We use a dated sediment core from Lake Whittington (USA) in the lower Mississippi River to reconstruct linkages in the carbon cycling and fluvial sediment dynamics over the past 80 years. Organic carbon (OC) sources were characterized using bulk (δ13C, ramped pyrolysis-oxidation (PyrOx) 14C, δ15N, and TN:OC ratios) and compound-specific (lignin phenols and fatty acids, including δ13C and 14C of the fatty acids) analyses. Damming of the Missouri River in the 1950s, other hydrological modifications to the river, and soil conservation measures resulted in reduced net OC export, in spite of increasing OC concentrations. Decreasing δ13C values coincided with increases in δ15N, TN:OC ratios, long-chain fatty acids, and lignin-phenol concentrations, suggesting increased inputs of soil-derived OC dominated by C3 vegetation, mainly resulting from changes in farming practices and crop distribution. However, ramped PyrOx 14C showed no discernible differences downcore in thermochemical stability, indicating a limited impact on soil OC turnover.
","language":"English","publisher":"AGU","doi":"10.1002/2015GL065595","usgsCitation":"Bianchi, T.S., Galy, V., Rosenheim, B.E., Shields, M., Cui, X., and Van Metre, P., 2015, Paleoreconstruction of organic carbon inputs to an oxbow lake in the Mississippi River watershed: Effects of dam construction and land use change on regional inputs: Geophysical Research Letters, v. 42, no. 19, p. 7983-7991, https://doi.org/10.1002/2015GL065595.","productDescription":"9 p.","startPage":"7983","endPage":"7991","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066306","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":471580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl065595","text":"Publisher Index Page"},{"id":311893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Lake Whittington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.15837097167967,\n 33.65420905128059\n ],\n [\n -91.15837097167967,\n 33.72334023851457\n ],\n [\n -91.02739334106445,\n 33.72334023851457\n ],\n [\n -91.02739334106445,\n 33.65420905128059\n ],\n [\n -91.15837097167967,\n 33.65420905128059\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"19","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-10","publicationStatus":"PW","scienceBaseUri":"566167b9e4b06a3ea36c5663","contributors":{"authors":[{"text":"Bianchi, Thomas S.","contributorId":150225,"corporation":false,"usgs":false,"family":"Bianchi","given":"Thomas","email":"","middleInitial":"S.","affiliations":[{"id":17943,"text":"Univ of Florida","active":true,"usgs":false}],"preferred":false,"id":581051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galy, Valier","contributorId":150226,"corporation":false,"usgs":false,"family":"Galy","given":"Valier","email":"","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":581052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenheim, Brad E.","contributorId":150227,"corporation":false,"usgs":false,"family":"Rosenheim","given":"Brad","email":"","middleInitial":"E.","affiliations":[{"id":12607,"text":"Univ of South florida, School of Geosciences, Tampa FL","active":true,"usgs":false}],"preferred":false,"id":581053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shields, Michael","contributorId":150228,"corporation":false,"usgs":false,"family":"Shields","given":"Michael","email":"","affiliations":[{"id":17943,"text":"Univ of Florida","active":true,"usgs":false}],"preferred":false,"id":581054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cui, Xingquan","contributorId":150229,"corporation":false,"usgs":false,"family":"Cui","given":"Xingquan","email":"","affiliations":[{"id":17943,"text":"Univ of Florida","active":true,"usgs":false}],"preferred":false,"id":581055,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Metre, Peter C. pcvanmet@usgs.gov","contributorId":486,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":581050,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159914,"text":"70159914 - 2015 - Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations","interactions":[],"lastModifiedDate":"2017-01-18T09:55:38","indexId":"70159914","displayToPublicDate":"2015-12-03T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations","docAbstract":"Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) and may result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystem services is preferred. The 30-m Landsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. The main goal of this study is to develop a 30-m grassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based on MODIS and Landsat (r = 0.91) was developed, and a 30-m MODIS equivalent GSN map was generated. Finally, a 30-m grassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass production map and will be useful for regional ecosystem study and local land management practices.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2015.10.018","usgsCitation":"Gu, Y., and Wylie, B.K., 2015, Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations: Remote Sensing of Environment, v. 171, p. 291-298, https://doi.org/10.1016/j.rse.2015.10.018.","productDescription":"8 p.","startPage":"291","endPage":"298","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068578","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":311883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.162353515625,\n 41.00477542222949\n ],\n [\n -100.162353515625,\n 42.52879629320373\n ],\n [\n -96.624755859375,\n 42.52879629320373\n ],\n [\n -96.624755859375,\n 41.00477542222949\n ],\n [\n -100.162353515625,\n 41.00477542222949\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"171","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566167b8e4b06a3ea36c565b","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":139586,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"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":581015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"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":581016,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159917,"text":"70159917 - 2015 - Classification of ephemeral, intermittent, and perennial stream reaches using a TOPMODEL-based approach","interactions":[],"lastModifiedDate":"2019-06-03T13:22:56","indexId":"70159917","displayToPublicDate":"2015-12-03T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Classification of ephemeral, intermittent, and perennial stream reaches using a TOPMODEL-based approach","docAbstract":"Whether a waterway is temporary or permanent influences regulatory protection guidelines, however, classification can be subjective due to a combination of factors, including time of year, antecedent moisture conditions, and previous experience of the field investigator. Our objective was to develop a standardized protocol using publicly available spatial information to classify ephemeral, intermittent, and perennial streams. Our hypothesis was that field observations of flow along the stream channel could be compared to results from a hydrologic model, providing an objective method of how these stream reaches can be identified. Flow-state sensors were placed at ephemeral, intermittent, and perennial stream reaches from May to December 2011 in the Appalachian coal basin of eastern Kentucky. This observed flow record was then used to calibrate the simulated saturation deficit in each channel reach based on the topographic wetness index used by TOPMODEL. Saturation deficit values were categorized as flow or no-flow days, and the simulated record of streamflow was compared to the observed record. The hydrologic model was more accurate for simulating flow during the spring and fall seasons. However, the model effectively identified stream reaches as intermittent and perennial in each of the two basins.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12352","usgsCitation":"Williamson, T., Agouridis, C.T., Barton, C.D., Villines, J.A., and Lant, J.G., 2015, Classification of ephemeral, intermittent, and perennial stream reaches using a TOPMODEL-based approach: Journal of the American Water Resources Association, v. 51, no. 6, p. 1739-1759, https://doi.org/10.1111/1752-1688.12352.","productDescription":"21 p.","startPage":"1739","endPage":"1759","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051282","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":311879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-18","publicationStatus":"PW","scienceBaseUri":"566167b7e4b06a3ea36c5655","contributors":{"authors":[{"text":"Williamson, Tanja N. tnwillia@usgs.gov","contributorId":452,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja N.","email":"tnwillia@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":581038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agouridis, Carmen T. 0000-0001-9580-6143","orcid":"https://orcid.org/0000-0001-9580-6143","contributorId":150223,"corporation":false,"usgs":false,"family":"Agouridis","given":"Carmen","email":"","middleInitial":"T.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":581040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barton, Christopher D.","contributorId":150222,"corporation":false,"usgs":false,"family":"Barton","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":581039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villines, Jonathan A.","contributorId":150224,"corporation":false,"usgs":false,"family":"Villines","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":581041,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lant, Jeremiah G. 0000-0001-6688-4820 jlant@usgs.gov","orcid":"https://orcid.org/0000-0001-6688-4820","contributorId":4912,"corporation":false,"usgs":true,"family":"Lant","given":"Jeremiah","email":"jlant@usgs.gov","middleInitial":"G.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":581042,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159003,"text":"sir20155151 - 2015 - Regression Equations for Monthly and Annual Mean and Selected Percentile Streamflows for Ungaged Rivers in Maine","interactions":[],"lastModifiedDate":"2015-12-31T10:46:01","indexId":"sir20155151","displayToPublicDate":"2015-12-03T12:00:00","publicationYear":"2015","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":"2015-5151","title":"Regression Equations for Monthly and Annual Mean and Selected Percentile Streamflows for Ungaged Rivers in Maine","docAbstract":"In an effort to delineate hydrologic conditions in Maine, the U.S. Geological Survey, in cooperation with the Maine Department of Transportation, used streamflow data to develop dependent variables for 130 regression equations for estimating monthly and annual mean and 1, 5, 10, 25, 50, 75, 90, 95, and 99 percentile streamflows for ungaged, unregulated rivers in Maine. Daily streamflow data from 24 rural unregulated basins with drainage areas between 14.9 and 1,419 square miles in Maine and northern New Hampshire were used in the derivation of the equations. Streamflow data collected from October 1, 1982, through September 30, 2012, were used to derive the dependent variables for this study to represent current [2015] hydrologic conditions in Maine and northern New Hampshire. Weighted least squares regression techniques were used to derive the final coefficients and measures of uncertainty for the regression equations. Eight basin characteristics serve as the explanatory variables: drainage area, distance from the coast, mean and maximum basin elevation, mean basin slope, mean basin percentage of hydrologic soil group A, fraction of sand and gravel aquifers, and percentage of open water.
