Premise of the Study
Astragalus sect. Humillimi is distributed across the southwestern United States and contains two endangered taxa, A. cremnophylax var. cremnophylax and A. humillimus. The former was originally described from the South Rim of the Grand Canyon. Analysis of individuals discovered on the North Rim of the Grand Canyon yielded some evidence that the population represented a distinct species. To enable effective conservation, we clarify the group's taxonomy and characterize the genetic diversity of A. cremnophylax and A. humillimus.
Methods
We used AFLPs to genotype most species in sect. Humillimi, focusing on the two endangered forms. We examined patterns of genetic diversity using complementary analytical approaches.
Key Results
Our results demonstrate that North Rim populations group with A. c. var. cremnophylax. We found low levels of genetic diversity at certain localities and strong differentiation among populations. Astragalus humillimus, which has suffered recent and severe population declines, exhibits weak differentiation among and low diversity within populations.
Conclusions
Our results clarify the taxonomy of sect. Humillimi and define the boundaries of A. c. var. cremnophylax, which is shown to inhabit both rims of the Grand Canyon. This clarification, and detailed analysis of genetic variation within both endangered taxa, may advance ongoing efforts to conserve these taxa. Our results suggest that range‐wide genetic analysis of A. humillimus may inform recovery strategies for this taxon.
In river valleys, sediment moves between active river channels, near-channel deposits including bars and floodplains, and upland environments such as terraces and aeolian dunefields. Sediment availability is a prerequisite for the sustained transfer of material between these areas, and for the eco-geomorphic functioning of river networks in general. However, the difficulty of monitoring sediment availability and movement at the reach or corridor scale has hindered our ability to quantify and forecast the response of sediment transfer to hydrologic or land cover alterations. Here we leverage spatiotemporally extensive datasets quantifying sediment areal coverage along a 28 km reach of the Colorado River in Grand Canyon, southwestern USA. In concert with information on hydrologic alteration and vegetation encroachment resulting from the operation of Glen Canyon Dam (constructed in 1963) upstream of our study reach, we model the relative and combined influence of changes in (a) flow and (b) riparian vegetation extent on the areal extent of sediment available for transport in the river valley over the period from 1921 to 2016. In addition, we use projections of future streamflow and vegetation encroachment to forecast sediment availability over the 20 year period from 2016 to 2036. We find that hydrologic alteration has reduced the areal extent of bare sediment by 9% from the pre- to post-dam periods, whereas vegetation encroachment further reduced bare sediment extent by 45%. Over the next 20 years, the extent of bare sediment is forecast to be reduced by an additional 12%. Our results demonstrate the impact of river regulation, specifically the loss of annual low flows and associated vegetation encroachment, on reducing the sediment available for transfer within river valleys. This work provides an extendable framework for using high-resolution data on streamflow and land cover to assess and forecast the impact of watershed perturbation (e.g. river regulation, land cover shifts, climate change) on sediment connectivity at the corridor scale.
","language":"English","publisher":"SAGE Publishing","doi":"10.1177/0309133318795846","usgsCitation":"Kasprak, A., Sankey, J.B., Buscombe, D.D., Caster, J., East, A.E., and Grams, P.E., 2018, Quantifying and forecasting changes in the areal extent of river valley sediment in response to altered hydrology and land cover: Progress in Physical Geography: Earth and Environment, v. 42, no. 6, p. 739-764, https://doi.org/10.1177/0309133318795846.","productDescription":"26 p.","startPage":"739","endPage":"764","ipdsId":"IP-088947","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468374,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/0309133318795846","text":"Publisher Index Page"},{"id":437745,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SX3MGY","text":"USGS data release","linkHelpText":"River Valley Sediment Connectivity Data, Colorado River, Grand Canyon"},{"id":357659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park, Lower Marble Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.93145751953125,\n 36.16781389727332\n ],\n [\n -111.77352905273438,\n 36.16781389727332\n ],\n [\n -111.77352905273438,\n 36.4223874864237\n ],\n [\n -111.93145751953125,\n 36.4223874864237\n ],\n [\n -111.93145751953125,\n 36.16781389727332\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-13","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538d3","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":204162,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":745885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":745886,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745887,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70212475,"text":"70212475 - 2018 - A new Enceladus global control network, image mosaic, and updated pointing kernels from Cassini's thirteen-year mission","interactions":[],"lastModifiedDate":"2020-08-18T13:45:37.871805","indexId":"70212475","displayToPublicDate":"2018-09-24T09:06:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"A new Enceladus global control network, image mosaic, and updated pointing kernels from Cassini's thirteen-year mission","docAbstract":"NASA's Cassini spacecraft spent 13 years exploring the Saturn system, including 23 targeted flybys of the small, geologically active moon Enceladus. These flybys provided a wealth of image data from Cassini's Imaging Science Subsystem. To improve the usability of the Enceladus data set, we created a new, global photogrammetric control network for Enceladus that enabled compilation of a versatile cartographic package to support geologic mapping and other investigations. The network used 586 images in four image filters with a pixel scale generally between 50 and 500 m per pixel and a phase angle less than 120° and consisted of 10,362 tie points and 173,704 individual image measures, averaging nearly 17 measures per tie point. Least squares bundle adjustment resulted in a root‐mean‐square residual of 0.45 pixel, corresponding to root‐mean‐square ground point uncertainties of 66, 51, and 46 m in latitude, longitude, and radius, respectively. Using our geodetic control network, we created new global image mosaics, coregistered flyby mosaics to support geologic mapping, and updated pointing kernels for every image used in the solution. These products, including the updated pointing kernels, are available to the community through NASA's Planetary Data System Imaging Annex. The bundle adjustment solution also yielded independently determined shape information, resulting in radii within the stated uncertainty of International Astronomical Union values. The challenges of the data set, and the technical methodology described here are applicable to bodies imaged during multiple flybys with variable viewing and illumination geometry, including other midsized satellites of Saturn, and the Europa Clipper mission.
Water use in the State of Washington has evolved during the past century from small withdrawals used for domestic and stock needs to the diverse needs of current public supply systems, domestic water users, irrigation projects, industrial plants, and aquaculture industries. Increasing demand for water makes the accountability of water use an important issue.
A few State and local agencies in Washington collect water-use information for specific categories of water use; currently, only the U.S. Geological Survey (USGS) compiles cumulative water-use information across the State for a comprehensive range of uses.
