For more than 130 years, the type locality of the Plains Spotted Skunk, Spilogale putorius interrupta (Rafinesque, 1820) has been accepted to be along the upper Missouri River. The species’ description was based on a specimen observed by Constantine S. Rafinesque during his 1818 exploration of the Ohio River Valley, but Rafinesque never ventured into the animal’s geographic range west of the Mississippi River, calling into question the type locality and, therefore, the identity of the taxon. We reconstruct Rafinesque’s itinerary from his notes, publications, and correspondence and determine that Rafinesque probably observed the specimen on 20 September in Middletown, Kentucky, while traveling between Louisville and Lexington. He spent the day with John Bradbury, who participated in the 1811 Astor expedition up the Missouri River. On 1 April 1811, Bradbury collected the skin of a skunk, and evidence suggests that it was this skin that Rafinesque described. The type specimen of the Plains Spotted Skunk was obtained on the Missouri River flood plain in southern Chariton County or northern Saline County, Missouri, and this area should be considered the type locality for M. interrupta.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/jmammal/gyab094","usgsCitation":"Woodman, N., and Ferguson, A.W., 2021, The relevance of a type locality: The case of Mephitis interrupta Rafinesque, 1820 (Carnivora: Mephitidae): Journal of Mammalogy, v. 102, no. 6, p. 1583-1591, https://doi.org/10.1093/jmammal/gyab094.","productDescription":"9 p.","startPage":"1583","endPage":"1591","ipdsId":"IP-132396","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":449934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyab094","text":"Publisher Index Page"},{"id":393854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Kentucky, Missouri, New York, Ohio, Pennsylvania, Virginia, West Virginia","county":"Chariton County, Saline County","city":"Lexington, Louisville, New York City, Pittsburgh, Philadelphia","otherGeospatial":"Illinois Territory, Louisiana Territory, Missouri River, Ohio River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.296875,\n 36.54494944148322\n ],\n [\n -83.3642578125,\n 36.54494944148322\n ],\n [\n -71.9384765625,\n 40.64730356252251\n ],\n [\n -72.04833984375,\n 41.07935114946899\n ],\n [\n -80.2001953125,\n 40.84706035607122\n ],\n [\n -81.2548828125,\n 38.993572058209466\n ],\n [\n -89.07714843749999,\n 38.44498466889473\n ],\n [\n -89.296875,\n 36.54494944148322\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.2684326171875,\n 38.34596449365382\n ],\n [\n -91.82373046875,\n 38.34596449365382\n ],\n [\n -91.82373046875,\n 39.92237576385941\n ],\n [\n -93.2684326171875,\n 39.92237576385941\n ],\n [\n -93.2684326171875,\n 38.34596449365382\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":830034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferguson, Adam W.","contributorId":270785,"corporation":false,"usgs":false,"family":"Ferguson","given":"Adam","email":"","middleInitial":"W.","affiliations":[{"id":13087,"text":"Field Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":830035,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227684,"text":"70227684 - 2021 - Technique to estimate generalized skew coefficients of annual peak streamflow for natural watershed conditions in Texas, Oklahoma, and eastern New Mexico","interactions":[],"lastModifiedDate":"2022-09-12T17:03:23.740912","indexId":"70227684","displayToPublicDate":"2021-12-31T11:51:41","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"4","title":"Technique to estimate generalized skew coefficients of annual peak streamflow for natural watershed conditions in Texas, Oklahoma, and eastern New Mexico","docAbstract":"Reliable information about the frequency of annual peak streamflow is needed for floodplain management, objective assessment of flood risk, and cost-effective design of dams, levees, other flood-control structures, and roads, bridges, and culverts. Generalized skew coefficients are among the data needed for log-Pearson type III peak-streamflow frequency analyses of annual peak streamflows. A technique is presented to estimate generalized skew coefficients used for log-Pearson type III peak-streamflow frequency analyses of annual peak streamflow from natural watersheds (minimal regulation and minimal impervious cover). The estimation of generalized skew coefficients was based on annual and historical peak streamflow data from an initial set of 444 selected USGS streamgaging stations (streamgages) with at least 30 years of recorded annual peak streamflows from natural watersheds in Texas, Oklahoma, and the part of New Mexico east of the Great Continental Divide. The primary focus was to obtain information that could be used to update previously published generalized skew coefficients in Texas.\n\nOf the 444 candidate streamgages, 341 were used in the final construction of statistical models. Two generalized additive models (GAMs) were used to predict generalized skew based on a 2-dimensional smooth on projected Albers equal area coordinates of either (1) the locations of the centroids of the gaged watersheds or (2) the streamgage locations. To create maps of generalized skew coefficients, predictions were made on a 1-kilometer grid and contour lines were superimposed. The centroid-location map, with a mean-squared error (MSE) of 0.216, is preferred. Generalized skew coefficients from the centroid-location map, along with the MSE, are useful for computing weighted-skew values when conducting frequency analyses of annual peak streamflow following the guidelines set forth in Bulletin 17C. Based on the results of the study, text revision of the TxDOT Hydraulic Design Manual could be made.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Generalized skew update and regional study of distribution shape for Texas flood frequency analyses","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"Texas Tech University Center for Multidisciplinary Research in Transportation","doi":"10.18738/T8/SVLCOQ","collaboration":"Texas Department of Transportation","usgsCitation":"Asquith, W.H., Yesildirek, M.V., Landers, R.N., Cleveland, T.G., Fang, Z.N., and Zhang, J., 2021, Technique to estimate generalized skew coefficients of annual peak streamflow for natural watershed conditions in Texas, Oklahoma, and eastern New Mexico, chap. 4 of Generalized skew update and regional study of distribution shape for Texas flood frequency analyses, p. 31-58, https://doi.org/10.18738/T8/SVLCOQ.","productDescription":"28 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Beginning in 2015, the benthic preyfish survey expanded from US-only to incorporate lake-wide sampling sites which increased the survey’s spatial coverage, and resumed sampling in eastern embayments (Black River, Chaumont, Guffin, and Henderson Bays) that were historically sampled during a September bottom trawl survey to index yellow perch from 1978 to 2007. In 2021, the collaborative benthic preyfish survey completed 195 bottom trawl tows across main lake and embayments at depths from 5 to 226 m. New embayment sites at Bay of Quinte, Sodus, and Little Sodus Bay were added to the survey in 2021 to compare fish communities across nearshore sites. In total, the 2021 survey sampled 109,178 fish from 35 species. Round goby (Neogobius melanostomus) was the most numerically abundant species comprising 44% of the total catch, followed by deepwater sculpin (Myoxocephalus thompsonii), and alewife (Alosa pseudoharengus) at 17% and 11%, respectively. Deepwater sculpin accounted for most (406 kg) of the fish biomass sampled during the 2021 survey (total=1,995 kg), followed by round goby (257 kg), and common carp (252 kg). Slimy sculpin (Cottus cognatus) biomass was higher in 2021 than in 2020, when spatial coverage was reduced. Deepwater sculpin biomass remained high in 2021 and similar to observations since 2019. White perch biomass (Morone americana) in Black River Bay has increased compared to observations from historical surveys. Yellow perch (Perca flavescens) accounted for most of the benthic preyfish biomass across the embayments surveyed in 2021 except for the Bay of Quinte and Black River Bay, where white perch accounted for a greater proportion of the fish community biomass.
