The Miocene Columbia River Basalt Group and younger sedimentary deposits of lacustrine, fluvial, eolian, and cataclysmic-flood origins compose the aquifer system of the Quincy Basin in eastern Washington. Irrigation return flow and canal leakage from the Columbia Basin Project have caused groundwater levels to rise substantially in some areas. Water resource managers are considering extraction of additional stored groundwater to supply increasing demand. To help address these concerns, the transient groundwater model of the Quincy Basin documented in this report was developed to quantify the changes in groundwater flow and storage.
The model based on the U.S. Geological Survey modular three-dimensional finite-difference numerical code MODFLOW uses a 1-kilometer finite-difference grid and is constrained by logs from 698 wells in the study area. Five model layers represent two sedimentary hydrogeologic units and underlying basalt formations. Head-dependent flux boundaries represent the Columbia River and other streams, lakes and reservoirs, underflow to and (or) from adjacent areas, and discharge to agricultural drains and springs. Specified flux boundaries represent recharge from precipitation and anthropogenic sources, including irrigation return flow and leakage from water-distribution canals and discharge through groundwater withdrawal wells. Transient conditions were simulated from 1920 to 2013 using annual stress periods. The model was calibrated with the parameter-estimation code PEST to a total of 4,064 water levels measured in 710 wells. Increased recharge since predevelopment resulted in an 11.5 million acre-feet increase in storage in the Quincy Groundwater Management Subarea of the Quincy Basin.
Four groundwater-management scenarios were formulated with input from project stakeholders and were simulated using the calibrated model to provide representative examples of how the model could be used to evaluate the effect on groundwater levels as a result of potential changes in recharge, groundwater withdrawals, or increased flow in Crab Creek. Decreased recharge and increased groundwater withdrawals both resulted in declines in groundwater levels over 2013 conditions, whereas increasing the flow in Crab Creek resulted in increased groundwater levels over 2013 conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185162","collaboration":"Prepared in cooperation with the Washington State Department of Ecology and the Bureau of Reclamation","usgsCitation":"Frans, L.M., Kahle, S.C., Tecca, A.E., and Olsen, T.D., 2018, Simulation of groundwater storage changes in the Quincy Basin, Washington: U.S. Geological Survey Scientific Investigations Report 2018-5162, 63 p., https://doi.org/10.3133/sir20185162.","productDescription":"Report: viii, 63 p.; Model archive","onlineOnly":"Y","ipdsId":"IP-098440","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":437647,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MCIR8M","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater storage changes in the Quincy Basin, Washington"},{"id":360527,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5162/coverthb.jpg"},{"id":360528,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5162/sir20185162.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5162"},{"id":360529,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P9MCIR8M","text":"USGS model archive —","description":"USGS Model Archive","linkHelpText":"MODFLOW-NWT model used in Simulation of Groundwater Storage Changes in the Quincy Basin, Washington"}],"country":"United States","state":"Washington","otherGeospatial":"Quincy Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.13275146484374,\n 46.61548796222358\n ],\n [\n -118.52874755859376,\n 46.61548796222358\n ],\n [\n -118.52874755859376,\n 47.615421267605434\n ],\n [\n -120.13275146484374,\n 47.615421267605434\n ],\n [\n -120.13275146484374,\n 46.61548796222358\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
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934 Broadway, Suite 300
Tacoma, Washington 98402
Animals co‐occurring in a region (sympatry) may use the same habitat (syntopy) within that region. A central aim in ecology is determining what factors drive species distributions (i.e., abiotic conditions, dispersal limitations, and/or biotic interactions). Assessing the degree of biotic interactions can be difficult for species with wide ranges at sea. This study investigated the spatial ecology of two sea turtle species that forage on benthic invertebrates in neritic GoM waters: Kemp's ridleys (Lepidochelys kempii) and loggerheads (Caretta caretta). We used satellite tracking and modeled behavioral modes, then calculated individual home ranges, compared foraging areas, and determined extent of co‐occurrence. Using six environmental variables and principal component analysis, we assessed similarity of chosen foraging sites. We predicted foraging location (eco‐region) based on species, nesting site, and turtle size. For 127 turtles (64 Kemp's ridleys, 63 loggerheads) tracked from 1989 to 2013, foraging home ranges were nine to ten times larger for Kemp's ridleys than for loggerheads. Species intersected off all U.S. coasts and the Yucatán Peninsula, but co‐occurrence areas were small compared to species' distributions. Kemp's ridley foraging home ranges were concentrated in the northern GoM, whereas those for loggerheads were concentrated in the eastern GoM. The two species were different in all habitat variables compared (latitude, longitude, distance to shore, net primary production, mean sea surface temperature, and bathymetry). Nesting site was the single dominant variable that dictated foraging ecoregion. Although Kemp's ridleys and loggerheads may compete for resources, the separation in foraging areas, significant differences in environmental conditions, and importance of nesting location on ecoregion selection (i.e., dispersal ability) indicate that adult females of these species do not interact greatly during foraging and that dispersal and environmental factors more strongly determine their distributions. These species show sympatry in this region but evidence for syntopy was rare.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4691","usgsCitation":"Hart, K., Iverson, A., Fujisaki, I., Lamont, M.M., Bucklin, D.N., and Shaver, D.J., 2018, Sympatry or syntopy? Investigating drivers of distribution and co‐occurrence for two imperiled sea turtle species in Gulf of Mexico neritic waters: Ecology and Evolution, v. 8, no. 24, p. 12656-12669, https://doi.org/10.1002/ece3.4691.","productDescription":"14 p.","startPage":"12656","endPage":"12669","ipdsId":"IP-091384","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4691","text":"Publisher Index Page"},{"id":360480,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99,\n 18\n ],\n [\n -81,\n 18\n ],\n [\n -81,\n 32\n ],\n [\n -99,\n 32\n ],\n [\n -99,\n 18\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"24","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-26","publicationStatus":"PW","scienceBaseUri":"5c1a1530e4b0708288c23514","contributors":{"authors":[{"text":"Hart, Kristen M. 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":209782,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":754495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iverson, Autumn R. 0000-0002-8353-6745","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":173555,"corporation":false,"usgs":false,"family":"Iverson","given":"Autumn R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":754496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":754497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":754498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bucklin, David N.","contributorId":175273,"corporation":false,"usgs":false,"family":"Bucklin","given":"David","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":754499,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shaver, Donna J.","contributorId":191186,"corporation":false,"usgs":false,"family":"Shaver","given":"Donna","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":754500,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201673,"text":"70201673 - 2018 - Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence","interactions":[],"lastModifiedDate":"2018-12-20T15:36:37","indexId":"70201673","displayToPublicDate":"2018-12-17T15:36:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence","docAbstract":"The highly urbanized estuary of San Francisco Bay is an excellent example of a location susceptible to flooding from both coastal and fluvial influences. As part of developing a forecast model that integrates fluvial and oceanic drivers, a case study of the Napa River and its interactions with the San Francisco Bay was performed. For this application we utilize Delft3D-FM, a hydrodynamic model that computes conservation of mass and momentum on a flexible mesh grid, to calculate water levels that account for tidal forcing, storm surge generated by wind and pressure fields, and river flows. We simulated storms with realistic atmospheric pressure, river discharge, and tidal forcing to represent a realistic joint fluvial and coastal storm event. Storm conditions were applied to both a realistic field-scale Napa river drainage as well as an idealized geometry. With these scenarios, we determine how the extent, level, and duration of flooding is dependent on these atmospheric and hydrologic parameters. Unsurprisingly, the model indicates that maximal water levels will occur in a tidal river when high tides, storm surge, and large fluvial discharge events are coincident. Model results also show that large tidal amplitudes diminish storm surge propagation upstream and that phasing between peak fluvial discharges and high tide is important for predicting when and where the highest water levels will occur. The interactions between tides, river discharge, and storm surge are not simple, indicating the need for more integrated flood forecasting models in the future.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse6040158","usgsCitation":"Herdman, L.M., Erikson, L.H., and Barnard, P., 2018, Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence: Journal of Marine Science and Engineering, v. 6, no. 4, p. 1-26, https://doi.org/10.3390/jmse6040158.","productDescription":"Article 158; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-100898","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse6040158","text":"Publisher Index Page"},{"id":360648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay, Napa River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.5,\n 36.5\n ],\n [\n -121,\n 36.5\n ],\n [\n -121,\n 39\n ],\n [\n -124.5,\n 39\n ],\n [\n -124.5,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-17","publicationStatus":"PW","scienceBaseUri":"5c1cb860e4b0708288c83827","contributors":{"authors":[{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754832,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200671,"text":"sir20185146 - 2018 - Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0","interactions":[],"lastModifiedDate":"2018-12-17T13:23:00","indexId":"sir20185146","displayToPublicDate":"2018-12-17T10:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5146","displayTitle":"Methods Used to Estimate Daily Streamflow and Water Availability in the Massachusetts Sustainable-Yield Estimator Version 2.0","title":"Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0","docAbstract":"The Massachusetts Sustainable-Yield Estimator is a decision support tool that provides estimates of daily unaltered streamflow, water-use-adjusted streamflow, and water availability for ungaged, user-defined basins in Massachusetts. Daily streamflow at the ungaged site is estimated for unaltered (no water use) and water-use scenarios. The procedure for estimating streamflow was developed previously and has been implemented with minor changes and updated water-use data in version 2.0 of the Massachusetts Sustainable-Yield Estimator. Unaltered streamflow at selected exceedance probabilities is estimated by previously published regression equations. Streamflow is interpolated between the regressed quantiles to produce a continuous flow duration curve. A daily streamflow time series is produced for the ungaged site by relating the estimated flow duration curve at the ungaged site to a flow duration curve at a gaged reference site and then transferring the dates from the reference site to the ungaged site.