\nThe largest average errors of prediction are associated with regression equations for the lowest streamflows derived for months during which the lowest streamflows of the year occur (such as the 5 and 1 monthly percentiles for August and September). The regression equations have been derived on the basis of streamflow and basin characteristics data for unregulated, rural drainage basins without substantial streamflow or drainage modifications (for example, diversions and (or) regulation by dams or reservoirs, tile drainage, irrigation, channelization, and impervious paved surfaces), therefore using the equations for regulated or urbanized basins with substantial streamflow or drainage modifications will yield results of unknown error. Input basin characteristics derived using techniques or datasets other than those documented in this report or using values outside the ranges used to develop these regression equations also will yield results of unknown error.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155151","collaboration":"Prepared in cooperation with the Maine Department of Transportation","usgsCitation":"Dudley, R.W., 2015, Regression equations for monthly and annual mean and selected percentile streamflows for ungaged rivers in Maine (ver. 1.1, December 21, 2015): U.S. Geological Survey Scientific Investigations Report 2015–5151, 35 p., https://dx.doi.org/10.3133/sir20155151.","productDescription":"viii, 35 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066284","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":311685,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5151/sir20155151.pdf","text":"Report","size":"8.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5151"},{"id":312572,"rank":3,"type":{"id":25,"text":"Version 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\"}}]}","edition":"Version 1: Originally posted December 3, 2015; Version 1.1: December 21, 2015","contact":"Director, New England Water Science Center
U.S. Geological Survey
196 Whitten Road
Augusta, ME 04330
Or visit our Web site at:
http://newengland.water.usgs.gov
The U.S. Fish and Wildlife Service (USFWS) has begun to issue incidental take permits (ITPs) to wind power companies to allow limited take of bird and bat species that are protected under the Endangered Species Act, the Bald and Golden Eagle Protection Act, or the Migratory Bird Treaty Act (Huso and others, 2015). Expected take rates are determined using scientifically based collision-risk models and knowledge about the ecology of the population of interest. ITPs often include mitigation requirements to compensate for estimated take and further describe (1) adaptive management actions (AMAs) that may be required to reduce take rates if permitted rate is exceeded, or (2) additional compensatory mitigation to offset take that exceeds permitted levels.
\nConfirming the accuracy of predicted take and providing evidence that permitted take levels have not been exceeded can be challenging because carcasses may be detected with probability much less than 1, and often no carcasses are observed. When detection probability is high, finding 0 carcasses can be interpreted as evidence that none (or few) were actually killed. As the probability of observing an individual decreases, the likelihood of missing carcasses increases, making it unclear how to interpret having observed 0 (or few) carcasses. In a practical sense, the consequences of incorrect inference can be significant: overestimating take could result in costly and unjustified mitigation, whereas underestimating could result in unanticipated declines in species populations already at risk.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151227","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Dalthorp, Daniel, and Huso, Manuela, 2015, A framework for decision points to trigger adaptive management actions in long-term incidental take permits: U.S. Geological Survey Open-File Report 2015-1227, 88 p., https://dx.doi.org/10.3133/ofr20151227.","productDescription":"vi, 88 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068559","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":311799,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1227/coverthb.jpg"},{"id":311800,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1227/ofr20151227.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1227"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
The U.S. Geological Survey seismic hazard maps for the central and eastern United States were updated in 2014. We analyze results and changes for the eastern part of the region. Ratio maps are presented, along with tables of ground motions and deaggregations for selected cities. The Charleston fault model was revised, and a new fault source for Charlevoix was added. Background seismicity sources utilized an updated catalog, revised completeness and recurrence models, and a new adaptive smoothing procedure. Maximum-magnitude models and ground motion models were also updated. Broad, regional hazard reductions of 5%–20% are mostly attributed to new ground motion models with stronger near-source attenuation. The revised Charleston fault geometry redistributes local hazard, and the new Charlevoix source increases hazard in northern New England. Strong increases in mid- to high-frequency hazard at some locations—for example, southern New Hampshire, central Virginia, and eastern Tennessee—are attributed to updated catalogs and/or smoothing.
","language":"English","publisher":"Earthquake Engineering Research Institute","publisherLocation":"Berkeley","doi":"10.1193/110414EQS182M","usgsCitation":"Mueller, C., Boyd, O.S., Petersen, M.D., Moschetti, M.P., Rezaeian, S., and Shumway, A., 2015, Seismic hazard in the eastern United States: Earthquake Spectra, v. 31, no. 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abundance during migration: Managing the spectrum of conditions faced by migrants","docAbstract":"The development of robust modelling techniques to derive inferences from large-scale migratory bird monitoring data at appropriate scales has direct relevance to their management. The Integrated Waterbird Management and Monitoring programme (IWMM) represents one of the few attempts to monitor migrating waterbirds across entire flyways using targeted local surveys. This dataset included 13,208,785 waterfowl (eight Anas species) counted during 28,000 surveys at nearly 1,000 locations across the eastern United States between autumn 2010 and spring 2013 and was used to evaluate potential predictors of waterfowl abundance at the wetland scale. Mixed-effects, log-linear models of local abundance were built for the Atlantic and Mississippi flyways during spring and autumn migration to identify factors relating to habitat structure, forage availability, and migration timing that influence target dabbling duck species abundance. Results indicated that migrating dabbling ducks responded differently to environmental factors. While the factors identified demonstrated a high degree of importance, they were inconsistent across species, flyways and seasons. Furthermore, the direction and magnitude of the importance of each covariate group considered here varied across species. Given our results, actionable policy recommendations are likely to be most effective if they consider species-level variation within targeted taxonomic units and across management areas. The methods implemented here can easily be applied to other contexts, and serve as a novel investigation into local-level population patterns using data from broad-scale monitoring programmes.
","language":"English","publisher":"Wildfowl & Wetlands Trust","publisherLocation":"Slimbridge","collaboration":"The Nature Conservancy; U.S. Fish and Wildlife Service","usgsCitation":"Aagaard, K., Crimmins, S.M., Thogmartin, W.E., Tavernia, B., and Lyons, J., 2015, Evaluating predictors of local dabbling duck abundance during migration: Managing the spectrum of conditions faced by migrants: Wildfowl, v. 65, p. 100-120.","productDescription":"21 p.","startPage":"100","endPage":"120","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066133","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":312659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312658,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2628/1750","linkFileType":{"id":1,"text":"pdf"}}],"country":"United 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E.","affiliations":[],"preferred":false,"id":571574,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156911,"text":"70156911 - 2015 - Factors associated with the deposition of Cladophora on Lake Michigan beaches in 2012","interactions":[],"lastModifiedDate":"2015-12-21T15:15:00","indexId":"70156911","displayToPublicDate":"2015-12-01T16:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Factors associated with the deposition of Cladophora on Lake Michigan beaches in 2012","docAbstract":"Deposition of the macroalgae Cladophora spp. was monitored on 18 beaches around Lake Michigan during 2012 at a high temporal frequency. We observed a high degree of spatial variability in Cladophora deposition among beaches on Lake Michigan, even within local regions, with no clear regional pattern in the intensity of Cladophora deposition. A strong seasonal pattern in Cladophora deposition was observed, with the heaviest deposition occurring during mid-summer. Several beaches exhibited high temporal variability in Cladophora deposition over short time scales, suggesting that drifting algal mats may be extremely dynamic in nearshore environments of the Great Lakes. Cladophora deposition on Lake Michigan beaches was primarily related to the presence of nearshore structures, local population density, and nearshore bathymetry. There was relatively little evidence that waves, winds, or currents were associated with Cladophora deposition on beaches, but this may be due to the relatively poor resolution of existing nearshore hydrodynamic data. Developing a predictive understanding of beach-cast Cladophora dynamics in Great Lakes environments may require both intensive Cladophora monitoring and fine-scale local hydrodynamic modeling efforts.