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threshold","interactions":[],"lastModifiedDate":"2023-02-06T16:05:37.397759","indexId":"70240352","displayToPublicDate":"2021-12-31T10:03:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13291,"text":"Human–Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"A desert tortoise-common raven viable conflict threshold","docAbstract":"Since 1966, common raven (Corvus corax; raven) abundance has increased throughout much of this species’ Holarctic distribution, fueled by an ever-expanding supply of anthropogenic resource subsidies (e.g., water, food, shelter, and nesting substrate) to ecoregion specific raven population carrying capacities. Consequently, ravens are implicated in declines of both avian and reptilian species of conservation concern, including the California (USA) endangered and federally threatened Mojave desert tortoise (Gopherus agassizii; desert tortoise). While ravens are a natural predator of desert tortoises, the inter-generational stability of desert tortoise populations is expected to be compromised as annual juvenile survival is suppressed below 0.77 through a combination of raven depredation and other sources of mortality. To estimate the extent to which raven depredation suppresses desert tortoise recruitment within the Mojave Desert of California, we collected data from 274 variable-radius point counts, 78 desert tortoise decoy stations, and 8 control stations during the spring of 2020. Additionally, we complied a geodatabase of previously active raven nests, observed between 2013 and 2020. Raven density estimates from 4 monitoring areas ranged between 0.63 (eastern most) and 2.44 (western most) raven km-2 (95% CI: 0.35–1.14 and 1.33–4.48, respectively). We used a Bayesian shared frailty model to estimate the effects of raven density and distance to the nearest previously active raven nest on the annual “survival” of juvenile desert tortoise decoys (75-mm Midline Carapace Length), which we then converted into survival estimates for 0- to 10-year-old desert tortoises by adjusting exposure to reflect natural activity patterns. At the 1.72-km median distance from the nearest previously active raven nest, the estimated annual survival of desert tortoises decreased as raven density increased, ranging among conservation areas from 0.774 (eastern most) to 0.733 (western most). Accordingly, our model predicts that desert tortoise populations exposed to raven densities in excess of 0.89 raven km-2, at a distance
","language":"English","publisher":"Berryman Institute","doi":"10.26077/eeca-1eec","usgsCitation":"Holcomb, K.L., Coates, P.S., Prochazka, B.G., Shields, T., and Boarman, W., 2021, A desert tortoise-common raven viable conflict threshold: Human–Wildlife Interactions, v. 15, no. 3, p. 405-421, https://doi.org/10.26077/eeca-1eec.","productDescription":"17 p.","startPage":"405","endPage":"421","ipdsId":"IP-130973","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":412742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Basin & Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.97303916756042,\n 35.71726205140463\n ],\n [\n -117.97303916756042,\n 34.34636579137755\n ],\n [\n -114.99857556861961,\n 34.34636579137755\n ],\n [\n -114.99857556861961,\n 35.71726205140463\n ],\n [\n -117.97303916756042,\n 35.71726205140463\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Holcomb, Kerry L.","contributorId":296962,"corporation":false,"usgs":false,"family":"Holcomb","given":"Kerry","email":"","middleInitial":"L.","affiliations":[{"id":64256,"text":"U.S. Fish and Wildlife Service, Carlsbad Fish and Wildlife Office, 777 East Tahquitz Canyon Way, Suite 208, Palm Springs, California, 92262, USA","active":true,"usgs":false}],"preferred":false,"id":863528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shields, Timothy","contributorId":296963,"corporation":false,"usgs":false,"family":"Shields","given":"Timothy","affiliations":[{"id":64257,"text":"Hardshell Labs, Inc., P.O. Box 362, Haines, Alaska, 99827, USA","active":true,"usgs":false}],"preferred":false,"id":863531,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boarman, William I.","contributorId":302114,"corporation":false,"usgs":false,"family":"Boarman","given":"William I.","affiliations":[{"id":65416,"text":"Hardshell Labs","active":true,"usgs":false}],"preferred":false,"id":863532,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231183,"text":"70231183 - 2021 - Stop 3 – The Petersburg “Granite” redefined: Recognition and implications of Silurian to Devonian rocks in central-eastern Virginia","interactions":[],"lastModifiedDate":"2022-05-03T14:37:56.400105","indexId":"70231183","displayToPublicDate":"2021-12-31T09:22:07","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Stop 3 – The Petersburg “Granite” redefined: Recognition and implications of Silurian to Devonian rocks in central-eastern Virginia","docAbstract":"Introduction Although the Petersburg Granite had long been in practical use as a building stone since the 1830s (Watson, 1906; 1907; 1910; Darton, 1911; Steidtmann, 1945), it was first formally defined as a geologic unit by Anna Jonas on the 1928 geologic map of Virginia. Anna Jonas defined this unit as a Precambrian coarse-grained porphyritic biotite granite that was intruded by finer grained granite and cut by pegmatite (Nelson, 1928). This belt of mostly granitic rocks extends from near Ashland, Virginia north of Richmond, to near Stony Creek, south of Petersburg, Virginia (e.g., Virginia Division of Mineral Resources, 1993) and is bounded by the Hylas fault zone to the northwest, the Mesozoic Richmond basin to the west, and the newly recognized Nottoway River fault zone to the southwest (e.g., Carter and others, 2020; 2021). The eastern boundary of this belt is covered by Coastal Plain sediments, but geophysical and deep borehole data suggest an orogen-scale suture separates it from the Neoproterozoic Chesapeake block to the east (Figure 1; Carter and others, 2021).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From the Eastern Piedmont to the Coastal Plain: a cross section through the Richmond Area Fall Zone: Guidebook for 2021 Virginia Geologic Field Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"William and Mary","usgsCitation":"Carter, M.W., McAleer, R.J., Occhi, M., Holm-Denoma, C., Vazquez, J.A., and Owens, B.E., 2021, Stop 3 – The Petersburg “Granite” redefined: Recognition and implications of Silurian to Devonian rocks in central-eastern Virginia, in From the Eastern Piedmont to the Coastal Plain: a cross section through the Richmond Area Fall Zone: Guidebook for 2021 Virginia Geologic Field Conference, p. 18-25.","productDescription":"8 p.","startPage":"18","endPage":"25","ipdsId":"IP-137667","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":400054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":399998,"type":{"id":15,"text":"Index Page"},"url":"https://vgfc.blogs.wm.edu/past-conferences/"}],"country":"United States","state":"Virginia","otherGeospatial":"Petersburg granite","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78,\n 36.75\n ],\n [\n -77.25,\n 36.75\n ],\n [\n -77.25,\n 38\n ],\n [\n -78,\n 38\n ],\n [\n -78,\n 36.75\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":841878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":841879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Occhi, Marcie","contributorId":191116,"corporation":false,"usgs":false,"family":"Occhi","given":"Marcie","affiliations":[],"preferred":false,"id":841880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":219763,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher S.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":841881,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":841882,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Owens, Brent E.","contributorId":178190,"corporation":false,"usgs":false,"family":"Owens","given":"Brent","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":841883,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227374,"text":"70227374 - 2021 - Geologic map of the Middendorf quadrangle, Chesterfield County, South Carolina","interactions":[],"lastModifiedDate":"2023-03-13T14:40:41.012899","indexId":"70227374","displayToPublicDate":"2021-12-31T07:21:51","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":13452,"text":"South Carolina Geological Survey Geologic Quadrangle Map","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"GQM-56","title":"Geologic map of the Middendorf quadrangle, Chesterfield County, South Carolina","docAbstract":"The Middendorf 7.5-minute quadrangle is located entirely within the Carolina Sandhills region of the upper Atlantic Coastal Plain province in Chesterfield County, South Carolina. The Carolina Sandhills, which has been recognized as a separate region for a long time (e.g., McGee, 1890, 1891; Holmes, 1893), extends from central North Carolina across South Carolina to the western border of Georgia along the updip (inland) margin of the Atlantic Coastal Plain province. In Chesterfield County, the Carolina Sandhills form a relatively high plateau that is bounded to the west by Paleozoic metamorphic rocks of the Piedmont province. This plateau is bounded to the east by the east-facing Orangeburg Scarp, which is interpreted as a shoreline formed by wave erosion during a middle Pliocene time of high sea level (Dowsett and Cronin, 1990).
