Estimates of fish entrainment on the Sacramento River near the Fremont Weir are a critical component in determining the feasibility and design of a proposed notch in the weir to increase access to the Yolo Bypass, a seasonal floodplain of the Sacramento River. Detailed hydrodynamic and velocity measurements were made at a river bend near the Fremont Weir in the winter and spring of 2016 to examine backwater conditions and estimate the hydraulic entrainment zone, a zone where fish would be predicted to be entrained into the notch. Secondary circulation near the river bend was shown to shift the velocity and discharge distributions toward the outside of the bend. Variability in the stage-discharge relation was shown to be the biggest source of uncertainty in determining the location of the hydraulic entrainment zone. Outflow from the Sutter Bypass and high flow on the Feather River resulted in backwater conditions near the Fremont Weir about 25 percent of the time over the 27-year period from April 1990–April 2017. Velocity measurements used to estimate the critical streakline position (the outer edge of the hydraulic entrainment zone) were not made over a sufficient range of conditions to explicitly quantify the variability in the location of the critical streakline. The variability in the critical streakline position was therefore represented stochastically with a random effects model. The estimated position of the critical streakline and the random effects model are input parameters used in a simulation designed to estimate fish entrainment over a 15-year period. The estimates of the critical streakline and likely fish entrainment could be much improved with velocity measurements over a broader range of stage and discharge conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185115","collaboration":"Prepared in cooperation with the California Department of Water Resources and U.S. Bureau of Reclamation","usgsCitation":"Stumpner, P.R., Blake, A.R., and Burau, J.R., 2018, Hydrology and hydrodynamics on the Sacramento River near the Fremont Weir, California—Implications for juvenile salmon entrainment estimates: U.S. Geological Survey Scientific Investigations Report 2018–5115, 50 p., https://doi.org/10.3133/sir20185115. ","productDescription":"Report: viii, 50 p.","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-092827","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437691,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QZ296Z","text":"USGS data release","linkHelpText":"Velocity mapping using moving boat acoustic Doppler current profiler on the Sacramento River near the western end of the Fremont Weir in February and March 2016, and May 2017"},{"id":359279,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5115/sir20185115_.pdf","text":"Report","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5115"},{"id":359284,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5115/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 38.5833\n ],\n [\n -121.5,\n 38.5833\n ],\n [\n -121.5,\n 39.0833\n ],\n [\n -122,\n 39.0833\n ],\n [\n -122,\n 38.5833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
We integrated field measurements, hydroponic experiments, microscopy, and spectroscopy to investigate the effect of Ca(II) on dissolved U(VI) uptake by plants in 1 mM HCO3– solutions at circumneutral pH. The accumulation of U in plants (3.1–21.3 mg kg–1) from the stream bank of the Rio Paguate, Jackpile Mine, New Mexico served as a motivation for this study. Brassica junceawas the model plant used for the laboratory experiments conducted over a range of U (30–700 μg L–1) and Ca (0–240 mg L–1) concentrations. The initial U uptake followed pseudo-second-order kinetics. The initial U uptake rate (V0) ranged from 4.4 to 62 μg g–1 h–1 in experiments with no added Ca and from 0.73 to 2.07 μg g–1 h–1 in experiments with 12 mg L–1 Ca. No measurable U uptake over time was detected for experiments with 240 mg L–1 Ca. Ternary Ca–U–CO3complexes may affect the decrease in U bioavailability observed in this study. Elemental X-ray mapping using scanning transmission electron microscopy–energy-dispersive spectrometry detected U–P-bearing precipitates within root cell walls in water free of Ca. These results suggest that root interactions with Ca and carbonate in solution affect the bioavailability of U in plants. This study contributes relevant information to applications related to U transport and remediation of contaminated sites.
","language":"English","publisher":"ACS","doi":"10.1021/acs.est.8b02724","usgsCitation":"El Hayek, E., Torres, C., Rodriguez-Freire, L., Blake, J., De Vore, C.L., Brearley, A.J., Spilde, M.N., Cabaniss, S., Ali, A.S., and Cerrato, J.M., 2018, Effect of calcium on the bioavailability of dissolved uranium(VI) in plant roots under circumneutral pH: Environmental Science & Technology, v. 52, no. 22, p. 13089-13098, https://doi.org/10.1021/acs.est.8b02724.","productDescription":"10 p.","startPage":"13089","endPage":"13098","ipdsId":"IP-096227","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":460811,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6341987","text":"External Repository"},{"id":360794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"22","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"El Hayek, Eliane","contributorId":207797,"corporation":false,"usgs":false,"family":"El Hayek","given":"Eliane","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":755189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torres, Chris","contributorId":211908,"corporation":false,"usgs":false,"family":"Torres","given":"Chris","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":755190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez-Freire, Lucia","contributorId":211909,"corporation":false,"usgs":false,"family":"Rodriguez-Freire","given":"Lucia","email":"","affiliations":[{"id":38351,"text":"New Jersey Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":755191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blake, Johanna M. 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":211907,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":755188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Vore, Cherie L.","contributorId":211910,"corporation":false,"usgs":false,"family":"De Vore","given":"Cherie","email":"","middleInitial":"L.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":755192,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brearley, Adrian J.","contributorId":211911,"corporation":false,"usgs":false,"family":"Brearley","given":"Adrian","email":"","middleInitial":"J.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":755193,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Spilde, Michael N.","contributorId":211912,"corporation":false,"usgs":false,"family":"Spilde","given":"Michael","email":"","middleInitial":"N.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":755194,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cabaniss, Stephen","contributorId":211913,"corporation":false,"usgs":false,"family":"Cabaniss","given":"Stephen","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":755195,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ali, Abdul-Mehdi S.","contributorId":211914,"corporation":false,"usgs":false,"family":"Ali","given":"Abdul-Mehdi","email":"","middleInitial":"S.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":755196,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cerrato, Jose M.","contributorId":211915,"corporation":false,"usgs":false,"family":"Cerrato","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":755197,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70219471,"text":"70219471 - 2018 - Volcanic hail detected with GPS: The 2011 eruption of Grímsvötn Volcano, Iceland","interactions":[],"lastModifiedDate":"2021-04-08T12:23:23.066734","indexId":"70219471","displayToPublicDate":"2018-11-09T07:20:20","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Volcanic hail detected with GPS: The 2011 eruption of Grímsvötn Volcano, Iceland","docAbstract":"Volcanic plumes are challenging to detect and characterize rapidly, but insights into processes such as hail formation or ash aggregation are valuable to hazard forecasts during volcanic crises. Global Navigation Satellite System (GNSS, which includes GPS) signals traveling from satellites to ground receivers can be disturbed by volcanic plumes. To date, two effects aiding plume detection from GNSS observations have been described: (a) ash‐rich plumes scatter the signal, lowering the signal‐to‐noise ratio (SNR), and (b) some plumes refract and thus delay GNSS signals. Using GNSS data from the VEI 4 2011 Grímsvötn eruption, we show that tephra and water contents of plumes distinctly affect SNR and phase residuals. The signals suggest high‐altitude freezing of plume water into volcanic hail—corroborated by 1‐D modeling and volcanic hail deposits. Combining GNSS SNR and phase residual analyses is valuable for detecting processes that rapidly scrub fine ash out of the atmosphere.
Burning and grazing are natural processes in native prairies that also serve as important tools in grassland management to conserve plant diversity, to limit encroachment of woody and invasive plants, and to maintain or improve prairies. Native prairies managed by the U.S. Fish and Wildlife Service (FWS) in the Prairie Pothole Region of the northern Great Plains have been extensively invaded by nonnative, cool-season species of grasses. These invasions were believed to reflect a common management history of long-term rest and little or no defoliation by natural processes (burning and grazing). To address the challenges associated with these invasive species, the FWS embraced a collaborative approach in 2008, in partnership with U.S. Geological Survey, to restore native prairies on lands managed by FWS. This approach is known as the Native Prairie Adaptive Management (NPAM) initiative and was based on the application of an adaptive decision-support framework to assist managers in selecting management actions despite uncertainty and in maximizing learning from management outcomes. The primary objective of this approach was to increase the composition of native grasses and forbs on native, unbroken sod while minimizing costs. The alternative management actions that were used to meet this objective include grazing, burning, burning and grazing, and rest (no action).
A major challenge for FWS resource managers participating in the NPAM initiative was the recognition that other taxa, besides native grasses and forbs, may be affected by the alternative management practices, thus complicating the adaptive-management cycle and deepening the uncertainty. Specifically, many grassland birds are sensitive to changes in vegetation composition and structure, and thus management that alters vegetation also may affect bird populations. The primary objectives of this study were to assess the effects of alternative management actions on grassland birds on FWS-owned grasslands that are managed under the adaptive-management framework, and to assess the association of vegetation structure and composition as mechanisms for triggering grassland bird responses to management.
