -75.377197265625,\n 41.43449030894922\n ],\n [\n -75.399169921875,\n 41.6154423246811\n ],\n [\n -75.34423828125,\n 41.68111756290652\n ],\n [\n -75.2783203125,\n 41.91045347666418\n ],\n [\n -75.38818359375,\n 42.00848901572399\n ],\n [\n -75.377197265625,\n 42.09007006868398\n ],\n [\n -75.223388671875,\n 42.17968819665961\n ],\n [\n -74.970703125,\n 42.26917949243506\n ],\n [\n -74.8388671875,\n 42.32606244456202\n ],\n [\n -74.520263671875,\n 42.415346114253616\n ],\n [\n -74.278564453125,\n 42.54498667313236\n ],\n [\n -74.322509765625,\n 42.64204079304426\n ],\n [\n -74.410400390625,\n 42.80346172417078\n ],\n [\n -74.68505859374999,\n 42.924251753870685\n ],\n [\n -75.069580078125,\n 42.98053954751642\n ],\n [\n -75.38818359375,\n 42.96446257387128\n ],\n [\n -75.684814453125,\n 42.93229601903058\n ],\n [\n -75.9375,\n 42.87596410238256\n ],\n [\n -76.201171875,\n 42.827638636242284\n ],\n [\n -76.26708984375,\n 42.72280375732727\n ],\n [\n -76.2890625,\n 42.601619944327965\n ],\n [\n -76.2890625,\n 42.52069952914966\n ],\n [\n -76.343994140625,\n 42.415346114253616\n ],\n [\n -76.46484375,\n 42.382894009614034\n ],\n [\n -76.640625,\n 42.431565872579185\n ],\n [\n -76.7724609375,\n 42.39912215986002\n ],\n [\n -76.80541992187499,\n 42.24478535602799\n ],\n [\n -76.88232421875,\n 42.285437007491545\n ],\n [\n -76.9482421875,\n 42.415346114253616\n ],\n [\n -77.04711914062499,\n 42.44778143462245\n ],\n [\n -77.14599609375,\n 42.415346114253616\n ],\n [\n -77.2998046875,\n 42.382894009614034\n ],\n [\n -77.222900390625,\n 42.54498667313236\n ],\n [\n -77.442626953125,\n 42.69858589169842\n ],\n [\n -77.574462890625,\n 42.60970621339408\n ],\n [\n -77.640380859375,\n 42.48830197960227\n ],\n [\n -77.728271484375,\n 42.439674178149424\n ],\n [\n -77.6513671875,\n 42.31793945446847\n ],\n [\n -77.596435546875,\n 42.22851735620852\n ],\n [\n -77.5634765625,\n 42.09007006868398\n ],\n [\n -77.6953125,\n 41.92680320648791\n ],\n [\n -77.9150390625,\n 41.83682786072714\n ],\n [\n -78.0908203125,\n 41.795888098191426\n ],\n [\n -78.453369140625,\n 41.599013054830216\n ],\n [\n -78.453369140625,\n 41.50857729743935\n ],\n [\n -78.42041015625,\n 41.376808565702355\n ],\n [\n -78.3984375,\n 41.21172151054787\n ],\n [\n -78.519287109375,\n 41.054501963290505\n ],\n [\n -78.541259765625,\n 40.9218144123785\n ],\n [\n -78.409423828125,\n 40.713955826286046\n ],\n [\n -78.299560546875,\n 40.55554790286311\n ],\n [\n -78.343505859375,\n 40.48873742102282\n ],\n [\n -78.475341796875,\n 40.30466538259176\n ],\n [\n -78.64013671875,\n 40.06125658140474\n ],\n [\n -78.826904296875,\n 39.9434364619742\n ],\n [\n -78.848876953125,\n 39.80853604144591\n ],\n [\n -78.85986328125,\n 39.715638134796336\n ],\n [\n -78.99169921875,\n 39.69873414348139\n ],\n [\n -79.046630859375,\n 39.64799732373418\n ],\n [\n -79.266357421875,\n 39.436192999314095\n ],\n [\n -79.420166015625,\n 39.2832938689385\n ],\n [\n -79.354248046875,\n 39.26628442213066\n ],\n [\n -79.266357421875,\n 39.232253141714885\n ],\n [\n -79.2333984375,\n 39.155622393423215\n ],\n [\n -79.244384765625,\n 39.01918369029134\n ],\n [\n -79.27734374999999,\n 38.89103282648846\n ],\n [\n -79.398193359375,\n 38.74551518488265\n ],\n [\n -79.661865234375,\n 38.54816542304656\n ],\n [\n -79.683837890625,\n 38.47079371120379\n ],\n [\n -79.727783203125,\n 38.34165619279595\n ],\n [\n -79.815673828125,\n 38.20365531807149\n ],\n [\n -80.04638671875,\n 38.013476231041935\n ],\n [\n -80.17822265625,\n 37.779398571318765\n ],\n [\n -80.2880859375,\n 37.59682400108367\n ],\n [\n -80.4638671875,\n 37.47485808497102\n ],\n [\n -80.694580078125,\n 37.38761749978395\n ],\n [\n -80.771484375,\n 37.23032838760387\n ],\n [\n -80.57373046875,\n 37.26530995561875\n ],\n [\n -80.44189453125,\n 37.309014074275915\n ],\n [\n -80.255126953125,\n 37.31775185163688\n ],\n [\n -80.013427734375,\n 37.3002752813443\n ],\n [\n -79.8486328125,\n 37.23907530202184\n ],\n [\n -79.771728515625,\n 37.18657859524883\n ],\n [\n -79.6728515625,\n 37.07271048132943\n ],\n [\n -79.541015625,\n 37.09900294387622\n ],\n [\n -79.354248046875,\n 37.142803443716836\n ],\n [\n -79.1455078125,\n 37.10776507118514\n ],\n [\n -79.112548828125,\n 37.055177106660814\n ],\n [\n -78.936767578125,\n 36.932330061503144\n ],\n [\n -78.837890625,\n 36.94111143010769\n ],\n [\n -78.662109375,\n 37.055177106660814\n ],\n [\n -78.486328125,\n 37.03763967977139\n ],\n [\n -78.42041015625,\n 36.94111143010769\n ],\n [\n -78.20068359374999,\n 36.96744946416934\n ],\n [\n -77.904052734375,\n 37.03763967977139\n ],\n [\n -77.750244140625,\n 37.081475648860525\n ],\n [\n -77.53051757812499,\n 37.081475648860525\n ],\n [\n -77.354736328125,\n 37.07271048132943\n ],\n [\n -77.069091796875,\n 37.081475648860525\n ],\n [\n -76.959228515625,\n 37.01132594307015\n ],\n [\n -76.893310546875,\n 36.932330061503144\n ],\n [\n -76.871337890625,\n 36.83566824724438\n ],\n [\n -76.849365234375,\n 36.677230602346214\n ],\n [\n -76.7724609375,\n 36.527294814546245\n ],\n [\n -76.629638671875,\n 36.55377524336089\n ],\n [\n -76.46484375,\n 36.589068371399115\n ],\n [\n -76.35498046875,\n 36.48314061639213\n ],\n [\n -76.256103515625,\n 36.57142382346277\n ],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Qian 0000-0003-0500-5655","orcid":"https://orcid.org/0000-0003-0500-5655","contributorId":174393,"corporation":false,"usgs":false,"family":"Zhang","given":"Qian","email":"","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":883837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blomquist, Joel D. 0000-0002-0140-6534","orcid":"https://orcid.org/0000-0002-0140-6534","contributorId":215461,"corporation":false,"usgs":true,"family":"Blomquist","given":"Joel","middleInitial":"D.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":206608,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keisman, Jennifer L. 0000-0001-6808-9193","orcid":"https://orcid.org/0000-0001-6808-9193","contributorId":274827,"corporation":false,"usgs":true,"family":"Keisman","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883840,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moyer, Douglas L. 0000-0001-6330-478X dlmoyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6330-478X","contributorId":174389,"corporation":false,"usgs":true,"family":"Moyer","given":"Douglas","email":"dlmoyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883841,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Langland, Michael J. 0000-0002-8350-8779","orcid":"https://orcid.org/0000-0002-8350-8779","contributorId":330001,"corporation":false,"usgs":false,"family":"Langland","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":883842,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254595,"text":"70254595 - 2023 - A Carboniferous apex for the late Paleozoic icehouse","interactions":[],"lastModifiedDate":"2024-06-04T11:47:40.559175","indexId":"70254595","displayToPublicDate":"2023-06-06T06:46:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"A Carboniferous apex for the late Paleozoic icehouse","docAbstract":"Title VII of Division N in the Consolidated Appropriations Act, 2023 (Public Law 117–328), was enacted on December 29, 2022. The U.S. Geological Survey received $41.04 million in disaster emergency supplemental funding for repairing and replacing facilities and equipment, collecting high-resolution elevation data in affected areas, and completing scientific assessments to support direct recovery and rebuilding decisions in the wake of declared disasters related to hurricanes and typhoons in 2022.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233025","usgsCitation":"Hinck, J.E., and Stachyra, J., 2023, Consolidated Appropriations Act, 2023—USGS disaster emergency recovery activities: U.S. Geological Survey Fact Sheet 2023–3025, 4 p., https://doi.org/10.3133/fs20233025.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"links":[{"id":417777,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3025/coverthb.jpg"},{"id":417778,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3025/fs20233025.pdf","text":"Report","size":"3.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023–3025"},{"id":417779,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3025/fs20233025.XML"}],"contact":"Associate Director, Natural Hazards Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey, in cooperation with the Suffolk County Water Authority, evaluated the groundwater-flow characteristics and aquifer properties of the North Magee Street well field north of the village of Southampton, New York. Characteristics and properties included groundwater-flow direction, potential groundwater-contributing areas to the well field production wells, and aquifer transmissivity and storage. The groundwater flow and aquifer properties were also evaluated to allow Suffolk County Water Authority to better assess the potential source of dissolved halocarbons (refrigerants, such as chlorofluorocarbons).
