Fluorescence spectroscopy via confocal laser scanning microscopy (CLSM) was used to analyze ancient sedimentary organic matter, including Tasmanites microfossils in Devonian shale and Gloecapsomorpha prisca (G. prisca) in Ordovician kukersite from North American basins. We examined fluorescence emission as a function of excitation laser wavelength, sample orientation, and with respect to location within individual organic entities and in transects across bedded organic matter. Results from spectral scans of the same field of view in Tasmanites with different laser lines showed progressive red-shift in emission maxima with longer excitation wavelengths. This result indicates steady-state Tasmanites fluorescence emission is an overlapping combination of emission from multiple fluorophore functions. Stokes shift decreased with increasing excitation wavelength, further suggesting the presence of multiple fluorophore functions with different S1 → S0 transition energies. This observation also indicates that at longer excitation wavelengths, less absorbed light energy is dissipated via collisional transfer than at shorter excitation wavelengths and may suggest fewer polar functions are preferentially absorbing. Confirming earlier results, emission spectra observed from high fluorescence intensity regions (fold apices) in individual Tasmanites are blue-shifted relative to emission from other locations in the same microfossil. We suggest high intensity emission is from photoselective alignment of polarized excitation with the fluorophore absorption and emission transition moment. The blue shift observed in regions of high intensity emission may be due to relative absence or realignment of polar species, e.g., bridging ether or ester functions, although variations in O abundance could not be confirmed with preliminary time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis. Tasmanites occurring in consolidated sediments are flattened from original spherical morphology and, in optical microscopy, this burial deformation results in generally parallel extinction (strain-influenced) and positive elongation. The deformation also induces fluorescence anisotropy observed as variations in emission wavelength when individual Tasmanites are measured from their long axis parallel to bedding, whereas this effect is absent in bedding-normal view. Transects from G. prisca-rich source layers into adjacent reservoir layers show decrease in fluorescence intensity and spectral red-shift (increase in full-width half-maximum with increasing red portion of the half-width). These results may suggest an increase in fluorescence quenching across the source-to-reservoir transition zone, consistent with an increase in aromaticity following petroleum expulsion and migration. These observations are supported by increasing reflectance values measured across similar micro-scale transects. Our results highlight the applicability of CLSM as a broad and under-utilized approach for the characterization of sedimentary organic matter and are discussed with perspective toward petroleum processes and thermal indices research.
As atmospheric dust deposition continues to increase across the southwestern United States, it has the potential to alter ecosystem productivity and structure by delivering nutrients, base cations, and pollutants to remote mountain sites. Due to the sparse distribution of dust monitoring sites, open questions remain about the spatial and temporal variability of dust fluxes and composition across mountainous terrain. We present a 1 year (November 2017 to November 2018) record of seasonal dust fluxes and composition from an elevation transect across the Colorado Front Range extending from the urban plains to the remote alpine. At all nine sites, dust was enriched in the essential nutrient phosphorus and the metals copper, zinc, lead, and cadmium, elements that are enriched in dust deposited at sites across the Rocky Mountain West. We observed a seasonal pattern in dust composition, with the highest concentrations of zinc and cadmium during the summer, when back trajectory modeling suggested a greater contribution of dust from local urban and agricultural regions to the east of the collection sites. During the summer, there was also a trend of higher dust fluxes at lower elevations; dust fluxes ranged from 18.9 ± 0.1 g m−2 yr−1 on the plains to 5.9 ± 0.2 g m−2 yr−1 in the alpine. Our results suggest that urban and agricultural land east of the Colorado Front Range is an important source of nutrients and pollutants to all elevations of the mountain range.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JF005436","usgsCitation":"Heindel, R.C., Putman, A.L., Murphy, S.F., Repert, D.A., and Hinckley, E.S., 2020, Atmospheric dust deposition varies by season and elevation in the Colorado Front Range, USA: Journal of Geophysical Research: Earth Surface, v. 125, no. 5, e2019JF005436, 18 p., https://doi.org/10.1029/2019JF005436.","productDescription":"e2019JF005436, 18 p.","ipdsId":"IP-117827","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":375411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Colorado Front Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.578369140625,\n 39.65645604812829\n ],\n [\n -104.5458984375,\n 39.65645604812829\n ],\n [\n -104.5458984375,\n 40.463666324587685\n ],\n [\n -106.578369140625,\n 40.463666324587685\n ],\n [\n -106.578369140625,\n 39.65645604812829\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Heindel, Ruth C. 0000-0001-6292-2076","orcid":"https://orcid.org/0000-0001-6292-2076","contributorId":225133,"corporation":false,"usgs":false,"family":"Heindel","given":"Ruth","email":"","middleInitial":"C.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":790482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putman, Annie L. 0000-0002-9424-1707","orcid":"https://orcid.org/0000-0002-9424-1707","contributorId":225134,"corporation":false,"usgs":true,"family":"Putman","given":"Annie","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":790484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Repert, Deborah A. 0000-0001-7284-1456 darepert@usgs.gov","orcid":"https://orcid.org/0000-0001-7284-1456","contributorId":2578,"corporation":false,"usgs":true,"family":"Repert","given":"Deborah","email":"darepert@usgs.gov","middleInitial":"A.