Kingsbury Pond is a glacial kettle pond in the town of Norfolk, Massachusetts, in the Mill River Basin, which is part of the Upper Charles River Basin in eastern Massachusetts. The pond is hydraulically connected to the surrounding groundwater-flow system, and water levels in the pond fluctuate in response to recharge to the aquifer from precipitation and wastewater return flows through septic systems, to withdrawals from the aquifer at nearby wells, and to precipitation directly on the pond surface. Concerns about the effects of withdrawals on water levels in the pond prompted an investigation to better understand the hydrology of Kingsbury Pond and its response to groundwater withdrawals and to determine if withdrawals from wells in Franklin, Mass., can be modified to simultaneously reduce the effect on water levels in the pond and yet meet the water-supply demands of the Town of Franklin.
An existing, transient groundwater-flow model of the Upper Charles River Basin was modified for this study in the area near Kingsbury Pond to improve representation of the hydrologic system near the pond. The mean annual water-level altitude simulated for the pond for nonpumping conditions using the modified model is 136 feet (ft), which falls within the range of likely annual pond-altitude fluctuations of 135 to 140 ft estimated for average hydrologic conditions before the beginning of withdrawals at two nearby wells operated by the Town of Franklin (wells FR–04 and FR–05). The mean annual water-level altitude at the pond decreased by 3.8 ft to 132.2 ft for simulated mean monthly withdrawal rates at all wells within the Upper Charles River Basin from 2010 to 2019 (referred to as the baseline withdrawal condition).
A groundwater management model that links the groundwater-flow model with a mathematical optimization method was developed to evaluate the effects of three alternative groundwater-withdrawal scenarios for the Franklin public-water system on water levels in Kingsbury Pond. In the first scenario, monthly withdrawal rates at wells FR–04 and FR–05 were increased from the baseline withdrawal rates to their maximum authorized rates for all months of the year; all other Franklin wells were specified at their baseline withdrawal rates. This scenario resulted in a mean annual water-level altitude at the pond of 129.3 ft, or a mean annual decline of 6.7 ft compared with nonpumping conditions and a decline of 2.9 ft compared with baseline conditions.
The results of the second scenario showed that water levels in the pond can be increased relative to 2010–19 conditions while meeting Franklin’s 2010–19 monthly water-supply demands if withdrawals at wells FR–04 and FR–05 were shifted to other Franklin wells. In this scenario, monthly withdrawal rates at wells FR–04 and FR–05 were decreased from their baseline rates to one-third their maximum practical rates for all months of the year; increased withdrawal rates at other Franklin wells were determined by the management model. The decrease in withdrawal rates at wells FR–04 and FR–05 resulted in a mean water-level altitude at the pond of 134.1 ft, which was equivalent to a 51 percent increase (improvement) in the mean annual water level of the pond relative to the baseline condition.
A third scenario was done to determine if Franklin’s existing water-supply system has the capacity to meet the mean annual maximum permitted withdrawal rate of the system of 3.45 million gallons per day while maintaining monthly withdrawal rates at wells FR–04 and FR–05 at their 2010–19 rates and water levels in Kingsbury Pond at baseline conditions. The analysis indicated that the capacity of the system cannot meet the increased demand during some months of the year with withdrawal rates at the two wells fixed at their monthly 2010–19 rates; however, the existing system is capable of meeting about 90 percent of the maximum permitted rate (3.10 million gallons per day) by increasing withdrawal rates at other Franklin wells above their 2010–19 rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235083","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Barlow, P.M., Friesz, P.J., and Barbaro, J.R., 2023, Evaluation of alternative groundwater-withdrawal scenarios on water levels in Kingsbury Pond, upper Charles River Basin, eastern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2023–5083, 36 p., https://doi.org/10.3133/sir20235083.","productDescription":"Report: viii, 36 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-141684","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501046,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115124.htm","linkFileType":{"id":5,"text":"html"}},{"id":419446,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V49N3R","text":"USGS data release","linkHelpText":"MODFLOW–2000 and management-optimization models used to evaluate alternative groundwater-withdrawal scenarios on water levels in Kingsbury Pond, upper Charles River Basin, eastern Massachusetts"},{"id":419445,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5083/images/"},{"id":419444,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5083/sir20235083.XML"},{"id":419442,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5083/sir20235083.pdf","text":"Report","size":"3.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5083"},{"id":419441,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5083/coverthb.jpg"},{"id":419443,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235083/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5083"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Upper Charles River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.61642753245717,\n 42.29469041974528\n ],\n [\n -71.61642753245717,\n 41.90357856449015\n ],\n [\n -71.16069045053953,\n 41.90357856449015\n ],\n [\n -71.16069045053953,\n 42.29469041974528\n ],\n [\n -71.61642753245717,\n 42.29469041974528\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Rattlesnakes play important roles in their ecosystems by regulating prey populations, are involved in complex coevolutionary dynamics with their prey, and exhibit a variety of unusual adaptations, including maternal care, heat-sensing pit organs, hinged fangs, and medically-significant venoms. The western rattlesnake (Crotalus oreganus) is one of the widest ranging rattlesnake species, with a distribution from British Columbia, where it is listed as threatened, to Baja California and east across the Great Basin to western Wyoming, Colorado and New Mexico. Here, we report a new reference genome assembly for one of six currently recognized subspecies, C. oreganus helleri, as part of the California Conservation Genomics Project (CCGP). Consistent with the reference genomic sequencing strategy of the CCGP, we used Pacific Biosciences HiFi long reads and Hi-C chromatin-proximity sequencing technology to produce a de novo assembled genome. The assembly comprises a total of 698 scaffolds spanning 1,564,812,557 base pairs, has a contig N50 of 64.7 Mb, a scaffold N50 of 110.8 Mb, and BUSCO complete score of 90.5%. This reference genome will be valuable for studies on the genomic basis of venom evolution and variation within Crotalus, in resolving the taxonomy of C. oreganus and its relatives, and for the conservation and management of rattlesnakes in general.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jhered/esad045","usgsCitation":"Westeen, E.P., Escalona, M., Holding, M., Beraut, E., Fairbairn, C., Marimuthu, M.P., Nguyen, O., Perri, R., Fisher, R., Toffelmier, E., Shaffer, H., and Wang, I.J., 2023, A genome assembly for the southern Pacific rattlesnake, Crotalus oreganus helleri, in the western rattlesnake species complex: Journal of Heredity, v. 114, no. 6, p. 681-689, https://doi.org/10.1093/jhered/esad045.","productDescription":"9 p.","startPage":"681","endPage":"689","ipdsId":"IP-153896","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442647,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jhered/esad045","text":"Publisher Index Page"},{"id":422778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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The CBLCM simulates infill development, residential and commercial development, natural land and agricultural land conversion, and growth served by sewer or septic wastewater treatment. The CBLCM is unique among land change models by simulating multiple types of development and explicitly accounting for infill development and the spatial patterns of development densities. The CBLCM was used to simulate five future land use scenarios, holding population constant, for all counties within and adjacent to the Chesapeake Bay watershed from 2013 to 2055. Results are presented here for the state of Maryland over the period 2013–2025 to illustrate model functionality and validation. The growth management (GM) scenario achieved the least development and potential impacts to natural and agricultural lands while accommodating the same amount of population growth as the other four scenarios. Scenarios focusing exclusively on natural or agricultural land protection shifted development to unprotected areas resulting in unforeseen water quality consequences. Simultaneously achieving more compact development while protecting the most valued natural and agricultural lands requires a combination of GM and land conservation policies and actions.
