The Round Goby Neogobius melanostomus has spread rapidly around the Great Lakes region since its introduction to North America in 1990. In 2014, a specimen was captured in the New York State Canal System west of Utica, prompting concerns that Round Goby would soon reach the ecologically and economically valuable watersheds of Lake Champlain and the Hudson River estuary. The establishment of Round Goby populations elsewhere has been linked to a number of negative ecological consequences, yet methods for monitoring the invasion front of this species remain limited. The objectives of this study were to assess the current distribution of Round Goby in central New York and to determine the most effective methods for monitoring the invasion front. This was achieved by concurrently using benthic trawling, seining, minnow traps, and environmental DNA (eDNA) twice annually from 2016 to 2019 at 12 sites on the canal system between Oneida Lake and the Hudson River. Of the three traditional gear types, benthic trawling was the most effective method and captured Round Goby as far east as Utica by 2019. This finding suggests only minimal eastward expansion of Round Goby occurred between 2014 and 2019. Round Goby DNA was detected in water samples during all surveys in which individuals were captured with trawling, and the estimated concentration of DNA explained 69% of the variability in trawl catch. At multiple study sites, Round Goby DNA was identified during consecutive surveys before Round Goby were first captured with trawling. This suggests that in lotic waters, eDNA has the potential to forecast or serve as a sentinel for the expansion of Round Goby to new locations. Our results demonstrate the importance of using eDNA in a repeated sampling framework and supplementing eDNA sampling with some level of effort with traditional sampling methods.
Bird conservation as an endeavor engages a broad range of partners and a coordinated effort across State and Federal agencies, nongovernment organizations, universities and, at times, international partnerships. To understand information needs and respond to the many challenges in bird conservation, U.S. Geological Survey (USGS) scientists participate in Flyway committees, on Joint Venture boards and working groups, in professional organizations, and in other conservation partnerships. These activities connect USGS scientists to conservation partners with whom they work to address substantial challenges. More than one hundred USGS scientists are dedicated to the scientific study of migratory birds.
This report presents the current (2021) representative breadth of activities of USGS scientists supporting the conservation and management of migratory birds. Ninety USGS scientists contributed to the project descriptions and other information detailing the work of the USGS. The science herein is organized and presented thematically by research strengths and by management topics. The report emphasizes the geographic framework of the North American Flyway councils through which USGS engages regularly with Federal and State government agencies and others who are responsible for managing migratory bird populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1480","usgsCitation":"Pearse, A.T., Sherfy, M.H., Wimer, M., Khalil, M., and Wiltermuth, M.T., 2021, U.S. Geological Survey migratory bird science, 2020–21: U.S. Geological Survey Circular 1480, 131 p., https://doi.org/10.3133/cir1480.","productDescription":"vi, 131 p.","numberOfPages":"142","onlineOnly":"Y","ipdsId":"IP-125814","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":384209,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1480/cir1480.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"USGS Circular 1480"},{"id":384208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1480/coverthb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.24609374999999,\n 32.509761735919426\n ],\n [\n -114.697265625,\n 32.65787573695528\n ],\n [\n -110.9619140625,\n 31.203404950917395\n ],\n [\n -108.28125,\n 31.353636941500987\n ],\n [\n -108.1494140625,\n 31.690781806136822\n ],\n [\n -106.5673828125,\n 31.690781806136822\n ],\n [\n -104.80957031249999,\n 30.486550842588485\n ],\n [\n -104.3701171875,\n 29.420460341013133\n ],\n [\n -102.919921875,\n 28.844673680771795\n ],\n [\n -102.6123046875,\n 29.726222319395504\n ],\n [\n -101.3818359375,\n 29.726222319395504\n ],\n [\n -100.2392578125,\n 28.459033019728043\n ],\n [\n -99.49218749999999,\n 27.254629577800063\n ],\n [\n -99.03076171875,\n 26.45090222367262\n ],\n [\n -97.2509765625,\n 25.918526162075153\n ],\n [\n -96.7236328125,\n 27.877928333679495\n ],\n [\n -93.8671875,\n 29.152161283318915\n ],\n [\n -90.1318359375,\n 28.9023972285585\n ],\n [\n -88.61572265625,\n 28.86391842622456\n ],\n [\n -88.11035156249999,\n 29.99300228455108\n ],\n [\n -84.44091796875,\n 29.668962525992505\n ],\n [\n -83.78173828125,\n 29.7453016622136\n ],\n [\n -82.880859375,\n 28.94086176940557\n ],\n [\n -82.880859375,\n 27.371767300523047\n ],\n [\n -80.74951171875,\n 24.766784522874453\n ],\n [\n -79.541015625,\n 26.64745870265938\n ],\n [\n -81.01318359375,\n 31.39115752282472\n ],\n [\n -76.26708984375,\n 34.867904962568716\n ],\n [\n -75.08056640625,\n 35.94243575255426\n ],\n [\n -75.6298828125,\n 37.24782120155428\n ],\n [\n -71.87255859375,\n 40.88029480552824\n ],\n [\n -69.71923828125,\n 40.9964840143779\n ],\n [\n -59.765625,\n 45.767522962149876\n ],\n [\n -52.53662109375,\n 46.558860303117164\n ],\n [\n -52.14111328125,\n 48.1367666796927\n ],\n [\n -55.52490234375,\n 53.44880683542759\n ],\n [\n -62.46826171874999,\n 59.085738569819505\n ],\n [\n -64.48974609375,\n 61.2913492826376\n ],\n [\n -60.79833984374999,\n 66.72254132270653\n ],\n [\n -67.7197265625,\n 70.38523137082291\n ],\n [\n -78.1787109375,\n 73.80644709395935\n ],\n [\n -78.42041015625,\n 75.97355295343336\n ],\n [\n -74.1357421875,\n 78.67755670538617\n ],\n [\n -69.54345703125,\n 80.26454391261787\n ],\n [\n -61.17187499999999,\n 82.89698689394207\n ],\n [\n -77.34374999999999,\n 83.23642648170203\n ],\n [\n -101.6015625,\n 80.70399666821143\n ],\n [\n -124.45312499999999,\n 76.434603583513\n ],\n [\n -129.0234375,\n 71.85622888185527\n ],\n [\n -136.0546875,\n 69.65708627301174\n ],\n [\n -157.5,\n 71.41317683396566\n ],\n [\n -164.1796875,\n 70.25945200030638\n ],\n [\n -168.046875,\n 66.93006025862448\n ],\n [\n -166.9921875,\n 61.10078883158897\n ],\n [\n -165.9375,\n 53.9560855309879\n ],\n [\n -150.82031249999997,\n 58.44773280389084\n ],\n [\n -143.08593749999997,\n 58.26328705248601\n ],\n [\n -132.1875,\n 54.16243396806779\n ],\n [\n -126.21093749999999,\n 46.31658418182218\n ],\n [\n -125.15625000000001,\n 38.54816542304656\n ],\n [\n -117.24609374999999,\n 32.509761735919426\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Indirect climate effects on tree fecundity that come through variation in size and growth (climate-condition interactions) are not currently part of models used to predict future forests. Trends in species abundances predicted from meta-analyses and species distribution models will be misleading if they depend on the conditions of individuals. Here we find from a synthesis of tree species in North America that climate-condition interactions dominate responses through two pathways, i) effects of growth that depend on climate, and ii) effects of climate that depend on tree size. Because tree fecundity first increases and then declines with size, climate change that stimulates growth promotes a shift of small trees to more fecund sizes, but the opposite can be true for large sizes. Change the depresses growth also affects fecundity. We find a biogeographic divide, with these interactions reducing fecundity in the West and increasing it in the East. Continental-scale responses of these forests are thus driven largely by indirect effects, recommending management for climate change that considers multiple demographic rates.
Simulating long-term, landscape level changes in forest composition requires estimates of stand age to initialize succession models. Detailed stand ages are rarely available, and even general information on stand history often is lacking. We used data from USDA Forest Service Forest Inventory and Analysis (FIA) database to estimate broad age classes for a forested landscape to simulate changes in landscape composition and structure relative to climate change at Fort Drum, a 43,000 ha U.S. Army installation in northwestern New York. Using simple linear regression, we developed relationships between tree diameter and age for FIA site trees from the host and adjacent ecoregions and applied those relationships to forest stands at Fort Drum. We observed that approximately half of the variation in age was explained by diameter breast height (DBH) across all species studied (r2 = 0.42 for sugar maple Acer saccharum to 0.63 for white ash Fraxinus americana). We then used age-diameter relationships from published research on northern hardwood species to calibrate results from the FIA-based analysis. With predicted stand age, we used tree species life histories and environmental conditions represented by ecological site types to parameterize a stochastic forest landscape model (LANDIS-II) to spatially and temporally model successional changes in forest communities at Fort Drum. Forest stands modeled over 100 years without significant disturbance appeared to reflect expected patterns of increasing dominance by shade-tolerant mesophytic tree species such as sugar maple, red maple (Acer rubrum), and eastern hemlock (Tsuga canadensis) where soil moisture was sufficient. On drier sandy soils, eastern white pine (Pinus strobus), red pine (P. resinosa), northern red oak (Quercus rubra), and white oak (Q. alba) continued to be important components throughout the modeling period with no net loss at the landscape scale. Our results suggest that despite abundant precipitation and relatively low evapotranspiration rates for the region, low soil water holding capacity and fertility may be limiting factors for the spread of mesophytic species on excessively drained soils in the region. Increasing atmospheric temperatures projected for the region could alter moisture regimes for many coarse-textured soils providing a possible mechanism for expansion of xerophytic tree species.