Since 1950, on a 5-year cycle, the USGS has compiled and published estimates of water withdrawal and use for specific categories aggregated at the county, State, and national level. The information is shared publicly through the USGS Water Use in the United States website (https://water.usgs.gov/watuse/) and national publications that detail water use definitions, categories, trends, and data for every state. The data are compiled individually by each state from available sources, and are augmented by estimates from national models for categories that have limited data. The USGS Washington Water Science Center is responsible for compiling their estimates and maintains the State water use webpage (https://wa.water.usgs.gov/data/wuse/) of State-level information and links to the national program.
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\"}}]}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The 2018 census of southern sea otters (Enhydra lutris nereis) was conducted from late April to mid-May along the mainland coast of central California and in April at San Nicolas Island in southern California. The 3-year average of combined counts from the mainland range and San Nicolas Island was 3,128, a decrease of 58 sea otters from the previous year. The 5-year average trend in abundance, including both the mainland range and San Nicolas Island populations, remains positive at 1.3 percent per year. Continuing lack of growth in the range peripheries likely explains the cessation of range expansion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1097","usgsCitation":"Hatfield, B.B., Yee, J.L., Kenner, M.C., Tomoleoni, J.A., and Tinker, M.T., 2018, California sea otter (Enhydra lutris nereis) census results, spring 2018: U.S. Geological Survey Data Series 1097, 10 p., https://doi.org/10.3133/ds1097.","productDescription":"Report: iv, 10 p.; Data release","onlineOnly":"Y","ipdsId":"IP-101451","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":357646,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98012HE","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Annual California sea otter census—2018 spring census summary"},{"id":357644,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1097/coverthb.jpg"},{"id":357645,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1097/ds1097.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1097"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 33\n ],\n [\n -119,\n 33\n ],\n [\n -119,\n 37.2009909007\n ],\n [\n -123,\n 37.2009909007\n ],\n [\n -123,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
Modoc Hall, Room 4004
Sacramento, California 95819
We tested the use of high‐resolution infrared (IR) camera technology and distance sampling analyses to estimate abundance of feral horses (Equus caballus) during 2015–2016 in the McCullough Peaks Herd Management Area, Wyoming, USA. Infrared technology is becoming more common in ungulate population monitoring. The quality of IR cameras now allows ungulate species to be differentiated. Imperfect detection is a common problem in aerial surveys, so we tested the use of distance sampling analyses to account for imperfect detection probability. We conducted 2 aerial surveys in a sagebrush ecosystem with a demographically closed horse population. True abundance was known to within ±4 animals as a result of intensive, ground‐based monitoring of each animal, all of which are uniquely identifiable. After truncation of our data, the most supported detection function was a uniform function with a detection probability equal to 1.0 out to 255 m. Our analyses yielded results that were within 10% of true abundance, but the coefficient of variation (CV) was large (36–58%) assuming a small sampling fraction. However, our truncated surveys covered approximately 95% of the herd management area. By including a finite population correction factor in our calculations of variance estimates, CVs (8–13%) were dramatically reduced. We found the combination of IR surveys and distance sampling analysis to be a useful method to estimate feral horse abundance in sagebrush vegetation type, which had limited cover to obscure horses. Repeated testing in sagebrush ecosystems as well as further testing in other habitat types and under differing conditions will inform how general our approach can be.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.912","usgsCitation":"Schoenecker, K.A., Doherty, P., Hourt, J., and Romero, J., 2018, Testing infrared camera surveys and distance analyses to estimate feral horse abundance in a known population: Wildlife Society Bulletin, v. 42, no. 3, p. 452-459, https://doi.org/10.1002/wsb.912.","productDescription":"8 p.","startPage":"452","endPage":"459","ipdsId":"IP-085078","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468376,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/fcd332e3ab024f1d9ae4580186a01eee","text":"Publisher Index Page"},{"id":373552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"McCullough Peaks Herd Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.8416,\n 44.3333\n ],\n [\n -108.5083,\n 44.3333\n ],\n [\n -108.5083,\n 44.8333\n ],\n [\n -108.8416,\n 44.8333\n ],\n [\n -108.8416,\n 44.3333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X schoeneckerk@usgs.gov","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":2001,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn","email":"schoeneckerk@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doherty, Paul","contributorId":223632,"corporation":false,"usgs":false,"family":"Doherty","given":"Paul","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":785660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hourt, Jacob","contributorId":223633,"corporation":false,"usgs":false,"family":"Hourt","given":"Jacob","email":"","affiliations":[{"id":40752,"text":"Owyhee Air Research","active":true,"usgs":false}],"preferred":false,"id":785661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Romero, John","contributorId":223634,"corporation":false,"usgs":false,"family":"Romero","given":"John","affiliations":[{"id":40752,"text":"Owyhee Air Research","active":true,"usgs":false}],"preferred":false,"id":785662,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199616,"text":"70199616 - 2018 - Assessing the impact of site-specific BMPs using a spatially explicit, field-scale SWAT model with edge-of-field and tile hydrology and water-quality data in the Eagle Creek watershed, Ohio","interactions":[],"lastModifiedDate":"2018-09-24T11:21:25","indexId":"70199616","displayToPublicDate":"2018-09-21T11:21:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the impact of site-specific BMPs using a spatially explicit, field-scale SWAT model with edge-of-field and tile hydrology and water-quality data in the Eagle Creek watershed, Ohio","docAbstract":"The Eagle Creek watershed, a small subbasin (125 km2) within the Maumee River Basin, Ohio, was selected as a part of the Great Lakes Restoration Initiative (GLRI) “Priority Watersheds” program to evaluate the effectiveness of agricultural Best Management Practices (BMPs) funded through GLRI at the field and watershed scales. The location and quantity of BMPs were obtained from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) database. A Soil and Water Assessment Tool (SWAT) model was built and calibrated for this predominantly agricultural Eagle Creek watershed, incorporating NCP BMPs and monitoring data at the watershed outlet, an edge-of-field (EOF), and tile monitoring sites. Input air temperature modifications were required to induce simulated tile flow to match monitoring data. Calibration heavily incorporated tile monitoring data to correctly proportion surface and subsurface flow, but calibration statistics were unsatisfactory at the EOF and tile monitoring sites. At the watershed outlet, satisfactory to very good calibration statistics were achieved over a 2-year calibration period, and satisfactory statistics were found in the 2-year validation period. SWAT fixes parameters controlling nutrients primarily at the watershed level; a refinement of these parameters at a smaller-scale could improve field-level calibration. Field-scale modeling results indicate that filter strips (FS) are the most effective single BMPs at reducing dissolved reactive phosphorus, and FS typically decreased sediment and nutrient yields when added to any other BMP or BMP combination. Cover crops were the most effective single, in-field practice by reducing nutrient loads over winter months. Watershed-scale results indicate BMPs can reduce sediment and nutrients, but reductions due to NCP BMPs in the Eagle Creek watershed for all water-quality constituents were less than 10%. Hypothetical scenarios simulated with increased BMP acreages indicate larger investments of the appropriate BMP or BMP combination can decrease watershed level loads.