Minor refinements were made to the previously published methods to estimate unaltered and water-use-adjusted streamflow, including a procedure to enforce the monotonic structure of the regression-based unaltered flow quantiles, improvements to the interpolation method used for computing the estimated flow duration curve, and updates to the methods used to compute time-lagged stream alterations from groundwater pumping or discharges. Additionally, a procedure was developed to estimate prediction intervals for daily and monthly unregulated streamflow time series at an ungaged site.
The Massachusetts Sustainable-Yield Estimator computes water-use-adjusted streamflow using water-use data provided by the Massachusetts Department of Environmental Protection. Available water-use data included monthly withdrawal and wastewater discharge volumes from 2010 to 2014 for surface-water and groundwater sources. Water-use-adjusted streamflow represents the potential effect of current water use on natural streamflow in the basin over the range of historical hydrologic conditions. Georeferenced water withdrawal and discharge volumes were incorporated into the Massachusetts StreamStats web application for use in version 2.0 of the Massachusetts Sustainable-Yield Estimator. To compute water-use-adjusted streamflow, mean daily withdrawals and discharges within a user-defined basin are subtracted and added to the unaltered time series, respectively. Surface-water volumes are applied directly to the equation. Time-lagged streamflow alterations from groundwater withdrawal or wastewater discharge sources are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models in Massachusetts.
The Massachusetts Sustainable-Yield Estimator was updated to version 2.0 to improve software stability and usability. The version 2.0 software application was developed in Microsoft Access with a graphical user interface. All geoprocessing steps, including basin delineation and compilation of basin characteristics and water use within the basin, were completed in the Massachusetts StreamStats web application and exported for use by the Massachusetts Sustainable-Yield Estimator version 2.0.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185146","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Levin, S.B., and Granato, G.E., 2018, Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0: U.S. Geological Survey Scientific Investigations Report 2018–5146, 16 p., https://doi.org/10.3133/sir20185146.","productDescription":"Report: vi, 16 p.; Software release","ipdsId":"IP-087736","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5146/coverthb.jpg"},{"id":360271,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95VX5AX ","text":"USGS software release","description":"USGS software 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Occupancy models provide a reliable method of estimating species distributions while accounting for imperfect detectability. The cost of accounting for false absences is that detection and nondetection surveys typically require repeated visits to a site or multiple-observer techniques. More efficient methods of collecting data to estimate detection probabilities would allow additional sites to be surveyed for the same amount of effort, which would support more precise estimation of covariate effects to improve inference about underlying ecological processes. Time-to-detection surveys allow the estimation of detection probability based on a single site visit by one observer, and therefore might be an efficient technique for herpetological occupancy studies. We evaluated the use of time-to-detection surveys to estimate the occupancy of pond-breeding amphibians at Point Reyes National Seashore, California, USA, including variables that affected detection rates and the probability of occurrence. We found that detection times were short enough, and occupancy was high enough, to estimate reliably the probability of occurrence of three pond-breeding amphibians at Point Reyes National Seashore, and that survey and site conditions had species-specific effects on detection rates. In particular, pond characteristics affected detection times of all commonly detected species. Probability of occurrence of Sierran Treefrogs (Hyliola sierra) and Rough-Skinned Newts (Taricha granulosa) was negatively related to the detection of fish and pond area. Time-to-detection surveys can provide an efficient method for estimating detection probabilities and accounting for false absences in occupancy studies of reptiles and amphibians.
","language":"English","publisher":"The Society for the Study of Amphibians and Reptiles","doi":"10.1670/18-049","usgsCitation":"Halstead, B., Kleeman, P.M., and Rose, J.P., 2018, Time-to-detection occupancy modeling: An efficient method for analyzing the occurrence of amphibians and reptiles: Journal of Herpetology, v. 52, no. 4, p. 415-424, https://doi.org/10.1670/18-049.","productDescription":"10 p.; Data Release","startPage":"415","endPage":"424","ipdsId":"IP-098079","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437651,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9LA1O","text":"USGS data release","linkHelpText":"Time to detection data for Point Reyes pond-breeding amphibians, 2017"},{"id":360358,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Point Reyes National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.03451538085939,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 37.92578434712101\n ],\n [\n -122.68913269042967,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 38.24842651622814\n ],\n [\n -123.03451538085939,\n 37.92578434712101\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c18c423e4b006c4f856acce","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":754352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":754354,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201485,"text":"70201485 - 2018 - Ecosystem responses to elevated CO2 using airborne remote sensing at Mammoth Mountain, California","interactions":[],"lastModifiedDate":"2018-12-14T14:35:41","indexId":"70201485","displayToPublicDate":"2018-12-14T14:35:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ecosystem responses to elevated CO2 using airborne remote sensing at Mammoth Mountain, California","title":"Ecosystem responses to elevated CO2 using airborne remote sensing at Mammoth Mountain, California","docAbstract":"We present an exploratory study examining the use of airborne remote-sensing observations to detect ecological responses to elevated CO2emissions from active volcanic systems. To evaluate these ecosystem responses, existing spectroscopic, thermal, and lidar data acquired over forest ecosystems on Mammoth Mountain volcano, California, were exploited, along with in situ measurements of persistent volcanic soil CO2fluxes. The elevated CO2 response was used to statistically model ecosystem structure, composition, and function, evaluated via data products including biomass, plant foliar traits and vegetation indices, and evapotranspiration (ET). Using regression ensemble models, we found that soil CO2 flux was a significant predictor for ecological variables, including canopy greenness (normalized vegetation difference index, NDVI), canopy nitrogen, ET, and biomass. With increasing CO2, we found a decrease in ET and an increase in canopy nitrogen, both consistent with theory, suggesting more water- and nutrient-use-efficient canopies. However, we also observed a decrease in NDVI with increasing CO2 (a mean NDVI of 0.27 at 200 g m−2 d−1 CO2 reduced to a mean NDVI of 0.10 at 800 g m−2 d−1 CO2). This is inconsistent with theory though consistent with increased efficiency of fewer leaves. We found a decrease in above-ground biomass with increasing CO2, also inconsistent with theory, but we did also find a decrease in biomass variance, pointing to a long-term homogenization of structure with elevated CO2. Additionally, the relationships between ecological variables changed with elevated CO2, suggesting a shift in coupling/decoupling among ecosystem structure, composition, and function synergies. For example, ET and biomass were significantly correlated for areas without elevated CO2 flux but decoupled with elevated CO2 flux. This study demonstrates that (a) volcanic systems show great potential as a means to study the properties of ecosystems and their responses to elevated CO2 emissions and (b) these ecosystem responses are measurable using a suite of airborne remotely sensed data.