We surveyed breeding birds and sampled vegetation on 89 native prairie NPAM units managed by the FWS during 2011–13, including 55 units in 2011, 87 units in 2012, and 87 units in 2013. The NPAM units were in 19 FWS refuge complexes and wetland management districts, including 14 complexes in FWS Region 6 (North Dakota, South Dakota, and Montana) and 5 complexes in FWS Region 3 (Minnesota). Generalized linear mixed models were used to evaluate the effects of management actions on vegetation structure, vegetation composition, and densities of common bird species. Vegetation structure and composition varied among study units and years, and many of these differences were linked to specific management activities or to the recency of those activities. We recorded 110 bird species in the 89 adaptive-management units. Models of bird abundance reflected not only disturbance-derived changes in vegetation structure and species-specific vegetation preferences but also the influence of defoliation treatments. Vegetation composition was less important to grassland birds than vegetation structure; in particular, mean vertical obstruction (vegetation height-density), bare-ground cover, and litter depth positively or negatively influenced densities of some grassland bird species. The diversity of bird responses to management in this study underscores the complexity of natural grassland systems and the need for heterogeneity management in grasslands in this region.
Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
In this report, we constructed and parameterized the Stream Salmonid Simulator (S3) for the 64-kilometer “Restoration Reach” of the Trinity River, just downstream of Lewiston Dam in northern California. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive survival and growth within each habitat unit and movement of fish among habitat units.
The physical template of the Restoration Reach was formed by classifying the river into 356 meso-habitat units comprised of runs, riffles, and pools. For each habitat unit, we developed a timeseries of daily flow, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg growth and survival and juvenile movement, growth, and survival.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181174","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Perry, R.W., Jones, E.C., Plumb, J.M., Som, N.A., Hetrick, N.J., Hardy, T.B., Polos, J.C., Martin, A.C., Alvarez, J.S., and De Juilio, K.P., 2018, Application of the Stream Salmonid Simulator (S3) to the restoration reach of the Trinity River, California—Parameterization and calibration: U.S. Geological Survey Open-File Report 2018-1174, 64 p., https://doi.org/10.3133/ofr20181174.","productDescription":"vi, 65 p.","onlineOnly":"Y","ipdsId":"IP-092954","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":359376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1174/ofr20181174.pdf","text":"Report","size":"10.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1174"},{"id":359375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1174/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Trinity River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.12927246093751,\n 40.635319920747456\n ],\n [\n -122.7674102783203,\n 40.635319920747456\n ],\n [\n -122.7674102783203,\n 40.77950154452172\n ],\n [\n -123.12927246093751,\n 40.77950154452172\n ],\n [\n -123.12927246093751,\n 40.635319920747456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The rocks and landforms of the Fort Collins 30′ × 60′ 1:100,000-scale U.S. Geological Survey quadrangle reveals a particularly complete record of geologic history in the northern Front Range of Colorado. The Proterozoic basement rocks exposed in the core of the range preserve evidence of Paleoproterozoic marine sedimentation, volcanism, and regional soft-sediment deformation, followed by regional folding and gradational metamorphism. Mesoproterozoic time was marked by intrusion of the Berthoud Plutonic Suite into crust that was structurally neutral or moderately extending in an east-northeast direction.
Evidence of the late Paleozoic Anasazi uplift (Ancestral Rocky Mountains uplift) within the quadrangle is recorded by removal of Permian and older sediments and deposition of proximal Pennsylvanian and Permian strata unconformably onto the exhumed Proterozoic basement rocks. The Phanerozoic sediments indicate a steady progression of fluvial, eolian, and lacustrine environments throughout most of the Mesozoic Era which was a time of relatively slow sediment accumulation. Early Cretaceous time was marked by incursion of the Cretaceous Western Interior Seaway, a shallow-water marine embayment that persisted throughout the latter part of the Mesozoic Era. Sedimentation rates increased significantly in the latter part of this period during down-warping related to distant crustal loading by thrusting along the western continental margin.
With onset of the Laramide orogeny in latest Cretaceous time, mountain building resumed in this region. This deformation placed Proterozoic rock over Cretaceous and Paleocene strata along the western margin of the Front Range and Medicine Bow Mountains. Post-Laramide time was marked by a prolonged period of weathering, erosion, and planation of the basement-rock surface, extending perhaps into late Oligocene or early Miocene time.
Erosion on the eastern slope of the Front Range in late Paleogene to early Neogene time produced a broad, rolling surface surrounding residual highlands and east-trending fluvial channels filled with coarse, boulder gravel.
Significant global cooling during the Pliocene led to glaciation during the Quaternary. In the Rocky Mountain region, renewed uplift allowed erosion to accentuate the topographic relief across the high mountains of the map area and established the elevations necessary to trigger accumulation of persistent snow and ice. Mountain glaciers advanced and retreated during at least three glacial-interglacial cycles during the middle and late Pleistocene in this area.
Erosion continues to this day on the High Plains east of the mountain front, and progressive incision of the drainage is recorded by at least five major gravel-clad terrace and pediment surfaces along the major fluvial channels that connect to the South Platte River system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3399","usgsCitation":"Workman, J.B., Cole, J.C., Shroba, R.R., Kellogg, K.S., and Premo, W.R., 2018, Geologic map of the Fort Collins 30'×60' quadrangle, Larimer and Jackson Counties, Colorado, and Albany and Laramie Counties, Wyoming: U.S. Geological Survey Scientific Investigations Map 3399, pamphlet 83 p., scale 1:100,000, https://doi.org/10.3133/sim3399/.","productDescription":"Report: vii, 83 p.; 2 Maps: 59.0 x 38.5 inches; Data Release; Read Me","onlineOnly":"Y","ipdsId":"IP-078484","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":359260,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G44PHV","text":"USGS data release","linkHelpText":"Data release for geologic map of the Fort Collins 30' x 60' quadrangle, Larimer and Jackson Counties, Colorado and Albany and Laramie Counties, Wyoming"},{"id":359258,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3399/sim3399_sheet_georeferenced.pdf","text":"Georeferenced Map","size":"59.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3399 Georeferenced Map"},{"id":359257,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3399/sim3399_sheet.pdf","text":"Map","size":"57.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3399 Map"},{"id":359259,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3399/sim3399_Readme.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3399 Read Me"},{"id":359255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3399/coverthb2.jpg"},{"id":359256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3399/sim3399_pamphlet.pdf","text":"Report","size":"19.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3399 Pamphlet"}],"country":"United States","state":"Colorado, Wyoming","county":"Albany County, Jackson County, Laramie County, Larimer County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 40.5\n ],\n [\n -105,\n 40.5\n ],\n [\n -105,\n 41\n ],\n [\n -106,\n 41\n ],\n [\n -106,\n 40.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
GenEst (a generalized estimator of mortality) is a suite of statistical models and software tools for generalized mortality estimation. It was specifically designed for estimating the number of bird and bat fatalities at solar and wind power facilities, but both the software (Dalthorp and others, 2018) and the underlying statistical models are general enough to be useful in various situations to estimate the size of open populations when detection probabilities and search coverages are less than 1. In this report, we outline the statistical models and data structures underlying the estimator. The models are numerous, complex, and intricately interwoven. Discussion begins with broad, high-level overviews of the general models. The lower-level technical details are then gradually added. Broader and less technical discussions on the general context and applications of the models and the use of the software are available in the software user guide (Simonis and others, 2018), vignettes bundled with the software, and the help files within the software itself.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Algorithm in Book 7:Automated data processing and computations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7A2","collaboration":"Prepared in cooperation with Bureau of Land Management and the National Renewable Energy Laboratory","usgsCitation":"Dalthorp, D., Madsen, L., Huso, M., Rabie, P., Wolpert, R., Studyvin, J., Simonis, J., and Mintz, J., 2018, GenEst statistical models—A generalized estimator of mortality: U.S. Geological Survey Techniques and Methods, book 7, chap. A2, 13 p., https://doi.org/10.3133/tm7A2.","productDescription":"Report: iv, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-101458","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":359137,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/7a2/coverthb.jpg"},{"id":359138,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/7a2/tm7a2.pdf","text":"Report","size":"371 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-A2"},{"id":359326,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O9BATL","text":"USGS data release","linkHelpText":"Generalized Mortality Estimator (GenEst) - R code & GUI"},{"id":359139,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm7C19","text":"Techniques and Methods 7-C19 —","description":"TM 7-C19","linkHelpText":"GenEst User Guide—Software for a Generalized Estimator of Mortality"}],"publicComments":"This report is Chapter 2 of Section A: Algorithm in Book 7:Automated data processing and computations.","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Epithermal gold-silver deposits are vein, stockwork, disseminated, and replacement deposits that are mined primarily for their gold and silver contents; some deposits also contain substantial resources of lead, zinc, copper, and (or) mercury. These deposits form in the uppermost parts of the crust, at depths less than about 1,500 meters below the water table, and at temperatures below about 300 °C. Most epithermal gold-silver deposits are genetically related to hydrothermal systems associated with subaerial volcanism and intrusion of calc-alkaline magmas along convergent plate margins. These deposits formed throughout most of geologic time, although most known deposits are Cenozoic, which reflects preferential preservation of these shallowly formed deposits in tectonically unstable regions. Epithermal gold-silver deposits range in size from tens of thousands to greater than 1 billion metric tons of ore and have gold contents of 0.1 to greater than 30 grams per metric ton and silver contents of less than 1 to several thousand grams per metric ton. Historically, these deposits have been an important source of gold and silver and are estimated to contain about 8 percent of global gold. The wide range of tonnage-grade characteristics makes epithermal gold-silver deposits an attractive target for small and large exploration and mining companies.