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":790485,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hinckley, Eve-Lyn S.","contributorId":181894,"corporation":false,"usgs":false,"family":"Hinckley","given":"Eve-Lyn","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":790486,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206370,"text":"ofr20191115 - 2020 - A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts","interactions":[],"lastModifiedDate":"2024-03-04T19:21:20.997009","indexId":"ofr20191115","displayToPublicDate":"2020-04-10T09:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1115","displayTitle":"A Decision Framework to Analyze Tide-Gate Options for Restoration of the Herring River Estuary, Massachusetts","title":"A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts","docAbstract":"The collective set of decisions involved with the restoration of degraded wetlands is often more complex than considering only ecological responses and outcomes. Restoration is commonly driven by a complex interaction of social, economic, and ecological factors representing the mandate of resource stewards and the values of stakeholders. The authors worked with the Herring River Restoration Committee (HRRC) to develop a decision framework to understand the implications of complex tradeoffs and to guide decision making for the restoration of the 1,100-acre Herring River estuary within Cape Cod National Seashore, which has been restricted from tidal influence for more than 100 years. The HRRC represents decision maker and stakeholder interests in the restoration process. For a 25-year planning horizon, decisions involve the rate at which newly constructed water-control structures allow tidal exchange, and the timing and location of implementing numerous secondary management options. Decisions affect multiple stakeholders, including residents of two adjacent towns who value the watershed for numerous benefits and whose economy relies on seasonal activities and aquaculture. System response to management decisions is characterized by a high degree of uncertainty and risk with positive and negative outcomes possible. Decision policies will affect biophysical (for example, sediment transport, discharge of fecal coliform bacteria) and ecological (for example, vegetation response, fish passage, effects on shellfish) processes, as well as socioeconomic interests (for example, effects on property, viewscapes, recreation). The framework provides a structured approach for evaluating tradeoffs among multiple objectives (ecological and social) while appropriately characterizing relevant uncertainties and accounting for levels of risk tolerances and the values of decision makers and stakeholders. Consequences of tide-gate management options are predicted using a range of methods from quantitative physical process models to elicited expert judgement. The decision framework is presented, and the software developed to implement the tradeoff analysis is introduced. The results from an initial prototype analysis using a software application developed for analyses of tradeoffs and of sensitivity of the decision to risk and uncertainty are presented. The next step is to use the decision-support application to analyze options using improved predictions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191115","collaboration":"Prepared in cooperation with National Park Service and U.S. Fish and Wildlife Service","usgsCitation":"Smith, D.R., Eaton, M.J., Gannon, J.J., Smith, T.P., Derleth, E.L., Katz, J., Bosma, K.F., and Leduc, E., 2020, A decision framework to analyze tide-gate options for restoration of the Herring River Estuary, Massachusetts: U.S. Geological Survey Open-File Report 2019–1115, 42 p., https://doi.org/10.3133/ofr20191115.","productDescription":"viii, 42 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101813","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":373779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1115/ofr20191115.pdf","text":"Report","size":"3.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1115"},{"id":373778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1115/coverthb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Herring River Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.07286071777344,\n 41.92961289444422\n ],\n [\n -70.02462387084961,\n 41.92961289444422\n ],\n [\n -70.02462387084961,\n 41.96357478222518\n ],\n [\n -70.07286071777344,\n 41.96357478222518\n ],\n [\n -70.07286071777344,\n 41.92961289444422\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Groundwater in eastern Abu Dhabi in the United Arab Emirates is an important resource that is widely used for irrigation and domestic supplies in rural areas. The U.S. Geological Survey and the Environment Agency—Abu Dhabi cooperated on an investigation to integrate existing hydrogeologic information and to answer questions about regional groundwater resources in Abu Dhabi by developing a numerical groundwater flow model based on MODFLOW–2005 software. The groundwater flow model developed in this investigation provides an improved understanding of groundwater conditions in the eastern region of the Emirate of Abu Dhabi. The flow model simulates steady-state predevelopment conditions from before the rapid growth of modern pumping in the 1980s and was calibrated with 1,342 groundwater-level observations by use of automated and manual calibration techniques. The calibrated model provides good accuracy, with a mean error of 0.50 meters and a standard error of 5.92 meters for simulated groundwater levels. The results of the regional water budget simulation show that gap recharge, which is groundwater inflow through mountain-front gap alluvium, is the greatest source of water to the aquifer. In the base simulation scenario, gap recharge represents 80 percent of total inflow (119,470 of 149,403 cubic meters per day) and the greatest outflow from the aquifer is from evapotranspiration (93 percent of total outflow). Model scenario and sensitivity results reveal a need for data that more thoroughly and more accurately describe aquifer hydraulic conductivity, inflow to the aquifer from the Oman Mountains, and recharge from precipitation on the piedmont. Additional long-term aquifer pumping test observations would improve understanding of aquifer hydraulic conductivity, which would also improve model accuracy. Future studies can modify the model to understand the effect of land-use change and water use on groundwater supplies and simulate more complex groundwater flow conditions in a predictive mode.