","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.13131","usgsCitation":"Claggett, P., Ahmed, L., Irani, F., McDonald, S., and Thompson, R., 2023, The Chesapeake Bay Land Change Model (CBLCM): Simulating future land use scenarios and potential impacts on water quality: Journal of the American Water Resources Association, 21-0151, 26 p., https://doi.org/10.1111/1752-1688.13131.","productDescription":"21-0151, 26 p.","ipdsId":"IP-134156","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":442650,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.13131","text":"Publisher Index Page"},{"id":419413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","noUsgsAuthors":false,"publicationDate":"2023-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Claggett, Peter 0000-0002-5335-2857","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":238920,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":879320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahmed, Labeeb 0000-0003-4524-9611","orcid":"https://orcid.org/0000-0003-4524-9611","contributorId":303117,"corporation":false,"usgs":true,"family":"Ahmed","given":"Labeeb","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irani, Frederick 0000-0002-2424-0135 firani@usgs.gov","orcid":"https://orcid.org/0000-0002-2424-0135","contributorId":303119,"corporation":false,"usgs":true,"family":"Irani","given":"Frederick","email":"firani@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonald, Sarah 0000-0003-3534-325X","orcid":"https://orcid.org/0000-0003-3534-325X","contributorId":303116,"corporation":false,"usgs":true,"family":"McDonald","given":"Sarah","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Renee 0000-0003-1463-5173 rthompson1@usgs.gov","orcid":"https://orcid.org/0000-0003-1463-5173","contributorId":303115,"corporation":false,"usgs":true,"family":"Thompson","given":"Renee","email":"rthompson1@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879324,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246624,"text":"ofr20231047 - 2023 - Multiple-well monitoring site within the Poso Creek Oil Field, Kern County, California","interactions":[],"lastModifiedDate":"2026-02-11T21:28:50.272733","indexId":"ofr20231047","displayToPublicDate":"2023-07-18T11:37:02","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":"2023-1047","displayTitle":"Multiple-Well Monitoring Site Within the Poso Creek Oil Field, Kern County, California","title":"Multiple-well monitoring site within the Poso Creek Oil Field, Kern County, California","docAbstract":"The Poso Creek Oil Field is one of the many fields selected for regional groundwater mapping and monitoring by the California State Water Resources Control Board as part of the Oil and Gas Regional Monitoring Program (RMP; California State Water Resources Control Board, 2015, 2022b; U.S. Geological Survey, 2022a). The U.S. Geological Survey (USGS), in cooperation with the California State Water Resources Control Board, is evaluating several questions about oil and gas development and groundwater resources in California, including (1) the location of groundwater resources; (2) the proximity of oil and gas operations to groundwater and the geologic materials between them; (3) evidence (or no evidence) of fluids from oil and gas sources in groundwater; and (4) the pathways or processes responsible when fluids from oil and gas sources are present in groundwater (U.S. Geological Survey, 2022a). As part of this evaluation, the USGS installed a multiple-well monitoring site within the administrative boundary of the Poso Creek Oil Field about 12 miles north of Bakersfield, California (fig. 1). Data collected at the Poso Creek multiple-well monitoring site (PCCT) provide information about the geology, hydrology, geophysical properties, and water quality of the aquifer system overlying the oil-bearing zone, thus enhancing understanding of relations between adjacent groundwater and the Poso Creek Oil Field in an area where groundwater data are limited, particularly at different depths in the aquifer. This report presents construction information for the PCCT and initial geohydrologic data collected from the site. Similar sites installed on the east side of the Lost Hills Oil Field and North and South Belridge Oil Fields were described by Everett and others (2020a, b).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231047","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Everett, R.R., McMahon, P.B., Stephens, M.J., Gillespie, J.M., Shepherd, M.M., and Fenton, N.C., 2023, Multiple-well monitoring site within the Poso Creek Oil Field, Kern County, California: U.S. Geological Survey Open-File Report 2023-1047, 11 p., https://doi.org/10.3133/ofr20231047.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-143467","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499783,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114968.htm","linkFileType":{"id":5,"text":"html"}},{"id":418877,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/preview/ofr20231047/full"},{"id":418876,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1047/images"},{"id":418875,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1047/ofr20231047.xml"},{"id":418874,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1047/ofr20231047.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":418873,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1047/covrthb.jpg"}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Poso Creek Oil Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.02751948230053,\n 35.55715768005527\n ],\n [\n -119.02751948230053,\n 35.37156425616723\n ],\n [\n -118.8051417495576,\n 35.37156425616723\n ],\n [\n -118.8051417495576,\n 35.55715768005527\n ],\n [\n -119.02751948230053,\n 35.55715768005527\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
The iconic and threatened Caribbean coral, Acropora palmata, is an essential reef-ecosystem engineer. Understanding the processes underpinning this coral’s survival and growth is essential to restoring this foundational species. Here, we compared replicate A. palmata colonies transplanted along 350 km of Florida’s offshore coral reef to determine holobiont and/or environmental variables that predict transplant success. We found a west-to-east gradient in coral physiology coupled with site-specific coral-associated microbiomes. Interestingly, no variables were linked to coral genet. Our results suggest that the unique oceanographic conditions with periodic upwelling events in the Dry Tortugas provide corals with greater opportunity for heterotrophy that in turn enhances coral growth and survivorship, and positively influences the microbiome. Our findings indicate that restoration efforts in the Dry Tortugas, and other places exhibiting higher food availability, could be most effective for A. palmata.
Climate change may induce mismatches between wildlife reproductive phenology and temporal occurrence of resources necessary for reproductive success. Verifying and elucidating the causal mechanisms behind potential mismatches requires large-scale, longer-duration data. We used eastern wild turkey (Meleagris gallopavo silvestris) nesting data collected across the southeastern U.S. over eight years to investigate potential climatic drivers of variation in nest initiation dates. We investigated climactic relationships with two datasets, one inclusive of successful and unsuccessful nests (full dataset) and another of just successful nests (successfully hatched dataset), to determine whether successfully hatched nests responded differently to weather changes than all nests did. In the full dataset, each 10 cm increase in January precipitation was associated with nesting occurring 0.46-0.66 days earlier, and each 10 cm increase in precipitation during the 30 days preceding nesting was associated with nesting occurring 0.17-0.21 days later. In the successfully hatched dataset, a 10 cm increase in March precipitation was associated with nesting occurring 0.67-0.74 days earlier, and an increase of one unit of variation in February maximum temperature was associated with nesting occurring 0.02 days later. We combined the results of these modeled relationships with multiple climate scenarios to understand potential implications of future climate change on wild turkey nesting phenology; results indicated that mean nest initiation date is projected to change by <0.1 day by 2040-2060. Wild turkey nesting phenology did not track changes in spring green-up timing, which could result in phenological mismatch between the timing of nesting and the availability of resources critical for successful reproduction.