This report constitutes a new descriptive model for epithermal gold-silver deposits. It summarizes characteristics of known deposits, including their geological, geophysical, geochemical, and geoenvironmental aspects. Models concerning the genesis of epithermal gold-silver deposits are discussed. The application of descriptive and genetic aspects of the model to mineral exploration and resource assessment of undiscovered deposits is described. Finally, areas where additional research is needed to better understand the genesis of these deposits are identified. An extensive summary table outlining the characteristics of about 100 epithermal gold-silver deposits is included as an appendix; this summary table includes most of the world’s largest epithermal gold-silver deposits, and many smaller, well-studied deposits.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Mineral deposit models for resource assessment (Investigations Report 2010–5070)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070Q","usgsCitation":"John, D.A., Vikre, P.G., du Bray, E.A., Blakely, R.J., Fey, D.L., Rockwell, B.W., Mauk, J.L., Anderson, E.D., and Graybeal, F.T., 2018, Descriptive models for epithermal gold-silver deposits: U.S. Geological Survey Scientific Investigations Report 2010–5070–Q, 247 p., https://doi.org/10.3133/sir20105070Q.","productDescription":"Report: xi, 246 p.; 1 Figure; 3 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069851","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":359100,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5070/q/sir20105070q_appendix2.xlsx","text":"Appendix 2","size":"19 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2010-5070 Chapter Q Appendix 2","linkHelpText":"Grade and tonnage data and data sources for epithermal gold deposits"},{"id":359099,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5070/q/sir20105070q_appendix1.xlsx","text":"Appendix 1","size":"55 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2010-5070 Chapter Q Appendix 1","linkHelpText":"Characteristics of epithermal gold-silver deposits"},{"id":359096,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5070/q/coverthb.jpg"},{"id":359097,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/q/sir20105070q.pdf","text":"Report","size":"40.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5070 Chapter Q"},{"id":359098,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5070/q/sir20105070q_figA1.pdf","text":"Figure A1","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5070 Chapter Q Figure A1"},{"id":359101,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5070/q/sir20105070q_appendix3.xlsx","text":"Appendix 3","size":"4 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2010-5070 Chapter Q Appendix 3","linkHelpText":"Compilation of isotopic data for epithermal gold-silver mineral deposits"}],"contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
Accounting for migration and connectivity of mobile species across the annual cycle can present challenges for conservation and management efforts. The use of stable isotope approaches to examine the movements and ecology of wildlife has been widespread over the past two decades. Hydrogen stable isotope (δ2H) composition, in particular, has been frequently used to provide insight into the origin of migratory species, although isotopes of other elements are sometimes used. These intrinsic markers can yield valuable information about distributions of wildlife on a broad scale, with reduced labor and expense compared to tracking and telemetry. Many of the applications of isotopes to migratory species to date have addressed connectivity and origin, and studies in support of conservation biology are less common. In addition, there are few guides for how to best employ these methods for management. Therefore, we provide an overview for the wildlife conservation and management community on how stable isotope methods may be applied to conservation problems and a primer on the process for assigning geographic origins to terrestrial wildlife. We also discuss best practices for employing environmental isoscapes (isotopic distributions across landscapes), rescaling functions, and the assumptions required for assignment to origin while highlighting emerging issues in the modeling process. Finally, we provide example applications to illustrate these principles, and we explore strengths and limitations of this approach in a conservation context.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.10.019","usgsCitation":"Vander Zanden, H.B., Nelson, D.M., Wunder, M., Conkling, T., and Katzner, T., 2018, Application of isoscapes to determine geographic origin of terrestrial wildlife for conservation and management: Biological Conservation, v. 228, p. 268-280, https://doi.org/10.1016/j.biocon.2018.10.019.","productDescription":"13 p.","startPage":"268","endPage":"280","ipdsId":"IP-096404","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":366325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"228","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vander Zanden, Hanna B.","contributorId":217914,"corporation":false,"usgs":false,"family":"Vander Zanden","given":"Hanna","email":"","middleInitial":"B.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":767805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, David M.","contributorId":175098,"corporation":false,"usgs":false,"family":"Nelson","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":13479,"text":"University of Maryland Center for Environmental Science, Appalachian Laboratory, 301 Braddock Road, Frostburg, Maryland","active":true,"usgs":false}],"preferred":false,"id":767806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wunder, Michael B.","contributorId":80599,"corporation":false,"usgs":false,"family":"Wunder","given":"Michael B.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":767807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conkling, Tara 0000-0003-1926-8106","orcid":"https://orcid.org/0000-0003-1926-8106","contributorId":217915,"corporation":false,"usgs":true,"family":"Conkling","given":"Tara","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":767808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":767804,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273410,"text":"70273410 - 2018 - Sulfur cycle in the Valles Caldera volcanic complex, New Mexico – Letter 1: Sulfate sources in aqueous system, and implications for S isotope record in Gale Crater on Mars","interactions":[],"lastModifiedDate":"2026-01-14T14:29:24.274387","indexId":"70273410","displayToPublicDate":"2018-11-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Sulfur cycle in the Valles Caldera volcanic complex, New Mexico – Letter 1: Sulfate sources in aqueous system, and implications for S isotope record in Gale Crater on Mars","docAbstract":"Initial in situ sulfur (S) isotope measurements of the Martian bedrock in Gale Crater have revealed an unexpectedly wide range of δ34S values (−47 to +28%). Generally, it is unclear what processes could have contributed to these large isotope fractionations. Therefore, we studied S sources and aqueous SO2−4 cycling in the Valles Caldera volcanic complex, New Mexico to better understand S isotope fractionations related to S degassing, hydrothermal activity, and low-temperature processes in aqueous environment. Overall, our study demonstrates that volcanic systems show large spatial heterogeneity in δ34S. Magmatic S sources are obvious in steam-dominated H2S degassing and precipitation of secondary minerals from hydrothermal fluids with low δ34S values of +0.9 ±3%. Locally, however, hydrothermal processes have resulted in more negative δ34S values in sulfide minerals (−18 to −4%) and more positive δ34S values in sulfate minerals (−1 to +3%). Major aqueous SO2−4 sources are oxidation of H2S from modern hydrothermal gas emission, and oxidation and dissolution of sulfide and sulfate minerals present in the hydrothermally altered bedrock and crater-lake sediments. The δ34S of aqueous SO2−4 in surface water and groundwater varies widely (−8 to +5%) and is similar to major S endmembers that undergo oxidation and/or dissolution by active hydrological system. Minor SO2−4 contributions with more positive δ34S values (+9 to +14%) come from deeply circulating geothermal fluids and negligible amounts from atmospheric deposition (+5 to +7% in snow). Elevated SO2−4contents are mainly associated with modern and past H2S emissions and oxidations near the surface. On regional scale, however, most of the intracaldera bedrock is S-depleted, thus the SO2−4contents are usually low in the surface aquatic system and younger sedimentary lake deposits formed at times of negligible near surface hydrothermal activity. In general, magmatic-hydrothermal processes apparently cause the largest δ34S variation in S-bearing minerals on volcanic terrains. Therefore, we infer that the measured wide range of δ34S values in the Gale sediments by the Curiosity rover on Mars can be explained by S isotope composition of magmatic-hydrothermal sulfide and sulfate minerals that were present in the initial igneous/volcanic rocks prior to crater formation. Later aqueous processes involved oxidation and dissolution of S minerals initially present in these rocks and led to subsequent formation of diagenetic fluids and alteration products enriched in SO2−4 with relatively large δ34S variation. Additionally, physical erosion, transport and deposition of detrital hydrothermal S minerals from igneous/volcanic rocks might be in part responsible for the measured wide range of δ34S in Gale Crater. These unique S isotope results, measured in situ on another planet for the first time, imply the importance of magmatic-hydrothermal fluids in S transport on early Mars and their subsequent alteration in low-temperature aqueous environments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.10.036","usgsCitation":"Szynkiewicz, A., Goff, F.E., Vaniman, D., and Pribil, M., 2018, Sulfur cycle in the Valles Caldera volcanic complex, New Mexico – Letter 1: Sulfate sources in aqueous system, and implications for S isotope record in Gale Crater on Mars: Earth and Planetary Science Letters, v. 506, p. 540-551, https://doi.org/10.1016/j.epsl.2018.10.036.","productDescription":"12 p.","startPage":"540","endPage":"551","ipdsId":"IP-101952","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":498587,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Gale Crater, Mars, Valles Caldera volcanic complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.23576880836745,\n 36.186869071716416\n ],\n [\n -108.23576880836745,\n 35.36300791120573\n ],\n [\n -107.20620355256943,\n 35.36300791120573\n ],\n [\n -107.20620355256943,\n 36.186869071716416\n ],\n [\n -108.23576880836745,\n 36.186869071716416\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"506","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Szynkiewicz, Anna","contributorId":365045,"corporation":false,"usgs":false,"family":"Szynkiewicz","given":"Anna","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":953619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goff, Fraser E.","contributorId":291490,"corporation":false,"usgs":false,"family":"Goff","given":"Fraser","email":"","middleInitial":"E.","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":953620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vaniman, David","contributorId":173231,"corporation":false,"usgs":false,"family":"Vaniman","given":"David","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":953621,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pribil, Michael J. 0000-0003-4859-8673 