","language":"English","publisher":"Hindawi","doi":"10.1155/2021/6650821","usgsCitation":"Odom, R.H., and Ford, W., 2021, Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model: International Journal of Forestry Research, v. 2021, 6650821, 16 p., https://doi.org/10.1155/2021/6650821.","productDescription":"6650821, 16 p.","ipdsId":"IP-111053","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":453196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.1155/2021/6650821","text":"Publisher Index Page"},{"id":393572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fort Drum","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.0089111328125,\n 43.95921358836687\n ],\n [\n -75.509033203125,\n 43.95921358836687\n ],\n [\n -75.509033203125,\n 44.209772586984485\n ],\n [\n -76.0089111328125,\n 44.209772586984485\n ],\n [\n -76.0089111328125,\n 43.95921358836687\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2021","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Odom, Richard H.","contributorId":171659,"corporation":false,"usgs":false,"family":"Odom","given":"Richard","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":829633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":829632,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70220584,"text":"70220584 - 2021 - Organic petrographic evaluation of carbonaceous material in sediments of the Kinnickinnic River, Milwaukee, WI, U.S.A.","interactions":[],"lastModifiedDate":"2021-05-20T12:48:36.583937","indexId":"70220584","displayToPublicDate":"2021-03-03T07:39:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Organic petrographic evaluation of carbonaceous material in sediments of the Kinnickinnic River, Milwaukee, WI, U.S.A.","docAbstract":"This study examines the use of organic petrology techniques to quantify the amount of coal and carbonaceous combustion by-products (i.e., coke, coal tar/pitch, cenospheres) in sediments taken from the Kinnickinnic River adjacent to the former site of the Milwaukee Solvay Coke and Gas Company. These materials are of concern as contaminants like polycyclic aromatic hydrocarbons (PAHs) are known to readily adsorb to coal and combustion byproducts. Kinnickinnic River sediment samples (n = 36) ranging in depth (1–11 ft.) were collected from eight core locations to quantify and characterize carbonaceous material in the sediments. To determine the amount (vol%) of organic particulates, U.S. Geological Survey (USGS) modified the existing ASTM D2799 using the following categories: coal, coke, coal tar/pitch, inertinite organics, plant material, cenospheres, and mineral matter. Coal fragments were subdivided by rank using vitrinite reflectance (Ro, %) and organic components were further subdivided into the size fractions of coarse (250–1000 μm), fine (63–250 μm), and very fine (<63 μm). Of the 36 samples analyzed, concentrations of coal, coke, and coal tar/pitch ranged from 0 to 18.2 vol%, 0 to 32.0 vol%, and 0 to 2.6 vol%, respectively, with the highest concentrations occurring near point sources (e.g. discharge pipe and coal unloading operations). Samples that were furthest upstream and downstream from the Solvay site exhibited a marked decrease in particulate organics, with exception of one upstream location which had 19.8 vol% coke. Overall, the modified ASTM method provided a means to quantify the abundance of carbonaceous material present in the sediments. Petrography and total PAH concentrations did not provide a clear correlation to organic matter type or size fraction but the samples with the highest vol% organic matter in each core generally corresponded to the sample with the highest bulk PAH content.
The purpose of this data series is to compile information on the occurrence and conservation status of the freshwater mussel fauna of Nebraska, Kansas, and Oklahoma and to map the distribution of a freshwater mussel assemblage for the U.S. Department of the Interior, Bureau of Land Management Rapid Ecoregional Assessment (REA) program. The six focal species in the freshwater mussel assemblage are Amblema plicata (threeridge), Fusconaia flava (Wabash pigtoe), Lampsilis cardium (plain pocketbook), Lampsilis teres (yellow sandshell), Pyganodon grandis (giant floater), and Uniomerus tetralasmus (pondhorn). The focal species were selected using the following criteria: (1) the species are regionally significant, (2) occurrence records are sufficient to map the distribution of the species by hydrologic subbasins, (3) the assemblage includes species representing a range of State-level conservation priorities, and (4) the species are not listed as federally endangered or threatened. In addition, the species represent a broad array of life history strategies and habitat associations.
A total of 61 native species of freshwater mussels have documented occurrences within at least 1 of the 3 States, including 6 species that appear to have been extirpated from all the States and 6 species that may have been extirpated from at least 1 State. Of the 61 species, 8 species (including 3 potentially extirpated species) are listed as federally threatened or endangered and an additional 5 species are ranked as imperiled or vulnerable across their range. Approximately 80 percent of the native species known to have occurred within the three-State area have a secure conservation status, in comparison to only 40 percent of all freshwater mussel species or subspecies occurring within the United States. The compiled records for the contemporary period (1970–2017) documented the occurrence of 24 extant species in Nebraska, 42 in Kansas, and 48 in Oklahoma.
The contemporary distributions of the six focal species were mapped by subbasins and the larger hydrologic subregions. Historical records (prior to 1962) were also mapped but were limited. Amblema plicata, Fusconaia flava, and Lampsilis cardium were present in approximately one-third of all subbasins and slightly more than half of the subregions, primarily along the eastern portion of the three-State area. Lampsilis teres and Uniomerus tetralasmus were more widespread, occurring in close to half of the subbasins and about three-quarters of the subregions. Pyganodon grandis was the most widespread, occurring in about three-quarters of the subbasins and almost all subregions. There were very few subbasins with historical occurrences that lacked contemporary occurrences. The broad-scale distribution maps for the freshwater mussel assemblage presented with this report are intended to contribute baseline information for regional assessments, such as the Southern Great Plains Rapid Ecoregional Assessment. Despite the limitations of the available data, such baseline information can be useful for identifying data gaps, monitoring future trends, identifying conservation priorities, and providing the larger context for more detailed watershed- or catchment-level studies. ScienceBase data release files associated with this data series are available at https://doi.org/10.5066/P9SBFZJU (Fancher and Carr, 2021).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1133","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Carr, N.B., and Fancher, T.S., 2021, Compilation of information on occurrence and conservation status for the freshwater mussel fauna of Nebraska, Kansas, and Oklahoma: U.S. Geological Survey Data Series 1133, 22 p., https://doi.org/10.3133/ds1133.","productDescription":"Report: vi, 22 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119647","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":383657,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1133/ds1133.pdf","text":"Report","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1133"},{"id":383666,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SBFZJU","text":"USGS data 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\"}}]}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
USA: CALIFORNIA: Orange Co.: San Juan Capistrano (33.51°N,117.66°W; WGS 84). 25 August 2020. Samuel Fisher, Chelsea Martin, Robert Fisher. Verified by Gregory B. Pauly. Natural History Museum of Los Angeles County (LACM 191974). New county record. One juvenile (33 mm SVL) was collected, and another juvenile was seen 40 m away. Another juvenile was also observed during a second visit to the site on 19 September 2020. Wall geckos were first documented at this site since at least 2019 by Gary Nafis (G. Nafis, pers. comm. and as posted on www.californiaherps.com; 23 Aug 2020). Given that multiple individuals were observed at this site over 2 mo, this appears to be an established population. Invasive T. annularis were first detected in California in Redlands, San Bernardino County in the early 2000s (Wilcox et al. 2014. Herpetol. Rev. 45:464). This new Orange County population is ca. 80 km SW of the other known California population. While T. annularis has not spread much in the downtown urban center in Redlands over the last 20 years (S. Fisher, unpubl. data), it is possible it might expand its range more rapidly in a less urbanized habitat if there were more landscaping and natural features present. The only other published records for North America are from Florida where they are also invasive, and they have been known since the 1990s from several locations and continued to spread (Krysko et al. 2016. IRCF Rept. Amphib. 23:110-143). In the native range of T. annularis their habitat consists of desert, indicating that even though they are able to breed and persist in coastal Orange County they may not be in the optimal habitat (Ibrahim 2004. Zool. Middle East 31:23–38). A potential concern is that if T. annularis becomes more widespread in Southern California, they could present a risk to endemic nocturnal rock-dwelling species such as Xantusia henshawi and Phyllodactylus nocticolus because T. annularis has been shown to engage in saurophagy (Ibrahim 2004, op. cit.). It is much larger than these species (Xantusia henshawi SVL = 70 mm; Phyllodactylus nocticolus SVL = 63 mm; Tarentola SVL = 108 mm) and well adapted to desert habitats where it could be a potential predator or competitor.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Fisher, S., Martin, C.E., and Fisher, R.N., 2021, Tarentola annularis (white-spotted wall gecko): Herpetological Review, v. 52, no. 1.","productDescription":"1 p.","startPage":"85","ipdsId":"IP-128505","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":389481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Orange County","city":"San Juan Capistrano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.67378807067873,\n 33.49330726228523\n ],\n [\n -117.65027046203613,\n 33.49330726228523\n ],\n [\n -117.65027046203613,\n 33.51477815748719\n ],\n [\n -117.67378807067873,\n 33.51477815748719\n ],\n [\n -117.67378807067873,\n 33.49330726228523\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fisher, Samuel R","contributorId":225265,"corporation":false,"usgs":false,"family":"Fisher","given":"Samuel R","affiliations":[{"id":41086,"text":"La Sierra University","active":true,"usgs":false}],"preferred":false,"id":816868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Chelsea E","contributorId":259234,"corporation":false,"usgs":false,"family":"Martin","given":"Chelsea","email":"","middleInitial":"E","affiliations":[{"id":52330,"text":"Loma Linda University","active":true,"usgs":false}],"preferred":false,"id":816869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816870,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219061,"text":"70219061 - 2021 - Molecular and isotopic gas composition of the Devonian Berea Sandstone and implications for gas evolution, eastern Kentucky","interactions":[],"lastModifiedDate":"2021-03-23T14:29:33.528613","indexId":"70219061","displayToPublicDate":"2021-03-01T09:25:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":701,"text":"American Association of Petroleum Geologists Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Molecular and isotopic gas composition of the Devonian Berea Sandstone and implications for gas evolution, eastern Kentucky","docAbstract":"Since 2011, the Devonian Berea Sandstone in northeastern Kentucky has produced oil where thermal maturity studies indicate that likely source rocks, namely, the Devonian Ohio Shale and Mississippian Sunbury Shale, are thermally immature. Downdip, where source rocks are mature for oil, the Berea Sandstone and Ohio Shale primarily produce gas. To investigate this thermal maturity discordancy, the molecular and isotopic composition of gases from the Berea Sandstone (oil associated) and Ohio Shale (nonassociated) were analyzed to understand the gas generation and migration history.