","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Toronto","doi":"10.1016/j.jglr.2015.09.008","collaboration":"CSS-Dynamac; USGS Michigan Water Science Center; National Park Service","usgsCitation":"Riley, S.C., Tucker, T.R., Adams, J.V., Fogarty, L.R., and Lafrancois, B.M., 2015, Factors associated with the deposition of Cladophora on Lake Michigan beaches in 2012: Journal of Great Lakes Research, v. 41, no. 4, p. 1094-1105, https://doi.org/10.1016/j.jglr.2015.09.008.","productDescription":"12 p.","startPage":"1094","endPage":"1105","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063264","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":312650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Michigan, Wisconsin","otherGeospatial":"Lake Michigan beaches","volume":"41","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567930c7e4b0da412f4fb561","contributors":{"authors":[{"text":"Riley, Stephen C. 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":2661,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":571125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Taaja R. 0000-0003-1534-4677 trtucker@usgs.gov","orcid":"https://orcid.org/0000-0003-1534-4677","contributorId":5172,"corporation":false,"usgs":true,"family":"Tucker","given":"Taaja","email":"trtucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":571126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":571127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fogarty, Lisa R. 0000-0003-0329-3251 lrfogart@usgs.gov","orcid":"https://orcid.org/0000-0003-0329-3251","contributorId":2053,"corporation":false,"usgs":true,"family":"Fogarty","given":"Lisa","email":"lrfogart@usgs.gov","middleInitial":"R.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":571128,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lafrancois, Brenda Moraska","contributorId":68559,"corporation":false,"usgs":true,"family":"Lafrancois","given":"Brenda","email":"","middleInitial":"Moraska","affiliations":[],"preferred":false,"id":571129,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160657,"text":"70160657 - 2015 - Non-invasive flow path characterization in a mining-impacted wetland","interactions":[],"lastModifiedDate":"2018-09-04T15:29:32","indexId":"70160657","displayToPublicDate":"2015-12-01T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Non-invasive flow path characterization in a mining-impacted wetland","docAbstract":"Time-lapse electrical resistivity (ER) was used to capture the dilution of a seasonal pulse of acid mine drainage (AMD) contamination in the subsurface of a wetland downgradient of the abandoned Pennsylvania mine workings in central Colorado. Data were collected monthly from mid-July to late October of 2013, with an additional dataset collected in June of 2014. Inversion of the ER data shows the development through time of multiple resistive anomalies in the subsurface, which corroborating data suggest are driven by changes in total dissolved solids (TDS) localized in preferential flow pathways. Sensitivity analyses on a synthetic model of the site suggest that the anomalies would need to be at least several meters in diameter to be adequately resolved by the inversions. The existence of preferential flow paths would have a critical impact on the extent of attenuation mechanisms at the site, and their further characterization could be used to parameterize reactive transport models in developing quantitative predictions of remediation strategies.
","language":"English","publisher":"Elsevier","publisherLocation":"New York","doi":"10.1016/j.jconhyd.2015.10.002","usgsCitation":"Bethune, J., Randell, J., Runkel, R.L., and Singha, K., 2015, Non-invasive flow path characterization in a mining-impacted wetland: Journal of Contaminant Hydrology, v. 183, p. 29-39, https://doi.org/10.1016/j.jconhyd.2015.10.002.","productDescription":"11 p.","startPage":"29","endPage":"39","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066981","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471587,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jconhyd.2015.10.002","text":"Publisher Index Page"},{"id":312932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.24603271484375,\n 39.257778150283336\n ],\n [\n -106.24603271484375,\n 39.85915479295669\n ],\n [\n -105.08697509765625,\n 39.85915479295669\n ],\n [\n -105.08697509765625,\n 39.257778150283336\n ],\n [\n -106.24603271484375,\n 39.257778150283336\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"183","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56826b46e4b0a04ef4925b88","contributors":{"authors":[{"text":"Bethune, James","contributorId":150889,"corporation":false,"usgs":false,"family":"Bethune","given":"James","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":583484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Randell, Jackie","contributorId":150890,"corporation":false,"usgs":false,"family":"Randell","given":"Jackie","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":583485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":583483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini","contributorId":76733,"corporation":false,"usgs":true,"family":"Singha","given":"Kamini","affiliations":[],"preferred":false,"id":583486,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160877,"text":"70160877 - 2015 - A new record of the late Pleistocene coral Pocillopora palmata from the Dry Tortugas, Florida reef tract, USA","interactions":[],"lastModifiedDate":"2016-01-04T13:31:13","indexId":"70160877","displayToPublicDate":"2015-12-01T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3000,"text":"Palaios","active":true,"publicationSubtype":{"id":10}},"title":"A new record of the late Pleistocene coral Pocillopora palmata from the Dry Tortugas, Florida reef tract, USA","docAbstract":"Pocilloporid corals dominated shallow-water environments in the Caribbean during much of the Cenozoic; however, the regional diversity of this family declined over the last 15 My, culminating with the extinction of its final member, Pocillopora palmata, during the latest Pleistocene. Here we present a new record of P. palmata from Dry Tortugas National Park in the Florida Keys and infer its likely age. Although most existing records of P. palmata are from the sub-aerial reef deposits of MIS5e (∼ 125 ka), the presently submerged reef in the Dry Tortugas was too deep (> 18 m) during this period to support significant reef growth. In contrast, the maximum water depth during MIS5a (∼ 82 ka) was only ∼ 5.6 m, which would have been ideal for P. palmata. Diagenetic alteration prevented direct dating of the samples; however, the similarity between the depths of the Pleistocene bedrock in the Dry Tortugas and other reefs in the Florida Keys, which have been previously dated to MIS5a, support the conclusion that P. palmata likely grew in the Dry Tortugas during this period. Our study provides important new information on the history of P. palmata, but it also highlights the vital need for more comprehensive studies of the Quaternary history of Caribbean reef development. With modern reef degradation already driving yet another restructuring of Caribbean coral assemblages, insights from past extinctions may prove critical in determining the prognosis of Caribbean reefs in the future.
","language":"English","publisher":"Society for Sedimentary Geology (SEPM)","publisherLocation":"Tulsa, OK","doi":"10.2110/palo.2015.030","collaboration":"Ilsa B. Kuffner (USGS), Hai Cheng (U. Minnesota), and R. Lawrence Edwards (U. Minnesota)","usgsCitation":"Toth, L., Kuffner, I.B., Cheng, H., and Edwards, R.L., 2015, A new record of the late Pleistocene coral Pocillopora palmata from the Dry Tortugas, Florida reef tract, USA: Palaios, v. 30, no. 12, p. 827-835, https://doi.org/10.2110/palo.2015.030.","productDescription":"9 p.","startPage":"827","endPage":"835","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065691","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":313208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.8618049621582,\n 24.631023880670345\n ],\n [\n -82.86755561828613,\n 24.633286469281998\n ],\n [\n -82.8742504119873,\n 24.633754585948758\n ],\n [\n -82.88128852844238,\n 24.63110190164926\n ],\n [\n -82.8823184967041,\n 24.62610846080021\n ],\n [\n -82.88008689880371,\n 24.621114820458505\n ],\n [\n -82.86961555480957,\n 24.620958765983687\n ],\n [\n -82.86043167114258,\n 24.619944407149372\n ],\n [\n -82.85313606262206,\n 24.623299562653035\n ],\n [\n -82.85511016845702,\n 24.627590909374685\n ],\n [\n -82.8618049621582,\n 24.631023880670345\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"12","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-28","publicationStatus":"PW","scienceBaseUri":"568ba5bee4b0e7594ee77644","contributors":{"authors":[{"text":"Toth, Lauren T. ltoth@usgs.gov","contributorId":151036,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren T.","email":"ltoth@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":584128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 ikuffner@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7847","contributorId":3105,"corporation":false,"usgs":true,"family":"Kuffner","given":"Ilsa","email":"ikuffner@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":584129,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cheng, Hai","contributorId":85896,"corporation":false,"usgs":true,"family":"Cheng","given":"Hai","affiliations":[],"preferred":false,"id":584130,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, R. Lawrence","contributorId":69760,"corporation":false,"usgs":true,"family":"Edwards","given":"R.","email":"","middleInitial":"Lawrence","affiliations":[],"preferred":false,"id":584131,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159835,"text":"70159835 - 2015 - Quantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR","interactions":[],"lastModifiedDate":"2015-12-01T12:46:29","indexId":"70159835","displayToPublicDate":"2015-12-01T13:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR","docAbstract":"Peatlands are a major reservoir of global soil carbon, yet account for just 3% of global land cover. Human impacts like draining can hinder the ability of peatlands to sequester carbon and expose their soils to fire under dry conditions. Estimating soil carbon loss from peat fires can be challenging due to uncertainty about pre-fire surface elevations. This study uses multi-temporal LiDAR to obtain pre- and post-fire elevations and estimate soil carbon loss caused by the 2011 Lateral West fire in the Great Dismal Swamp National Wildlife Refuge, VA, USA. We also determine how LiDAR elevation error affects uncertainty in our carbon loss estimate by randomly perturbing the LiDAR point elevations and recalculating elevation change and carbon loss, iterating this process 1000 times. We calculated a total loss using LiDAR of 1.10 Tg C across the 25 km2 burned area. The fire burned an average of 47 cm deep, equivalent to 44 kg C/m2, a value larger than the 1997 Indonesian peat fires (29 kg C/m2). Carbon loss via the First-Order Fire Effects Model (FOFEM) was estimated to be 0.06 Tg C. Propagating the LiDAR elevation error to the carbon loss estimates, we calculated a standard deviation of 0.00009 Tg C, equivalent to 0.008% of total carbon loss. We conclude that LiDAR elevation error is not a significant contributor to uncertainty in soil carbon loss under severe fire conditions with substantial peat consumption. However, uncertainties may be more substantial when soil elevation loss is of a similar or smaller magnitude than the reported LiDAR error.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2015.09.017","usgsCitation":"Reddy, A.D., Hawbaker, T., Wurster, F., Zhu, Z., Ward, S., Newcomb, D., and Murray, R., 2015, Quantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR: Remote Sensing of Environment, v. 170, p. 306-316, https://doi.org/10.1016/j.rse.2015.09.017.","productDescription":"11 p.","startPage":"306","endPage":"316","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058007","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":471590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2015.09.017","text":"Publisher Index Page"},{"id":311766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Great Dismal Swamp National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.52286529541016,\n 36.54522526304657\n ],\n [\n -76.52286529541016,\n 36.60726008752079\n ],\n [\n -76.46724700927734,\n 36.60726008752079\n ],\n [\n -76.46724700927734,\n 36.54522526304657\n ],\n [\n -76.52286529541016,\n 36.54522526304657\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"170","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"565ec4b2e4b071e7ea544415","chorus":{"doi":"10.1016/j.rse.2015.09.017","url":"http://dx.doi.org/10.1016/j.rse.2015.09.017","publisher":"Elsevier BV","authors":"Reddy A.D., Hawbaker T.J., Wurster F., Zhu Z., Ward S., Newcomb D., Murray R.","journalName":"Remote Sensing of Environment","publicationDate":"12/2015","auditedOn":"3/22/2016","publiclyAccessibleDate":"10/2/2015"},"contributors":{"authors":[{"text":"Reddy, Ashwan D. areddy@usgs.gov","contributorId":5347,"corporation":false,"usgs":true,"family":"Reddy","given":"Ashwan","email":"areddy@usgs.gov","middleInitial":"D.","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":580658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":580657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wurster, F.","contributorId":150077,"corporation":false,"usgs":false,"family":"Wurster","given":"F.","email":"","affiliations":[{"id":17901,"text":"US Fish and Wildlife Service, Suffolk, VA","active":true,"usgs":false}],"preferred":false,"id":580659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":580660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ward, S.","contributorId":150079,"corporation":false,"usgs":false,"family":"Ward","given":"S.","affiliations":[{"id":17902,"text":"US Fish and Wildlife Service, Raleigh, NC","active":true,"usgs":false}],"preferred":false,"id":580661,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newcomb, Doug","contributorId":150080,"corporation":false,"usgs":false,"family":"Newcomb","given":"Doug","email":"","affiliations":[{"id":17902,"text":"US Fish and Wildlife Service, Raleigh, NC","active":true,"usgs":false}],"preferred":false,"id":580662,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murray, R.","contributorId":150081,"corporation":false,"usgs":false,"family":"Murray","given":"R.","affiliations":[{"id":17901,"text":"US Fish and Wildlife Service, Suffolk, VA","active":true,"usgs":false}],"preferred":false,"id":580663,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70168440,"text":"70168440 - 2015 - The 1868 Hayward fault, California, earthquake: Implications for earthquake scaling relations on partially creeping faults","interactions":[],"lastModifiedDate":"2016-02-15T12:25:14","indexId":"70168440","displayToPublicDate":"2015-12-01T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"The 1868 Hayward fault, California, earthquake: Implications for earthquake scaling relations on partially creeping faults","docAbstract":"The 21 October 1868 Hayward, California, earthquake is among the best-characterized historical earthquakes in California. In contrast to many other moderate-to-large historical events, the causative fault is clearly established. Published magnitude estimates have been fairly consistent, ranging from 6.8 to 7.2, with 95% confidence limits including values as low as 6.5. The magnitude is of particular importance for assessment of seismic hazard associated with the Hayward fault and, more generally, to develop appropriate magnitude–rupture length scaling relations for partially creeping faults. The recent reevaluation of archival accounts by Boatwright and Bundock (2008), together with the growing volume of well-calibrated intensity data from the U.S. Geological Survey “Did You Feel It?” (DYFI) system, provide an opportunity to revisit and refine the magnitude estimate. In this study, we estimate the magnitude using two different methods that use DYFI data as calibration. Both approaches yield preferred magnitude estimates of 6.3–6.6, assuming an average stress drop. A consideration of data limitations associated with settlement patterns increases the range to 6.3–6.7, with a preferred estimate of 6.5. Although magnitude estimates for historical earthquakes are inevitably uncertain, we conclude that, at a minimum, a lower-magnitude estimate represents a credible alternative interpretation of available data. We further discuss implications of our results for probabilistic seismic-hazard assessment from partially creeping faults.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/0120140372","usgsCitation":"Hough, S.E., and Martin, S., 2015, The 1868 Hayward fault, California, earthquake: Implications for earthquake scaling relations on partially creeping faults: Bulletin of the Seismological Society of America, v. 105, no. 6, p. 2894-2909, https://doi.org/10.1785/0120140372.","productDescription":"16 p.","startPage":"2894","endPage":"2909","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056942","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":318023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Hayward","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.79394531249999,\n 39.68182601089365\n ],\n [\n -123.321533203125,\n 39.740986355883564\n ],\n [\n -122.684326171875,\n 39.65645604812829\n ],\n [\n -122.33276367187499,\n 39.317300373271024\n ],\n [\n -122.01416015625,\n 38.788345355085625\n ],\n [\n -121.35498046875,\n 38.08268954483802\n ],\n [\n -121.11328124999999,\n 37.52715361723378\n ],\n [\n -120.59692382812499,\n 36.96744946416934\n ],\n [\n -120.33325195312499,\n 36.1733569352216\n ],\n [\n -120.465087890625,\n 35.79999392988527\n ],\n [\n -120.904541015625,\n 35.55904339525894\n ],\n [\n -121.168212890625,\n 35.53222622770337\n ],\n [\n -121.53076171875,\n 35.89795019335754\n ],\n [\n -121.97021484374999,\n 36.2265501474709\n ],\n [\n -122.33276367187499,\n 36.721273880045004\n ],\n [\n -122.71728515624999,\n 37.35269280367274\n ],\n [\n -123.15673828124999,\n 37.97018468810549\n ],\n [\n -123.49731445312499,\n 38.26406296833961\n ],\n [\n -123.695068359375,\n 38.865374851611634\n ],\n [\n -123.848876953125,\n 39.21523130910493\n ],\n [\n -123.848876953125,\n 39.65645604812829\n ],\n [\n -123.79394531249999,\n 39.68182601089365\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-30","publicationStatus":"PW","scienceBaseUri":"56c304dbe4b0946c652087f2","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":620144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Stacey","contributorId":35165,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","affiliations":[{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":620145,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70160371,"text":"70160371 - 2015 - Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","interactions":[],"lastModifiedDate":"2015-12-23T11:00:01","indexId":"70160371","displayToPublicDate":"2015-12-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","docAbstract":"Growing use of two-dimensional (2-D) hydraulic models has created a need for high resolution data to support flood volume estimates, floodplain specific engineering data, and accurate flood inundation scenarios. Elevation data are a critical input to these models that guide the flood-wave across the landscape allowing the computation of valuable engineering specific data that provides a better understanding of flooding impacts on structures, debris movement, bed scour, and direction. High resolution elevation data are becoming publicly available that can benefit the 2-D flood modeling community. Comparison of these newly available data with legacy data suggests that better modeling outcomes are achieved by using 3D Elevation Program (3DEP) lidar point data and the derived 1 m Digital Elevation Model (DEM) product relative to the legacy 3 m, 10 m, or 30 m products currently available in the U.S. Geological Survey (USGS) National Elevation Dataset. Within the low topographic relief of a coastal floodplain, the newer 3DEP data better resolved elevations within the forested and swampy areas achieving simulations that compared well with a historic flooding event. Results show that the 1 m DEM derived from 3DEP lidar source provides a more conservative estimate of specific energy, static pressure, and impact pressure for grid elements at maximum flow relative to the legacy DEM data. Better flood simulations are critically important in coastal floodplains where climate change driven storm frequency and sea level rise will contribute to more frequent flooding events.