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":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","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":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","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":"- Potentiometric surface of the Wenonah-Mount Laurel aquifer, 2013"},{"id":383039,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2019/5146/sir20195146_plate4.pdf","text":"Plate 4","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Potentiometric surface of the Vincentown aquifer, 2013"},{"id":383038,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2019/5146/sir20195146_plate3.pdf","text":"Plate 3","size":"1.19 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Potentiometric surface of the Piney Point aquifer, 2013"},{"id":383036,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2019/5146/sir20195146_plate1.pdf","text":"Plate 1","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Potentiometric surface of the confined Cohansey aquifer and the Rio Grande water-bearing zone, 2013"},{"id":383035,"rank":3,"type":{"id":30,"text":"Data 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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 sand, 2013"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.99017333984375,\n 40.490826256468054\n ],\n [\n -74.3115234375,\n 40.48873742102282\n ],\n [\n -74.37469482421875,\n 40.48873742102282\n ],\n [\n -74.78118896484375,\n 40.195659093364654\n ],\n [\n -75.146484375,\n 39.96238554917605\n ],\n [\n -75.146484375,\n 39.886557705928475\n ],\n [\n -75.3826904296875,\n 39.83595916247957\n ],\n [\n -75.51177978515625,\n 39.71352536237346\n ],\n [\n -75.57220458984375,\n 39.61626788999701\n ],\n [\n -75.53924560546875,\n 39.47648555419739\n ],\n [\n -75.16021728515624,\n 39.18969082109678\n ],\n [\n -74.91851806640624,\n 39.172658670429946\n ],\n [\n -74.97894287109375,\n 38.9380483825641\n ],\n [\n -74.937744140625,\n 38.91881851059804\n ],\n [\n -74.81414794921875,\n 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U.S. Geological Survey
3450 Princeton Pike
Suite 110
Lawrenceville, NJ 08648
The U.S. Geological Survey (USGS) completed hydrologic and hydraulic analyses for selected reaches of the Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan, in cooperation with the city of Lansing. The study comprised a 3.1-mile reach of the Grand River, a 30.3-mile reach of the Red Cedar River, and a 12.0-mile reach of Sycamore Creek. The information produced from the study can be used to update and expand an existing Federal Emergency Management Agency Flood Insurance Study for Ingham County, Mich.
Historical streamflow data from USGS streamgages on Grand River at Lansing, Mich. (station number 04113000); Red Cedar River at East Lansing, Mich. (station number 04112500); Red Cedar River near Williamston, Mich. (station number 04111379); and Sycamore Creek at Holt Road near Holt, Mich. (station number 04112850) were used to estimate instantaneous peak streamflows for floods with 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities (AEPs) and a “1-percent plus” AEP.
The Hydrologic Engineering Center’s River Analysis System step-backwater model was used to determine water-surface elevation profiles for the 10-, 4-, 2-, 1-, and 0.2-percent AEP floods, the 1-percent plus AEP flood, and a regulatory floodway for each stream reach. The hydraulic models were calibrated based on stage-streamflow ratings at USGS streamgages. Flood-inundation boundaries for the 1- and 0.2-percent annual exceedance probability floods and regulatory floodway were created for each stream.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20205144","collaboration":"Prepared in cooperation with the city of Lansing, Michigan","usgsCitation":"Whitehead, M.T., and Ostheimer, C.J., 2021, Hydrologic and hydraulic analyses of the Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan: U.S. Geological Survey Scientific Investigations Report 2020–5144, \n17 p., https://doi.org/10.3133/sir2020–5144.","productDescription":"Report: iv, 17 p.; Data Realease","onlineOnly":"Y","ipdsId":"IP-118378","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":382823,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5144/coverthb.jpg"},{"id":382824,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5144/sir20205144.pdf","text":"Report","size":"3.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5144"},{"id":382825,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91CQ755","text":"USGS data release","linkHelpText":"Geospatial datasets and hydraulic models for the Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan"}],"country":"United States","state":"Michigan","otherGeospatial":"Grand River, Red Cedar River, Sycamore Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.57550048828125,\n 42.48526384858916\n ],\n [\n -83.9959716796875,\n 42.48526384858916\n ],\n [\n -83.9959716796875,\n 42.76465818533266\n ],\n [\n -84.57550048828125,\n 42.76465818533266\n ],\n [\n -84.57550048828125,\n 42.48526384858916\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Science Center
U.S. Geological Survey
6460 Busch Blvd., Suite 100
Columbus, OH 43229
The Yellowstone Volcano Observatory (YVO) monitors volcanic and hydrothermal activity associated with the Yellowstone magmatic system, conducts research into magmatic processes occurring beneath Yellowstone Caldera, and issues timely warnings and guidance related to potential future geologic hazards. This report summarizes the activities and findings of YVO during the year 2018, focusing on the Yellowstone magmatic system. The most noteworthy seismic activity of the year was a February swarm of hundreds of earthquakes in the same area as the 2017 Maple Creek earthquake swarm. The February 2018 activity is viewed as a continuation of the 2017 swarm. Ground deformation trends were mostly unchanged throughout the year, with uplift of the Norris Geyser Basin area and subsidence of the caldera.