Collected along a northwest-southeast transect in eastern Kentucky, samples range from 1079 to 4602 ft, respectively. All are wet gases with a thermogenic origin (δ13C-CH4 = −53.5‰ to −46.1‰). This is mostly consistent with a reevaluation of thermal maturity in a companion study that expands the area mature for oil. Gas migration is required, however, in updip parts of the Berea play where vitrinite reflectance (VRo) values are less than 0.6%. Southeast regional dip exerts a first-order influence on thermal maturity as gases become drier and isotopically heavier downdip. Correlation of δ13C values for heavier hydrocarbon gases in a natural gas plot with VRo contour spacing demonstrates the influence of nearby source rock thermal maturity on gas composition. Downdip, migration of oil and the attendant increase in permeability relative to gas may account for the dominance of gas production in the Ohio Shale. Migration along with basin uplift after the Alleghany orogeny may have contributed to development of a gas phase that exsolved from oil.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/10142019103","usgsCitation":"Parris, T.M., Hackley, P.C., Greb, S.F., and Eble, C.F., 2021, Molecular and isotopic gas composition of the Devonian Berea Sandstone and implications for gas evolution, eastern Kentucky: American Association of Petroleum Geologists Bulletin, v. 105, no. 3, p. 575-595, https://doi.org/10.1306/10142019103.","productDescription":"21 p.","startPage":"575","endPage":"595","ipdsId":"IP-103910","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":384581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.078125,\n 36.686041276581925\n ],\n [\n -82.11181640625,\n 36.686041276581925\n ],\n [\n -82.11181640625,\n 38.70265930723801\n ],\n [\n -85.078125,\n 38.70265930723801\n ],\n [\n -85.078125,\n 36.686041276581925\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Parris, T. M.","contributorId":255584,"corporation":false,"usgs":false,"family":"Parris","given":"T.","email":"","middleInitial":"M.","affiliations":[{"id":40489,"text":"Kentucky Geological Survey","active":true,"usgs":false}],"preferred":false,"id":812628,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":812629,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greb, S. F.","contributorId":255538,"corporation":false,"usgs":false,"family":"Greb","given":"S.","email":"","middleInitial":"F.","affiliations":[{"id":40489,"text":"Kentucky Geological Survey","active":true,"usgs":false}],"preferred":false,"id":812630,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eble, C. F.","contributorId":255536,"corporation":false,"usgs":false,"family":"Eble","given":"C.","email":"","middleInitial":"F.","affiliations":[{"id":40489,"text":"Kentucky Geological Survey","active":true,"usgs":false}],"preferred":false,"id":812631,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220142,"text":"70220142 - 2021 - Paragenesis of an orogenic gold deposit: New insights on mineralizing processes at the Grass Valley District, California","interactions":[],"lastModifiedDate":"2021-04-21T14:25:38.79225","indexId":"70220142","displayToPublicDate":"2021-03-01T09:21:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Paragenesis of an orogenic gold deposit: New insights on mineralizing processes at the Grass Valley District, California","docAbstract":"The Grass Valley orogenic gold district in the Sierra Nevada foothills province, central California, is the largest historical gold producer of the North American Cordillera. Gold mineralization is associated with shallowly dipping north-south veins hosted by the 160 Ma Grass Valley granodiorite to the southwest of the Grass Valley fault and steeply dipping east-west veins in accreted oceanic rocks to the northeast of this major fault. Quartz veins from both vein types show well-preserved primary textural relationships. Using a combination of petrographic and microanalytical techniques, the paragenetic sequence of minerals within the veins and the compositions of ore minerals were determined to constrain the mechanisms of quartz vein formation and gold deposition. The veins are composed of early quartz that formed through cooling of hydrothermal fluids derived from a geopressured reservoir at depth. The early quartz shows growth zoning in optical cathodoluminescence and contains abundant growth bands of primary inclusions. The primary inclusion assemblages and myriads of crosscutting secondary fluid inclusions have been affected by postentrapment modification, suggesting that early quartz formation was postdated by pronounced pressure fluctuations. These pressure fluctuations, presumably involving changes from lithostatic to hydrostatic conditions, may be related to fault failure of the host structure as predicted by the fault-valve model. Fluid flow associated with pressure cycling took place along microfractures and grain boundaries resulting in extensive recrystallization of the early quartz. Deposition of pyrite, arsenopyrite, and first-generation gold from these hydrothermal fluids causing recrystallization of the early quartz occurred as a result of wall-rock sulfidation. The gold forms invisible gold in the compositionally zoned pyrite or micron-sized inclusions within pyrite growth zones. The latest growth zones in euhedral quartz crystals that formed in association with this stage of the paragenesis contain very rare primary fluid inclusions that have not been affected by postentrapment modification. The hydrothermal system transitioned entirely to hydrostatic conditions immediately after formation of the latest quartz, explaining the preservation of the primary fluid inclusions. The formation of minor quartz in open spaces was followed by the deposition of second-generation native gold and telluride minerals that are commonly associated with base metal sulfides. Ore formation at this stage of the paragenesis is attributed to the rapid decompression of hydrothermal fluids escaping from the geopressured part of the crust into the overlying hydrostatic realm. There is no fluid inclusion evidence that this pressure drop resulted in fluid immiscibility of the hydrothermal fluids. Fluid inclusion evidence suggests that the north-south veins formed at a paleodepth of ~8 km, whereas the east-west veins appear to have formed at ~10 to 11 km below surface, confirming previous inferences that the NE-dipping Grass Valley reverse fault accommodated a large displacement. The findings of the study at Grass Valley have significant implications for the model for orogenic gold deposits, as the reconstruction of the paragenetic relationships provides evidence for the occurrence of two discrete events of gold introduction that occurred at different conditions during the evolution of the hydrothermal system.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4794","usgsCitation":"Taylor, R., Monecke, T., Reynolds, T.J., and Monecke, J., 2021, Paragenesis of an orogenic gold deposit: New insights on mineralizing processes at the Grass Valley District, California: Economic Geology, v. 116, no. 2, p. 323-356, https://doi.org/10.5382/econgeo.4794.","productDescription":"34 p.","startPage":"323","endPage":"356","ipdsId":"IP-112775","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":385250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Grass Valley district","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.16845703125,\n 36.99377838872517\n ],\n [\n -118.63037109375,\n 37.622933594900864\n ],\n [\n -120.05859375,\n 39.223742741391305\n ],\n [\n -120.201416015625,\n 40.85537053192494\n ],\n [\n -122.40966796874999,\n 40.95501133048621\n ],\n [\n -122.11303710937499,\n 39.62261494094297\n ],\n [\n -121.234130859375,\n 37.96152331396614\n ],\n [\n -120.16845703125,\n 36.99377838872517\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"116","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Ryan D. 0000-0002-8845-5290","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":201948,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":814576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monecke, Thomas","contributorId":210730,"corporation":false,"usgs":false,"family":"Monecke","given":"Thomas","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":814577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, T. James","contributorId":257560,"corporation":false,"usgs":false,"family":"Reynolds","given":"T.","email":"","middleInitial":"James","affiliations":[{"id":39908,"text":"FLUID INC.","active":true,"usgs":false}],"preferred":false,"id":814578,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monecke, Jochen","contributorId":237834,"corporation":false,"usgs":false,"family":"Monecke","given":"Jochen","email":"","affiliations":[{"id":47621,"text":"Institute of Theoretical Physics, TU Bergakademie Freiberg, Leipziger Strae 23, 09596 Freiberg, Germany","active":true,"usgs":false}],"preferred":false,"id":814579,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220129,"text":"70220129 - 2021 - Preface to the Focus Section on the 2020 Intermountain West earthquakes","interactions":[],"lastModifiedDate":"2021-04-21T11:42:18.512601","indexId":"70220129","displayToPublicDate":"2021-03-01T06:39:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Preface to the Focus Section on the 2020 Intermountain West earthquakes","docAbstract":"The Intermountain West region of the United States extends from the eastern margin of the Sierra Nevada and Cascade Mountains in the west to the Rocky Mountains in the east. The region is characterized by dextral shear along the eastern margin of the Sierra Nevada and nearly east-west extension in the Basin and Range. This region experienced four significant earthquake sequences in the first half of 2020. The most significant mainshocks were the 18 March 2020 Mw 5.7 earthquake north of Magna, Utah (a suburb of Salt Lake City), the 31 March 2020 Mw 6.5 earthquake northwest of Stanley, Idaho, the 15 May 2020 Mw 6.5 earthquake in the Monte Cristo Range, northwest of Tonopah, Nevada, and the 24 June 2020 Mw 5.8 earthquake near Lone Pine, California. The 15 articles appearing in this focus section explore timely and important topics associated with these sequences, including kinematic rupture models, near-field ground motions, aftershock statistics, geologic observations, seismic hazard implications, and seismotectonics. It is noteworthy that the efforts to record and characterize these earthquake sequences took place during travel and work restrictions necessitated by the COVID-19 pandemic.