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.jhydrol.2015.10.051","usgsCitation":"Witt, E.C., 2015, Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain: Journal of Hydrology, v. 531, no. 3, p. 759-767, https://doi.org/10.1016/j.jhydrol.2015.10.051.","productDescription":"9 p.","startPage":"759","endPage":"767","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066431","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":312794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","city":"Greenville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.3298454284668,\n 35.628488848361336\n ],\n [\n -77.32804298400879,\n 35.60330002507124\n ],\n [\n -77.36005783081055,\n 35.604346810028304\n ],\n [\n -77.37645149230957,\n 35.61174370007563\n ],\n [\n -77.37722396850586,\n 35.62583776685229\n ],\n [\n -77.3298454284668,\n 35.628488848361336\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"531","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567bd3bbe4b0a04ef491a1f9","contributors":{"authors":[{"text":"Witt, Emitt C. III 0000-0002-1814-7807 ecwitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7807","contributorId":1612,"corporation":false,"usgs":true,"family":"Witt","given":"Emitt","suffix":"III","email":"ecwitt@usgs.gov","middleInitial":"C.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":582830,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70170986,"text":"70170986 - 2015 - Probabilistic 3-D time-lapse inversion of magnetotelluric data: Application to an enhanced geothermal system","interactions":[],"lastModifiedDate":"2016-05-17T10:44:52","indexId":"70170986","displayToPublicDate":"2015-12-01T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic 3-D time-lapse inversion of magnetotelluric data: Application to an enhanced geothermal system","docAbstract":"Surface-based monitoring of mass transfer caused by injections and extractions in deep boreholes is crucial to maximize oil, gas and geothermal production. Inductive electromagnetic methods, such as magnetotellurics, are appealing for these applications due to their large penetration depths and sensitivity to changes in fluid conductivity and fracture connectivity. In this work, we propose a 3-D Markov chain Monte Carlo inversion of time-lapse magnetotelluric data to image mass transfer following a saline fluid injection. The inversion estimates the posterior probability density function of the resulting plume, and thereby quantifies model uncertainty. To decrease computation times, we base the parametrization on a reduced Legendre moment decomposition of the plume. A synthetic test shows that our methodology is effective when the electrical resistivity structure prior to the injection is well known. The centre of mass and spread of the plume are well retrieved.We then apply our inversion strategy to an injection experiment in an enhanced geothermal system at Paralana, South Australia, and compare it to a 3-D deterministic time-lapse inversion. The latter retrieves resistivity changes that are more shallow than the actual injection interval, whereas the probabilistic inversion retrieves plumes that are located at the correct depths and oriented in a preferential north-south direction. To explain the time-lapse data, the inversion requires unrealistically large resistivity changes with respect to the base model. We suggest that this is partly explained by unaccounted subsurface heterogeneities in the base model from which time-lapse changes are inferred.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford","doi":"10.1093/gji/ggv406","usgsCitation":"Rosas-Carbajal, M., Linde, N., Peacock, J.R., Zyserman, F.I., Kalscheuer, T., and Thiel, S., 2015, Probabilistic 3-D time-lapse inversion of magnetotelluric data: Application to an enhanced geothermal system: Geophysical Journal International, v. 203, no. 3, p. 1946-1960, https://doi.org/10.1093/gji/ggv406.","productDescription":"15 p.","startPage":"1946","endPage":"1960","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068406","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":471594,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggv406","text":"Publisher Index Page"},{"id":321296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"203","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-30","publicationStatus":"PW","scienceBaseUri":"574d661fe4b07e28b6684bbd","contributors":{"authors":[{"text":"Rosas-Carbajal, Marina","contributorId":169322,"corporation":false,"usgs":false,"family":"Rosas-Carbajal","given":"Marina","affiliations":[{"id":25473,"text":"Applied and Environmental Group, University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":629336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Linde, Nicolas","contributorId":169323,"corporation":false,"usgs":false,"family":"Linde","given":"Nicolas","email":"","affiliations":[{"id":25474,"text":"Institut de Physique du Globe, Paris, France","active":true,"usgs":false}],"preferred":false,"id":629337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peacock, Jared R. 0000-0002-0439-0224 jpeacock@usgs.gov","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":4996,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared","email":"jpeacock@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":629335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zyserman, F. I.","contributorId":169324,"corporation":false,"usgs":false,"family":"Zyserman","given":"F.","email":"","middleInitial":"I.","affiliations":[{"id":25475,"text":"CONICET-Facultad de Ciencias Astronomicas y Geofisicas, Universidad Nacional de La Plata, Argentina","active":true,"usgs":false}],"preferred":false,"id":629338,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kalscheuer, Thomas","contributorId":169325,"corporation":false,"usgs":false,"family":"Kalscheuer","given":"Thomas","email":"","affiliations":[{"id":25476,"text":"Department of Earth Sciences, Uppsala University, Sweden","active":true,"usgs":false}],"preferred":false,"id":629339,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thiel, Stephan","contributorId":169326,"corporation":false,"usgs":false,"family":"Thiel","given":"Stephan","email":"","affiliations":[{"id":25477,"text":"Geological Survey of South Australia","active":true,"usgs":false}],"preferred":false,"id":629340,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70175000,"text":"70175000 - 2015 - Western water and climate change","interactions":[],"lastModifiedDate":"2016-07-27T11:37:12","indexId":"70175000","displayToPublicDate":"2015-12-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Western water and climate change","docAbstract":"The western United States is a region long defined by water challenges. Climate change adds to those historical challenges, but does not, for the most part, introduce entirely new challenges; rather climate change is likely to stress water supplies and resources already in many cases stretched to, or beyond, natural limits. Projections are for continued and, likely, increased warming trends across the region, with a near certainty of continuing changes in seasonality of snowmelt and streamflows, and a strong potential for attendant increases in evaporative demands. Projections of future precipitation are less conclusive, although likely the northernmost West will see precipitation increases while the southernmost West sees declines. However, most of the region lies in a broad area where some climate models project precipitation increases while others project declines, so that only increases in precipitation uncertainties can be projected with any confidence. Changes in annual and seasonal hydrographs are likely to challenge water managers, users, and attempts to protect or restore environmental flows, even where annual volumes change little. Other impacts from climate change (e.g., floods and water-quality changes) are poorly understood and will likely be location dependent.
\nIn this context, four iconic river basins offer glimpses into specific challenges that climate change may bring to the West. The Colorado River is a system in which overuse and growing demands are projected to be even more challenging than climate-change-induced flow reductions. The Rio Grande offers the best example of how climate-change-induced flow declines might sink a major system into permanent drought. The Klamath is currently projected to face the more benign precipitation future, but fisheries and irrigation management may face dire straits due to warming air temperatures, rising irrigation demands, and warming waters in a basin already hobbled by tensions between endangered fisheries and agricultural demands. Finally, California's Bay-Delta system is a remarkably localized and severe weakness at the heart of the region's trillion-dollar economy. It is threatened by the full range of potential climate-change impacts expected across the West, along with major vulnerabilities to increased flooding and rising sea levels.