Digital Elevation Models (DEMs) of the Middendorf quadrangle derived from lidar point cloud data reveal a landscape incised by creeks and streams. The highest elevation in the Middendorf quadrangle is 596 ft (182 m) on top of a sandhill in the northwest quadrant of the quadrangle, whereas the lowest elevation is 230 ft (70 m) in the floodplain of Big Black Creek on the southern margin of the quadrangle. Most of the landscape is covered by a mantle of unconsolidated sand that is mapped as the Quaternary Pinehurst Formation. At many locations, the unconsolidated sand is <2 m thick and forms a sand sheet of low relief. In areas of higher elevation, however, the unconsolidated sand can be up to 10 m thick and forms subdued hills (degraded dunes) of up to 6 m relief with steeper sides on the east and southeast. Many of these subdued hills (degraded dunes) are present in the area of closed depressions in the southwest corner of the map. Outcrops within the quadrangle are not common, and are limited mostly to a few exposures of sandstone and clay of the Cretaceous Middendorf Formation in a few road cuts, railroad cuts, and borrow pits as well as some slopes and roadside ditches.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"South Carolina Geological Survey Geologic Quadrangle Map (GQM)","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"South Carolina Geological Survey","usgsCitation":"Swezey, C.S., Fitzwater, B.A., and Whittecar, G.R., 2021, Geologic map of the Middendorf quadrangle, Chesterfield County, South Carolina: South Carolina Geological Survey Geologic Quadrangle Map GQM-56, 2 Plates: 30.00 x 32.50 inches or smaller.","productDescription":"2 Plates: 30.00 x 32.50 inches or smaller","ipdsId":"IP-082619","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":394243,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394224,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.dnr.sc.gov/geology/publications.html"}],"country":"United States","state":"South Carolina","county":"Chesterfield County","otherGeospatial":"Middendorf quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.25,\n 34.5\n ],\n [\n -80.125,\n 34.5\n ],\n [\n -80.125,\n 34.625\n ],\n [\n -80.25,\n 34.625\n ],\n [\n -80.25,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"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":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":830646,"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":830647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whittecar, G. Richard","contributorId":177212,"corporation":false,"usgs":false,"family":"Whittecar","given":"G.","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":830648,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229403,"text":"70229403 - 2021 - Revising the marine range of the endangered black-capped petrel Pterodroma hasitata: occurrence in the northern Gulf of Mexico and exposure to conservation threats","interactions":[],"lastModifiedDate":"2022-03-07T12:58:13.997591","indexId":"70229403","displayToPublicDate":"2021-12-31T06:56:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Revising the marine range of the endangered black-capped petrel Pterodroma hasitata: occurrence in the northern Gulf of Mexico and exposure to conservation threats","docAbstract":"The black-capped petrel Pterodroma hasitata is an Endangered seabird endemic to the western North Atlantic. Although estimated at ~1000 breeding pairs, only ~100 nests have been located at 2 sites in Haiti and 3 sites in the Dominican Republic. At sea, the species primarily occupies waters of the western Gulf Stream in the Atlantic and the Caribbean Sea. Due to limited data, there is currently no consensus on the geographic marine range of the species although no current proposed ranges include the Gulf of Mexico. Here, we report on observations of black-capped petrels during 2 vessel-based survey efforts throughout the northern Gulf of Mexico from 2010-2011 and 2017-2019. During 558 d and ~54700 km of surveys, we tallied 40 black-capped petrels. Most observations occurred in the eastern Gulf, although birds were observed over much of the east-west and north-south footprint of the survey area. Predictive models indicated that habitat suitability for black-capped petrels was highest in areas associated with dynamic waters of the Loop Current. We used the extent of occurrence and area of occupancy concepts to delimit the geographic range of the species within the northern Gulf. We suggest that the marine range for black-capped petrels be modified to include the northern Gulf of Mexico, recognizing that distribution may be more clumped in the eastern Gulf and that occurrence in the southern Gulf remains unknown due to a lack of surveys there. To date, however, it remains unclear which nesting areas are linked to the Gulf of Mexico.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.1101/2021.01.19.427288","usgsCitation":"Jodice, P.G., Michael, P., Gleason, J., Haney, J., and Satge, Y., 2021, Revising the marine range of the endangered black-capped petrel Pterodroma hasitata: occurrence in the northern Gulf of Mexico and exposure to conservation threats: Endangered Species Research, v. 46, p. 49-65, https://doi.org/10.1101/2021.01.19.427288.","productDescription":"17 p.","startPage":"49","endPage":"65","ipdsId":"IP-124873","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":449960,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1101/2021.01.19.427288","text":"Publisher Index Page"},{"id":396779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.96484375,\n 25.799891182088334\n ],\n [\n -80.771484375,\n 25.799891182088334\n ],\n [\n -80.771484375,\n 31.42866311735861\n ],\n [\n -98.96484375,\n 31.42866311735861\n ],\n [\n -98.96484375,\n 25.799891182088334\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michael, P.E.","contributorId":288015,"corporation":false,"usgs":false,"family":"Michael","given":"P.E.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":837281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gleason, J.S.","contributorId":288017,"corporation":false,"usgs":false,"family":"Gleason","given":"J.S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":837282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, J.C.","contributorId":288019,"corporation":false,"usgs":false,"family":"Haney","given":"J.C.","email":"","affiliations":[{"id":61685,"text":"Terra Mar Applied Sciences","active":true,"usgs":false}],"preferred":false,"id":837283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Satge, Y.G.","contributorId":279816,"corporation":false,"usgs":false,"family":"Satge","given":"Y.G.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":837284,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227631,"text":"70227631 - 2021 - Kittlitz’s murrelet seasonal distribution and post-breeding migration from the Gulf of Alaska to the Arctic Ocean","interactions":[],"lastModifiedDate":"2022-01-21T12:48:30.213593","indexId":"70227631","displayToPublicDate":"2021-12-30T06:43:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":894,"text":"Arctic","active":true,"publicationSubtype":{"id":10}},"title":"Kittlitz’s murrelet seasonal distribution and post-breeding migration from the Gulf of Alaska to the Arctic Ocean","docAbstract":"Kittlitz’s Murrelets (Brachyramphus brevirostris) nest during summer in glaciated or recently deglaciated (post-Wisconsin) landscapes. They forage in adjacent marine waters, especially those influenced by glacial meltwater. Little is known of their movements and distribution outside the breeding season. To identify post-breeding migrations of murrelets, we attached satellite transmitters to birds (n = 47) captured at sea in the Gulf of Alaska and Aleutian Islands during May – July 2009 – 15 and tracked 27 birds that migrated from capture areas. Post-breeding murrelets migrated toward the Bering Sea, with short periods of movement (median 2 d) separated by short stopovers (median 1 d). Travel speeds averaged 79.4 km d-1 (83.5 SD, 449.1 maximum). Five Kittlitz’s Murrelets tagged in Prince William Sound in May migrated to the Bering Sea by August and four continued north to the Arctic Ocean, logging 2500 – 4000 km of travel. Many birds spent 2‒3 weeks with little movement along coasts of the Alaska Peninsula or eastern Bering Sea during late August through September, also the pre-basic molt period. Ship-based surveys, many of which were conducted concurrently with our telemetry studies, confirmed that substantial numbers of Kittlitz’s Murrelets migrate into the Arctic Ocean during autumn. They also revealed that some birds spend winter and spring in the Bering Sea in association with ice-edge, polynya, or marginal ice zone habitats before returning to summer breeding grounds. We conclude that this species is best characterized as a sub-Arctic and Arctic species, which has implications for future risk assessments and threat mitigation.