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210001","usgsCitation":"Gold, R.D., Bormann, J., and Koper, K.D., 2021, Preface to the Focus Section on the 2020 Intermountain West earthquakes: Seismological Research Letters, v. 92, no. 2A, 4 p., https://doi.org/10.1785/0220210001.","productDescription":"4 p.","ipdsId":"IP-125613","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":385240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"2A","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":814551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bormann, Jayne","contributorId":257546,"corporation":false,"usgs":false,"family":"Bormann","given":"Jayne","affiliations":[{"id":52053,"text":"Nevada Seismological Laboratory, University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":814552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koper, Keith D.","contributorId":175489,"corporation":false,"usgs":false,"family":"Koper","given":"Keith","email":"","middleInitial":"D.","affiliations":[{"id":27579,"text":"Swiss Federal Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":814553,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70262197,"text":"70262197 - 2021 - Mixed-stock analysis in the age of genomics: Rapture genotyping enables evaluation of stock-specific exploitation in a freshwater fish population with weak genetic structure","interactions":[],"lastModifiedDate":"2025-01-16T14:39:33.330248","indexId":"70262197","displayToPublicDate":"2021-03-01T00:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Mixed-stock analysis in the age of genomics: Rapture genotyping enables evaluation of stock-specific exploitation in a freshwater fish population with weak genetic structure","docAbstract":"Mixed-stock analyses using genetic markers have informed fisheries management in cases where strong genetic differentiation occurs among local spawning populations, yet many fisheries are supported by multiple spawning stocks that are weakly differentiated. Freshwater fisheries exemplify this problem, with many harvested populations supported by multiple stocks of young evolutionary age and that are isolated across small spatial scales. As a result, attempts to conduct genetic mixed-stock analyses of inland fisheries have often been unsuccessful. Advances in genomic sequencing now offer the ability to discriminate among populations with weak population structure, by providing the necessary resolution to conduct mixed-stock assignment among previously indistinguishable stocks. We demonstrate the use of genomic data to conduct a mixed-stock analysis of Lake Erie's commercial and recreational walleye (Sander vitreus) fisheries and estimate the relative harvest of weakly differentiated stocks (pairwise FST < 0.01). We used RAD-capture (Rapture) to sequence and genotype individuals at 12,081 loci that had been previously determined to be capable of discriminating between western and eastern basin stocks with 95% reassignment accuracy. An outcome not possible in the past with microsatellite markers. Genetic assignment of 1,075 fish harvested from recreational and commercial fisheries in the eastern basin indicated that western basin stocks constituted the majority of individuals harvested during peak walleye fishing season (July – September). Composition of harvest changed seasonally, with eastern basin fish comprising much of the early season harvest (May – June). Clear spatial structure in stock-specific harvest existed; more easterly sites contained more individuals of east basin origin than did westerly sites. Our study provides important stock contribution estimates for Lake Erie fishery management and demonstrates the power of genomic data to facilitate mixed-stock analysis in exploited fish populations with weak population structure or limited existing genetic resources.","language":"English","publisher":"Wiley","doi":"10.1111/eva.13209","usgsCitation":"Euclide, P., MacDougall, T., Robinson, J., Faust, M., Wilson, C., Chen, K., Marschall, E., Larson, W., and Ludsin, S., 2021, Mixed-stock analysis in the age of genomics: Rapture genotyping enables evaluation of stock-specific exploitation in a freshwater fish population with weak genetic structure: Evolutionary Applications, v. 14, p. 1403-1420, https://doi.org/10.1111/eva.13209.","productDescription":"18 p.","startPage":"1403","endPage":"1420","ipdsId":"IP-123728","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467253,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/eva.13209","text":"External Repository"},{"id":466430,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, New York, Ohio, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.92283643736553,\n 42.39179507562275\n ],\n [\n -83.61537738216629,\n 41.32610638842888\n ],\n [\n -81.8676036360458,\n 41.224638678509734\n ],\n [\n -78.67742205297884,\n 42.732057855200225\n ],\n [\n -80.92283643736553,\n 42.39179507562275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2021-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Euclide, Peter T.","contributorId":348469,"corporation":false,"usgs":false,"family":"Euclide","given":"Peter T.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":923467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacDougall, Tom","contributorId":348471,"corporation":false,"usgs":false,"family":"MacDougall","given":"Tom","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":923469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robinson, Jason M.","contributorId":348470,"corporation":false,"usgs":false,"family":"Robinson","given":"Jason M.","affiliations":[{"id":56930,"text":"New York DEC","active":true,"usgs":false}],"preferred":false,"id":923468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faust, Matthew D.","contributorId":348473,"corporation":false,"usgs":false,"family":"Faust","given":"Matthew D.","affiliations":[{"id":13589,"text":"Ohio DNR","active":true,"usgs":false}],"preferred":false,"id":923470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Chris C.","contributorId":348475,"corporation":false,"usgs":false,"family":"Wilson","given":"Chris C.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":923471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chen, Kuan-Yu","contributorId":348477,"corporation":false,"usgs":false,"family":"Chen","given":"Kuan-Yu","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":923472,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marschall, Elizabeth A.","contributorId":348479,"corporation":false,"usgs":false,"family":"Marschall","given":"Elizabeth A.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":923473,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Larson, Wesley 0000-0003-4473-3401 wlarson@usgs.gov","orcid":"https://orcid.org/0000-0003-4473-3401","contributorId":199509,"corporation":false,"usgs":true,"family":"Larson","given":"Wesley","email":"wlarson@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923466,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ludsin, Stuart A.","contributorId":348481,"corporation":false,"usgs":false,"family":"Ludsin","given":"Stuart A.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":923474,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70227199,"text":"70227199 - 2021 - U–Pb zircon eruption age of the Old Crow tephra and review of extant age constraints","interactions":[],"lastModifiedDate":"2022-01-04T13:52:32.345028","indexId":"70227199","displayToPublicDate":"2021-02-27T07:48:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3216,"text":"Quaternary Geochronology","active":true,"publicationSubtype":{"id":10}},"title":"U–Pb zircon eruption age of the Old Crow tephra and review of extant age constraints","docAbstract":"Eruption of the Old Crow tephra deposited ~200 km3 of volcanic ash throughout Alaska and the northwestern Yukon (eastern Beringia), providing an isochronous marker across the region on a scale unique in the Pleistocene. The Old Crow tephra represents a critical temporal piercing point used extensively to link geographically disparate stratigraphic sections and the paleo-environmental records they contain. Although the canonical age of the Old Crow suggests eruption during the transition between the glacial and interglacial periods of Marine Isotope Stages (MIS) 5 and 6 at ~125 ka, recent U–Th–Pb and (U–Th)/He zircon dating of the tephra suggests eruption at ~200 ka, within MIS 7. If accurate, this revised eruption age begets significant change to existing models describing the geologic and biotic evolution of Beringia in the Pleistocene. Thus, confidently knowing the age of the tephra is critical to its time-stratigraphic utility and for past and future work in the region where the tephra has been found. With this contribution, we review existing Old Crow age constraints and present an eruption age for the tephra determined via high spatial resolution ion microprobe U–Pb surface analysis on zircon crystals isolated from source-proximal (<500 km from plausible source) pumiceous pyroclasts of the tephra. By dating only glass-mantled crystals isolated from discrete pumice clasts, we limit the potential for sample contamination from exotic crystals and resulting age bias. The young population of dates from this dataset corroborate previous radiometric dates and confirm Old Crow eruption within late MIS 7 at 207 ± 13 ka.