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Bradley","contributorId":87862,"corporation":false,"usgs":true,"family":"Udall","given":"Bradley","email":"","affiliations":[],"preferred":false,"id":643552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Georgakakos, Aris P.","contributorId":59828,"corporation":false,"usgs":true,"family":"Georgakakos","given":"Aris","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":643553,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203506,"text":"70203506 - 2015 - A practical guide to the use of major elements, trace elements, and isotopes in compositional data analysis: Applications for deep formation brine geochemistry","interactions":[],"lastModifiedDate":"2019-05-20T10:16:54","indexId":"70203506","displayToPublicDate":"2015-12-01T10:16:27","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A practical guide to the use of major elements, trace elements, and isotopes in compositional data analysis: Applications for deep formation brine geochemistry","docAbstract":"In the geosciences, isotopic ratios and trace element concentrations are often used along with major element concentrations to help determine sources of and processes affecting geochemical variation. Compositional Data Analysis (CoDA) is a set of tools, generally attuned to major element data, concerned with the proper statistical treatment and removal of spurious correlations from compositional data. Though recent insights have been made on the incorporation of trace elements and stable isotope ratios to CoDA, this study provides a general approach to thinking about how radiogenic isotopes, stable isotopes, and trace elements fit with major elements in the CoDA framework. In the present study, we use multiple data sets of deep formation brines and compare traditional mixing models to their CoDA counterparts to examine fluid movement between reservoirs. Concentrations of individual isotopes are calculated using isotopic ratios and global mean isotopic abundances. One key result is that isotope parts (e.g. 18O, 17O, 16O, 2H, 1H, 87Sr, 86Sr) can simply be modelled by the major element concentration (H2O, Sr) in a clr-biplot as they are perfectly dependent. Another important result is that an ilr transformation of radiogenic isotope parts (e.g. 86Sr and 87Sr in 87Sr/86Sr) and trace elements can, like stable isotopes in delta notation, be treated as a linear function of the isotopic ratio or trace element concentration, scaled only by a constant. This implies that there are multiple situations in which an ilr transformation provides little additional insight for the analysis of trends: (1) any two parts with low log ratio variance (e.g. an isotope ratio), no matter their concentrations in the solution, (2) any low concentration parts (trace elements) or a ratio of a trace to a major element, no matter the variance of the elements, and (3) large positive ratios (major/trace) over a restricted range of variance. Similarly, a multivariate ilr transformation of a large data set with many parts will also be a simple perturbation if the balances are evenly split between parts. CoDA transformations, however, even if they do not provide new insight in some specific cases, will provide consistent interpretations for all types of data.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the International Workshop on Compositional Data Analysis","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Workshop on Compositional Data Analysis","conferenceDate":"June 1-5, 2015","conferenceLocation":"L'Escala, Spain","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-44811-4_2","usgsCitation":"Blondes, M., Engle, M.A., and Geboy, N., 2015, A practical guide to the use of major elements, trace elements, and isotopes in compositional data analysis: Applications for deep formation brine geochemistry, in Proceedings of the International Workshop on Compositional Data Analysis, L'Escala, Spain, June 1-5, 2015, p. 13-29, https://doi.org/10.1007/978-3-319-44811-4_2.","productDescription":"17 p.","startPage":"13","endPage":"29","ipdsId":"IP-070706","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":364003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engle, Mark A. 0000-0001-5258-7374 engle@usgs.gov","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":584,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","email":"engle@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geboy, Nicholas 0000-0003-3949-3001 ngeboy@usgs.gov","orcid":"https://orcid.org/0000-0003-3949-3001","contributorId":215664,"corporation":false,"usgs":true,"family":"Geboy","given":"Nicholas","email":"ngeboy@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160736,"text":"70160736 - 2015 - Current land bird distribution and trends in population abundance between 1982 and 2012 on Rota, Mariana Islands","interactions":[],"lastModifiedDate":"2018-01-04T13:06:31","indexId":"70160736","displayToPublicDate":"2015-12-01T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Current land bird distribution and trends in population abundance between 1982 and 2012 on Rota, Mariana Islands","docAbstract":"The western Pacific island of Rota is the fourth largest human-inhabited island in the Mariana archipelago and designated an Endemic Bird Area. Between 1982 and 2012, 12 point-transect distance-sampling surveys were conducted to assess bird population status. Surveys did not consistently sample the entire island; thus, we used a ratio estimator to estimate bird abundances in strata not sampled during every survey. Trends in population size were reliably estimated for 11 of 13 bird species, and 7 species declined over the 30-y time series, including the island collared-dove Streptopelia bitorquata, white-throated ground-dove Gallicolumba xanthonura, Mariana fruit-dove Ptilinopus roseicapilla, collared kingfisher Todiramphus chloris orii, Micronesian myzomela Myzomela rubratra, black drongo Dicrurus macrocercus, and Mariana crow Corvus kubaryi. The endangered Mariana crow (x̄ = 81 birds, 95% CI 30–202) declined sharply to fewer than 200 individuals in 2012, down from 1,491 birds in 1982 (95% CI = 815–3,115). Trends increased for white tern Gygis alba, rufous fantail Rhipidura rufifrons mariae, and Micronesian starling Aplonis opaca. Numbers of the endangered Rota white-eye Zosterops rotensis declined from 1982 to the late 1990s but returned to 1980s levels by 2012, resulting in an overall stable trend. Trends for the yellow bittern Ixobrychus sinensis were inconclusive. Eurasian tree sparrow Passer montanus trends were not assessed; however, their numbers in 1982 and 2012 were similar. Occupancy models of the 2012 survey data revealed general patterns of land cover use and detectability among 12 species that could be reliably modeled. Occupancy was not assessed for the Eurasian tree sparrow because of insufficient detections. Based on the 2012 survey, bird distribution and abundance across Rota revealed three general patterns: 1) range restriction, including Mariana crow, Rota white-eye, and Eurasian tree sparrow; 2) widespread distribution, low abundance, including collared kingfisher, island collared-dove, white-throated ground-dove, Mariana fruit-dove, white tern, yellow bittern, black drongo, and Micronesian myzomela; and 3) widespread distribution, high abundance, including rufous fantail and Micronesian starling. The Mariana crow was dispersed around the periphery of the island in steep forested land-cover types. In contrast, the Rota white-eye was restricted to the high-elevation mesa. Only for the white-throated ground-dove was there a significant difference among cover types, with lower occupancy in open field than in forested areas. Vegetation was included in the best-fit occupancy models for yellow bittern, black drongo, Micronesian myzomela, and Micronesian starling, but vegetation type was not a significant variable nor included in the top models for the remaining five species: white tern, island collared-dove, Mariana fruit-dove, collared kingfisher, and rufous fantail. Given declining population trends, the Rota bird-monitoring program could benefit from establishing threshold and alert limits and identifying alternative research and management actions. Continued monitoring and demographic sampling, in conjunction with ecological studies, are needed to understand why most bird species on Rota are declining, identify the causative agents, and assess effectiveness of conservation actions, especially for the Mariana crow.
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Background seismicity sources were improved using a new moment-magnitude-based catalog; a new adaptive, nearest-neighbor smoothing kernel was implemented; and maximum magnitudes for background sources were updated. Areal source zones developed by the Central and Eastern United States Seismic Source Characterization for Nuclear Facilities project were simplified and adopted. The weighting scheme for ground motion models was updated, giving more weight to models with a faster attenuation with distance compared to the previous maps. Overall, hazard changes (2% probability of exceedance in 50 years, across a range of ground-motion frequencies) were smaller than 10% in most of the CUS relative to the 2008 USGS maps despite new ground motion models and their assigned logic tree weights that reduced the probabilistic ground motions by 5–20%.
","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/103114EQS174M","usgsCitation":"Boyd, O.S., Haller, K., Luco, N., Moschetti, M.P., Mueller, C., Petersen, M.D., Rezaeian, S., and Rubinstein, J.L., 2015, Seismic hazard in the Nation's breadbasket: Earthquake Spectra, v. S1, no. 31, p. 109-130, https://doi.org/10.1193/103114EQS174M.","productDescription":"22 p.","startPage":"109","endPage":"130","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064918","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1193/103114eqs174m","text":"Publisher Index Page"},{"id":324614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"S1","issue":"31","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"5774f2c6e4b07dd077c6aa3c","contributors":{"authors":[{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":641246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haller, Kathleen 0000-0001-8847-7302 haller@usgs.gov","orcid":"https://orcid.org/0000-0001-8847-7302","contributorId":172556,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":641247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":641248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":641249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":641250,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":641251,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":641252,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785 jrubinstein@usgs.gov","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":2404,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"jrubinstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":641253,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70174114,"text":"70174114 - 2015 - Why are freshwater fish so threatened?","interactions":[],"lastModifiedDate":"2016-06-28T16:20:39","indexId":"70174114","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Why are freshwater fish so threatened?","docAbstract":"The huge diversity of freshwater fishes is concentrated into an area of habitat that covers only about 1% of the Earth's surface, and much of this limited area has already been extensively impacted and intensively managed to meet human needs (Dudgeon et al., 2006). As outlined in Chapter 1, the number and proportions of threatened species tend to rise wherever fish diversity coincides with dense human populations, intensive resource use and development pressure. Of particular concern is the substantial proportion of the global diversity of freshwater fishes concentrated within the Mekong and Amazon Basins and west-central Africa (Berra, 2001; Abell et al., 2008; Dudgeon, 2011; Chapter 1) with extensive exploitation of water resources planned to accelerate in future years (Dudgeon, 2011; Chapter 1). If current trends continue, and the social, political and economic models that have been used to develop industrialised regions of the world over the past two centuries prevail, then the future of a significant proportion of global diversity of freshwater fish species is clearly uncertain.