The High Point paleosol is 2.28-meters-thick aggradational soil developed in fining upward estuarine-alluvial sand and loess. The paleosol is exposed in a few shoreline cliff faces of Mason Neck, Virginia. Although a former A horizon is missing, the E, Bw, Bt, and C horizon sequence seen in the sediments indicates subaerial pedogenesis. Pedogenesis began with initial estuarine-alluvial floodplain emergence as sea level was lowering in late marine isotope stage 5 (MIS5) and MIS4, continued during eolian silt deposition accompanied by incorporation of the silt into the estuarine-alluvial sand, and ended with a period of loess and eolian sand deposition, erosion, and development of periglacial(?) features. Six optically stimulated luminescence ages provide an age range from 86 to 56 ka (thousand years ago) for sedimentary units below and above the paleosol. These ages indicate a 10,000- to 30,000-year interval in late MIS5 and MIS4 for these events to have occurred.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211113","usgsCitation":"Markewich, H.W., Wysocki, D.A., Pavich, M.J., Smoot, J.P., and Litwin, R.J., 2021, Stratigraphy and age of a prominent paleosol in a late Pleistocene sedimentary sequence, Mason Neck, Virginia: U.S. Geological Survey Open-File Report 2021–1113, 24 p., https://doi.org/10.3133/ofr20211113.","productDescription":"vii, 24 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-129382","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":393454,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1113/ofr20211113.pdf","text":"Report","size":"2.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1113"},{"id":393453,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1113/coverthb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Mason Neck","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.40966796875,\n 38.507340712903456\n ],\n [\n -76.7724609375,\n 38.507340712903456\n ],\n [\n -76.7724609375,\n 38.884619201291905\n ],\n [\n -77.40966796875,\n 38.884619201291905\n ],\n [\n -77.40966796875,\n 38.507340712903456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges in Virginia. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of six marsh management units within the refuges, totaling about 575 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $143,000, but that further expenditures may yield diminishing return on investment. Potential management actions in optimal portfolios at total costs less than $143,000 included digging runnels by hand to improve drainage from the marsh surface, breaching a road to restore natural hydrology, trapping predators to enhance nest success of tidal marsh birds, and reducing the abundance of Odocoileus virginianus (white-tailed deer) to minimize their effects on marsh vegetation. The potential management benefits were derived from expected increases in number of tidal marsh obligate breeding birds, species richness of nekton, and density of spiders (as an indicator of trophic health); and an expected decrease in duration of surface flooding. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211117","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Denmon, P., and Leffel, R., 2021, Optimization of salt marsh management at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges, Virginia, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1117, 32 p., https://doi.org/10.3133/ofr20211117.","productDescription":"Report: vi, 32 p.; Database","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131973","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":393431,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/121918","text":"U.S. Fish and Wildlife Service database","linkHelpText":"- Salt marsh integrity and Hurricane Sandy vegetation, bird and nekton data"},{"id":393427,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1117/coverthb.jpg"},{"id":393428,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1117/ofr20211117.pdf","text":"Report","size":"2.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1117"},{"id":393429,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1117/images/"},{"id":393430,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1117/ofr20211117.XML"}],"country":"United States","state":"Virginia","otherGeospatial":"Fisherman Island National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.99586486816406,\n 37.072162624715375\n ],\n [\n -75.92857360839844,\n 37.072162624715375\n ],\n [\n -75.92857360839844,\n 37.14061402065652\n ],\n [\n -75.99586486816406,\n 37.14061402065652\n ],\n [\n -75.99586486816406,\n 37.072162624715375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Moosehorn National Wildlife Refuge in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of four marsh management units within the refuge, totaling about 13 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to $1,000, and may continue to increase at a lower rate with further expenditures. Potential management actions in optimal portfolios at total costs less than or equal to $1,000 included improving nesting habitat for Ammodramus nelsoni (Nelson’s sparrow) or restoring hydrologic connections to the upper marsh in one marsh management unit (Hobart Stream West). The potential management benefits were derived from expected increases in the density of nekton and of spiders (as an indicator of trophic health). The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Moosehorn National Wildlife Refuge that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211115","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Mills, M., Brown, R.E., and Ramos, K., 2021, Optimization of salt marsh management at the Moosehorn National Wildlife Refuge, Maine, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1115, 28 p., https://doi.org/10.3133/ofr20211115.","productDescription":"Report: vi, 28 p.; Database","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131976","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":393375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1115/coverthb.jpg"},{"id":393376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1115/ofr20211115.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":393377,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1115/ofr20211115.xml"},{"id":393379,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/121918","text":"U.S. Fish and Wildlife Service database","linkHelpText":"- Salt marsh integrity and Hurricane Sandy vegetation, bird and nekton data"},{"id":393378,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1115/images"}],"country":"United States","state":"Maine","otherGeospatial":"Moosehorn National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.27890014648438,\n 44.80132682904856\n ],\n [\n -67.15,\n 44.80132682904856\n ],\n [\n -67.15,\n 44.918625522424925\n ],\n [\n -67.27890014648438,\n 44.918625522424925\n ],\n [\n -67.27890014648438,\n 44.80132682904856\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
In 2019, the U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, drilled and constructed boreholes USGS 148A and USGS 149 for stratigraphic framework analyses and long-term groundwater monitoring of the eastern Snake River Plain aquifer at the Idaho National Laboratory (INL) in southeastern Idaho. Initially, boreholes USGS 148A and USGS 149 were continuously cored to allow the USGS and INL subcontractor to collect select geophysical and seismic data and evaluate properties of recovered core material. The USGS geophysical data and descriptions of core material are described in this report; however, data collected by the INL contractor, including seismic data, are not included as part of the report.