Field work in 2018, conducted under research permits granted by the National Park Service, included routine maintenance visits to seismic and geodetic stations as well as deployment of a semipermanent Global Positioning System network during the summer months; installation of an eddy covariance system for tracking carbon dioxide emissions and heat flux near Norris Geyser Basin; deployment of nodal seismic arrays on Geyser Hill, near Steamboat Geyser, and around Yellowstone Lake; and collection of water and gas samples from the Bechler River area in the southwest part of Yellowstone National Park. In addition, examination of satellite thermal imagery resulted in the discovery of a new thermal area on the east side of the Sour Creek resurgent dome, near west Tern Lake. This thermal area appears to have started forming in the early 2000s; before then it was an area of healthy forest. The year might best be remembered, however, for some extraordinary geyser and hot spring activity, specifically at Steamboat Geyser and Ear Spring.
Yellowstone Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court, Suite 100
Vancouver, WA 98683
Email: yvowebteam@usgs.gov
","tableOfContents":"Endocrine-disrupting compounds (EDCs), specifically estrogenic endocrine-disrupting compounds, vary in concentration and composition in surface waters under the influence of different landscape sources and landcover gradients. Estrogenic activity in surface waters may lead to adverse effects in aquatic species at both individual and population levels, often observed through the presence of intersex and vitellogenin induction in male fish. In the Chesapeake Bay Watershed, located on the mid-Atlantic coast of the USA, intersex has been observed in several sub-watersheds where previous studies have identified specific landscape sources of EDCs in tandem with observed fish health effects. Previous work in the Potomac River Watershed (PRW), the largest basin within the Chesapeake Bay Watershed, was leveraged to build random forest regression models to predict estrogenic activity at unsampled reaches in both the Potomac River and larger Chesapeake Bay Watersheds (CBW). Model outputs including important variables, partial dependence plots, and predicted values of estrogenic activity at unsampled reaches provide insight into drivers of estrogenic activity at different seasons and scales. Using the US Environmental Protection Agency effects-based threshold of 1.0 ng/L 17 β-estradiol equivalents, catchments predicted to exceed this value were categorized as at risk for adverse effects from exposure to estrogenic compounds and evaluated relative to healthy watersheds and recreation access locations throughout the PRW. Results show immediate catchment scale models are more reliable than upstream models, and the best predictive variables differ by season and scale. A small percentage of healthy watersheds (< 13%) and public access sites were classified as at risk using the “Total” (annual) model in the CBW. This study is the first Potomac River Watershed assessment of estrogenic activity, providing a new foundation for future risk assessment and management design efforts, with additional context provided for the entire Chesapeake Bay Watershed.