The well field production wells are screened in the upper glacial aquifer and an observation well is screened in the Magothy aquifer. Based on depth and available logs, groundwater from wells screened in the upper glacial aquifer was classified as under water-table (unconfined) conditions, and groundwater from wells screened in the Magothy aquifer was classified as being under semiconfined conditions.
Groundwater flows radially to the well field during production and in a northwesterly direction under the effect of the regional flow regime. A previously published particle tracking analysis identified the following recharge contributing areas nearby the well field: (1) contributing areas to surface-water bodies of the Peconic Estuary, (2) contributing areas to surface-water bodies of the South Shore Estuary Reserve, (3) a contributing area to the Atlantic Ocean, and (4) a contributing area to another Suffolk County Water Authority well field. Five other pumping well contributing areas were identified within the study area, including those of various wells pumped for golf-course irrigation.
Analysis of drawdown and recovery data collected during the multiple-well aquifer test, through the application of a Neuman analytical model, provided estimates of upper glacial aquifer characteristics and properties. Inclusion of lateral aquifer boundaries was not necessary for the analysis to result in satisfactory matches with the observed water-level responses. Aquifer transmissivity was estimated to be 170,000 feet squared per day. Storativity was estimated to be 0.02 (dimensionless), and specific yield was estimated to be 0.08 (dimensionless), consistent with the inferred degree of confinement and well field characteristics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231028","collaboration":"Prepared in cooperation with the Suffolk County Water Authority","usgsCitation":"Misut, P.E., 2023, Analysis of aquifer framework and properties, North Magee Street well field, Southampton, New York: U.S. Geological Survey Open-File Report 2023–1028, 14 p., https://doi.org/10.3133/ofr20231028.","productDescription":"Report: iv, 14 p.; Dataset","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-124210","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":499775,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114761.htm","linkFileType":{"id":5,"text":"html"}},{"id":417746,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the nation"},{"id":417745,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1028/images/"},{"id":417744,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1028/ofr20231028.XML"},{"id":417743,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231028/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1028"},{"id":417742,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1028/ofr20231028.pdf","text":"Report","size":"2.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1028"},{"id":417741,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1028/coverthb.jpg"}],"country":"United States","state":"New York","city":"Southampton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.43897301957882,\n 40.91839299249426\n ],\n [\n -72.43897301957882,\n 40.87699855750361\n ],\n [\n -72.37328061868494,\n 40.87699855750361\n ],\n [\n -72.37328061868494,\n 40.91839299249426\n ],\n [\n -72.43897301957882,\n 40.91839299249426\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Biogeographic history can set initial conditions for vegetation community assemblages that determine their climate responses at broad extents that land surface models attempt to forecast. Numerous studies have indicated that evolutionarily conserved biochemical, structural, and other functional attributes of plant species are captured in visible-to-short wavelength infrared, 400 to 2,500 nm, reflectance properties of vegetation. Here, we present a remotely sensed phylogenetic clustering and an evolutionary framework to accommodate spectra, distributions, and traits. Spectral properties evolutionarily conserved in plants provide the opportunity to spatially aggregate species into lineages (interpreted as “lineage functional types” or LFT) with improved classification accuracy. In this study, we use Airborne Visible/Infrared Imaging Spectrometer data from the 2013 Hyperspectral Infrared Imager campaign over the southern Sierra Nevada, California flight box, to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from 1372 surveys and a phylogeny representing 1,572 species. Despite temporal and spatial differences in our training data, we classified plant lineages with moderate reliability (Kappa = 0.76) and overall classification accuracy of 80.9%. We present an assessment of classification error and detail study limitations to facilitate future LFT development. This work demonstrates that lineage-based methods may be a promising way to leverage the new-generation high-resolution and high return-interval hyperspectral data planned for the forthcoming satellite missions with sparsely sampled existing ground-based ecological data.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2215533120","usgsCitation":"Griffith, D.M., Byrd, K.B., Anderegg, L., Allen, E., Gatziolis, D., Roberts, D.A., Yacoub, R., and Nemani, R., 2023, Capturing patterns of evolutionary relatedness with reflectance spectra to model and monitor biodiversity: Proceedings of the Natural Academy of Sciences, v. 120, no. 24, e2215533120, 8 p., https://doi.org/10.1073/pnas.2215533120.","productDescription":"e2215533120, 8 p.","ipdsId":"IP-133705","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":443193,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://escholarship.org/uc/item/57x530fd","text":"Publisher Index Page"},{"id":417780,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"24","noUsgsAuthors":false,"publicationDate":"2023-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Griffith, Daniel Mark 0000-0001-7463-4004","orcid":"https://orcid.org/0000-0001-7463-4004","contributorId":271033,"corporation":false,"usgs":true,"family":"Griffith","given":"Daniel","email":"","middleInitial":"Mark","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderegg, Lee","contributorId":305688,"corporation":false,"usgs":false,"family":"Anderegg","given":"Lee","email":"","affiliations":[{"id":66268,"text":"Department of Ecology, Evolution & Marine Biology, University of California Santa Barbara, Santa Barbara, CA 93106","active":true,"usgs":false}],"preferred":false,"id":873560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Elijah","contributorId":305689,"corporation":false,"usgs":false,"family":"Allen","given":"Elijah","email":"","affiliations":[{"id":65456,"text":"Shonto Chapter, Diné (Navajo) Nation","active":true,"usgs":false}],"preferred":false,"id":873561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gatziolis, Demetrios","contributorId":305690,"corporation":false,"usgs":false,"family":"Gatziolis","given":"Demetrios","email":"","affiliations":[{"id":66269,"text":"USDA Forest Service, PNW Research Station, Portland, OR 97205","active":true,"usgs":false}],"preferred":false,"id":873562,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roberts, Dar A.","contributorId":100503,"corporation":false,"usgs":false,"family":"Roberts","given":"Dar","email":"","middleInitial":"A.