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185158","collaboration":"Prepared in cooperation with the Environment Agency—Abu Dhabi","usgsCitation":"Eggleston, J.R., Mack, T.J., Imes, J.L., Kress, W., Woodward, D.W., and Bright, D.J., 2020, Hydrogeologic framework and simulation of predevelopment groundwater flow, eastern Abu Dhabi Emirate, United Arab Emirates: U.S. Geological Survey Scientific Investigations Report 2018–5158, 48 p., https://doi.org/10.3133/sir20185158.","productDescription":"Report: viii, 48 p.; Data Release","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088658","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":373295,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5158/coverthb.jpg"},{"id":373296,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5158/sir20185158.pdf","text":"Report","size":"6.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5158"},{"id":373297,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZWZISB","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 Groundwater Flow Model to Simulate Predevelopment Groundwater Flow in the Eastern Abu Dhabi Emirate, United Arab Emirates"}],"country":"United Arab Emirates","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[51.57952,24.2455],[51.75744,24.29407],[51.79439,24.01983],[52.57708,24.17744],[53.40401,24.15132],[54.008,24.12176],[54.69302,24.79789],[55.43902,25.43915],[56.07082,26.05546],[56.26104,25.71461],[56.39685,24.92473],[55.88623,24.92083],[55.80412,24.2696],[55.98121,24.13054],[55.52863,23.9336],[55.52584,23.52487],[55.23449,23.11099],[55.20834,22.70833],[55.0068,22.49695],[52.00073,23.00115],[51.61771,24.01422],[51.57952,24.2455]]]},\"properties\":{\"name\":\"United Arab Emirates\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Water is an important resource in the arid southwest region of the United States where there is a limited supply of surface water and groundwater. In the Death Valley regional groundwater flow system (DVRFS) in southern Nevada and eastern California, groundwater is the main source of supply for agricultural, commercial, and domestic water needs.
For over four decades, the United States Geological Survey (USGS) Nevada Water Science Center (NVWSC) has assisted environmental programs with the collection of hydrologic information within the DVRFS. Three hydrologic networks, managed in cooperation with local (Nye County, Nev., and Inyo County, Calif.) and federal (Bureau of Land Management, Fish and Wildlife Service, National Park Service, U.S. Department of Energy National Nuclear Security Administration) agencies, are used to actively monitor wells and springs in the region.
Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 89701
The geology of northwestern Arizona is prominently displayed on the canyon and cliff walls that compose the high-desert landscape of the Hualapai Plateau and that border the Truxton basin. The Truxton basin is a small topographic basin filled with Quaternary and Tertiary deposits and volcanic rock (about 1,600 feet thick near Truxton, Arizona) that overlie Proterozoic crystalline metamorphic rocks in the west or Cambrian sedimentary rocks in the east. The Hualapai Plateau is a large block of Paleozoic-age sedimentary rocks that are dissected by many deep canyons. Most surface-water drainages in the Truxton basin and Hualapai Plateau are ephemeral and flow only in response to significant precipitation events, but a few drainages have perennial reaches that are supported by groundwater discharge from springs. Saturated basin-fill sediments in the Truxton basin compose the Truxton aquifer, which is currently used as a water supply for the community of Peach Springs, Arizona, and supplies a small number of livestock and domestic wells. Usable groundwater on the Hualapai Plateau is in either perched water-bearing zones close to land surface or in the Muav Limestone aquifer at depths of greater than 2,000 feet below land surface. To date, only two test wells have been drilled through the Muav Limestone on the Hualapai Plateau, and neither of those wells encountered water in the limestone, indicating the unit is not saturated in all areas of the plateau.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205017B","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Mason, J.P., Bills, D.J., and Macy, J.P., 2020, Geology and hydrology of the Truxton basin and Hualapai Plateau, northwestern Arizona, chap. B of Mason, J.P., ed., Geophysical surveys, hydrogeologic characterization, and groundwater flow model for the Truxton basin and Hualapai Plateau, northwestern Arizona: U.S. Geological Survey Scientific Investigations Report 2020–5017, 9 p., https://doi.org/10.3133/sir20205017B.","productDescription":"iv, 9 p.","numberOfPages":"9","onlineOnly":"Y","ipdsId":"IP-115098","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":373640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5017/b/sir20205017_chap_b.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5017 Chapter B"},{"id":399685,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109884.htm"},{"id":373501,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5017/b/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Hualapai Plateau, Truxton Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.2125,\n 35.2281\n ],\n [\n -113.0603,\n 35.2281\n ],\n [\n -113.0603,\n 36.2139\n ],\n [\n -114.2125,\n 36.2139\n ],\n [\n -114.2125,\n 35.2281\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Terrestrial salamanders are adapted to moist, cool microenvironments that facilitate cutaneous respiration and decrease risk of desiccation. Warmer, drier microenvironments may induce habitat use changes by salamanders to alleviate stressful microenvironmental conditions. Changes in salamander habitat use may bias population metrics when sampling occurs in areas with different microenvironmental conditions. The objective of this study was to determine whether Plethodon cinereus (Eastern Red-backed Salamander) exhibit surface cover object refugia preferences or occupancy rate differences at sampling locations with different microenvironmental conditions and with respect to sampling day of year. We assessed P. cinereus occupancy rates and preference of surface cover refugia using artificial and natural cover objects in two sampling locations: forests along rights-of-way (EDGEFOR) and interior forests (INTFOR). Plethodon cinereus showed no preference for cover object type (coverboards, logs, and rocks) in either EDGEFOR or INTFOR sampling plots. Occupancy rates were greater under cover objects in INTFOR plots than EDGEFOR plots. Occupancy rates increased with increasing cover object width and decreased with day of year (spring-late summer) irrespective of cover object type or sampling location. Our study suggests that incorporating multiple cover object types into study designs will not incur bias resulting from preference of P. cinereus for cover objects.