\nUnderstanding why so many freshwater fish species are threatened requires some understanding of their biology, diversity, distribution, biogeography and ecology, but also some appreciation of the social, economic and political forces that are causing humans to destroy the natural ecosystems upon which we all ultimately depend. To begin to understand the diversity of freshwater fishes, we first need to consider the processes that generated and continue to sustain the diversity of species we see today. Based on an understanding of how freshwater fish diversity is generated and sustained, we consider how vulnerable or resilient various freshwater fishes are to the range of anthropogenic impacts that impinge on freshwater ecosystems. Finally, we discuss how social, political and economic drivers influence human impacts on natural systems, and the changes needed to current models of development that can lead to a sustainable future for humans and the diverse range of freshwater fish species with which we share our planet. The aim of this chapter is to provide an overview of the key issues and threats driving the declines in freshwater fish diversity identified in Chapter 1; subsequent chapters provide more detail on the key issues and address our options for developing a sustainable future for freshwater fishes.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Conservation of Freshwater Fishes","language":"English","publisher":"Cambridge University Press","doi":"10.1017/CBO9781139627085","usgsCitation":"Closs, G.P., Angermeier, P.L., Darwall, W.R., and Balcombe, S.R., 2015, Why are freshwater fish so threatened?, chap. of Conservation of Freshwater Fishes, p. 37-75, https://doi.org/10.1017/CBO9781139627085.","productDescription":"39 p.","startPage":"37","endPage":"75","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059105","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":324566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-05","publicationStatus":"PW","scienceBaseUri":"57739fb9e4b07657d1a90daa","contributors":{"authors":[{"text":"Closs, Gerard P.","contributorId":172538,"corporation":false,"usgs":false,"family":"Closs","given":"Gerard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":641138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":640957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Darwall, William R.T.","contributorId":94981,"corporation":false,"usgs":true,"family":"Darwall","given":"William","email":"","middleInitial":"R.T.","affiliations":[],"preferred":false,"id":641139,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Balcombe, Stephen R.","contributorId":172539,"corporation":false,"usgs":false,"family":"Balcombe","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":641140,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174146,"text":"70174146 - 2015 - Management and the conservation of freshwater ecosystems","interactions":[],"lastModifiedDate":"2016-06-28T15:41:28","indexId":"70174146","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Management and the conservation of freshwater ecosystems","docAbstract":"Riparian areas are the terrestrial environment adjacent to water that both influences and is influenced by the aquatic feature (Gregory et al., 1991; Naiman et al., 2010). Riparian areas along streams provide shade, sources of wood and organic matter, contribute to bank stability, filter sediments, take up excess nutrients from groundwater inputs, and other key processes that protect freshwaters (e.g. Naiman et al., 2010; Richardson & Danehy, 2007; Figure 9.1). Riparian areas also increase biodiversity through habitat complexity and close juxtaposition of aquatic and terrestrial environments (Quinn et al., 2004; Naiman et al., 2010). Alterations to riparian areas, despite their small area relative to the landscape, have disproportionate effects on habitats and fish communities (Naiman et al., 2010; Wipfli & Baxter, 2010). Key habitat losses and alterations are derived from modification of riparian areas by reducing instream habitat complexity (Bilby & Ward, 1989; Fausch & Northcote, 1992; Naiman et al., 2010), diminishing the productive basis of freshwater food webs (Belsky et al., 1999; Quinn et al., 2004), increasing nutrient, contaminant and sediment intrusion (Muscutt et al., 1993; Daniels & Gilliam, 1996; Nguyen et al., 1998; Waters, 1999).
\nRiparian and freshwater ecosystems are typically tightly coupled, especially in their natural states, and the linkages that couple them frequently exert strong influence on their associated invertebrate and fish fauna (e.g. Gregory et al., 1991; Naiman et al., 2010). Riparian habitats, and the condition of these habitats, further plays a key role in the ecology of these fresh waters, influencing critical processes such as water, nutrient and sediment delivery and dynamics; prey resources for fish and other consumers, and other organic materials exchanged between aquatic and terrestrial habitats (Nakano et al., 1999; Naiman et al., 2010); light and water temperature dynamics that in turn affect food web processes and fish metabolism and growth; aquatic physical habitat (wood); and terrestrial consumers that prey upon fishes (Bisson & Bilby, 1998; Naiman et al., 2010; Wipfli & Baxter, 2010). These processes in turn directly or indirectly influence fishes in freshwater systems (Wang et al., 2001; Pusey & Arthington, 2003; Allan, 2004; Richardson et al., 2010a).
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/CBO9781139627085.010","usgsCitation":"Wipfli, M.S., and Richardson, J.S., 2015, Management and the conservation of freshwater ecosystems, p. 270-291, https://doi.org/10.1017/CBO9781139627085.010.","productDescription":"22 p.","startPage":"270","endPage":"291","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055418","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":324546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57739fb1e4b07657d1a90cde","contributors":{"authors":[{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":640993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, John S.","contributorId":172517,"corporation":false,"usgs":false,"family":"Richardson","given":"John","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":641099,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70162509,"text":"70162509 - 2015 - Validation of simulated earthquake ground motions based on evolution of intensity and frequency content","interactions":[],"lastModifiedDate":"2016-01-28T09:10:09","indexId":"70162509","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Validation of simulated earthquake ground motions based on evolution of intensity and frequency content","docAbstract":"Simulated earthquake ground motions can be used in many recent engineering applications that require time series as input excitations. However, applicability and validation of simulations are subjects of debate in the seismological and engineering communities. We propose a validation methodology at the waveform level and directly based on characteristics that are expected to influence most structural and geotechnical response parameters. In particular, three time-dependent validation metrics are used to evaluate the evolving intensity, frequency, and bandwidth of a waveform. These validation metrics capture nonstationarities in intensity and frequency content of waveforms, making them ideal to address nonlinear response of structural systems. A two-component error vector is proposed to quantify the average and shape differences between these validation metrics for a simulated and recorded ground-motion pair. Because these metrics are directly related to the waveform characteristics, they provide easily interpretable feedback to seismologists for modifying their ground-motion simulation models. To further simplify the use and interpretation of these metrics for engineers, it is shown how six scalar key parameters, including duration, intensity, and predominant frequency, can be extracted from the validation metrics. The proposed validation methodology is a step forward in paving the road for utilization of simulated ground motions in engineering practice and is demonstrated using examples of recorded and simulated ground motions from the 1994 Northridge, California, earthquake.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120140210","usgsCitation":"Rezaeian, S., Zhong, P., Hartzell, S.H., and Zareian, F., 2015, Validation of simulated earthquake ground motions based on evolution of intensity and frequency content: Bulletin of the Seismological Society of America, v. 105, no. 6, p. 3036-3049, https://doi.org/10.1785/0120140210.","productDescription":"14 p.","startPage":"3036","endPage":"3049","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068675","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":314936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","otherGeospatial":"Northridge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.55552673339842,\n 34.20044475954112\n ],\n [\n -118.55552673339842,\n 34.27651009584797\n ],\n [\n -118.47278594970702,\n 34.27651009584797\n ],\n [\n -118.47278594970702,\n 34.20044475954112\n ],\n [\n -118.55552673339842,\n 34.20044475954112\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-03","publicationStatus":"PW","scienceBaseUri":"56ab49d8e4b07ca61bfea61a","contributors":{"authors":[{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":589705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhong, Peng","contributorId":152543,"corporation":false,"usgs":false,"family":"Zhong","given":"Peng","email":"","affiliations":[{"id":6641,"text":"University of California at Merced","active":true,"usgs":false}],"preferred":false,"id":589706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":589707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zareian, Farzin","contributorId":152544,"corporation":false,"usgs":false,"family":"Zareian","given":"Farzin","email":"","affiliations":[{"id":6641,"text":"University of California at Merced","active":true,"usgs":false}],"preferred":false,"id":589708,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176400,"text":"70176400 - 2015 - Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: Application of hydrodynamic and particle tracking models","interactions":[],"lastModifiedDate":"2016-09-13T09:39:55","indexId":"70176400","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: Application of hydrodynamic and particle tracking models","docAbstract":"Estuarine residence time is a major driver of eutrophication and water quality. Barnegat Bay-Little Egg Harbor (BB-LEH), New Jersey, is a lagoonal back-barrier estuary that is subject to anthropogenic pressures including nutrient loading, eutrophication, and subsequent declines in water quality. A combination of hydrodynamic and particle tracking modeling was used to identify the mechanisms controlling flushing, residence time, and spatial variability of particle retention. The models demonstrated a pronounced northward subtidal flow from Little Egg Inlet in the south to Pt. Pleasant Canal in the north due to frictional effects in the inlets, leading to better flushing of the southern half of the estuary and particle retention in the northern estuary. Mean residence time for BB-LEH was 13 days but spatial variability was between ∼0 and 30 days depending on the initial particle location. Mean residence time with tidal forcing alone was 24 days (spatial variability between ∼0 and 50 days); the tides were relatively inefficient in flushing the northern end of the Bay. Scenarios with successive exclusion of physical processes from the models revealed that meteorological and remote offshore forcing were stronger drivers of exchange than riverine inflow. Investigations of water quality and eutrophication should take into account spatial variability in hydrodynamics and residence time in order to better quantify the roles of nutrient loading, production, and flushing.