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":873563,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yacoub, Rosie","contributorId":305691,"corporation":false,"usgs":false,"family":"Yacoub","given":"Rosie","email":"","affiliations":[{"id":66271,"text":"California Dept. of Fish and Wildlife, Vegetation Classification and Mapping Program, Sacramento, CA 95811","active":true,"usgs":false}],"preferred":false,"id":873564,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nemani, Ramakrishna","contributorId":305692,"corporation":false,"usgs":false,"family":"Nemani","given":"Ramakrishna","affiliations":[{"id":66273,"text":"NASA Ames Research Center, Moffett Field, CA, 94035","active":true,"usgs":false}],"preferred":false,"id":873565,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70244095,"text":"ofr20231022 - 2023 - Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018","interactions":[],"lastModifiedDate":"2026-02-11T20:59:01.863472","indexId":"ofr20231022","displayToPublicDate":"2023-06-05T12:00:00","publicationYear":"2023","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":"2023-1022","displayTitle":"Distribution of Chlorinated Volatile Organic Compounds and Per- and Polyfluoroalkyl Substances in Groundwater and Surface Water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018","title":"Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018","docAbstract":"Groundwater wells and surface-water storm sewers contaminated with volatile organic compounds (VOCs) and per- and polyfluoroalkyl substances (PFASs) at the former Naval Air Warfare Center (NAWC) site in West Trenton, New Jersey were sampled in 2018 as part of the Navy’s long-term monitoring program. Trichloroethene (TCE), cis-1,2-dichloroethene (cisDCE), and vinyl chloride concentrations were plotted in map view and selected cross sections to elucidate the vertical and horizontal extent and distribution of contamination, along with a tabular comparison between 2018 and previous analytical results. The 2018 data showed that the areas of VOC contamination (>1 microgram per liter) decreased slightly on the north and east sides of the NAWC site from previous sampling dates; these decreases are attributed to the influence of the pump-and-treat system, natural attenuation processes, and various engineered bioaugmentation experiments that have occurred onsite. Off-site groundwater samples indicate the VOC contaminated groundwater is likely hydraulically constrained by the pump-and-treat system and appears to not be moving offsite to the south and west of NAWC. Only one offsite well, 50BR, located along the eastern margin of the site, was found to have detectable TCE and cisDCE concentrations, indicating that VOC contamination continues to migrate a short distance offsite to the east. Detectable VOC contamination was found in wells as deep as 200 and 221 feet on both the east and west sides of the NAWC site. Comparisons of present-day data to data from past sampling efforts indicate that TCE concentrations in most wells have decreased slowly over time.
Results from surface-water samples indicate that VOCs enter surface water predominantly through the West Ditch drainage system. Concentrations and fluxes of VOCs are higher when groundwater levels are higher, indicating contaminated groundwater discharges into the surface water system. Higher VOC concentrations at the Interceptor site relative to other sites in the West Ditch indicate the contamination in the West Ditch system is likely caused by contaminated groundwater discharging to the West Ditch storm sewer near manhole MH-140 when water table levels are high.
The pump-and-treat extraction wells at the former NAWC site were sampled for per- and polyfluoroalkyl substances (PFAS) in 2018. The suite of reported PFAS include perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid, and perfluorobutane sulfonate. Concentrations were plotted in map view to determine the areal extent of the PFAS contamination at the site. Extraction well 48BR sampled on the eastern half of the site was found to have PFOS and PFOA concentrations greater than the New Jersey Department of Environmental Protection Drinking Water maximum contaminant levels (MCLs), which is consistent with the distribution of highest PFAS concentrations in surface water in the OF-4 storm sewer system that drains that area, as well as previously collected PFAS concentrations in monitoring wells. On the western half of the site, the extraction well 08BR sample exceeded MCLs for PFOA and PFOS and the extraction well 22BR sample exceeded the MCL for PFOA, but samples from all other extraction wells were below the MCLs or other criteria for all PFAS analyzed. Concentrations of PFOA exceeded concentrations of PFOS on the west side of NAWC in both groundwater and surface water, which contrasts with the conditions on the east side of NAWC where PFOS concentrations exceeded PFOA concentrations. However, this observation was based on a limited number of samples on the west side of NAWC from 2018 and previous years, so more PFAS sampling is needed on the west side to assess this further.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231022","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Fiore, A.R., Imbrigiotta, T.E., and Wilson, T.P., 2023, Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018: U.S. Geological Survey Open-File Report 2023–1022, 81 p., https://doi.org/10.3133/ofr20231022.","productDescription":"Report: ix, 81 p.; Data Release","numberOfPages":"81","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114249","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":417658,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCAQ5N","text":"USGS data release","linkHelpText":"Concentrations of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water, former Naval Air Warfare Center, West Trenton, New Jersey"},{"id":417657,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1022/images/"},{"id":417656,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1022/ofr20231022.XML"},{"id":417655,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231022/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1022"},{"id":417654,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1022/ofr20231022.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1022"},{"id":417653,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1022/coverthb.jpg"},{"id":499772,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114760.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"former Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.816667,\n 40.275\n ],\n [\n -74.816667,\n 40.2667\n ],\n [\n -74.808333,\n 40.2667\n ],\n [\n -74.808333,\n 40.275\n ],\n [\n -74.816667,\n 40.275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ, 08648
The age and source of the late Pleistocene Roxana Silt in the Mississippi Valley have been studied since the middle 1800s. Published age and paleoenvironmental data for the Roxana Silt in the Mississippi Valley show that deposition occurred from late marine isotope stage 5 (MIS5) through late marine isotope stage 3 (MIS3) (80–30 kilo-annum [ka]), when the warm to hot interglacial climate of early to middle MIS5 (about 130 to about 80 ka) was transitioning to a considerably cooler and wetter climate. Scanning electron microscopy/energy dispersive X-ray (SEM/EDS) analysis of silt and sand grains from the Roxana Silt exposed in an abandoned borrow pit near Phillips Bayou, Arkansas, was performed as part of a 1990s study of late middle and late Pleistocene loess in the unglaciated lower Mississippi Valley. Results from that study were summarized in 1990s publications, but the data for sand and silt grain morphology and mineralogy were not published. Some of the SEM/EDS analyses of the Roxana Silt from that late 1990s study are presented in this report. Combined with previously published chronostratigraphic and pedostratigraphic data for the Roxana Silt at Phillips Bayou, the SEM/EDS data indicate some degree of syndepositional weathering and pedogenic alteration during and after gradual eolian deposition in late marine isotope stage 4 (MIS4) and MIS3 (about 60 to about 30 ka). Results from the SEM/EDS analyses support previously published paleoclimate interpretations indicating that at least as far south as northern Mississippi, the climate of the Mississippi Valley in MIS4 and MIS3 (about 70 to about 30 ka) was cool to cold and humid to wet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235062","usgsCitation":"Markewich, H.W., Wysocki, D.A., White, G.N., and Dixon, J.B., Scanning electron microscope images of sand and silt from the early MIS4–MIS3 Roxana Silt, Phillips Bayou, Arkansas: U.S. Geological Survey Scientific Investigations Report 2023–5062, 24 p., https://doi.org/10.3133/sir20235062.","productDescription":"vii, 24 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-145015","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":500943,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114758.htm","linkFileType":{"id":5,"text":"html"}},{"id":417689,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5062/sir20235062.XML"},{"id":417686,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5062/coverthb.jpg"},{"id":417690,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5062/images/"},{"id":417687,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5062/sir20235062.pdf","text":"Report","size":"3.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5062"},{"id":417688,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235062/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5062"}],"country":"United States","state":"Arkansas","otherGeospatial":"Phillips Bayou","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.66670327420083,\n 34.70118993977516\n ],\n [\n -90.66670327420083,\n 34.592483973324875\n ],\n [\n -90.5829724351348,\n 34.592483973324875\n ],\n [\n -90.5829724351348,\n 34.70118993977516\n ],\n [\n -90.66670327420083,\n 34.70118993977516\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