","language":"English","publisher":"MDPI","doi":"10.3390/w10101299","usgsCitation":"Merriman, K.R., Daggupati, P., Srinivasan, R., Toussant, C., Russell, A.M., and Hayhurst, B.A., 2018, Assessing the impact of site-specific BMPs using a spatially explicit, field-scale SWAT model with edge-of-field and tile hydrology and water-quality data in the Eagle Creek watershed, Ohio: Water, v. 10, no. 10, p. 1-37, https://doi.org/10.3390/w10101299.","productDescription":"Article 1299; 37 p.","startPage":"1","endPage":"37","ipdsId":"IP-092960","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468377,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10101299","text":"Publisher Index Page"},{"id":357665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Eagle Creek Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.8333,\n 40.67\n ],\n [\n -83.5,\n 40.67\n ],\n [\n -83.5,\n 41\n ],\n [\n -83.8333,\n 41\n ],\n [\n -83.8333,\n 40.67\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-21","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538d9","contributors":{"authors":[{"text":"Merriman, Katherine R. 0000-0002-1303-2410 kmerriman@usgs.gov","orcid":"https://orcid.org/0000-0002-1303-2410","contributorId":4973,"corporation":false,"usgs":true,"family":"Merriman","given":"Katherine","email":"kmerriman@usgs.gov","middleInitial":"R.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":745973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daggupati, Prasad","contributorId":203354,"corporation":false,"usgs":false,"family":"Daggupati","given":"Prasad","affiliations":[{"id":36214,"text":"Univeristy of Guelph","active":true,"usgs":false}],"preferred":false,"id":745974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Srinivasan, Raghavan","contributorId":203355,"corporation":false,"usgs":false,"family":"Srinivasan","given":"Raghavan","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":745975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Toussant, Chad","contributorId":208117,"corporation":false,"usgs":true,"family":"Toussant","given":"Chad","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Amy M. 0000-0003-0582-0094 arussell@usgs.gov","orcid":"https://orcid.org/0000-0003-0582-0094","contributorId":200011,"corporation":false,"usgs":true,"family":"Russell","given":"Amy","email":"arussell@usgs.gov","middleInitial":"M.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayhurst, Brett A. 0000-0002-1717-2015 bhayhurs@usgs.gov","orcid":"https://orcid.org/0000-0002-1717-2015","contributorId":3398,"corporation":false,"usgs":true,"family":"Hayhurst","given":"Brett","email":"bhayhurs@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745978,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229790,"text":"70229790 - 2018 - Dynamic occupancy modeling of temperate marine fish in area-based closures","interactions":[],"lastModifiedDate":"2022-03-17T15:46:42.731317","indexId":"70229790","displayToPublicDate":"2018-09-21T10:38:02","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic occupancy modeling of temperate marine fish in area-based closures","docAbstract":"Species distribution models (SDMs) are commonly used to model the spatial structure of species in the marine environment, however, most fail to account for detectability of the target species. This can result in underestimates of occupancy, where nondetection is conflated with absence. The site occupancy model (SOM) overcomes this failure by treating occupancy as a latent variable of the model and incorporates a detection submodel to account for variability in detection rates. These have rarely been applied in the context of marine fish and never for the multiseason dynamic occupancy model (DOM). In this study, a DOM is developed for a designated species of concern, cusk (Brosme brosme), over a four-season period. Making novel use of a high-resolution 3-dimensional hydrodynamic model, detectability of cusk is considered as a function of current speed and algae cover. Algal cover on the seabed is measured from video surveys to divide the study area into two distinct regions: those with canopy forming species of algae and those without (henceforth bottom types). Modeled estimates of the proportion of sites occupied in each season are 0.88, 0.45, 0.74, and 0.83. These are significantly greater than the proportion of occupied sites measured from underwater video observations which are 0.57, 0.28, 0.43, and 0.57. Individual fish are detected more frequently with increasing current speed in areas lacking canopy and less frequently with increasing current speed in areas with canopy. The results indicate that, where possible, SDM studies for all marine species should take account of detectability to avoid underestimating the proportion of sites occupied at a given study area. Sampling closed areas or areas of conservation often requires the use of nonphysical, low impact sampling methods like camera surveys. These methods inherently result in detection probabilities less than one, an issue compounded by time-varying features of the environment that are rarely accounted for marine studies. This work highlights the use of modeled hydrodynamics as a tool to correct some of this imbalance.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4493","usgsCitation":"Calvert, J., McGonigle, C., Sethi, S., Harris, B., Quinn, R., and Grabowski, J., 2018, Dynamic occupancy modeling of temperate marine fish in area-based closures: Ecology and Evolution, v. 8, no. 20, p. 10192-10205, https://doi.org/10.1002/ece3.4493.","productDescription":"14 p.","startPage":"10192","endPage":"10205","ipdsId":"IP-127035","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468378,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4493","text":"Publisher Index Page"},{"id":397252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.983333,\n 43\n ],\n [\n -68.916667,\n 43\n ],\n [\n -68.916667,\n 42.88\n ],\n [\n -68.983333,\n 42.88\n ],\n [\n -68.983333,\n 43\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"20","noUsgsAuthors":false,"publicationDate":"2018-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Calvert, Jay","contributorId":288770,"corporation":false,"usgs":false,"family":"Calvert","given":"Jay","email":"","affiliations":[{"id":61838,"text":"University of Ulster","active":true,"usgs":false}],"preferred":false,"id":838269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGonigle, Chris","contributorId":288771,"corporation":false,"usgs":false,"family":"McGonigle","given":"Chris","email":"","affiliations":[{"id":61838,"text":"University of Ulster","active":true,"usgs":false}],"preferred":false,"id":838270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":838268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Bradley","contributorId":288772,"corporation":false,"usgs":false,"family":"Harris","given":"Bradley","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":838271,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quinn, Rory","contributorId":288773,"corporation":false,"usgs":false,"family":"Quinn","given":"Rory","email":"","affiliations":[{"id":61838,"text":"University of Ulster","active":true,"usgs":false}],"preferred":false,"id":838272,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grabowski, Jon","contributorId":288774,"corporation":false,"usgs":false,"family":"Grabowski","given":"Jon","email":"","affiliations":[{"id":61840,"text":"Northeaster University","active":true,"usgs":false}],"preferred":false,"id":838273,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223491,"text":"70223491 - 2018 - Responses of unimpaired flows, storage, and managed flows to scenarios of climate change in the San Francisco Bay-Delta watershed","interactions":[],"lastModifiedDate":"2021-08-30T13:08:42.994302","indexId":"70223491","displayToPublicDate":"2018-09-21T08:06:37","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Responses of unimpaired flows, storage, and managed flows to scenarios of climate change in the San Francisco Bay-Delta watershed","docAbstract":"Projections of meteorology downscaled from global climate model runs were used to drive a model of unimpaired hydrology of the Sacramento/San Joaquin watershed, which in turn drove models of operational responses and managed flows. Twenty daily climate change scenarios for water years 1980–2099 were evaluated with the goal of producing inflow boundary conditions for a watershed sediment model and for a hydrodynamical model of the San Francisco Bay-Delta estuary. The resulting time series of meteorology, snowpack, unimpaired flow, reservoir storage, and managed flow were analyzed for century-scale trends. In the Sacramento basin, which dominates Bay-Delta inflows, all 20 scenarios portrayed warming trends (with a mean of 4.1 °C) and most had precipitation increases (with a mean increase of 9%). Sacramento basin snowpack water equivalent declined sharply (by 89%), which was associated with a major shift toward earlier unimpaired runoff timing (33% more flow arriving prior to 1 April). Sacramento basin reservoirs showed large declines in end-of-September storage. Water-year averaged outflows increased for most scenarios for both unimpaired and impaired flows, and frequency of extremely high daily unimpaired and impaired flows increased (increases of 175% and 170%, respectively). Managed Delta inflows were projected to experience large increases in the wet season and declines in the dry season. Changes in management strategy and infrastructure can mitigate some of these changes, though to what degree is uncertain.