First-order dynamic occupancy models (FODOMs) are a class of state-space model in which the true state (occurrence) is observed imperfectly. An important assumption of FODOMs is that site dynamics only depend on the current state and that variations in dynamic processes are adequately captured with covariates or random effects. However, it is often difficult to understand and/or measure the covariates that generate ecological data, which are typically spatiotemporally correlated. Consequently, the non-independent error structure of correlated data causes underestimation of parameter uncertainty and poor ecological inference. Here, we extend the FODOM framework with a second-order Markov process to accommodate site memory when covariates are not available. Our modeling framework can be used to make reliable inference about site occupancy, colonization, extinction, turnover, and detection probabilities. We present a series of simulations to illustrate the data requirements and model performance. We then applied our modeling framework to 13 yr of data from an amphibian community in southern Arizona, USA. In this analysis, we found residual temporal autocorrelation of population processes for most species, even after accounting for long-term drought dynamics. Our approach represents a valuable advance in obtaining inference on population dynamics, especially as they relate to metapopulations.
The Fairweather fault (southeastern Alaska, USA) is Earth’s fastest-slipping intracontinental strike-slip fault, but its long-term role in localizing Yakutat–(Pacific–)North America plate motion is poorly constrained. This plate boundary fault transitions northward from pure strike slip to transpression where it comes onshore and undergoes a <25°, 30-km-long restraining double bend. To the east, apatite (U-Th)/He (AHe) ages indicate that North America exhumation rates increase stepwise from ~0.7 to 1.7 km/m.y. across the bend. In contrast, to the west, AHe age-depth data indicate that extremely rapid 5–10 km/m.y. Yakutat exhumation rates are localized within the bend. Further northwest, Yakutat AHe and zircon (U-Th)/He (ZHe) ages gradually increase from 0.3 to 2.6 Ma over 150 km and depict an interval of extremely rapid >6–8 km/m.y. exhumation rates that increases in age away from the bend. We interpret this migration of rapid, transient exhumation to reflect prolonged advection of the Cenozoic–Cretaceous sedimentary cover of the eastern Yakutat microplate through a stationary restraining bend along the edge of the North America plate. Yakutat cooling ages imply a long-term strike-slip rate (54 ± 6 km/m.y.) that mimics the millennial (53 ± 5 m/k.y.) and decadal (46 mm/yr) rates. Fairweather fault slip can account for all Pacific–North America relative plate motion throughout Quaternary time and indicates stability of highly localized plate boundary strike slip on a single fault where extreme rock uplift rates are persistently localized within a restraining bend.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G48464.1","usgsCitation":"Lease, R.O., Haeussler, P., Witter, R., Stockli, D.F., Bender, A., Kelsey, H., and O’Sullivan, P., 2021, Extreme Quaternary plate boundary exhumation and strike slip localized along the southern Fairweather fault, Alaska, USA: Geology, v. 49, no. 5, p. 602-606, https://doi.org/10.1130/G48464.1.","productDescription":"5 p.","startPage":"602","endPage":"606","ipdsId":"IP-124679","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":453351,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g48464.1","text":"Publisher Index Page"},{"id":436496,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FUIJG8","text":"USGS data release","linkHelpText":"Low-Temperature Thermochronometric Data along the Fairweather Fault, Southeast Alaska, 2015-2020"},{"id":384056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"southern Fairweather fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -146.64734789789867,\n 60.62832977945311\n ],\n [\n -142.84447658755874,\n 56.344276134374155\n ],\n [\n -130.03801608165645,\n 54.104139652147495\n ],\n [\n -130.03801608165645,\n 60.62832977945311\n ],\n [\n -146.64734789789867,\n 60.62832977945311\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":811420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":811421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":811422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stockli, Daniel F. 0000-0001-7652-2129","orcid":"https://orcid.org/0000-0001-7652-2129","contributorId":254375,"corporation":false,"usgs":false,"family":"Stockli","given":"Daniel","email":"","middleInitial":"F.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":811423,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bender, Adrian 0000-0001-7469-1957","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":219952,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":811424,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelsey, Harvey","contributorId":254376,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":811425,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Sullivan, Paul 0000-0002-7247-5107","orcid":"https://orcid.org/0000-0002-7247-5107","contributorId":254377,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":811426,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70218177,"text":"sir20215002 - 2021 - Multilevel groundwater monitoring of hydraulic head, water temperature, and chemical constituents in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2014–18","interactions":[],"lastModifiedDate":"2021-02-17T12:58:55.815161","indexId":"sir20215002","displayToPublicDate":"2021-02-16T13:00:15","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5002","displayTitle":"Multilevel Groundwater Monitoring of Hydraulic Head, Water Temperature, and Chemical Constituents in the Eastern Snake River Plain Aquifer, Idaho National Laboratory, Idaho, 2014–18","title":"Multilevel groundwater monitoring of hydraulic head, water temperature, and chemical constituents in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2014–18","docAbstract":"Radiochemical and chemical wastewater discharged to infiltration ponds and disposal wells since the early 1950s at the Idaho National Laboratory (INL), southeastern Idaho, has affected the water quality of the eastern Snake River Plain (ESRP) aquifer. In 2006, the U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, added a multilevel well-monitoring network to their ongoing monitoring program to begin describing the vertical movement and distribution of the chemical constituents in the ESRP aquifer.
The multilevel monitoring system (MLMS) at the INL has been ongoing since 2006, and this report summarizes data collected during 2014–18 from 11 multilevel monitoring wells. Hydraulic head (head) and groundwater temperature data were collected, including 177 measurements from hydraulically isolated depth intervals from 448.0 to 1,377.6 feet below land surface. One port (port 3) within well USGS 134 was not monitored owing to a valve failure.
Note: This is a partial abstract.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215002","collaboration":"DOE/ID-22254Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
In 2015, the U.S. Geological Survey completed a geology-based assessment to estimate the volumes of undiscovered, technically recoverable petroleum resources in the Cherokee Platform Province area of southeastern Kansas, northeastern Oklahoma, and southwestern Missouri. The U.S. Geological Survey identified four stratigraphic intervals that contain petroleum source rocks: (1) thin shales in the Middle to Upper Ordovician Simpson Group, (2) shales within the Upper Devonian to Lower Mississippian Woodford Shale and stratigraphically equivalent Chattanooga Shale, (3) coals and coal-associated shales and mudstones in the Middle Pennsylvanian (Desmoinesian) Cherokee and Marmaton Groups, and (4) thin marine shales within the Marmaton Group and the Upper Pennsylvanian (Missourian) Kansas City and Lansing Groups. Based on the nature of the petroleum accumulations, the characterization of the compositions and thermal maturity of the organic matter in the rocks, and the compositions of the produced petroleum, the U.S. Geological Survey identified three total petroleum systems (TPS) containing four assessment units (AU): the Paleozoic Composite TPS with the Paleozoic Conventional Assessment Unit (AU), the Woodford/Chattanooga TPS with the Woodford Shale Oil AU and the Woodford Biogenic Gas AU, and the Desmoinesian Coal TPS with the Desmoinesian Coalbed Gas AU. Assessment unit summaries follow
1. Three source rock intervals have contributed geochemically distinct oils to reservoirs within the Paleozoic Conventional AU. These intervals are the Simpson Group; the Woodford and Chattanooga Shales; and the Marmaton, Kansas City, and Lansing Groups. The major petroleum source rocks are the Woodford and Chattanooga Shales. The Paleozoic Conventional AU includes reservoirs that range in age from the Upper Cambrian Arbuckle Group to the lower Permian Chase Group. Most oil production in the province has been from Pennsylvanian sandstone reservoirs. Estimated undiscovered petroleum resources for this AU are a mean of 3 million barrels of oil (MMBO), 140 billion cubic feet of gas (BCFG), and 4 million barrels of natural gas liquids (MMBNGL).
2. The Woodford Shale Oil AU contains undiscovered continuous petroleum resources within the Woodford Shale and Chattanooga Shale. The geologic model for the AU assumes that petroleum resources remain trapped within the shale following petroleum migration. For most of the AU, organic matter within the Woodford Shale and Chattanooga Shale is thermally mature with respect to petroleum generation as shown by vitrinite reflectance values between 0.6 and 1 percent. Petroleum has been produced from the Woodford Shale and Chattanooga Shale. Estimated undiscovered petroleum resources for this AU are means of 460 MMBO, 640 BCFG, and 7 MMBNGL.
3. The Woodford Shale Biogenic Gas AU contains undiscovered continuous petroleum resources in the east-central portion of the Cherokee Platform Province near the Ozark uplift where the Woodford Shale and Chattanooga Shale are at depths of 1,250 ft or shallower. At those depths, methanogenesis and(or) biodegradation of thermogenic natural gases can be found where the shale may be more fractured and more susceptible to groundwater penetrations. The mean assessed volume of undiscovered gas for this assessment unit is 416 BCFG and 1 MMBNGL.
4. The Desmoinesian Coalbed Gas AU contains undiscovered continuous petroleum resources within the Middle Pennsylvanian coals and coal-associated shales and mudstones. The boundaries for the Desmoinesian Coalbed Gas AU are, in part, defined by the extent, depth, and thickness of the coals. Within the Desmoinesian Coalbed Gas AU, a sweet spot area was delineated based on a 10 foot or greater net coal thickness. Gas analytical data show that natural gas produced from the coals has a mixed biogenic and thermogenic origin and that there is significant migration of natural gas into the coals from adjacent conventional sandstone reservoirs. The estimated mean volume of undiscovered gas is 10.0 trillion cubic ft of gas (TCFG), and 23 MMBNGL.