","language":"English","publisher":"European Biogeosciences Union","doi":"10.5194/bg-15-7403-2018","usgsCitation":"Cawse-Nicholson, K., Fisher, J.B., Famiglietti, C.A., Braverman, A., Schwandner, F.M., Lewicki, J.L., Townsend, P.A., Schimel, D.S., Pavlick, R., Bormann, K., Ferraz, A., Kang, E.L., Ma, P., Bogue, R.R., Youmans, T., and Pieri, D.C., 2018, Ecosystem responses to elevated CO2 using airborne remote sensing at Mammoth Mountain, California: Biogeosciences, v. 15, p. 7403-7418, https://doi.org/10.5194/bg-15-7403-2018.","productDescription":"16 p.","startPage":"7403","endPage":"7418","ipdsId":"IP-094903","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468185,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-15-7403-2018","text":"Publisher Index Page"},{"id":360330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","volume":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-14","publicationStatus":"PW","scienceBaseUri":"5c14cfb4e4b006c4f8545d1c","contributors":{"authors":[{"text":"Cawse-Nicholson, Kerry","contributorId":211502,"corporation":false,"usgs":false,"family":"Cawse-Nicholson","given":"Kerry","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Joshua B.","contributorId":211503,"corporation":false,"usgs":false,"family":"Fisher","given":"Joshua","email":"","middleInitial":"B.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Famiglietti, Caroline A.","contributorId":211504,"corporation":false,"usgs":false,"family":"Famiglietti","given":"Caroline","email":"","middleInitial":"A.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braverman, Amy","contributorId":211505,"corporation":false,"usgs":false,"family":"Braverman","given":"Amy","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwandner, Florian M.","contributorId":211506,"corporation":false,"usgs":false,"family":"Schwandner","given":"Florian","email":"","middleInitial":"M.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":754297,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Townsend, Philip A.","contributorId":211507,"corporation":false,"usgs":false,"family":"Townsend","given":"Philip","email":"","middleInitial":"A.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":754303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schimel, David S.","contributorId":211508,"corporation":false,"usgs":false,"family":"Schimel","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754304,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pavlick, Ryan","contributorId":211509,"corporation":false,"usgs":false,"family":"Pavlick","given":"Ryan","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754305,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bormann, Kathryn J.","contributorId":211510,"corporation":false,"usgs":false,"family":"Bormann","given":"Kathryn J.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754306,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ferraz, Antonio","contributorId":211511,"corporation":false,"usgs":false,"family":"Ferraz","given":"Antonio","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754307,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kang, Emily L.","contributorId":211512,"corporation":false,"usgs":false,"family":"Kang","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":38260,"text":"University of Cincinnnati","active":true,"usgs":false}],"preferred":false,"id":754308,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ma, Pulong","contributorId":211513,"corporation":false,"usgs":false,"family":"Ma","given":"Pulong","email":"","affiliations":[{"id":38260,"text":"University of Cincinnnati","active":true,"usgs":false}],"preferred":false,"id":754309,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bogue, Robert R.","contributorId":211528,"corporation":false,"usgs":false,"family":"Bogue","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754334,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Youmans, Thomas","contributorId":211529,"corporation":false,"usgs":false,"family":"Youmans","given":"Thomas","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754335,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pieri, David C.","contributorId":211514,"corporation":false,"usgs":false,"family":"Pieri","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":754310,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70201189,"text":"ofr20131024D - 2018 - Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California","interactions":[{"subject":{"id":70201189,"text":"ofr20131024D - 2018 - Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California","indexId":"ofr20131024D","publicationYear":"2018","noYear":false,"chapter":"D","title":"Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California"},"predicate":"IS_PART_OF","object":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"id":1}],"isPartOf":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"lastModifiedDate":"2024-06-26T15:40:52.511787","indexId":"ofr20131024D","displayToPublicDate":"2018-12-14T12:31:47","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":"2013-1024","chapter":"D","title":"Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California","docAbstract":"In 2011 and 2012, the sedimentary basins in the Fort Irwin National Training Center, California, were evaluated for groundwater resources using a variety of techniques, including drilling of boreholes. This study summarizes lithostratigraphic features and deposits in 8 of 10 boreholes drilled in 2 basins located in the western part of Fort Irwin. The western part of Fort Irwin straddles the eastern edge of the Miocene Eagle Crags volcanic field; therefore, many of the rocks penetrated in the boreholes are primary volcanic deposits (lava flow, pyroclastic flow, and fallout tephra deposits) and tuffaceous or lithic-rich sedimentary rocks (siltstone to cobble conglomerates) deposited in alluvial, fluvial, lacustrine, and possibly groundwater discharge environments. Boreholes were drilled with mud-rotary techniques that result in cuttings samples, and only two to four cores ranging in length from 3 to 5 feet (ft) were collected in each borehole.
Correlation of lithostratigraphic features to borehole geophysical logs (especially gamma and resistivity) helps to establish properties of the rock and enables identification of depositional sequences of similar rock types. Lithostratigraphic features and resistivity in boreholes compare reasonably well to nearby time-domain electromagnetic sounding (resistivity) model results.
There is no direct age control on the rocks penetrated in the boreholes. The abundance of tuffaceous material as primary or slightly redeposited matrix is used to identify rocks deposited during the activity of the Eagle Crags volcanic field in the Miocene. In contrast, sedimentary rocks composed of detrital and epiclastic grains (only a few of which are tuffaceous rocks as clasts) are inferred to have been deposited during the Quaternary or Pliocene(?). The lithostratigraphic-based estimates of relative age indicate the typical thickness of the Quaternary or Pliocene(?) deposits is 70–170 ft, and that several water-bearing horizons are probable in the Miocene(?) section.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131024D","usgsCitation":"Buesch, D.C., 2018, Lithostratigraphic framework in boreholes from Goldstone Lake and Nelson Lake Basins, Fort Irwin, California, chap. D of Buesch, D.C., ed., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-file Report 2013–1024–D, 133 p., https://doi.org/10.3133/ofr20131024D.","productDescription":"vi, 133 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079918","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":362164,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2013/1024/d/ofr20131024d_table2.1.xls","text":"Table 2.1","size":"56 KB xls","description":"OFR 2013-1024 Chapter D Table 2.1"},{"id":360342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1024/d/ofr20131024d.pdf","text":"Report","size":"8.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2013-1024 Chapter D"},{"id":360343,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1024/d/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","city":"Fort Irwin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 35\n ],\n [\n -116,\n 35\n ],\n [\n -116,\n 35.67\n ],\n [\n -117,\n 35.67\n ],\n [\n -117,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
One important component of continental-scale hydrologic modeling is quantifying the level of uncertainty in long-term hydrologic simulations and providing a range of possible simulated streamflow and/or runoff values for gaged and ungaged locations. In this paper, uncertainty was quantified for simulated streamflow and runoff generated from a monthly water balance model (MWBM) at 1575 streamgages and 109,951 hydrologic response units (HRUs), which span the conterminous United States (CONUS). A stochastic-approach, which incorporated the properties of modeled streamflow residuals back into the simulated model output, was used to create time series of upper and lower uncertainty intervals (UIs) around the simulated monthly time series. This approach was applied to an existing hydrologic regionalization implementation. Metrics used to evaluate the UIs across the CONUS (the coverage ratio, average width index, and interval skill score) indicated that on average the UIs were reliable, skillful, and sharp in being able to both contain measured streamflow observations and reduce estimates of uncertainty based on expected model predictions. These uncertainty evaluation metrics can complement each other in characterizing model skill and uncertainty over large-scale domains.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2018.10.005","usgsCitation":"Bock, A.R., Farmer, W.H., and Hay, L., 2018, Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model: Advances in Water Resources, v. 122, p. 166-175, https://doi.org/10.1016/j.advwatres.2018.10.005.","productDescription":"10 p.","startPage":"166","endPage":"175","ipdsId":"IP-094722","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":360293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c14cfb5e4b006c4f8545d26","contributors":{"authors":[{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":754253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":211478,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":754252,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199284,"text":"ofr20131024C - 2018 - Cenozoic geology of Fort Irwin and vicinity, California","interactions":[{"subject":{"id":70199284,"text":"ofr20131024C - 2018 - Cenozoic geology of Fort Irwin and vicinity, California","indexId":"ofr20131024C","publicationYear":"2018","noYear":false,"chapter":"C","displayTitle":"Cenozoic Geology of Fort Irwin and Vicinity, California","title":"Cenozoic geology of Fort Irwin and vicinity, California"},"predicate":"IS_PART_OF","object":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"id":1}],"isPartOf":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"lastModifiedDate":"2019-03-18T18:19:25","indexId":"ofr20131024C","displayToPublicDate":"2018-12-14T10:31:31","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":"2013-1024","chapter":"C","displayTitle":"Cenozoic Geology of Fort Irwin and Vicinity, California","title":"Cenozoic geology of Fort Irwin and vicinity, California","docAbstract":"The geology of the Fort Irwin National Training Center in the north-central Mojave Desert, California, provides insights into the hydrology and water resources of the area. The Fort Irwin area is underlain by rocks ranging in age from Proterozoic to Quaternary that have been deformed by faults as young as Quaternary. Pre-Tertiary sedimentary, igneous, and metamorphic bedrock and Miocene volcanic and sedimentary rocks are exposed in the mountains and ridges, between which are basins containing Quaternary to Pliocene deposits. During the Miocene, in the western part of Fort Irwin, development of the Eagle Crags volcanic field resulted in a complex assemblage of lava flows, pyroclastic flow and fallout tephra deposits, and volcaniclastic sedimentary rocks that were deposited in alluvial, fluvial, and locally lacustrine environments; in the eastern part of Fort Irwin, epiclastic sedimentary rocks and minor tuffaceous rocks were deposited in alluvial, fluvial, and locally lacustrine environments. In the Pliocene and Quaternary, sandstone and conglomerate were deposited in alluvial and fluvial environments, and locally fine-grained materials were deposited in lacustrine, eolian, playa, and groundwater discharge environments. The Fort Irwin area is transected by Neogene to Holocene northwest- and east-striking (and fewer northeast-striking) strike-slip, normal, and locally thrust faults. Structural blocks between faults are broadly warped, and locally rocks adjacent to the faults are folded and sheared. Many of these faults influenced the formation or modification of basins, especially after about 11 million years, when the Eastern California Shear Zone developed in this area. The three-dimensional geologic framework produced by the late Cenozoic stratigraphic and structural history is represented by the continuity or spatial limitations of lithostratigraphic and correlative hydrogeologic properties. The continuity or limitations of rocks and properties influence how water moved (and moves) through the hydrogeologic system.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131024C","collaboration":"Prepared in cooperation with the U.S. Army, Fort Irwin National Training Center","usgsCitation":"Buesch, D.C., Miller, D.M., and Menges, C.M., 2018, Cenozoic geology of Fort Irwin and vicinity, California, chap. C of Buesch, D.C., ed., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-File Report 2013–1024–C, 39 p., https://doi.org/10.3133/ofr20131024C.","productDescription":"Report: iv, 39 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-079524","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":359938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1024/c/ofr20131024c.pdf","text":"Report","size":"7.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2013-1024"},{"id":359937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1024/c/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","city":"Fort Irwin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 35\n ],\n [\n -116,\n 35\n ],\n [\n -116,\n 35.67\n ],\n [\n -117,\n 35.67\n ],\n [\n -117,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
Freshwater streams in Connecticut are subject to many competing demands, including public water supply; agricultural, commercial, and industrial water use; and ecosystem and habitat needs. In recent years, drought has further stressed Connecticut’s water resources. To sustainably allocate and manage water resources among these competing uses, Federal, State, and local water-resource managers require data and modeling tools to estimate the water availability at a variety of temporal and spatial scales for planning purposes. The Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE), developed by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection, is a decision-support tool for estimating daily unaltered streamflow and sustainable water use at ungaged sites in Connecticut.