Decades of acidic deposition have adversely affected aquatic and terrestrial ecosystems in acid-sensitive watersheds in parts of the eastern United States. The national Acid Rain Program (Title IV of the 1990 Clean Air Act Amendments - CAAA) helped reduce emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) and resulted in sharp decreases in the acidity of atmospheric deposition. The decrease in acidic deposition produced a steady decline in the acidity of streams in many poorly buffered waters across the western Adirondacks and parts of the Catskill Mountains of New York. Until recently, however, there has been little evidence of biological recovery in most acid-sensitive streams in both regions. Long-term deposition and stream-chemistry records and fish-community data from quantitative surveys done during 1991–93 and again during 2012–19 at 13 sites in the upper Neversink River and its tributaries were evaluated to determine if chemical and biological recovery were evident in this Catskill Mountain watershed and if they could be linked to regional declines in acidic deposition. Between 1991 and 2019, large decreases in sulfate and nitrate deposition in the basin mirrored declines in total nationwide SO2 and NOx emissions. There were corresponding decreases in sulfate and nitrate concentrations in deposition at a National Trends Network station at Frost Valley (NY68) and coincident declines in sulfate concentrations at four long-term monitoring sites in the Neversink River watershed. Mean acid neutralizing capacity and pH increased and inorganic aluminum (Ali) concentrations from routine summertime samples decreased significantly at most moderately to severely acidified sites between the two study periods. Richness, density, and biomass of fish communities increased at most sites, while the density and biomass of brook trout Salvelinus fontinalis populations increased at fewer sites that were undergoing chemical recovery. Although recovery is far from complete, trends in deposition chemistry, water quality, and fish assemblages in streams of the upper Neversink watershed indicate that the 1990 CAAA is having positive impacts on aquatic ecosystems in the Catskill Mountain region, New York.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2021.118235","usgsCitation":"Baldigo, B.P., George, S.D., Winterhalter, D., and McHale, M., 2021, Biological and chemical recovery of acidified Catskill Mountain streams in response to the Clean Air Act Amendments of 1990: Atmospheric Environment, v. 249, 118235, 18 p., https://doi.org/10.1016/j.atmosenv.2021.118235.","productDescription":"118235, 18 p.","ipdsId":"IP-121887","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":453636,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2021.118235","text":"Publisher Index Page"},{"id":383377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Neversink watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.63973999023438,\n 41.81175536180908\n ],\n [\n -74.53399658203125,\n 41.873139978873574\n ],\n [\n -74.4275665283203,\n 41.937019660425264\n ],\n [\n -74.33967590332031,\n 41.963064211132306\n ],\n [\n -74.28680419921875,\n 42.039094188385945\n ],\n [\n -74.34104919433594,\n 42.10382653879911\n ],\n [\n -74.40696716308594,\n 42.11859868281563\n ],\n [\n -74.45571899414062,\n 42.08395512413707\n ],\n [\n -74.62806701660156,\n 41.95080927751363\n ],\n [\n -74.70291137695312,\n 41.86700416724044\n ],\n [\n -74.67750549316406,\n 41.81021999190292\n ],\n [\n -74.63973999023438,\n 41.81175536180908\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"249","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winterhalter, Dylan R. 0000-0003-1774-8034","orcid":"https://orcid.org/0000-0003-1774-8034","contributorId":251765,"corporation":false,"usgs":true,"family":"Winterhalter","given":"Dylan R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810548,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249479,"text":"70249479 - 2021 - Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting","interactions":[],"lastModifiedDate":"2023-10-10T14:16:37.55892","indexId":"70249479","displayToPublicDate":"2021-01-30T09:10:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting","docAbstract":"Cleveland and Tana are remote volcanoes located in the central Aleutian volcanic arc on the eastern end of the Islands of Four Mountains (IFM). The persistently active Mount Cleveland volcano, on the western side of Chuginadak Island, is surrounded by several closely spaced Quaternary volcanic centers including Carlisle, Herbert, Kagamil, Tana, and Uliaga, and numerous small satellite vents on Chiginadak between Cleveland and Tana. The Alaska Volcano Observatory (AVO) installed two permanent broadband seismometers on Chuginadak Island in 2014, and we operated a temporary broadband network focused on the western side of the island in 2015–2016. Collectively, these stations provided the first seismic observations of this frequently active volcano and the surrounding Holocene-aged volcanic vents. During the study period (July 2014–January 2019), eruptive activity at Cleveland was characterized by small explosions separated by periods of lava effusion that formed small