The unsaturated zone at both borehole locations is relatively thick, depth to water was measured at approximately 663.6 feet (ft) below land surface (BLS) in USGS 148A, and at approximately 654.1 ft BLS at USGS 149. On completion of coring and data collection, both boreholes (USGS 148A and USGS 149) were repurposed as monitoring wells. Well USGS 148A was constructed to a depth of 759 ft BLS and instrumented with a dedicated submersible pump and measurement line; well USGS 149 was constructed to a depth of 974 ft BLS and instrumented with a multilevel monitoring system (WestbayTM).
Geophysical data, collected by the USGS, were used to characterize the subsurface geology and aquifer conditions. Natural gamma log measurements were used to assess sediment-layer thickness and location. Neutron and gamma-gamma source logs were used to confirm fractured and vesicular basalt identified for aquifer testing and multilevel monitoring well zone testing. Acoustic televiewer logs, collected for well USGS 149, were used to identify fractures and assess groundwater movement when compared with neutron measurements. Furthermore, gyroscopic deviation measurements were used to measure horizontal and vertical displacement for the constructed boreholes USGS 148A and USGS 149.
A single-well aquifer test was done in well USGS 148A during November 6–7, 2019, to provide estimates of transmissivity and hydraulic conductivity. Estimates for transmissivity and hydraulic conductivity were 6.34×103 feet squared per day and 3.17 feet per day, respectively. The aquifer test was run overnight (21.3 hours) and measured drawdown was relatively small (0.09 ft) at sustained pumping rates ranging from 15.7 to 16.1 gallons per minute. The transmissivity estimates for well USGS 148A were slightly lower than those determined from previous aquifer tests for wells near the Materials and Fuels Complex, but well within range of other aquifer tests done at the INL.
Water-quality samples, collected from well USGS 148A and from four zones in well USGS 149, were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Water samples for most of the inorganic constituents showed similar chemistry in USGS 148A and all four zones in USGS 149. Water samples for stable isotopes of oxygen and hydrogen indicated some possible influence of irrigation on the water quality. Nitrate plus nitrite concentrations indicated influence from anthropogenic sources. The volatile organic compound and radiochemical data indicated that wastewater disposal practices at the Materials and Fuels Complex or from drilling had no detectable influence on these wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215131","collaboration":"DOE/ID-22255Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
Documenting the spatial distribution of high-quality habitat patches, the distributions of threats and protected areas, and the vulnerability of habitat patches to changes in environmental conditions is vital for conservation of rare species. Range-wide species distribution models were developed for Black Rails (Laterallus jamaicensis) to predict the distribution of high-quality habitat patches for breeding Eastern Black Rails (L. j. jamaicensis). Overlay analyses were conducted to quantify the distribution of habitat relative to human development and existing protected areas, as well as the vulnerability of the best habitat to future sea level rise. The amount of high-quality habitat varied among states (0.4-7.6% of area) and was relatively rare throughout the subspecies' range (3.3% of area). Human development was common but the amount varied spatially among states (2.2-15.3% of area). Higher-quality breeding habitat was more common on federal lands (9.4% of area) and protected areas (6.4% of area), yet 33-42% of the highest-quality habitat patches were vulnerable to sea level rise of 0.61-1.83 m. Our results imply that even though many of the highest-quality habitat patches may be less likely sites for development they are often vulnerable to rising seas, and thus maintenance of existing high-quality habitat patches may be difficult without management that takes into account the likelihood of future inundation.
Methane (CH4) emissions from climate-sensitive ecosystems within the northern permafrost region represent a potentially large but highly uncertain source, with current estimates spanning a factor of seven (11–75 Tg CH4 yr−1). Accelerating permafrost thaw threatens significant increases in pan-Arctic CH4 emissions, amplifying the permafrost carbon feedback. We used airborne imaging spectroscopy with meter-scale spatial resolution and broad coverage to identify a previously undiscovered CH4 emission hotspot adjacent to a thermokarst lake in interior Alaska. Hotspot emissions were confined to <1% of the 10 ha lake study area. Ground-based chamber measurements confirmed average daily fluxes from the hotspot of 1,170 mg CH4 m−2 d−1, with extreme daily maxima up to 24,200 mg CH4 m−2 d−1. Ground-based geophysical measurements revealed thawed permafrost directly beneath the CH4 hotspot, extending to a depth of ∼15 m, indicating that the intense CH4 emissions likely originated from recently thawed permafrost. Hotspot emissions accounted for ∼40% of total diffusive CH4 emissions from the lake study site. Combining study site findings with hotspot statistics from our 70,000 km2 airborne survey across Alaska and northwestern Canada, we estimate that pan-Arctic terrestrial thermokarst hotspots currently emit 1.1 (0.1–5.2) Tg CH4 yr−1, or roughly 4% of the annual pan-Arctic wetland budget from just 0.01% of the northern permafrost land area. Our results suggest that significant proportions of pan-Arctic CH4 emissions originate from disproportionately small areas of previously undetermined thermokarst emissions hotspots, and that pan-Arctic CH4 emissions may increase non-linearly as thermokarst processes increase under a warming climate.
Pre-Cretaceous, predominantly dioritic plutonic rocks in the Lane Mountain area, California, intrude metasedimentary and metavolcanic rocks considered part of the El Paso terrane. New geochronologic (uranium-lead zircon), geochemical, and isotopic data provide a reliable basis for dividing these pre-Cretaceous plutonic rocks into two mappable suites of Permian–Triassic and Late Jurassic ages. The 26 Permian–Triassic samples included in this report have a mean age of ~248 mega-annum (Ma), range in composition from monzodiorite to quartz monzonite and granodiorite, and have a mean initial 87Sr/86Sr ratio (Sri) of ~0.7045. The 22 Late Jurassic samples have a mean age of ~149 Ma, range in composition from gabbro to granite, and have a mean Sri of ~0.7055. Accurate mapping of these two plutonic suites and their detailed field relations with the associated metamorphic rocks is essential for resolving the geologic history and regional tectonic significance of the Lane Mountain area.