mpribil@usgs.gov","orcid":"https://orcid.org/0000-0003-4859-8673","contributorId":141158,"corporation":false,"usgs":true,"family":"Pribil","given":"Michael","email":"mpribil@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":953622,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199785,"text":"ofr20181156 - 2018 - First comprehensive list of non-native species established in three major regions of the United States","interactions":[],"lastModifiedDate":"2018-11-13T14:40:52","indexId":"ofr20181156","displayToPublicDate":"2018-11-06T16:20:00","publicationYear":"2018","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":"2018-1156","displayTitle":"First Comprehensive List of Non-Native Species Established in Three Major Regions of the United States","title":"First comprehensive list of non-native species established in three major regions of the United States","docAbstract":"Invasive species are a subset of non-native (or alien) species, and knowing what species are non-native to a region is a first step to managing invasive species. People have been compiling non-native and invasive species lists ever since these species started causing harm, yet national non-native species lists are neither universal, nor common. Non-native species lists serve diverse purposes: watch lists for preventing invasions, inventory and monitoring lists for research and modeling, regulatory lists for species control, and nonregulatory lists for raising awareness. This diversity of purpose and the lists’ variation in geographic scope make compiling comprehensive lists of established (or naturalized) species for large regions difficult. However, listing what species are non-native in an area helps measure Essential Biodiversity Variables for invasive species monitoring and mount an effective response to established non-native species. In total, 1,166 authoritative sources were reviewed to compile the first comprehensive non-native species list for three large regions of the United States: Alaska, Hawaii, and the conterminous United States (lower 48 States). The list contains 11,344 unique names: 598 taxa for Alaska, 5,848 taxa for Hawaii, and 6,675 taxa for the conterminous United States. The list is available to the public from U.S. Geological Survey ScienceBase (https://doi.org/10.5066/P9E5K160), and the intent, though not a guarantee, is to update the list as non-native species become established in, or are eliminated from, the United States. The list has been used to annotate non-native species occurrence records in the U.S. Geological Survey all-taxa mapping application, Biodiversity Information Serving Our Nation (BISON, https://bison.usgs.gov).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181156","collaboration":" ","usgsCitation":"Simpson, A., and Eyler, M.C., 2018, First comprehensive list of non-native species established in three major regions of the United States: U.S. Geological Survey Open-File Report 2018-1156, 15 p., https://doi.org/10.3133/ofr20181156.","productDescription":"v; 15 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090660","costCenters":[{"id":38106,"text":"Science Analytics and Synthesis Program ","active":true,"usgs":true}],"links":[{"id":437693,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E5K160","text":"USGS data release","linkHelpText":"A comprehensive list of non-native species established in three major regions of the United States: Version 3.0"},{"id":358802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1156/coverthb.jpg"},{"id":358803,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1156/ofr20181156.pdf","text":"Report","size":"1.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1156"}],"country":"United States","contact":"Director, Science Analytics Synthesis Program
U.S. Geological Survey
West 6th Avenue and Kipling Street
Lakewood, CO 80225
Wind and other energy development are expanding rapidly and on an unprecedented scale within the range of the Golden Eagle (Aquila chrysaetos) while other anthropogenic-related changes, wildfires, invasive plants, drought, and climate change are altering or destroying native habitats occupied by Golden Eagles. However, the potential effects of these factors on North American Golden Eagle populations are largely unknown and the most recent evidence indicates that the population in the western United States is declining slightly. Impediments to evaluating the potential effects of energy development projects on wintering Golden Eagles include issues of scale and a paucity of available information about eagle winter use areas and ecology. We applied a predictive model of eagle winter distribution developed for Idaho and Montana, to Idaho, Utah, Nevada and eastern Oregon to help identify potential wintering areas and identify risks that occur in those areas. The model identifies ~40% of the four state study area as potentially suitable eagle winter habitat and provides a basis for spatial assessment of possible risk factors to eagles wintering there. We used eBird and Christmas Bird Count citizen science datasets for an independent evaluation of the accuracy of our predictive distribution model. The model was robust, accurately predicting the presence of wintering Golden Eagles significantly more often than expected. We used digital environmental datasets (layers) of potential risk factors, in conjunction with model predicted eagle distribution, to better understand and estimate the extent of risks to the wintering eagle population in the study area. These layers represent available data for some of the factors previously identified as risks in the landscape to wintering Golden Eagles. The majority of predicted eagle wintering areas occurred where there was little habitat fragmentation (<10%). All predicted winter areas contained at least one potential risk factor (e.g., potential for energy development); 39.4% of predicted winter areas contained at least two known risk factors. The greatest number of risks often occurred where the human footprint was highest and where eagles were less likely to occur during winter. Our results can be used to help prioritize field surveys for identifying important Golden Eagle winter areas in the western United States and determine potential locations where energy development is least likely to have negative effects on wintering eagles. Survey efforts can be allocated in consideration of management and conservation objectives based on predicted habitat suitability and risk factors. For example, surveys for areas of high suitability and low risk can identify places to focus management for conservation of eagle winter areas. Further, sites proposed for wind energy development could be reviewed initially based on model predicted eagle wintering areas and then surveyed to determine if permitting for development is appropriate.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Machine learning for ecology and sustainable natural resource management","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-96978-7_19","usgsCitation":"Craig, E.H., Fuller, M.R., Craig, T.H., and Huettmann, F., 2018, Assessment of potential risks from renewable energy development and other anthropogenic factors to wintering Golden Eagles in the western United States, chap. of Machine learning for ecology and sustainable natural resource management, p. 379-407, https://doi.org/10.1007/978-3-319-96978-7_19.","productDescription":"29 p.","startPage":"379","endPage":"407","ipdsId":"IP-097959","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":361650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-06","publicationStatus":"PW","contributors":{"editors":[{"text":"Humphries, Grant","contributorId":213887,"corporation":false,"usgs":false,"family":"Humphries","given":"Grant","email":"","affiliations":[],"preferred":false,"id":758612,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Magness, Dawn","contributorId":147692,"corporation":false,"usgs":false,"family":"Magness","given":"Dawn","affiliations":[{"id":16903,"text":"U.S. Fish and Wildlife Service, Kenai National Wildlife Refuge, Soldotna, AK, 99669, USA","active":true,"usgs":false}],"preferred":false,"id":758613,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Huettmann, Falk","contributorId":15663,"corporation":false,"usgs":false,"family":"Huettmann","given":"Falk","email":"","affiliations":[],"preferred":false,"id":758614,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Craig, Erica H.","contributorId":176469,"corporation":false,"usgs":false,"family":"Craig","given":"Erica","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":758021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Mark R. 0000-0001-7459-1729 mark_fuller@usgs.gov","orcid":"https://orcid.org/0000-0001-7459-1729","contributorId":2296,"corporation":false,"usgs":true,"family":"Fuller","given":"Mark","email":"mark_fuller@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":758022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Craig, Tim H.","contributorId":213558,"corporation":false,"usgs":false,"family":"Craig","given":"Tim","email":"","middleInitial":"H.","affiliations":[{"id":27672,"text":"Aquila Environmental","active":true,"usgs":false}],"preferred":false,"id":758023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huettmann, Falk","contributorId":15663,"corporation":false,"usgs":false,"family":"Huettmann","given":"Falk","email":"","affiliations":[],"preferred":false,"id":758024,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199978,"text":"sir20185137 - 2018 - Revised groundwater-flow model of the glacial aquifer system north of Aberdeen, South Dakota, through water year 2015","interactions":[],"lastModifiedDate":"2019-03-27T11:06:00","indexId":"sir20185137","displayToPublicDate":"2018-11-06T08:06:51","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":"2018-5137","displayTitle":"Revised Groundwater-flow Model of the Glacial Aquifer System North of Aberdeen, South Dakota, Through Water Year 2015","title":"Revised groundwater-flow model of the glacial aquifer system north of Aberdeen, South Dakota, through water year 2015","docAbstract":"The city of Aberdeen, in northeastern South Dakota, requires an expanded and sustainable supply of water to meet current and future demands. Conceptual and numerical models of the glacial aquifer system in the area north of Aberdeen were developed by the U.S. Geological Survey in cooperation with the City of Aberdeen in 2012. The U.S. Geological Survey, in cooperation with the City of Aberdeen, completed a study to revise the original numerical groundwater-flow model using data through water year (WY) 2015 to aid the City of Aberdeen in their development of plans and strategies for a sustainable water supply and to increase understanding of the glacial aquifer system and groundwater-flow system near Aberdeen. The original model was revised to improve the fit between model-simulated values and observed (measured or estimated) data, provide greater insight into surface-water interactions, and improve the usefulness of the model for water-supply planning. The revised groundwater-flow model (hereafter referred to as the “revised model”) presented in this report supersedes the original model.
The purpose of this report is to describe a revised groundwater-flow model including data collection, model calibration, and model results for the glacial aquifer system including the Elm, Middle James, and Deep James aquifers north of Aberdeen, South Dakota, using updated hydrologic data through WY 2015. The original numerical model was revised in several ways. The model was modified by adding four new layers, which included a surficial layer, two intervening confining layers, and a shale bedrock layer. The revised model provides an improved understanding of the groundwater-flow system in comparison to the original model.