","language":"English","usgsCitation":"Margenau, E.L., Wood, P.B., and Brown, D.A., 2020, Efficacy and biases of cover object survey design for sampling eastern red-backed salamanders (Plethodon cinereus) at forest edge and interior locations: Herpetological Conservation and Biology, v. 15, no. 2, p. 440-447.","productDescription":"8 p.","startPage":"440","endPage":"447","ipdsId":"IP-117511","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Beury Mountain, Lewis Wetzel Wildlife Management 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Wood Tar in Pennsylvania","title":"Assessment of microscopic pathology in fishes collected at sites impacted by wood tar in Pennsylvania","docAbstract":"In an effort to determine whether fish populations in an area affected by wood tar waste exhibited health effects, fish were collected and analyzed with histopathology. Multiple species, including Mottled Sculpin (Cottus bairdii), Creek Chub (Semotilus atromaculatus), White Sucker (Catostumus commersonii), Redside Dace (Clinostomus elongatus), Common Shiner (Luxilus cornutus), and Western Blacknose Dace (Rhinichthys obtusus) were sampled from a reference site, Meade Run, and potentially affected streams, Kinzua Creek and Threemile Run, in northwestern Pennsylvania. A full histopathological evaluation was conducted to identify microscopic abnormalities potentially associated with wood tar exposure. The evaluation identified primarily parasites associated with tissue changes. These included microsporidian parasites in the ovaries of Common Shiner and Western Blacknose Dace; myxozoan cysts in the muscle of Common Shiner, Creek Chub, and Western Blacknose Dace; trematode cysts in the muscle of Creek Chub, Redside Dace and Common Shiner; and coccidia in spleen or pancreas of Creek Chub and Common Shiner. Microscopic abnormalities potentially associated with chemical exposure included ceroid/lipofuscin deposits in the meninges of the olfactory lobe of the brain in Common Shiner, Western Blacknose Dace, and Creek Chub, as well as bile duct proliferation and a biliary tumor in Creek Chub. Overall, the findings did not reveal significant microscopic pathology consistent with exposure to wood tar waste.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201024","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Walsh, H.L., Blazer, V.S., Mazik, P.M., Sperry, A.J., and Pavlick, D., 2020, Assessment of microscopic pathology in fishes collected at sites impacted by wood tar in Pennsylvania: U.S. Geological Survey Open-File Report 2020–1024, 14 p., https://doi.org/10.3133/ofr20201024.","productDescription":"vi, 14 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-116287","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science 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\"}}]}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Recent work on cores and outcrops of the Middle-Upper Triassic Shublik Formation has facilitated surface to subsurface correlation of depositional sequences across the Alaska North Slope. Five transgressive-regressive depositional sequences have been defined within three large-scale stratigraphic units. Outcrop spectral gamma-ray (GR) profiles were used to correlate observed stacking patterns with nearby exploration wells, and GR logs from 161 exploration wells were used to correlate the three large-scale stratigraphic units across the North Slope and nearby offshore. Interpretations of depositional facies and sequence stratigraphy in cores from 26 wells were used to corroborate regional correlations. Isochore maps constructed for each of the three stratigraphic units illustrate the influence of accommodation on depositional patterns and suggest reactivation of several older tectonic elements during Shublik deposition. An isochore map of the richest, oil-prone interval of the Shublik Formation reveals a thick pod south of Harrison Bay, the eastern part of which lies beneath a recent giant Shublik-sourced oil discovery in the Cretaceous Nanushuk Formation. In addition, when integrated with thermal maturity, this isochore map may provide leads for areas that are optimal for unconventional resource exploration.