Tectonic tremor can be used to constrain seismic‐wave attenuation for use in ground‐motion prediction equations (GMPEs) in regions where moderately sized earthquakes occur infrequently. Here we quantify seismic‐wave attenuation by inverting tremor ground motion amplitudes in different frequency bands of interest, to determine frequency dependence of and spatial variations in seismic‐wave attenuation in Cascadia. Due to the density of tremor data, we are able to resolve along‐strike variations in the attenuation parameter. We find that tectonic tremor exhibits the frequency dependence expected for attenuation, as determined from GMPEs developed from moderate‐to‐large magnitude earthquakes. This implies that attenuation along these paths is independent of the source mechanism. This study demonstrates that tectonic tremor can be used to provide insight into the physical factors responsible for attenuation, and to refine estimates of attenuation for ground‐motion prediction, thus having important implications for hazard assessment and engineering seismology.
","language":"English","publisher":"AGU","doi":"10.1029/2018GL079344","usgsCitation":"Littel, G.F., Thomas, A.M., and Baltay Sundstrom, A.S., 2018, Using tectonic tremor to constrain seismic‐wave attenuation in Cascadia: Geophysical Research Letters, v. 45, no. 18, p. 9579-9587, https://doi.org/10.1029/2018GL079344.","productDescription":"9 p.","startPage":"9579","endPage":"9587","ipdsId":"IP-101242","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gl079344","text":"Publisher Index Page"},{"id":357578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128,\n 39.5\n ],\n [\n -121,\n 39.5\n ],\n [\n -121,\n 50.5\n ],\n [\n -128,\n 50.5\n ],\n [\n -128,\n 39.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"18","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-27","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538db","contributors":{"authors":[{"text":"Littel, Geena F.","contributorId":208081,"corporation":false,"usgs":false,"family":"Littel","given":"Geena","email":"","middleInitial":"F.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":745834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Amanda M.","contributorId":200641,"corporation":false,"usgs":false,"family":"Thomas","given":"Amanda","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":745835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":745833,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199530,"text":"70199530 - 2018 - Compositional data analysis of coal combustion products with an application to a Wyoming power plant","interactions":[],"lastModifiedDate":"2018-09-20T15:40:17","indexId":"70199530","displayToPublicDate":"2018-09-20T15:40:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2701,"text":"Mathematical Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Compositional data analysis of coal combustion products with an application to a Wyoming power plant","docAbstract":"A mathematically sound approach for summarizing chemical analyses of feed coal and all its combustion products (bottom ash, economizer fly ash, and fly ash) is presented. The nature of the data requires the application of compositional techniques when conducting statistical analysis, techniques that have not been applied before to the study of partitioning of elements between the coal that enters the boiler and the associated coal combustion products. A collection of descriptive and inferential compositional techniques was used to analyze the coal combustion products from a Wyoming power plant burning Paleocene Wyodak–Anderson coal. The significance of the fluctuation in ash composition is determined by using a Hotelling’s T-squared test and bootstrapping. Tree displays allow for visualization of the progressive effect of filters in removal of chemical species based on their geochemical composition. Results indicate that, in general, as the suspended combustion products entrained in the flue gases move closer to the stack, chemical species are removed from the combustion gas, starting with minerals associated with elements having the lowest volatility.