The principal aquifers of the model area include portions of the Elm, Middle James, and Deep James aquifers. The lithologic information used to define and describe the aquifers in the model area was unaltered; however, aquifer properties and boundary conditions were reviewed and updated using geological information reported by the South Dakota Department of Environmental and Natural Resources and information obtained from geophysical investigations for this study. The horizontal extent of the Elm, Middle James, and Deep James aquifers was unaltered from the original model. The thickness of the Deep James aquifer was modified based on interpretations from the geophysical investigations. In general, groundwater in the Elm aquifer flowed from northwest to southeast and locally towards rivers and streams. Similarly, in the Middle James and Deep James aquifers, groundwater also typically flowed southeast.
The revisions made to the original model include use of the following MODFLOW stress packages: Recharge, Evapotranspiration, Time-Variant Specified Head, Wells, Drains, and Stream Flow Routing, all of which were updated from the original model except for the Stream Flow Routing Package, which replaced the River Package used in the original model. Model calibration is the process of estimating model parameters to minimize the differences, or residuals, between observed data and simulated values; therefore, Parameter ESTimation (PEST) software was used to optimize model input parameters by matching model-simulated values to observed data. Calibration parameters included horizontal hydraulic conductivity, vertical hydraulic conductivity, specific yield, specific storage, and vertical streambed conductance for stream and drain cells. Multipliers were used to calibrate the recharge and evapotranspiration stresses. Evapotranspiration extinction depth also was adjusted during model calibration.
Comparisons to the original model are described to highlight the changes made in the revised model. In general, the revised model adequately simulates the natural system and compares favorably with observed hydrologic data. Simulated water levels were evaluated by comparing them to single water-level observations at selected well locations. The selected wells were the same wells used in the original model. The coefficient of determination value between simulated and observed water levels for the revised model was 0.89 and included simulated and observed values from October 1, 1974 (WY 1975), through September 30, 2015 (WY 2015). The coefficient of determination value for the original model was 0.94 and included simulated and observed values from October 1, 1974, through September 30, 2009. The difference may indicate that the original model could have been overfit to hydraulic head observations because base flow was not simulated. The additional data used in the revised model included some climatically wetter, more extreme periods, such as 2011, in which annual precipitation was 30.9 inches. Average annual precipitation for the original model timeframe, which included data from WYs 1975–2009, was 20.26 inches. Additional precipitation data for WYs 2010–15, included in the revised model timeframe, resulted in an average annual precipitation for WYs 1975–2015 in the model area of 20.6 inches. The larger variability in climate data coupled with the additional water-level data could explain the lower coefficient of determination for water levels in the revised model.
The revised model was used to calculate various groundwater-budget components for steady-state and transient conditions for WYs 1975–2015. The time-variant specified-head cells in the revised model had the largest change when compared to the original steady-state model for inflows and outflows. Comparing the transient budget components between the original and the revised models indicated that inflow from recharge and time-variant specified-head cells had the greatest effect on groundwater inflows, and outflow from storage had the greatest effect on groundwater outflows. The simulated potentiometric contours from the revised model were compared with (1) the observed (interpreted) potentiometric surface (layer 2) and the hydraulic head values (layers 4 and 6) and (2) the simulated contours from the original model. The simulated hydraulic gradients and general direction of groundwater flow in the Elm aquifer in the revised model generally matched the observed potentiometric contours, the simulated potentiometric contours from the original model, and general flow directions interpreted to be perpendicular to the contours. Minor discrepancies between simulated potentiometric contours from the revised model and the observed potentiometric contours may be due to the lack of observed data in the model area.
The revised model was designed to reduce the limitations of the original model. The revisions were validated by comparing the results of the original model with the revised model. A primary benefit of the revised model is the inclusion of the surficial deposits and the confining units as explicit layers in the model. The addition of the surficial layer was beneficial for three primary reasons: (1) more accurate representation of recharge from precipitation, (2) more accurate representation of groundwater evapotranspiration, and (3) more accurate representation of groundwater and surface-water interactions. The groundwater model is a numeric approximation of a complex physical hydrologic system, and the revised model data were interpolated in regions with sparse data. Additionally, model discretization included averaged and interpolated values for water use, withdrawal rates, and hydraulic conductivity. The revised model provides a useful estimate for hydraulic gradients, groundwater-flow directions, and aquifer response to groundwater withdrawals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185137","collaboration":"Prepared in cooperation with the City of Aberdeen","usgsCitation":"Valder, J.F., Eldridge, W.G., Davis, K.W., Medler, C.J., and Koth, K.R., 2018, Revised groundwater-flow model of the glacial aquifer system north of Aberdeen, South Dakota, through water year 2015: U.S. Geological Survey Scientific Investigations Report 2018–5137, 56 p., https://doi.org/10.3133/sir20185137.","productDescription":"Report: viii, 56 p.; Data Release","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-080010","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":359157,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JVNFLY","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model of the glacial aquifer system north of Aberdeen, South Dakota, through water year 2015"},{"id":359156,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5137/sir20185137.pdf","text":"Report","size":"4.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5137"},{"id":359155,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5137/coverthb.jpg"}],"country":"United States","state":"South Dakota","city":"Aberdeen","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.6,\n 45.45\n ],\n [\n -98.27,\n 45.45\n ],\n [\n -98.27,\n 45.7\n ],\n [\n -98.6,\n 45.7\n ],\n [\n -98.6,\n 45.45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
Multi-state occupancy modeling can often improve assessments of habitat use and site quality when animal activity or behavior data are available. We examine the use of the approach for evaluating foraging habitat suitability of the endangered Hawaiian hoary bat (Lasiurus cinereus semotus) from classifications of site occupancy based on flight activity levels and feeding behavior. In addition, we used data from separate visual and auditory sources, namely thermal videography and acoustic (echolocation) detectors, jointly deployed at sample sites to compare the effectiveness of each method in the context of occupancy modeling. Video-derived observations demonstrated higher and more accurate estimates of the prevalence of high bat flight activity and feeding events than acoustic sampling methods. Elevated levels of acoustic activity by Hawaiian hoary bats were found to be related primarily to beetle biomass in this study. The approach may have a variety of applications in bat research, including inference about species-resource relationships, habitat quality and the extent to which species intensively use areas for activities such as foraging.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0205150","usgsCitation":"Gorresen, P., Brinck, K.W., DeLisle, M.A., Montoya-Aiona, K., Pinzari, C., and Bonaccorso, F., 2018, Multi-state occupancy models of foraging habitat use by the Hawaiian hoary bat Lasiurus cinereus semotus: PLoS ONE, v. 13, no. 10, p. 1-14, https://doi.org/10.1371/journal.pone.0205150.","productDescription":"e0205150; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-099393","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":460815,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0205150","text":"Publisher Index Page"},{"id":437695,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PPSHLW","text":"USGS data release","linkHelpText":"Oahu multi-state occupancy models of foraging habitat use by Hawaiian hoary bats 2017"},{"id":359218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-31","publicationStatus":"PW","scienceBaseUri":"5be2b6b0e4b0b3fc5cf5b0bf","contributors":{"authors":[{"text":"Gorresen, P. Marcos 0000-0002-0707-9212","orcid":"https://orcid.org/0000-0002-0707-9212","contributorId":196628,"corporation":false,"usgs":false,"family":"Gorresen","given":"P. Marcos","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":750750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":150936,"corporation":false,"usgs":false,"family":"Brinck","given":"Kevin","email":"kbrinck@usgs.gov","middleInitial":"W.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":750751,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLisle, Megan A.","contributorId":210453,"corporation":false,"usgs":false,"family":"DeLisle","given":"Megan","email":"","middleInitial":"A.","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":750752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Montoya-Aiona, Kristina 0000-0002-1776-5443 kmontoya-aiona@usgs.gov","orcid":"https://orcid.org/0000-0002-1776-5443","contributorId":5899,"corporation":false,"usgs":true,"family":"Montoya-Aiona","given":"Kristina","email":"kmontoya-aiona@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":750753,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pinzari, Corinna A. 0000-0001-9794-7564","orcid":"https://orcid.org/0000-0001-9794-7564","contributorId":208455,"corporation":false,"usgs":false,"family":"Pinzari","given":"Corinna A.","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":750754,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bonaccorso, Frank 0000-0002-5490-3083 fbonaccorso@usgs.gov","orcid":"https://orcid.org/0000-0002-5490-3083","contributorId":143709,"corporation":false,"usgs":true,"family":"Bonaccorso","given":"Frank","email":"fbonaccorso@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":750749,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200824,"text":"70200824 - 2018 - Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling","interactions":[],"lastModifiedDate":"2019-01-28T08:51:33","indexId":"70200824","displayToPublicDate":"2018-11-05T08:56:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling","docAbstract":"A wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/aaeae7","usgsCitation":"Vicca, S., Stocker, B., Reed, S.C., Wieder, W.R., Bahn, M., Fay, P.A., Janssens, I., Lambers, H., Penuelas, J., Piao, S., Rebel, K., Sardans, J., Sigurdsson, B.D., Van Sundert, K., Wang, Y., Zaehle, S., and Ciais, P., 2018, Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling: Environmental