The Ibex Hollow Tuff, 12.08 ± 0.03 Ma (40Ar/39Ar), is a widespread tephra layer erupted from the Bruneau-Jarbidge volcanic field of southern Idaho. Tephra from this eruption was deposited across much of western and central North America and adjacent ocean areas. We identified the Ibex Hollow Tuff at Trapper Creek, Idaho, near its eruption site, and at 15 distal sites, from the Pacific Ocean to the Gulf of Mexico, by the chemical composition of its glass shards, using electron-microprobe analysis, instrumental neutron activation analysis, and laser-ablation–inductively coupled plasma–mass spectrometry. By these methods, we distinguished the Ibex Hollow Tuff from overlying and underlying tephra layers near its source and at distal sites. Fluvially reworked Ibex Hollow Tuff ash was transported by the ancestral Mississippi River drainage from the interior of the North American continent to the Gulf of Mexico, where it is present within an ~50-m-thick deposit in marine sediments in the subsurface. The minimum fallout area covered by the ash is ~2.7 million km2, with a minimum volume of ~800 km3, and potential dispersal farther to the north and northeast. The areal distribution for the Ibex Hollow Tuff is similar to that of the Lava Creek B (0.63 Ma) supereruption. The Ibex Hollow Tuff represents a unique chronostratigraphic marker allowing a synoptic view of paleoenvironments at a virtual moment in time across a large terrestrial and marine region. The Ibex Hollow Tuff is also an important marker bed for North American Land Mammal Ages, and it coincides with climatic cooling in the middle to late Miocene documented in marine cores.
The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across multiple burn areas. We used this inventory to evaluate the predictive performance of the US Geological Survey M1 likelihood model, a tool that presently underlies the emergency assessment of postfire debris-flow hazards in the western USA. To test model performance, we used the threat score skill statistic and found that the rainfall thresholds estimated by the M1 model for the Central California coast performed similarly to training (Southern California) and testing (Intermountain West) data associated with the original model calibration. Model performance decreased when differentiating between “minor” and “major” postfire hydrologic response types, which weigh effects on human life and infrastructure. Our results underscore that the problem of false positives is a major challenge for developing accurate rainfall thresholds for the occurrence of postfire debris flows. As wildfire activity increases throughout the western USA, so too will the demand for the assessment of postfire debris-flow hazards. We conclude that additional collection of field-verified inventories of postfire hydrologic response will be critical to prioritize which model variables may be suitable candidates for regional calibration or replacement.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-023-02106-7","usgsCitation":"Thomas, M.A., Kean, J.W., McCoy, S., Lindsay, D.N., Kostelnik, J., Cavagnaro, D.B., Rengers, F.K., East, A.E., Schwartz, J., Smith, D.P., and Collins, B.D., 2023, Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards: Landslides, v. 20, p. 2421-2436, https://doi.org/10.1007/s10346-023-02106-7.","productDescription":"16 p.","startPage":"2421","endPage":"2436","ipdsId":"IP-139528","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442830,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index 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aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":877150,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schwartz, Jonathan","contributorId":312505,"corporation":false,"usgs":false,"family":"Schwartz","given":"Jonathan","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":877151,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Douglas P.","contributorId":201716,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"P.","affiliations":[{"id":35924,"text":"California State University, Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":877152,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":877153,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70246616,"text":"70246616 - 2023 - A detailed view of the 2020-2023 southwestern Puerto Rico seismic sequence with deep learning","interactions":[],"lastModifiedDate":"2023-12-04T16:59:36.832347","indexId":"70246616","displayToPublicDate":"2023-07-06T08:36:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A detailed view of the 2020-2023 southwestern Puerto Rico seismic sequence with deep learning","docAbstract":"The 2020–2023 southwestern Puerto Rico seismic sequence, still ongoing in 2023, is remarkable for its multiple‐fault rupture complexity and elevated aftershock productivity. We applied an automatic workflow to continuous data from 43 seismic stations in Puerto Rico to build an enhanced earthquake catalog with ∼180,000 events for the 3+ yr sequence from 28 December 2019 to 1 January 2023. This workflow contained the EQTransformer (EQT) deep learning model for event detection and phase picking, the EikoNet‐Hypocenter Inversion with Stein Variational Inference probabilistic earthquake location approach with a neural network trained to solve the eikonal wave equation, and relocation with event‐pair waveform cross correlation. EQT increased the number of catalog events in the sequence by about seven times, though its performance was not quite as good as thorough analyst review. The enhanced catalog revealed new structural details of the sequence space–time evolution, including sudden changes in activity, on a complex system of many small normal and strike‐slip faults. 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Macrophage aggregate (MA) abundance in fish is a useful general biomarker of contaminant exposures and environmental stress. Hepatic and splenic MAs were evaluated in semi-anadromous white perch Morone americana (Gmelin, 1789) from the urbanized Severn River (S) and the more rural Choptank River (C), Chesapeake Bay. Fish were collected from different sites in the annual migratory circuit in each river that corresponded to active spawning in late winter-early spring, summer regenerating, autumn developing, and winter spawning-capable phases. An age-associated progressive increase in the total volume of MAs (MAV) was evident in the liver and spleen. Mean hepatic MAV (range in seasonal means, C: 6.4-23.1 mm3; S: 15.7-48.7 mm3) and mean splenic MAV (C: 7.3-12.6 mm3; S: 16.0-33.0 mm3) differed significantly among seasons and were significantly greater in females and in Severn River fish. Age and river were the most influential factors, suggesting that increased MAV in Severn River fish resulted from chronic exposures to higher concentrations of environmental contaminants. Hepatic MAV was directly related to the relative volume of copper granules in the liver. Less influential factors on splenic MAV included fish condition, trematode infections, and granulomas, indicating possible functional differences in MAs by organ. While organ volumes were strongly linked to gonadosomatic index (GSI) and reproductive phase, the reason for seasonal differences in MAV was less clear. Water temperature, salinity, and dissolved oxygen were not significantly related to MAV, and indicators of reproductive phase (hepatosomatic index and GSI) were significant but less important in explaining variation in MAV.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/dao03734","usgsCitation":"Blazer, V., Matsche, M.A., and Pulster, E.L., 2023, White perch health relative to urbanization and habitat degradation in Chesapeake Bay tributaries. II. Hepatic and splenic macrophage aggregates: Diseases of Aquatic Organisms, v. 154, p. 107-130, https://doi.org/10.3354/dao03734.","productDescription":"24 p.","startPage":"107","endPage":"130","ipdsId":"IP-146829","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":419144,"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 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I. Biliary neoplasms and hepatic lesions","interactions":[],"lastModifiedDate":"2023-07-19T11:43:15.216964","indexId":"70246797","displayToPublicDate":"2023-07-06T06:38:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"title":"White perch health relative to urbanization and habitat degradation in Chesapeake Bay tributaries. I. Biliary neoplasms and hepatic lesions","docAbstract":"White perch Morone americana (Gmelin, 1789) from the Chesapeake Bay (USA) watershed have a high incidence of liver disease, including neoplasms of bile duct origin. Fish collected seasonally from spring 2019 to winter 2020 from the urban Severn River and the more rural Choptank River were evaluated for hepatic lesions. Biliary hyperplasia (64.1%), neoplasms (cholangioma and cholangiocarcinoma, 27%), and dysplasia (24.9%) were significantly higher in Severn River fish compared to Choptank River fish (52.9, 16.2, and 15.8%, respectively). Hepatocellular lesions were less common, including foci of hepatocellular alteration (FHA, 13.3%) and hepatocellular neoplasms (1%). There was also a progressive age-related increase in copper-laden granules in hepatocytes, which was a significant risk factor for FHA and could be a source of oxidative stress in the liver. Significant risk factors for biliary neoplasms included age, bile duct fibrosis, and infections by the myxozoan parasite Myxidium murchelanoi, but the prevalence and relative intensity of M. murchelanoi infections did not differ significantly between fish populations. Hepatic disease in this species appears to be chronic and may stem from an age-related accumulation of damage, possibly from parasitic infections and contaminants such as polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), and copper. Watershed development and exposures to PCBs and PAHs were generally higher for white perch in the Severn River, but similar suites of chemical contaminants were detected in the Choptank River. A broader survey of white perch within and outside Chesapeake Bay may allow determination of the extent of biliary neoplasia in this species.