domes in the volcano's summit crater. We characterize seismicity beneath Chuginadak Island through automated analysis of event waveform frequency content, development of a one-dimensional P-wave velocity model, calculation of earthquake hypocenters, magnitudes, focal mechanisms, and identification of earthquake families. This analysis reveals the full range of seismic event types expected in a highly active volcanic environment and includes Volcano-Tectonic (VT) earthquakes, Long-Period (LP) events, and explosion signals. LP events appear to cluster at shallow depth beneath the active crater of Mount Cleveland and almost all of the explosions occur without identifiable short-term (hours to days) seismic precursors. VT earthquakes beneath Mount Cleveland occur at depths of 2 to 8 km below sea level (BSL) and range in magnitude from −0.2 to 1.8. VT focal mechanisms have horizontal P-axes that align with the regional axis of maximum stress. These observations, and a relatively slow one-dimensional seismic velocity model, are consistent with a shallow body of magma that is fed through a deeper conduit system. The time-history of VT earthquakes and shallow LP events suggest their occurrence may track the transfer of magma and fluids from the mid-crust to the shallow portions of the conduit system and may provide a means to anticipate future explosions and periods of dome growth. VT hypocenters also extend ~7 km northeast of Cleveland's summit at depths of 5 to 10 km BSL, under a group of Holocene-aged vents between Mount Cleveland and Tana. These earthquakes have vertically-oriented P-axes and a greater percentage occur in families. These observations, combined with observations of vent orientation and morphology and gas flux, suggest the area between Cleveland and Tana represents a zone of complicated volcano-tectonic interaction, similar to calderas elsewhere in the Aleutian arc. The presence of a larger volcanic system in the eastern IFM could influence magmatism and account for the multiple closely spaced volcanic centers in this region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107182","usgsCitation":"Power, J., Roman, D., Lyons, J.J., Haney, M.M., Rasmussen, D.J., Plank, T., Nicolaysen, K., Izbekov, P., Werner, C., and Kaufman, A., 2021, Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting: Journal of Volcanology and Geothermal Research, v. 412, 107182, 18 p., https://doi.org/10.1016/j.jvolgeores.2021.107182.","productDescription":"107182, 18 p.","ipdsId":"IP-121823","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453641,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107182","text":"Publisher Index Page"},{"id":421816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chuginadak Island, Cleveland Volcano, Tana Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -169.65098413866693,\n 52.904805932105404\n ],\n [\n -169.83106863712771,\n 52.8971644246661\n ],\n [\n -170.01036155537554,\n 52.86086066337441\n ],\n [\n -170.01669419707966,\n 52.78767701983992\n ],\n [\n -169.66364942207514,\n 52.76373370379605\n ],\n [\n -169.65098413866693,\n 52.904805932105404\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"412","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Power, John 0000-0002-7233-4398","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":215240,"corporation":false,"usgs":true,"family":"Power","given":"John","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":885873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roman, Diana","contributorId":237832,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","affiliations":[{"id":47620,"text":"Dept. of Terrestrial Magnetism, Carnegie Institution for Science, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":885874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":885875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":885876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rasmussen, Daniel J.","contributorId":237828,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":47619,"text":"Lamont-Doherty Earth Observatory, Columbia University, New York, NY 10027","active":true,"usgs":false}],"preferred":false,"id":885877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Plank, Terry","contributorId":237829,"corporation":false,"usgs":false,"family":"Plank","given":"Terry","affiliations":[{"id":47619,"text":"Lamont-Doherty Earth Observatory, Columbia University, New York, NY 10027","active":true,"usgs":false}],"preferred":false,"id":885878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nicolaysen, K. 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Selenium is derived from bedrock of the Mancos Shale and is mobilized and transported to groundwater and surface water by application of irrigation water. Although it is recognized that groundwater contributes an appreciable amount of selenium to surface water, few studies have addressed interactions between the two. The U.S. Geological Survey in cooperation with the Colorado Water Conservation Board conducted a study during 2017–19 to characterize the quality and quantity of groundwater discharging to an agricultural drainage near Delta, Colorado, locally known as Sunflower Drain.