Research Letters, v. 13, p. 1-13, https://doi.org/10.1088/1748-9326/aaeae7.","productDescription":"Article 125006; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-101808","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468261,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aaeae7","text":"Publisher Index Page"},{"id":359217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-07","publicationStatus":"PW","scienceBaseUri":"5be2b6b0e4b0b3fc5cf5b0c1","contributors":{"authors":[{"text":"Vicca, Sara","contributorId":169514,"corporation":false,"usgs":false,"family":"Vicca","given":"Sara","email":"","affiliations":[{"id":25541,"text":"University of Antwerp, Belgium","active":true,"usgs":false}],"preferred":false,"id":750781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stocker, Benjamin","contributorId":169502,"corporation":false,"usgs":false,"family":"Stocker","given":"Benjamin","email":"","affiliations":[{"id":25536,"text":"Imperial College, UK","active":true,"usgs":false}],"preferred":false,"id":750804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":750780,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wieder, William R.","contributorId":75792,"corporation":false,"usgs":true,"family":"Wieder","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":750805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bahn, Michael","contributorId":210470,"corporation":false,"usgs":false,"family":"Bahn","given":"Michael","email":"","affiliations":[],"preferred":false,"id":750806,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fay, Philip A.","contributorId":51443,"corporation":false,"usgs":true,"family":"Fay","given":"Philip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":750807,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Janssens, Ivan","contributorId":169508,"corporation":false,"usgs":false,"family":"Janssens","given":"Ivan","affiliations":[{"id":25541,"text":"University of Antwerp, Belgium","active":true,"usgs":false}],"preferred":false,"id":750808,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lambers, Hans","contributorId":80165,"corporation":false,"usgs":true,"family":"Lambers","given":"Hans","email":"","affiliations":[],"preferred":false,"id":750809,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Penuelas, Josep","contributorId":177422,"corporation":false,"usgs":false,"family":"Penuelas","given":"Josep","affiliations":[],"preferred":false,"id":750810,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Piao, Shilong","contributorId":105424,"corporation":false,"usgs":true,"family":"Piao","given":"Shilong","email":"","affiliations":[],"preferred":false,"id":750811,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rebel, Karin","contributorId":169512,"corporation":false,"usgs":false,"family":"Rebel","given":"Karin","email":"","affiliations":[{"id":25545,"text":"Utrecht University, Netherlands","active":true,"usgs":false}],"preferred":false,"id":750812,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sardans, Jordi","contributorId":210471,"corporation":false,"usgs":false,"family":"Sardans","given":"Jordi","email":"","affiliations":[],"preferred":false,"id":750813,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sigurdsson, Bjarni D.","contributorId":75857,"corporation":false,"usgs":true,"family":"Sigurdsson","given":"Bjarni","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":750814,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Van Sundert, Kevin","contributorId":210472,"corporation":false,"usgs":false,"family":"Van Sundert","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":750815,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wang, Ying-Ping","contributorId":210473,"corporation":false,"usgs":false,"family":"Wang","given":"Ying-Ping","email":"","affiliations":[],"preferred":false,"id":750816,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Zaehle, Sonke","contributorId":210474,"corporation":false,"usgs":false,"family":"Zaehle","given":"Sonke","affiliations":[],"preferred":false,"id":750817,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ciais, Philippe 0000-0001-8560-4943","orcid":"https://orcid.org/0000-0001-8560-4943","contributorId":197934,"corporation":false,"usgs":false,"family":"Ciais","given":"Philippe","email":"","affiliations":[{"id":35082,"text":"LSCE, CEA CNRS UVSQ IPSL, Université Paris Saclay, 91191 Gif sur Yvette, France","active":true,"usgs":false}],"preferred":false,"id":750818,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70199569,"text":"70199569 - 2018 - Ground motions from the 7 and 19 September, 2017 Tehuantepec and Puebla-Morelos, Mexico, earthquakes","interactions":[],"lastModifiedDate":"2018-11-21T14:56:14","indexId":"70199569","displayToPublicDate":"2018-11-02T14:40:11","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Ground motions from the 7 and 19 September, 2017 Tehuantepec and Puebla-Morelos, Mexico, earthquakes","docAbstract":"The 2017
Background
While many species have suffered from the detrimental impacts of increasing human population growth, some species, such as cougars (Puma concolor), have been observed using human-modified landscapes. However, human-modified habitat can be a source of both increased risk and increased food availability, particularly for large carnivores. Assessing preferential use of the landscape is important for managing wildlife and can be particularly useful in transitional habitats, such as at the wildland-urban interface. Preferential use is often evaluated using resource selection functions (RSFs), which are focused on quantifying habitat preference using either a temporally static framework or researcher-defined temporal delineations. Many applications of RSFs do not incorporate time-varying landscape availability or temporally-varying behavior, which may mask conflict and avoidance behavior.
Methods
Contemporary approaches to incorporate landscape availability into the assessment of habitat selection include spatio-temporal point process models, step selection functions, and continuous-time Markov chain (CTMC) models; in contrast with the other methods, the CTMC model allows for explicit inference on animal movement in continuous-time. We used a hierarchical version of the CTMC framework to model speed and directionality of fine-scale movement by a population of cougars inhabiting the Front Range of Colorado, U.S.A., an area exhibiting rapid population growth and increased recreational use, as a function of individual variation and time-varying responses to landscape covariates.
Results
We found evidence for individual- and daily temporal-variability in cougar response to landscape characteristics. Distance to nearest kill site emerged as the most important driver of movement at a population-level. We also detected seasonal differences in average response to elevation, heat loading, and distance to roads. Motility was also a function of amount of development, with cougars moving faster in developed areas than in undeveloped areas.
Conclusions
The time-varying framework allowed us to detect temporal variability that would be masked in a generalized linear model, and improved the within-sample predictive ability of the model. The high degree of individual variation suggests that, if agencies want to minimize human-wildlife conflict management options should be varied and flexible. However, due to the effect of recursive behavior on cougar movement, likely related to the location and timing of potential kill-sites, kill-site identification tools may be useful for identifying areas of potential conflict.
","language":"English","publisher":"BioMed Central","doi":"10.1186/s40462-018-0140-6","usgsCitation":"Buderman, F.E., Hooten, M., Alldredge, M.W., Hanks, E., and Ivan, J., 2018, Time-varying predatory behavior is primary predictor of fine-scale movement of wildland-urban cougars: Movement Ecology, v. 6, p. 1-16, https://doi.org/10.1186/s40462-018-0140-6.","productDescription":"22, 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-092873","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468265,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-018-0140-6","text":"Publisher Index Page"},{"id":395133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Front Range, Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.0015869140625,\n 39.26203141523749\n ],\n [\n -104.78759765625,\n 39.26203141523749\n ],\n [\n -104.78759765625,\n 40.451127265872316\n ],\n [\n -106.0015869140625,\n 40.451127265872316\n ],\n [\n -106.0015869140625,\n 39.26203141523749\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2018-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Buderman, Frances E.","contributorId":171634,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":832263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":832264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alldredge, Mathew W.","contributorId":147536,"corporation":false,"usgs":false,"family":"Alldredge","given":"Mathew","email":"","middleInitial":"W.","affiliations":[{"id":16861,"text":"Colorado Parks and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":832265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanks, Ephraim M.","contributorId":265331,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim M.","affiliations":[{"id":24698,"text":"PSU","active":true,"usgs":false}],"preferred":false,"id":832266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ivan, Jacob S.","contributorId":200243,"corporation":false,"usgs":false,"family":"Ivan","given":"Jacob S.","affiliations":[],"preferred":false,"id":832267,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199518,"text":"70199518 - 2018 - Monitoring wadeable stream habitat conditions in Southeast Coast Network parks: Protocol narrative","interactions":[],"lastModifiedDate":"2018-11-16T17:24:25","indexId":"70199518","displayToPublicDate":"2018-11-01T17:24:16","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/SECN/NRR—2018/1715 ","title":"Monitoring wadeable stream habitat conditions in Southeast Coast Network parks: Protocol narrative","docAbstract":"The Southeast Coast Network (SECN) has initiated a monitoring effort to assess habitat conditions in wadeable streams at national parks, recreation areas, battlefields, and monuments in Alabama, Georgia, and South Carolina. This monitoring effort includes Chattahoochee River National Recreation Area, Kennesaw Mountain National Battlefield Park, Congaree National Park, Horseshoe Bend National Military Park, and Ocmulgee National Monument.
Stream habitat monitoring was implemented in 2016, and focuses specifically on providing relevant data to assess the physical condition of Piedmont and upper Coastal Plain streams with respect to aquatic and riparian habitats and how these habitats may be changing over time. The habitat assessment methods proposed in this protocol rely on standard data collection methods and standard operating procedures currently in use by the U.S. Geological Survey, U.S. Environmental Protection Agency, and U.S. Forest Service that have been modified to better meet the needs of National Park Service (NPS) managers.
The Southeast Coast Network’s wadeable stream protocol was developed to begin a monitoring program that will provide insight into the status of, and trends in, stream and riparian habitat conditions. The number of reaches surveyed at each park is dependent on the spatial extent of the park and the total number of wadeable streams that are present within park boundaries. Regardless of the size of the park and the number of reaches that are to be monitored, selected reaches (1) are representative of the processes influencing the streams in each park; (2) can address current and anticipated management concerns, and (3) offer the most utility for future complementary studies.