","language":"English","publisher":"Springer","doi":"10.1007/s11004-018-9736-z","usgsCitation":"Martín-Fernández, J., Olea, R., and Ruppert, L.F., 2018, Compositional data analysis of coal combustion products with an application to a Wyoming power plant: Mathematical Geosciences, v. 50, no. 6, p. 639-657, https://doi.org/10.1007/s11004-018-9736-z.","productDescription":"19 p.","startPage":"639","endPage":"657","ipdsId":"IP-089735","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-03","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538dd","contributors":{"authors":[{"text":"Martín-Fernández, J. A.","contributorId":208080,"corporation":false,"usgs":false,"family":"Martín-Fernández","given":"J. A.","affiliations":[],"preferred":false,"id":745831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":26436,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruppert, Leslie F. 0000-0002-7453-1061 lruppert@usgs.gov","orcid":"https://orcid.org/0000-0002-7453-1061","contributorId":660,"corporation":false,"usgs":true,"family":"Ruppert","given":"Leslie","email":"lruppert@usgs.gov","middleInitial":"F.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":745832,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199535,"text":"70199535 - 2018 - The ecology of movement and behaviour: a saturated tripartite network for describing animal contacts","interactions":[],"lastModifiedDate":"2018-09-21T10:58:38","indexId":"70199535","displayToPublicDate":"2018-09-20T15:35:21","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The ecology of movement and behaviour: a saturated tripartite network for describing animal contacts","docAbstract":"Ecologists regularly use animal contact networks to describe interactions underlying pathogen transmission, gene flow, and information transfer. However, empirical descriptions of contact often overlook some features of individual movement, and decisions about what kind of network to use in a particular setting are commonly ad hoc. Here, we relate individual movement trajectories to contact networks through a tripartite network model of individual, space, and time nodes. Most networks used in animal contact studies (e.g. individual association networks, home range overlap networks, and spatial networks) are simplifications of this tripartite model. The tripartite structure can incorporate a broad suite of alternative ecological metrics like home range sizes and patch occupancy patterns into inferences about contact network metrics such as modularity and degree distribution. We demonstrate the model's utility with two simulation studies using alternative forms of ecological data to constrain the tripartite network's structure and inform expectations about the harder-to-measure metrics related to contact.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2018.0670","usgsCitation":"Manlove, K.R., Aiello, C.M., Sah, P., Cummins, B., Hudson, P.J., and Cross, P.C., 2018, The ecology of movement and behaviour: a saturated tripartite network for describing animal contacts: Proceedings of the Royal Society B: Biological Sciences, v. 285, no. 1887, https://doi.org/10.1098/rspb.2018.0670.","ipdsId":"IP-092136","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468381,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1098/rspb.2018.0670","text":"External Repository"},{"id":357568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"285","issue":"1887","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-19","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538df","contributors":{"authors":[{"text":"Manlove, Kezia R.","contributorId":198305,"corporation":false,"usgs":false,"family":"Manlove","given":"Kezia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":745807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aiello, Christina M. 0000-0002-2399-5464 caiello@usgs.gov","orcid":"https://orcid.org/0000-0002-2399-5464","contributorId":5617,"corporation":false,"usgs":true,"family":"Aiello","given":"Christina","email":"caiello@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":745808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sah, Pratha","contributorId":127768,"corporation":false,"usgs":false,"family":"Sah","given":"Pratha","email":"","affiliations":[{"id":7145,"text":"Department of Biology, Georgetown University, Washington DC","active":true,"usgs":false}],"preferred":false,"id":745809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cummins, Bree","contributorId":208072,"corporation":false,"usgs":false,"family":"Cummins","given":"Bree","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":745810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson, Peter J.","contributorId":204377,"corporation":false,"usgs":false,"family":"Hudson","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":745811,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":745806,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201121,"text":"70201121 - 2018 - Segmentation of Mississippi’s natural and artificial lakes","interactions":[],"lastModifiedDate":"2019-01-28T08:42:44","indexId":"70201121","displayToPublicDate":"2018-09-20T14:21:48","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Segmentation of Mississippi’s natural and artificial lakes","docAbstract":"Segmentations divide a diverse resource into groups, or segments, based on distinctive attributes that may respond similarly to management actions. A 4-way segmentation based on lake origin (natural or artificial) and size (small or large) was constructed for Mississippi lakes using a 30 yr data set. We aimed to document elements distinguishing these segments to understand relationships among them and to seek insight into lake management that may be apparent at the segment scale but not at the lake scale. Analyses pinpointed differences among the 4 segments relative to nutrient levels, fish assemblage composition, fishery characteristics, angler catch, and fishery management objectives. In general, most artificial lakes were eutrophic, varied widely relative to species composition depending on whether they impounded small or large rivers, their fish assemblages could be heavily influenced by stocking, provided principally centrarchid fisheries, and the management focus was on angler harvest. Most natural lakes were hypereutrophic, included higher species richness, provided a greater diversity of fisheries, and the management focus was on fish populations and habitat. Fishing success was similar across segments. The group-wise differences substantiate the segmentation and bring into focus a new level of concepts not typically relevant when considering lakes in isolation, such as issues about lake quantities, similarities, and geographical distributions. The segmentation represents the framework needed for considering lakes as parts of a larger and interactive management system.
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Discontinuity approaches remain a fruitful avenue of research in the quest for quantitative measures of resilience because discontinuity analysis provides an objective means of identifying scales in complex systems and facilitates delineation of hierarchical patterns in processes, structure, and resources. However, current discontinuity methods have been considered too subjective, too complicated and opaque, or have become computationally obsolete; given the ubiquity of discontinuities in ecological and other complex systems, a simple and transparent method for detection is needed. In this study, we present a method to detect discontinuities in census data based on resampling of a neutral model and provide the R code used to run the analyses. This method has the potential for advancing basic and applied ecological research.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4297","usgsCitation":"Barichievy, C., Angeler, D., Eason, T.N., Garmestani, A.S., Nash, K., Stow, C., Sundstrom, S., and Allen, C.R., 2018, A method to detect discontinuities in census data: Ecology and Evolution, v. 8, no. 19, p. 9614-9623, https://doi.org/10.1002/ece3.4297.","productDescription":"10 p.","startPage":"9614","endPage":"9623","ipdsId":"IP-098532","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468382,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4297","text":"Publisher Index Page"},{"id":378407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"19","noUsgsAuthors":false,"publicationDate":"2018-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Barichievy, C. 0000-0003-4088-953X","orcid":"https://orcid.org/0000-0003-4088-953X","contributorId":240685,"corporation":false,"usgs":false,"family":"Barichievy","given":"C.","affiliations":[{"id":13431,"text":"Zoological Society of London","active":true,"usgs":false}],"preferred":false,"id":798757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angeler, D. G.","contributorId":240686,"corporation":false,"usgs":false,"family":"Angeler","given":"D. G.","affiliations":[{"id":12665,"text":"University of Cape Town","active":true,"usgs":false}],"preferred":false,"id":798758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eason, T. N.","contributorId":205437,"corporation":false,"usgs":false,"family":"Eason","given":"T.","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":798759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garmestani, A. S.","contributorId":240687,"corporation":false,"usgs":false,"family":"Garmestani","given":"A.","email":"","middleInitial":"S.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":798760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nash, K.L. 0000-0003-0976-3197","orcid":"https://orcid.org/0000-0003-0976-3197","contributorId":240688,"corporation":false,"usgs":false,"family":"Nash","given":"K.L.","email":"","affiliations":[{"id":48132,"text":"Centre for Marine Socioecology","active":true,"usgs":false}],"preferred":false,"id":798761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stow, C.A.","contributorId":240689,"corporation":false,"usgs":false,"family":"Stow","given":"C.A.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":798762,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sundstrom, S.","contributorId":240690,"corporation":false,"usgs":false,"family":"Sundstrom","given":"S.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":798763,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":798764,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70198480,"text":"fs20183047 - 2018 - Assessment of undiscovered oil and gas resources in the Akita Basin Province, Japan, 2018","interactions":[],"lastModifiedDate":"2018-09-20T16:08:22","indexId":"fs20183047","displayToPublicDate":"2018-09-20T12:48:42","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3047","title":"Assessment of undiscovered oil and gas resources in the Akita Basin Province, Japan, 2018","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 111 million barrels of oil and 85 billion cubic feet of gas in the Akita Basin Province of Japan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183047","collaboration":"National and Global Petroleum Assessment","usgsCitation":"Schenk, C.J., Mercier, T.J., Tennyson, M.E., Woodall, C.A., Finn, T.M., Le, P.A., Marra, K.R., Gaswirth, S.B., Leathers-Miller, H.M., and Drake, R.M., II, 2018, Assessment of undiscovered oil and gas resources in the Akita Basin Province, Japan, 2018: U.S. Geological Survey Fact Sheet 2018–3047, 2 p., https://doi.org/10.3133/fs20183047.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-096722","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357506,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3047/coverthb2.jpg"},{"id":357507,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3047/fs20183047.pdf","text":"Report","size":"561 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3047"}],"country":"Japan","otherGeospatial":"Akita Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 138.5,\n 38.25\n ],\n [\n 141,\n 38.25\n ],\n [\n 141,\n 40.5\n ],\n [\n 138.5,\n 40.5\n ],\n [\n 138.5,\n 38.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS–939
Denver, CO 80225–0046
In 2006, the U.S. Geological Survey (USGS), in
cooperation with the Texas Department of Transportation,
began collecting annual and approximately quarterly series
peak-streamflow data at streamflow-gaging stations in smallto
medium-sized watersheds in central and western Texas
as part of a crest-stage gage (CSG) network, along with
selected flood-hydrograph data at a subset of these stations.