Water quality in the study area is characterized by high dissolved solids with elevated concentrations of selenium and nitrate resulting from dissolution of soluble salts in the Mancos Shale. Selenium concentrations have decreased by 50 percent since the early 2000s, possibly in response to irrigation system improvements. Stable water isotopes indicate streamflow is dominated by canal water during the irrigation season (April to October) and, during the nonirrigation season (November to March), is dominated by groundwater that has undergone some degree of evaporation. Pesticide and pharmaceutical compounds were infrequently detected, and results indicate they were derived from sources outside the study area such that they do not appear to be useful as tracers of groundwater sources. Stable isotopes of nitrate indicate that nitrate originates from the Mancos Shale, and the isotopic composition is enriched by denitrification in the groundwater system. Using a mass-balance approach, estimated groundwater discharge rates to Sunflower Drain ranged from 0.15 to 0.27 cubic feet per second per mile with one losing reach identified. Selenium, sulfate, and nitrate concentrations in groundwater estimated by mass-balance calculations were similar to concentrations measured in the Poly 17 observation well, located in a largely irrigated area in east tributary. One tributary reach had higher concentrations of selenium, sulfate, and nitrate likely reflecting localized inputs of more concentrated groundwater, similar to the concentrations in the Poly 7 observation well, which is downgradient from a residential area in the west tributary.
Three pilot studies were conducted, including fiber optic distributed temperature sensing to detect groundwater discharge zones in the stream channel, a passive seismic technique to estimate depth to bedrock, and use of radon-222 as a geochemical tracer of groundwater discharge. All three techniques show promise as additional approaches for investigating groundwater discharge surface-water systems in irrigated drainage areas on Mancos Shale.
The factors that affect groundwater movement mainly include when and where irrigation water is transported and applied, and the distribution of bedrock of the Mancos Shale and overlying alluvial deposits. The average groundwater recharge rate for the study area was estimated at 8.1 inches per year, based on mass balance calculations from synoptic survey data. Along the western tributary of Sunflower Drain, there was evidence that spills from the East Canal may recharge the groundwater aquifer adjacent to the stream channel. Groundwater movement to the stream channel may be controlled by the topography of the alluvial/bedrock interface or focused along human-made features, such as tile drains and ditches constructed around irrigated fields. On larger scales, the top of bedrock was also important, creating a topographic constriction that caused a zone of groundwater discharge. The groundwater system is complex, and further study could better define the system, possibly through application of a groundwater flow model and more extensive studies using some of the exploratory methods evaluated in this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20205132","collaboration":"Prepared in cooperation with Colorado Water Conservation Board","usgsCitation":"Mast, M.A., 2021, Characterization of groundwater quality and discharge with emphasis on selenium in an irrigated agricultural drainage near Delta, Colorado, 2017–19: U.S. Geological Survey Scientific Investigations Report 2020–5132, 34 p., https://doi.org/10.3133/sir20205132.","productDescription":"Report: vi, 34 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119514","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":382809,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LKYX9H","text":"USGS data release","linkHelpText":"Near-surface geophysical data collected in the Sunflower Drain study area near Delta, Colorado, March 2018"},{"id":382805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5132/coverthb.jpg"},{"id":382806,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5132/sir20205132.pdf","text":"Report","size":"5.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5132"}],"country":"United States","state":"Colorado","city":"Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.21945190429688,\n 38.638327308061875\n ],\n [\n -107.97019958496094,\n 38.638327308061875\n ],\n [\n -107.97019958496094,\n 38.82205601494022\n ],\n [\n -108.21945190429688,\n 38.82205601494022\n ],\n [\n -108.21945190429688,\n 38.638327308061875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225