Groundwater quality in the Northern San Joaquin Valley region of California was studied as part of California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment Program-Priority Basin Project (GAMA-PBP). The GAMA-PBP made a spatially unbiased assessment of the aquifer system used for domestic drinking-water supply in the study region and compared the results to the aquifer system used for public drinking-water supply. These assessments characterized the quality of raw groundwater to evaluate ambient conditions in regional aquifers and not the quality of treated drinking water. The study included two components: (1) a status assessment presenting study results summarizing the status of groundwater quality used for domestic supply in the Northern San Joaquin Valley and (2) a comparative assessment of groundwater resources used for domestic and public drinking-water supply in the study region.
The status assessment was based on data collected by the GAMA-PBP from 45 sites in the Northern San Joaquin Valley domestic-supply aquifer assessment study unit during 2019. To contextualize water-quality results, concentrations of water-quality constituents in ambient groundwater were compared to regulatory and non-regulatory benchmarks used by the State of California and Federal agencies as health-based or aesthetic standards for public drinking water. A grid-based method to estimate aquifer-scale proportions of groundwater resources with concentrations approaching or exceeding benchmark thresholds was used in the status assessment. This method provides spatially unbiased results and allows inter-comparability with similar groundwater-quality assessments. A spatially weighted method was used to calculate aquifer-scale proportions for public-supply wells within the domestic assessment grid network using contemporaneous regulatory compliance monitoring data. Differences among aquifer-scale proportions for constituents exceeding regulatory and non-regulatory benchmarks in domestic- and public-supply aquifers were quantitatively evaluated. Factors influencing the vertical and lateral distribution of key contaminants of concern (nitrate, fumigants, and arsenic) across overlapping aquifer systems used for domestic and public drinking-water supply were also evaluated.
Status assessment results indicated inorganic and organic constituents with health-based benchmarks were present at high relative concentrations (RCs), meaning they exceeded a benchmark threshold, in 20 and 9 percent of the domestic-supply aquifer system in the Northern San Joaquin Valley, respectively. Inorganic constituents with health-based benchmarks present at high RCs included nitrate and arsenic. The only organic constituents with health-based benchmarks present at high RCs were the fumigants 1,2-dibromo-3-chloropropane (DBCP) and 1,2,3-trichloropropane (1,2,3-TCP). Inorganic constituents with aesthetic-based benchmarks were present at high RCs in 13 percent of the domestic-supply aquifer system in the Northern San Joaquin Valley and included iron and manganese. Microbial indicators (total coliform bacteria and Enterococci) were present in 18 and 2 percent of the domestic-supply aquifer system in the Northern San Joaquin Valley, respectively.
Comparative assessment results indicated inorganic and organic constituents with health-based benchmarks were present at high RCs in 13 and 6 percent of the public-supply aquifer system in the Northern San Joaquin Valley, respectively. Inorganic constituents with aesthetic-based benchmarks were present at high RCs in 22 percent of the public-supply aquifer system in the Northern San Joaquin Valley. There were no significant differences among high RC proportions for individual water-quality constituents, except for nitrate, which was greater in the domestic- compared to public-supply aquifer system in the Northern San Joaquin Valley. The most prevalent constituents with health-based benchmarks contributing to high RC proportions in the public-supply aquifer system were arsenic and fumigants, including DBCP and 1,2,3-TCP.
Analysis of construction data for wells included in the comparative assessment indicated that, although depth to top of perforations are comparable for domestic and public-supply wells in the Northern San Joaquin Valley (median depth about 60 meters [m]), public-supply wells have longer perforation intervals and extend to deeper parts of the aquifer system than domestic wells that typically draw exclusively from the shallower aquifer system in the upper 80 m of unconsolidated sediments. Analysis of the vertical and lateral distribution of constituents of interest (nitrate, fumigants, and arsenic) across domestic- and public-supply aquifers indicated that nitrate is prevalent in shallow aquifers throughout the Northern San Joaquin Valley but is potentially diluted by mixing with deeper, older groundwater at long-screened public-supply wells. Fumigants were prevalent in areas of urban and agricultural land use in the western part of the Northern San Joaquin Valley, particularly in areas near Lodi, California, but 1,2,3-TCP was more widespread than DBCP and was detected in shallow and deeper parts of the aquifer system, potentially because of its recalcitrance in groundwater and ability to be detected at low concentrations. Arsenic was most prevalent in the western part of the Northern San Joaquin Valley with proximity to deltaic sediments and was detected at high RCs in wells tapping shallow and deep parts of the aquifer system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235049","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","usgsCitation":"Bennett, G.L., V, Haugen, E.A., and Levy, Z.F., 2023, Comparing domestic and public-supply groundwater quality in the northern San Joaquin Valley, 2019—California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2023–5049, 44 p., https://doi.org/10.3133/sir20235049.","productDescription":"Report: x, 44 p.; 2 Data Releases","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-136374","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":417722,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5049/images"},{"id":417725,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90OHVIC","text":"Compilation of public-supply well construction depths in California","description":"Levy, Z.F., and Borkovich, J.G., 2022, Compilation of public-supply well construction depths in California: U.S. Geological Survey data release, https://doi.org/10.5066/P90OHVIC."},{"id":417719,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5049/covrthb.jpg"},{"id":417720,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5049/sir20235049.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":417721,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5049/sir20235049.xml"},{"id":417723,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235049/full"},{"id":417724,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q083IB","text":"Groundwater-quality data in the Northern San Joaquin Valley Domestic-Supply Aquifer Study Unit, 2019: Results from the California GAMA Priority Basin Project","description":"Balkan, M., Levy, Z.F., Shelton, J.L., Johnson, T.D., and Watson, E., 2021, Groundwater-quality data in the Northern San Joaquin Valley Domestic-Supply Aquifer Study Unit, 2019: Results from the California GAMA Priority Basin Project: U.S. Geological Survey data release, https://doi.org/10.5066/P9Q083IB."},{"id":500927,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114762.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Northern San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.78743448158886,\n 38.35484127947586\n ],\n [\n -121.78743448158886,\n 37.32696097611618\n ],\n [\n -120.59999292604016,\n 37.32696097611618\n ],\n [\n -120.59999292604016,\n 38.35484127947586\n ],\n [\n -121.78743448158886,\n 38.35484127947586\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
No abstract available.