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sturgeon Acipenser oxyrinchus oxyrinchus was once of great commercial importance in many coastal rivers of the eastern USA. Over the 19th and 20th centuries, most historical stocks of Atlantic sturgeon were depleted by human activities. Estimating recruitment for the remaining populations is challenging due to sampling constraints, limited age data, and natural variability. However, recruitment estimates could inform recovery efforts. The objectives of this study were to compare 2 modeling approaches to estimate recruitment of age-1 Atlantic sturgeon and provide an updated index of abundance across more than a decade of sampling in the Altamaha River, Georgia. First, we constructed capture histories of river-resident juveniles, using capture-mark-recapture data collected from 2008 to 2020, and assigned ages based on length-frequency analysis. Second, we compared more traditional Huggins closed population models and a recent nonlinear extension of Huggins models—vector generalized additive models (VGAMs)—to estimate abundance of age-1 fish. Both model types indicated similar yearly age-1 abundance estimates (Huggins: 163 in 2017 to 3839 in 2010; VGAM: 312 in 2020 to 4448 in 2010), but the VGAMs provided more direct interpretation for factors that might affect capture probability (e.g. sampling effort, temperature, fish length). This study indicates that the age-1 Altamaha River Atlantic sturgeon population has remained relatively stable over the past decade and provides a long-term baseline which will better enable managers to assess the effects of either future restoration actions or environmental disturbances on the population.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01250","usgsCitation":"Baker, M., Ingram, E., Higginbotham, D., Irwin, B., and Fox, A., 2023, Refining capture-recapture recruitment estimation methods for Atlantic sturgeon: Endangered Species Research, v. 51, p. 203-214, https://doi.org/10.3354/esr01250.","productDescription":"12 p.","startPage":"203","endPage":"214","ipdsId":"IP-143737","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432972,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":442856,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01250","text":"Publisher Index Page"}],"country":"United States","state":"Georgia","otherGeospatial":"Altamaha River estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.48760060177855,\n 31.490539509150565\n ],\n [\n -81.48760060177855,\n 31.14793158914553\n ],\n [\n -81.23488559221977,\n 31.14793158914553\n ],\n [\n -81.23488559221977,\n 31.490539509150565\n ],\n [\n -81.48760060177855,\n 31.490539509150565\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baker, M.A.","contributorId":340977,"corporation":false,"usgs":false,"family":"Baker","given":"M.A.","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ingram, E.C.","contributorId":340978,"corporation":false,"usgs":false,"family":"Ingram","given":"E.C.","email":"","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":907757,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higginbotham, D.L.","contributorId":340979,"corporation":false,"usgs":false,"family":"Higginbotham","given":"D.L.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, Brian J. 0000-0002-0666-2641","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":280043,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907759,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fox, A.G.","contributorId":340980,"corporation":false,"usgs":false,"family":"Fox","given":"A.G.","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":907760,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262161,"text":"70262161 - 2023 - Biotic and abiotic factors shaping bat activity in Maryland soybean fields","interactions":[],"lastModifiedDate":"2025-01-15T16:06:14.466194","indexId":"70262161","displayToPublicDate":"2023-07-03T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Biotic and abiotic factors shaping bat activity in Maryland soybean fields","docAbstract":"Bats are important pest control agents in agriculture. Yet, the underlying fine-scale biotic and abiotic mechanisms that drive their foraging behaviors and responses to insect outbreaks are unclear. Herbivore-induced plant volatiles (HIPVs) can attract both invertebrate and vertebrate natural enemies that use the chemical plant cues to locate insect prey. The ability of HIPVs to attract multiple species raises the question of whether they may also be a biotic factor influencing insectivorous bat activity. Additionally, abiotic factors, such as weather conditions, can affect bat activity in agricultural settings, but little is known about how bats respond to shifting environmental conditions on short timescales in this landscape context. Using a model crop system, soybean (Glycine max), our study asked three questions: (1) Which bat species are active in eastern Maryland soybean fields? (2) Is insectivorous bat activity affected by naturally occurring soybean HIPVs and/or synthetic soybean HIPVs (indole or farnesene)? (3) How is insectivorous bat activity affected by hourly weather conditions in this landscape? In soybean fields in eastern Maryland, we created paired treatment plots: HIPV plots (damaged plants or synthetic HIPV dispensers) and control plots (undamaged plants or empty dispensers). We measured bat activity using ultrasonic recorders, summarizing hourly and nightly activity, and detected 10 total species. The most abundant species were big brown/silver-haired bats (Eptesicus fuscus/Lasionycteris noctivagans). Bat activity did not significantly differ between control and HIPV plots in any of the three experiments. Thus, our results do not support our expectation that bats in eastern Maryland use soybean HIPVs to locate insect prey. However, bat activity did increase with increasing average hourly temperature and wind speed. This initial study of bats and HIPVs, as well as the fine-scale examination of weather conditions on bat activity, may serve as a guide for future research on bat–plant interactions that can support the development of new strategies for sustainable pest management.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4575","usgsCitation":"Maynard, L., Ford, W., Parker, J., and Whitehead, S., 2023, Biotic and abiotic factors shaping bat activity in Maryland soybean fields: Ecosphere, v. 14, no. 7, e4575, 13 p., https://doi.org/10.1002/ecs2.4575.","productDescription":"e4575, 13 p.","ipdsId":"IP-145893","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4575","text":"Publisher Index Page"},{"id":466422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":22,\"properties\":{\"name\":\"Maryland\",\"nation\":\"USA 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Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":923305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parker, John D.","contributorId":348247,"corporation":false,"usgs":false,"family":"Parker","given":"John D.","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":923306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitehead, Susan R.","contributorId":348249,"corporation":false,"usgs":false,"family":"Whitehead","given":"Susan R.