The CT SSWUE estimates unaltered daily mean streamflow and water-use-adjusted streamflow for the period from October 1, 1960, to September 30, 2015, and the monthly sustainable net withdrawal at ungaged sites in Connecticut. Unaltered streamflow is the estimated daily mean streamflow in a drainage basin in the absence of any water withdrawals or wastewater discharges and with minimal human development. Sustainable net withdrawal is the maximum net withdrawal (withdrawal minus wastewater discharges) that can be drawn from a basin without critically depleting the water available through natural streamflow patterns. Sustainable net withdrawal is defined for this study as the difference between the unaltered daily mean streamflow and a user-defined target minimum streamflow.
Weighted least squares and Tobit regression techniques were used to develop equations for estimating streamflow at ungaged sites at 19 streamflow quantiles with exceedance probabilities ranging from 0.005 to 99.995 percent. Regressions were based on streamflow quantiles and basin characteristics from 36 reference streamgages in and around Connecticut. Four basin characteristics—drainage area, mean of the soil permeability, mean of the average annual precipitation, and ratio of the length of streams that overlay sand and gravel deposits to the total length of streams in the basin—are used as explanatory variables in the equations. At an ungaged site, interpolation between the streamflow quantiles estimated from the regression equations produces a continuous flow-duration curve. A time series of daily mean streamflow at an ungaged site is then estimated by assuming that for each day, the streamflow quantile occurs on the same date at both a reference streamgage and the ungaged site.
In a remove-one cross validation, estimated unaltered daily mean streamflow agreed well with observed values at reference streamgages, with a few exceptions. Nash Sutcliffe efficiency ranged from −0.43 to 0.97 with a median value of 0.88. The normalized root-mean-square error ranged from 16.6 to 120.4 percent with a median value of 34.5 percent.
An empirical method for estimating 95-percent prediction intervals for unaltered daily and monthly mean streamflow was developed and tested by using the cross-validation data. Prediction intervals for unaltered daily mean streamflow at the cross-validation reference streamgages performed well in most cases. Gaged streamflow values from the cross-validation data fell within the prediction intervals a median 96.6 percent of the time for daily mean time series and 93.9 percent of the time for monthly mean time series.
The CT SSWUE computes water-use-adjusted streamflow using spatially referenced water-use information provided by the Connecticut Department of Energy and Environmental Protection. Available water-use information included permitted and registered water withdrawals and permitted wastewater discharges during 1998 to 2015 for the Thames River Basin and central coastal drainage basins. Water-use information was incorporated into the U.S. Geological Survey StreamStats web application for Connecticut and can be used for computing water-use-adjusted streamflow and sustainable net withdrawal at selected points of interest. Altered daily streamflow is computed by applying average daily withdrawals and wastewater discharges to the water balance equation. Average daily surface water withdrawals and wastewater discharges are applied directly to the daily water balance equation. Time-lagged alterations on streamflow from groundwater withdrawals or wastewater discharges are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185135","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Levin, S.B., Olson, S.A., Nielsen, M.G., and Granato, G.E., 2018, The Connecticut Streamflow and Sustainable Water Use Estimator—A decision-support tool to estimate water availability at ungaged stream locations in Connecticut: U.S. Geological Survey Scientific Investigations Report 2018–5135, 34 p., https://doi.org/10.3133/sir20185135.","productDescription":"Report: vii, 34 p.; Table; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087738","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":360020,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5135/sir20185135.pdf","text":"Report","size":"8.92 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release","linkHelpText":"Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) Application Software "},{"id":360022,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5135/sir20185135_table1.csv","text":"Tabel 1 - CSV","size":"10.7 KB","linkFileType":{"id":7,"text":"csv"}}],"country":"United 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Karst subterranean estuaries (KSEs) extend into carbonate platforms along 12% of all coastlines. A recent study has shown that microbial methane (CH4) consumption is an important component of the carbon cycle and food web dynamics within flooded caves that permeate KSEs. In this study, we obtained high‐resolution (~2.5‐day) temporal records of dissolved methane concentrations and its stable isotopic content (δ13C) to evaluate how regional meteorology and hydrology control methane dynamics in KSEs. Our records show that less methane was present in the anoxic fresh water during the wet season (4,361 ± 89 nM) than during the dry season (5,949 ± 132 nM), suggesting that the wet season hydrologic regime enhances mixing of methane and other constituents into the underlying brackish water. The δ13C of the methane (−38.1 ± 1.7‰) in the brackish water was consistently more 13C‐enriched than fresh water methane (−65.4 ± 0.4‰), implying persistent methane oxidation in the cave. Using a hydrologically based mass balance model, we calculate that methane consumption in the KSE was 21–28 mg CH4·m−2·year−1 during the 6‐month dry period, which equates to ~1.4 t of methane consumed within the 102‐ to 138‐km2 catchment basin for the cave. Unless wet season methane consumption is much greater, the magnitude of methane oxidized within KSEs is not likely to affect the global methane budget. However, our estimates constrain the contribution of a critical resource for this widely distributed subterranean ecosystem.
","language":"English","publisher":"AGU","doi":"10.1029/2018GB006026","usgsCitation":"Brankovits, D., Pohlman, J.W., Ganju, N., Iliffe, T., Lowell, N., Roth, E., Sylva, S., Emmert, J., and Lapham, L.L., 2018, Hydrologic controls of methane dynamics in karst subterranean estuaries: Global Biogeochemical Cycles, v. 32, no. 12, p. 1759-1775, https://doi.org/10.1029/2018GB006026.","productDescription":"17 p.","startPage":"1759","endPage":"1775","ipdsId":"IP-102700","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gb006026","text":"Publisher Index Page"},{"id":360248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"12","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-07","publicationStatus":"PW","scienceBaseUri":"5c137dd2e4b006c4f8514874","contributors":{"authors":[{"text":"Brankovits, David 0000-0002-0863-5698","orcid":"https://orcid.org/0000-0002-0863-5698","contributorId":210617,"corporation":false,"usgs":true,"family":"Brankovits","given":"David","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pohlman, John W. 0000-0002-3563-4586 jpohlman@usgs.gov","orcid":"https://orcid.org/0000-0002-3563-4586","contributorId":145771,"corporation":false,"usgs":true,"family":"Pohlman","given":"John","email":"jpohlman@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iliffe, T.M.","contributorId":201287,"corporation":false,"usgs":false,"family":"Iliffe","given":"T.M.","email":"","affiliations":[],"preferred":false,"id":753873,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowell, N.","contributorId":211383,"corporation":false,"usgs":false,"family":"Lowell","given":"N.","email":"","affiliations":[{"id":38240,"text":"Lowell Instruments","active":true,"usgs":false}],"preferred":false,"id":753874,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roth, E.","contributorId":90499,"corporation":false,"usgs":true,"family":"Roth","given":"E.","affiliations":[],"preferred":false,"id":753875,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sylva, S.P.","contributorId":211384,"corporation":false,"usgs":false,"family":"Sylva","given":"S.P.","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":753876,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Emmert, J.A.","contributorId":211385,"corporation":false,"usgs":false,"family":"Emmert","given":"J.A.","email":"","affiliations":[{"id":38241,"text":"Moody Gardens Aquarium","active":true,"usgs":false}],"preferred":false,"id":753877,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lapham, L. L.","contributorId":140085,"corporation":false,"usgs":false,"family":"Lapham","given":"L.","email":"","middleInitial":"L.","affiliations":[{"id":13383,"text":"University of Maryland Center for Environmental Science, Chesapeake Biological Laboratory, 6 Solomons, Maryland 20688","active":true,"usgs":false}],"preferred":false,"id":753878,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70202360,"text":"70202360 - 2018 - Intensive oyster aquaculture can reduce disease impacts on sympatric wild oysters","interactions":[],"lastModifiedDate":"2019-02-25T13:33:46","indexId":"70202360","displayToPublicDate":"2018-12-13T13:33:37","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5806,"text":"Aquaculture Environment Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Intensive oyster aquaculture can reduce disease impacts on sympatric wild oysters","docAbstract":"Risks associated with disease spread from fish and shellfish farming have plagued the growth and public perception of aquaculture worldwide. However, by processing nutrients and organic material from the water column, the culture of many suspension-feeding bivalves has been proposed as a novel solution toward mitigating problems facing coastal water quality, including the removal of disease-causing parasites. Here we developed and simulated an epidemiological model describing sympatric oyster Crassostrea virginica populations in aquaculture and the wild impacted by the protozoan parasite Perkinsus marinus. Our model captured the indirect interaction between wild and cultured populations that occurs through sharing water-borne P. marinus transmission stages, and we hypothesized that oyster aquaculture can enhance wild oyster populations through reduced parasitism as long as cultured oysters are harvested prior to spreading disease. We found that the density of oysters in aquaculture, which is commonly thought to lead to the spread of disease through farms and out to nearby populations in the wild, has only indirect effects on P. marinustransmission through its interaction with the rate of aquaculture harvests. Sufficient aquaculture harvest, which varies with the susceptibility of farmed oysters to P. marinus infection and their lifespan once infected, reduces disease by diluting parasites in the environment. Our modeling results offer new insights toward the broader epidemiological implications of oyster aquaculture and effective disease management.