","language":"English","publisher":"Society of Exploration Geophysicists, American Association of Petroleum Geologists","doi":"10.1190/INT-2019-0195.1","usgsCitation":"Rouse, W.A., Whidden, K.J., Dumoulin, J.A., and Houseknecht, D.W., 2020, Surface to subsurface correlation of the Middle-Upper Triassic Shublik Formation within a revised sequence stratigraphic framework: Interpretation, v. 8, no. 2, p. SJ1-SJ16, https://doi.org/10.1190/INT-2019-0195.1.","productDescription":"16 p.","startPage":"SJ1","endPage":"SJ16","ipdsId":"IP-111994","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":377207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.5654296875,\n 66.96447630005638\n ],\n [\n -140.9765625,\n 66.96447630005638\n ],\n [\n -140.9765625,\n 71.31487666166718\n ],\n [\n -159.5654296875,\n 71.31487666166718\n ],\n [\n -159.5654296875,\n 66.96447630005638\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rouse, William A. 0000-0002-0790-370X wrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0790-370X","contributorId":4172,"corporation":false,"usgs":true,"family":"Rouse","given":"William","email":"wrouse@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":795306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":795307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","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":795308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":795309,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211571,"text":"70211571 - 2020 - Development of microsatellite markers for three at risk tiger beetles Cicindela dorsalis dorsalis, C. d. media, and C. puritana","interactions":[],"lastModifiedDate":"2020-07-31T15:08:52.822033","indexId":"70211571","displayToPublicDate":"2020-03-23T10:01:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":958,"text":"BMC Research Notes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Development of microsatellite markers for three at risk tiger beetles Cicindela dorsalis dorsalis, C. d. media, and C. puritana","title":"Development of microsatellite markers for three at risk tiger beetles Cicindela dorsalis dorsalis, C. d. media, and C. puritana","docAbstract":"Tiger beetles inhabiting sandy beaches and cliffs along the east coast of the United States are facing increasing habitat loss due to erosion, urbanization, and sea level rise. The northeastern beach tiger beetle Cicindela dorsalis dorsalis and Puritan tiger beetle Cicindela puritana are both listed as threatened under the Endangered Species Act of 1973, while the white beach tiger beetle Cicindela dorsalis media is not listed but has been declining. Extirpation of these beetles, in some cases from entire states, has isolated many populations reducing gene flow and elevating the risk for the loss of genetic variation. To facilitate investigations of population genetic structure, we developed suites of microsatellite loci for conservation genetic studies.
Shotgun genomic sequencing of all species identified thousands of candidate microsatellite loci, among which 17 loci were optimized and verified to cross-amplify within C. d. media and C. d. dorsalis, and eight separate loci were optimized for C. puritana. Most loci conformed to Hardy–Weinberg equilibrium, showed no evidence of linkage disequilibrium or null alleles, and revealed population genetic characteristics informative for natural resource managers among the populations tested.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s13104-020-04985-8","usgsCitation":"Aunins, A.W., Eackles, M.S., Kazyak, D., Drummond, M., and King, T.L., 2020, Development of microsatellite markers for three at risk tiger beetles Cicindela dorsalis dorsalis, C. d. media, and C. puritana: BMC Research Notes, v. 13, no. 1, 171, 10 p., https://doi.org/10.1186/s13104-020-04985-8.","productDescription":"171, 10 p.","ipdsId":"IP-111048","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":457289,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13104-020-04985-8","text":"Publisher Index Page"},{"id":376950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eackles, Michael S. 0000-0001-5624-5769 meackles@usgs.gov","orcid":"https://orcid.org/0000-0001-5624-5769","contributorId":218936,"corporation":false,"usgs":true,"family":"Eackles","given":"Michael","email":"meackles@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drummond, Michael","contributorId":236902,"corporation":false,"usgs":false,"family":"Drummond","given":"Michael","email":"","affiliations":[],"preferred":false,"id":794652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794653,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221059,"text":"70221059 - 2020 - Characterization of feed coals and coal combustion byproducts from the Wyodak-Anderson coal zone, Powder River Basin, Wyoming","interactions":[],"lastModifiedDate":"2021-06-01T16:19:05.452779","indexId":"70221059","displayToPublicDate":"2020-03-20T11:15:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of feed coals and coal combustion byproducts from the Wyodak-Anderson coal zone, Powder River Basin, Wyoming","docAbstract":"The U.S. Geological Survey (USGS) determined the physical and chemical properties of more than 260 feed coal and coal combustion byproducts from two coal-fired power plants. These plants utilized a low-sulfur (0.23-0.47 wt. % S) and low ash (4.9-6.3 wt. % ash) subbituminous coal from the Wyodak-Anderson coal zone in the Tongue River Member of the Paleocene Fort Union Formation, Powder River Basin, Wyoming. Fifty-three samples of bituminous coal were collected and analyzed from a Kentucky power plant, which used several sources of bituminous coals from the Appalachian and Illinois Basins.