","language":"English","publisher":"International Reptile Conservation Foundation","doi":"10.17161/randa.v30i1.19517","usgsCitation":"Woytek, K., Anderson, G.E., Donmoyer, K., Ridgley, F., Romagosa, C., Yackel Adams, A.A., and Currylow, A.F., 2023, Testicular abnormalities in the invasive Argentine Black-and-White Tegu lizard (Salvator merianae) in the Florida Everglades: Reptiles & Amphibians, v. 30, no. 1, e19517, 5 p., https://doi.org/10.17161/randa.v30i1.19517.","productDescription":"e19517, 5 p.","ipdsId":"IP-149172","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":443197,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.17161/randa.v30i1.19517","text":"Publisher Index Page"},{"id":418897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.81796201143997,\n 26.282480982885218\n ],\n [\n -81.81796201143997,\n 25.09156104129292\n ],\n [\n -80.20680880135845,\n 25.09156104129292\n ],\n [\n -80.20680880135845,\n 26.282480982885218\n ],\n [\n -81.81796201143997,\n 26.282480982885218\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Woytek, Kyra","contributorId":316353,"corporation":false,"usgs":false,"family":"Woytek","given":"Kyra","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":877457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Gretchen Erika 0000-0002-5887-4961","orcid":"https://orcid.org/0000-0002-5887-4961","contributorId":271047,"corporation":false,"usgs":true,"family":"Anderson","given":"Gretchen","email":"","middleInitial":"Erika","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":877458,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donmoyer, Kevin","contributorId":316354,"corporation":false,"usgs":false,"family":"Donmoyer","given":"Kevin","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":877459,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ridgley, Frank","contributorId":316355,"corporation":false,"usgs":false,"family":"Ridgley","given":"Frank","affiliations":[{"id":68562,"text":"Zoo Miami","active":true,"usgs":false}],"preferred":false,"id":877460,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romagosa, Christina M.","contributorId":316356,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","middleInitial":"M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":877461,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":877462,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Currylow, Andrea Faye 0000-0003-1631-8964","orcid":"https://orcid.org/0000-0003-1631-8964","contributorId":257055,"corporation":false,"usgs":true,"family":"Currylow","given":"Andrea","email":"","middleInitial":"Faye","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":877463,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70254885,"text":"70254885 - 2023 - Habitat selection and water dependency of feral burros in the Mojave Desert, California, USA","interactions":[],"lastModifiedDate":"2024-06-11T11:24:12.755768","indexId":"70254885","displayToPublicDate":"2023-06-05T06:20:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Habitat selection and water dependency of feral burros in the Mojave Desert, California, USA","docAbstract":"Expansion of feral burro (Equus asinus) populations across the southwestern United States is causing human–wildlife conflicts including rangeland degradation, competition with livestock and native species, and burro–vehicle collisions. On the Fort Irwin National Training Center (NTC) in California, feral burros interfere with military training and are involved in vehicle collisions and other conflicts (e.g., burros blocking access to buildings). Limited data on burro movements and resource use poses a challenge for the development of management plans and mitigation strategies. We estimated home range size, second- and third-order seasonal resource selection, and water dependency of 10 adult female feral burros fitted with global positioning system (GPS) collars on the NTC from November 2015 to April 2017. Mean 95% autocorrelated kernel home range size of female burros (253.9 ± 30.7 km2 [SE]) did not differ among seasons or between burros that resided close to or far from urban areas. Burros selected areas closer to water in all seasons and at both spatial scales, but selection was stronger in the dry season and at the landscape scale. When available, burros strongly selected for areas closer to urban areas. Burros consistently selected for areas with green forage and at lower elevations, but selection for other topographical features was variable. Water use patterns were consistent with the resource selection results. Burros visited water sources twice as often (every 22.2 ± 6.3 hr) during the hot-dry season (Apr–Oct) compared to the cool-wet seasons (Nov–Mar; 2015: 45.9 ± 21.0; 2016: 39.7 ± 9.3 hr). Our results suggest that urban areas, and resources therein, and water sources have the biggest influence on burro resource selection, and management plans could focus mitigation programs on these areas.
Understanding potential limiting factors affecting population growth of the endangered pallid sturgeon, Scaphirhynchus albus, is important in the upper (UMOR) and lower Missouri River (LMOR) basins. The UMOR is upstream of several reservoirs and generally has more natural habitat features, whereas the LMOR is downstream of these reservoirs and has been channelized to support navigation. In both sections, pallid sturgeon recruitment to age-1 is a concern, but hypothesized for different reasons. One hypothesis in the LMOR centers on food limitation for age-0 fish, which is not considered an issue in the UMOR, but evaluating this hypothesis is challenging given the rarity of age-0 pallid sturgeon. As a result, the related, more abundant shovelnose sturgeon (S. platorhynchus) has been considered as a potential surrogate to assess food-related hypotheses. Thus, the purpose of our study was to compare diets of age-0 sturgeon captured in 2016 from three reaches in the LMOR (Copeland, Langdon, and Lexington) with individuals captured from a reach in the UMOR (Williston) during the same year to provide additional context regarding potential food limitation in the LMOR. Consumption percentage (prey weight in the gut as a percentage of body weight) was similar among all reaches, but diet composition was different for the most downstream reach in the LMOR. Age-0 sturgeon in the UMOR reach as well as the two upstream LMOR reaches primarily consumed Diptera larvae along with Ephemeroptera nymphs. In contrast, age-0 sturgeon in the most downstream LMOR reach (Lexington) almost exclusively consumed Diptera larvae. These results may provide information on relative differences in prey availability between Lexington and the other upstream reaches but the similarity in consumption percentage values across all reaches provide further evidence that age-0 sturgeon are not food limited in the LMOR.