","language":"English","publisher":"Inter-Research","doi":"10.3354/aei00290","usgsCitation":"Ben-Horin, T., Burge, C.A., Bushek, D., Groner, M.L., Proestou, D.A., Huey, L.I., Bidegain, G., and Carnegie, R.B., 2018, Intensive oyster aquaculture can reduce disease impacts on sympatric wild oysters: Aquaculture Environment Interactions, v. 10, p. 557-567, https://doi.org/10.3354/aei00290.","productDescription":"11 p.","startPage":"557","endPage":"567","ipdsId":"IP-098954","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/aei00290","text":"Publisher Index Page"},{"id":361500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ben-Horin, Tal","contributorId":58137,"corporation":false,"usgs":false,"family":"Ben-Horin","given":"Tal","email":"","affiliations":[],"preferred":false,"id":757989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burge, Colleen A.","contributorId":213539,"corporation":false,"usgs":false,"family":"Burge","given":"Colleen","email":"","middleInitial":"A.","affiliations":[{"id":38781,"text":"Institute of Marine and Environmental Technology, University of Maryland Baltimore County, Baltimore, MD 21202","active":true,"usgs":false}],"preferred":false,"id":757990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bushek, David","contributorId":213540,"corporation":false,"usgs":false,"family":"Bushek","given":"David","email":"","affiliations":[{"id":38782,"text":"Haskin Shellfish Research Laboratory, Rutgers University, Port Norris, NJ 08349","active":true,"usgs":false}],"preferred":false,"id":757991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Groner, Maya L. 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":213541,"corporation":false,"usgs":true,"family":"Groner","given":"Maya","email":"","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757992,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Proestou, Dina A.","contributorId":213542,"corporation":false,"usgs":false,"family":"Proestou","given":"Dina","email":"","middleInitial":"A.","affiliations":[{"id":38783,"text":"National Cold Water Marine Aquaculture Center, U.S. Department of Agriculture Agricultural Research Service, Kingston, RI 02881","active":true,"usgs":false}],"preferred":false,"id":757993,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huey, Lauren I.","contributorId":213543,"corporation":false,"usgs":false,"family":"Huey","given":"Lauren","email":"","middleInitial":"I.","affiliations":[{"id":38784,"text":"Virginia Institute of Marine Science, College of William & Mary, P.O. Box 1346, Gloucester Point, VA 23062","active":true,"usgs":false}],"preferred":false,"id":757994,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bidegain, Gorka","contributorId":167008,"corporation":false,"usgs":false,"family":"Bidegain","given":"Gorka","email":"","affiliations":[{"id":13403,"text":"University of Southern Mississippi, Department of Biological Sciences, Hattiesburg, Mississippi, USA","active":true,"usgs":false}],"preferred":false,"id":757995,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carnegie, Ryan B.","contributorId":213544,"corporation":false,"usgs":false,"family":"Carnegie","given":"Ryan","email":"","middleInitial":"B.","affiliations":[{"id":38784,"text":"Virginia Institute of Marine Science, College of William & Mary, P.O. Box 1346, Gloucester Point, VA 23062","active":true,"usgs":false}],"preferred":false,"id":757996,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70201462,"text":"70201462 - 2018 - Accuracies achieved in classifying five leading world crop types and their growth stages using optimal Earth Observing-1 Hyperion hyperspectral narrowbands on Google Earth Engine","interactions":[],"lastModifiedDate":"2018-12-14T10:46:19","indexId":"70201462","displayToPublicDate":"2018-12-13T10:46:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Accuracies achieved in classifying five leading world crop types and their growth stages using optimal Earth Observing-1 Hyperion hyperspectral narrowbands on Google Earth Engine","docAbstract":"As the global population increases, we face increasing demand for food and nutrition. Remote sensing can help monitor food availability to assess global food security rapidly and accurately enough to inform decision-making. However, advances in remote sensing technology are still often limited to multispectral broadband sensors. Although these sensors have many applications, they can be limited in studying agricultural crop characteristics such as differentiating crop types and their growth stages with a high degree of accuracy and detail. In contrast, hyperspectral data contain continuous narrowbands that provide data in terms of spectral signatures rather than a few data points along the spectrum, and hence can help advance the study of crop characteristics. To better understand and advance this idea, we conducted a detailed study of five leading world crops (corn, soybean, winter wheat, rice, and cotton) that occupy 75% and 54% of principal crop areas in the United States and the world respectively. The study was conducted in seven agroecological zones of the United States using 99 Earth Observing-1 (EO-1) Hyperion hyperspectral images from 2008–2015 at 30 m resolution. The authors first developed a first-of-its-kind comprehensive Hyperion-derived Hyperspectral Imaging Spectral Library of Agricultural crops (HISA) of these crops in the US based on USDA Cropland Data Layer (CDL) reference data. Principal Component Analysis was used to eliminate redundant bands by using factor loadings to determine which bands most influenced the first few principal components. This resulted in the establishment of 30 optimal hyperspectral narrowbands (OHNBs) for the study of agricultural crops. The rest of the 242 Hyperion HNBs were redundant, uncalibrated, or noisy. Crop types and crop growth stages were classified using linear discriminant analysis (LDA) and support vector machines (SVM) in the Google Earth Engine cloud computing platform using the 30 optimal HNBs (OHNBs). The best overall accuracies were between 75% to 95% in classifying crop types and their growth stages, which were achieved using 15–20 HNBs in the majority of cases. However, in complex cases (e.g., 4 or more crops in a Hyperion image) 25–30 HNBs were required to achieve optimal accuracies. Beyond 25–30 bands, accuracies asymptote. This research makes a significant contribution towards understanding modeling, mapping, and monitoring agricultural crops using data from upcoming hyperspectral satellites, such as NASA’s Surface Biology and Geology mission (formerly HyspIRI mission) and the recently launched HysIS (Indian Hyperspectral Imaging Satellite, 55 bands over 400–950 nm in VNIR and 165 bands over 900–2500 nm in SWIR), and contributions in advancing the building of a novel, first-of-its-kind global hyperspectral imaging spectral-library of agricultural crops (GHISA: www.usgs.gov/WGSC/GHISA).
","language":"English","publisher":"MDPI","doi":"10.3390/rs10122027","usgsCitation":"Aneece, I., and Thenkabail, P.S., 2018, Accuracies achieved in classifying five leading world crop types and their growth stages using optimal Earth Observing-1 Hyperion hyperspectral narrowbands on Google Earth Engine: Remote Sensing, v. 10, no. 12, p. 1-29, https://doi.org/10.3390/rs10122027.","productDescription":"Article 2027; 29 p.","startPage":"1","endPage":"29","ipdsId":"IP-097093","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468188,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs10122027","text":"Publisher Index Page"},{"id":360295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"10","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-13","publicationStatus":"PW","scienceBaseUri":"5c14cfb7e4b006c4f8545d30","contributors":{"authors":[{"text":"Aneece, Itiya 0000-0002-1201-5459","orcid":"https://orcid.org/0000-0002-1201-5459","contributorId":211471,"corporation":false,"usgs":true,"family":"Aneece","given":"Itiya","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":754190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":754191,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201410,"text":"70201410 - 2018 - Best practices for elevation-based assessments of sea-level rise and coastal flooding exposure","interactions":[],"lastModifiedDate":"2018-12-13T14:59:37","indexId":"70201410","displayToPublicDate":"2018-12-12T14:59:31","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Best practices for elevation-based assessments of sea-level rise and coastal flooding exposure","docAbstract":"Elevation data are critical for assessments of sea-level rise (SLR) and coastal flooding exposure. Previous research has demonstrated that the quality of data used in elevation-based assessments must be well understood and applied to properly model potential impacts. The cumulative vertical uncertainty of the input elevation data substantially controls the minimum increments of SLR and the minimum planning horizons that can be effectively used in assessments. For regional, continental, or global assessments, several digital elevation models (DEMs) are available for the required topographic information to project potential impacts of increased coastal water levels, whether a simple inundation model is used or a more complex process-based or probabilistic model is employed. When properly characterized, the vertical accuracy of the DEM can be used to report assessment results with the uncertainty stated in terms of a specific confidence level or likelihood category. An accuracy evaluation has been conducted of global DEMs to quantify their inherent vertical uncertainty to demonstrate how accuracy information should be considered when planning and implementing a SLR or coastal flooding assessment. The evaluation approach includes comparison of the DEMs with high-accuracy geodetic control points as the independent reference data over a variety of coastal relief settings. The global DEMs evaluated include SRTM, ASTER GDEM, ALOS World 3D, TanDEM-X, NASADEM, and MERIT. High-resolution, high-accuracy DEM sources, such as airborne lidar and stereo imagery, are also included to give context to the results from the global DEMs. The accuracy characterization results show that current global DEMs are not adequate for high confidence mapping of exposure to fine increments (<1 m) of SLR or with shorter planning horizons (<100 years) and thus they should not be used for such mapping, but they are suitable for general delineation of low elevation coastal zones. In addition to the best practice of rigorous accounting for vertical uncertainty, other recommended procedures are presented for delineation of different types of impact areas (marine and groundwater inundation) and use of regional relative SLR scenarios. The requirement remains for a freely available, high-accuracy, high-resolution global elevation model that supports quantitative SLR and coastal inundation assessments at high confidence levels.