For the three continuous (unconventional) assessment units and one conventional assessment unit in the Cherokee Platform Province, total mean volumes of undiscovered petroleum resources are estimated to be 463 MMBO, 11.2 TCFG and 35 MMBNGL.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205110","issn":"978-1-4113-4399-3","usgsCitation":"Drake, R.M., II, and Hatch, J.R., 2021, Geologic assessment of undiscovered oil and gas resources in the Cherokee Platform area of Kansas, Oklahoma, and Missouri: U.S. Geological Survey Scientific Investigations Report 2020–5110, 39 p., https://doi.org/10.3133/sir20205110.","productDescription":"viii, 39 p.","onlineOnly":"N","ipdsId":"IP-069652","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":383204,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5110/sir20205110.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5110"},{"id":383203,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5110/coverthb2.jpg"}],"country":"United States","state":"Kansas, Missouri, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.2392578125,\n 33.43144133557529\n ],\n [\n -93.251953125,\n 33.578014746143985\n ],\n [\n -93.2958984375,\n 40.04443758460856\n ],\n [\n -100.0634765625,\n 40.04443758460856\n ],\n [\n -100.2392578125,\n 33.43144133557529\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
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Atomic chlorine (Cl•) affects air quality and atmospheric oxidizing capacity. Nitryl chloride (ClNO2) – a common Cl• source–forms when chloride-containing aerosols react with dinitrogen pentoxide (N2O5). A recent study showed that saline lakebed (playa) dust is an inland source of particulate chloride (Cl–) that generates high ClNO2. However, the underlying physiochemical factors responsible for observed yields are poorly understood. To elucidate these controlling factors, we utilized single particle and bulk techniques to determine the chemical composition and mineralogy of playa sediment and dust samples from the southwest United States. Single particle analysis shows trace highly hygroscopic magnesium and calcium Cl-containing minerals are present and likely facilitate ClNO2 formation at low humidity. Single particle and mineralogical analysis detected playa sediment organic matter that hinders N2O5 uptake as well as 10 Å-clay minerals (e.g., Illite) that compete with water and chloride for N2O5. Finally, we show that the composition of the aerosol surface, rather than the bulk, is critical in ClNO2 formation. These findings underscore the importance of mixing state, competing reactions, and surface chemistry on N2O5 uptake and ClNO2 yield for playa dusts and, likely, other aerosol systems. Therefore, consideration of particle surface composition is necessary to improve ClNO2 and air quality modeling.
The presence of many pathogens varies in a predictable manner with latitude, with infections decreasing from the equator towards the poles. We investigated the geographic trends of pathogens infecting a widely distributed carnivore: the gray wolf (Canis lupus). Specifically, we investigated which variables best explain and predict geographic trends in seroprevalence across North American wolf populations and the implications of the underlying mechanisms. We compiled a large serological dataset of nearly 2000 wolves from 17 study areas, spanning 80° longitude and 50° latitude. Generalized linear mixed models were constructed to predict the probability of seropositivity of four important pathogens: canine adenovirus, herpesvirus, parvovirus, and distemper virus—and two parasites: Neospora caninum and Toxoplasma gondii. Canine adenovirus and herpesvirus were the most widely distributed pathogens, whereas N. caninum was relatively uncommon. Canine parvovirus and distemper had high annual variation, with western populations experiencing more frequent outbreaks than eastern populations. Seroprevalence of all infections increased as wolves aged, and denser wolf populations had a greater risk of exposure. Probability of exposure was positively correlated with human density, suggesting that dogs and synanthropic animals may be important pathogen reservoirs. Pathogen exposure did not appear to follow a latitudinal gradient, with the exception of N. caninum. Instead, clustered study areas were more similar: wolves from the Great Lakes region had lower odds of exposure to the viruses, but higher odds of exposure to N. caninum and T. gondii; the opposite was true for wolves from the central Rocky Mountains. Overall, mechanistic predictors were more informative of seroprevalence trends than latitude and longitude. Individual host characteristics as well as inherent features of ecosystems determined pathogen exposure risk on a large scale. This work emphasizes the importance of biogeographic wildlife surveillance, and we expound upon avenues of future research of cross-species transmission, spillover, and spatial variation in pathogen infection.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-021-81192-w","usgsCitation":"Brandell, E., Cross, P., Craft, M.E., Smith, D., Dubovi, E., Gilbertson, M.L., Wheeldon, T., Stephenson, J.A., Barber-Meyer, S., Borg, B.L., Sorum, M., Stahler, D.R., Kelly, A.P., Anderson, M., Cluff, H.D., MacNulty, D., Watts, D.L., Roffler, G., Schwantje, H.M., Hebblewhite, M., Beckman, K., and Hudson, P.J., 2021, Patterns and processes of pathogen exposure in gray wolves across North America: Scientific Reports, v. 11, https://doi.org/10.1038/s41598-021-81192-w.","productDescription":"3722, 14 p.","startPage":"3722","ipdsId":"IP-124041","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":453472,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-81192-w","text":"Publisher Index 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E.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":810319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":810320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Craft, Meggan E.","contributorId":168372,"corporation":false,"usgs":false,"family":"Craft","given":"Meggan","email":"","middleInitial":"E.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":810321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Douglas W.","contributorId":179181,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas W.","affiliations":[],"preferred":false,"id":810322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubovi, E. 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J.","affiliations":[{"id":38415,"text":"Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA","active":true,"usgs":false}],"preferred":false,"id":810324,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wheeldon, Tyler","contributorId":251693,"corporation":false,"usgs":false,"family":"Wheeldon","given":"Tyler","email":"","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":810325,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stephenson, John A.","contributorId":251694,"corporation":false,"usgs":false,"family":"Stephenson","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":37975,"text":"Grand Teton National Park","active":true,"usgs":false}],"preferred":false,"id":810326,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barber-Meyer, Shannon 0000-0002-3048-2616","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":217939,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":810327,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Borg, B. L.","contributorId":251695,"corporation":false,"usgs":false,"family":"Borg","given":"B.","email":"","middleInitial":"L.","affiliations":[{"id":50375,"text":"Denali National Park","active":true,"usgs":false}],"preferred":false,"id":810328,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sorum, Mathew","contributorId":204962,"corporation":false,"usgs":false,"family":"Sorum","given":"Mathew","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":810329,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stahler, Daniel R.","contributorId":179180,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":810330,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kelly, Allicia P","contributorId":243472,"corporation":false,"usgs":false,"family":"Kelly","given":"Allicia","email":"","middleInitial":"P","affiliations":[],"preferred":false,"id":810331,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Anderson, Morgan","contributorId":251706,"corporation":false,"usgs":false,"family":"Anderson","given":"Morgan","email":"","affiliations":[],"preferred":false,"id":810332,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Cluff, H. D.","contributorId":251696,"corporation":false,"usgs":false,"family":"Cluff","given":"H.","email":"","middleInitial":"D.","affiliations":[{"id":50376,"text":"Government of the Northwest Territories","active":true,"usgs":false}],"preferred":false,"id":810333,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"MacNulty, Daniel R.","contributorId":179179,"corporation":false,"usgs":false,"family":"MacNulty","given":"Daniel R.","affiliations":[],"preferred":false,"id":810334,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Watts, David L.","contributorId":214781,"corporation":false,"usgs":false,"family":"Watts","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":810335,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Roffler, G.","contributorId":251697,"corporation":false,"usgs":false,"family":"Roffler","given":"G.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":810336,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Schwantje, Helen M.","contributorId":190378,"corporation":false,"usgs":false,"family":"Schwantje","given":"Helen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":810337,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Hebblewhite, Mark","contributorId":190188,"corporation":false,"usgs":false,"family":"Hebblewhite","given":"Mark","email":"","affiliations":[],"preferred":false,"id":810338,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Beckman, K.","contributorId":251698,"corporation":false,"usgs":false,"family":"Beckman","given":"K.","email":"","affiliations":[{"id":50377,"text":"Alaska Dept of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":810339,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Hudson, P. J.","contributorId":236937,"corporation":false,"usgs":false,"family":"Hudson","given":"P.","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":810340,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70218013,"text":"sir20205148 - 2021 - Nutrient concentrations, loads, and yields in the Middle Iowa River Basin, Iowa","interactions":[],"lastModifiedDate":"2021-02-12T12:56:57.224275","indexId":"sir20205148","displayToPublicDate":"2021-02-11T17:37:55","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5148","displayTitle":"Nutrient Concentrations, Loads, and Yields in the Middle Iowa River Basin, Iowa","title":"Nutrient concentrations, loads, and yields in the Middle Iowa River Basin, Iowa","docAbstract":"Concentrations, loads, and yields of nitrate plus nitrite, total nitrogen, and total phosphorus were assessed in the Iowa River upstream from the Coralville Reservoir in east-central Iowa. The results of this study describe baseline nutrient transport during two historical reference periods, 1980–96 and 2006–10, that can be used to evaluate the progress of the implementation of reduction strategies in the Middle Iowa River Basin. Where available, nutrient data during the more recent period 2011–18 are also described. Data included nutrient concentrations and streamflow from multiple Federal, State, and Tribal agencies, and loads were computed using multiple techniques to provide valuable insights, which would otherwise not be possible.