Genetic diversity is theorized to decrease in populations closer to a species' range edge, where habitat may be suboptimal. Generalist species capable of long-range dispersal may maintain sufficient gene flow to counteract this, though the presence of significant barriers to dispersal (e.g., large water bodies, human-dominated landscapes) may still lead to, and exacerbate, the edge effect. We used microsatellite data for 2421 gray wolves (Canis lupus) from 24 subpopulations (groups) to model how allelic richness and expected heterozygosity varied with mainland–island position and two measures of range edge (latitude and distance from range center) across >7.3 million km2 of northern North America. We expected low genetic diversity both at high latitudes, due to harsh environmental conditions, and on islands, but no change in diversity with distance to the range center due to the species' exceptional dispersal ability and favorable conditions in far eastern and western habitats. We found that allelic richness and expected heterozygosity of island groups were measurably less than that of mainland groups, and that these differences increased with the island's distance to the species' range center in the study area. Our results demonstrate how multiple axes of geographic isolation (distance from range center and island habitation) can act synergistically to erode the genetic diversity of wide-ranging terrestrial vertebrate populations despite the counteracting influence of long-range dispersal ability. These findings emphasize how geographic isolation is a potential threat to the genetic diversity and viability of terrestrial vertebrate populations even among species capable of long-range dispersal.
The establishment of invasive dreissenid mussels Dreissena polymorpha and Dreissena rostriformis bugensis in the Laurentian Great Lakes has affected multiple aspects of the ecosystem. However, the effects of their larvae (veligers) on lower trophic levels are relatively unknown. Previous research has documented that some larval fishes consume veligers, but it is unclear if they select for veligers. To assess the role of veligers in larval fish diets in Lake Huron, we examined the diets of larval burbot Lota lota, rainbow smelt Osmerus mordax, and Coregonus spp., mainly bloater Coregonus hoyi, sampled in July of 2017. Preference for available zooplankton prey was evaluated using Vanderploeg and Scavia’s E*. Results indicated that veligers were on average avoided by large larval burbot, rainbow smelt, and coregonines but were sometimes preferred by small (< 7 mm) and medium-sized (7–10 mm) larval burbot. A mixed model analyzing factors contributing to veliger preference by larval burbot indicated that greater environmental zooplankton prey size is associated with more positive preference for veligers. Thus, veligers may be important for gape-limited larval fish. We also found that, on average, larval burbot and coregonines consumed larger veligers than those sampled in the environment. Overall, consideration of larval fishes’ ability to exploit veligers could help managers to understand the role of dreissenid mussels in Great Lakes food webs.
The Great Dismal Swamp wetland, spanning >400 km2 along the Virginia and North Carolina border, was shaped by a complex combination of geomorphic, climatic, and anthropogenic forcings during the last 14,000 years. Pollen, macrofossils, charcoal, and physical properties from sediment cores at seven sites provide a detailed record of the spatial heterogeneity of the wetland and the roles played by natural hydrologic variability, wildfire, and human modification of drainage in shaping vegetation and habitats. Cold-temperate forests occupied regional uplands from at least 13.5–10.3 cal ka BP. Marshes dominated by grasses and other herbaceous taxa began developing along low-elevation streams as early as 10.3 cal ka BP, resulting in accumulation of organic silts. Long-hydroperiod, peat accumulating marshes, with abundant floating aquatic plants, developed as early as 9.6 cal ka BP, as rapid rates of sea-level rise elevated the water table and facilitated wetland development and peat accumulation along stream courses. By the mid-Holocene (c. 7–6.5 cal ka BP), when local sea-level rise began slowing and reached about 12–15 m below present, shorter hydroperiod, peat-accumulating marshes dominated the landscape, with increased wildfire activity. Great Dismal Swamp vegetation shifted from marshes to peat-accumulating forested wetlands by c. 3.7 cal ka BP; these were dominated by varying combinations of Nyssa (tupelo), Taxodium (cypress), and Chamaecyparis thyoides (Atlantic white cedar). Wildfires were infrequent during this time, and the forested wetlands persisted, with minor compositional changes related to climate-driven fluctuations in stream flow, until colonial ditching and logging began in the swamp during the late 18th century. These activities decreased cypress and cedar populations, and, by the mid-20th century, expanded ditching resulted in even drier conditions and expansion of maple-gum (dominated by Acer and Liquidambar), and pine-pocosin (dominated by Pinus) forests. The distribution of these forests differs from that of the late Holocene and represents a fundamental shift in hydrology, peat structure, vegetation, and fire regime due to landscape alterations of the last few centuries.
Explosive eruptions expel volcanic gases and particles at high pressures and velocities. Within this multiphase fluid, small ash particles affect the flow dynamics, impacting mixing, entrainment, turbulence, and aggregation. To examine the role of turbulent particle behavior, we conducted an analogue experiment using a particle-laden jet. We used compressed air as the carrier fluid, considering turbulent conditions at Reynolds numbers from approximately 5,000 to 20,000. Two different particles were examined: 14-μm diameter solid nickel spheres and 13-μm diameter hollow glass spheres. These resulted in Stokes numbers between 1 and 35 based on the convective scale. The particle mass percentage in the mixture is varied from 0.3% to more than 20%. Based on a 1-D volcanic plume model, these Stokes numbers and mass loadings corresponded to millimeter-scale particle diameters at heights of 4–8 km above the vent during large, sustained eruptions. Through particle image velocimetry, we measured the mean flow behavior and the turbulence statistics in the near-exit region, primarily focusing on the dispersed phase. We show that the flow behavior is dominated by the particle inertia, with high Stokes numbers reducing the entrainment by more than 40%. When applied to volcanic plumes, these results suggest that high-density particles can greatly increase the probability of column collapse.
Between 2015 and 2019, the U.S. Geological Survey (USGS) studied concerns related to projected increases in demand for groundwater, in collaboration with municipal water providers and county managers within the study area, Aiken County and part of Lexington County, South Carolina. A three-dimensional (3D), numerical groundwater-flow model of the Atlantic Coastal Plain (ACP) aquifers, confining units, and the underlying bedrock aquifer in the study area was constructed using the USGS software program MODFLOW–NWT in conjunction with a groundwater-recharge model using the Soil-Water-Balance (SWB) model. Water budgets for dry (2012) and wet (2015) year conditions, future (2017–2065) groundwater-demand scenarios based on general circulation models (GCMs) of future climates, and future agricultural irrigation demands were simulated. Overall, the GCMs projected increased recharge rates. Simulation of projected increased demand on groundwater by agriculture irrigation indicated little drawdown in the study area.