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":923307,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247321,"text":"70247321 - 2023 - Cryptic tolerant fish species and their potential effect on index of biotic integrity (IBI) scores","interactions":[],"lastModifiedDate":"2023-07-27T16:32:22.397158","indexId":"70247321","displayToPublicDate":"2023-06-28T11:29:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic tolerant fish species and their potential effect on index of biotic integrity (IBI) scores","docAbstract":"Indices such as the Index of Biotic Integrity (IBI) are often used by management agencies to estimate the abstract property of stream health. These indices are usually predicated on the belief that certain fish species are tolerant to environmental perturbation while others are sensitive. Species are usually designated as either tolerant or sensitive in these analyses based on inherent ecological or taxonomic characteristics. However, previous literature has shown that certain species from ecological or taxonomic “sensitive” groups experience increased abundance in degraded streams. We term such species “cryptic tolerants”. Using a stream fish assemblage dataset of 433 unique sample locations across the state of Alabama and the National Landcover Dataset, our objectives were to 1) identify the most common cryptic tolerant species, 2) investigate how cryptic tolerant species might inflate indices of stream health, and 3) compare an alternative measure of stream health in which species are statistically defined rather than defined using the traditional trait-based approach. We identified cryptic tolerants using Nonmetric Multidimensional Scaling in six ecoregions. A series of regressions revealed that the proportion of cryptic tolerant species decreased in response to an increasing proportion of forested land in catchments while the proportion of true sensitives increased in all ecoregions except for the Cumberland Plateau. An index that simply used the percentage of statistically defined, non-tolerant species generally had lower p-values and higher r2 values than IBI scores when both were regressed against percentage of forest in catchment. However, both indices had low degrees of correlation with expected disturbance, indicating a univariate index may be inadequate to characterize stream health. Our results highlight a potential issue with applying the IBI to diverse southeastern systems in the United States, which may be alleviated by designating species sensitivity based on empirical response to disturbance rather than taxonomic or ecological characteristics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2023.110546","usgsCitation":"Hilburn, B.G., Freeman, M., Lawson, K., Rider, S.J., and Johnston, C.E., 2023, Cryptic tolerant fish species and their potential effect on index of biotic integrity (IBI) scores: Ecological Indicators, v. 154, 110546, 13 p., https://doi.org/10.1016/j.ecolind.2023.110546.","productDescription":"110546, 13 p.","ipdsId":"IP-150939","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":442924,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2023.110546","text":"Publisher Index Page"},{"id":419401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"154","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hilburn, Bryson G.","contributorId":317735,"corporation":false,"usgs":false,"family":"Hilburn","given":"Bryson","email":"","middleInitial":"G.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":879202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":879203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawson, Katelyn M.","contributorId":201981,"corporation":false,"usgs":false,"family":"Lawson","given":"Katelyn M.","affiliations":[{"id":36314,"text":"University of Florida/IFAS","active":true,"usgs":false}],"preferred":false,"id":879204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rider, Steven J.","contributorId":317736,"corporation":false,"usgs":false,"family":"Rider","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":35940,"text":"Alabama Division of Wildlife and Freshwater Fisheries","active":true,"usgs":false}],"preferred":false,"id":879205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnston, Carol E.","contributorId":317737,"corporation":false,"usgs":false,"family":"Johnston","given":"Carol","email":"","middleInitial":"E.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":879206,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246263,"text":"70246263 - 2023 - Modeling the maturation history of the stacked petroleum systems of the Williston Basin, USA","interactions":[],"lastModifiedDate":"2023-06-29T11:44:43.799768","indexId":"70246263","displayToPublicDate":"2023-06-27T06:41:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the maturation history of the stacked petroleum systems of the Williston Basin, USA","docAbstract":"A three-dimensional petroleum systems model was built to support U.S. Geological Survey assessments of undiscovered oil and gas resources in the Williston Basin of North Dakota, Montana, and South Dakota. Numerous Paleozoic source rocks have been proven or postulated in the basin, of which five were the focus of maturation and migration modeling: the Ordovician Icebox Formation, the kukersite beds of the Ordovician Red River Formation, the shales of the Devonian–Mississippian Bakken Formation, the Mississippian Madison Group, and the Pennsylvanian Tyler Formation. Calibration of the three-dimensional model to present-day temperature data indicates the existence of a north-south trend of high heat flow in western North Dakota, along with a region of high heat flow in eastern Montana. These high heat flow trends strongly control the maturity of all studied source intervals. A Bakken-specific hydrocarbon generation kinetic model was developed to match the calibrated time-temperature history of the basin to spatial trends in hydrogen index from programmed pyrolysis data. Generation of hydrocarbons occurred in the Cretaceous through Paleogene due to increased burial. Subsequent uplift and erosion in the Neogene cooled the basin, ending hydrocarbon generation for all source rocks. The cumulative volume of hydrocarbons generated by each of the source rocks was calculated and used to compare their relative robustness. The shales of the Bakken Formation are estimated to have generated approximately 460 billion barrels of oil equivalent (BBOE), while the Red River Formation generated approximately 130 BBOE, the Tyler Formation 94 BBOE, the Madison Group 44 BBOE, and the Icebox Formation 28 BBOE. Gross migration trends were analyzed with respect to historical oil and gas production in the basin and generally indicate segregation of petroleum systems throughout the stratigraphic column. However, most modeled scenarios indicated significant loss of Bakken oil to the Madison Group, suggesting that mixing of Madison and Bakken oils may be more prevalent than has recently been recognized in the U.S. portion of the Williston Basin and is particularly likely in fractured regions of the basin.
The Upper Cretaceous (Turonian?) Middendorf Formation is a sand-rich stratigraphic unit of fluvial origin that forms a large aquifer in the U.S. Atlantic Coastal Plain. In Chesterfield County (South Carolina), which is the site of the type locality, the formation ranges in thickness from 66.5 to > 119.7 meters. The base of the formation is an unconformity above Paleozoic metasiltstone, and the upper contact is an unconformity above which lies sand of the Quaternary Pinehurst Formation. Outcrops display the following five facies assemblages: 1) sandstone to conglomeratic sandstone (fluvial bar and channel deposits), 2) beds of alternating laminae of sandstone and mudstone (fluvial overbank or floodplain deposits), 3) ≥ 1 m-thick beds of clay (swamp deposits, floodplain deposits, and/or sediment that accumulated in abandoned fluvial channels), 4) 0.2–0.5 m-thick planar to slightly undulatory beds of framework-supported sandstone with a mud matrix (traction-dominated current deposits at the top of fluvial bars, upper-flow-regime bedform deposits in subsidiary fluvial channels, or coarse-grained overbank deposits), and 5) sandstone to conglomeratic sandstone cemented by iron (interpreted as fluvial bar and channel deposits, with the iron cement being a diagenetic “groundwater ferricrete” that formed via the circulation of shallow groundwater and the oxidation of iron-bearing minerals). Kaolinite in various forms is pervasive throughout the formation and is interpreted as an early diagenetic phenomenon that formed by prolonged postdepositional weathering and flushing by meteoric water under a warm and humid paleoclimate.