Based on scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses of feed coal samples collected and analyzed from 1996 through the late 2000s, two mineral suites were identified: (1) a primary or detrital suite consisting of quartz (including beta-form grains), biotite, feldspar, and minor zircon; and (2) a secondary authigenic mineral suite containing alumino-phosphates (crandallite and gorceixite), kaolinite, carbonates (calcite and dolomite), quartz, anatase, barite, and pyrite. The detrital mineral suite is interpreted, in part, to be of volcanic origin, whereas the authigenic mineral suite is interpreted, in part, to be the result of the alteration of the volcanic minerals. The mineral suites have contributed to the higher amounts of barium, calcium, magnesium, phosphorus, sodium, strontium, and titanium in the Powder River Basin feed coals in comparison to eastern US coals.
XRD analysis indicates that (1) fly ash is mostly aluminate glass, perovskite, lime, gehlenite, quartz, and phosphates with minor amounts of periclase, anhydrite, hematite, and spinel group minerals; and (2) bottom ash is predominantly quartz, plagioclase (albite and anorthite), pyroxene (augite and fassaite), rhodonite, and akermanite, and spinel group minerals. Microprobe and SEM analyses of fly ash samples revealed quartz, zircon, and monazite, euhedral laths of corundum with merrillite, hematite, dendritic spinels/ferrites, wollastonite, and periclase. The abundant calcium and magnesium mineral phases in the fly ash are attributed to the alteration of carbonate, clay, and phosphate minerals in the feed coal during combustion.
The calcium- and magnesium-rich and alumino-phosphate mineral phases in the coal combustion byproducts can be attributed to volcanic minerals deposited in peat-forming mires. Dissolution and alteration of these detrital volcanic minerals occurred either in the peat-forming stage or during coalification and diagenesis, resulting in the authigenic mineral suite.
The presence of free lime (CaO) in fly ash produced from Wyodak-Anderson coal acts as a self-contained “scrubber” for SO3, where CaO + SO3 form anhydrite either during combustion or in the upper parts of the boiler. Considering the high lime content in the fly ash and the resulting hydration reactions after its contact with water, there is little evidence that major amounts of leachable metals are mobilized in the disposal or utilization of this fly ash.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.31582/rmag.mg.57.3.199","usgsCitation":"Brownfield, M.E., 2020, Characterization of feed coals and coal combustion byproducts from the Wyodak-Anderson coal zone, Powder River Basin, Wyoming: Mountain Geologist, v. 57, no. 3, p. 199-240, https://doi.org/10.31582/rmag.mg.57.3.199.","productDescription":"42 p.","startPage":"199","endPage":"240","ipdsId":"IP-112921","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":386034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","county":"Campbell County","otherGeospatial":"Powder River basin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-105.0874,45.0001],[-105.0855,44.9688],[-105.0861,44.8811],[-105.0764,44.8818],[-105.0773,44.8014],[-105.0773,44.7868],[-105.0863,44.787],[-105.0869,44.7574],[-105.0869,44.7277],[-105.0869,44.699],[-105.0863,44.6533],[-105.0869,44.6387],[-105.0861,44.6118],[-105.0859,44.5283],[-105.0853,44.5118],[-105.0853,44.4977],[-105.086,44.4826],[-105.0817,44.1793],[-105.076,44.1791],[-105.0776,44.1409],[-105.0776,44.1263],[-105.0804,44.0033],[-105.0842,44.0029],[-105.0849,43.9414],[-105.0849,43.9268],[-105.0848,43.9154],[-105.0851,43.8936],[-105.0848,43.8411],[-105.0847,43.8275],[-105.0809,43.8269],[-105.0821,43.7395],[-105.0821,43.7103],[-105.0821,43.6807],[-105.0822,43.6652],[-105.0821,43.6511],[-105.0822,43.6356],[-105.0821,43.6211],[-105.082,43.5942],[-105.082,43.5646],[-105.082,43.55],[-105.082,43.5341],[-105.082,43.5195],[-105.0817,43.4981],[-105.242,43.4984],[-105.2616,43.4979],[-105.2818,43.4978],[-105.302,43.4978],[-105.3216,43.4977],[-105.3418,43.4981],[-105.362,43.4981],[-105.4018,43.498],[-105.5028,43.4977],[-105.5236,43.4976],[-105.6833,43.4973],[-106.0204,43.4946],[-106.0197,43.7619],[-106.0198,43.822],[-106.0084,43.8223],[-106.0082,43.8501],[-106.0084,43.8647],[-106.008,43.8792],[-106.0082,43.8938],[-106.0078,43.9958],[-106.0076,44.0227],[-106.0078,44.0373],[-106.008,44.0524],[-106.0082,44.0665],[-106.0078,44.082],[-106.0087,44.0961],[-106.0089,44.1107],[-106.0091,44.1253],[-106.0093,44.1403],[-106.0095,44.1545],[-106.0097,44.1695],[-106.0199,44.1697],[-106.0204,44.1966],[-106.0206,44.2112],[-106.0208,44.2257],[-106.0218,44.2996],[-106.0203,44.3748],[-106.0205,44.3894],[-106.0207,44.404],[-106.0203,44.4191],[-106.0194,44.4478],[-106.0196,44.4642],[-106.0198,44.4783],[-106.02,44.4934],[-106.0203,44.5066],[-106.0205,44.5208],[-106.0115,44.5211],[-106.0115,44.5653],[-106.0078,44.8423],[-106.0076,44.8715],[-106.0166,44.8716],[-106.0164,44.8999],[-106.0171,44.9437],[-106.0165,44.962],[-106.0168,44.9968],[-106.0007,44.9967],[-105.9331,44.9973],[-105.9226,45.0007],[-105.9196,45.0017],[-105.897,45.0017],[-105.7601,45.0016],[-105.6974,45.0017],[-105.694,45.0016],[-105.6768,45.0016],[-105.5876,45.0013],[-105.2874,45.0009],[-105.2834,45.0009],[-105.2674,45.0009],[-105.2468,45.0009],[-105.2381,45.0009],[-105.2268,45.0009],[-105.0874,45.0001]]]},\"properties\":{\"name\":\"Campbell\",\"state\":\"WY\"}}]}","volume":"57","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":816670,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70228430,"text":"70228430 - 2020 - Electrofishing encounter probability, survival, and dispersal of stocked age-0 Muskellunge in Wisconsin lakes","interactions":[],"lastModifiedDate":"2022-02-10T15:05:58.812086","indexId":"70228430","displayToPublicDate":"2020-03-20T08:58:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Electrofishing encounter probability, survival, and dispersal of stocked age-0 Muskellunge in Wisconsin lakes","docAbstract":"Boat electrofishing is often used to sample age-0 Muskellunge Esox masquinongy for indexing recruitment or evaluating stocking success. However, electrofishing samples typically result in low CPUE, prompting concerns regarding whether catch rates reflect actual abundance or whether boat electrofishing is generally ineffective for capturing age-0 Muskellunge (i.e., if fish are not being encountered by the gear). To address these concerns, we used radiotelemetry to evaluate the probability of encountering stocked age-0 Muskellunge (230–350 mm TL) during standardized fall electrofishing surveys in three Wisconsin lakes. Our approach also allowed us to evaluate short-term survival and dispersal from stocking locations. Despite limited dispersal (<2.5 km) from the stocking locations and relatively high short-term survival (75–94%) of radio-tagged fish, few age-0 Muskellunge were located within the path of the electrofishing boat (7–30%). Furthermore, the probability of encounter by boat electrofishing varied by as much as 6.3 times among lakes. Differences in encounter probability among lakes appeared to be related to lake basin and habitat characteristics. Overlays of electrofishing sampling effort and fish locations revealed that traditional shoreline electrofishing may not be an effective way of estimating age-0 Muskellunge CPUE. Modifications to electrofishing protocols, including increased effort in offshore areas and consideration of basin characteristics and habitat, may be needed to increase encounter probabilities and the utility of boat electrofishing for sampling age-0 Muskellunge.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10418","usgsCitation":"Dembkowski, D., Kerns, J.A., Easterly, E.G., and Isermann, D.A., 2020, Electrofishing encounter probability, survival, and dispersal of stocked age-0 Muskellunge in Wisconsin lakes: North American Journal of Fisheries Management, v. 40, no. 2, p. 383-393, https://doi.org/10.1002/nafm.10418.","productDescription":"11 p.","startPage":"383","endPage":"393","ipdsId":"IP-111289","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Stella Lake, Twin Valley Lake, Upper Gresham Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.21207427978516,\n 45.70557989372282\n ],\n [\n -89.17963027954102,\n 45.70557989372282\n ],\n [\n -89.17963027954102,\n 45.72236042939562\n ],\n [\n -89.21207427978516,\n 45.72236042939562\n ],\n [\n -89.21207427978516,\n 45.70557989372282\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.75199222564697,\n 46.06087385306044\n ],\n [\n -89.723,\n 46.06087385306044\n ],\n [\n -89.723,\n 46.07721993221842\n ],\n [\n -89.75199222564697,\n 46.07721993221842\n ],\n [\n -89.75199222564697,\n 46.06087385306044\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.10273933410645,\n 43.01569327500512\n ],\n [\n -90.08136749267578,\n 43.01569327500512\n ],\n [\n -90.08136749267578,\n 43.03708953184211\n ],\n [\n -90.10273933410645,\n 43.03708953184211\n ],\n [\n -90.10273933410645,\n 43.01569327500512\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Dembkowski, Daniel J.","contributorId":275781,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":834283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kerns, Janice A.","contributorId":275782,"corporation":false,"usgs":false,"family":"Kerns","given":"Janice","email":"","middleInitial":"A.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":834284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Easterly, Emma G.","contributorId":275785,"corporation":false,"usgs":false,"family":"Easterly","given":"Emma","email":"","middleInitial":"G.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":834285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834282,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208050,"text":"sim3447 - 2020 - Geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico","interactions":[],"lastModifiedDate":"2022-04-22T20:02:50.44033","indexId":"sim3447","displayToPublicDate":"2020-03-19T13:23:38","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3447","displayTitle":"Geologic Map of Petroglyph National Monument and Vicinity, Bernalillo County, New Mexico","title":"Geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico","docAbstract":"This geologic map depicts and briefly describes geologic units underlying Petroglyph National Monument and immediately adjacent areas in