","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2018.00230","usgsCitation":"Gesch, D.B., 2018, Best practices for elevation-based assessments of sea-level rise and coastal flooding exposure: Frontiers in Earth Science, v. 6, p. 1-19, https://doi.org/10.3389/feart.2018.00230.","productDescription":"Article 230; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-099709","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468189,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2018.00230","text":"Publisher Index Page"},{"id":360254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-12","publicationStatus":"PW","scienceBaseUri":"5c137dd3e4b006c4f851487e","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":754063,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239437,"text":"70239437 - 2018 - Communicating information on nature-related topics: Preferred information channels and trust in sources","interactions":[],"lastModifiedDate":"2023-01-13T13:18:11.190282","indexId":"70239437","displayToPublicDate":"2018-12-12T07:15:19","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Communicating information on nature-related topics: Preferred information channels and trust in sources","docAbstract":"How information is communicated influences the public’s environmental perceptions and behaviors. Information channels and sources both play an important role in the dissemination of information. Trust in a source is often used as a proxy for whether a particular piece of information is credible. To determine preferences for information channels and trust in various sources for information on nature-related topics, a mail-out survey was sent to randomly selected U.S. addresses (n = 1,030). Diverse groups of people may have differing communication preferences. Therefore, we explored differences in channel preferences and trust by demographics using regression models. Overall, the most preferred channels were personal experience, reading online content, and watching visual media online. The most trusted sources were science organizations, universities, and friends/family. Channel preferences varied the most by education level and age, while source trust was most influenced by education, race, age, and size of current residence (rural-urban). The influence of demographics varied depending on the individual channel and source, with some groups preferring certain channels or sources but not others. Results are useful to consider when disseminating information on nature-related topics to a general public audience. More broadly, results also suggest spreading information using different channels and sources depending on the specific audience being targeted.
Acoustic surveys of vocalizing animals are conducted to determine density, distribution, and diversity. Acoustic surveys are traditionally performed by human listeners, but automated recording devices (ARD) are becoming increasingly popular. Signal strength decays, or attenuates, with increasing distance between source and receiver and some habitat types may differentially increase attenuation beyond the effects of distance alone. These combined effects are rarely accounted for in acoustic monitoring programs. We evaluated the performance of three playback devices and three ARD models using the calls of six anurans, six birds, and four pure tones. Based on these evaluations, we determined the optimal playback and recording devices. Using these optimal devices, we broadcast and recorded vocalizations in five habitat types along 1,000 m transects. We used generalized linear models to test for effects of habitat, distance, species, environmental, and landscape variables. We predicted detection probabilities for each vocalization, in each habitat type, from 0 to 1,000 m. Among playback devices, only a remote predator caller simulated vocalizations consistently. Differences of ~10 dB were observed among ARDs. For all species, we found differences in detectability between open and closed canopy habitats. We observed large differences in predicted detection probability among species in each habitat type, as well as along 1,000 m transects. Increases in temperature, barometric pressure, and wind speed significantly decreased detection probability. However, aside from differences among species, habitat, and distance, topography impeding a line‐of‐sight between sound source and receiver had the greatest negative influence on detections. Our results suggest researchers should model the effects of habitat, distance, and frequency on detection probability when performing acoustic surveys. To optimize survey design, we recommend pilot measurements among varying habitats.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4752","usgsCitation":"MacLaren, A.R., Crump, P.S., Royle, J.A., and Forstner, M., 2018, Observer-free experimental evaluation of habitat and distance effects on the detection of anuran and bird vocalizations: Ecology and Evolution, v. 8, no. 24, p. 12991-13003, https://doi.org/10.1002/ece3.4752.","productDescription":"13 p.","startPage":"12991","endPage":"13003","ipdsId":"IP-101421","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468190,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4752","text":"Publisher Index Page"},{"id":360722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"24","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-11","publicationStatus":"PW","scienceBaseUri":"5c5022c4e4b0708288f7e814","contributors":{"authors":[{"text":"MacLaren, Andrew R.","contributorId":211837,"corporation":false,"usgs":false,"family":"MacLaren","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":38329,"text":"Texas State Univ.","active":true,"usgs":false}],"preferred":false,"id":755001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crump, Paul S.","contributorId":211838,"corporation":false,"usgs":false,"family":"Crump","given":"Paul","email":"","middleInitial":"S.","affiliations":[{"id":38330,"text":"Texas State Univ","active":true,"usgs":false}],"preferred":false,"id":755002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":755000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forstner, Michael R. J.","contributorId":211839,"corporation":false,"usgs":false,"family":"Forstner","given":"Michael R. J.","affiliations":[{"id":38330,"text":"Texas State Univ","active":true,"usgs":false}],"preferred":false,"id":755003,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201353,"text":"70201353 - 2018 - The metabolic regimes of 356 rivers in the United States","interactions":[],"lastModifiedDate":"2020-09-02T12:52:01.189155","indexId":"70201353","displayToPublicDate":"2018-12-11T10:56:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"The metabolic regimes of 356 rivers in the United States","docAbstract":"A national-scale quantification of metabolic energy flow in streams and rivers can improve understanding of the temporal dynamics of in-stream activity, links between energy cycling and ecosystem services, and the effects of human activities on aquatic metabolism. The two dominant terms in aquatic metabolism, gross primary production (GPP) and aerobic respiration (ER), have recently become practical to estimate for many sites due to improved modeling approaches and the availability of requisite model inputs in public datasets. We assembled inputs from the U.S. Geological Survey and National Aeronautics and Space Administration for October 2007 to January 2017. We then ran models to estimate daily GPP, ER, and the gas exchange rate coefficient for 356 streams and rivers across the continental United States. We also gathered potential explanatory variables and spatial information for cross-referencing this dataset with other datasets of watershed characteristics. This dataset offers a first national assessment of many-day time series of metabolic rates for up to 9 years per site, with a total of 490,907 site-days of estimates.
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Jr.","contributorId":145459,"corporation":false,"usgs":false,"family":"Hall","given":"Robert O.","suffix":"Jr.","affiliations":[{"id":16121,"text":"Uni. of Wyoming, Department of Zoology and Physiology","active":true,"usgs":false}],"preferred":false,"id":753722,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":753723,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Heffernan, James B. 0000-0001-7641-9949","orcid":"https://orcid.org/0000-0001-7641-9949","contributorId":211189,"corporation":false,"usgs":false,"family":"Heffernan","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":753724,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":753725,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":753726,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":753727,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70199787,"text":"70199787 - 2018 - Crop water productivity estimation with hyperspectral remote sensing","interactions":[],"lastModifiedDate":"2020-05-27T15:58:19.713875","indexId":"70199787","displayToPublicDate":"2018-12-11T10:48:12","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"5","title":"Crop water productivity estimation with hyperspectral remote sensing","docAbstract":"Crop water productivity (CWP) is the ratio of accumulated crop biomass or yield (Y) to the water utilized to produce it, which is typically estimated using transpiration (ETC). CWP is an important metric to test and monitor water-saving strategies in agroecosystems across the globe. Red and near-infrared broadbands have been used to estimate CWP, because they capture biophysical constraints based on crop-light interaction principles at pixel level (e.g., 30-meter resolution) over large areas through time. Hyperspectral remote sensing, which allows for the more precise measurement of crop-light interactions at higher spectral resolution, should in theory provide higher accuracy in CWP estimation but has been underutilized by the remote sensing community due to computational challenges and lack of availability. In this study, a simple methodology is presented to demonstrate how CWP could be estimated using hyperspectral remote sensing. Due to a lack of hyperspectral data, Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data were used for the demonstration. Landsat is a broadband sensor that provides considerable spectral information for CWP estimation. New bands were identified in the workflow outside the typical Landsat bands used to estimate CWP and its components (Y and ETC). Landsat bands 1 and 3 were the most effective at estimating CWP and Y with an R2 of 0.72 (RMSE = 0.50 kg m−3) and 0.64 (RMSE = 0.31 kg m−2), respectively. All of the bands were poor at estimating ETC, with Landsat bands 1 and 7 being the most highly correlated (R2 = 0.13, RMSE = 0.08 m). Future work should train models with multiple estimates of CWP and Y over the growing season, while ETC may be better estimated with thermal infrared bands not considered in this study. Finally, studies should also consider estimating CWP categorically, instead of continuously, if the same objectives of testing and monitoring are met.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Hyperspectral remote sensing of vegetation: Advanced applications in remote Sensing of agricultural crops and natural vegetation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Taylor & Francis","usgsCitation":"Marshall, M., Aneece, I.P., Foley, D., Xueliang, C., and Biggs, T., 2018, Crop water productivity estimation with hyperspectral remote sensing, chap. 5 of Hyperspectral remote sensing of vegetation: Advanced applications in remote Sensing of agricultural crops and natural vegetation, v. 4, p. 79-96.","productDescription":"18 p.","startPage":"79","endPage":"96","ipdsId":"IP-097174","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":375087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375086,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/books/9780429431166/chapters/10.1201/9780429431166-5"}],"volume":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, Michael","contributorId":145855,"corporation":false,"usgs":false,"family":"Marshall","given":"Michael","affiliations":[{"id":16265,"text":"Dept. of Geography, UC Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":746604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aneece, Itiya P. 0000-0002-1201-5459","orcid":"https://orcid.org/0000-0002-1201-5459","contributorId":208265,"corporation":false,"usgs":true,"family":"Aneece","given":"Itiya","middleInitial":"P.