","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"McDonald, J.M., Gregory, M., Riley, J.W., and Starkey, E.N., 2018, Monitoring wadeable stream habitat conditions in Southeast Coast Network parks: Protocol narrative: Natural Resource Report NPS/SECN/NRR—2018/1715 , xiii, 103 p.","productDescription":"xiii, 103 p.","ipdsId":"IP-066204","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":359534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":357534,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2254874"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.890625,\n 29.49698759653577\n ],\n [\n -75.34423828125,\n 29.49698759653577\n ],\n [\n -75.34423828125,\n 36.56260003738545\n ],\n [\n -87.890625,\n 36.56260003738545\n ],\n [\n -87.890625,\n 29.49698759653577\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5befe5bae4b045bfcadf7f2e","contributors":{"authors":[{"text":"McDonald, Jacob M.","contributorId":208029,"corporation":false,"usgs":false,"family":"McDonald","given":"Jacob","email":"","middleInitial":"M.","affiliations":[{"id":37679,"text":"National Park Service Southeast Coast Inventory and Monitoring Unit","active":true,"usgs":false}],"preferred":false,"id":745742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gregory, Mark B.","contributorId":151024,"corporation":false,"usgs":false,"family":"Gregory","given":"Mark B.","affiliations":[],"preferred":false,"id":745741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riley, Jeffrey W. 0000-0001-5525-3134 jriley@usgs.gov","orcid":"https://orcid.org/0000-0001-5525-3134","contributorId":3605,"corporation":false,"usgs":true,"family":"Riley","given":"Jeffrey","email":"jriley@usgs.gov","middleInitial":"W.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745740,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starkey, Eric N.","contributorId":208030,"corporation":false,"usgs":false,"family":"Starkey","given":"Eric","email":"","middleInitial":"N.","affiliations":[{"id":37679,"text":"National Park Service Southeast Coast Inventory and Monitoring Unit","active":true,"usgs":false}],"preferred":false,"id":745743,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199846,"text":"70199846 - 2018 - Increasing soil organic carbon to mitigate greenhouse gases and increase climate resiliency for California","interactions":[],"lastModifiedDate":"2018-11-16T17:07:34","indexId":"70199846","displayToPublicDate":"2018-11-01T17:07:31","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesNumber":"CCCA4-CNRA-2018-006","title":"Increasing soil organic carbon to mitigate greenhouse gases and increase climate resiliency for California","docAbstract":"Rising air temperatures are projected to continue to drive up urban, agricultural, and rangeland water use, straining both surface and groundwater resources. Scientific studies have shown that managing farms, ranches, and public lands to increase soil carbon can increase soil waterholding capacity and increase hydrologic benefits such as increased baseflows and aquifer recharge, reduced flooding and erosion, and reduced climate-related water deficits. Coincident improvements in forage and crop yields are also indicated, while simultaneously sequestering carbon, reducing atmospheric greenhouse gases and mitigating climate change. This study was developed to consider the multiple benefits of increasing the organic matter content of soils across California’s working lands.
Study results indicate that a one-time ¼” application of compost to rangelands can lead to carbon sequestration rates in soils that are maximized after approximately 15 years, and more than offset greenhouse gas emissions stimulated by the compost addition for at least five decades longer. Modeled increases in total soil organic matter of 3% enhanced hydrologic benefits across 97% of working lands, and reduced climate change impacts. Economic valuation indicated all benefits increasing over time, demonstrating a large potential for the California carbon market to support incentives in regionalizing the impacts in the coming decades. Socioeconomic and related land use pressures pose barriers to implementing management practices to increase soil organic matter by driving conversion of rangeland to urban or to more greenhouse-gas emission intensive agriculture. Results can be effectively used with land use change scenarios to identify where on California’s working lands hydrologic benefits of soil organic matter enhancement coincide with development risk, highlighting counties in California in which there may be resilience to climate change when strategic soil management and land conservation are combined.
","language":"English","publisher":"California Natural Resources Agency","usgsCitation":"Flint, L.E., Flint, A.L., Stern, M.A., Mayer, A., Silver, W.L., Casey, C., Franco, F., Byrd, K.B., Sleeter, B.M., Alvarez, P., Creque, J., Estrada, T., and Cameron, D., 2018, Increasing soil organic carbon to mitigate greenhouse gases and increase climate resiliency for California, 113 p.","productDescription":"113 p.","ipdsId":"IP-094187","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":359532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":357952,"type":{"id":11,"text":"Document"},"url":"https://www.climateassessment.ca.gov/techreports/docs/20180827-Agriculture_CCCA4-CNRA-2018-006.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United 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Berkeley","active":true,"usgs":false}],"preferred":false,"id":746875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casey, Clyde","contributorId":208366,"corporation":false,"usgs":true,"family":"Casey","given":"Clyde","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":746876,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Franco, Fabiano 0000-0002-4849-3057","orcid":"https://orcid.org/0000-0002-4849-3057","contributorId":208367,"corporation":false,"usgs":true,"family":"Franco","given":"Fabiano","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":746877,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":746878,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":746879,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Alvarez, P.","contributorId":210675,"corporation":false,"usgs":false,"family":"Alvarez","given":"P.","email":"","affiliations":[],"preferred":false,"id":751429,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Creque, J.","contributorId":210676,"corporation":false,"usgs":false,"family":"Creque","given":"J.","email":"","affiliations":[],"preferred":false,"id":751430,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Estrada, T.","contributorId":92062,"corporation":false,"usgs":true,"family":"Estrada","given":"T.","email":"","affiliations":[],"preferred":false,"id":751431,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Cameron, D.","contributorId":95018,"corporation":false,"usgs":true,"family":"Cameron","given":"D.","affiliations":[],"preferred":false,"id":751432,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70201230,"text":"70201230 - 2018 - Inland waters","interactions":[],"lastModifiedDate":"2018-12-07T15:09:08","indexId":"70201230","displayToPublicDate":"2018-11-01T15:09:02","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Inland waters","docAbstract":"1. The total flux of carbon—which includes gaseous emissions, lateral flux, and burial—from inland waters across the conterminous United States (CONUS) and Alaska is 193 teragrams of carbon (Tg C) per year. The dominant pathway for carbon movement out of inland waters is the emission of carbon dioxide gas across water surfaces of streams, rivers, and lakes (110.1 Tg C per year), a flux not identified in the First State of the Carbon Cycle Report (SOCCR1; CCSP 2007). Second to gaseous emissions are the lateral fluxes of carbon through rivers to coastal environments (59.8 Tg C per year). Total carbon burial in lakes and reservoirs represents the smallest flux for CONUS and Alaska (22.5 Tg C per year) (medium confidence).
2. Based on estimates presented herein, the carbon flux from inland waters is now understood to be four times larger than estimates presented in SOCCR1. The total flux of carbon from inland waters across North America is estimated to be 507 Tg C per year based on a modeling approach that integrates high-resolution U.S. data and continental-scale estimates of water area, discharge, and carbon emissions. This estimate represents a weighted average of 24 grams of carbon per m2 per year of continental area exported and removed through inland waters in North America (low confidence).
3. Future research can address critical knowledge gaps and uncertainties related to inland water carbon fluxes. This chapter, for example, does not include methane emissions, which cannot be calculated as precisely as other carbon fluxes because of significant data gaps. Key to reducing uncertainties in estimated carbon fluxes is increased temporal resolution of carbon concentration and discharge sampling to provide better representations of storms and other extreme events for estimates of total inland water carbon fluxes. Improved spatial resolution of sampling also could potentially highlight anthropogenic influences on the quantity and quality of carbon fluxes in inland waters and provide information for land-use planning and management of water resources. Finally, uncertainties could likely be reduced if the community of scientists working in inland waters establishes and adopts standard measurement techniques and protocols similar to those maintained through collaborative efforts of the International Ocean Carbon Coordination Project and relevant governmental agencies from participating nations.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report","language":"English","publisher":"U.S. Global Change Research Program","publisherLocation":"Washington, D.C.","doi":"10.7930/SOCCR2.2018.Ch14","usgsCitation":"Butman, D.E., Striegl, R.G., Stackpoole, S.M., Del Giorgio, P., Prairie, Y., Pilcher, D., Raymond, P., Paz Pellat, F., and Alcocer, J., 2018, Inland waters, chap. of Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report, p. 568-595, https://doi.org/10.7930/SOCCR2.2018.Ch14.","productDescription":"28 p.","startPage":"568","endPage":"595","ipdsId":"IP-084988","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":360064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0b957ee4b0c53ecb2aca8a","contributors":{"editors":[{"text":"Cavallaro, N.","contributorId":211183,"corporation":false,"usgs":false,"family":"Cavallaro","given":"N.","email":"","affiliations":[],"preferred":false,"id":753366,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Shrestha, G.","contributorId":211184,"corporation":false,"usgs":false,"family":"Shrestha","given":"G.","email":"","affiliations":[],"preferred":false,"id":753367,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Birdsey, R.","contributorId":14670,"corporation":false,"usgs":true,"family":"Birdsey","given":"R.","email":"","affiliations":[],"preferred":false,"id":753368,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Mayes, M. 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2018 - Radium attenuation and mobilization in stream sediments following oil and gas wastewater disposal in western Pennsylvania","interactions":[],"lastModifiedDate":"2018-12-13T15:06:56","indexId":"70201431","displayToPublicDate":"2018-11-01T15:06:49","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Radium attenuation and mobilization in stream sediments following oil and gas wastewater disposal in western Pennsylvania","docAbstract":"Centralized waste treatment facilities (CWTs) in Pennsylvania discharged wastewater from conventional and unconventional oil and gas (O&G) wells into surface waters until 2011, when a voluntary request from the Pennsylvania Department of Environmental Protection (PA DEP) encouraged recycling rather than treating and discharging unconventional O&G wastewater. To determine the effect of this request on the occurrence of radium in streams, we sampled sediments at five CWTs that processed conventional O&G wastewater from 2011 to 2017 and compared results to published data. Despite the policy change in 2011 that reduced disposal of unconventional wastes (i.e., Marcellus) to surface water in Pennsylvania, the continued disposal of conventional O&G wastewater led to elevated radium activities in sediments at the point of discharge that were often hundreds of times higher than background. While these elevated activities were also present in downstream sediments (1.5× higher than background), the elimination of unconventional O&G wastewater disposal through the CWTs since 2011 decreased radium loading to the stream by approximately 95%.