Groundwater-quality samples were collected from representative public-supply wells (PSWs) and analyzed in the field and laboratory. In general, the groundwater in the ACP aquifers is acidic, dilute, and oxic. Conversely, groundwater in the bedrock aquifer was of neutral pH, mineralized, and anoxic. Total-radium concentrations across all PSWs ranged from 0.55 to 6.69 picocuries per liter (pCi/L). Groundwater from some PSWs contained detectable but low concentrations of commonly and historically used volatile organic compounds, such as chloroform, methyl tert-butyl ether (MTBE), cis-1,2-dichloroethylene (cis-1,2-DCE), 1,1-dichloroethane (1,1-DCA), and 1,1-dichloroethylene (1,1-DCE). The stable isotopes of groundwater sampled from all wells indicate the possibility that groundwater from the bedrock aquifer may discharge into the ACP. Finally, groundwater age-dating results and MODPATH simulations indicate recharge between the 1950s and 1980s for PSWs in the ACP and recharge between the 1940s and 1950s for PSWs in bedrock. Maximum groundwater-flow pathways ranged from 270 to 7,470 feet, with the longest simulated-flow pathway for wells pumped at higher rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225036","collaboration":"Prepared in cooperation with Aiken County, City of Aiken, Breezy Hill Water and Sewer Company, Inc., Gilbert-Summit Rural Water District, and Montmorenci-Couchton Water & Sewer District, Inc.","programNote":"Water Availability and Use Science Program","usgsCitation":"Campbell, B.G., and Landmeyer, J.E., 2023, Groundwater availability, geochemistry, and flow pathways to public-supply wells in the Atlantic Coastal Plain and bedrock aquifers, Aiken County and part of Lexington County, South Carolina, 2015–2019: U.S. Geological Survey Scientific Investigations Report 2022–5036, 117 p., https://doi.org/10.3133/sir20225036.","productDescription":"Report: xiv, 117 p.; Data Release","numberOfPages":"117","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-111003","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":417685,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U0GHLU","text":"USGS data release","linkHelpText":"MODFLOW–NWT and MODPATH 5 used to evaluate groundwater availability, geochemistry, and flow pathways to public-supply wells in the Atlantic Coastal Plain and bedrock aquifers, Aiken County and part of Lexington County, South Carolina, 2015–2019"},{"id":413200,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5036/coverthb.jpg"},{"id":417681,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5036/sir20225036.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5036"},{"id":417683,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5036/sir20225036.XML"},{"id":417684,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5036/images/"},{"id":500904,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114757.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"South Carolina","county":"Aiken County, Lexington County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-81.1873,33.6526],[-81.373,33.4907],[-81.5165,33.3824],[-81.7575,33.1982],[-81.7577,33.1995],[-81.7588,33.2017],[-81.7605,33.2035],[-81.7621,33.2054],[-81.7628,33.2063],[-81.7644,33.2085],[-81.765,33.2095],[-81.7655,33.2103],[-81.7666,33.2131],[-81.7679,33.2159],[-81.7706,33.2182],[-81.7725,33.2198],[-81.7732,33.2203],[-81.776,33.2216],[-81.7777,33.2219],[-81.7788,33.2219],[-81.7809,33.2201],[-81.781,33.2188],[-81.7802,33.2167],[-81.78,33.216],[-81.7793,33.2146],[-81.7787,33.213],[-81.7792,33.2112],[-81.7814,33.2098],[-81.7858,33.2088],[-81.7939,33.2098],[-81.799,33.2115],[-81.8006,33.212],[-81.8017,33.2124],[-81.8039,33.2128],[-81.8056,33.2137],[-81.8072,33.2151],[-81.8084,33.2186],[-81.8084,33.2209],[-81.8101,33.2237],[-81.8127,33.2255],[-81.816,33.227],[-81.82,33.2282],[-81.8255,33.229],[-81.8263,33.2295],[-81.8286,33.2311],[-81.8321,33.235],[-81.8367,33.238],[-81.8421,33.2403],[-81.846,33.243],[-81.8466,33.2435],[-81.8487,33.2452],[-81.8494,33.2461],[-81.8503,33.2472],[-81.8511,33.2485],[-81.8515,33.2493],[-81.8519,33.2513],[-81.8518,33.2519],[-81.8515,33.2525],[-81.8499,33.2535],[-81.8477,33.2534],[-81.8453,33.2531],[-81.843,33.253],[-81.8416,33.2538],[-81.8414,33.2546],[-81.8414,33.2553],[-81.8419,33.2568],[-81.8435,33.2577],[-81.8458,33.2596],[-81.8473,33.2613],[-81.8481,33.2627],[-81.8483,33.2634],[-81.8477,33.2648],[-81.8467,33.2662],[-81.844,33.2661],[-81.8418,33.2654],[-81.8401,33.2635],[-81.8385,33.2617],[-81.8362,33.2603],[-81.8345,33.2596],[-81.8313,33.2594],[-81.8296,33.2603],[-81.8291,33.2613],[-81.8291,33.2634],[-81.8308,33.2643],[-81.833,33.2653],[-81.8352,33.2663],[-81.8369,33.2676],[-81.8363,33.2695],[-81.8358,33.2713],[-81.836,33.2735],[-81.8367,33.2744],[-81.8385,33.2754],[-81.8405,33.2763],[-81.8426,33.2777],[-81.8443,33.2799],[-81.8454,33.2826],[-81.8481,33.284],[-81.8491,33.2842],[-81.8513,33.2848],[-81.8557,33.2852],[-81.8572,33.2859],[-81.8596,33.2874],[-81.8617,33.2887],[-81.8622,33.2915],[-81.8622,33.2938],[-81.8622,33.296],[-81.8619,33.297],[-81.8613,33.2979],[-81.8608,33.2989],[-81.8597,33.2993],[-81.857,33.2993],[-81.8548,33.2989],[-81.8531,33.2985],[-81.8509,33.298],[-81.8495,33.2981],[-81.849,33.2986],[-81.8484,33.3],[-81.8478,33.3023],[-81.8467,33.3037],[-81.8474,33.3061],[-81.8494,33.3082],[-81.8512,33.3087],[-81.8527,33.3089],[-81.8549,33.3084],[-81.8568,33.3071],[-81.8576,33.3065],[-81.8593,33.3052],[-81.8608,33.3047],[-81.8631,33.3057],[-81.8642,33.3075],[-81.8642,33.3093],[-81.8647,33.3115],[-81.8669,33.3125],[-81.8697,33.312],[-81.8724,33.3107],[-81.8746,33.3083],