The sub-0.706 Sri values of both plutonic suites at Lane Mountain are consistent with previous suggestions that the El Paso terrane is allochthonous and did not develop on Precambrian continental lithosphere. Both suites are considered parts of northwest-trending magmatic arcs interpreted to have formed above east-dipping subduction zones along the evolving North American continental margin, and both arcs are interpreted to cross a major east-west-trending boundary between the El Paso terrane and rocks considered part of ancestral North America in the San Bernardino Mountains area to the south. The El Paso terrane thus appears to have been attached to the San Bernardino Mountains area at least since Permian–Triassic time, although the boundary probably has been modified by Cenozoic faulting.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211094","usgsCitation":"Stone, P., Brown, H.J., Cecil, M.R., Fleck, R.J., Vazquez, J.A., and Fitzpatrick, J.A., 2021, Geochronologic, isotopic, and geochemical data from pre-Cretaceous plutonic rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2021–1094, 74 p., https://doi.org/10.3133/ofr20211094.","productDescription":"viii, 74 p.","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-121822","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":436088,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KRD45S","text":"USGS data release","linkHelpText":"Tabular geochronologic, geochemical, and isotopic data from igneous rocks in the Lane Mountain area, San Bernardino County, California"},{"id":414904,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221115","text":"Open-File Report 2022-1115","description":"Stone, P., Cecil, M.R., Brown, H.J., and Vazquez, J.A., 2023, Geochronologic and geochemical data from metasedimentary and associated rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2022–1115, 34 p., https://doi.org/10.3133/ofr20221115.","linkHelpText":"- Geochronologic and Geochemical Data from Metasedimentary and Associated Rocks in the Lane Mountain Area, San Bernardino County, California"},{"id":392864,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191070","text":"Open-File Report 2019-1070","linkHelpText":"- Geochronologic, Isotopic, and Geochemical Data from Igneous Rocks in the Lane Mountain Area, San Bernardino County, 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Bernardino\",\"state\":\"CA\"}}]}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
The saguaro cactus (Carnegiea gigantea [Engelm.] Britton & Rose) is a keystone species endemic to the Sonoran Desert of northern Mexico and the southwestern United States. The saguaro produces large white flowers near its stem apex (crown) during April–June, which bloom at night and close the following day. In 1924, Duncan Johnson reported that saguaro floral buds are likely to have an asymmetrical distribution in which buds occur in higher densities on the eastern half of a plant's crown. Using technology not available to Johnson, we tested his observations to determine whether flowers are asymmetrically distributed using repeat photography. We also tested whether there is a seasonal pattern of flowering that may explain Johnson’s observations. We tracked intra-individual flowering phenology of 20 saguaros and measured 2372 flowers across two reproductive seasons in Saguaro National Park, Tucson, Arizona. Flowers first appeared on the east side of all saguaro crowns at the start of the reproductive season, and then spread radially in a counterclockwise direction as the season progressed. In contrast to previous reports, saguaro flowers were consistently more abundant on the northern part of the crown than in the eastern part. To our knowledge, this study is the first to document a seasonal, counterclockwise pattern of asynchronous flowering in saguaro or any angiosperm. We discuss potential drivers of this phenomenon as well as implications for saguaros responding to climate change.
Horn Island, one of the two most stable barriers along the Mississippi-Alabama chain (Cat, East and West Ship, Horn, West Petit Bois, Petit Bois, and Dauphin), provides critical habitat, helps regulate estuarine conditions in the Mississippi Sound, and reduces wave energy and storm surge before they reach the mainland shore. However, important details of the formation and evolution of the island in response to sea-level rise, storms, and antecedent geology remain unclear. This study integrates 2200 km of high-resolution geophysical data, 35 sediment cores, and 18 radiocarbon ages to better understand the geologic history of the island. Incised valleys of the Biloxi and Pascagoula Rivers underlie Horn Island and played a profound role in the evolution of the system. Within the incised valleys, sandy paleochannel deposits represent potential sediment sources during island development. Scour associated with wave and tidal ravinement processes liberated sand from the paleochannels and along with numerous other sizable sand sources on the shelf contributed to the formation and continued maintenance of Horn Island. Based on radiocarbon ages, transgressive ephemeral islands/shoals with no preserved shoreface existed at least 8000 cal yr BP and were frequently overwashed when sea-level rise rates were ~ 4–5 mm/yr. Approximately 5000 cal yr BP, coinciding with a deceleration in sea-level rise to about 1.4 mm/yr and attendant increased sand supply, radiocarbon ages associated with Horn Island's barrier complex and lower shoreface indicate a period of island stabilization. Seismic and sediment core data show a long history of westward lateral migration by longshore currents through tidal ravinement and inlet fill. Subsurface sand packages associated with tidal inlet fill and paleochannels are available for ravinement and may be important sand sources for Horn Island to maintain subaerial exposure with the expected accelerated future sea-level rise.
Transgression into adjacent uplands is an important global response of coastal wetlands to accelerated rates of sea level rise. “Ghost forests” mark a signature characteristic of marsh transgression on the landscape, as changes in tidal inundation and salinity cause bordering upland tree mortality, increase light availability, and the emergence of tidal marsh species due to reduced competition. To investigate these mechanisms of the marsh migration process, we conducted a field experiment to simulate a natural disturbance event (e.g., storm-induced flooding) by inducing the death of established trees (coastal loblolly pine, Pinus taeda) at the marsh-upland forest ecotone. After this simulated disturbance in 2014, we monitored changes in vegetation along an elevation gradient in control and treatment areas to determine if disturbance can lead to an ecosystem shift from forested upland to wetland vegetation. Light availability initially increased in the disturbed area, leading to an increase in biodiversity of vegetation with early successional grass and shrub species. However, over the course of this 5-year experiment, there was no increase in inundation in the disturbed areas relative to the control and pine trees recolonized becoming the dominant plant cover in the disturbed study areas. Thus, in the 5 years since the disturbance, there has been no overall shift in species composition toward more hydrophytic vegetation that would be indicative of marsh transgression with the removal of trees. These findings suggest that disturbance is necessary but not sufficient alone for transgression to occur. Unless hydrological characteristics suppress tree re-growth within a period of several years following disturbance, the regenerating trees will shade and outcompete any migrating wetland vegetation species. Our results suggest that complex interactions between disturbance, biotic resistance, and slope help determine the potential for marsh transgression.
Spatial organization plays prominent roles in disease transmission, genetics, and demography of wildlife populations and is therefore an important consideration not only for wildlife management, but also for inference about populations and processes. We used hierarchical agglomerative clustering of a spatial graph network to partition Wind Cave National Park (WICA) into five regions used by 163 female elk (Cervus elaphus) marked with global positioning system collars during 2005–08 and 2011–13. We grouped elk based on differential use of the five regions, developed a priori models for inter-group variation in the occurrence of chronic wasting disease (CWD), and used Akaike's information criterion to compare models and stratify regions. Previous descriptions of elk population structure, which have been based on social contact or overlap of individual ranges, have distinguished spatially disjunct population subsets. Constructing hierarchical partitions of the landscape enabled us to also discern and describe overlapping and nested subsets. During 2016–18, apparent park-wide prevalence of CWD was 0.18 (90% CI = [0.146, 0.182]); however, prevalence within three spatial strata used primarily by different elk ranged from 0.03 ([0.008, 0.074]) to 0.29 ([0.211, 0.375]). In context with published estimates of recruitment, predation, and anthropogenic mortality, such differences in prevalence equate to increasing local abundance of elk in southwestern WICA, stable to declining abundance in the west/northwest, and rapidly declining abundance in the east. Despite the modest size of WICA (11,357 ha), park-wide averages conflate effects of elk distribution and disease, obscuring spatial patterns with profound implications for study and management of elk and CWD. Graph networks have been used widely in ecology to describe such phenomena as social relationships, connectivity of habitat patches, animal movements, and the spread of disease. Extension to partitioning of geographic range is straightforward but entails different considerations. We discuss allocation of sampling effort, construction of an initial partition, specification of a model for graph cohesion, selection of a clustering algorithm, and identification of useful partitions.