The fluvial system that formed the Middendorf Formation prograded into the area from the west or northwest from uplifted margins of Mesozoic rift basins and/or the Appalachian Mountains. This progradation was a response to a base-level fall and the sediment accumulated during base-level lowstand and subsequent early transgression. In Chesterfield County, the Middendorf Formation can be subdivided into three fining-upward sequences. Each sequence consists predominantly of medium to coarse sand with a greater abundance of gravel in the lower part of the sequence and a greater abundance of clay and silt beds in the upper part. Each sequence is interpreted as either a response to autogenic processes or a response to allogenic sea-level changes, specifically a higher-order (higher-frequency) progression from relative lowstand conditions to early transgression whereby coarse sand and gravel (e.g., fluvial bar and channel deposits) were preserved during initial lowstand conditions and a greater proportion of mud and finer-grained sand (floodplain deposits) were preserved during subsequent early transgression. The Middendorf Formation is correlative with several other kaolinite-rich fluvial sandstones in North America including the Raritan Formation in New Jersey, the Tuscaloosa Formation of the eastern Gulf of Mexico (Alabama, Mississippi, Louisiana), the Woodbine Formation of the central Gulf of Mexico (Texas), and the Frontier Formation of Wyoming. The accumulation and preservation of these formations occurred in response to a Turonian eustatic sea-level fall and subsequent transgression, and the early diagenetic kaolinite in these formations is attributed to similar warm and humid paleoclimate conditions.
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Middendorf Formation, Chesterfield County, South Carolina, U.S.A.: Journal of Sedimentary Research, v. 93, p. 327-349, https://doi.org/10.2110/jsr.2022.034.","productDescription":"23 p.","startPage":"327","endPage":"349","ipdsId":"IP-134100","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":418461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","county":"Chesterfield County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-80.32,34.8137],[-80.2121,34.8121],[-79.9763,34.8089],[-79.9248,34.8084],[-79.9345,34.8027],[-79.9346,34.7977],[-79.9277,34.7681],[-79.9244,34.7645],[-79.9044,34.752],[-79.8945,34.7437],[-79.8864,34.7269],[-79.8781,34.7159],[-79.8723,34.694],[-79.8536,34.672],[-79.8408,34.6696],[-79.8298,34.6568],[-79.8175,34.659],[-79.8092,34.6511],[-79.7959,34.6478],[-79.7959,34.6456],[-79.7987,34.6429],[-79.8021,34.6402],[-79.7927,34.6337],[-79.7916,34.6324],[-79.7894,34.631],[-79.79,34.6296],[-79.7912,34.6242],[-79.7852,34.6182],[-79.7791,34.6159],[-79.778,34.6131],[-79.7831,34.6077],[-79.787,34.6064],[-79.7937,34.606],[-79.7992,34.6102],[-79.8026,34.6102],[-79.8054,34.608],[-79.8095,34.5989],[-79.809,34.593],[-79.8085,34.5862],[-79.8103,34.5807],[-79.8148,34.5758],[-79.8183,34.5722],[-79.8289,34.5346],[-79.8378,34.5356],[-79.8423,34.5343],[-79.8474,34.5289],[-79.8592,34.5204],[-79.8621,34.5104],[-79.8723,34.5041],[-79.8746,34.5001],[-79.8852,34.4943],[-79.8931,34.4916],[-79.902,34.4921],[-79.9125,34.4963],[-79.9203,34.4973],[-79.9422,34.4902],[-79.9623,34.4868],[-79.9673,34.4891],[-79.9733,34.4969],[-79.9772,34.4992],[-79.9877,34.5002],[-80.0001,34.4971],[-80.0141,34.4904],[-80.0247,34.4855],[-80.0336,34.4874],[-80.0425,34.4916],[-80.2867,34.3711],[-80.2871,34.3929],[-80.2993,34.3975],[-80.3053,34.4089],[-80.3108,34.4144],[-80.3141,34.4226],[-80.3224,34.4272],[-80.3318,34.4409],[-80.3272,34.4522],[-80.3304,34.4731],[-80.3273,34.499],[-80.3289,34.5081],[-80.3378,34.5145],[-80.3456,34.5146],[-80.3534,34.5205],[-80.3566,34.5346],[-80.3715,34.5506],[-80.3743,34.5597],[-80.3742,34.5679],[-80.3814,34.5761],[-80.3791,34.5865],[-80.3951,34.603],[-80.4079,34.613],[-80.4168,34.6162],[-80.4122,34.6271],[-80.4228,34.6344],[-80.4339,34.6404],[-80.4344,34.6477],[-80.4305,34.6576],[-80.4332,34.6599],[-80.4394,34.6604],[-80.4488,34.6682],[-80.4516,34.6759],[-80.4599,34.6787],[-80.476,34.6983],[-80.4871,34.7061],[-80.4904,34.7229],[-80.5153,34.7593],[-80.5141,34.7666],[-80.5247,34.7707],[-80.5303,34.7798],[-80.5437,34.7853],[-80.5559,34.8013],[-80.5614,34.8157],[-80.4444,34.8148],[-80.32,34.8137]]]},\"properties\":{\"name\":\"Chesterfield\",\"state\":\"SC\"}}]}","volume":"93","noUsgsAuthors":false,"publicationDate":"2023-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":876250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzwater, Bradley A.","contributorId":177211,"corporation":false,"usgs":false,"family":"Fitzwater","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":876251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whittecar, G. Richard","contributorId":313541,"corporation":false,"usgs":false,"family":"Whittecar","given":"G. 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Drinking-water exposures to per- and poly-fluoroalkyl substances (PFAS) are a national concern, however, there is limited information on PFAS in residential tapwater at the point-of-use, especially from private-wells. We conducted a national reconnaissance to compare human PFAS exposures in unregulated private-well and regulated public-supply tapwater. Tapwater from 716 locations (269 private-wells; 447 public supply) across the US was collected during 2016–2021 including three locations where temporal sampling was conducted. Concentrations of PFAS were assessed by three laboratories and compared with land-use and potential-source metrics to explore drivers of contamination. The number of individual PFAS observed ranged from 1 to 9 (median: 2) with corresponding cumulative concentrations (sum of detected PFAS) ranging from 0.348 to 346 ng/L. Seventeen PFAS were observed at least once with PFBS, PFHxS and PFOA observed most frequently in approximately 15% of the samples. Across the US, PFAS profiles and estimated median cumulative concentrations were similar among private wells and public-supply tapwater. We estimate that at least one PFAS could be detected in about 45% of US drinking-water samples. These detection probabilities varied spatially with limited temporal variation in concentrations/numbers of PFAS detected. Benchmark screening approaches indicated potential human exposure risk was dominated by PFOA and PFOS, when detected. Potential source and land-use information was related to cumulative PFAS concentrations, and the number of PFAS detected; however, corresponding relations with specific PFAS were limited likely due to low detection frequencies and higher detection limits. Information generated supports the need for further assessments of cumulative health risks of PFAS as a class and in combination with other co-occurring contaminants, particularly in unmonitored private-wells where information is limited or not available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envint.2023.108033","usgsCitation":"Smalling, K., Romanok, K.M., Bradley, P.M., Morriss, M.C., Gray, J., Kanagy, L.K., Gordon, S.E., Williams, B., Breitmeyer, S.E., Jones, D.K., DeCicco, L.A., Eagles-Smith, C., and Wagner, T., 2023, Per- and polyfluoroalkyl substances (PFAS) in United States tapwater: Comparison of underserved private-well and public-supply exposures and associated health implications: Environment International, v. 178, 108033, 12 p., https://doi.org/10.1016/j.envint.2023.108033.","productDescription":"108033, 12 p.","ipdsId":"IP-137132","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science 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Water Information","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876204,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":876205,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":876206,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70247338,"text":"70247338 - 2023 - The March 1940 superstorm: Geoelectromagnetic hazards and impacts on American communication and power systems","interactions":[],"lastModifiedDate":"2023-07-27T15:39:00.979793","indexId":"70247338","displayToPublicDate":"2023-06-22T10:35:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"The March 1940 superstorm: Geoelectromagnetic hazards and impacts on American communication and power systems","docAbstract":"An analysis is made of geophysical records of the 24 March 1940, magnetic storm and related reports of interference on long-line communication and power systems across the contiguous United States and, to a lesser extent, Canada. Most long-line system interference occurred during local daytime, after the second of two storm sudden commencements and during the early part of the storm's main phase. The high degree of system interference experienced during this storm is inferred to have been due to unusually large-amplitude and unusually rapid geomagnetic field variation, possibly driven by interacting interplanetary coronal-mass ejections. Geomagnetic field variation, in turn, induced geoelectric fields in the electrically conducting solid Earth, establishing large potential differences (voltages) between grounding points at communication depots and transformer substations connected by long transmission lines. It is shown that March 1940 storm-time communication- and power-system interference was primarily experienced over regions of high electromagnetic surface impedance, mainly in the upper Midwest and eastern United States. Potential differences measured on several grounded long lines during the storm exceeded 1-min resolution voltages that would have been induced by the March 1989 storm. In some places, voltages exceeded American electric-power-industry benchmarks. It is concluded that the March 1940 magnetic storm was unusually effective at inducing geoelectric fields. Although modern communication systems are now much less dependent on long electrically conducting transmission lines, modern electric-power-transmission systems are more dependent on such lines, and they, thus, might experience interference with the future occurrence of a storm as effective as that of March 1940.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022SW003379","usgsCitation":"Love, J.J., Rigler, E.J., Hartinger, M.D., Lucas, G., Kelbert, A., and Bedrosian, P.A., 2023, The March 1940 superstorm: Geoelectromagnetic hazards and impacts on American communication and power systems: Space Weather, v. 21, no. 6, e2022SW003379, 22 p., https://doi.org/10.1029/2022SW003379.","productDescription":"e2022SW003379, 22 p.","ipdsId":"IP-152212","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":442987,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022sw003379","text":"Publisher Index Page"},{"id":419393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartinger, Michael D 0000-0002-2643-2202","orcid":"https://orcid.org/0000-0002-2643-2202","contributorId":296645,"corporation":false,"usgs":false,"family":"Hartinger","given":"Michael","email":"","middleInitial":"D","affiliations":[{"id":48422,"text":"Space Science Institute","active":true,"usgs":false}],"preferred":false,"id":879261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":223556,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":879262,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879263,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":879264,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70245777,"text":"70245777 - 2023 - Mapping abandoned uranium mine features using Worldview-3 imagery in portions of Karnes, Atascosa and Live Oak Counties, Texas","interactions":[],"lastModifiedDate":"2023-06-27T12:00:36.399687","indexId":"70245777","displayToPublicDate":"2023-06-22T06:54:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":15678,"text":"MDPI-Minerals","active":true,"publicationSubtype":{"id":10}},"title":"Mapping abandoned uranium mine features using Worldview-3 imagery in portions of Karnes, Atascosa and Live Oak Counties, Texas","docAbstract":"In urbanized areas, the “freshwater salinization syndrome” (FSS), which pertains to long-term increases in concentrations of major ions and metals in fresh surface waters, has been attributed to road salt application. In addition to FSS, the water composition changes as an influx of sodium (Na+) in recharge may displace calcium (Ca2+), magnesium (Mg2+), potassium (K+), and trace metals by reverse cation exchange. These changing ion fluxes can result in adverse impacts on groundwater and surface waters used for municipal supplies. Few datasets exist to quantify the FSS on a watershed scale or link its manifestation to potential controlling factors such as changes in urban development, land use/land cover (LULC), or wastewater treatment plant (WWTP) discharges in upstream areas. Here, we use two decades (1999–2019) of monthly streamwater quality data combined with daily streamflow for six exurban and suburban watersheds in southeastern Pennsylvania to examine the relations among Ca2+, Mg2+, K+, Na+, chloride (Cl−), sulfate (SO42-), and alkalinity (HCO3−) concentrations and upstream controlling factors. Flow-normalized annual and baseflow (August ̶ November) concentrations for Ca2+, Mg2+, Na+, and Cl− increased in all six watersheds over the 20-year study, providing evidence of FSS’s impacts on groundwater that sustains streamflow. Additionally, a redundancy analysis using 2019 flow-normalized values identified the following positive associations between solute concentrations and controlling variables: 1) Cl−, Mg2+, and Ca2+ with impervious surface cover (ISC), 2) Na+ and SO42- with ISC and total WWTP discharge volume, and 3) HCO3− with agriculture and total WWTP discharge volume. From a human health perspective, 2019 flow-normalized Na+ concentrations exceeded the U.S. Environmental Protection Agency’s 20 mg L-1 threshold for individuals restricted to a low sodium diet. Furthermore, indices used to evaluate the corrosivity of source waters to drinking water infrastructure and inform municipal water treatment practices, such as the Chloride to Sulfate Mass Ratio and Larson Ratio, increased between two- and seven-fold over the 20-year time. Collectively, the results elucidate the causal factors of the FSS in suburban and exurban watersheds and its potential impacts on human health and drinking water infrastructure.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2023.1153133","usgsCitation":"Rossi, M.L., Kremer, P., Cravotta, C., Seng, K.E., and Goldsmith, S.T., 2023, Land development and road salt usage drive long-term changes in major-ion chemistry of streamwater in six exurban and suburban watersheds, southeastern Pennsylvania, 1999-2019: Frontiers in Environmental Science, v. 11, 1153133, 21 p ., https://doi.org/10.3389/fenvs.2023.1153133.","productDescription":"1153133, 21 p .","ipdsId":"IP-147665","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":443021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1153133","text":"Publisher Index Page"},{"id":418218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Chester Creek, Crum Creek, East Branch Brandywine Creek, Neshaminy Creek, Perkiomen Creek, Ridley Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.5237058720174,\n 39.713850779802925\n ],\n [\n -74.67929211102248,\n 39.713850779802925\n ],\n [\n -74.67929211102248,\n 40.9985953543042\n ],\n [\n -76.5237058720174,\n 40.9985953543042\n ],\n [\n -76.5237058720174,\n 39.713850779802925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Rossi, Marissa Lee 0000-0003-2341-0312","orcid":"https://orcid.org/0000-0003-2341-0312","contributorId":310430,"corporation":false,"usgs":true,"family":"Rossi","given":"Marissa","email":"","middleInitial":"Lee","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kremer, Peleg","contributorId":296521,"corporation":false,"usgs":false,"family":"Kremer","given":"Peleg","email":"","affiliations":[{"id":12766,"text":"Villanova University","active":true,"usgs":false}],"preferred":false,"id":875663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cravotta, Charles A. 