Bernalillo County, New Mexico. The Monument is underlain dominantly by Quaternary basalts of the Albuquerque Volcanoes volcanic field, a series of basin-filling volcanic flows and associated vents from a monogenetic volcanic highland along the eastern margin of the Llano de Albuquerque. This compilation builds on data of previously published geologic maps and reports but includes new interpretive synthesis of volcanic stratigraphy and a unified representation of Quaternary surficial deposits overlying volcanic deposits within the Monument and areas immediately adjacent. This geologic map emphasizes the distribution of Quaternary volcanic vent areas and lava flow deposits which were incompletely mapped on previous publications. Surficial deposits are simplified, but uniformly mapped and described in contrast to varying map unit distributions, names and descriptions presented in the references above. Underlying deposits of the upper Santa Fe Group are exposed in the western part of the map area and described briefly.
North-trending, syn- and post-eruption faulting is well preserved in the volcanic field and reflected in the subsurface models of aeromagnetic data. These faults are dominated by dip-slip displacement and are interpreted as extensional faults of the central Albuquerque Basin of the northern Rio Grande rift. Elongate distribution of vents for most of the volcanic deposits are spatially associated with the easternmost of these faults and are interpreted to reflect eruptions from fissures paralleling the regional extensional fault trends of the rift.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3447","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Thompson, R.A., Chan, C.F., Gilmer, A.K., and Shroba, R.R., 2020, Geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico: U.S. Geological Survey Scientific Investigations Map 3447, scale 1:24,000, https://doi.org/10.3133/sim3447.","productDescription":"2 Sheets: 50.50 inches x 40.00 inches; Data Release; ReadMe","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102605","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":373216,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LW817K","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Release for Geologic Map of Petroglyph National Monument and Vicinity, Bernalillo County, New Mexico"},{"id":373215,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3447/sim3447_georeferenced.pdf","text":"Sheet—Georeferenced geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3447"},{"id":399520,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109803.htm"},{"id":373213,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3447/coverthb.jpg"},{"id":373222,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3447/ReadMe.txt","text":"Read Me","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3447 Read Me"},{"id":373214,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3447/sim3447.pdf","text":"Sheet—Geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3447"}],"scale":"24000","country":"United States","state":"New Mexico","county":"Bernalillo County","otherGeospatial":"Petroglyph National Monument and vicinity","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.79946899414062,\n 35.097439809364204\n ],\n [\n -106.68823242187499,\n 35.097439809364204\n ],\n [\n -106.68823242187499,\n 35.188961188789925\n ],\n [\n -106.79946899414062,\n 35.188961188789925\n ],\n [\n -106.79946899414062,\n 35.097439809364204\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, Mail Stop 980
Denver, CO 80225
The U.S. Pacific Northwest has a history of frequent and occasionally deadly landslides caused by various factors. Using a multivariate, machine-learning approach, we combined a Pacific Northwest Landslide Inventory with a 36-year gridded hydrologic dataset from the National Climate Assessment – Land Data Assimilation System to produce a landslide hazard indicator (LHI) on a daily 0.125-degree grid. The LHI identified where and when landslides were most probable over the years 1979–2016, addressing issues of bias and completeness that muddy the analysis of multi-decadal landslide inventories. The seasonal cycle was strong along the west coast, with a peak in the winter, but weaker east of the Cascade Range. This lagging indicator can fill gaps in the observational record to identify the seasonality of landslides over a large spatiotemporal domain and show how landslide hazard has responded to a changing climate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2020.104692","usgsCitation":"Stanley, T.A., Kirschbaum, D.B., Sobieszczyk, S., Jasinski, M.F., Borak, J.S., and Slaughter, S.L., 2020, Building a landslide hazard indicator with machine learning and land surface models: Environmental Modelling & Software, v. 129, 104692, 15 p., https://doi.org/10.1016/j.envsoft.2020.104692.","productDescription":"104692, 15 p.","ipdsId":"IP-114297","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":457392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2020.104692","text":"Publisher Index Page"},{"id":410787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, 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