A targeted commercial fishery for Atlantic Sturgeon Acipenser oxyrinchus oxyrinchus once operated in the New York Bight, where it was assumed that most harvested Atlantic Sturgeon were natal to the Hudson River population. However, more recent evidence suggests that the fishery may have been targeting a mixed-stock aggregation, in which case harvested Atlantic Sturgeon could have been comprised of individuals from multiple populations throughout the species’ range. Although there is now a moratorium on Atlantic Sturgeon harvest in the New York Bight, modern molecular approaches provide an opportunity to use archived tissues to perform a retrospective mixed-stock analysis on the fishery. Genomic DNA extracted from archived fin spines from 80 Atlantic Sturgeon collected nearly 30 years ago suggests that the fishery primarily harvested individuals from the Hudson River population. However, based on individual-based assignment tests, our results indicate that the fishery also harvested individuals from at least eight other populations located throughout the species’ range. This study highlights how archival hard parts that were previously used for age and growth analyses can be employed for retrospective genetic analyses. Further, because the New York Bight harbors relatively high concentrations of Atlantic Sturgeon, the study shows how localized management decisions can influence Atlantic Sturgeon conservation at rangewide scales. When integrated with more recent knowledge of species ecology, these analyses can be used to evaluate the efficacy of previous management strategies and understand the effects of historical processes on contemporary demography.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10187","usgsCitation":"White, S.L., Johnson, R.L., Lubinski, B.A., Eackles, M.S., Secor, D.H., and Kazyak, D., 2021, Stock composition of the historical New York Bight Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) intercept fishery revealed through microsatellite analysis of archived spines: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 13, no. 6, p. 720-727, https://doi.org/10.1002/mcf2.10187.","productDescription":"8 p.","startPage":"720","endPage":"727","ipdsId":"IP-126143","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":450069,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10187","text":"Publisher Index Page"},{"id":393866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"New York Bight","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.89978027343749,\n 40.63896734381723\n ],\n [\n -73.9324951171875,\n 40.41976938144622\n ],\n [\n -74.168701171875,\n 39.223742741391305\n ],\n [\n -72.89978027343749,\n 40.63896734381723\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":829934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Robin L. 0000-0003-4314-3792 rjohnson1@usgs.gov","orcid":"https://orcid.org/0000-0003-4314-3792","contributorId":224717,"corporation":false,"usgs":true,"family":"Johnson","given":"Robin","email":"rjohnson1@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":829935,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":829936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eackles, Michael S. 0000-0001-5624-5769 meackles@usgs.gov","orcid":"https://orcid.org/0000-0001-5624-5769","contributorId":218936,"corporation":false,"usgs":true,"family":"Eackles","given":"Michael","email":"meackles@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":829937,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Secor, David H.","contributorId":179379,"corporation":false,"usgs":false,"family":"Secor","given":"David","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":829938,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":829939,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226731,"text":"70226731 - 2021 - Reproductive health and endocrine disruption in smallmouth bass (Micropterus dolomieu) from the Lake Erie drainage, Pennsylvania, USA","interactions":[],"lastModifiedDate":"2021-12-08T12:55:37.263109","indexId":"70226731","displayToPublicDate":"2021-12-04T06:51:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive health and endocrine disruption in smallmouth bass (Micropterus dolomieu) from the Lake Erie drainage, Pennsylvania, USA","docAbstract":"Smallmouth bass Micropterus dolomieu were sampled from three sites within the Lake Erie drainage (Elk Creek, Twentymile Creek, and Misery Bay, an embayment in Presque Isle Bay). Plasma, tissues for histopathological analyses, and liver and testes preserved in RNALater® were sampled from 30 smallmouth bass (of both sexes) at each site. Liver and testes samples were analyzed for transcript abundance with Nanostring nCounter® technology. Evidence of estrogenic endocrine disruption was assessed by the presence and severity of intersex (testicular oocytes; TO) and concentrations of plasma vitellogenin in male fish. Abundance of 17 liver transcripts associated with reproductive function, endocrine activity, and contaminant detoxification pathways and 40 testes transcripts associated with male and female reproductive function, germ cell development, and steroid biosynthesis were also measured. Males with a high rate of TO (87–100%) and plasma vitellogenin were noted at all sites; however, TO severity was greatest at the site with the highest agricultural land cover. Numerous transcripts were differentially regulated among the sites and patterns of transcript abundance were used to better understand potential risk factors for estrogenic endocrine disruption. The results of this study suggest endocrine disruption is prevalent in this region and further research would benefit to identify the types of contaminants that may be associated with the observed biological effects.
Saltwater intrusion and declining water levels have been a water-supply problem in Cape May County, New Jersey, for decades. Cape May County is surrounded by saltwater on three sides. Several communities in the county have only one aquifer from which freshwater withdrawals can be made, and that sole source is threatened by saltwater intrusion and (or) substantial declines in water levels caused by groundwater withdrawals. Growth of the year-round and summer tourism populations have caused water demand for some purveyors to approach the full-allocation withdrawal rates set by the New Jersey Department of Environmental Protection, leading these purveyors to request increases in allocations. Simulated water levels resulting from withdrawals including proposed increases in allocations by four purveyors and a shift of some withdrawals from one aquifer to another by a fifth purveyor were compared to simulated baseline water levels with withdrawals at 2012 full-allocation rates.
The Lower Township Scenario simulates proposed full-allocation withdrawals of 1,079 million gallons per year (Mgal/yr) from the Cohansey aquifer, 211 Mgal/yr (24 percent) higher than the 2012 full allocation withdrawals. Lower Township Scenario simulated water levels are between 2 and 4 feet (ft) lower than those of the shallow-aquifer-system Baseline Scenario simulation in much of Lower Township. The simulated 250-milligrams per liter (mg/L) isochlor is a maximum of 750 ft farther eastward than the simulated position in the shallow-aquifer-system Baseline Scenario, and the isochlor is simulated to be 700 ft from the northwestern-most Lower Township Municipal Utility Authority well at the airport in 2050.
The Wildwood Scenario simulates proposed full-allocation withdrawals of 388 Mgal/yr at the Wildwood Water Utility Rio Grande well field in Middle Township from the Rio Grande water-bearing zone (upper Kirkwood Formation) and 776 Mgal/yr from the Atlantic City 800-foot sand (lower Kirkwood Formation). Simulated water levels in the Atlantic City 800-foot sand near the well field are 30–55 ft lower than in the deep-aquifer-system Baseline Scenario, more than 15 ft lower south and west of Cape May Court House, and 5–10 ft lower between Cape May Court House and Woodbine and Upper Township.
The Avalon Scenario simulates proposed full-allocation withdrawals from the Atlantic City 800-foot sand in Avalon Borough of 495 Mgal/yr, which is 141 Mgal/yr (40 percent) higher than the 2012 full-allocation withdrawals. The Cape May Court House Scenario simulates proposed full-allocation withdrawals near Cape May Court House from the Atlantic City 800-foot sand of 495 Mgal/yr, which is 150 Mgal/yr (64 percent) higher than 2012 full-allocation withdrawals. The Strathmere Scenario simulates proposed full-allocation withdrawals in Strathmere from the Atlantic City 800-foot sand of 30 Mgal/yr, which is 11 Mgal/yr (58 percent) higher than 2012 full-allocation withdrawals. All three of these scenarios generally show simulated water levels to be less than 10 ft lower compared to the deep-aquifer-system Baseline Scenario.