Sequential extractions and geochemical modeling using PHREEQC indicate that radium likely co-precipitates with barite or barite-celestite solid solutions and accumulates in the sediment as treated O&G effluent enters the stream. Adsorption of “exchangeable” radium, barium, and strontium on hydrous iron and manganese oxide coatings on fine-grained stream sediments is an important radium sequestration mechanism further downstream that can decrease the cation concentrations and potential for radio-barite co-precipitation. Radium downstream of CWTs was more abundant and more available for dissolution and desorption than radium in upstream sediments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2018.10.011","usgsCitation":"Van Sice, K., Cravotta, C., McDevitt, B., Tasker, T.L., Landis, J.D., Puhr, J., and Warner, N.R., 2018, Radium attenuation and mobilization in stream sediments following oil and gas wastewater disposal in western Pennsylvania: Applied Geochemistry, v. 98, p. 393-403, https://doi.org/10.1016/j.apgeochem.2018.10.011.","productDescription":"11 p.","startPage":"393","endPage":"403","ipdsId":"IP-101262","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":468266,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2018.10.011","text":"Publisher Index Page"},{"id":360257,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","volume":"98","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c137dd4e4b006c4f8514890","contributors":{"authors":[{"text":"Van Sice, Katherine","contributorId":211454,"corporation":false,"usgs":false,"family":"Van Sice","given":"Katherine","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":754123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDevitt, Bonnie","contributorId":211455,"corporation":false,"usgs":false,"family":"McDevitt","given":"Bonnie","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":754124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tasker, Travis L.","contributorId":211456,"corporation":false,"usgs":false,"family":"Tasker","given":"Travis","email":"","middleInitial":"L.","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":754125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landis, Joshua D.","contributorId":211459,"corporation":false,"usgs":false,"family":"Landis","given":"Joshua","email":"","middleInitial":"D.","affiliations":[{"id":38249,"text":"Department of Earth Sciences, Dartmouth College, Hanover, NH","active":true,"usgs":false}],"preferred":false,"id":754128,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Puhr, Johnna","contributorId":211457,"corporation":false,"usgs":false,"family":"Puhr","given":"Johnna","email":"","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":754126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warner, Nathaniel R.","contributorId":211458,"corporation":false,"usgs":false,"family":"Warner","given":"Nathaniel","email":"","middleInitial":"R.","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":754127,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200905,"text":"70200905 - 2018 - Long-term impacts of exotic grazer removal on native shrub recovery, Santa Cruz Island, California","interactions":[],"lastModifiedDate":"2020-12-16T16:22:04.670834","indexId":"70200905","displayToPublicDate":"2018-11-01T15:05:46","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Long-term impacts of exotic grazer removal on native shrub recovery, Santa Cruz Island, California","docAbstract":"A combination of overgrazing and exotic species introduction has led to the degradation of habitats worldwide. It is often unclear whether removal of exotic ungulates will lead to the natural reestablishment of native plant communities without further management inputs. I describe here my return to sites on Santa Cruz Island, California, 12 years after initial sampling in order to gain a long-term view on native shrub reestablishment into exotic grasslands after exotic grazer removal. Santa Cruz Island was grazed by feral sheep and cattle for over a century; these exotic grazers were removed in the late 1980s and feral pigs were removed in 2005–2006. I resampled 5 sites on south-facing slopes in the Central Valley of the island to quantify native shrub cover, density, and size. Previous data suggested that one species, Eriogonum arborescens, would be able to naturally recruit in exotic grass–dominated areas. Native shrubs have shown a modest increase in cover over time, although more striking was a sharp increase in the amount of dead shrub cover and density. Recruitment events during high rainfall years probably led to the slight increase in Eriogonum cover between sampling periods. Recent drought periods, however, have probably increased mortality and otherwise slowed shrub reestablishment in these arid sites.
","language":"English","publisher":"Brigham Young University","doi":"10.3398/064.078.0417","usgsCitation":"Yelenik, S.G., 2018, Long-term impacts of exotic grazer removal on native shrub recovery, Santa Cruz Island, California: Western North American Naturalist, v. 78, p. 777-786, https://doi.org/10.3398/064.078.0417.","productDescription":"10 p.","startPage":"777","endPage":"786","ipdsId":"IP-093127","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":359428,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Cruz Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.96109008789061,\n 33.911454454267606\n ],\n [\n -119.49005126953124,\n 33.911454454267606\n ],\n [\n -119.49005126953124,\n 34.101570854106576\n ],\n [\n -119.96109008789061,\n 34.101570854106576\n ],\n [\n -119.96109008789061,\n 33.911454454267606\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bed4271e4b0b3fc5cf91c7c","contributors":{"authors":[{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769 syelenik@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":5251,"corporation":false,"usgs":true,"family":"Yelenik","given":"Stephanie","email":"syelenik@usgs.gov","middleInitial":"G.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":751213,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70200636,"text":"70200636 - 2018 - Automated road breaching to enhance extraction of natural drainage networks from elevation models through deep learning","interactions":[],"lastModifiedDate":"2018-11-26T14:23:15","indexId":"70200636","displayToPublicDate":"2018-11-01T14:23:11","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Automated road breaching to enhance extraction of natural drainage networks from elevation models through deep learning","docAbstract":"High-resolution (HR) digital elevation models (DEMs), such as those at resolutions of 1 and 3 meters, have increasingly become more widely available, along with lidar point cloud data. In a natural environment, a detailed surface water drainage network can be extracted from a HR DEM using flow-direction and flow-accumulation modeling. However, elevation details captured in HR DEMs, such as roads and overpasses, can form barriers that incorrectly alter flow accumulation models, and hinder the extraction of accurate surface water drainage networks. This study tests a deep learning approach to identify the intersections of roads and stream valleys, whereby valley channels can be burned through road embankments in a HR DEM for subsequent flow accumulation modeling, and proper natural drainage network extraction.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Society for Photogrammetry and Remote Sensing","doi":"10.5194/isprs-archives-XLII-4-597-2018","usgsCitation":"Stanislawski, L., Brockmeyer, T., and Shavers, E.J., 2018, Automated road breaching to enhance extraction of natural drainage networks from elevation models through deep learning, in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. XLII-4, p. 597-601, https://doi.org/10.5194/isprs-archives-XLII-4-597-2018.","productDescription":"5 p.","startPage":"597","endPage":"601","ipdsId":"IP-099807","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":468269,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/isprs-archives-xlii-4-597-2018","text":"Publisher Index Page"},{"id":359672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"XLII-4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-19","publicationStatus":"PW","scienceBaseUri":"5bfd146ee4b0815414ca38f4","contributors":{"authors":[{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":210088,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":749787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brockmeyer, Tyler","contributorId":210089,"corporation":false,"usgs":true,"family":"Brockmeyer","given":"Tyler","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":749788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":749789,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200703,"text":"70200703 - 2018 - Gravity signature of basaltic fill in Kīlauea caldera, Island of Hawai‘i","interactions":[],"lastModifiedDate":"2019-10-28T09:35:22","indexId":"70200703","displayToPublicDate":"2018-11-01T13:06:15","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"13","title":"Gravity signature of basaltic fill in Kīlauea caldera, Island of Hawai‘i","docAbstract":"Characterization of the subsurface structure of a volcanic edifice is essential to understanding volcanic behavior. One of the best-studied volcanoes is Kīlauea (Island of Hawai‘i). Geological evidence suggests that the formation of the summit caldera of Kīlauea is cyclic, with repeated collapse followed by filling with lava. The most recent collapse occurred ca. 1500 CE, producing a basin that is several hundred meters deeper than the current caldera. In this study, we used two- and three-dimensional gravity modeling of spatially dense gravity data covering the summit area to suggest that, since its formation in 1500 CE, the caldera has been progressively filled by lava flows that are slightly denser than those found in the rim and outboard of the caldera. The geometry of this fill, inferred from gravity data, enables us to reconstruct the morphology of the 1500 CE caldera before its subsequent filling. The coincidence of fumarolic zones and thermal anomalies observed at the surface with the interpreted 1500 CE caldera rim suggests that hydrothermal fluid circulation is guided by the more permeable inner faults bounding the main caldera.
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