CSGs record the peak stage during storm events, which is
the maximum gage height (elevation of water surface above
a local vertical datum), at each CSG station. Established and
widely used indirect methods of peak streamflow estimation
and interpretation, such as culvert-flow, slope-area, and
flow-over-road methods, are used in conjunction with peak
gage height data to create the database of peak streamflow
described herein. The CSG network is focused on hydrology
of small- to medium-sized watersheds in central and western
Texas because additional streamflow data for this semiarid
to arid study area will eventually provide for more statistical
information and presumably reduced uncertainty in regional
regression equations or other regionalized statistical methods
for peak-streamflow frequency estimation at ungaged
locations. The database of annual and approximately quarterly
peak streamflow is published through USGS ScienceBase and
described in this report.
Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
Perchlorate (ClO4−) in groundwater can be from synthetic or natural sources. Natural sources include ClO4− associated with historical application of imported natural nitrate fertilizer from the Atacama Desert of Chile, and indigenous ClO4− that accumulates locally in arid regions from atmospheric deposition. The Rialto-Colton groundwater subbasin, 80 km east of Los Angeles, California, includes two mapped ClO4− plumes from known military/industrial sources. Larger areas downgradient from those plumes, and in the Chino subbasin to the southwest, also contain ClO4−. Perchlorate from wells was analyzed for chlorine and oxygen stable isotope ratios (δ37Cl, δ18O, Δ17O) and radioactive chlorine-36(36Cl) isotopic abundance, along with other geochemical, isotopic, and hydrogeologic data. Isotopic data show that synthetic ClO4− was the dominant source within the mapped plumes. Downgradient from the mapped plumes, and in the Chino subbasin, the dominant source of ClO4− was related to past agricultural use of Chilean (Atacama) nitrate fertilizer. The 36Cl and δ18O data indicate that wells having predominantly synthetic or Atacama ClO4− also contained small fractions of indigenous ClO4−. Little or no differences were observed in isotopic composition or ClO4− source with depth in depth-dependent data from selected wells. Indigenous ClO4− was most evident in upgradient wells having ClO4− concentrations <1 μg/L, consistent with its occurrence as a background constituent throughout the region. Stable isotope ratios of chlorine and oxygen and 36Cl isotopic abundance data provided relatively unambiguous discrimination of synthetic and Atacama sources in most wells having ClO4− concentrations greater than 1 μg/L.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2018.08.020","usgsCitation":"Hatzinger, P.B., Bohlke, J., Sturchio, N.C., Izbicki, J.A., and Teague, N.F., 2018, Four-dimensional isotopic approach to identify perchlorate sources in groundwater: Application to the Rialto-Colton and Chino subbasins, southern California (USA): Applied Geochemistry, v. 97, p. 213-225, https://doi.org/10.1016/j.apgeochem.2018.08.020.","productDescription":"13 p.","startPage":"213","endPage":"225","ipdsId":"IP-095009","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468383,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2018.08.020","text":"Publisher Index Page"},{"id":357543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Rialto-Colton and Chino subbasins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.5,\n 34.0333\n ],\n [\n -117.25,\n 34.0333\n ],\n [\n -117.25,\n 34.1833\n ],\n [\n -117.5,\n 34.1833\n ],\n [\n -117.5,\n 34.0333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"97","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f9ae4b0fc368eb538e5","contributors":{"authors":[{"text":"Hatzinger, Paul B.","contributorId":149376,"corporation":false,"usgs":false,"family":"Hatzinger","given":"Paul","email":"","middleInitial":"B.","affiliations":[{"id":17721,"text":"Shaw Environmental, Princeton, NJ","active":true,"usgs":false}],"preferred":false,"id":745394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":745393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sturchio, Neil C.","contributorId":149375,"corporation":false,"usgs":false,"family":"Sturchio","given":"Neil","email":"","middleInitial":"C.","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":745395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":152474,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","email":"jaizbick@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":745396,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teague, Nicholas F. 0000-0001-5289-1210 nteague@usgs.gov","orcid":"https://orcid.org/0000-0001-5289-1210","contributorId":2145,"corporation":false,"usgs":true,"family":"Teague","given":"Nicholas","email":"nteague@usgs.gov","middleInitial":"F.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745397,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198867,"text":"sir20185095 - 2018 - Geochemical conditions and nitrogen transport in nearshore groundwater and the subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts, 2013–14","interactions":[],"lastModifiedDate":"2018-09-20T11:10:08","indexId":"sir20185095","displayToPublicDate":"2018-09-20T09:00:00","publicationYear":"2018","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":"2018-5095","title":"Geochemical conditions and nitrogen transport in nearshore groundwater and the subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts, 2013–14","docAbstract":"Nitrogen transport and transformation were studied during 2013 to 2014 by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, in a subterranean estuary beneath onshore locations on the Seacoast Shores peninsula, a residential area in Falmouth, Massachusetts, served by septic systems and cesspools, and adjacent offshore locations in the Eel River, a saltwater embayment connected to the ocean. The field investigation included installation and sampling of clusters of wells and temporary sampling points near a transect extending from about 35 meters (m) onshore to 18 m offshore.
