With an increased interest in nongame fishes such as buffalofishes (Catostomidae, Ictiobus), there is a need for better foundational data on their life history. Bigmouth Buffalo I. cyprinellus, for example, have been found to live for more than a century. Age estimates for other sucker species have similarly suggested long life spans, but validation studies as reference points are often lacking. We conducted a 3-year study on Smallmouth Buffalo I. bubalus in Oklahoma to validate annual increments on three hard part structures (otoliths [lapilli], pectoral fin rays, and opercula) typically used for age estimation. We marked wild fish with oxytetracycline (OTC) injection and stocked those fish into a hatchery pond to create a population of fish with known times since marking. Furthermore, reproduction in the pond allowed us to validate annulus formation in young fish. We analyzed 117 fish and found that otoliths were more reliable, precise, and accurate than the other two structures for detecting OTC marks and counting annuli. Age estimates, from 1 to 61 years, were greatest when otoliths were used, with 99% of estimates corresponding to known time since marking or known age. Otoliths appear to be the only reliable structure for accurately estimating the age of Smallmouth Buffalo within 1 year of actual age, and their use indicates that this species can live for more than six decades in Oklahoma.
The Precipitation-Runoff Modeling System (PRMS) was used to develop and calibrate a streamflow and water balance model for the Red River Basin as part of the U.S. Geological Survey National Water Census, a research effort focused on developing innovative water accounting tools and conducting assessments of water use and availability at regional and national spatial scales. The PRMS is a deterministic model that simulates the effects of climate, land cover, and water use on watershed hydrology on the basis of physical processes and spatial attributes of the watershed. The model was used to estimate streamflow at daily and monthly temporal scales for the 1980–2016 period and to evaluate the impacts of natural and anthropogenic influences on streamflow and water budget components.
Sixty-three percent of streamgages were calibrated successfully for the monthly time step and 43 percent of streamgages were successfully calibrated for the daily time step. Some of the challenges of calibrating streamgages included estimating low amounts of streamflow in dry areas of the basin and accurately representing watershed characteristics related to evapotranspiration in the basin, among other factors. The model estimated streamflow with some accuracy for 42 percent and 29 percent of the 73 streamgages used to evaluate the model at monthly and daily time steps, respectively. Relative to no-water-use conditions, water use increased streamflow volumes (that is, return flow from reservoir releases) the most on the main stem of the Red River, the North Fork of the Red River, and the Ouachita River. Water withdrawal decreased streamflow volumes most in the Red River near the outlet of the basin and in Caney Creek. Streamflow volumes on the North Fork of the Red River changed most as a result of water use. The Red River Basin PRMS model provided estimates of streamflow that were limited in their accuracy by (1) the availability of accurate water-use data; (2) the coarse resolution of spatial parameters (such as those for impervious area or plant canopy), which leads to the homogenization of physical features in small watersheds in the model domain; and (3) the accuracy of spatial patterns of precipitation distribution across the model domain. Improvements in the quality and quantity of available water-use data and finer resolution spatial parameter and climate data could lead to the development of better-informed models in the future that are capable of making more accurate estimates of streamflow, because they are more representative of physical and hydrologic conditions in the Red River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225105","issn":"2328-0328","programNote":"Water Availability and Use Science Program","usgsCitation":"Roland, V.L., II, 2023, Application of the Precipitation-Runoff Modeling System (PRMS) to simulate the streamflows and water balance of the Red River Basin, 1980–2016: U.S. Geological Survey Scientific Investigations Report 2022–5105, 37 p., https://doi.org/10.3133/sir20225105.","productDescription":"Report: viii, 37 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-091577","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":417622,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5105/coverthb.jpg"},{"id":500454,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114764.htm","linkFileType":{"id":5,"text":"html"}},{"id":417790,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZI5IVX","text":"USGS data release—Model input and output from Precipitation Runoff Modeling System (PRMS) simulation of the Red River Basin 1981–2016"},{"id":417789,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5105/images/"},{"id":417921,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225105/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5105 HTML"},{"id":417787,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5105/sir20225105.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2022-5105 XML"},{"id":417786,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5105/sir20225105.pdf","size":"16.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5105"}],"country":"United States","state":"Arkansas, Louisiana, Texas, Oklahoma","otherGeospatial":"Red River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.48949921760368,\n 36.13692959102481\n ],\n [\n -103.48949921760368,\n 31.242144043970583\n ],\n [\n -89.91622130795812,\n 31.242144043970583\n ],\n [\n -89.91622130795812,\n 36.13692959102481\n ],\n [\n -103.48949921760368,\n 36.13692959102481\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"For more information about this publication, contact
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
https://www.usgs.gov/centers/lmg-water/
Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.