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To reveal migration patterns, and understand drivers of over-water flight, we captured and radio-tagged 115 eastern red bats using novel technology, and subsequently tracked and described their movements throughout the region. We compared over-water flight movements to randomly generated patterns using a use-availability framework, and subsequently used a generalized linear mixed effects model to assess the relationship of over-water flight to atmospheric variables. We used hidden Markov models to assess daily activity patterns and site residency. Most bats with long-distance movements traveled in a southwesterly direction, however path vectors were often oriented interior toward the continental landmass rather than along the coastline. We observed that some bats transited wide sections of the Chesapeake and Delaware bays, confirming their ability to travel across large water bodies. This over-water flight typically occurred in the early hours of the night and during favorable flying conditions. If flight over large water bodies is a proxy for over-ocean flight, then collision risk at offshore wind turbines – a major source of migratory bat fatalities – may be linked nightly to warm temperatures that occur early in the fall season. Risk, then, may be somewhat predictable and manageable with mitigation options linking wind-energy operation to weather conditions and seasonality.
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\"}}]}","volume":"11","issue":"35","noUsgsAuthors":false,"publicationDate":"2023-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"True, Michael C.","contributorId":270631,"corporation":false,"usgs":false,"family":"True","given":"Michael C.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":910116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorman, Katherine M.","contributorId":270924,"corporation":false,"usgs":false,"family":"Gorman","given":"Katherine","email":"","middleInitial":"M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":910117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Hila","contributorId":270923,"corporation":false,"usgs":false,"family":"Taylor","given":"Hila","email":"","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":910118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reynolds, Richard J.","contributorId":348217,"corporation":false,"usgs":false,"family":"Reynolds","given":"Richard J.","affiliations":[{"id":83324,"text":"Virginia Dept. of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":910119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":910120,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246291,"text":"70246291 - 2023 - Long-term effects of timber harvest on ephemeral pool and occupancy of Spotted Salamanders (Ambystoma maculatum) and Wood Frogs (Lithobates sylvaticus)","interactions":[],"lastModifiedDate":"2023-06-30T12:10:12.357923","indexId":"70246291","displayToPublicDate":"2023-06-14T07:06:11","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Long-term effects of timber harvest on ephemeral pool and occupancy of Spotted Salamanders (Ambystoma maculatum) and Wood Frogs (Lithobates sylvaticus)","docAbstract":"The effects of timber harvest on amphibians can be complex and persist for years postharvest, but overall they are poorly understood. We examined how timber harvest has impacted two pool-breeding species, Spotted Salamander (Ambystoma maculatum) and Wood Frog (Lithobates sylvaticus), across the Canaan Valley National Wildlife Refuge, West Virginia, USA. We surveyed Spotted Salamanders and Wood Frogs at 49 pools from 2004 to 2016. Pools in recently harvested tracts tended to be smaller and less likely to hold water than pools in unharvested tracts for the duration of the breeding period. For both species, mean egg mass abundance was lower in harvested tracts than in the unharvested tracts, and over time declined substantially for Wood Frogs. Similarly, occupancy rates were lower in harvested sites for the duration of the study for both species. Occupancy rates declined over time for both species across all sites; this decline was steeper for Wood Frogs in harvested sites. Our results show the importance of long-term landscape-level studies when evaluating the effects of habitat disturbance. Understanding how forest loss and degradation impact pool-breeding amphibians will help to develop better management targets and mitigate compounding factors of decline to promote survival of these species.
Biodiversity is responsible for important ecological processes like productivity and ecosystem stability, and rare species are a major component of biodiversity. Rarity increases a species' vulnerability to disturbances and also makes them difficult to study. Globally, species of freshwater systems are some of the most threatened, and evaluation of rare freshwater species and their habitats is needed to help preserve natural flexibility and ecological function. We conducted an analysis of full fish communities of the upper St. Lawrence River and its major US tributaries, with the goals of determining species locations and abundances, associated environmental conditions, the distribution of distinct fish assemblages across the landscape (with emphasis on communities supporting rare species), and potential threats. From 2009 to 2015, the US Geological Survey (USGS) and Saint Regis Mohawk Tribe (SRMT) worked together using standardized methods to collect community samples within 4 different aquatic realms (shallow and deep lentic, and small and large lotic systems) and determine species-specific fish abundances, frequencies of occurrence, and associated habitat signatures and spatial distributions. Distinct fish assemblages and associated habitat conditions were objectively identified by multivariate and hypothesis-testing methods. We used a geographic information system (GIS) to spatially associate habitat, biotic, and landscape attributes within each stream reach throughout the study area, facilitating quantification of distribution patterns. Comparisons with historical data provided estimates of loss or gain of threatened and endangered species (T&E) colonies. We developed a disturbance index to highlight potential threats to aquatic species. More than 140,000 fishes of 87 species were collected from a total of 1140 sample sites, covering 278 stream reaches, including the endangered Notropis anogenus (Pugnose Shiner), and threatened Hiodon tergisus (Mooneye), Etheostoma pellucidum (Eastern Sand Darter), and Acipenser fulvescens (Lake Sturgeon). We identified 50 distinct fish assemblages differing in species composition, abundance, and/or diversity, but only 13 of those assemblages included a T&E species. The rareness, extent, and patchiness of fish assemblages created a mosaic of fish communities across the landscape, from headwaters to the mainstem of the St. Lawrence River. Comparisons with historic surveys (1978–2008) showed a stable number of T&E species colonies or an increase for some species. The geographic distribution of multimetric disturbance index values showed where combinations of disturbances to fish habitats might affect rare fish species and aquatic communities in the region. The species–habitat associations and fish assemblage distributions can be used for evaluation of species, communities, or habitats that may need protection or restoration.