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":746603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Daniel 0000-0002-2051-6325","orcid":"https://orcid.org/0000-0002-2051-6325","contributorId":208266,"corporation":false,"usgs":true,"family":"Foley","given":"Daniel","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":746605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xueliang, Cai","contributorId":208267,"corporation":false,"usgs":false,"family":"Xueliang","given":"Cai","email":"","affiliations":[],"preferred":false,"id":746606,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Biggs, Trent","contributorId":208268,"corporation":false,"usgs":false,"family":"Biggs","given":"Trent","affiliations":[],"preferred":false,"id":746607,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201540,"text":"70201540 - 2018 - Root endophytes and invasiveness: no difference between native and non‐native Phragmites in the Great Lakes Region","interactions":[],"lastModifiedDate":"2018-12-17T13:01:14","indexId":"70201540","displayToPublicDate":"2018-12-10T13:01:06","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Root endophytes and invasiveness: no difference between native and non‐native Phragmites in the Great Lakes Region","docAbstract":"Microbial interactions could play an important role in plant invasions. If invasive plants associate with relatively more mutualists or fewer pathogens than their native counterparts, then microbial communities could foster plant invasiveness. Studies examining the effects of microbes on invasive plants commonly focus on a single microbial group (e.g., bacteria) or measure only plant response to microbes, not documenting the specific taxa associating with invaders. We surveyed root microbial communities associated with co‐occurring native and non‐native lineages of Phragmites australis, across Michigan, USA. Our aim was to determine whether (1) plant lineage was a stronger predictor of root microbial community composition than environmental variables and (2) the non‐native lineage associated with more mutualistic and/or fewer pathogenic microbes than the native lineage. We used microscopy and culture‐independent molecular methods to examine fungal colonization rate and community composition in three major microbial groups (bacteria, fungi, and oomycetes) within roots. We also used microbial functional databases to assess putative functions of the observed microbial taxa. While fungal colonization of roots was significantly higher in non‐native Phragmites than the native lineage, we found no differences in root microbial community composition or potential function between the two Phragmites lineages. Community composition did differ significantly by site, with soil saturation playing a significant role in structuring communities in all three microbial groups. The relative abundance of some specific bacterial taxa did differ between Phragmites lineages at the phylum and genus level (e.g., Proteobacteria, Firmicutes). Purported function of root fungi and respiratory mode of root bacteria also did not differ between native and non‐native Phragmites. We found no evidence that native and non‐native Phragmites harbored distinct root microbial communities; nor did those communities differ functionally. Therefore, if the trends revealed at our sites are widespread, it is unlikely that total root microbial communities are driving invasion by non‐native Phragmites plants.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2526","usgsCitation":"Bickford, W.A., Goldberg, D.E., Kowalski, K., and Zak, D.R., 2018, Root endophytes and invasiveness: no difference between native and non‐native Phragmites in the Great Lakes Region: Ecosphere, v. 9, no. 12, p. 1-14, https://doi.org/10.1002/ecs2.2526.","productDescription":"e02526; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-098851","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":468192,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2526","text":"Publisher Index Page"},{"id":360369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"12","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-10","publicationStatus":"PW","scienceBaseUri":"5c18c424e4b006c4f856acd7","contributors":{"authors":[{"text":"Bickford, Wesley A. 0000-0001-7612-1325 wbickford@usgs.gov","orcid":"https://orcid.org/0000-0001-7612-1325","contributorId":5687,"corporation":false,"usgs":true,"family":"Bickford","given":"Wesley","email":"wbickford@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":754421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldberg, Deborah E.","contributorId":211585,"corporation":false,"usgs":false,"family":"Goldberg","given":"Deborah","email":"","middleInitial":"E.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":754422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":754423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zak, Donald R.","contributorId":211586,"corporation":false,"usgs":false,"family":"Zak","given":"Donald","email":"","middleInitial":"R.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":754424,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200851,"text":"pp1814F - 2018 - U-Pb geochronology and tectonic implications of a Silurian ash in the Farewell Terrane, Alaska","interactions":[{"subject":{"id":70200851,"text":"pp1814F - 2018 - U-Pb geochronology and tectonic implications of a Silurian ash in the Farewell Terrane, Alaska","indexId":"pp1814F","publicationYear":"2018","noYear":false,"chapter":"F","displayTitle":"U-Pb Geochronology and Tectonic Implications of a Silurian Ash in the Farewell Terrane, Alaska","title":"U-Pb geochronology and tectonic implications of a Silurian ash in the Farewell Terrane, Alaska"},"predicate":"IS_PART_OF","object":{"id":70158938,"text":"pp1814 - 2015 - Studies by the U.S. Geological Survey in Alaska, Volume 15","indexId":"pp1814","publicationYear":"2015","noYear":false,"title":"Studies by the U.S. Geological Survey in Alaska, Volume 15"},"id":1}],"isPartOf":{"id":70158938,"text":"pp1814 - 2015 - Studies by the U.S. Geological Survey in Alaska, Volume 15","indexId":"pp1814","publicationYear":"2015","noYear":false,"title":"Studies by the U.S. Geological Survey in Alaska, Volume 15"},"lastModifiedDate":"2018-12-11T12:38:31","indexId":"pp1814F","displayToPublicDate":"2018-12-10T12:49:51","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1814","chapter":"F","displayTitle":"U-Pb Geochronology and Tectonic Implications of a Silurian Ash in the Farewell Terrane, Alaska","title":"U-Pb geochronology and tectonic implications of a Silurian ash in the Farewell Terrane, Alaska","docAbstract":"The Farewell terrane is an exotic continental fragment in interior Alaska that during the early Paleozoic was the site of a passive margin. We report a 238U/206Pb zircon age of 432.9±3.0 Ma from a Farewell terrane ash in Mt. McKinley quadrangle, Alaska. This age overlaps with prominent detrital zircon age maxima reported from Silurian and Devonian strata from the Farewell, Arctic Alaska-Chukotka, White Mountains, Alexander, and Yreka terranes, and from parautochtonous Silurian and Devonian foreland-basin strata along the Laurentian margin in the Canadian Arctic and Alaska. These findings can be explained in terms of refinements to the extrusion model of Colpron and Nelson (2011). In the original model, the Farewell terrane was interpreted as having been extruded westward into the paleo-Pacific realm from an initial position along the Siberian margin of the Uralian seaway, that is, the early Paleozoic ocean between Siberia and Baltica. We suggest (1) that the Farewell terrane was deposited along a passive margin that faced into the Uralian seaway; (2) that the terrane more likely originated along the northern or eastern margin of Baltica (present directions), rather than Siberia; and (3) that the Silurian ash and Silurian detrital zircons were derived from a magmatic source along a convergent margin that overrode distal parts of the Farewell passive margin during the Late Ordovician and Silurian. The Farewell terrane was eventually dislodged from Baltica, began to travel with the extruding plate, and was conveyed toward the Pacific to its eventual resting place in Alaska.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Studies by the U.S. Geological Survey in Alaska, Volume 15","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1814F","usgsCitation":" Bradley, D.C., Dumoulin, J.A., and Bradley, D.B., 2018, U-Pb geochronology and tectonic implications of a Silurian ash in the Farewell terrane, Alaska, in Dumoulin, J.A., ed., Studies by the U.S. Geological Survey in Alaska, vol. 15: U.S. Geological Survey Professional Paper 1814–F, 13 p., https://doi.org/10.3133/pp1814F. ","productDescription":"Report: iii, 12 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-097623","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":360106,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1814/f/coverthb.jpg"},{"id":360107,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1814/f/pp1814f.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Professional Paper 1814 Chapter F"}],"country":"United States","state":"Alaska","otherGeospatial":"Farewell Terrane","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158,\n 61\n ],\n [\n -149,\n 61\n ],\n [\n -149,\n 65\n ],\n [\n -158,\n 65\n ],\n [\n -158,\n 61\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center staff
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Alaska Mineral Resources
Alaska Science Center
Emerging infectious pathogens are responsible for some of the most severe host mass mortality events in wild populations. Yet, effective pathogen control strategies are notoriously difficult to identify, in part because quantifying and forecasting pathogen spread and disease dynamics is challenging. Following an outbreak, hosts must cope with the presence of the pathogen, leading to host–pathogen coexistence or extirpation. Despite decades of research, little is known about host–pathogen coexistence post‐outbreak when low host abundances and cryptic species make these interactions difficult to study. Using a novel disease‐structured N‐mixture model, we evaluate empirical support for three host–pathogen coexistence hypotheses (source–sink, eco‐evolutionary rescue, and spatial variation in pathogen transmission) in a Neotropical amphibian community decimated by Batrachochytrium dendrobatidis (Bd) in 2004. During 2010–2014, we surveyed amphibians in Parque Nacional G. D. Omar Torríjos Herrera, Coclé Province, El Copé, Panama. We found that the primary driver of host–pathogen coexistence was eco‐evolutionary rescue, as evidenced by similar amphibian survival and recruitment rates between infected and uninfected hosts. Average apparent monthly survival rates of uninfected and infected hosts were both close to 96%, and the expected number of uninfected and infected hosts recruited (via immigration/reproduction) was less than one host per disease state per 20‐m site. The secondary driver of host–pathogen coexistence was spatial variation in pathogen transmission as we found that transmission was highest in areas of low abundance but there was no support for the source–sink hypothesis. Our results indicate that changes in the host community (i.e., through genetic or species composition) can reduce the impacts of emerging infectious disease post‐outbreak. Our disease‐structured N‐mixture model represents a valuable advancement for conservation managers trying to understand underlying host–pathogen interactions and provides new opportunities to study disease dynamics in remnant host populations decimated by virulent pathogens.