The Combined Scenario simulates proposed full-allocation withdrawals, including increased withdrawals from the Atlantic City 800-foot sand in all four locations—the Rio Grande well field, Avalon, Cape May Court House, and Strathmere. Water levels from the Combined Scenario are 40–65 ft lower than those from the deep-aquifer-system Baseline Scenario near the Wildwood Water Utility Rio Grande well field, 15–40 ft lower south of Dennis Township, and 5–15 ft lower in much of the rest of Cape May County.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205052","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Carleton, G.B., 2021, Simulation of potential water allocation changes, Cape May County, New Jersey: U.S. Geological Survey Scientific Investigations Report 2020–5052, 39 p., https://doi.org/10.3133/sir20205052.","productDescription":"Report: vi, 39 p.; Data Release","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044323","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":392461,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20205052/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":392262,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5052/sir20205052.XML"},{"id":392260,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KC1PGV","text":"USGS data release","linkHelpText":"SEAWAT, MODFLOW-2000, and SHARP models used to simulate potential water-allocation changes, Cape May County, New Jersey"},{"id":392261,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5052/images/"},{"id":392259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5052/sir20205052.pdf","text":"Report","size":"4.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5052"},{"id":392258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5052/coverthb.jpg"}],"country":"United States","state":"New Jersey","county":"Cape May County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.99404907226562,\n 38.92843409820933\n ],\n [\n -74.91439819335938,\n 38.91133881927712\n ],\n [\n -74.82376098632812,\n 38.92629741358616\n ],\n [\n -74.77844238281249,\n 38.9807627650163\n ],\n [\n -74.74925994873047,\n 39.041319605445445\n ],\n [\n -74.95010375976561,\n 39.0882354732187\n ],\n [\n -74.99404907226562,\n 38.92843409820933\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
From October 1, 1999, through September 30, 2009, water-quality samples were collected, and discharge was measured at 13 streamgages within the Catskill and Delaware watersheds of the New York City water supply system. The Catskill and Delaware watersheds supply about 90 percent of the water needed by 9 million customers. On average, 59 water-quality samples were collected at each station during each year of the study and analyzed for major ions and nutrients. At six stations, suspended-sediment samples were collected during 2001–09, and turbidity samples were collected during 2003–09. Surficial geology exerted a strong influence on the water quality of streams in the region. Stations in the Cannonsville Reservoir watershed, which has a high percentage of glacial till, had circumneutral stream water, whereas stations in the Neversink Reservoir watershed, which has a high percentage of sedimentary bedrock outcrops, had acidic stream water. All stations showed significant decreases in stream water sulfate concentrations during the study period; however, only the most acidic watersheds showed decreases in hydrogen-ion concentration. Two of the most acidic stations, East Branch Neversink River northeast of Denning and Rondout Creek above Red Brook at Peekamoose also had significant decreasing trends in inorganic monomeric aluminum concentrations, a form of aluminum that is toxic to some aquatic biota at concentrations greater than 0.05 milligram per liter. Three stations in the Neversink Reservoir watershed had inorganic monomeric aluminum concentrations that commonly exceeded 0.05 milligram per liter during the study period. At the West Branch Neversink River at Winnisook Lake near Frost Valley station concentrations of inorganic monomeric aluminum exceeded 0.3 milligram per liter at the beginning of the study, but never exceeded that level during the last 2 water years of the study. The East Branch Neversink River northeast of Denning and Rondout Creek above Red Brook at Peekamoose stations also showed decreases in inorganic monomeric aluminum concentrations during the study. The reduction in inorganic monomeric aluminum concentrations were the result of reductions in stream acidity. The reductions in stream acidity were driven by reductions in sulfate concentrations in precipitation in response to emission regulations included in title IV of the Clean Air Act Amendments of 1990 (42 USC §7651).
Results indicated increasing trends in sodium and chloride concentrations for all stations with high road density relative to other stations included in the study, which could be a future water-quality concern in the region. The Town Brook watershed southeast of Hobart, the only study watershed that contained dairy farms, had a significant decreasing trend in total dissolved phosphorus concentration that may have been a result of agricultural best management practices implemented on farms by the Watershed Agricultural Program. The watershed with the second highest total phosphorus and total dissolved phosphorus concentrations was a completely forested, but previously agricultural, watershed (Town Brook tributary southeast of Hobart) that had not been actively farmed in about 80 years. The phosphorus concentrations at the Town Brook tributary southeast of Hobart station indicated that previously agricultural watersheds may continue to leach phosphorus to streams for many decades after farming has ceased.
At six of the study watersheds, samples of suspended-sediment and turbidity were also collected. The watersheds with the highest suspended-sediment concentrations and turbidity also had the strongest relations between discharge and suspended-sediment concentrations. In general, the relations between discharge and turbidity were not as strong as the relations between discharge and suspended-sediment concentrations. Results indicated strong relations between suspended-sediment concentrations and turbidity levels at each station; however, relations were less strong in the agricultural watersheds. Suspended-sediment concentrations appeared to decrease at the Stony Clove Creek below Ox Clove at Chichester station following a stream stabilization project completed during the study period. However, we were unable to directly attribute the decrease to the stabilization project; there were many complicating variables that made a direct attribution difficult, such as a series of large storms shortly after the stabilization project was completed and differences in flow conditions before and after the project. However, the results have led to additional monitoring within the watershed specifically designed to determine the effectiveness of stream stabilization projects for reducing suspended-sediment concentrations and turbidity in the upper Esopus Creek watershed, the primary source of water to the Ashokan Reservoir. Water quality in the Catskill and Delaware watersheds is generally improving, and although sodium and chloride concentrations increased at some of the stations from 1999 to 2009, the concentrations in 2009 were still well below U.S. Environmental Protection Agency drinking water standards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205049","collaboration":"Prepared in cooperation with New York City Department of Environmental Protection and the U.S. Environmental Protection Agency","usgsCitation":"McHale, M.R., Siemion, J., and Murdoch, P.S., 2021, The water quality of selected streams in the Catskill and Delaware water-supply watersheds in New York, 1999–2009: U.S. Geological Survey Scientific Investigations Report 2020–5049, 48 p., https://doi.org/10.3133/sir20205049.","productDescription":"viii, 48 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060224","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":392036,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20205049/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":391750,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5049/sir20205049.XML"},{"id":391749,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5049/images/"},{"id":391748,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5049/sir20205049.pdf","text":"Report","size":"6.70 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5049"},{"id":391747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5049/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Catskill Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.16845703125001,\n 41.672911819602085\n ],\n [\n -73.93798828125,\n 41.672911819602085\n ],\n [\n -73.93798828125,\n 42.43156587257916\n ],\n [\n -75.16845703125001,\n 42.43156587257916\n ],\n [\n -75.16845703125001,\n 41.672911819602085\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349