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-014-9885-3","usgsCitation":"Defne, Z., and Ganju, N., 2015, Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: Application of hydrodynamic and particle tracking models: Estuaries and Coasts, v. 38, no. 5, p. 1719-1734, https://doi.org/10.1007/s12237-014-9885-3.","productDescription":"16 p.","startPage":"1719","endPage":"1734","ipdsId":"IP-057196","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471614,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/7506","text":"External Repository"},{"id":328587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"5","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-23","publicationStatus":"PW","scienceBaseUri":"57d92340e4b090824ffa1b23","contributors":{"authors":[{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":149613,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":648604,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169234,"text":"70169234 - 2015 - Assessment of model estimates of land-atmosphere CO2 exchange across northern Eurasia","interactions":[],"lastModifiedDate":"2016-03-24T13:40:28","indexId":"70169234","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of model estimates of land-atmosphere CO2 exchange across northern Eurasia","docAbstract":"A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m−2 yr−2, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-12-4385-2015","usgsCitation":"Rawlins, M., McGuire, A., Kimball, J., Dass, P., Lawrence, D., Burke, E., Chen, X., Delire, C., Koven, C., MacDougall, A., Peng, S., Rinke, A., Saito, K., Zhang, W., Alkama, R., Bohn, T.J., Ciais, P., Decharme, B., Gouttevin, I., Hajima, T., Ji, D., Krinner, G., Lettenmaier, D., Miller, P., Moore, J., Smith, B., and Sueyoshi, T., 2015, Assessment of model estimates of land-atmosphere CO2 exchange across northern Eurasia: Biogeosciences, v. 12, no. 14, p. 4385-4405, https://doi.org/10.5194/bg-12-4385-2015.","productDescription":"21 p.","startPage":"4385","endPage":"4405","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059953","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471618,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-12-4385-2015","text":"Publisher Index Page"},{"id":319370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Eurasia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.68242645263672,\n 46.13036330589103\n ],\n [\n -89.68242645263672,\n 46.150107913663334\n ],\n [\n -89.65873718261719,\n 46.150107913663334\n ],\n [\n -89.65873718261719,\n 46.13036330589103\n ],\n [\n -89.68242645263672,\n 46.13036330589103\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.73096370697021,\n 45.77300107536654\n ],\n [\n -89.73096370697021,\n 45.78153149170592\n ],\n [\n -89.71843242645264,\n 45.78153149170592\n ],\n [\n -89.71843242645264,\n 45.77300107536654\n ],\n [\n -89.73096370697021,\n 45.77300107536654\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 5.9765625,\n 51.39920565355378\n ],\n [\n 5.9765625,\n 77.38950400539731\n ],\n [\n 180.35156249999997,\n 77.38950400539731\n ],\n [\n 180.35156249999997,\n 51.39920565355378\n ],\n [\n 5.9765625,\n 51.39920565355378\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"14","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-28","publicationStatus":"PW","scienceBaseUri":"56f50fb0e4b0f59b85e1ea97","contributors":{"authors":[{"text":"Rawlins, M.A.","contributorId":73445,"corporation":false,"usgs":true,"family":"Rawlins","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":623730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, A. D.","contributorId":16552,"corporation":false,"usgs":true,"family":"McGuire","given":"A. D.","affiliations":[],"preferred":false,"id":623731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kimball, J.S.","contributorId":79141,"corporation":false,"usgs":true,"family":"Kimball","given":"J.S.","email":"","affiliations":[],"preferred":false,"id":623732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dass, P.","contributorId":167840,"corporation":false,"usgs":false,"family":"Dass","given":"P.","email":"","affiliations":[],"preferred":false,"id":623733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lawrence, D.","contributorId":167819,"corporation":false,"usgs":false,"family":"Lawrence","given":"D.","affiliations":[],"preferred":false,"id":623734,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burke, E.","contributorId":167820,"corporation":false,"usgs":false,"family":"Burke","given":"E.","affiliations":[],"preferred":false,"id":623735,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chen, X.","contributorId":76527,"corporation":false,"usgs":true,"family":"Chen","given":"X.","affiliations":[],"preferred":false,"id":623736,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Delire, C.","contributorId":167821,"corporation":false,"usgs":false,"family":"Delire","given":"C.","affiliations":[],"preferred":false,"id":623737,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Koven, C.","contributorId":39655,"corporation":false,"usgs":true,"family":"Koven","given":"C.","email":"","affiliations":[],"preferred":false,"id":623738,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"MacDougall, A.","contributorId":167822,"corporation":false,"usgs":false,"family":"MacDougall","given":"A.","affiliations":[],"preferred":false,"id":623739,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Peng, S.","contributorId":68688,"corporation":false,"usgs":true,"family":"Peng","given":"S.","email":"","affiliations":[],"preferred":false,"id":623740,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rinke, A.","contributorId":13118,"corporation":false,"usgs":true,"family":"Rinke","given":"A.","email":"","affiliations":[],"preferred":false,"id":623741,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Saito, K.","contributorId":167823,"corporation":false,"usgs":false,"family":"Saito","given":"K.","email":"","affiliations":[],"preferred":false,"id":623742,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Zhang, W.","contributorId":92399,"corporation":false,"usgs":true,"family":"Zhang","given":"W.","email":"","affiliations":[],"preferred":false,"id":623743,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Alkama, R.","contributorId":167824,"corporation":false,"usgs":false,"family":"Alkama","given":"R.","affiliations":[],"preferred":false,"id":623744,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Bohn, T. J.","contributorId":167813,"corporation":false,"usgs":false,"family":"Bohn","given":"T.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":623745,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ciais, P.","contributorId":39604,"corporation":false,"usgs":true,"family":"Ciais","given":"P.","affiliations":[],"preferred":false,"id":623746,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Decharme, B.","contributorId":167825,"corporation":false,"usgs":false,"family":"Decharme","given":"B.","affiliations":[],"preferred":false,"id":623747,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Gouttevin, I.","contributorId":167818,"corporation":false,"usgs":false,"family":"Gouttevin","given":"I.","affiliations":[],"preferred":false,"id":623748,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Hajima, T.","contributorId":167826,"corporation":false,"usgs":false,"family":"Hajima","given":"T.","affiliations":[],"preferred":false,"id":623749,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Ji, D.","contributorId":167827,"corporation":false,"usgs":false,"family":"Ji","given":"D.","email":"","affiliations":[],"preferred":false,"id":623750,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Krinner, G.","contributorId":11911,"corporation":false,"usgs":true,"family":"Krinner","given":"G.","affiliations":[],"preferred":false,"id":623751,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Lettenmaier, D.P.","contributorId":61175,"corporation":false,"usgs":true,"family":"Lettenmaier","given":"D.P.","email":"","affiliations":[],"preferred":false,"id":623752,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Miller, P.","contributorId":167841,"corporation":false,"usgs":false,"family":"Miller","given":"P.","email":"","affiliations":[],"preferred":false,"id":623753,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Moore, J.C.","contributorId":95141,"corporation":false,"usgs":true,"family":"Moore","given":"J.C.","email":"","affiliations":[],"preferred":false,"id":623754,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Smith, B.","contributorId":53740,"corporation":false,"usgs":true,"family":"Smith","given":"B.","affiliations":[],"preferred":false,"id":623755,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Sueyoshi, T.","contributorId":167828,"corporation":false,"usgs":false,"family":"Sueyoshi","given":"T.","affiliations":[],"preferred":false,"id":623756,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}} ,{"id":70189525,"text":"70189525 - 2015 - Removal of terrestrial DOC in aquatic ecosystems of a temperate river network","interactions":[],"lastModifiedDate":"2017-07-14T12:24:34","indexId":"70189525","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Removal of terrestrial DOC in aquatic ecosystems of a temperate river network","docAbstract":"Surface waters play a potentially important role in the global carbon balance. Dissolved organic carbon (DOC) fluxes are a major transfer of terrestrial carbon to river systems, and the fate of DOC in aquatic systems is poorly constrained. We used a unique combination of spatially distributed sampling of three DOC fractions throughout a river network and modeling to quantify the net removal of terrestrial DOC during a summer base flow period. We found that aquatic reactivity of terrestrial DOC leading to net loss is low, closer to conservative chloride than to reactive nitrogen. Net removal occurred mainly from the hydrophobic organic acid fraction, while hydrophilic and transphilic acids showed no net change, indicating that partitioning of bulk DOC into different fractions is critical for understanding terrestrial DOC removal. These findings suggest that river systems may have only a modest ability to alter the amounts of terrestrial DOC delivered to coastal zones.
We determined whole-fish polychlorinated biphenyl (PCB) concentrations in 26 female lake whitefish (Coregonus clupeaformis) and 34 male lake whitefish from northern Lake Huron. In 5 of the 26 female lake whitefish, we also determined PCB concentrations in the somatic tissue and ovaries. In addition, bioenergetics modeling was used to determine the contribution of the growth dilution effect to the observed difference in PCB concentrations between the sexes. Whole-fish PCB concentrations for females and males averaged 60 ng/g and 80 ng/g, respectively; thus males were 34% higher in PCB concentration compared with females. Based on the PCB determinations in the somatic tissue and ovaries, we predicted that PCB concentration of females would increase by 2.5%, on average, immediately after spawning due to release of eggs. Thus, the change in PCB concentration due to release of eggs did not explain, to any degree, the higher PCB concentrations observed in males compared with females. Bioenergetics modeling results indicated that the growth dilution effect could account for males being only 0.7% higher in PCB concentration compared with females. Thus, the growth dilution effect contributed very little to the observed difference in PCB concentrations between the sexes. We conclude that males were higher than females in PCB concentration most likely due to a higher rate of energy expenditure, stemming from greater activity and a greater resting metabolic rate. A higher rate of energy expenditure leads to a higher rate of food consumption, which, in turn, leads to a higher PCB accumulation rate.
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