","language":"English","publisher":"ESA","doi":"10.1002/eap.1792","usgsCitation":"DiRenzo, G.V., Zipkin, E.F., Campbell Grant, E.H., Royle, J.A., Longo, A.V., Zamudio, K.R., and Lips, K.R., 2018, Eco‐evolutionary rescue promotes host–pathogen coexistence: Ecological Applications, v. 28, no. 8, p. 1948-1962, https://doi.org/10.1002/eap.1792.","productDescription":"15 p.","startPage":"1948","endPage":"1962","ipdsId":"IP-082685","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468195,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.1792","text":"Publisher Index Page"},{"id":360085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-03","publicationStatus":"PW","scienceBaseUri":"5c0f897ae4b0c53ecb2c71f3","contributors":{"authors":[{"text":"DiRenzo, Graziella V.","contributorId":192177,"corporation":false,"usgs":false,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":753432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zipkin, Elise F. 0000-0003-4155-6139","orcid":"https://orcid.org/0000-0003-4155-6139","contributorId":192755,"corporation":false,"usgs":false,"family":"Zipkin","given":"Elise","email":"","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":753433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":753431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":753434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Longo, Ana V.","contributorId":202587,"corporation":false,"usgs":false,"family":"Longo","given":"Ana","email":"","middleInitial":"V.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":753435,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zamudio, Kelly R.","contributorId":8320,"corporation":false,"usgs":true,"family":"Zamudio","given":"Kelly","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":753436,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lips, Karen R.","contributorId":26258,"corporation":false,"usgs":true,"family":"Lips","given":"Karen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":753437,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204565,"text":"70204565 - 2018 - Will increased storm surge frequency impact food availability for Semipalmated Sandpipers (Calidris pusilla) at the beginning of fall migration?","interactions":[],"lastModifiedDate":"2019-08-05T11:47:16","indexId":"70204565","displayToPublicDate":"2018-12-09T10:29:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5557,"text":"Wader Study","active":true,"publicationSubtype":{"id":10}},"title":"Will increased storm surge frequency impact food availability for Semipalmated Sandpipers (Calidris pusilla) at the beginning of fall migration?","docAbstract":"Hatch-year Semipalmated Sandpipers (Calidris pusilla) use river deltas along the Beaufort Sea as their first stops during fall migration. However, these sites are subject to extreme changes in water levels that affect available foraging habitat. We examined relationships between timing of fall migration and storm surges, with respect to forage availability, using different water level scenarios to predict impacts on food availability for fueling migration at three river deltas. We compared available calories at observed water levels to modeled values derived from changes due to lunar tides (35% decline) and storm surges (58% decline). Peak use by shorebirds varied temporally among sites, while the peak in forage availability occurred late in the season, mismatched with the largest peak in migration at the most used river delta. Shifts in breeding phenology due to climate warming may allow shorebirds to migrate earlier and miss some storm surges, but this may create a mismatch between peak migration and greater food availability. Additionally, changes in climate will likely increase frequency and severity of storm surges that negatively impact availability of foraging habitat for migrant shorebirds.
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The IPTEI is modeled on the familiar Periodic Table of the Chemical Elements. The IPTEI is intended to hang on the walls of chemistry laboratories and classrooms. Each cell of the IPTEI provides the chemical name, symbol, atomic number, and standard atomic weight of an element. Color-coded pie charts in each element cell display the stable isotopes and the relatively long lived radioactive isotopes having characteristic terrestrial isotopic compositions that determine the standard atomic weight of each element. The background color scheme of cells categorizes the 118 elements into four groups: (1) white indicates the element has no standard atomic weight, (2) blue indicates the element has only one isotope that is used to determine its standard atomic weight, which is given as a single value with an uncertainty, (3) yellow indicates the element has two or more isotopes that are used to determine its standard atomic weight, which is given as a single value with an uncertainty, and (4) pink indicates the element has a well-documented variation in its atomic weight, and the standard atomic weight is expressed as an interval. An element-by-element review accompanies the IPTEI and includes a chart of all known stable and radioactive isotopes for each element. Practical applications of isotopic measurements and technologies are included for the following fields: forensic science, geochronology, Earth-system sciences, environmental science, and human health sciences, including medical diagnosis and treatment.","language":"English","publisher":"De Gruyter","doi":"10.1515/pac-2015-0703","usgsCitation":"Holden, N.E., Coplen, T.B., Bohlke, J., Tarbox, L.V., Benefield, J., de Laeter, J.R., Mahaffy, P.G., O’Connor nee Singleton, G., Roth, E., Tepper, D., Walczyk, T., Wieser, M.E., and Yoneda, S., 2018, IUPAC Periodic Table of the Elements and Isotopes (IPTEI) for the education community (IUPAC Technical Report): Pure and Applied Chemistry, v. 90, no. 12, p. 1833-2092, https://doi.org/10.1515/pac-2015-0703.","productDescription":"260 p.","startPage":"1833","endPage":"2092","ipdsId":"IP-077158","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468197,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1515/pac-2015-0703","text":"Publisher Index Page"},{"id":371782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Holden, Norman E.","contributorId":189167,"corporation":false,"usgs":false,"family":"Holden","given":"Norman","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":780971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37464,"text":"WMA - 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2018 - An integrated population model for greater Sage-Grouse (Centrocercus urophasianus) in the bi-state distinct population segment, California and Nevada, 2003–17","interactions":[],"lastModifiedDate":"2018-12-10T10:28:00","indexId":"ofr20181177","displayToPublicDate":"2018-12-07T14:23:08","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":"2018-1177","displayTitle":"An Integrated Population Model for Greater Sage-Grouse (Centrocercus urophasianus) in the Bi-State Distinct Population Segment, California and Nevada, 2003–17","title":"An integrated population model for greater Sage-Grouse (Centrocercus urophasianus) in the bi-state distinct population segment, California and Nevada, 2003–17","docAbstract":"The Bi-State Distinct Population Segment (DPS) of greater sage-grouse (Centrocercus urophasianus, hereinafter “sage-grouse”) occupies parts of Alpine, Mono, and Inyo Counties in California, and parts of Douglas, Esmeralda, Lyon, Carson City, and Mineral Counties in Nevada and was proposed for listing as threatened under the Endangered Species Act (ESA) by the U.S. Fish and Wildlife Service (USFWS) in October 2013. In April 2015, the USFWS determined that the Bi-State DPS did not warrant listing under the ESA, but monitoring continued for assessment of long-term population stability (U.S. Fish and Wildlife Service, 2015a). Threats to this population include geographic isolation, expansion of single-leaf pinyon (Pinus monophylla) and Utah juniper (Juniperus osteosperma), anthropogenic activities, changes in historical wildfire cycles and the conversion of native shrubs to invasive annual grasslands, and recent changes in predator communities. As part of a broad long-term monitoring program, we used an integrated population model to estimate finite rate of population change (λ) of each subpopulation within the Bi-State DPS from 2003 to 2017. Since 2012, the Bi-State DPS experienced multiple years of drought conditions associated with periods of population decline across multiple populations. The 14-year average (λ) for the Bi-State DPS is 0.98 (95 percent CRI=0.70–1.31). Three subpopulations (Mount Grant, Fales, Bodie Hills) showed continued evidence of stability and growth as the average λ exceeded 1.0. Moreover, we implemented the first year of an experimental pre-nesting female and brood translocation program to bolster a critically low population of sage-grouse in Parker Meadows, California. Finally, we report summary statistics describing sage-grouse movements and relative abundance of avian predators across all years of the study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181177","collaboration":"Prepared in cooperation with the Bureau of Land Management, California Department of Fish and Wildlife, Nevada Department of Wildlife, and the U.S. Forest Service","usgsCitation":"Mathews, S.R., Coates, P.S., Prochazka, B.G., Ricca, M.A., Meyerpeter, M.B., Espinosa, S.P., Lisius, S., Gardner, S.C., and Delehanty, D.J., 2018, An integrated population model for greater sage-grouse (Centrocercus urophasianus) in the Bi-State Distinct Population Segment, California and Nevada, 2003–17: U.S. Geological Survey Open-File Report 2018-1177, 89 p., https://doi.org/10.3133/ofr20181177.","productDescription":"ix, 89 p.","onlineOnly":"Y","ipdsId":"IP-098330","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":360049,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1177/coverthb.jpg"},{"id":360050,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1177/ofr20181177.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1177"}],"contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819