[-81.8756,33.3073],[-81.8763,33.3066],[-81.8776,33.3062],[-81.879,33.306],[-81.8817,33.3064],[-81.8823,33.3073],[-81.8829,33.3085],[-81.8828,33.3108],[-81.8822,33.3135],[-81.8822,33.3158],[-81.8833,33.3167],[-81.8841,33.3169],[-81.8857,33.3169],[-81.889,33.3159],[-81.891,33.3159],[-81.8921,33.3173],[-81.891,33.3195],[-81.8912,33.3204],[-81.8914,33.321],[-81.894,33.3219],[-81.8946,33.322],[-81.8968,33.3227],[-81.8984,33.3236],[-81.899,33.326],[-81.8985,33.3282],[-81.898,33.331],[-81.8985,33.3331],[-81.8993,33.3339],[-81.9001,33.3346],[-81.9019,33.3346],[-81.9029,33.3345],[-81.9051,33.3313],[-81.9057,33.3279],[-81.9061,33.3253],[-81.9064,33.3239],[-81.9068,33.3233],[-81.9083,33.3213],[-81.9104,33.3208],[-81.9116,33.3218],[-81.9113,33.3229],[-81.9107,33.3243],[-81.9095,33.3261],[-81.9095,33.3281],[-81.9111,33.3294],[-81.9128,33.3312],[-81.9155,33.3321],[-81.9182,33.3339],[-81.9198,33.3357],[-81.9193,33.3375],[-81.9187,33.3383],[-81.9173,33.3398],[-81.9163,33.3406],[-81.9148,33.3416],[-81.9124,33.3431],[-81.9102,33.3445],[-81.9097,33.3456],[-81.9106,33.3463],[-81.9113,33.3467],[-81.9148,33.3467],[-81.9175,33.3453],[-81.9197,33.3444],[-81.9212,33.3439],[-81.923,33.3444],[-81.9245,33.3452],[-81.9294,33.3447],[-81.9324,33.3441],[-81.9338,33.3438],[-81.9366,33.3442],[-81.9384,33.345],[-81.9395,33.3464],[-81.9383,33.3488],[-81.9372,33.351],[-81.9366,33.3545],[-81.9366,33.3567],[-81.9367,33.3574],[-81.94,33.3611],[-81.9431,33.3632],[-81.9458,33.3655],[-81.9466,33.3676],[-81.9467,33.3682],[-81.9457,33.371],[-81.9434,33.3725],[-81.9429,33.3728],[-81.9408,33.3728],[-81.9385,33.3719],[-81.9372,33.3711],[-81.9363,33.3706],[-81.9348,33.3698],[-81.9331,33.3691],[-81.9317,33.3688],[-81.9303,33.3688],[-81.9292,33.369],[-81.9282,33.3695],[-81.9265,33.3713],[-81.926,33.3724],[-81.9254,33.3737],[-81.926,33.3749],[-81.9265,33.3757],[-81.9287,33.3784],[-81.9314,33.3816],[-81.9334,33.3854],[-81.9338,33.3879],[-81.9338,33.3888],[-81.9334,33.3929],[-81.9345,33.3956],[-81.9349,33.3961],[-81.9361,33.3974],[-81.9389,33.3992],[-81.9416,33.4006],[-81.9443,33.4024],[-81.9454,33.4051],[-81.9447,33.4074],[-81.9426,33.4088],[-81.9406,33.4091],[-81.94,33.4092],[-81.9368,33.4088],[-81.9352,33.4088],[-81.934,33.4088],[-81.9331,33.4088],[-81.9315,33.4091],[-81.9293,33.41],[-81.927,33.4118],[-81.9254,33.4144],[-81.9254,33.4171],[-81.9258,33.419],[-81.928,33.4218],[-81.9294,33.4238],[-81.9302,33.425],[-81.9306,33.426],[-81.9309,33.4275],[-81.931,33.4284],[-81.9306,33.4297],[-81.9299,33.4302],[-81.9273,33.4317],[-81.9244,33.4326],[-81.9206,33.4336],[-81.9196,33.4338],[-81.9178,33.4344],[-81.9151,33.4363],[-81.9135,33.4386],[-81.9135,33.4408],[-81.914,33.4436],[-81.9156,33.4462],[-81.9188,33.4499],[-81.9199,33.4517],[-81.9208,33.454],[-81.9236,33.4595],[-81.9259,33.4626],[-81.9285,33.4651],[-81.9292,33.4656],[-81.9314,33.4671],[-81.9331,33.468],[-81.9351,33.4687],[-81.9392,33.4706],[-81.9419,33.4715],[-81.9437,33.4722],[-81.9458,33.4729],[-81.9464,33.4732],[-81.9488,33.4738],[-81.9509,33.4748],[-81.952,33.4752],[-81.9553,33.4771],[-81.9564,33.4776],[-81.9586,33.4785],[-81.9603,33.4793],[-81.9624,33.48],[-81.9668,33.4817],[-81.9709,33.4827],[-81.9757,33.4845],[-81.9801,33.4853],[-81.9834,33.4862],[-81.9862,33.4875],[-81.9889,33.4903],[-81.9912,33.493],[-81.9918,33.4975],[-81.9918,33.5016],[-81.9924,33.5043],[-81.9935,33.5071],[-81.994,33.5077],[-81.9967,33.5116],[-81.9989,33.5148],[-82.001,33.5175],[-82.0037,33.5207],[-82.0065,33.5235],[-82.0086,33.5253],[-82.0096,33.5263],[-82.0108,33.5276],[-82.0119,33.5294],[-82.0119,33.5313],[-82.0125,33.532],[-81.9062,33.6151],[-81.8608,33.6514],[-81.7595,33.7308],[-81.736,33.7505],[-81.652,33.8142],[-81.5751,33.8751],[-81.551,33.9188],[-81.5134,34.0004],[-81.4997,34.0182],[-81.464,34.0833],[-81.4446,34.0779],[-81.4302,34.0835],[-81.4247,34.0835],[-81.423,34.0821],[-81.4129,34.0735],[-81.4029,34.0708],[-81.3952,34.0713],[-81.3897,34.0754],[-81.3886,34.08],[-81.3964,34.0854],[-81.4031,34.0895],[-81.4137,34.1067],[-81.422,34.1099],[-81.4332,34.1225],[-81.4371,34.1302],[-81.4041,34.1776],[-81.3874,34.1772],[-81.3735,34.18],[-81.3724,34.1805],[-81.363,34.1869],[-81.3525,34.1969],[-81.3392,34.1974],[-81.3286,34.1892],[-81.3114,34.1856],[-81.2996,34.1639],[-81.3007,34.1602],[-81.3118,34.1547],[-81.3151,34.1461],[-81.3123,34.1411],[-81.2928,34.1189],[-81.2777,34.1007],[-81.2733,34.0985],[-81.2583,34.1021],[-81.25,34.1022],[-81.2284,34.1018],[-81.2051,34.0982],[-81.1823,34.0914],[-81.1484,34.0751],[-81.1284,34.0587],[-81.1168,34.0451],[-81.109,34.0342],[-81.1046,34.0238],[-81.0979,34.0179],[-81.0918,34.0142],[-81.0735,34.0065],[-81.0613,34.0047],[-81.0547,33.9997],[-81.0513,33.9965],[-81.0469,33.9879],[-81.0463,33.977],[-81.0397,33.9693],[-81.017,33.9306],[-81.0192,33.9211],[-81.0303,33.9152],[-81.0231,33.9093],[-81.0148,33.9084],[-81.0087,33.9043],[-81.0092,33.9002],[-81.0109,33.8979],[-81.017,33.897],[-81.0192,33.8952],[-81.0219,33.8879],[-81.0186,33.882],[-81.0125,33.8802],[-81.0236,33.8761],[-81.038,33.8706],[-81.0418,33.8592],[-81.0385,33.8442],[-81.0462,33.7983],[-81.0462,33.7965],[-81.0479,33.7888],[-81.0556,33.7765],[-81.0595,33.771],[-81.0606,33.7633],[-81.0583,33.7469],[-81.0363,33.7451],[-81.033,33.7642],[-81.0142,33.781],[-80.9606,33.7788],[-80.9507,33.7719],[-80.9429,33.7692],[-80.9407,33.7692],[-80.9253,33.7556],[-80.9496,33.7456],[-80.9667,33.7365],[-80.9777,33.7306],[-80.9816,33.7301],[-80.9993,33.7265],[-81.0197,33.7201],[-81.0429,33.7069],[-81.0865,33.6955],[-81.108,33.6837],[-81.1873,33.6526]]]},\"properties\":{\"name\":\"Aiken\",\"state\":\"SC\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093