Operation of large, multipurpose dams within the Middle Fork Willamette River Basin, Oregon, including the Fall Creek sub-basin, have disrupted natural streamflow and sediment transport regimes and fish passage along the river corridors. Documenting channel morphology, including channel planform, landforms, vegetation cover, and river channel elevations at multiple points in time spanning the 20th and early 21st centuries, is useful for characterizing net changes occurring in response to construction and operation of these dams. The U.S. Geological Survey assessed historical channel changes that occurred within the past century in response to the construction and operation of flood-control dams by evaluating planimetric datasets (from 1926 plan and profile surveys and 1936 and 2016 aerial photographs) and elevation datasets (from 1926 plan and profile surveys and 2015 light detection and ranging [lidar]). This study specifically focuses on the lower 27.3 kilometers (km) of the Middle Fork Willamette River and the lower 11.5 km of Fall Creek, or the reaches downstream from the U.S. Army Corps of Engineers Dexter Dam and Fall Creek Dam, to the confluence with Coast Fork Willamette River. Altogether, compilation and evaluation of datasets for Fall Creek and the Middle Fork Willamette River downstream from the dams provide a foundation for understanding:
Findings from this study can be used to provide historical and geomorphic context for geomorphic responses to deep reservoir drawdowns on Fall Creek Lake that mobilize reservoir sediment downstream and informing other restoration and river-management activities; this report summarizes one component of a larger research effort to document the magnitude and spatial distribution of geomorphic responses to sediment releases from draining Fall Creek Lake.
As of 2016, the modern Fall Creek flows through a narrow, semi-alluvial channel that efficiently conveys water and sediment at typical streamflows downstream from Fall Creek Dam. This channel planform, including the positions and distributions of bars and secondary water features (side channels, alcoves, and ponds), generally reflects pre-dam conditions in 1936, suggesting relatively modest morphological adjustments resulted from reductions in sediment supply and alterations to peak streamflow after dam construction. The most substantial morphologic change detected over this period was a reduction in unvegetated gravel bars.
As of 2016, the modern Middle Fork Willamette River is a large, gravel-bed river that, despite substantial transformations in channel morphology and reduction in lateral dynamism following the construction of multiple upstream dams, remains a dominantly alluvial river. Prior to dam construction in 1926 and 1936, the reaches of the Middle Fork Willamette River downstream from Dexter Dam were laterally active with multi-thread and single-thread channels flanked by large, shifting gravel bars. Since streamflow regulation and other channel modifications in the mid-20th century, these reaches have become less laterally active and encompass a narrower floodplain corridor as abundant former gravel bars were converted to low-elevation floodplains colonized by young, dense forests. The Middle Fork Willamette River downstream from Dexter Dam has remained mostly vertically stable between 1926 and 2015, although localized segments possibly decreased in elevation as much as 2.3 meters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235048","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Keith, M.K., Wallick, J.R., Gordon, G.W., and Bervid, H.D., 2023, Historical changes to channel planform and bed elevations downstream from dams along Fall Creek and Middle Fork Willamette River, Oregon, 1926–2016: U.S. Geological Survey Scientific Investigations Report 2023–5048, 34 p., https://doi.org/10.3133/sir20235048.","productDescription":"Report: viii, 34 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-136568","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":500925,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114772.htm","linkFileType":{"id":5,"text":"html"}},{"id":417882,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5048/sir20235048.XML"},{"id":417881,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5048/images"},{"id":417880,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9THIZD6","text":"USGS data release","description":"USGS data release.","linkHelpText":"Fall Creek and Middle Fork Willamette Geomorphic Mapping Geodatabase"},{"id":417877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5048/coverthb.jpg"},{"id":417878,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5048/sir20235048.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Fall Creek, Middle Fork Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123,\n 44\n ],\n [\n -123,\n 43.916667\n ],\n [\n -122.75,\n 43.916667\n ],\n [\n -122.75,\n 44\n ],\n [\n -123,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