The fresh groundwater at the study site formed a lens about 11 m thick at the shoreline that was underlain by saline groundwater. Groundwater flow in the water-table aquifer was oriented northwestward toward the embayment. Nitrate concentrations in the fresh groundwater at a site about 35 m onshore increased in the downward direction from less than 500 micromoles per liter near the water table to about 1,700 micromoles per liter just above the freshwater/saltwater transition zone. Dissolved oxygen was largely absent in the onshore fresh groundwater. Distributions of salinity, dissolved oxygen, and nitrate at the shoreline and offshore generally were similar to those onshore; at some locations, however, shallow saline water was present above the freshwater, and there were scattered occurrences of elevated dissolved oxygen concentrations.
Geochemical indicators of nitrate reduction, including concentrations of the reaction product nitrogen gas, stable isotope ratios of nitrate and nitrogen gas, and changes in alkalinity, provided evidence for nitrate reduction in two zones separated vertically by a zone 7–8 m thick with no evidence of nitrate reduction. The shallow nitrate-reduction zone was near the water table in fresh groundwater onshore, where nitrate reduction may be related to particular recharge conditions at nearby sources. The shallow nitrate-reduction zone also may be related to an interval of fine-grained sediments at about the same altitude (−1 to −6 m relative to the National Geodetic Vertical Datum of 1929), where flow is slower and reactive electron donors such as solid organic carbon, iron, or sulfide phases may be present to drive the reduction. The deep nitrate-reduction zone was near the freshwater/saltwater transition zone, where nitrate reduction may be related to mixing of freshwater containing nitrate and saltwater containing dissolved organic carbon and ammonium, or to fine-grained sediments near the transition zone. The maximum amount of nitrate converted to nitrogen gas was estimated to be less than or equal to 300 micromoles per liter in both nitrate-reduction zones.
The presence of nitrate and low dissolved oxygen concentrations in the 7–8-meter-thick zone between the shallow and deep nitrate-reduction zones are conditions that could permit nitrate reduction. The absence of evidence of nitrate reduction in the high-nitrate zone may have resulted from the lack of reactive electron donors in that depth interval. The high-nitrate zone dissipated somewhat in the offshore direction, but the current study did not extend far enough to encompass the fresh groundwater discharge area or determine how much of the nitrate was removed prior to discharge.
A shallow intertidal saltwater cell was formed during a spring tide by saltwater infiltration during tidal run-up on the beach. Nitrate reduction might have occurred if nitrate-containing fresh groundwater discharging to the estuary mixed with the saltwater containing dissolved organic carbon in this zone, but samples collected from the intertidal saltwater cell during this study were not analyzed for indicators of nitrate reduction.
Elevated dissolved oxygen concentrations in fresh groundwater 9 m offshore may indicate that groundwater flow was partly oblique to the sampling transect or that groundwater from a regional flow system was converging under the river near the study area. Flow directions also may have been affected by aquifer heterogeneity such as the shallow fine-grained sediments onshore and at the bottom of the Eel River. Improved understanding of the fate of nitrate in this type of complex setting might be gained by including additional characterization of aquifer heterogeneity and groundwater flow and extending investigations of nitrate reduction to the shallow sediments in the intertidal saltwater cell and adjacent subtidal zone and to locations farther offshore beneath the estuary.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185095","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Office of Research and Development and Region 1 (New England)","usgsCitation":"Colman, J.A., LeBlanc, D.R., Böhlke, J.K., McCobb, T.D., Kroeger, K.D., Belaval, M., Cambareri, T.C., Pirolli, G.F., Brooks, T.W., Garren, M.E., Stover, T.B., and Keeley, A., 2018, Geochemical conditions and nitrogen transport in nearshore groundwater and the subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts, 2013–14: U.S. Geological Survey Scientific Investigations Report 2018–5095, 69 p., https://doi.org/10.3133/sir20185095.","productDescription":"ix, 69 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062996","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":357427,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RR1WF0 ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geochemical data supporting analysis of geochemical conditions and nitrogen transport in nearshore groundwater and the subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts, 2013"},{"id":437746,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RR1WF0","text":"USGS data release","linkHelpText":"Geochemical data supporting analysis of geochemical conditions and nitrogen transport in nearshore groundwater and the subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts"},{"id":356663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5095/coverthb.jpg"},{"id":357426,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5095/sir20185095.pdf","text":"Report","size":"32.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5095"}],"country":"United States","state":"Massachusetts","city":"East Falmouth","otherGeospatial":"Cape Cod Embayment","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.55076599121094,\n 41.56203190200195\n ],\n [\n -70.52553176879881,\n 41.56203190200195\n ],\n [\n -70.52553176879881,\n 41.580525125613846\n ],\n [\n -70.55076599121094,\n 41.580525125613846\n ],\n [\n -70.55076599121094,\n 41.56203190200195\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
For more than three decades, the U.S. Geological Survey (USGS) Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project has compiled paleoenvironmental data with the goal of reconstructing global conditions during the warm interval in the middle of the Piacenzian Age of the Pliocene Epoch (about 3.3 to 3.0 million years ago). Because this is the most recent interval of time in which climatic conditions were similar to those expected in the near future, a global reconstruction of conditions from this interval offers an imperfect yet useful representation of near future conditions. PRISM reconstructions have been used extensively as boundary conditions in general circulation model experiments aimed at better understanding Pliocene climate. They have also served as hindcasting targets when testing the ability of climate models to simulate real climates of the past, an exercise in estimating a model’s ability to accurately predict future climate. As data coverage has grown and model precision has improved, PRISM datasets have become important validation tools for pinpointing discrete areas of data-model disagreement and model-model disagreement. The Pliocene sea surface temperature (SST) dataset is the best developed component of the PRISM reconstructions and is the keystone of Pliocene paleoclimate research. For the first time, we compile all data related to PRISM SST estimation. This discussion chronicles the history of PRISM SST research as it evolved, responding to advances in paleochronology and paleotemperature estimation. Paleoclimatic considerations unique to each location are illustrated, as are any new developments since the initial publication of the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181148","usgsCitation":"Robinson, M.M., Dowsett, H.J., Foley, K.M., and Riesselman, C.R., 2018, PRISM marine sites—The history of PRISM sea surface temperature estimation: U.S. Geological Survey Open-File Report 2018–1148, 49 p., https://doi.org/10.3133/ofr20181148.","productDescription":"vi, 49 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087999","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":357306,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1148/ofr20181148.pdf","text":"Report","size":"1 MB","description":"OFR 2018-1148"},{"id":357305,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1148/coverthb3.jpg"}],"contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
926A National Center
Reston, VA 20192
In south-central Texas, the amount of streamflow in the Guadalupe River is a primary concern for local and downstream communities because of municipal, agricultural, wildlife, and recreational uses. Understanding the flow paths and rates of exchange between the surface water in the river and the groundwater in the underlying Carrizo-Wilcox aquifer is vital for understanding the water budget and streamflow variations. In areas where the Guadalupe River crosses the Carrizo-Wilcox aquifer outcrop, the surface-water and groundwater exchanges are not well characterized. Traditional methods to measure these interactions, such as measuring differences in surface-water flows at different locations to infer gains and losses between the locations, are not feasible along this stretch of the Guadalupe River because of upstream dams that cause large daily fluctuations in streamflow. Consequently, the U.S. Geological Survey, in cooperation with the Guadalupe-Blanco River Authority, applied geophysical methods in an exploratory study to identify reaches of the river where streamflow gains and losses (surface-water/groundwater exchanges) might be occurring.
Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Treated domestic septage can be used to irrigate agricultural fields as a disposal method or as a means to reuse water. Because traditional on-site treatment systems are not designed to remove wastewater indicators, hormones, sterols, antibiotics, and pharmaceuticals, land application of septage potentially results in soil contamination. Soils were collected and analyzed from four sites in a central Minnesota agricultural field irrigated with domestic septage. Soil samples were analyzed for 111 unique contaminants, including wastewater indicators, hormones, sterols, antibiotics, and pharmaceuticals. In total, 32 contaminants were detected in soil samples. Several wastewater indicators were detected in soil, including fragrances, alkylphenols, and flame-retardants, at concentrations ranging from 1 (2,6-dimethylnaphthalene at soil site 4) to 1,550 (β-sitosterol at soil site 1) micrograms per kilogram. Relative to the number of contaminants analyzed, steroid hormones had the most frequent detections in soil samples (33 percent), and androgens were more prevalent compared to estrogens (50 and 22 percent, respectively). Androgens and estrogens were detected at concentrations ranging from 0.21 (estrone at soil site 3) to 3.9 (dihydrotestosterone at soil site 1) micrograms per kilogram. Quantifiable concentrations of antibiotics and pharmaceuticals ranged from 1.4 (carbamazepine at soil site 1) to 540 (azithromycin at soil site 3) micrograms per kilogram. Two antibiotics, ciprofloxacin and ofloxacin, were detected at concentrations above the limit of quantification (greater than 1,000 micrograms per kilogram at soil sites 2 and 3). This pilot sampling indicates that soils may be a repository for some contaminants introduced to the environment through land application of domestic septage.
Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Mean random vitrinite reflectance (Ro) is the most widely accepted method to determine thermal maturity of coal and other sedimentary rocks. However, oil-immersion Ro of polished rock or kerogen samples is commonly lower than Ro values measured in samples from adjacent vitrinite-rich coals that have undergone the same level of thermal stress. So-called suppressed Ro values have also been observed in hydrous pyrolysis experiments designed to simulate petroleum formation. Various hypotheses to explain Ro suppression, such as sorption of products generated from liptinite during maturation, diagenetic formation of perhydrous vitrinite or overpressure, remain controversial. To experimentally test for suppression of vitrinite reflectance, artificial rock was prepared using silica and a calcined blend of limestone and clay with various proportions of thermally immature vitrinite-rich Wyodak-Anderson coal and liptinite-rich kerogen isolated from the oil-prone Parachute Creek Member of the Green River Formation. The samples were subjected to hydrous pyrolysis for 72 h. at isothermal temperatures of 300 °C, 330 °C, and 350 °C to simulate burial maturation. Compared to artificial rock that contains only coal, samples with different proportions of oil-prone kerogen show distinct suppression of calibrated Ro at 300 °C and 330 °C. The reflectance of solid bitumen generated during heating of the samples is lower than that of the associated vitrinite and does not interfere with the Ro measurements. These results provide the first experimental evidence that Ro suppression occurs in vitrinite mixed with liptinite-rich kerogen in a rock matrix. Although the precise chemical mechanism for Ro suppression by liptinite remains unclear, free radicals generated from solid bitumen and associated volatile products during maturation of liptinite may contribute to termination reactions that slow the aromatization and rearrangement of polyaromatic sheets in vitrinite, thus suppressing Ro. This mechanism does not preclude Ro suppression that might result from overpressure or differences in redox conditions during diagenesis.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2018.09.010","usgsCitation":"Peters, K.E., Hackley, P.C., Thomas, J., and Pomerantz, A.E., 2018, Suppression of vitrinite reflectance by bitumen generated from liptinite during hydrous pyrolysis of artificial source rock: Organic Geochemistry, v. 125, p. 220-228, https://doi.org/10.1016/j.orggeochem.2018.09.010.","productDescription":"9 p.","startPage":"220","endPage":"228","ipdsId":"IP-098867","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468384,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.orggeochem.2018.09.010","text":"Publisher Index Page"},{"id":437748,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S3CVNI","text":"USGS data release","linkHelpText":"Data release for mean random reflectance for products of hydrous pyrolysis experiments on artificial rock mixtures of humic Wyodak-Anderson coal (2018)"},{"id":437747,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S3CVNI","text":"USGS data release","linkHelpText":"Data release for mean random reflectance for products of hydrous pyrolysis experiments on artificial rock mixtures of humic Wyodak-Anderson coal (2018)"},{"id":384586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peters, Kenneth E.","contributorId":213618,"corporation":false,"usgs":false,"family":"Peters","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[{"id":27162,"text":"Schlumberger","active":true,"usgs":false}],"preferred":false,"id":812668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":812669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, J. J.","contributorId":255620,"corporation":false,"usgs":false,"family":"Thomas","given":"J. J.","affiliations":[{"id":27322,"text":"Schlumberger-Doll Research","active":true,"usgs":false}],"preferred":false,"id":812670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pomerantz, A. E.","contributorId":255623,"corporation":false,"usgs":false,"family":"Pomerantz","given":"A.","email":"","middleInitial":"E.","affiliations":[{"id":27322,"text":"Schlumberger-Doll Research","active":true,"usgs":false}],"preferred":false,"id":812671,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}