Despite an upward trend for mean annual and base streamflow (the trend in high streamflow was not significant), average nutrient loads and yields in the Iowa River were smaller in the recent period (2011–18) than in either historical reference period. Notably smaller loads during the 2012 drought, however, caused pronounced skewed average loads for 2011–18. Comparisons among periods were difficult to make because of a short period of data upstream from Marshalltown, Iowa, at the upstream boundary of the study area and a lack of recent data near Marengo, Iowa, at the downstream boundary of the study area. Though spring and summer loads were a disproportionate part of annual loads, up to 90 percent, seasonal load comparisons to determine load reduction were more sensitive to one or the other historical period than was assessment of annual loads. Runoff-transport relations may provide an additional tool to assess load reduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205148","collaboration":"Prepared in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa","usgsCitation":"Garrett, J.D., and Kalkhoff, S.J., 2021, Nutrient concentrations, loads, and yields in the Middle Iowa River Basin, Iowa: U.S. Geological Survey Scientific Investigations Report 2020–5148, 22 p., https://doi.org/10.3133/sir20205148.","productDescription":"Report: vii, 22 p.; 1 Table; Dataset","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-116761","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":383240,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5148/sir20205148_table1.1.csv","text":"Table 1.1","size":"23.3 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5148 Table 1.1","linkHelpText":"— Tributary sites in the Middle Iowa River Basin, upstream of Coralville Reservoir"},{"id":383239,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5148/sir20205148_table1.1.xlsx","text":"Table 1.1","size":"28.1 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5148 Table 1.1","linkHelpText":"— Tributary sites in the Middle Iowa River Basin, upstream of Coralville Reservoir"},{"id":383241,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":383238,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5148/sir20205148.pdf","text":"Report","description":"SIR 2020–5148"},{"id":383237,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5148/coverthb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Middle Iowa River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.065673828125,\n 41.380930388318\n ],\n [\n -90.911865234375,\n 41.529141988723104\n ],\n [\n -90.9613037109375,\n 41.79179268262892\n ],\n [\n -91.2249755859375,\n 42.020732852644294\n ],\n [\n -91.5655517578125,\n 42.17968819665961\n ],\n [\n -91.900634765625,\n 42.34636533160187\n ],\n [\n -92.142333984375,\n 42.66224137632748\n ],\n [\n -92.3291015625,\n 42.984558134256076\n ],\n [\n -92.5323486328125,\n 43.18114705939968\n ],\n [\n -92.7685546875,\n 43.20917969039356\n ],\n [\n -92.9058837890625,\n 43.08894918346591\n ],\n [\n -92.8564453125,\n 42.807491865911544\n ],\n [\n -92.6641845703125,\n 42.55712670332118\n ],\n [\n -92.46093749999999,\n 42.28137302193453\n ],\n [\n -92.1148681640625,\n 42.00848901572399\n ],\n [\n -91.8731689453125,\n 41.70982942509964\n ],\n [\n -91.6644287109375,\n 41.40565583808169\n ],\n [\n -91.4117431640625,\n 41.1455697310095\n ],\n [\n -91.175537109375,\n 41.000629848685385\n ],\n [\n -91.0052490234375,\n 40.9964840143779\n ],\n [\n -90.911865234375,\n 41.017210578228436\n ],\n [\n -90.94482421875,\n 41.104190944576466\n ],\n [\n -90.99426269531249,\n 41.21585377825921\n ],\n [\n -91.04919433593749,\n 41.25716209782705\n ],\n [\n -91.065673828125,\n 41.380930388318\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
The response of macrophage aggregates in fish to a variety of environmental stressors has been useful as a biomarker of exposure to habitat degradation. Total volume of macrophage aggregates (MAV) was estimated in the liver and spleen of white perch Morone americana from Chesapeake Bay using stereological approaches. Hepatic and splenic MAV were compared between fish populations from the rural Choptank River (n = 122) and the highly urbanized Severn River (n = 131). Hepatic and splenic MAV increased with fish age, were greater in females from the Severn River only, and were significantly greater in fish from the more polluted Severn River (higher concentrations of polycyclic aromatic hydrocarbons, organochlorine pesticides, and brominated diphenyl ethers). Water temperature and dissolved oxygen had a significant effect on organ volumes, but not on MAV. Age and river were most influential on hepatic and splenic MAV, suggesting that increased MAV in Severn River fish resulted from chronic exposures to higher concentrations of environmental contaminants and other stressors. Hemosiderin was abundant in 97% of spleens and was inversely related to fish condition and positively related to fish age and trematode infections. Minor amounts of hemosiderin were detected in 30% of livers and positively related to concentrations of benzo[a] pyrene metabolite equivalents in the bile. This study demonstrated that hepatic and splenic MAV were useful indicators in fish from the 2 tributaries with different land use characteristics and concentrations of environmental contaminants. More data are needed from additional tributaries with a wider gradient of environmental impacts to validate our results in this species.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/dao03555","usgsCitation":"Matsche, M.A., Blazer, V., Pulster, E., and Mazik, P.M., 2021, Biological and anthropogenic influences on macrophage aggregates in white perch Morone americana from Chesapeake Bay, USA: Diseases of Aquatic Organisms, v. 143, p. 79-100, https://doi.org/10.3354/dao03555.","productDescription":"22 p.","startPage":"79","endPage":"100","ipdsId":"IP-122515","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":388726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.83837890625,\n 36.78289206199065\n ],\n [\n -75.65185546874999,\n 36.78289206199065\n ],\n [\n -75.65185546874999,\n 39.67337039176558\n ],\n [\n -76.83837890625,\n 39.67337039176558\n ],\n [\n -76.83837890625,\n 36.78289206199065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"143","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Matsche, Mark A","contributorId":194275,"corporation":false,"usgs":false,"family":"Matsche","given":"Mark","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":822263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":822264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pulster, Erin","contributorId":236999,"corporation":false,"usgs":false,"family":"Pulster","given":"Erin","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":822265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":822266,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227257,"text":"70227257 - 2021 - Winter roost selection of Lasiurine tree bats in a pyric landscape","interactions":[],"lastModifiedDate":"2022-01-05T13:24:20.027685","indexId":"70227257","displayToPublicDate":"2021-02-09T07:16:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Winter roost selection of Lasiurine tree bats in a pyric landscape","docAbstract":"Day-roost selection by Lasiurine tree bats during winter and their response to dormant season fires is unknown in the southeastern United States where dormant season burning is widely applied. Although fires historically were predominantly growing season, they now occur in the dormant season in this part of the Coastal Plain to support a myriad of stewardship activities, including habitat management for game species. To examine the response of bats to landscape condition and the application of prescribed fire, in the winter of 2019, we mist-netted and affixed radio-transmitters to 16 Lasiurine bats, primarily Seminole bats (Lasiurus seminolus) at Camp Blanding Joint Training Center in northern Florida. We then located day-roost sites to describe roost attributes. For five Seminole bats, one eastern red bat (Lasiurus borealis), and one hoary bat (Lasiurus cinereus), we applied prescribed burns in the roost area to observe bat response in real-time. Generally, Seminole bats selected day-roosts in mesic forest stands with high mean fire return intervals. At the roost tree scale, Seminole day-roosts tended to be larger, taller and in higher canopy dominance classes than surrounding trees. Seminole bats roosted in longleaf (Pinus palustris), slash (Pinus elliotii) and loblolly pine (Pinus taeda) more than expected based on availability, whereas sweetbay (Magnolia virginiana), water oak (Quercus nigra) and turkey oak (Quercus laevis), were roosted in less than expected based on availability. Of the seven roosts subjected to prescribed burns, only one male Seminole bat and one male eastern red bat evacuated during or immediately following burning. In both cases, these bats had day-roosted at heights lower than the majority of other day-roosts observed during our study. Our results suggest Seminole bats choose winter day-roosts that both maximize solar exposure and minimize risks associated with fire. Nonetheless, because selected day-roosts largely were fire-dependent or tolerant tree species, application of fire does need to periodically occur to promote recruitment and retention of suitable roost sites.