An expert meeting was organized by the World Health Organization (WHO) in 1997 to streamline assessments of risk posed by mixtures of dioxin-like chemicals (DLCs) through development of 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) equivalency factors (TEFs) for mammals, birds, and fishes. No reevaluation has been performed for fish TEFs. Therefore, the objective of the present study was to reevaluate the TEFs for fishes based on an updated database of relative potencies (RePs) for DLCs. Selection criteria consistent with the WHO meeting resulted in 53 RePs across 14 species of fish ultimately being considered. Of these RePs, 70% were not available at the time of the WHO meeting. These RePs were used to develop updated TEFs for fishes based on a similar decision process as used at the WHO meeting. The updated TEF for 16 DLCs was greater than the WHO TEF, but only four differed by more than an order of magnitude. Measured concentrations of DLCs in four environmental samples were used to compare 2,3,7,8-TCDD equivalents (TEQs) calculated using the WHO TEFs relative to the updated TEFs. The TEQs for none of these environmental samples differed by more than an order of magnitude. Therefore, present knowledge supports that the WHO TEFs are suitable potency estimates for fishes. However, the updated TEFs pull from a larger database with a greater breadth of data and as a result offer greater confidence relative to the WHO TEFs. Risk assessors will have different criteria in the selection of TEFs, and the updated TEFs are not meant to immediately replace the formal WHO TEFs; but those who value a larger database and increased confidence in TEQs could consider using the updated TEFs.
Aquatic systems worldwide can exist in multiple ecosystem states (i.e., a recurring collection of biological and chemical attributes), and effectively characterizing multidimensionality will aid protection of desirable states and guide rehabilitation. The Upper Mississippi River System is composed of a large floodplain river system spanning 2200 km and multiple federal, state, tribal and local governmental units. Multiple ecosystem states may occur within the system, and characterization of the variables that define these ecosystem states could guide river rehabilitation. We coupled a long-term (30-year) highly dimensional water quality monitoring dataset with multiple topological data analysis (TDA) techniques to classify ecosystem states, identify state variables, and detect state transitions over 30 years in the river to guide conservation. Across the entire system, TDA identified five ecosystem states. State 1 was characterized by exceptionally clear, clean, and cold-water conditions typical of winter (i.e., a clear-water state); State 2 had the greatest range of environmental conditions and contained most the data (i.e., a status-quo state); and States 3, 4, and 5 had extremely high concentrations of suspended solids (i.e., turbid states, with State 5 as the most turbid). The TDA mapped clear patterns of the ecosystem states across several riverine navigation reaches and seasons that furthered ecological understanding. State variables were identified as suspended solids, chlorophyll a, and total phosphorus, which are also state variables of shallow lakes worldwide. The TDA change detection function showed short-term state transitions based on seasonality and episodic events, and provided evidence of gradual, long-term changes due to water quality improvements over three decades. These results can inform decision making and guide actions for regulatory and restoration agencies by assessing the status and trends of this important river and provide quantitative targets for state variables. The TDA change detection function may serve as a new tool for predicting the vulnerability to undesirable state transitions in this system and other ecosystems with sufficient data. Coupling ecosystem state concepts and TDA tools can be transferred to any ecosystem with large data to help classify states and understand their vulnerability to state transitions.
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
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Laurel, Maryland 20708
Species We Study: Pollinators
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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":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},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":878927,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"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":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","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":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 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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":70244165,"text":"fs20233025 - 2023 - Consolidated Appropriations Act, 2023—USGS disaster emergency recovery activities","interactions":[],"lastModifiedDate":"2023-06-06T11:29:56.925519","indexId":"fs20233025","displayToPublicDate":"2023-06-06T06:05:59","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3025","displayTitle":"Consolidated Appropriations Act, 2023—USGS Disaster Emergency Recovery Activities","title":"Consolidated Appropriations Act, 2023—USGS disaster emergency recovery activities","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
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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
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.
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.