The diversification of modern birds has been shaped by a number of radiations. Rapid diversification events make reconstructing the evolutionary relationships among taxa challenging due to the convoluted effects of incomplete lineage sorting (ILS) and introgression. Phylogenomic data sets have the potential to detect patterns of phylogenetic incongruence, and to address their causes. However, the footprints of ILS and introgression on sequence data can vary between different phylogenomic markers at different phylogenetic scales depending on factors such as their evolutionary rates or their selection pressures. We show that combining phylogenomic markers that evolve at different rates, such as paired-end double-digest restriction site-associated DNA (PE-ddRAD) and ultraconserved elements (UCEs), allows a comprehensive exploration of the causes of phylogenetic discordance associated with short internodes at different timescales. We used thousands of UCE and PE-ddRAD markers to produce the first well-resolved phylogeny of shearwaters, a group of medium-sized pelagic seabirds that are among the most phylogenetically controversial and endangered bird groups. We found that phylogenomic conflict was mainly derived from high levels of ILS due to rapid speciation events. We also documented a case of introgression, despite the high philopatry of shearwaters to their breeding sites, which typically limits gene flow. We integrated state-of-the-art concatenated and coalescent-based approaches to expand on previous comparisons of UCE and RAD-Seq data sets for phylogenetics, divergence time estimation, and inference of introgression, and we propose a strategy to optimize RAD-Seq data for phylogenetic analyses. Our results highlight the usefulness of combining phylogenomic markers evolving at different rates to understand the causes of phylogenetic discordance at different timescales.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/sysbio/syaa101","usgsCitation":"Ferrer Obiol, J., James, H.F., Chesser, R., Bretagnolle, V., Gonzalez-Solis, J., Rozas, J., Riutort, M., and Welch, A., 2021, Integrating sequence capture and restriction-site associated DNA sequencing to resolve recent radiations of pelagic seabirds: Systematic Biology, v. 70, no. 5, p. 976-996, https://doi.org/10.1093/sysbio/syaa101.","productDescription":"21 p.","startPage":"976","endPage":"996","ipdsId":"IP-120576","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":453551,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/sysbio/syaa101","text":"Publisher Index Page"},{"id":383696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ferrer Obiol, Joan","contributorId":252895,"corporation":false,"usgs":false,"family":"Ferrer Obiol","given":"Joan","email":"","affiliations":[{"id":50463,"text":"Univ. of Barcelona","active":true,"usgs":false}],"preferred":false,"id":811077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"James, Helen F.","contributorId":54414,"corporation":false,"usgs":false,"family":"James","given":"Helen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":811078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chesser, R. Terry 0000-0003-4389-7092 tchesser@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-7092","contributorId":894,"corporation":false,"usgs":true,"family":"Chesser","given":"R. Terry","email":"tchesser@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":811079,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bretagnolle, Vincent","contributorId":213757,"corporation":false,"usgs":false,"family":"Bretagnolle","given":"Vincent","email":"","affiliations":[{"id":38848,"text":"CNRS & Université de La Rochelle","active":true,"usgs":false}],"preferred":false,"id":811080,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gonzalez-Solis, Jacob 0000-0002-8691-9397","orcid":"https://orcid.org/0000-0002-8691-9397","contributorId":252896,"corporation":false,"usgs":false,"family":"Gonzalez-Solis","given":"Jacob","email":"","affiliations":[{"id":50463,"text":"Univ. of Barcelona","active":true,"usgs":false}],"preferred":false,"id":811081,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rozas, Julio","contributorId":252897,"corporation":false,"usgs":false,"family":"Rozas","given":"Julio","email":"","affiliations":[{"id":50463,"text":"Univ. of Barcelona","active":true,"usgs":false}],"preferred":false,"id":811082,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Riutort, Marta","contributorId":252898,"corporation":false,"usgs":false,"family":"Riutort","given":"Marta","email":"","affiliations":[{"id":50463,"text":"Univ. of Barcelona","active":true,"usgs":false}],"preferred":false,"id":811083,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Welch, Andreanna J.","contributorId":79313,"corporation":false,"usgs":false,"family":"Welch","given":"Andreanna J.","affiliations":[],"preferred":false,"id":811084,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70207509,"text":"sir20195146 - 2021 - Water-level conditions in the confined aquifers of the New Jersey Coastal Plain, 2013","interactions":[],"lastModifiedDate":"2021-02-12T20:58:10.337303","indexId":"sir20195146","displayToPublicDate":"2021-02-05T13:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5146","displayTitle":"Water-Level Conditions in the Confined Aquifers of the New Jersey Coastal Plain, 2013","title":"Water-level conditions in the confined aquifers of the New Jersey Coastal Plain, 2013","docAbstract":"The Coastal Plain aquifers of New Jersey provide an important source of water for more than 3.5 million people. In 2013, groundwater withdrawals from 10 confined aquifers of the New Jersey Coastal Plain totaled about 190 million gallons per day. Steadily increasing withdrawals from the late 1800s to the early 1990s resulted in declining water levels and the formation of regional cones of depression in many confined Coastal Plain aquifers. Starting in 1978, the U.S. Geological Survey (USGS) began mapping the potentiometric surfaces of the major confined Coastal Plain aquifers every 5 years to provide a regional assessment of groundwater conditions.
In a study conducted by the USGS, in cooperation with the New Jersey Department of Environmental Protection, water levels in 10 confined aquifers of the New Jersey Coastal Plain were measured and evaluated to provide a regional overview of groundwater conditions during fall 2013. Water levels were measured in 987 wells in New Jersey, and parts of Pennsylvania and Delaware. Potentiometric-surface maps were prepared for, in ascending order of age, the confined Cohansey aquifer of Cape May County, Rio Grande water-bearing zone, Atlantic City 800-foot sand, Piney Point aquifer, Vincentown aquifer, Wenonah-Mount Laurel aquifer, Englishtown aquifer system, and the Upper, Middle, and Lower aquifers of the Potomac-Raritan-Magothy (PRM) aquifer system.
Persistent, regionally extensive cones of depression were present in the potentiometric surfaces of the Englishtown aquifer system and Wenonah-Mount Laurel aquifer in Ocean and Monmouth Counties; Wenonah-Mount Laurel and Upper, Middle, and Lower PRM aquifers in Camden County; and Atlantic City 800-foot sand in Atlantic County. Changes in water levels from 2008 to 2013 were measured in many Coastal Plain aquifers in New Jersey. In some areas, water levels continued to decline as a result of pumping, but in other areas water levels continued to recover as a result of regulated decreases in groundwater withdrawals. Since 2008, in the confined Cohansey aquifer in Cape May County, water levels generally did not change; however, cones of depression in the potentiometric surface of the Piney Point aquifer in some areas of Cumberland County deepened by more than 20 feet (ft). In Critical Area 1, an area of restricted withdrawals, measured water levels in the Wenonah-Mount Laurel aquifer declined in parts of southern Monmouth County by more than 10 ft; however, rises in water levels of more than 10 ft were measured in parts of northern Ocean and Monmouth Counties. Since 2008, in Critical Area 2, also an area of restricted withdrawals, measured water levels in the Wenonah-Mount Laurel aquifer rose more than 20 ft in parts of western Burlington County and more than 20 ft in parts of western Camden County. Since 2008, in Critical Area 1, measured water levels in the Englishtown aquifer system declined in parts of eastern Ocean County by more than 10 ft and in southeastern Monmouth County by more than 20 ft; however, rises in water levels of more than 10 ft were measured in other parts of Ocean and Monmouth Counties.
In general, since 2008 in Critical Area 2, in the Upper PRM aquifer, measured water levels continued to rise by 10 ft or more in central and western Burlington and central Camden Counties. In the Middle PRM aquifer in Critical Area 2, measured water levels rose in parts of central Camden County by 10 ft or more. However, measured water levels in the Lower PRM aquifer in Critical Area 2 were more than 10 ft lower in the center of the cone of depression in central Camden County, but measured water levels continued to rise updip from this area in Critical Area 2.
Seasonal water-level fluctuations are presented in time-series hydrographs for 77 wells during 1978–2013. Analyses of long-term water-level changes for the period 2008–13 indicate downward water-level trends at 14 wells (18 percent), upward trends at 34 wells (44 percent), and no substantial change at 29 wells (38 percent). Downward trends were most often observed for wells screened in the Piney Point aquifer and the Atlantic City 800-foot sand. Upward water-level trends were most often measured for wells screened in the PRM aquifer system. Upward water-level trends also were measured for wells in the Englishtown aquifer system and the Wenonah-Mount Laurel aquifer in Critical Area 1 in some areas; however, downward trends and no substantial changes were measured in other areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195146","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Gordon, A.D., Carleton, G.B., and Rosman, R., 2021, Water-level conditions in the confined aquifers of the New Jersey Coastal Plain, 2013: U.S. Geological Survey Scientific Investigations Report 2019–5146, 104 p., 9 pl., https://doi.org/10.3133/sir20195146.","productDescription":"Report: x, 104 p.; 9 Plates: 34 x 44 inches or smaller; Data Release","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073418","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":383040,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2019/5146/sir20195146_plate5.pdf","text":"Plate 5","size":"1.23 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- 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aquifer system, 2013"},{"id":383043,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2019/5146/sir20195146_plate8.pdf","text":"Plate 8","size":"1.26 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Potentiometric surface of the Middle and undifferentiated Potomac-Raritan-Magothy aquifer, 2013"},{"id":383044,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2019/5146/sir20195146_plate9.pdf","text":"Plate 9","size":"1.23 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Potentiometric surface of the Lower Potomac-Raritan-Magothy aquifer, 2013"},{"id":383033,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5146/coverthb.jpg"},{"id":383037,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2019/5146/sir20195146_plate2.pdf","text":"Plate 2","size":"1.27 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Potentiometric surface of the Atlantic City 800-foot 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U.S. Geological Survey
3450 Princeton Pike
Suite 110
Lawrenceville, NJ 08648